Date: 2019-12-26 00:16:05 CET, cola version: 1.3.2
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All available functions which can be applied to this res_list object:
res_list
#> A 'ConsensusPartitionList' object with 24 methods.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows are extracted by 'SD, CV, MAD, ATC' methods.
#> Subgroups are detected by 'hclust, kmeans, skmeans, pam, mclust, NMF' method.
#> Number of partitions are tried for k = 2, 3, 4, 5, 6.
#> Performed in total 30000 partitions by row resampling.
#>
#> Following methods can be applied to this 'ConsensusPartitionList' object:
#> [1] "cola_report" "collect_classes" "collect_plots" "collect_stats"
#> [5] "colnames" "functional_enrichment" "get_anno_col" "get_anno"
#> [9] "get_classes" "get_matrix" "get_membership" "get_stats"
#> [13] "is_best_k" "is_stable_k" "ncol" "nrow"
#> [17] "rownames" "show" "suggest_best_k" "test_to_known_factors"
#> [21] "top_rows_heatmap" "top_rows_overlap"
#>
#> You can get result for a single method by, e.g. object["SD", "hclust"] or object["SD:hclust"]
#> or a subset of methods by object[c("SD", "CV")], c("hclust", "kmeans")]
The call of run_all_consensus_partition_methods() was:
#> run_all_consensus_partition_methods(data = mat, mc.cores = 4)
Dimension of the input matrix:
mat = get_matrix(res_list)
dim(mat)
#> [1] 18147 167
The density distribution for each sample is visualized as in one column in the following heatmap. The clustering is based on the distance which is the Kolmogorov-Smirnov statistic between two distributions.
library(ComplexHeatmap)
densityHeatmap(mat, ylab = "value", cluster_columns = TRUE, show_column_names = FALSE,
mc.cores = 4)
Folowing table shows the best k (number of partitions) for each combination
of top-value methods and partition methods. Clicking on the method name in
the table goes to the section for a single combination of methods.
The cola vignette explains the definition of the metrics used for determining the best number of partitions.
suggest_best_k(res_list)
| The best k | 1-PAC | Mean silhouette | Concordance | Optional k | ||
|---|---|---|---|---|---|---|
| CV:kmeans | 2 | 1.000 | 0.980 | 0.992 | ** | |
| MAD:kmeans | 2 | 1.000 | 0.972 | 0.987 | ** | |
| ATC:mclust | 2 | 1.000 | 0.986 | 0.992 | ** | |
| CV:mclust | 3 | 1.000 | 0.964 | 0.985 | ** | |
| ATC:kmeans | 3 | 0.997 | 0.962 | 0.976 | ** | |
| ATC:pam | 4 | 0.993 | 0.941 | 0.974 | ** | 2 |
| CV:skmeans | 5 | 0.982 | 0.943 | 0.968 | ** | 2,3 |
| SD:NMF | 2 | 0.975 | 0.950 | 0.980 | ** | |
| SD:skmeans | 4 | 0.967 | 0.933 | 0.973 | ** | 2,3 |
| SD:pam | 2 | 0.963 | 0.970 | 0.986 | ** | |
| MAD:pam | 4 | 0.925 | 0.895 | 0.957 | * | 2,3 |
| ATC:skmeans | 4 | 0.923 | 0.844 | 0.926 | * | 2,3 |
| ATC:NMF | 3 | 0.918 | 0.903 | 0.959 | * | 2 |
| CV:pam | 5 | 0.915 | 0.884 | 0.950 | * | 2 |
| MAD:skmeans | 6 | 0.906 | 0.875 | 0.926 | * | 2,3,4 |
| CV:NMF | 6 | 0.903 | 0.800 | 0.900 | * | 2,5 |
| MAD:NMF | 2 | 0.878 | 0.917 | 0.965 | ||
| SD:kmeans | 2 | 0.859 | 0.943 | 0.972 | ||
| MAD:mclust | 4 | 0.718 | 0.842 | 0.862 | ||
| ATC:hclust | 3 | 0.714 | 0.836 | 0.910 | ||
| MAD:hclust | 3 | 0.573 | 0.799 | 0.879 | ||
| SD:hclust | 3 | 0.516 | 0.786 | 0.871 | ||
| SD:mclust | 2 | 0.498 | 0.695 | 0.876 | ||
| CV:hclust | 2 | 0.414 | 0.846 | 0.907 |
**: 1-PAC > 0.95, *: 1-PAC > 0.9
Cumulative distribution function curves of consensus matrix for all methods.
collect_plots(res_list, fun = plot_ecdf)
Consensus heatmaps for all methods. (What is a consensus heatmap?)
collect_plots(res_list, k = 2, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = consensus_heatmap, mc.cores = 4)
Membership heatmaps for all methods. (What is a membership heatmap?)
collect_plots(res_list, k = 2, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = membership_heatmap, mc.cores = 4)
Signature heatmaps for all methods. (What is a signature heatmap?)
Note in following heatmaps, rows are scaled.
collect_plots(res_list, k = 2, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 3, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 4, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 5, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 6, fun = get_signatures, mc.cores = 4)
The statistics used for measuring the stability of consensus partitioning. (How are they defined?)
get_stats(res_list, k = 2)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 2 0.975 0.950 0.980 0.491 0.510 0.510
#> CV:NMF 2 1.000 0.969 0.987 0.493 0.505 0.505
#> MAD:NMF 2 0.878 0.917 0.965 0.490 0.510 0.510
#> ATC:NMF 2 0.975 0.946 0.979 0.501 0.500 0.500
#> SD:skmeans 2 1.000 0.984 0.993 0.500 0.500 0.500
#> CV:skmeans 2 1.000 0.955 0.983 0.485 0.519 0.519
#> MAD:skmeans 2 0.925 0.927 0.969 0.491 0.502 0.502
#> ATC:skmeans 2 1.000 0.972 0.989 0.479 0.519 0.519
#> SD:mclust 2 0.498 0.695 0.876 0.462 0.508 0.508
#> CV:mclust 2 0.369 0.789 0.848 0.467 0.537 0.537
#> MAD:mclust 2 0.505 0.748 0.861 0.454 0.560 0.560
#> ATC:mclust 2 1.000 0.986 0.992 0.444 0.556 0.556
#> SD:kmeans 2 0.859 0.943 0.972 0.466 0.544 0.544
#> CV:kmeans 2 1.000 0.980 0.992 0.460 0.540 0.540
#> MAD:kmeans 2 1.000 0.972 0.987 0.459 0.544 0.544
#> ATC:kmeans 2 0.599 0.932 0.949 0.457 0.548 0.548
#> SD:pam 2 0.963 0.970 0.986 0.463 0.537 0.537
#> CV:pam 2 1.000 0.951 0.980 0.449 0.544 0.544
#> MAD:pam 2 0.962 0.962 0.983 0.464 0.537 0.537
#> ATC:pam 2 1.000 1.000 1.000 0.441 0.560 0.560
#> SD:hclust 2 0.327 0.734 0.778 0.407 0.560 0.560
#> CV:hclust 2 0.414 0.846 0.907 0.472 0.508 0.508
#> MAD:hclust 2 0.450 0.857 0.876 0.431 0.540 0.540
#> ATC:hclust 2 0.512 0.817 0.906 0.458 0.519 0.519
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.784 0.825 0.925 0.355 0.744 0.534
#> CV:NMF 3 0.886 0.911 0.960 0.360 0.742 0.528
#> MAD:NMF 3 0.810 0.831 0.925 0.357 0.758 0.556
#> ATC:NMF 3 0.918 0.903 0.959 0.294 0.812 0.638
#> SD:skmeans 3 1.000 0.953 0.982 0.311 0.787 0.597
#> CV:skmeans 3 1.000 0.980 0.991 0.379 0.781 0.591
#> MAD:skmeans 3 1.000 0.957 0.982 0.333 0.796 0.612
#> ATC:skmeans 3 1.000 0.984 0.994 0.396 0.760 0.560
#> SD:mclust 3 0.482 0.593 0.753 0.356 0.795 0.610
#> CV:mclust 3 1.000 0.964 0.985 0.429 0.757 0.563
#> MAD:mclust 3 0.617 0.655 0.794 0.400 0.770 0.589
#> ATC:mclust 3 0.517 0.582 0.712 0.405 0.790 0.622
#> SD:kmeans 3 0.799 0.872 0.935 0.376 0.797 0.634
#> CV:kmeans 3 0.744 0.865 0.900 0.431 0.759 0.566
#> MAD:kmeans 3 0.726 0.804 0.886 0.395 0.785 0.616
#> ATC:kmeans 3 0.997 0.962 0.976 0.441 0.785 0.611
#> SD:pam 3 0.699 0.872 0.925 0.431 0.780 0.595
#> CV:pam 3 0.884 0.855 0.944 0.484 0.734 0.534
#> MAD:pam 3 0.902 0.897 0.955 0.440 0.769 0.580
#> ATC:pam 3 0.765 0.749 0.890 0.430 0.787 0.625
#> SD:hclust 3 0.516 0.786 0.871 0.535 0.797 0.643
#> CV:hclust 3 0.565 0.719 0.832 0.352 0.827 0.666
#> MAD:hclust 3 0.573 0.799 0.879 0.465 0.796 0.634
#> ATC:hclust 3 0.714 0.836 0.910 0.398 0.819 0.651
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.899 0.876 0.945 0.0936 0.835 0.570
#> CV:NMF 4 0.842 0.891 0.911 0.1021 0.894 0.696
#> MAD:NMF 4 0.886 0.867 0.933 0.0979 0.842 0.586
#> ATC:NMF 4 0.777 0.794 0.905 0.1404 0.805 0.515
#> SD:skmeans 4 0.967 0.933 0.973 0.1326 0.897 0.707
#> CV:skmeans 4 0.827 0.902 0.911 0.1100 0.865 0.627
#> MAD:skmeans 4 0.959 0.935 0.973 0.1355 0.889 0.690
#> ATC:skmeans 4 0.923 0.844 0.926 0.0927 0.923 0.773
#> SD:mclust 4 0.618 0.773 0.822 0.1476 0.820 0.536
#> CV:mclust 4 0.871 0.910 0.910 0.0849 0.950 0.848
#> MAD:mclust 4 0.718 0.842 0.862 0.1348 0.875 0.648
#> ATC:mclust 4 0.572 0.647 0.750 0.1118 0.851 0.605
#> SD:kmeans 4 0.755 0.831 0.832 0.1331 0.861 0.632
#> CV:kmeans 4 0.826 0.853 0.858 0.1168 0.898 0.704
#> MAD:kmeans 4 0.708 0.800 0.813 0.1347 0.878 0.669
#> ATC:kmeans 4 0.879 0.860 0.939 0.1156 0.853 0.613
#> SD:pam 4 0.861 0.825 0.911 0.1109 0.852 0.599
#> CV:pam 4 0.757 0.650 0.801 0.0978 0.903 0.721
#> MAD:pam 4 0.925 0.895 0.957 0.1039 0.853 0.601
#> ATC:pam 4 0.993 0.941 0.974 0.1037 0.835 0.604
#> SD:hclust 4 0.549 0.675 0.814 0.0933 0.953 0.878
#> CV:hclust 4 0.575 0.550 0.716 0.1193 0.846 0.604
#> MAD:hclust 4 0.570 0.615 0.791 0.1004 0.972 0.924
#> ATC:hclust 4 0.732 0.603 0.786 0.1303 0.847 0.596
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.718 0.715 0.848 0.0804 0.874 0.578
#> CV:NMF 5 1.000 0.960 0.982 0.0782 0.926 0.726
#> MAD:NMF 5 0.746 0.655 0.853 0.0628 0.903 0.671
#> ATC:NMF 5 0.804 0.774 0.882 0.0479 0.901 0.662
#> SD:skmeans 5 0.864 0.852 0.869 0.0686 0.930 0.734
#> CV:skmeans 5 0.982 0.943 0.968 0.0804 0.915 0.686
#> MAD:skmeans 5 0.865 0.823 0.854 0.0689 0.923 0.708
#> ATC:skmeans 5 0.882 0.864 0.909 0.0527 0.940 0.787
#> SD:mclust 5 0.576 0.661 0.764 0.0716 0.915 0.689
#> CV:mclust 5 0.810 0.815 0.887 0.0561 0.953 0.837
#> MAD:mclust 5 0.649 0.738 0.822 0.0755 0.940 0.771
#> ATC:mclust 5 0.608 0.551 0.714 0.0860 0.893 0.628
#> SD:kmeans 5 0.774 0.748 0.813 0.0737 0.981 0.928
#> CV:kmeans 5 0.824 0.809 0.842 0.0689 0.934 0.751
#> MAD:kmeans 5 0.779 0.700 0.752 0.0743 0.910 0.669
#> ATC:kmeans 5 0.763 0.695 0.777 0.0676 0.905 0.675
#> SD:pam 5 0.795 0.722 0.824 0.0665 0.954 0.827
#> CV:pam 5 0.915 0.884 0.950 0.0878 0.887 0.615
#> MAD:pam 5 0.840 0.793 0.852 0.0664 0.910 0.674
#> ATC:pam 5 0.776 0.758 0.820 0.0977 0.914 0.728
#> SD:hclust 5 0.604 0.701 0.804 0.0467 0.951 0.859
#> CV:hclust 5 0.686 0.735 0.801 0.0893 0.874 0.584
#> MAD:hclust 5 0.611 0.534 0.731 0.0508 0.934 0.816
#> ATC:hclust 5 0.745 0.631 0.764 0.0451 0.902 0.667
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.786 0.797 0.867 0.0431 0.897 0.572
#> CV:NMF 6 0.903 0.800 0.900 0.0344 0.965 0.833
#> MAD:NMF 6 0.718 0.705 0.809 0.0485 0.850 0.458
#> ATC:NMF 6 0.750 0.595 0.779 0.0409 0.935 0.741
#> SD:skmeans 6 0.894 0.872 0.926 0.0494 0.949 0.753
#> CV:skmeans 6 0.876 0.702 0.864 0.0347 0.970 0.854
#> MAD:skmeans 6 0.906 0.875 0.926 0.0490 0.945 0.737
#> ATC:skmeans 6 0.861 0.853 0.880 0.0466 0.968 0.866
#> SD:mclust 6 0.649 0.543 0.750 0.0521 0.933 0.703
#> CV:mclust 6 0.777 0.686 0.825 0.0470 0.928 0.721
#> MAD:mclust 6 0.718 0.597 0.773 0.0430 0.952 0.785
#> ATC:mclust 6 0.672 0.620 0.748 0.0563 0.896 0.594
#> SD:kmeans 6 0.832 0.832 0.845 0.0447 0.915 0.656
#> CV:kmeans 6 0.777 0.651 0.753 0.0386 0.972 0.868
#> MAD:kmeans 6 0.822 0.797 0.830 0.0418 0.937 0.707
#> ATC:kmeans 6 0.763 0.733 0.809 0.0441 0.908 0.615
#> SD:pam 6 0.867 0.804 0.896 0.0535 0.915 0.648
#> CV:pam 6 0.836 0.689 0.864 0.0277 0.986 0.934
#> MAD:pam 6 0.879 0.814 0.893 0.0448 0.948 0.758
#> ATC:pam 6 0.804 0.727 0.862 0.0789 0.876 0.534
#> SD:hclust 6 0.631 0.584 0.766 0.0490 0.972 0.910
#> CV:hclust 6 0.698 0.700 0.799 0.0163 0.998 0.990
#> MAD:hclust 6 0.656 0.481 0.682 0.0347 0.908 0.730
#> ATC:hclust 6 0.772 0.711 0.799 0.0273 0.945 0.770
Following heatmap plots the partition for each combination of methods and the lightness correspond to the silhouette scores for samples in each method. On top the consensus subgroup is inferred from all methods by taking the mean silhouette scores as weight.
collect_stats(res_list, k = 2)
collect_stats(res_list, k = 3)
collect_stats(res_list, k = 4)
collect_stats(res_list, k = 5)
collect_stats(res_list, k = 6)
Collect partitions from all methods:
collect_classes(res_list, k = 2)
collect_classes(res_list, k = 3)
collect_classes(res_list, k = 4)
collect_classes(res_list, k = 5)
collect_classes(res_list, k = 6)
Overlap of top rows from different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "euler")
top_rows_overlap(res_list, top_n = 2000, method = "euler")
top_rows_overlap(res_list, top_n = 3000, method = "euler")
top_rows_overlap(res_list, top_n = 4000, method = "euler")
top_rows_overlap(res_list, top_n = 5000, method = "euler")
Also visualize the correspondance of rankings between different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "correspondance")
top_rows_overlap(res_list, top_n = 2000, method = "correspondance")
top_rows_overlap(res_list, top_n = 3000, method = "correspondance")
top_rows_overlap(res_list, top_n = 4000, method = "correspondance")
top_rows_overlap(res_list, top_n = 5000, method = "correspondance")
Heatmaps of the top rows:
top_rows_heatmap(res_list, top_n = 1000)
top_rows_heatmap(res_list, top_n = 2000)
top_rows_heatmap(res_list, top_n = 3000)
top_rows_heatmap(res_list, top_n = 4000)
top_rows_heatmap(res_list, top_n = 5000)
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "hclust"]
# you can also extract it by
# res = res_list["SD:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.327 0.734 0.778 0.4067 0.560 0.560
#> 3 3 0.516 0.786 0.871 0.5352 0.797 0.643
#> 4 4 0.549 0.675 0.814 0.0933 0.953 0.878
#> 5 5 0.604 0.701 0.804 0.0467 0.951 0.859
#> 6 6 0.631 0.584 0.766 0.0490 0.972 0.910
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.949 0.612 0.632 0.368
#> SRR1313063 1 0.949 0.612 0.632 0.368
#> SRR1313064 1 0.949 0.612 0.632 0.368
#> SRR1313065 1 0.891 0.640 0.692 0.308
#> SRR1313066 1 0.949 0.612 0.632 0.368
#> SRR1313067 1 0.943 0.615 0.640 0.360
#> SRR1313068 1 0.949 0.612 0.632 0.368
#> SRR1313069 1 0.949 0.612 0.632 0.368
#> SRR1313070 1 0.949 0.612 0.632 0.368
#> SRR1313071 1 0.949 0.612 0.632 0.368
#> SRR1313072 1 0.949 0.612 0.632 0.368
#> SRR1313073 1 0.949 0.612 0.632 0.368
#> SRR1313074 1 0.949 0.612 0.632 0.368
#> SRR1313075 1 0.949 0.612 0.632 0.368
#> SRR1313076 1 0.949 0.612 0.632 0.368
#> SRR1313077 1 0.949 0.612 0.632 0.368
#> SRR1313078 1 0.949 0.612 0.632 0.368
#> SRR1313079 1 0.949 0.612 0.632 0.368
#> SRR1313080 1 0.949 0.612 0.632 0.368
#> SRR1313081 1 0.949 0.612 0.632 0.368
#> SRR1313082 1 0.891 0.640 0.692 0.308
#> SRR1313083 1 0.891 0.640 0.692 0.308
#> SRR1313084 1 0.949 0.612 0.632 0.368
#> SRR1313085 1 0.949 0.612 0.632 0.368
#> SRR1313086 1 0.866 0.649 0.712 0.288
#> SRR1313087 1 0.949 0.612 0.632 0.368
#> SRR1313088 1 0.949 0.612 0.632 0.368
#> SRR1313089 1 0.949 0.612 0.632 0.368
#> SRR1313092 1 0.416 0.679 0.916 0.084
#> SRR1313090 1 0.443 0.693 0.908 0.092
#> SRR1313091 1 0.844 0.163 0.728 0.272
#> SRR1313093 1 0.745 0.714 0.788 0.212
#> SRR1313095 1 0.689 0.720 0.816 0.184
#> SRR1313096 1 0.753 0.713 0.784 0.216
#> SRR1313094 1 0.430 0.675 0.912 0.088
#> SRR1313097 1 0.416 0.679 0.916 0.084
#> SRR1313099 1 0.541 0.635 0.876 0.124
#> SRR1313098 1 0.494 0.722 0.892 0.108
#> SRR1313101 1 0.416 0.679 0.916 0.084
#> SRR1313102 1 0.402 0.683 0.920 0.080
#> SRR1313103 1 0.443 0.670 0.908 0.092
#> SRR1313100 1 0.689 0.721 0.816 0.184
#> SRR1313105 1 0.529 0.632 0.880 0.120
#> SRR1313104 1 0.456 0.690 0.904 0.096
#> SRR1313107 1 0.552 0.628 0.872 0.128
#> SRR1313106 1 0.595 0.586 0.856 0.144
#> SRR1313109 1 0.839 0.182 0.732 0.268
#> SRR1313108 1 0.753 0.713 0.784 0.216
#> SRR1313111 1 0.443 0.670 0.908 0.092
#> SRR1313110 1 0.494 0.722 0.892 0.108
#> SRR1313112 1 0.430 0.675 0.912 0.088
#> SRR1313113 1 0.469 0.660 0.900 0.100
#> SRR1313115 1 0.745 0.714 0.788 0.212
#> SRR1313114 1 0.402 0.715 0.920 0.080
#> SRR1313117 1 0.416 0.679 0.916 0.084
#> SRR1313118 1 0.482 0.713 0.896 0.104
#> SRR1313116 1 0.921 -0.172 0.664 0.336
#> SRR1313120 1 0.541 0.635 0.876 0.124
#> SRR1313119 1 0.416 0.679 0.916 0.084
#> SRR1313122 1 0.689 0.719 0.816 0.184
#> SRR1313124 1 0.443 0.693 0.908 0.092
#> SRR1313121 1 0.416 0.679 0.916 0.084
#> SRR1313125 1 0.402 0.684 0.920 0.080
#> SRR1313127 1 0.518 0.726 0.884 0.116
#> SRR1313123 1 0.388 0.713 0.924 0.076
#> SRR1313128 1 0.482 0.716 0.896 0.104
#> SRR1313126 1 0.689 0.721 0.816 0.184
#> SRR1313130 1 0.844 0.163 0.728 0.272
#> SRR1313132 1 0.506 0.664 0.888 0.112
#> SRR1313129 1 0.443 0.670 0.908 0.092
#> SRR1313133 1 0.482 0.704 0.896 0.104
#> SRR1313131 1 0.753 0.713 0.784 0.216
#> SRR1313134 1 0.506 0.703 0.888 0.112
#> SRR1313135 1 0.184 0.729 0.972 0.028
#> SRR1313136 1 0.163 0.721 0.976 0.024
#> SRR1313137 1 0.224 0.730 0.964 0.036
#> SRR1313138 1 0.278 0.726 0.952 0.048
#> SRR1313140 1 0.753 0.677 0.784 0.216
#> SRR1313141 1 0.753 0.713 0.784 0.216
#> SRR1313139 1 0.697 0.687 0.812 0.188
#> SRR1313143 1 0.753 0.713 0.784 0.216
#> SRR1313142 1 0.242 0.730 0.960 0.040
#> SRR1313144 1 0.224 0.730 0.964 0.036
#> SRR1313145 1 0.163 0.721 0.976 0.024
#> SRR1313146 1 0.163 0.726 0.976 0.024
#> SRR1313147 1 0.224 0.730 0.964 0.036
#> SRR1313150 1 0.224 0.730 0.964 0.036
#> SRR1313149 1 0.753 0.713 0.784 0.216
#> SRR1313152 1 0.224 0.730 0.964 0.036
#> SRR1313151 1 0.163 0.726 0.976 0.024
#> SRR1313154 1 0.295 0.722 0.948 0.052
#> SRR1313153 1 0.242 0.730 0.960 0.040
#> SRR1313156 1 0.295 0.725 0.948 0.052
#> SRR1313155 1 0.141 0.723 0.980 0.020
#> SRR1313157 1 0.224 0.730 0.964 0.036
#> SRR1313158 1 0.163 0.721 0.976 0.024
#> SRR1313161 1 0.242 0.729 0.960 0.040
#> SRR1313159 1 0.671 0.510 0.824 0.176
#> SRR1313160 1 0.242 0.729 0.960 0.040
#> SRR1313162 1 0.402 0.737 0.920 0.080
#> SRR1313163 1 0.278 0.726 0.952 0.048
#> SRR1313165 1 0.224 0.730 0.964 0.036
#> SRR1313166 1 0.163 0.721 0.976 0.024
#> SRR1313164 1 0.469 0.695 0.900 0.100
#> SRR1313167 1 0.224 0.730 0.964 0.036
#> SRR1313168 1 0.224 0.730 0.964 0.036
#> SRR1313170 1 0.966 -0.434 0.608 0.392
#> SRR1313169 1 0.224 0.730 0.964 0.036
#> SRR1313172 1 0.895 0.342 0.688 0.312
#> SRR1313171 1 0.469 0.695 0.900 0.100
#> SRR1313174 2 0.949 0.967 0.368 0.632
#> SRR1313173 1 0.753 0.713 0.784 0.216
#> SRR1313176 2 0.949 0.967 0.368 0.632
#> SRR1313175 2 0.963 0.953 0.388 0.612
#> SRR1313178 2 0.949 0.967 0.368 0.632
#> SRR1313177 2 0.949 0.967 0.368 0.632
#> SRR1313179 2 0.958 0.960 0.380 0.620
#> SRR1313180 2 1.000 0.777 0.492 0.508
#> SRR1313181 2 0.949 0.967 0.368 0.632
#> SRR1313183 2 0.949 0.967 0.368 0.632
#> SRR1313182 2 0.949 0.967 0.368 0.632
#> SRR1313184 2 0.958 0.960 0.380 0.620
#> SRR1313185 2 0.949 0.967 0.368 0.632
#> SRR1313188 2 1.000 0.777 0.492 0.508
#> SRR1313187 2 1.000 0.777 0.492 0.508
#> SRR1313186 2 0.949 0.967 0.368 0.632
#> SRR1313189 2 0.949 0.967 0.368 0.632
#> SRR1313190 2 0.949 0.967 0.368 0.632
#> SRR1313191 2 0.949 0.967 0.368 0.632
#> SRR1313192 2 0.949 0.967 0.368 0.632
#> SRR1313193 2 0.949 0.967 0.368 0.632
#> SRR1313194 2 0.992 0.865 0.448 0.552
#> SRR1313195 2 0.992 0.865 0.448 0.552
#> SRR1313196 2 1.000 0.786 0.488 0.512
#> SRR1313197 2 0.949 0.967 0.368 0.632
#> SRR1313198 2 0.963 0.953 0.388 0.612
#> SRR1313199 2 0.949 0.967 0.368 0.632
#> SRR1313200 2 0.998 0.820 0.472 0.528
#> SRR1313201 2 0.949 0.967 0.368 0.632
#> SRR1313202 2 0.991 0.872 0.444 0.556
#> SRR1313203 1 0.855 0.665 0.720 0.280
#> SRR1313204 2 0.949 0.967 0.368 0.632
#> SRR1313205 2 0.949 0.967 0.368 0.632
#> SRR1313207 2 0.949 0.967 0.368 0.632
#> SRR1313208 2 0.949 0.967 0.368 0.632
#> SRR1313206 2 0.949 0.967 0.368 0.632
#> SRR1313210 2 0.963 0.953 0.388 0.612
#> SRR1313209 2 0.949 0.967 0.368 0.632
#> SRR1313211 2 0.949 0.967 0.368 0.632
#> SRR1313212 2 0.949 0.967 0.368 0.632
#> SRR1313214 2 0.963 0.953 0.388 0.612
#> SRR1313215 2 0.963 0.953 0.388 0.612
#> SRR1313213 2 0.949 0.967 0.368 0.632
#> SRR1313216 2 0.963 0.953 0.388 0.612
#> SRR1313217 2 0.963 0.953 0.388 0.612
#> SRR1313219 2 0.963 0.953 0.388 0.612
#> SRR1313220 2 0.949 0.967 0.368 0.632
#> SRR1313218 2 0.949 0.967 0.368 0.632
#> SRR1313222 2 0.949 0.967 0.368 0.632
#> SRR1313221 2 0.949 0.967 0.368 0.632
#> SRR1313223 2 0.949 0.967 0.368 0.632
#> SRR1313224 2 0.949 0.967 0.368 0.632
#> SRR1313225 2 0.958 0.959 0.380 0.620
#> SRR1313226 1 0.963 -0.405 0.612 0.388
#> SRR1313227 2 0.949 0.967 0.368 0.632
#> SRR1313228 2 0.949 0.967 0.368 0.632
#> SRR1313229 2 0.949 0.967 0.368 0.632
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313063 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313064 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313065 1 0.2261 0.8788 0.932 0.000 0.068
#> SRR1313066 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313067 1 0.0747 0.9300 0.984 0.000 0.016
#> SRR1313068 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313069 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313073 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313074 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313076 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313077 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313078 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313079 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313080 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313081 1 0.0424 0.9356 0.992 0.000 0.008
#> SRR1313082 1 0.2261 0.8788 0.932 0.000 0.068
#> SRR1313083 1 0.2261 0.8788 0.932 0.000 0.068
#> SRR1313084 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313086 1 0.2860 0.8538 0.912 0.004 0.084
#> SRR1313087 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.9360 1.000 0.000 0.000
#> SRR1313092 3 0.1999 0.8244 0.012 0.036 0.952
#> SRR1313090 3 0.2689 0.8241 0.032 0.036 0.932
#> SRR1313091 3 0.4974 0.6217 0.000 0.236 0.764
#> SRR1313093 3 0.5061 0.6474 0.208 0.008 0.784
#> SRR1313095 3 0.6141 0.6778 0.232 0.032 0.736
#> SRR1313096 3 0.5247 0.6254 0.224 0.008 0.768
#> SRR1313094 3 0.1525 0.8229 0.004 0.032 0.964
#> SRR1313097 3 0.1832 0.8235 0.008 0.036 0.956
#> SRR1313099 3 0.1529 0.8164 0.000 0.040 0.960
#> SRR1313098 3 0.4217 0.8091 0.100 0.032 0.868
#> SRR1313101 3 0.1832 0.8235 0.008 0.036 0.956
#> SRR1313102 3 0.2152 0.8246 0.016 0.036 0.948
#> SRR1313103 3 0.0892 0.8205 0.000 0.020 0.980
#> SRR1313100 3 0.6224 0.6720 0.240 0.032 0.728
#> SRR1313105 3 0.2165 0.8179 0.000 0.064 0.936
#> SRR1313104 3 0.2806 0.8243 0.032 0.040 0.928
#> SRR1313107 3 0.1643 0.8155 0.000 0.044 0.956
#> SRR1313106 3 0.4110 0.7572 0.004 0.152 0.844
#> SRR1313109 3 0.4750 0.6416 0.000 0.216 0.784
#> SRR1313108 3 0.5247 0.6254 0.224 0.008 0.768
#> SRR1313111 3 0.0892 0.8205 0.000 0.020 0.980
#> SRR1313110 3 0.4056 0.8130 0.092 0.032 0.876
#> SRR1313112 3 0.1950 0.8236 0.008 0.040 0.952
#> SRR1313113 3 0.1860 0.8205 0.000 0.052 0.948
#> SRR1313115 3 0.5061 0.6474 0.208 0.008 0.784
#> SRR1313114 3 0.3434 0.8260 0.064 0.032 0.904
#> SRR1313117 3 0.1832 0.8235 0.008 0.036 0.956
#> SRR1313118 3 0.3456 0.8235 0.060 0.036 0.904
#> SRR1313116 3 0.5760 0.4328 0.000 0.328 0.672
#> SRR1313120 3 0.1529 0.8164 0.000 0.040 0.960
#> SRR1313119 3 0.1999 0.8239 0.012 0.036 0.952
#> SRR1313122 3 0.6056 0.6773 0.224 0.032 0.744
#> SRR1313124 3 0.2689 0.8241 0.032 0.036 0.932
#> SRR1313121 3 0.1832 0.8235 0.008 0.036 0.956
#> SRR1313125 3 0.1999 0.8246 0.012 0.036 0.952
#> SRR1313127 3 0.4591 0.7985 0.120 0.032 0.848
#> SRR1313123 3 0.3134 0.8279 0.052 0.032 0.916
#> SRR1313128 3 0.4059 0.8074 0.128 0.012 0.860
#> SRR1313126 3 0.6224 0.6720 0.240 0.032 0.728
#> SRR1313130 3 0.4974 0.6217 0.000 0.236 0.764
#> SRR1313132 3 0.3856 0.8245 0.072 0.040 0.888
#> SRR1313129 3 0.1529 0.8218 0.000 0.040 0.960
#> SRR1313133 3 0.3377 0.8171 0.092 0.012 0.896
#> SRR1313131 3 0.6540 0.2381 0.408 0.008 0.584
#> SRR1313134 3 0.2939 0.8135 0.072 0.012 0.916
#> SRR1313135 3 0.5466 0.8031 0.160 0.040 0.800
#> SRR1313136 3 0.4731 0.8144 0.128 0.032 0.840
#> SRR1313137 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313138 3 0.5847 0.7919 0.172 0.048 0.780
#> SRR1313140 1 0.6540 0.1064 0.584 0.008 0.408
#> SRR1313141 3 0.6669 0.0385 0.468 0.008 0.524
#> SRR1313139 1 0.6659 -0.1059 0.532 0.008 0.460
#> SRR1313143 3 0.6669 0.0385 0.468 0.008 0.524
#> SRR1313142 3 0.5526 0.7964 0.172 0.036 0.792
#> SRR1313144 3 0.5746 0.7910 0.180 0.040 0.780
#> SRR1313145 3 0.4731 0.8144 0.128 0.032 0.840
#> SRR1313146 3 0.5285 0.8085 0.148 0.040 0.812
#> SRR1313147 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313150 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313149 3 0.6669 0.0385 0.468 0.008 0.524
#> SRR1313152 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313151 3 0.5285 0.8085 0.148 0.040 0.812
#> SRR1313154 3 0.4209 0.8165 0.128 0.016 0.856
#> SRR1313153 3 0.5526 0.7964 0.172 0.036 0.792
#> SRR1313156 3 0.5791 0.7931 0.168 0.048 0.784
#> SRR1313155 3 0.4799 0.8135 0.132 0.032 0.836
#> SRR1313157 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313158 3 0.4731 0.8144 0.128 0.032 0.840
#> SRR1313161 3 0.5637 0.7938 0.172 0.040 0.788
#> SRR1313159 3 0.7582 0.3030 0.048 0.380 0.572
#> SRR1313160 3 0.5637 0.7938 0.172 0.040 0.788
#> SRR1313162 3 0.5574 0.7867 0.184 0.032 0.784
#> SRR1313163 3 0.5847 0.7919 0.172 0.048 0.780
#> SRR1313165 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313166 3 0.4731 0.8144 0.128 0.032 0.840
#> SRR1313164 3 0.2955 0.8224 0.080 0.008 0.912
#> SRR1313167 3 0.5746 0.7910 0.180 0.040 0.780
#> SRR1313168 3 0.5692 0.7927 0.176 0.040 0.784
#> SRR1313170 2 0.6513 0.4452 0.008 0.592 0.400
#> SRR1313169 3 0.5746 0.7910 0.180 0.040 0.780
#> SRR1313172 3 0.8780 0.3918 0.184 0.232 0.584
#> SRR1313171 3 0.2955 0.8224 0.080 0.008 0.912
#> SRR1313174 2 0.3267 0.8721 0.000 0.884 0.116
#> SRR1313173 3 0.6553 0.2263 0.412 0.008 0.580
#> SRR1313176 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313175 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313178 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313177 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313179 2 0.1860 0.8870 0.000 0.948 0.052
#> SRR1313180 2 0.5760 0.6414 0.000 0.672 0.328
#> SRR1313181 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313183 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313182 2 0.2261 0.8874 0.000 0.932 0.068
#> SRR1313184 2 0.1860 0.8870 0.000 0.948 0.052
#> SRR1313185 2 0.2625 0.8836 0.000 0.916 0.084
#> SRR1313188 2 0.5760 0.6414 0.000 0.672 0.328
#> SRR1313187 2 0.5760 0.6414 0.000 0.672 0.328
#> SRR1313186 2 0.2625 0.8836 0.000 0.916 0.084
#> SRR1313189 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313190 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313191 2 0.3267 0.8721 0.000 0.884 0.116
#> SRR1313192 2 0.1411 0.8899 0.000 0.964 0.036
#> SRR1313193 2 0.1289 0.8897 0.000 0.968 0.032
#> SRR1313194 2 0.5431 0.7100 0.000 0.716 0.284
#> SRR1313195 2 0.5431 0.7100 0.000 0.716 0.284
#> SRR1313196 2 0.5733 0.6484 0.000 0.676 0.324
#> SRR1313197 2 0.3192 0.8738 0.000 0.888 0.112
#> SRR1313198 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313199 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313200 2 0.5621 0.6754 0.000 0.692 0.308
#> SRR1313201 2 0.0592 0.8859 0.000 0.988 0.012
#> SRR1313202 2 0.5529 0.6943 0.000 0.704 0.296
#> SRR1313203 1 0.7726 0.5813 0.676 0.132 0.192
#> SRR1313204 2 0.0592 0.8859 0.000 0.988 0.012
#> SRR1313205 2 0.1411 0.8899 0.000 0.964 0.036
#> SRR1313207 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313208 2 0.1411 0.8899 0.000 0.964 0.036
#> SRR1313206 2 0.0592 0.8859 0.000 0.988 0.012
#> SRR1313210 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313209 2 0.3267 0.8721 0.000 0.884 0.116
#> SRR1313211 2 0.1289 0.8897 0.000 0.968 0.032
#> SRR1313212 2 0.0592 0.8859 0.000 0.988 0.012
#> SRR1313214 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313215 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313213 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313216 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313217 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313219 2 0.4002 0.8478 0.000 0.840 0.160
#> SRR1313220 2 0.0592 0.8859 0.000 0.988 0.012
#> SRR1313218 2 0.1411 0.8899 0.000 0.964 0.036
#> SRR1313222 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313221 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313223 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313224 2 0.1289 0.8897 0.000 0.968 0.032
#> SRR1313225 2 0.3816 0.8551 0.000 0.852 0.148
#> SRR1313226 2 0.6267 0.3260 0.000 0.548 0.452
#> SRR1313227 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313228 2 0.0424 0.8843 0.000 0.992 0.008
#> SRR1313229 2 0.0424 0.8843 0.000 0.992 0.008
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.4978 0.7792 0.384 0.000 0.004 0.612
#> SRR1313065 4 0.6305 0.6992 0.424 0.000 0.060 0.516
#> SRR1313066 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313067 4 0.0336 0.5891 0.000 0.000 0.008 0.992
#> SRR1313068 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.5016 0.7775 0.396 0.000 0.004 0.600
#> SRR1313070 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313071 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313072 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313073 4 0.2408 0.6543 0.104 0.000 0.000 0.896
#> SRR1313074 4 0.4991 0.7788 0.388 0.000 0.004 0.608
#> SRR1313075 4 0.4991 0.7788 0.388 0.000 0.004 0.608
#> SRR1313076 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313078 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313079 4 0.4978 0.7792 0.384 0.000 0.004 0.612
#> SRR1313080 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.0000 0.5983 0.000 0.000 0.000 1.000
#> SRR1313082 4 0.6292 0.7055 0.416 0.000 0.060 0.524
#> SRR1313083 4 0.6292 0.7055 0.416 0.000 0.060 0.524
#> SRR1313084 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313085 4 0.5039 0.7770 0.404 0.000 0.004 0.592
#> SRR1313086 4 0.6586 0.6731 0.420 0.000 0.080 0.500
#> SRR1313087 4 0.4978 0.7792 0.384 0.000 0.004 0.612
#> SRR1313088 4 0.5016 0.7775 0.396 0.000 0.004 0.600
#> SRR1313089 4 0.4991 0.7788 0.388 0.000 0.004 0.608
#> SRR1313092 3 0.1124 0.7426 0.012 0.004 0.972 0.012
#> SRR1313090 3 0.1598 0.7351 0.020 0.004 0.956 0.020
#> SRR1313091 3 0.4590 0.5406 0.036 0.192 0.772 0.000
#> SRR1313093 3 0.7504 -0.3498 0.344 0.000 0.464 0.192
#> SRR1313095 3 0.4692 0.4955 0.032 0.000 0.756 0.212
#> SRR1313096 3 0.7599 -0.3970 0.344 0.000 0.448 0.208
#> SRR1313094 3 0.0657 0.7435 0.012 0.000 0.984 0.004
#> SRR1313097 3 0.0992 0.7424 0.012 0.004 0.976 0.008
#> SRR1313099 3 0.3760 0.6534 0.136 0.028 0.836 0.000
#> SRR1313098 3 0.2984 0.7002 0.028 0.000 0.888 0.084
#> SRR1313101 3 0.0859 0.7427 0.008 0.004 0.980 0.008
#> SRR1313102 3 0.0992 0.7418 0.012 0.004 0.976 0.008
#> SRR1313103 3 0.2216 0.7094 0.092 0.000 0.908 0.000
#> SRR1313100 3 0.4764 0.4867 0.032 0.000 0.748 0.220
#> SRR1313105 3 0.1936 0.7383 0.028 0.032 0.940 0.000
#> SRR1313104 3 0.1745 0.7351 0.020 0.008 0.952 0.020
#> SRR1313107 3 0.3856 0.6508 0.136 0.032 0.832 0.000
#> SRR1313106 3 0.3350 0.6896 0.016 0.116 0.864 0.004
#> SRR1313109 3 0.5759 0.4786 0.112 0.180 0.708 0.000
#> SRR1313108 3 0.7599 -0.3970 0.344 0.000 0.448 0.208
#> SRR1313111 3 0.2216 0.7094 0.092 0.000 0.908 0.000
#> SRR1313110 3 0.2845 0.7069 0.028 0.000 0.896 0.076
#> SRR1313112 3 0.0859 0.7437 0.008 0.004 0.980 0.008
#> SRR1313113 3 0.1174 0.7414 0.012 0.020 0.968 0.000
#> SRR1313115 3 0.7504 -0.3498 0.344 0.000 0.464 0.192
#> SRR1313114 3 0.2224 0.7349 0.032 0.000 0.928 0.040
#> SRR1313117 3 0.0859 0.7427 0.008 0.004 0.980 0.008
#> SRR1313118 3 0.2275 0.7281 0.020 0.004 0.928 0.048
#> SRR1313116 3 0.5392 0.4238 0.040 0.280 0.680 0.000
#> SRR1313120 3 0.3760 0.6534 0.136 0.028 0.836 0.000
#> SRR1313119 3 0.1114 0.7412 0.016 0.004 0.972 0.008
#> SRR1313122 3 0.5429 0.4148 0.072 0.000 0.720 0.208
#> SRR1313124 3 0.1598 0.7351 0.020 0.004 0.956 0.020
#> SRR1313121 3 0.0992 0.7421 0.012 0.004 0.976 0.008
#> SRR1313125 3 0.0992 0.7437 0.012 0.004 0.976 0.008
#> SRR1313127 3 0.3372 0.6853 0.036 0.000 0.868 0.096
#> SRR1313123 3 0.1936 0.7405 0.032 0.000 0.940 0.028
#> SRR1313128 3 0.5110 0.5451 0.328 0.000 0.656 0.016
#> SRR1313126 3 0.4764 0.4867 0.032 0.000 0.748 0.220
#> SRR1313130 3 0.4590 0.5406 0.036 0.192 0.772 0.000
#> SRR1313132 3 0.5022 0.6498 0.264 0.028 0.708 0.000
#> SRR1313129 3 0.0927 0.7428 0.016 0.008 0.976 0.000
#> SRR1313133 3 0.5038 0.5183 0.336 0.000 0.652 0.012
#> SRR1313131 1 0.7689 0.7711 0.444 0.000 0.236 0.320
#> SRR1313134 3 0.5174 0.3693 0.368 0.000 0.620 0.012
#> SRR1313135 3 0.4004 0.7413 0.164 0.000 0.812 0.024
#> SRR1313136 3 0.3900 0.7446 0.164 0.000 0.816 0.020
#> SRR1313137 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313138 3 0.4693 0.7327 0.160 0.012 0.792 0.036
#> SRR1313140 3 0.7851 -0.0272 0.288 0.000 0.400 0.312
#> SRR1313141 1 0.7105 0.7868 0.560 0.000 0.184 0.256
#> SRR1313139 3 0.7706 0.1660 0.280 0.000 0.452 0.268
#> SRR1313143 1 0.7105 0.7868 0.560 0.000 0.184 0.256
#> SRR1313142 3 0.4290 0.7369 0.164 0.000 0.800 0.036
#> SRR1313144 3 0.4517 0.7321 0.168 0.004 0.792 0.036
#> SRR1313145 3 0.3900 0.7446 0.164 0.000 0.816 0.020
#> SRR1313146 3 0.3900 0.7435 0.164 0.000 0.816 0.020
#> SRR1313147 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313150 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313149 1 0.7105 0.7868 0.560 0.000 0.184 0.256
#> SRR1313152 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313151 3 0.3900 0.7435 0.164 0.000 0.816 0.020
#> SRR1313154 3 0.4524 0.7132 0.204 0.000 0.768 0.028
#> SRR1313153 3 0.4290 0.7369 0.164 0.000 0.800 0.036
#> SRR1313156 3 0.4647 0.7343 0.156 0.012 0.796 0.036
#> SRR1313155 3 0.3946 0.7433 0.168 0.000 0.812 0.020
#> SRR1313157 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313158 3 0.3900 0.7446 0.164 0.000 0.816 0.020
#> SRR1313161 3 0.4425 0.7349 0.160 0.004 0.800 0.036
#> SRR1313159 3 0.6248 0.3615 0.060 0.340 0.596 0.004
#> SRR1313160 3 0.4425 0.7349 0.160 0.004 0.800 0.036
#> SRR1313162 3 0.4599 0.7078 0.088 0.000 0.800 0.112
#> SRR1313163 3 0.4693 0.7327 0.160 0.012 0.792 0.036
#> SRR1313165 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313166 3 0.3900 0.7446 0.164 0.000 0.816 0.020
#> SRR1313164 3 0.4891 0.5753 0.308 0.000 0.680 0.012
#> SRR1313167 3 0.4517 0.7321 0.168 0.004 0.792 0.036
#> SRR1313168 3 0.4471 0.7336 0.164 0.004 0.796 0.036
#> SRR1313170 2 0.6120 0.3768 0.040 0.540 0.416 0.004
#> SRR1313169 3 0.4517 0.7321 0.168 0.004 0.792 0.036
#> SRR1313172 1 0.9182 0.6101 0.440 0.212 0.240 0.108
#> SRR1313171 3 0.4891 0.5753 0.308 0.000 0.680 0.012
#> SRR1313174 2 0.3324 0.8098 0.012 0.852 0.136 0.000
#> SRR1313173 1 0.7670 0.7758 0.448 0.000 0.232 0.320
#> SRR1313176 2 0.1118 0.8085 0.036 0.964 0.000 0.000
#> SRR1313175 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313178 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313177 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313179 2 0.3176 0.8211 0.036 0.880 0.084 0.000
#> SRR1313180 2 0.5649 0.5883 0.036 0.620 0.344 0.000
#> SRR1313181 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313183 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313182 2 0.2480 0.8246 0.008 0.904 0.088 0.000
#> SRR1313184 2 0.3176 0.8211 0.036 0.880 0.084 0.000
#> SRR1313185 2 0.2867 0.8197 0.012 0.884 0.104 0.000
#> SRR1313188 2 0.5649 0.5883 0.036 0.620 0.344 0.000
#> SRR1313187 2 0.5649 0.5883 0.036 0.620 0.344 0.000
#> SRR1313186 2 0.2867 0.8197 0.012 0.884 0.104 0.000
#> SRR1313189 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313190 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313191 2 0.3324 0.8098 0.012 0.852 0.136 0.000
#> SRR1313192 2 0.2101 0.8269 0.012 0.928 0.060 0.000
#> SRR1313193 2 0.1302 0.8249 0.000 0.956 0.044 0.000
#> SRR1313194 2 0.5430 0.6569 0.036 0.664 0.300 0.000
#> SRR1313195 2 0.5430 0.6569 0.036 0.664 0.300 0.000
#> SRR1313196 2 0.5632 0.5960 0.036 0.624 0.340 0.000
#> SRR1313197 2 0.3271 0.8112 0.012 0.856 0.132 0.000
#> SRR1313198 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313199 2 0.1118 0.8085 0.036 0.964 0.000 0.000
#> SRR1313200 2 0.5558 0.6254 0.036 0.640 0.324 0.000
#> SRR1313201 2 0.1209 0.8114 0.032 0.964 0.004 0.000
#> SRR1313202 2 0.5496 0.6429 0.036 0.652 0.312 0.000
#> SRR1313203 4 0.8161 -0.3319 0.240 0.120 0.084 0.556
#> SRR1313204 2 0.1209 0.8114 0.032 0.964 0.004 0.000
#> SRR1313205 2 0.1637 0.8265 0.000 0.940 0.060 0.000
#> SRR1313207 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313208 2 0.1637 0.8265 0.000 0.940 0.060 0.000
#> SRR1313206 2 0.1209 0.8114 0.032 0.964 0.004 0.000
#> SRR1313210 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313209 2 0.3324 0.8098 0.012 0.852 0.136 0.000
#> SRR1313211 2 0.1302 0.8249 0.000 0.956 0.044 0.000
#> SRR1313212 2 0.1209 0.8114 0.032 0.964 0.004 0.000
#> SRR1313214 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313215 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313213 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313216 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313217 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313219 2 0.4375 0.7799 0.032 0.788 0.180 0.000
#> SRR1313220 2 0.1209 0.8114 0.032 0.964 0.004 0.000
#> SRR1313218 2 0.1637 0.8265 0.000 0.940 0.060 0.000
#> SRR1313222 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313221 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313223 2 0.1302 0.8058 0.044 0.956 0.000 0.000
#> SRR1313224 2 0.1557 0.8263 0.000 0.944 0.056 0.000
#> SRR1313225 2 0.4095 0.7879 0.024 0.804 0.172 0.000
#> SRR1313226 2 0.5935 0.2589 0.036 0.496 0.468 0.000
#> SRR1313227 2 0.1118 0.8085 0.036 0.964 0.000 0.000
#> SRR1313228 2 0.1118 0.8085 0.036 0.964 0.000 0.000
#> SRR1313229 2 0.1118 0.8085 0.036 0.964 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313063 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313064 4 0.0963 0.8412 0.000 0.000 0.000 0.964 0.036
#> SRR1313065 4 0.3186 0.7744 0.056 0.000 0.052 0.872 0.020
#> SRR1313066 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313067 5 0.3203 0.9011 0.012 0.000 0.000 0.168 0.820
#> SRR1313068 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313069 4 0.0671 0.8479 0.000 0.000 0.004 0.980 0.016
#> SRR1313070 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313071 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313072 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313073 5 0.3990 0.7313 0.004 0.000 0.000 0.308 0.688
#> SRR1313074 4 0.0703 0.8466 0.000 0.000 0.000 0.976 0.024
#> SRR1313075 4 0.0703 0.8466 0.000 0.000 0.000 0.976 0.024
#> SRR1313076 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313077 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313078 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313079 4 0.0963 0.8412 0.000 0.000 0.000 0.964 0.036
#> SRR1313080 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313081 5 0.2970 0.9135 0.004 0.000 0.000 0.168 0.828
#> SRR1313082 4 0.3134 0.7787 0.056 0.000 0.044 0.876 0.024
#> SRR1313083 4 0.3134 0.7787 0.056 0.000 0.044 0.876 0.024
#> SRR1313084 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313085 4 0.0290 0.8467 0.000 0.000 0.008 0.992 0.000
#> SRR1313086 4 0.3514 0.7482 0.072 0.000 0.056 0.852 0.020
#> SRR1313087 4 0.0963 0.8412 0.000 0.000 0.000 0.964 0.036
#> SRR1313088 4 0.0671 0.8479 0.000 0.000 0.004 0.980 0.016
#> SRR1313089 4 0.0609 0.8473 0.000 0.000 0.000 0.980 0.020
#> SRR1313092 1 0.1280 0.7149 0.960 0.008 0.024 0.000 0.008
#> SRR1313090 1 0.1588 0.7034 0.948 0.008 0.028 0.000 0.016
#> SRR1313091 1 0.4333 0.5083 0.752 0.188 0.060 0.000 0.000
#> SRR1313093 3 0.6554 0.5455 0.396 0.000 0.404 0.000 0.200
#> SRR1313095 1 0.4316 0.4482 0.748 0.000 0.040 0.004 0.208
#> SRR1313096 3 0.6616 0.5711 0.380 0.000 0.404 0.000 0.216
#> SRR1313094 1 0.0898 0.7169 0.972 0.008 0.020 0.000 0.000
#> SRR1313097 1 0.1243 0.7142 0.960 0.008 0.028 0.000 0.004
#> SRR1313099 1 0.3616 0.5836 0.804 0.032 0.164 0.000 0.000
#> SRR1313098 1 0.2754 0.6673 0.880 0.000 0.040 0.000 0.080
#> SRR1313101 1 0.0960 0.7150 0.972 0.008 0.016 0.000 0.004
#> SRR1313102 1 0.1059 0.7132 0.968 0.008 0.020 0.000 0.004
#> SRR1313103 1 0.2411 0.6685 0.884 0.008 0.108 0.000 0.000
#> SRR1313100 1 0.4305 0.4384 0.744 0.000 0.036 0.004 0.216
#> SRR1313105 1 0.2149 0.7048 0.916 0.036 0.048 0.000 0.000
#> SRR1313104 1 0.1701 0.7030 0.944 0.012 0.028 0.000 0.016
#> SRR1313107 1 0.3695 0.5799 0.800 0.036 0.164 0.000 0.000
#> SRR1313106 1 0.2824 0.6681 0.864 0.116 0.020 0.000 0.000
#> SRR1313109 1 0.5263 0.4242 0.680 0.176 0.144 0.000 0.000
#> SRR1313108 3 0.6616 0.5711 0.380 0.000 0.404 0.000 0.216
#> SRR1313111 1 0.2411 0.6685 0.884 0.008 0.108 0.000 0.000
#> SRR1313110 1 0.2632 0.6754 0.888 0.000 0.040 0.000 0.072
#> SRR1313112 1 0.0740 0.7182 0.980 0.008 0.008 0.000 0.004
#> SRR1313113 1 0.1493 0.7138 0.948 0.028 0.024 0.000 0.000
#> SRR1313115 3 0.6554 0.5455 0.396 0.000 0.404 0.000 0.200
#> SRR1313114 1 0.2157 0.7021 0.920 0.004 0.040 0.000 0.036
#> SRR1313117 1 0.0854 0.7161 0.976 0.008 0.012 0.000 0.004
#> SRR1313118 1 0.2193 0.6937 0.920 0.008 0.028 0.000 0.044
#> SRR1313116 1 0.5535 0.3414 0.620 0.272 0.108 0.000 0.000
#> SRR1313120 1 0.3616 0.5836 0.804 0.032 0.164 0.000 0.000
#> SRR1313119 1 0.1153 0.7122 0.964 0.008 0.024 0.000 0.004
#> SRR1313122 1 0.4893 0.3481 0.704 0.000 0.088 0.000 0.208
#> SRR1313124 1 0.1588 0.7034 0.948 0.008 0.028 0.000 0.016
#> SRR1313121 1 0.1059 0.7138 0.968 0.008 0.020 0.000 0.004
#> SRR1313125 1 0.1059 0.7161 0.968 0.008 0.020 0.000 0.004
#> SRR1313127 1 0.3130 0.6545 0.856 0.000 0.048 0.000 0.096
#> SRR1313123 1 0.1901 0.7098 0.932 0.004 0.040 0.000 0.024
#> SRR1313128 1 0.6011 0.4242 0.556 0.000 0.356 0.052 0.036
#> SRR1313126 1 0.4305 0.4384 0.744 0.000 0.036 0.004 0.216
#> SRR1313130 1 0.4333 0.5083 0.752 0.188 0.060 0.000 0.000
#> SRR1313132 1 0.5361 0.5335 0.580 0.024 0.372 0.024 0.000
#> SRR1313129 1 0.1211 0.7151 0.960 0.016 0.024 0.000 0.000
#> SRR1313133 1 0.5723 0.3637 0.548 0.000 0.384 0.020 0.048
#> SRR1313131 3 0.6096 0.5437 0.116 0.000 0.576 0.012 0.296
#> SRR1313134 1 0.5865 0.1490 0.508 0.000 0.416 0.016 0.060
#> SRR1313135 1 0.4725 0.7173 0.732 0.000 0.188 0.076 0.004
#> SRR1313136 1 0.4465 0.7162 0.736 0.000 0.204 0.060 0.000
#> SRR1313137 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313138 1 0.5217 0.7059 0.716 0.012 0.176 0.092 0.004
#> SRR1313140 4 0.6162 0.1472 0.360 0.000 0.112 0.520 0.008
#> SRR1313141 3 0.7076 0.4836 0.072 0.000 0.556 0.208 0.164
#> SRR1313139 4 0.6164 -0.0436 0.408 0.000 0.116 0.472 0.004
#> SRR1313143 3 0.7076 0.4836 0.072 0.000 0.556 0.208 0.164
#> SRR1313142 1 0.4888 0.7124 0.720 0.000 0.188 0.088 0.004
#> SRR1313144 1 0.5006 0.7084 0.724 0.004 0.172 0.096 0.004
#> SRR1313145 1 0.4465 0.7162 0.736 0.000 0.204 0.060 0.000
#> SRR1313146 1 0.4677 0.7173 0.732 0.000 0.196 0.068 0.004
#> SRR1313147 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313150 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313149 3 0.7076 0.4836 0.072 0.000 0.556 0.208 0.164
#> SRR1313152 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313151 1 0.4677 0.7173 0.732 0.000 0.196 0.068 0.004
#> SRR1313154 1 0.5117 0.6546 0.672 0.000 0.268 0.044 0.016
#> SRR1313153 1 0.4888 0.7124 0.720 0.000 0.188 0.088 0.004
#> SRR1313156 1 0.5200 0.7075 0.716 0.012 0.180 0.088 0.004
#> SRR1313155 1 0.4527 0.7143 0.732 0.000 0.204 0.064 0.000
#> SRR1313157 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313158 1 0.4465 0.7162 0.736 0.000 0.204 0.060 0.000
#> SRR1313161 1 0.4919 0.7119 0.732 0.004 0.168 0.092 0.004
#> SRR1313159 1 0.6553 0.3369 0.512 0.336 0.132 0.020 0.000
#> SRR1313160 1 0.4919 0.7119 0.732 0.004 0.168 0.092 0.004
#> SRR1313162 1 0.5019 0.6836 0.740 0.000 0.136 0.020 0.104
#> SRR1313163 1 0.5217 0.7059 0.716 0.012 0.176 0.092 0.004
#> SRR1313165 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313166 1 0.4465 0.7162 0.736 0.000 0.204 0.060 0.000
#> SRR1313164 1 0.5280 0.4680 0.584 0.000 0.372 0.024 0.020
#> SRR1313167 1 0.5006 0.7084 0.724 0.004 0.172 0.096 0.004
#> SRR1313168 1 0.4970 0.7103 0.728 0.004 0.168 0.096 0.004
#> SRR1313170 2 0.5873 0.4073 0.372 0.532 0.092 0.004 0.000
#> SRR1313169 1 0.5006 0.7084 0.724 0.004 0.172 0.096 0.004
#> SRR1313172 3 0.7103 0.4075 0.100 0.216 0.572 0.004 0.108
#> SRR1313171 1 0.5280 0.4680 0.584 0.000 0.372 0.024 0.020
#> SRR1313174 2 0.3291 0.8180 0.088 0.848 0.064 0.000 0.000
#> SRR1313173 3 0.6217 0.5413 0.112 0.000 0.576 0.020 0.292
#> SRR1313176 2 0.1549 0.8169 0.000 0.944 0.040 0.000 0.016
#> SRR1313175 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313178 2 0.1701 0.8138 0.000 0.936 0.048 0.000 0.016
#> SRR1313177 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313179 2 0.3287 0.8279 0.068 0.864 0.052 0.000 0.016
#> SRR1313180 2 0.5452 0.6153 0.292 0.616 0.092 0.000 0.000
#> SRR1313181 2 0.1701 0.8138 0.000 0.936 0.048 0.000 0.016
#> SRR1313183 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313182 2 0.2300 0.8314 0.072 0.904 0.024 0.000 0.000
#> SRR1313184 2 0.3287 0.8279 0.068 0.864 0.052 0.000 0.016
#> SRR1313185 2 0.2694 0.8269 0.076 0.884 0.040 0.000 0.000
#> SRR1313188 2 0.5452 0.6153 0.292 0.616 0.092 0.000 0.000
#> SRR1313187 2 0.5452 0.6153 0.292 0.616 0.092 0.000 0.000
#> SRR1313186 2 0.2694 0.8269 0.076 0.884 0.040 0.000 0.000
#> SRR1313189 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313190 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313191 2 0.3291 0.8180 0.088 0.848 0.064 0.000 0.000
#> SRR1313192 2 0.1670 0.8342 0.052 0.936 0.012 0.000 0.000
#> SRR1313193 2 0.0963 0.8325 0.036 0.964 0.000 0.000 0.000
#> SRR1313194 2 0.5216 0.6731 0.248 0.660 0.092 0.000 0.000
#> SRR1313195 2 0.5216 0.6731 0.248 0.660 0.092 0.000 0.000
#> SRR1313196 2 0.5433 0.6213 0.288 0.620 0.092 0.000 0.000
#> SRR1313197 2 0.3226 0.8191 0.088 0.852 0.060 0.000 0.000
#> SRR1313198 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313199 2 0.1549 0.8169 0.000 0.944 0.040 0.000 0.016
#> SRR1313200 2 0.5353 0.6445 0.272 0.636 0.092 0.000 0.000
#> SRR1313201 2 0.1386 0.8192 0.000 0.952 0.032 0.000 0.016
#> SRR1313202 2 0.5287 0.6605 0.260 0.648 0.092 0.000 0.000
#> SRR1313203 5 0.6871 0.0701 0.016 0.100 0.380 0.024 0.480
#> SRR1313204 2 0.1386 0.8192 0.000 0.952 0.032 0.000 0.016
#> SRR1313205 2 0.1270 0.8340 0.052 0.948 0.000 0.000 0.000
#> SRR1313207 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313208 2 0.1270 0.8340 0.052 0.948 0.000 0.000 0.000
#> SRR1313206 2 0.1386 0.8192 0.000 0.952 0.032 0.000 0.016
#> SRR1313210 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313209 2 0.3291 0.8180 0.088 0.848 0.064 0.000 0.000
#> SRR1313211 2 0.0963 0.8325 0.036 0.964 0.000 0.000 0.000
#> SRR1313212 2 0.1386 0.8192 0.000 0.952 0.032 0.000 0.016
#> SRR1313214 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313215 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313213 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313216 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313217 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313219 2 0.4149 0.7913 0.128 0.784 0.088 0.000 0.000
#> SRR1313220 2 0.1386 0.8192 0.000 0.952 0.032 0.000 0.016
#> SRR1313218 2 0.1270 0.8340 0.052 0.948 0.000 0.000 0.000
#> SRR1313222 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313221 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313223 2 0.1893 0.8105 0.000 0.928 0.048 0.000 0.024
#> SRR1313224 2 0.1197 0.8338 0.048 0.952 0.000 0.000 0.000
#> SRR1313225 2 0.3946 0.7989 0.120 0.800 0.080 0.000 0.000
#> SRR1313226 2 0.5803 0.3172 0.420 0.488 0.092 0.000 0.000
#> SRR1313227 2 0.1549 0.8169 0.000 0.944 0.040 0.000 0.016
#> SRR1313228 2 0.1549 0.8169 0.000 0.944 0.040 0.000 0.016
#> SRR1313229 2 0.1549 0.8169 0.000 0.944 0.040 0.000 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313063 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313064 4 0.1141 0.8316 0.052 0.000 0.000 0.948 0.000 0.000
#> SRR1313065 4 0.3336 0.7459 0.024 0.000 0.052 0.840 0.000 0.084
#> SRR1313066 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313067 1 0.0363 0.9530 0.988 0.000 0.012 0.000 0.000 0.000
#> SRR1313068 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313069 4 0.0777 0.8375 0.024 0.000 0.000 0.972 0.000 0.004
#> SRR1313070 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313071 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313072 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313073 1 0.2402 0.7230 0.856 0.000 0.004 0.140 0.000 0.000
#> SRR1313074 4 0.0937 0.8363 0.040 0.000 0.000 0.960 0.000 0.000
#> SRR1313075 4 0.0937 0.8363 0.040 0.000 0.000 0.960 0.000 0.000
#> SRR1313076 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313077 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313078 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313079 4 0.1141 0.8316 0.052 0.000 0.000 0.948 0.000 0.000
#> SRR1313080 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313081 1 0.0146 0.9696 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313082 4 0.3455 0.7510 0.036 0.000 0.052 0.836 0.000 0.076
#> SRR1313083 4 0.3455 0.7510 0.036 0.000 0.052 0.836 0.000 0.076
#> SRR1313084 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313085 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313086 4 0.3671 0.7146 0.024 0.000 0.068 0.816 0.000 0.092
#> SRR1313087 4 0.1141 0.8316 0.052 0.000 0.000 0.948 0.000 0.000
#> SRR1313088 4 0.0777 0.8375 0.024 0.000 0.000 0.972 0.000 0.004
#> SRR1313089 4 0.0865 0.8369 0.036 0.000 0.000 0.964 0.000 0.000
#> SRR1313092 3 0.1321 0.6116 0.004 0.020 0.952 0.000 0.000 0.024
#> SRR1313090 3 0.1605 0.6059 0.012 0.016 0.940 0.000 0.000 0.032
#> SRR1313091 3 0.4313 0.3990 0.000 0.184 0.728 0.000 0.004 0.084
#> SRR1313093 6 0.6899 0.3771 0.148 0.000 0.356 0.000 0.092 0.404
#> SRR1313095 3 0.4248 0.4109 0.180 0.000 0.748 0.000 0.024 0.048
#> SRR1313096 6 0.6971 0.3645 0.164 0.000 0.340 0.000 0.092 0.404
#> SRR1313094 3 0.1261 0.6108 0.000 0.024 0.952 0.000 0.000 0.024
#> SRR1313097 3 0.1257 0.6097 0.000 0.020 0.952 0.000 0.000 0.028
#> SRR1313099 3 0.3388 0.4442 0.000 0.036 0.792 0.000 0.000 0.172
#> SRR1313098 3 0.2830 0.5727 0.064 0.000 0.864 0.000 0.004 0.068
#> SRR1313101 3 0.1003 0.6114 0.000 0.020 0.964 0.000 0.000 0.016
#> SRR1313102 3 0.1088 0.6121 0.000 0.016 0.960 0.000 0.000 0.024
#> SRR1313103 3 0.2311 0.5462 0.000 0.016 0.880 0.000 0.000 0.104
#> SRR1313100 3 0.4248 0.4021 0.188 0.000 0.744 0.000 0.024 0.044
#> SRR1313105 3 0.2265 0.5867 0.000 0.052 0.896 0.000 0.000 0.052
#> SRR1313104 3 0.1693 0.6053 0.012 0.020 0.936 0.000 0.000 0.032
#> SRR1313107 3 0.3456 0.4397 0.000 0.040 0.788 0.000 0.000 0.172
#> SRR1313106 3 0.2950 0.5267 0.000 0.148 0.828 0.000 0.000 0.024
#> SRR1313109 3 0.4968 0.3084 0.000 0.164 0.664 0.000 0.004 0.168
#> SRR1313108 6 0.6971 0.3645 0.164 0.000 0.340 0.000 0.092 0.404
#> SRR1313111 3 0.2311 0.5462 0.000 0.016 0.880 0.000 0.000 0.104
#> SRR1313110 3 0.2711 0.5776 0.056 0.000 0.872 0.000 0.004 0.068
#> SRR1313112 3 0.0909 0.6146 0.000 0.020 0.968 0.000 0.000 0.012
#> SRR1313113 3 0.1780 0.6005 0.000 0.048 0.924 0.000 0.000 0.028
#> SRR1313115 6 0.6899 0.3771 0.148 0.000 0.356 0.000 0.092 0.404
#> SRR1313114 3 0.1789 0.6027 0.032 0.000 0.924 0.000 0.000 0.044
#> SRR1313117 3 0.0806 0.6141 0.000 0.020 0.972 0.000 0.000 0.008
#> SRR1313118 3 0.1864 0.5970 0.040 0.004 0.924 0.000 0.000 0.032
#> SRR1313116 3 0.5406 0.2153 0.000 0.276 0.580 0.000 0.004 0.140
#> SRR1313120 3 0.3388 0.4442 0.000 0.036 0.792 0.000 0.000 0.172
#> SRR1313119 3 0.1003 0.6110 0.000 0.016 0.964 0.000 0.000 0.020
#> SRR1313122 3 0.4875 0.3281 0.164 0.000 0.704 0.000 0.024 0.108
#> SRR1313124 3 0.1605 0.6059 0.012 0.016 0.940 0.000 0.000 0.032
#> SRR1313121 3 0.0914 0.6127 0.000 0.016 0.968 0.000 0.000 0.016
#> SRR1313125 3 0.0914 0.6155 0.000 0.016 0.968 0.000 0.000 0.016
#> SRR1313127 3 0.3219 0.5600 0.076 0.000 0.840 0.000 0.008 0.076
#> SRR1313123 3 0.1549 0.6067 0.020 0.000 0.936 0.000 0.000 0.044
#> SRR1313128 6 0.5809 -0.0455 0.000 0.000 0.416 0.028 0.092 0.464
#> SRR1313126 3 0.4248 0.4021 0.188 0.000 0.744 0.000 0.024 0.044
#> SRR1313130 3 0.4313 0.3990 0.000 0.184 0.728 0.000 0.004 0.084
#> SRR1313132 3 0.5332 0.2126 0.000 0.024 0.488 0.000 0.052 0.436
#> SRR1313129 3 0.1334 0.6080 0.000 0.032 0.948 0.000 0.000 0.020
#> SRR1313133 6 0.5358 0.0668 0.000 0.000 0.392 0.000 0.112 0.496
#> SRR1313131 6 0.6932 -0.1117 0.144 0.000 0.060 0.016 0.340 0.440
#> SRR1313134 6 0.5583 0.2480 0.000 0.000 0.336 0.000 0.156 0.508
#> SRR1313135 3 0.4110 0.5640 0.000 0.000 0.608 0.016 0.000 0.376
#> SRR1313136 3 0.3945 0.5537 0.000 0.000 0.612 0.008 0.000 0.380
#> SRR1313137 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313138 3 0.4726 0.5588 0.000 0.012 0.600 0.036 0.000 0.352
#> SRR1313140 4 0.6004 0.1316 0.004 0.000 0.256 0.476 0.000 0.264
#> SRR1313141 6 0.6872 -0.2257 0.032 0.000 0.016 0.208 0.320 0.424
#> SRR1313139 4 0.6017 0.0252 0.000 0.000 0.304 0.428 0.000 0.268
#> SRR1313143 6 0.6872 -0.2257 0.032 0.000 0.016 0.208 0.320 0.424
#> SRR1313142 3 0.4333 0.5590 0.000 0.000 0.596 0.028 0.000 0.376
#> SRR1313144 3 0.4554 0.5565 0.000 0.004 0.600 0.036 0.000 0.360
#> SRR1313145 3 0.3945 0.5537 0.000 0.000 0.612 0.008 0.000 0.380
#> SRR1313146 3 0.3955 0.5593 0.000 0.000 0.608 0.008 0.000 0.384
#> SRR1313147 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313150 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313149 6 0.6872 -0.2257 0.032 0.000 0.016 0.208 0.320 0.424
#> SRR1313152 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313151 3 0.3955 0.5593 0.000 0.000 0.608 0.008 0.000 0.384
#> SRR1313154 3 0.4494 0.4236 0.000 0.000 0.544 0.000 0.032 0.424
#> SRR1313153 3 0.4333 0.5590 0.000 0.000 0.596 0.028 0.000 0.376
#> SRR1313156 3 0.4674 0.5598 0.000 0.012 0.600 0.032 0.000 0.356
#> SRR1313155 3 0.3955 0.5506 0.000 0.000 0.608 0.008 0.000 0.384
#> SRR1313157 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313158 3 0.3945 0.5537 0.000 0.000 0.612 0.008 0.000 0.380
#> SRR1313161 3 0.4531 0.5626 0.000 0.004 0.608 0.036 0.000 0.352
#> SRR1313159 3 0.6063 0.1571 0.000 0.368 0.412 0.000 0.004 0.216
#> SRR1313160 3 0.4531 0.5626 0.000 0.004 0.608 0.036 0.000 0.352
#> SRR1313162 3 0.4674 0.5481 0.080 0.000 0.684 0.000 0.008 0.228
#> SRR1313163 3 0.4726 0.5588 0.000 0.012 0.600 0.036 0.000 0.352
#> SRR1313165 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313166 3 0.3945 0.5537 0.000 0.000 0.612 0.008 0.000 0.380
#> SRR1313164 6 0.5188 -0.0724 0.000 0.004 0.424 0.000 0.076 0.496
#> SRR1313167 3 0.4554 0.5565 0.000 0.004 0.600 0.036 0.000 0.360
#> SRR1313168 3 0.4543 0.5602 0.000 0.004 0.604 0.036 0.000 0.356
#> SRR1313170 2 0.5412 0.4101 0.000 0.544 0.336 0.000 0.004 0.116
#> SRR1313169 3 0.4554 0.5565 0.000 0.004 0.600 0.036 0.000 0.360
#> SRR1313172 6 0.6784 -0.2887 0.000 0.200 0.044 0.008 0.292 0.456
#> SRR1313171 6 0.5188 -0.0724 0.000 0.004 0.424 0.000 0.076 0.496
#> SRR1313174 2 0.2905 0.7351 0.000 0.856 0.048 0.000 0.004 0.092
#> SRR1313173 6 0.7000 -0.1227 0.140 0.000 0.056 0.024 0.340 0.440
#> SRR1313176 2 0.2762 0.7105 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313175 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313178 2 0.2854 0.7040 0.000 0.792 0.000 0.000 0.208 0.000
#> SRR1313177 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313179 2 0.3706 0.7297 0.000 0.796 0.032 0.000 0.148 0.024
#> SRR1313180 2 0.5190 0.5556 0.000 0.620 0.244 0.000 0.004 0.132
#> SRR1313181 2 0.2854 0.7040 0.000 0.792 0.000 0.000 0.208 0.000
#> SRR1313183 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313182 2 0.2051 0.7498 0.000 0.916 0.040 0.000 0.008 0.036
#> SRR1313184 2 0.3706 0.7297 0.000 0.796 0.032 0.000 0.148 0.024
#> SRR1313185 2 0.2340 0.7453 0.000 0.896 0.044 0.000 0.004 0.056
#> SRR1313188 2 0.5190 0.5556 0.000 0.620 0.244 0.000 0.004 0.132
#> SRR1313187 2 0.5190 0.5556 0.000 0.620 0.244 0.000 0.004 0.132
#> SRR1313186 2 0.2340 0.7453 0.000 0.896 0.044 0.000 0.004 0.056
#> SRR1313189 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313190 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313191 2 0.2905 0.7351 0.000 0.856 0.048 0.000 0.004 0.092
#> SRR1313192 2 0.1003 0.7541 0.000 0.964 0.020 0.000 0.016 0.000
#> SRR1313193 2 0.1003 0.7529 0.000 0.964 0.020 0.000 0.016 0.000
#> SRR1313194 2 0.4908 0.6042 0.000 0.664 0.208 0.000 0.004 0.124
#> SRR1313195 2 0.4908 0.6042 0.000 0.664 0.208 0.000 0.004 0.124
#> SRR1313196 2 0.5169 0.5606 0.000 0.624 0.240 0.000 0.004 0.132
#> SRR1313197 2 0.2854 0.7364 0.000 0.860 0.048 0.000 0.004 0.088
#> SRR1313198 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313199 2 0.2762 0.7105 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313200 2 0.5080 0.5795 0.000 0.640 0.224 0.000 0.004 0.132
#> SRR1313201 2 0.2738 0.7198 0.000 0.820 0.004 0.000 0.176 0.000
#> SRR1313202 2 0.4983 0.5908 0.000 0.652 0.220 0.000 0.004 0.124
#> SRR1313203 5 0.4130 0.0000 0.068 0.004 0.000 0.020 0.780 0.128
#> SRR1313204 2 0.2738 0.7198 0.000 0.820 0.004 0.000 0.176 0.000
#> SRR1313205 2 0.0547 0.7540 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1313207 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313208 2 0.0547 0.7540 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1313206 2 0.2738 0.7198 0.000 0.820 0.004 0.000 0.176 0.000
#> SRR1313210 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313209 2 0.2905 0.7351 0.000 0.856 0.048 0.000 0.004 0.092
#> SRR1313211 2 0.1003 0.7529 0.000 0.964 0.020 0.000 0.016 0.000
#> SRR1313212 2 0.2738 0.7198 0.000 0.820 0.004 0.000 0.176 0.000
#> SRR1313214 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313215 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313213 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313216 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313217 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313219 2 0.3785 0.7127 0.000 0.788 0.088 0.000 0.004 0.120
#> SRR1313220 2 0.2738 0.7198 0.000 0.820 0.004 0.000 0.176 0.000
#> SRR1313218 2 0.0547 0.7540 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1313222 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313221 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313223 2 0.2912 0.6989 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313224 2 0.0692 0.7540 0.000 0.976 0.020 0.000 0.004 0.000
#> SRR1313225 2 0.3554 0.7209 0.000 0.808 0.080 0.000 0.004 0.108
#> SRR1313226 2 0.5555 0.3619 0.000 0.500 0.372 0.000 0.004 0.124
#> SRR1313227 2 0.2762 0.7105 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313228 2 0.2762 0.7105 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313229 2 0.2762 0.7105 0.000 0.804 0.000 0.000 0.196 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "kmeans"]
# you can also extract it by
# res = res_list["SD:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.859 0.943 0.972 0.4661 0.544 0.544
#> 3 3 0.799 0.872 0.935 0.3764 0.797 0.634
#> 4 4 0.755 0.831 0.832 0.1331 0.861 0.632
#> 5 5 0.774 0.748 0.813 0.0737 0.981 0.928
#> 6 6 0.832 0.832 0.845 0.0447 0.915 0.656
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.959 1.000 0.000
#> SRR1313063 1 0.0000 0.959 1.000 0.000
#> SRR1313064 1 0.0000 0.959 1.000 0.000
#> SRR1313065 1 0.0000 0.959 1.000 0.000
#> SRR1313066 1 0.0000 0.959 1.000 0.000
#> SRR1313067 1 0.0000 0.959 1.000 0.000
#> SRR1313068 1 0.0000 0.959 1.000 0.000
#> SRR1313069 1 0.0000 0.959 1.000 0.000
#> SRR1313070 1 0.0000 0.959 1.000 0.000
#> SRR1313071 1 0.0000 0.959 1.000 0.000
#> SRR1313072 1 0.0000 0.959 1.000 0.000
#> SRR1313073 1 0.0000 0.959 1.000 0.000
#> SRR1313074 1 0.0000 0.959 1.000 0.000
#> SRR1313075 1 0.0000 0.959 1.000 0.000
#> SRR1313076 1 0.0000 0.959 1.000 0.000
#> SRR1313077 1 0.0000 0.959 1.000 0.000
#> SRR1313078 1 0.0000 0.959 1.000 0.000
#> SRR1313079 1 0.0000 0.959 1.000 0.000
#> SRR1313080 1 0.0000 0.959 1.000 0.000
#> SRR1313081 1 0.0000 0.959 1.000 0.000
#> SRR1313082 1 0.0000 0.959 1.000 0.000
#> SRR1313083 1 0.0000 0.959 1.000 0.000
#> SRR1313084 1 0.0000 0.959 1.000 0.000
#> SRR1313085 1 0.0000 0.959 1.000 0.000
#> SRR1313086 1 0.0000 0.959 1.000 0.000
#> SRR1313087 1 0.0000 0.959 1.000 0.000
#> SRR1313088 1 0.0000 0.959 1.000 0.000
#> SRR1313089 1 0.0000 0.959 1.000 0.000
#> SRR1313092 1 0.0000 0.959 1.000 0.000
#> SRR1313090 1 0.0376 0.956 0.996 0.004
#> SRR1313091 2 0.0000 0.994 0.000 1.000
#> SRR1313093 1 0.0000 0.959 1.000 0.000
#> SRR1313095 1 0.0000 0.959 1.000 0.000
#> SRR1313096 1 0.0000 0.959 1.000 0.000
#> SRR1313094 1 0.0000 0.959 1.000 0.000
#> SRR1313097 1 0.7299 0.778 0.796 0.204
#> SRR1313099 1 0.8608 0.663 0.716 0.284
#> SRR1313098 1 0.0000 0.959 1.000 0.000
#> SRR1313101 1 0.7299 0.778 0.796 0.204
#> SRR1313102 1 0.7299 0.778 0.796 0.204
#> SRR1313103 1 0.8608 0.663 0.716 0.284
#> SRR1313100 1 0.0000 0.959 1.000 0.000
#> SRR1313105 1 0.6973 0.796 0.812 0.188
#> SRR1313104 1 0.0376 0.956 0.996 0.004
#> SRR1313107 1 0.7299 0.778 0.796 0.204
#> SRR1313106 1 0.4161 0.895 0.916 0.084
#> SRR1313109 2 0.8909 0.505 0.308 0.692
#> SRR1313108 1 0.0000 0.959 1.000 0.000
#> SRR1313111 1 0.7299 0.778 0.796 0.204
#> SRR1313110 1 0.0000 0.959 1.000 0.000
#> SRR1313112 1 0.8608 0.663 0.716 0.284
#> SRR1313113 1 0.7299 0.778 0.796 0.204
#> SRR1313115 1 0.0000 0.959 1.000 0.000
#> SRR1313114 1 0.0000 0.959 1.000 0.000
#> SRR1313117 1 0.0376 0.956 0.996 0.004
#> SRR1313118 1 0.0000 0.959 1.000 0.000
#> SRR1313116 1 0.8763 0.643 0.704 0.296
#> SRR1313120 1 0.7219 0.782 0.800 0.200
#> SRR1313119 1 0.0376 0.956 0.996 0.004
#> SRR1313122 1 0.0000 0.959 1.000 0.000
#> SRR1313124 1 0.0376 0.956 0.996 0.004
#> SRR1313121 1 0.0376 0.956 0.996 0.004
#> SRR1313125 1 0.0376 0.956 0.996 0.004
#> SRR1313127 1 0.0000 0.959 1.000 0.000
#> SRR1313123 1 0.0000 0.959 1.000 0.000
#> SRR1313128 1 0.0000 0.959 1.000 0.000
#> SRR1313126 1 0.0000 0.959 1.000 0.000
#> SRR1313130 2 0.0000 0.994 0.000 1.000
#> SRR1313132 1 0.0000 0.959 1.000 0.000
#> SRR1313129 1 0.8608 0.663 0.716 0.284
#> SRR1313133 1 0.0000 0.959 1.000 0.000
#> SRR1313131 1 0.0000 0.959 1.000 0.000
#> SRR1313134 1 0.0000 0.959 1.000 0.000
#> SRR1313135 1 0.0000 0.959 1.000 0.000
#> SRR1313136 1 0.0000 0.959 1.000 0.000
#> SRR1313137 1 0.0000 0.959 1.000 0.000
#> SRR1313138 1 0.7139 0.787 0.804 0.196
#> SRR1313140 1 0.0000 0.959 1.000 0.000
#> SRR1313141 1 0.0000 0.959 1.000 0.000
#> SRR1313139 1 0.0000 0.959 1.000 0.000
#> SRR1313143 1 0.0000 0.959 1.000 0.000
#> SRR1313142 1 0.0000 0.959 1.000 0.000
#> SRR1313144 1 0.0000 0.959 1.000 0.000
#> SRR1313145 1 0.0000 0.959 1.000 0.000
#> SRR1313146 1 0.0000 0.959 1.000 0.000
#> SRR1313147 1 0.0000 0.959 1.000 0.000
#> SRR1313150 1 0.0000 0.959 1.000 0.000
#> SRR1313149 1 0.0000 0.959 1.000 0.000
#> SRR1313152 1 0.0000 0.959 1.000 0.000
#> SRR1313151 1 0.0000 0.959 1.000 0.000
#> SRR1313154 1 0.0000 0.959 1.000 0.000
#> SRR1313153 1 0.0000 0.959 1.000 0.000
#> SRR1313156 1 0.5294 0.863 0.880 0.120
#> SRR1313155 1 0.0000 0.959 1.000 0.000
#> SRR1313157 1 0.0000 0.959 1.000 0.000
#> SRR1313158 1 0.0000 0.959 1.000 0.000
#> SRR1313161 1 0.0000 0.959 1.000 0.000
#> SRR1313159 1 0.9000 0.606 0.684 0.316
#> SRR1313160 1 0.0000 0.959 1.000 0.000
#> SRR1313162 1 0.0000 0.959 1.000 0.000
#> SRR1313163 1 0.5294 0.863 0.880 0.120
#> SRR1313165 1 0.0000 0.959 1.000 0.000
#> SRR1313166 1 0.0000 0.959 1.000 0.000
#> SRR1313164 1 0.0000 0.959 1.000 0.000
#> SRR1313167 1 0.0000 0.959 1.000 0.000
#> SRR1313168 1 0.0000 0.959 1.000 0.000
#> SRR1313170 1 0.7299 0.778 0.796 0.204
#> SRR1313169 1 0.0000 0.959 1.000 0.000
#> SRR1313172 1 0.7883 0.735 0.764 0.236
#> SRR1313171 1 0.0000 0.959 1.000 0.000
#> SRR1313174 2 0.0000 0.994 0.000 1.000
#> SRR1313173 1 0.0000 0.959 1.000 0.000
#> SRR1313176 2 0.0000 0.994 0.000 1.000
#> SRR1313175 2 0.0000 0.994 0.000 1.000
#> SRR1313178 2 0.0000 0.994 0.000 1.000
#> SRR1313177 2 0.0000 0.994 0.000 1.000
#> SRR1313179 2 0.0000 0.994 0.000 1.000
#> SRR1313180 2 0.0000 0.994 0.000 1.000
#> SRR1313181 2 0.0000 0.994 0.000 1.000
#> SRR1313183 2 0.0000 0.994 0.000 1.000
#> SRR1313182 2 0.0000 0.994 0.000 1.000
#> SRR1313184 2 0.0000 0.994 0.000 1.000
#> SRR1313185 2 0.0000 0.994 0.000 1.000
#> SRR1313188 2 0.0000 0.994 0.000 1.000
#> SRR1313187 2 0.0000 0.994 0.000 1.000
#> SRR1313186 2 0.0000 0.994 0.000 1.000
#> SRR1313189 2 0.0000 0.994 0.000 1.000
#> SRR1313190 2 0.0000 0.994 0.000 1.000
#> SRR1313191 2 0.0000 0.994 0.000 1.000
#> SRR1313192 2 0.0000 0.994 0.000 1.000
#> SRR1313193 2 0.0000 0.994 0.000 1.000
#> SRR1313194 2 0.0000 0.994 0.000 1.000
#> SRR1313195 2 0.0000 0.994 0.000 1.000
#> SRR1313196 2 0.0000 0.994 0.000 1.000
#> SRR1313197 2 0.0000 0.994 0.000 1.000
#> SRR1313198 2 0.0000 0.994 0.000 1.000
#> SRR1313199 2 0.0000 0.994 0.000 1.000
#> SRR1313200 2 0.0000 0.994 0.000 1.000
#> SRR1313201 2 0.0000 0.994 0.000 1.000
#> SRR1313202 2 0.0000 0.994 0.000 1.000
#> SRR1313203 1 0.0000 0.959 1.000 0.000
#> SRR1313204 2 0.0000 0.994 0.000 1.000
#> SRR1313205 2 0.0000 0.994 0.000 1.000
#> SRR1313207 2 0.0000 0.994 0.000 1.000
#> SRR1313208 2 0.0000 0.994 0.000 1.000
#> SRR1313206 2 0.0000 0.994 0.000 1.000
#> SRR1313210 2 0.0000 0.994 0.000 1.000
#> SRR1313209 2 0.0000 0.994 0.000 1.000
#> SRR1313211 2 0.0000 0.994 0.000 1.000
#> SRR1313212 2 0.0000 0.994 0.000 1.000
#> SRR1313214 2 0.0000 0.994 0.000 1.000
#> SRR1313215 2 0.0000 0.994 0.000 1.000
#> SRR1313213 2 0.0000 0.994 0.000 1.000
#> SRR1313216 2 0.0000 0.994 0.000 1.000
#> SRR1313217 2 0.0000 0.994 0.000 1.000
#> SRR1313219 2 0.0000 0.994 0.000 1.000
#> SRR1313220 2 0.0000 0.994 0.000 1.000
#> SRR1313218 2 0.0000 0.994 0.000 1.000
#> SRR1313222 2 0.0000 0.994 0.000 1.000
#> SRR1313221 2 0.0000 0.994 0.000 1.000
#> SRR1313223 2 0.0000 0.994 0.000 1.000
#> SRR1313224 2 0.0000 0.994 0.000 1.000
#> SRR1313225 2 0.0000 0.994 0.000 1.000
#> SRR1313226 2 0.0000 0.994 0.000 1.000
#> SRR1313227 2 0.0000 0.994 0.000 1.000
#> SRR1313228 2 0.0000 0.994 0.000 1.000
#> SRR1313229 2 0.0000 0.994 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.1529 0.9069 0.960 0.000 0.040
#> SRR1313063 1 0.1163 0.9133 0.972 0.000 0.028
#> SRR1313064 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313065 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313066 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313067 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313068 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313069 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313070 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313071 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313072 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313073 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313074 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313075 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313076 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313077 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313078 1 0.3267 0.8473 0.884 0.000 0.116
#> SRR1313079 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313080 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313081 1 0.1964 0.8972 0.944 0.000 0.056
#> SRR1313082 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313083 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313084 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313085 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313086 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313087 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313088 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313089 1 0.0237 0.9231 0.996 0.000 0.004
#> SRR1313092 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313091 2 0.6267 0.1781 0.000 0.548 0.452
#> SRR1313093 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313096 3 0.2448 0.8492 0.076 0.000 0.924
#> SRR1313094 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313100 3 0.4291 0.7440 0.180 0.000 0.820
#> SRR1313105 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313106 3 0.0237 0.8904 0.000 0.004 0.996
#> SRR1313109 3 0.4452 0.7028 0.000 0.192 0.808
#> SRR1313108 3 0.4452 0.7084 0.192 0.000 0.808
#> SRR1313111 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313116 3 0.0237 0.8904 0.000 0.004 0.996
#> SRR1313120 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313122 3 0.2066 0.8614 0.060 0.000 0.940
#> SRR1313124 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313128 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313126 3 0.2165 0.8586 0.064 0.000 0.936
#> SRR1313130 3 0.5859 0.4712 0.000 0.344 0.656
#> SRR1313132 3 0.1860 0.8832 0.052 0.000 0.948
#> SRR1313129 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313133 3 0.4121 0.8423 0.168 0.000 0.832
#> SRR1313131 3 0.6305 0.0443 0.484 0.000 0.516
#> SRR1313134 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313135 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313136 3 0.4121 0.8423 0.168 0.000 0.832
#> SRR1313137 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313138 3 0.2356 0.8806 0.072 0.000 0.928
#> SRR1313140 1 0.0747 0.9157 0.984 0.000 0.016
#> SRR1313141 1 0.6307 -0.1196 0.512 0.000 0.488
#> SRR1313139 3 0.5948 0.5831 0.360 0.000 0.640
#> SRR1313143 1 0.5988 0.3383 0.632 0.000 0.368
#> SRR1313142 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313144 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313145 3 0.4121 0.8423 0.168 0.000 0.832
#> SRR1313146 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313147 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313150 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313149 1 0.6095 0.2650 0.608 0.000 0.392
#> SRR1313152 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313151 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313154 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313153 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313156 3 0.2356 0.8806 0.072 0.000 0.928
#> SRR1313155 3 0.4235 0.8371 0.176 0.000 0.824
#> SRR1313157 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313158 3 0.2356 0.8806 0.072 0.000 0.928
#> SRR1313161 3 0.3619 0.8556 0.136 0.000 0.864
#> SRR1313159 3 0.2152 0.8777 0.016 0.036 0.948
#> SRR1313160 3 0.3816 0.8508 0.148 0.000 0.852
#> SRR1313162 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313163 3 0.2356 0.8806 0.072 0.000 0.928
#> SRR1313165 3 0.4796 0.8015 0.220 0.000 0.780
#> SRR1313166 3 0.3879 0.8513 0.152 0.000 0.848
#> SRR1313164 3 0.2711 0.8768 0.088 0.000 0.912
#> SRR1313167 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313168 3 0.4399 0.8286 0.188 0.000 0.812
#> SRR1313170 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313169 3 0.4974 0.7849 0.236 0.000 0.764
#> SRR1313172 3 0.0000 0.8929 0.000 0.000 1.000
#> SRR1313171 3 0.3879 0.8513 0.152 0.000 0.848
#> SRR1313174 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313173 1 0.6252 0.2140 0.556 0.000 0.444
#> SRR1313176 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313175 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313178 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313177 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313179 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313180 2 0.4452 0.7310 0.000 0.808 0.192
#> SRR1313181 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313183 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313182 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313184 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313185 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313189 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313190 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313191 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313192 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313193 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313199 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313200 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313201 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313202 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313203 1 0.0592 0.9203 0.988 0.000 0.012
#> SRR1313204 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313205 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313207 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313208 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313206 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313210 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313212 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313214 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313213 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313216 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313220 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313218 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313222 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313221 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313223 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313224 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9752 0.000 1.000 0.000
#> SRR1313226 2 0.6244 0.2296 0.000 0.560 0.440
#> SRR1313227 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313228 2 0.0237 0.9751 0.004 0.996 0.000
#> SRR1313229 2 0.0237 0.9751 0.004 0.996 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313063 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313064 4 0.0469 0.9174 0.012 0.000 0.000 0.988
#> SRR1313065 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313066 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313067 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313068 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313069 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313070 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313071 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313072 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313073 4 0.1022 0.9098 0.032 0.000 0.000 0.968
#> SRR1313074 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313075 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313076 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313077 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313078 4 0.4214 0.7984 0.204 0.000 0.016 0.780
#> SRR1313079 4 0.0469 0.9174 0.012 0.000 0.000 0.988
#> SRR1313080 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313081 4 0.2271 0.8970 0.076 0.000 0.008 0.916
#> SRR1313082 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313083 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313084 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313085 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313086 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313087 4 0.0469 0.9174 0.012 0.000 0.000 0.988
#> SRR1313088 4 0.0592 0.9175 0.016 0.000 0.000 0.984
#> SRR1313089 4 0.0817 0.9167 0.024 0.000 0.000 0.976
#> SRR1313092 3 0.0188 0.8682 0.004 0.000 0.996 0.000
#> SRR1313090 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313091 3 0.4817 0.4362 0.000 0.388 0.612 0.000
#> SRR1313093 3 0.3401 0.7446 0.152 0.000 0.840 0.008
#> SRR1313095 3 0.2198 0.8217 0.072 0.000 0.920 0.008
#> SRR1313096 3 0.5889 0.5784 0.212 0.000 0.688 0.100
#> SRR1313094 3 0.0188 0.8682 0.004 0.000 0.996 0.000
#> SRR1313097 3 0.0000 0.8690 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.2011 0.8157 0.080 0.000 0.920 0.000
#> SRR1313098 3 0.0524 0.8647 0.004 0.000 0.988 0.008
#> SRR1313101 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313102 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313103 3 0.0000 0.8690 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.3286 0.7832 0.080 0.000 0.876 0.044
#> SRR1313105 3 0.0000 0.8690 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313107 3 0.2589 0.7828 0.116 0.000 0.884 0.000
#> SRR1313106 3 0.1978 0.8137 0.004 0.068 0.928 0.000
#> SRR1313109 3 0.2408 0.7821 0.000 0.104 0.896 0.000
#> SRR1313108 3 0.6514 0.5111 0.212 0.000 0.636 0.152
#> SRR1313111 3 0.0000 0.8690 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313112 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313113 3 0.0000 0.8690 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.3249 0.7531 0.140 0.000 0.852 0.008
#> SRR1313114 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313117 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313118 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313116 3 0.3688 0.6510 0.000 0.208 0.792 0.000
#> SRR1313120 3 0.2589 0.7828 0.116 0.000 0.884 0.000
#> SRR1313119 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313122 3 0.2450 0.8150 0.072 0.000 0.912 0.016
#> SRR1313124 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313121 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313125 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313127 3 0.0672 0.8650 0.008 0.000 0.984 0.008
#> SRR1313123 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313128 1 0.5646 0.7876 0.672 0.000 0.272 0.056
#> SRR1313126 3 0.3286 0.7886 0.080 0.000 0.876 0.044
#> SRR1313130 3 0.3837 0.6343 0.000 0.224 0.776 0.000
#> SRR1313132 1 0.4936 0.7841 0.652 0.000 0.340 0.008
#> SRR1313129 3 0.0188 0.8691 0.004 0.000 0.996 0.000
#> SRR1313133 1 0.5672 0.7865 0.668 0.000 0.276 0.056
#> SRR1313131 4 0.7688 0.2367 0.232 0.000 0.328 0.440
#> SRR1313134 1 0.5672 0.7865 0.668 0.000 0.276 0.056
#> SRR1313135 1 0.6042 0.8625 0.560 0.000 0.392 0.048
#> SRR1313136 1 0.6020 0.8643 0.568 0.000 0.384 0.048
#> SRR1313137 1 0.6296 0.8631 0.548 0.000 0.388 0.064
#> SRR1313138 1 0.5650 0.8284 0.544 0.000 0.432 0.024
#> SRR1313140 1 0.6253 0.3370 0.544 0.000 0.060 0.396
#> SRR1313141 1 0.7040 0.0670 0.460 0.000 0.120 0.420
#> SRR1313139 1 0.6738 0.8324 0.544 0.000 0.352 0.104
#> SRR1313143 4 0.6607 0.2352 0.400 0.000 0.084 0.516
#> SRR1313142 1 0.5943 0.8612 0.592 0.000 0.360 0.048
#> SRR1313144 1 0.6233 0.8637 0.552 0.000 0.388 0.060
#> SRR1313145 1 0.5929 0.8597 0.596 0.000 0.356 0.048
#> SRR1313146 1 0.5957 0.8625 0.588 0.000 0.364 0.048
#> SRR1313147 1 0.6357 0.8616 0.544 0.000 0.388 0.068
#> SRR1313150 1 0.6357 0.8616 0.544 0.000 0.388 0.068
#> SRR1313149 1 0.6709 -0.0702 0.460 0.000 0.088 0.452
#> SRR1313152 1 0.6296 0.8631 0.548 0.000 0.388 0.064
#> SRR1313151 1 0.5954 0.8549 0.604 0.000 0.344 0.052
#> SRR1313154 1 0.5524 0.7984 0.676 0.000 0.276 0.048
#> SRR1313153 1 0.5957 0.8625 0.588 0.000 0.364 0.048
#> SRR1313156 1 0.5517 0.8435 0.568 0.000 0.412 0.020
#> SRR1313155 1 0.6020 0.8643 0.568 0.000 0.384 0.048
#> SRR1313157 1 0.6357 0.8616 0.544 0.000 0.388 0.068
#> SRR1313158 1 0.5517 0.8435 0.568 0.000 0.412 0.020
#> SRR1313161 1 0.5950 0.8423 0.544 0.000 0.416 0.040
#> SRR1313159 1 0.5263 0.7915 0.544 0.008 0.448 0.000
#> SRR1313160 1 0.6079 0.8506 0.544 0.000 0.408 0.048
#> SRR1313162 1 0.5268 0.7822 0.540 0.000 0.452 0.008
#> SRR1313163 1 0.5564 0.8236 0.544 0.000 0.436 0.020
#> SRR1313165 1 0.6306 0.8608 0.544 0.000 0.392 0.064
#> SRR1313166 1 0.5442 0.8027 0.672 0.000 0.288 0.040
#> SRR1313164 1 0.5085 0.7948 0.676 0.000 0.304 0.020
#> SRR1313167 1 0.6357 0.8616 0.544 0.000 0.388 0.068
#> SRR1313168 1 0.6296 0.8631 0.548 0.000 0.388 0.064
#> SRR1313170 3 0.0376 0.8668 0.004 0.004 0.992 0.000
#> SRR1313169 1 0.6357 0.8616 0.544 0.000 0.388 0.068
#> SRR1313172 3 0.3743 0.7242 0.160 0.000 0.824 0.016
#> SRR1313171 1 0.5672 0.7865 0.668 0.000 0.276 0.056
#> SRR1313174 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313173 4 0.7626 0.3090 0.232 0.000 0.304 0.464
#> SRR1313176 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313175 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313177 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313179 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313180 2 0.3074 0.7459 0.000 0.848 0.152 0.000
#> SRR1313181 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313183 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313182 2 0.1557 0.8926 0.056 0.944 0.000 0.000
#> SRR1313184 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313185 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313187 2 0.0469 0.8852 0.000 0.988 0.012 0.000
#> SRR1313186 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313190 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313191 2 0.0336 0.8916 0.008 0.992 0.000 0.000
#> SRR1313192 2 0.3873 0.8887 0.228 0.772 0.000 0.000
#> SRR1313193 2 0.0592 0.8922 0.016 0.984 0.000 0.000
#> SRR1313194 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313195 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313196 2 0.1389 0.8594 0.000 0.952 0.048 0.000
#> SRR1313197 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313200 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313201 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313202 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313203 4 0.1867 0.8995 0.072 0.000 0.000 0.928
#> SRR1313204 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313205 2 0.3873 0.8887 0.228 0.772 0.000 0.000
#> SRR1313207 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313208 2 0.3873 0.8887 0.228 0.772 0.000 0.000
#> SRR1313206 2 0.3873 0.8887 0.228 0.772 0.000 0.000
#> SRR1313210 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313214 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313216 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313217 2 0.0336 0.8875 0.000 0.992 0.008 0.000
#> SRR1313219 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313218 2 0.0336 0.8916 0.008 0.992 0.000 0.000
#> SRR1313222 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313221 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313223 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313224 2 0.0336 0.8916 0.008 0.992 0.000 0.000
#> SRR1313225 2 0.0000 0.8905 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.4925 0.3596 0.000 0.428 0.572 0.000
#> SRR1313227 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313228 2 0.3907 0.8884 0.232 0.768 0.000 0.000
#> SRR1313229 2 0.3907 0.8884 0.232 0.768 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313063 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313064 4 0.0693 0.8668 0.012 0.000 0.000 0.980 0.008
#> SRR1313065 4 0.0510 0.8670 0.016 0.000 0.000 0.984 0.000
#> SRR1313066 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313067 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313068 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313069 4 0.0404 0.8671 0.012 0.000 0.000 0.988 0.000
#> SRR1313070 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313071 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313072 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313073 4 0.2241 0.8406 0.008 0.000 0.008 0.908 0.076
#> SRR1313074 4 0.0404 0.8671 0.012 0.000 0.000 0.988 0.000
#> SRR1313075 4 0.0854 0.8655 0.012 0.000 0.008 0.976 0.004
#> SRR1313076 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313077 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313078 4 0.6137 -0.0851 0.020 0.000 0.076 0.496 0.408
#> SRR1313079 4 0.0693 0.8668 0.012 0.000 0.000 0.980 0.008
#> SRR1313080 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313081 4 0.3435 0.7905 0.004 0.000 0.020 0.820 0.156
#> SRR1313082 4 0.0404 0.8671 0.012 0.000 0.000 0.988 0.000
#> SRR1313083 4 0.0404 0.8671 0.012 0.000 0.000 0.988 0.000
#> SRR1313084 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313085 4 0.2580 0.8369 0.016 0.000 0.020 0.900 0.064
#> SRR1313086 4 0.0510 0.8670 0.016 0.000 0.000 0.984 0.000
#> SRR1313087 4 0.0693 0.8668 0.012 0.000 0.000 0.980 0.008
#> SRR1313088 4 0.1179 0.8623 0.016 0.000 0.004 0.964 0.016
#> SRR1313089 4 0.0854 0.8655 0.012 0.000 0.008 0.976 0.004
#> SRR1313092 3 0.2338 0.8542 0.112 0.000 0.884 0.000 0.004
#> SRR1313090 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313091 3 0.4392 0.4046 0.008 0.380 0.612 0.000 0.000
#> SRR1313093 3 0.5684 0.1833 0.096 0.000 0.600 0.004 0.300
#> SRR1313095 3 0.3754 0.7596 0.084 0.000 0.816 0.000 0.100
#> SRR1313096 5 0.6482 0.4021 0.080 0.000 0.432 0.036 0.452
#> SRR1313094 3 0.2286 0.8529 0.108 0.000 0.888 0.000 0.004
#> SRR1313097 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313099 3 0.1571 0.8064 0.060 0.000 0.936 0.000 0.004
#> SRR1313098 3 0.3477 0.8171 0.112 0.000 0.832 0.000 0.056
#> SRR1313101 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313102 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313103 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313100 3 0.3018 0.8173 0.084 0.000 0.872 0.008 0.036
#> SRR1313105 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313104 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313107 3 0.3301 0.7143 0.072 0.000 0.848 0.000 0.080
#> SRR1313106 3 0.2654 0.7993 0.048 0.064 0.888 0.000 0.000
#> SRR1313109 3 0.4113 0.7218 0.076 0.140 0.784 0.000 0.000
#> SRR1313108 5 0.6456 0.4102 0.072 0.000 0.436 0.040 0.452
#> SRR1313111 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313110 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313112 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313113 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313115 3 0.5544 0.2208 0.100 0.000 0.608 0.000 0.292
#> SRR1313114 3 0.2338 0.8542 0.112 0.000 0.884 0.000 0.004
#> SRR1313117 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313118 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313116 3 0.4356 0.4578 0.012 0.340 0.648 0.000 0.000
#> SRR1313120 3 0.3301 0.7143 0.072 0.000 0.848 0.000 0.080
#> SRR1313119 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313122 3 0.3956 0.7384 0.080 0.000 0.808 0.004 0.108
#> SRR1313124 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313121 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313125 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313127 3 0.3339 0.8234 0.112 0.000 0.840 0.000 0.048
#> SRR1313123 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313128 1 0.5299 0.4036 0.640 0.000 0.052 0.012 0.296
#> SRR1313126 3 0.5429 0.5625 0.080 0.000 0.696 0.028 0.196
#> SRR1313130 3 0.4604 0.3385 0.012 0.428 0.560 0.000 0.000
#> SRR1313132 1 0.3055 0.7886 0.864 0.000 0.064 0.000 0.072
#> SRR1313129 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313133 1 0.5341 0.4036 0.640 0.000 0.056 0.012 0.292
#> SRR1313131 5 0.7592 0.6454 0.072 0.000 0.212 0.252 0.464
#> SRR1313134 1 0.5432 0.3601 0.620 0.000 0.056 0.012 0.312
#> SRR1313135 1 0.0992 0.8962 0.968 0.000 0.024 0.008 0.000
#> SRR1313136 1 0.0671 0.8958 0.980 0.000 0.016 0.004 0.000
#> SRR1313137 1 0.1493 0.8946 0.948 0.000 0.024 0.028 0.000
#> SRR1313138 1 0.1597 0.8886 0.948 0.020 0.024 0.008 0.000
#> SRR1313140 1 0.2074 0.8111 0.896 0.000 0.000 0.104 0.000
#> SRR1313141 5 0.7655 0.6022 0.232 0.000 0.060 0.292 0.416
#> SRR1313139 1 0.1626 0.8872 0.940 0.000 0.016 0.044 0.000
#> SRR1313143 5 0.7603 0.5747 0.204 0.000 0.060 0.324 0.412
#> SRR1313142 1 0.0451 0.8942 0.988 0.000 0.008 0.004 0.000
#> SRR1313144 1 0.1310 0.8966 0.956 0.000 0.024 0.020 0.000
#> SRR1313145 1 0.0451 0.8942 0.988 0.000 0.008 0.004 0.000
#> SRR1313146 1 0.0451 0.8942 0.988 0.000 0.008 0.004 0.000
#> SRR1313147 1 0.1485 0.8944 0.948 0.000 0.020 0.032 0.000
#> SRR1313150 1 0.1485 0.8944 0.948 0.000 0.020 0.032 0.000
#> SRR1313149 5 0.7655 0.6022 0.232 0.000 0.060 0.292 0.416
#> SRR1313152 1 0.1493 0.8946 0.948 0.000 0.024 0.028 0.000
#> SRR1313151 1 0.0324 0.8925 0.992 0.000 0.004 0.004 0.000
#> SRR1313154 1 0.2464 0.8113 0.904 0.000 0.048 0.004 0.044
#> SRR1313153 1 0.0451 0.8942 0.988 0.000 0.008 0.004 0.000
#> SRR1313156 1 0.0771 0.8938 0.976 0.004 0.020 0.000 0.000
#> SRR1313155 1 0.0451 0.8942 0.988 0.000 0.008 0.004 0.000
#> SRR1313157 1 0.1485 0.8944 0.948 0.000 0.020 0.032 0.000
#> SRR1313158 1 0.0609 0.8950 0.980 0.000 0.020 0.000 0.000
#> SRR1313161 1 0.1493 0.8935 0.948 0.000 0.028 0.024 0.000
#> SRR1313159 1 0.1285 0.8857 0.956 0.004 0.036 0.000 0.004
#> SRR1313160 1 0.1493 0.8935 0.948 0.000 0.028 0.024 0.000
#> SRR1313162 1 0.3904 0.6759 0.792 0.000 0.156 0.000 0.052
#> SRR1313163 1 0.1202 0.8925 0.960 0.004 0.032 0.004 0.000
#> SRR1313165 1 0.1493 0.8946 0.948 0.000 0.024 0.028 0.000
#> SRR1313166 1 0.2940 0.7939 0.876 0.000 0.048 0.004 0.072
#> SRR1313164 1 0.3142 0.7851 0.864 0.000 0.056 0.004 0.076
#> SRR1313167 1 0.1485 0.8944 0.948 0.000 0.020 0.032 0.000
#> SRR1313168 1 0.1403 0.8960 0.952 0.000 0.024 0.024 0.000
#> SRR1313170 3 0.2179 0.8562 0.112 0.000 0.888 0.000 0.000
#> SRR1313169 1 0.1485 0.8944 0.948 0.000 0.020 0.032 0.000
#> SRR1313172 3 0.6042 -0.1029 0.100 0.000 0.532 0.008 0.360
#> SRR1313171 1 0.5415 0.3696 0.624 0.000 0.056 0.012 0.308
#> SRR1313174 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313173 5 0.7587 0.6426 0.072 0.000 0.208 0.256 0.464
#> SRR1313176 2 0.4434 0.7335 0.000 0.536 0.000 0.004 0.460
#> SRR1313175 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313178 2 0.4684 0.7329 0.000 0.536 0.008 0.004 0.452
#> SRR1313177 2 0.5086 0.7305 0.004 0.536 0.020 0.004 0.436
#> SRR1313179 2 0.4870 0.7298 0.004 0.532 0.016 0.000 0.448
#> SRR1313180 2 0.2732 0.5694 0.000 0.840 0.160 0.000 0.000
#> SRR1313181 2 0.4576 0.7332 0.000 0.536 0.004 0.004 0.456
#> SRR1313183 2 0.5086 0.7305 0.004 0.536 0.020 0.004 0.436
#> SRR1313182 2 0.2329 0.7415 0.000 0.876 0.000 0.000 0.124
#> SRR1313184 2 0.4865 0.7316 0.004 0.536 0.016 0.000 0.444
#> SRR1313185 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313188 2 0.1341 0.6959 0.000 0.944 0.056 0.000 0.000
#> SRR1313187 2 0.1671 0.6760 0.000 0.924 0.076 0.000 0.000
#> SRR1313186 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313189 2 0.5086 0.7305 0.004 0.536 0.020 0.004 0.436
#> SRR1313190 2 0.5086 0.7305 0.004 0.536 0.020 0.004 0.436
#> SRR1313191 2 0.1270 0.7401 0.000 0.948 0.000 0.000 0.052
#> SRR1313192 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313193 2 0.1671 0.7416 0.000 0.924 0.000 0.000 0.076
#> SRR1313194 2 0.0963 0.7128 0.000 0.964 0.036 0.000 0.000
#> SRR1313195 2 0.1197 0.7031 0.000 0.952 0.048 0.000 0.000
#> SRR1313196 2 0.2179 0.6352 0.000 0.888 0.112 0.000 0.000
#> SRR1313197 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313198 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313199 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313200 2 0.0963 0.7128 0.000 0.964 0.036 0.000 0.000
#> SRR1313201 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313202 2 0.0963 0.7128 0.000 0.964 0.036 0.000 0.000
#> SRR1313203 4 0.5170 0.2947 0.008 0.000 0.028 0.552 0.412
#> SRR1313204 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313205 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313207 2 0.4865 0.7319 0.000 0.536 0.016 0.004 0.444
#> SRR1313208 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313206 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313210 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313209 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313211 2 0.0794 0.7364 0.000 0.972 0.000 0.000 0.028
#> SRR1313212 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313214 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313215 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313213 2 0.5086 0.7305 0.004 0.536 0.020 0.004 0.436
#> SRR1313216 2 0.0609 0.7229 0.000 0.980 0.020 0.000 0.000
#> SRR1313217 2 0.0963 0.7128 0.000 0.964 0.036 0.000 0.000
#> SRR1313219 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313220 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313218 2 0.1478 0.7408 0.000 0.936 0.000 0.000 0.064
#> SRR1313222 2 0.4865 0.7319 0.000 0.536 0.016 0.004 0.444
#> SRR1313221 2 0.4779 0.7325 0.000 0.536 0.012 0.004 0.448
#> SRR1313223 2 0.4945 0.7311 0.004 0.536 0.020 0.000 0.440
#> SRR1313224 2 0.1478 0.7408 0.000 0.936 0.000 0.000 0.064
#> SRR1313225 2 0.0000 0.7337 0.000 1.000 0.000 0.000 0.000
#> SRR1313226 3 0.4650 0.2834 0.012 0.468 0.520 0.000 0.000
#> SRR1313227 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313228 2 0.4291 0.7337 0.000 0.536 0.000 0.000 0.464
#> SRR1313229 2 0.4576 0.7332 0.000 0.536 0.004 0.004 0.456
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313063 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313064 4 0.0653 0.843 0.004 0.012 0.000 0.980 0.000 0.004
#> SRR1313065 4 0.0260 0.844 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1313066 4 0.3399 0.793 0.012 0.080 0.008 0.840 0.000 0.060
#> SRR1313067 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313068 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313069 4 0.0405 0.844 0.008 0.004 0.000 0.988 0.000 0.000
#> SRR1313070 4 0.3339 0.796 0.012 0.080 0.008 0.844 0.000 0.056
#> SRR1313071 4 0.3339 0.796 0.012 0.080 0.008 0.844 0.000 0.056
#> SRR1313072 4 0.3339 0.796 0.012 0.080 0.008 0.844 0.000 0.056
#> SRR1313073 4 0.4242 0.760 0.004 0.136 0.008 0.760 0.000 0.092
#> SRR1313074 4 0.0405 0.844 0.008 0.004 0.000 0.988 0.000 0.000
#> SRR1313075 4 0.0551 0.843 0.008 0.004 0.004 0.984 0.000 0.000
#> SRR1313076 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313077 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313078 6 0.5763 0.155 0.000 0.152 0.012 0.296 0.000 0.540
#> SRR1313079 4 0.0551 0.843 0.004 0.008 0.000 0.984 0.000 0.004
#> SRR1313080 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313081 4 0.5102 0.708 0.000 0.152 0.012 0.664 0.000 0.172
#> SRR1313082 4 0.0260 0.844 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1313083 4 0.0260 0.844 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1313084 4 0.3339 0.796 0.012 0.080 0.008 0.844 0.000 0.056
#> SRR1313085 4 0.3339 0.796 0.012 0.080 0.008 0.844 0.000 0.056
#> SRR1313086 4 0.0551 0.843 0.008 0.004 0.000 0.984 0.000 0.004
#> SRR1313087 4 0.0653 0.843 0.004 0.012 0.000 0.980 0.000 0.004
#> SRR1313088 4 0.1173 0.836 0.008 0.016 0.000 0.960 0.000 0.016
#> SRR1313089 4 0.0551 0.843 0.008 0.004 0.004 0.984 0.000 0.000
#> SRR1313092 3 0.1657 0.897 0.040 0.012 0.936 0.000 0.000 0.012
#> SRR1313090 3 0.1082 0.905 0.040 0.004 0.956 0.000 0.000 0.000
#> SRR1313091 3 0.4746 0.473 0.000 0.016 0.616 0.000 0.332 0.036
#> SRR1313093 6 0.4629 0.356 0.016 0.020 0.388 0.000 0.000 0.576
#> SRR1313095 3 0.3509 0.779 0.024 0.032 0.816 0.000 0.000 0.128
#> SRR1313096 6 0.3457 0.668 0.008 0.028 0.152 0.004 0.000 0.808
#> SRR1313094 3 0.1555 0.902 0.040 0.012 0.940 0.000 0.000 0.008
#> SRR1313097 3 0.1082 0.905 0.040 0.004 0.956 0.000 0.000 0.000
#> SRR1313099 3 0.1675 0.879 0.008 0.024 0.936 0.000 0.000 0.032
#> SRR1313098 3 0.2711 0.860 0.048 0.016 0.880 0.000 0.000 0.056
#> SRR1313101 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313102 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313103 3 0.1391 0.902 0.040 0.016 0.944 0.000 0.000 0.000
#> SRR1313100 3 0.3229 0.817 0.020 0.068 0.856 0.008 0.000 0.048
#> SRR1313105 3 0.1297 0.903 0.040 0.012 0.948 0.000 0.000 0.000
#> SRR1313104 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313107 3 0.2786 0.813 0.012 0.024 0.864 0.000 0.000 0.100
#> SRR1313106 3 0.1049 0.885 0.008 0.000 0.960 0.000 0.032 0.000
#> SRR1313109 3 0.4068 0.745 0.024 0.016 0.788 0.000 0.140 0.032
#> SRR1313108 6 0.3457 0.668 0.008 0.028 0.152 0.004 0.000 0.808
#> SRR1313111 3 0.1297 0.903 0.040 0.012 0.948 0.000 0.000 0.000
#> SRR1313110 3 0.1082 0.905 0.040 0.004 0.956 0.000 0.000 0.000
#> SRR1313112 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313113 3 0.1297 0.903 0.040 0.012 0.948 0.000 0.000 0.000
#> SRR1313115 6 0.4719 0.188 0.016 0.020 0.448 0.000 0.000 0.516
#> SRR1313114 3 0.1340 0.902 0.040 0.004 0.948 0.000 0.000 0.008
#> SRR1313117 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313118 3 0.1082 0.905 0.040 0.004 0.956 0.000 0.000 0.000
#> SRR1313116 3 0.4552 0.505 0.000 0.012 0.636 0.000 0.320 0.032
#> SRR1313120 3 0.2786 0.813 0.012 0.024 0.864 0.000 0.000 0.100
#> SRR1313119 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313122 3 0.3969 0.709 0.020 0.032 0.760 0.000 0.000 0.188
#> SRR1313124 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313121 3 0.1082 0.905 0.040 0.004 0.956 0.000 0.000 0.000
#> SRR1313125 3 0.0937 0.906 0.040 0.000 0.960 0.000 0.000 0.000
#> SRR1313127 3 0.2519 0.869 0.048 0.016 0.892 0.000 0.000 0.044
#> SRR1313123 3 0.1219 0.902 0.048 0.004 0.948 0.000 0.000 0.000
#> SRR1313128 6 0.4289 0.437 0.360 0.028 0.000 0.000 0.000 0.612
#> SRR1313126 3 0.5478 0.431 0.024 0.100 0.600 0.000 0.000 0.276
#> SRR1313130 3 0.4602 0.506 0.000 0.012 0.636 0.000 0.316 0.036
#> SRR1313132 1 0.3519 0.775 0.804 0.044 0.008 0.000 0.000 0.144
#> SRR1313129 3 0.1297 0.903 0.040 0.012 0.948 0.000 0.000 0.000
#> SRR1313133 6 0.4176 0.359 0.404 0.016 0.000 0.000 0.000 0.580
#> SRR1313131 6 0.3286 0.658 0.008 0.012 0.056 0.076 0.000 0.848
#> SRR1313134 6 0.3714 0.490 0.340 0.004 0.000 0.000 0.000 0.656
#> SRR1313135 1 0.0909 0.949 0.968 0.020 0.012 0.000 0.000 0.000
#> SRR1313136 1 0.0767 0.950 0.976 0.012 0.008 0.000 0.000 0.004
#> SRR1313137 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313138 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313140 1 0.1036 0.932 0.964 0.004 0.000 0.024 0.000 0.008
#> SRR1313141 6 0.3972 0.644 0.068 0.012 0.000 0.144 0.000 0.776
#> SRR1313139 1 0.0551 0.948 0.984 0.004 0.004 0.008 0.000 0.000
#> SRR1313143 6 0.3955 0.640 0.064 0.012 0.000 0.148 0.000 0.776
#> SRR1313142 1 0.0951 0.945 0.968 0.020 0.004 0.000 0.000 0.008
#> SRR1313144 1 0.0622 0.951 0.980 0.008 0.012 0.000 0.000 0.000
#> SRR1313145 1 0.0922 0.945 0.968 0.024 0.004 0.000 0.000 0.004
#> SRR1313146 1 0.0837 0.946 0.972 0.020 0.004 0.000 0.000 0.004
#> SRR1313147 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313150 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313149 6 0.3972 0.644 0.068 0.012 0.000 0.144 0.000 0.776
#> SRR1313152 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313151 1 0.0909 0.942 0.968 0.020 0.000 0.000 0.000 0.012
#> SRR1313154 1 0.2662 0.830 0.856 0.024 0.000 0.000 0.000 0.120
#> SRR1313153 1 0.0837 0.946 0.972 0.020 0.004 0.000 0.000 0.004
#> SRR1313156 1 0.0951 0.948 0.968 0.020 0.008 0.000 0.000 0.004
#> SRR1313155 1 0.0653 0.948 0.980 0.012 0.004 0.000 0.000 0.004
#> SRR1313157 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313158 1 0.0951 0.948 0.968 0.020 0.008 0.000 0.000 0.004
#> SRR1313161 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313159 1 0.1628 0.937 0.940 0.036 0.012 0.004 0.000 0.008
#> SRR1313160 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313162 1 0.4512 0.674 0.748 0.032 0.088 0.000 0.000 0.132
#> SRR1313163 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313165 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313166 1 0.3050 0.802 0.832 0.028 0.004 0.000 0.000 0.136
#> SRR1313164 1 0.3210 0.759 0.804 0.028 0.000 0.000 0.000 0.168
#> SRR1313167 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313168 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313170 3 0.2239 0.885 0.040 0.016 0.912 0.000 0.004 0.028
#> SRR1313169 1 0.0508 0.952 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313172 6 0.3764 0.586 0.012 0.008 0.256 0.000 0.000 0.724
#> SRR1313171 6 0.3742 0.478 0.348 0.004 0.000 0.000 0.000 0.648
#> SRR1313174 5 0.0914 0.891 0.000 0.016 0.000 0.000 0.968 0.016
#> SRR1313173 6 0.3330 0.655 0.008 0.012 0.052 0.084 0.000 0.844
#> SRR1313176 2 0.3615 0.959 0.000 0.700 0.008 0.000 0.292 0.000
#> SRR1313175 5 0.0146 0.895 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1313178 2 0.4222 0.958 0.000 0.676 0.016 0.000 0.292 0.016
#> SRR1313177 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313179 2 0.4593 0.942 0.000 0.668 0.008 0.004 0.276 0.044
#> SRR1313180 5 0.2537 0.820 0.000 0.000 0.096 0.000 0.872 0.032
#> SRR1313181 2 0.3954 0.959 0.000 0.688 0.012 0.000 0.292 0.008
#> SRR1313183 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313182 5 0.2981 0.688 0.000 0.160 0.000 0.000 0.820 0.020
#> SRR1313184 2 0.4314 0.947 0.000 0.680 0.004 0.004 0.280 0.032
#> SRR1313185 5 0.0914 0.891 0.000 0.016 0.000 0.000 0.968 0.016
#> SRR1313188 5 0.1984 0.867 0.000 0.000 0.056 0.000 0.912 0.032
#> SRR1313187 5 0.2106 0.859 0.000 0.000 0.064 0.000 0.904 0.032
#> SRR1313186 5 0.0914 0.891 0.000 0.016 0.000 0.000 0.968 0.016
#> SRR1313189 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313190 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313191 5 0.1926 0.849 0.000 0.068 0.000 0.000 0.912 0.020
#> SRR1313192 2 0.4170 0.912 0.000 0.648 0.000 0.004 0.328 0.020
#> SRR1313193 5 0.2373 0.824 0.000 0.084 0.000 0.004 0.888 0.024
#> SRR1313194 5 0.1720 0.878 0.000 0.000 0.040 0.000 0.928 0.032
#> SRR1313195 5 0.1856 0.874 0.000 0.000 0.048 0.000 0.920 0.032
#> SRR1313196 5 0.2331 0.841 0.000 0.000 0.080 0.000 0.888 0.032
#> SRR1313197 5 0.0914 0.891 0.000 0.016 0.000 0.000 0.968 0.016
#> SRR1313198 5 0.0146 0.896 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1313199 2 0.3371 0.957 0.000 0.708 0.000 0.000 0.292 0.000
#> SRR1313200 5 0.1789 0.876 0.000 0.000 0.044 0.000 0.924 0.032
#> SRR1313201 2 0.3508 0.956 0.000 0.704 0.000 0.000 0.292 0.004
#> SRR1313202 5 0.2046 0.872 0.000 0.008 0.044 0.000 0.916 0.032
#> SRR1313203 6 0.4269 0.392 0.000 0.032 0.016 0.244 0.000 0.708
#> SRR1313204 2 0.3508 0.956 0.000 0.704 0.000 0.000 0.292 0.004
#> SRR1313205 2 0.4199 0.902 0.000 0.640 0.000 0.004 0.336 0.020
#> SRR1313207 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313208 2 0.4245 0.910 0.000 0.644 0.000 0.004 0.328 0.024
#> SRR1313206 2 0.4170 0.912 0.000 0.648 0.000 0.004 0.328 0.020
#> SRR1313210 5 0.0000 0.896 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.0914 0.891 0.000 0.016 0.000 0.000 0.968 0.016
#> SRR1313211 5 0.1972 0.857 0.000 0.056 0.000 0.004 0.916 0.024
#> SRR1313212 2 0.3508 0.956 0.000 0.704 0.000 0.000 0.292 0.004
#> SRR1313214 5 0.0458 0.895 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313215 5 0.0000 0.896 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313213 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313216 5 0.1854 0.883 0.000 0.016 0.020 0.004 0.932 0.028
#> SRR1313217 5 0.1789 0.876 0.000 0.000 0.044 0.000 0.924 0.032
#> SRR1313219 5 0.0000 0.896 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313220 2 0.3508 0.956 0.000 0.704 0.000 0.000 0.292 0.004
#> SRR1313218 5 0.2320 0.830 0.000 0.080 0.000 0.004 0.892 0.024
#> SRR1313222 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313221 2 0.4587 0.955 0.000 0.656 0.016 0.000 0.292 0.036
#> SRR1313223 2 0.4667 0.954 0.000 0.652 0.020 0.000 0.292 0.036
#> SRR1313224 5 0.2320 0.830 0.000 0.080 0.000 0.004 0.892 0.024
#> SRR1313225 5 0.0922 0.892 0.000 0.004 0.000 0.004 0.968 0.024
#> SRR1313226 5 0.4358 0.500 0.000 0.012 0.276 0.000 0.680 0.032
#> SRR1313227 2 0.3371 0.957 0.000 0.708 0.000 0.000 0.292 0.000
#> SRR1313228 2 0.3371 0.957 0.000 0.708 0.000 0.000 0.292 0.000
#> SRR1313229 2 0.3954 0.959 0.000 0.688 0.012 0.000 0.292 0.008
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "skmeans"]
# you can also extract it by
# res = res_list["SD:skmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.984 0.993 0.5003 0.500 0.500
#> 3 3 1.000 0.953 0.982 0.3110 0.787 0.597
#> 4 4 0.967 0.933 0.973 0.1326 0.897 0.707
#> 5 5 0.864 0.852 0.869 0.0686 0.930 0.734
#> 6 6 0.894 0.872 0.926 0.0494 0.949 0.753
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.994 1.000 0.000
#> SRR1313063 1 0.0000 0.994 1.000 0.000
#> SRR1313064 1 0.0000 0.994 1.000 0.000
#> SRR1313065 1 0.0000 0.994 1.000 0.000
#> SRR1313066 1 0.0000 0.994 1.000 0.000
#> SRR1313067 1 0.0000 0.994 1.000 0.000
#> SRR1313068 1 0.0000 0.994 1.000 0.000
#> SRR1313069 1 0.0000 0.994 1.000 0.000
#> SRR1313070 1 0.0000 0.994 1.000 0.000
#> SRR1313071 1 0.0000 0.994 1.000 0.000
#> SRR1313072 1 0.0000 0.994 1.000 0.000
#> SRR1313073 1 0.0000 0.994 1.000 0.000
#> SRR1313074 1 0.0000 0.994 1.000 0.000
#> SRR1313075 1 0.0000 0.994 1.000 0.000
#> SRR1313076 1 0.0000 0.994 1.000 0.000
#> SRR1313077 1 0.0000 0.994 1.000 0.000
#> SRR1313078 1 0.0000 0.994 1.000 0.000
#> SRR1313079 1 0.0000 0.994 1.000 0.000
#> SRR1313080 1 0.0000 0.994 1.000 0.000
#> SRR1313081 1 0.0000 0.994 1.000 0.000
#> SRR1313082 1 0.0000 0.994 1.000 0.000
#> SRR1313083 1 0.0000 0.994 1.000 0.000
#> SRR1313084 1 0.0000 0.994 1.000 0.000
#> SRR1313085 1 0.0000 0.994 1.000 0.000
#> SRR1313086 1 0.0000 0.994 1.000 0.000
#> SRR1313087 1 0.0000 0.994 1.000 0.000
#> SRR1313088 1 0.0000 0.994 1.000 0.000
#> SRR1313089 1 0.0000 0.994 1.000 0.000
#> SRR1313092 1 0.0000 0.994 1.000 0.000
#> SRR1313090 1 0.0000 0.994 1.000 0.000
#> SRR1313091 2 0.0000 0.992 0.000 1.000
#> SRR1313093 1 0.0000 0.994 1.000 0.000
#> SRR1313095 1 0.0000 0.994 1.000 0.000
#> SRR1313096 1 0.0000 0.994 1.000 0.000
#> SRR1313094 1 0.0000 0.994 1.000 0.000
#> SRR1313097 2 0.0000 0.992 0.000 1.000
#> SRR1313099 2 0.0000 0.992 0.000 1.000
#> SRR1313098 1 0.0000 0.994 1.000 0.000
#> SRR1313101 2 0.0000 0.992 0.000 1.000
#> SRR1313102 2 0.0000 0.992 0.000 1.000
#> SRR1313103 2 0.0000 0.992 0.000 1.000
#> SRR1313100 1 0.0000 0.994 1.000 0.000
#> SRR1313105 2 0.0000 0.992 0.000 1.000
#> SRR1313104 1 0.0000 0.994 1.000 0.000
#> SRR1313107 2 0.0000 0.992 0.000 1.000
#> SRR1313106 2 0.1184 0.977 0.016 0.984
#> SRR1313109 2 0.0000 0.992 0.000 1.000
#> SRR1313108 1 0.0000 0.994 1.000 0.000
#> SRR1313111 2 0.0000 0.992 0.000 1.000
#> SRR1313110 1 0.0672 0.987 0.992 0.008
#> SRR1313112 2 0.0000 0.992 0.000 1.000
#> SRR1313113 2 0.0000 0.992 0.000 1.000
#> SRR1313115 1 0.0000 0.994 1.000 0.000
#> SRR1313114 1 0.0000 0.994 1.000 0.000
#> SRR1313117 2 0.9881 0.222 0.436 0.564
#> SRR1313118 1 0.0000 0.994 1.000 0.000
#> SRR1313116 2 0.0000 0.992 0.000 1.000
#> SRR1313120 2 0.0376 0.989 0.004 0.996
#> SRR1313119 1 0.3114 0.938 0.944 0.056
#> SRR1313122 1 0.0000 0.994 1.000 0.000
#> SRR1313124 1 0.0000 0.994 1.000 0.000
#> SRR1313121 1 0.0000 0.994 1.000 0.000
#> SRR1313125 1 0.3431 0.930 0.936 0.064
#> SRR1313127 1 0.0000 0.994 1.000 0.000
#> SRR1313123 1 0.0000 0.994 1.000 0.000
#> SRR1313128 1 0.0000 0.994 1.000 0.000
#> SRR1313126 1 0.0000 0.994 1.000 0.000
#> SRR1313130 2 0.0000 0.992 0.000 1.000
#> SRR1313132 1 0.0000 0.994 1.000 0.000
#> SRR1313129 2 0.0000 0.992 0.000 1.000
#> SRR1313133 1 0.0000 0.994 1.000 0.000
#> SRR1313131 1 0.0000 0.994 1.000 0.000
#> SRR1313134 1 0.0000 0.994 1.000 0.000
#> SRR1313135 1 0.0000 0.994 1.000 0.000
#> SRR1313136 1 0.0000 0.994 1.000 0.000
#> SRR1313137 1 0.0000 0.994 1.000 0.000
#> SRR1313138 2 0.5178 0.864 0.116 0.884
#> SRR1313140 1 0.0000 0.994 1.000 0.000
#> SRR1313141 1 0.0000 0.994 1.000 0.000
#> SRR1313139 1 0.0000 0.994 1.000 0.000
#> SRR1313143 1 0.0000 0.994 1.000 0.000
#> SRR1313142 1 0.0000 0.994 1.000 0.000
#> SRR1313144 1 0.0000 0.994 1.000 0.000
#> SRR1313145 1 0.0000 0.994 1.000 0.000
#> SRR1313146 1 0.0000 0.994 1.000 0.000
#> SRR1313147 1 0.0000 0.994 1.000 0.000
#> SRR1313150 1 0.0000 0.994 1.000 0.000
#> SRR1313149 1 0.0000 0.994 1.000 0.000
#> SRR1313152 1 0.0000 0.994 1.000 0.000
#> SRR1313151 1 0.0000 0.994 1.000 0.000
#> SRR1313154 1 0.0000 0.994 1.000 0.000
#> SRR1313153 1 0.0000 0.994 1.000 0.000
#> SRR1313156 1 0.7219 0.753 0.800 0.200
#> SRR1313155 1 0.0000 0.994 1.000 0.000
#> SRR1313157 1 0.0000 0.994 1.000 0.000
#> SRR1313158 1 0.0000 0.994 1.000 0.000
#> SRR1313161 1 0.0000 0.994 1.000 0.000
#> SRR1313159 2 0.0000 0.992 0.000 1.000
#> SRR1313160 1 0.0000 0.994 1.000 0.000
#> SRR1313162 1 0.0000 0.994 1.000 0.000
#> SRR1313163 1 0.7219 0.753 0.800 0.200
#> SRR1313165 1 0.0000 0.994 1.000 0.000
#> SRR1313166 1 0.0000 0.994 1.000 0.000
#> SRR1313164 1 0.0000 0.994 1.000 0.000
#> SRR1313167 1 0.0000 0.994 1.000 0.000
#> SRR1313168 1 0.0000 0.994 1.000 0.000
#> SRR1313170 2 0.0000 0.992 0.000 1.000
#> SRR1313169 1 0.0000 0.994 1.000 0.000
#> SRR1313172 2 0.0000 0.992 0.000 1.000
#> SRR1313171 1 0.0000 0.994 1.000 0.000
#> SRR1313174 2 0.0000 0.992 0.000 1.000
#> SRR1313173 1 0.0000 0.994 1.000 0.000
#> SRR1313176 2 0.0000 0.992 0.000 1.000
#> SRR1313175 2 0.0000 0.992 0.000 1.000
#> SRR1313178 2 0.0000 0.992 0.000 1.000
#> SRR1313177 2 0.0000 0.992 0.000 1.000
#> SRR1313179 2 0.0000 0.992 0.000 1.000
#> SRR1313180 2 0.0000 0.992 0.000 1.000
#> SRR1313181 2 0.0000 0.992 0.000 1.000
#> SRR1313183 2 0.0000 0.992 0.000 1.000
#> SRR1313182 2 0.0000 0.992 0.000 1.000
#> SRR1313184 2 0.0000 0.992 0.000 1.000
#> SRR1313185 2 0.0000 0.992 0.000 1.000
#> SRR1313188 2 0.0000 0.992 0.000 1.000
#> SRR1313187 2 0.0000 0.992 0.000 1.000
#> SRR1313186 2 0.0000 0.992 0.000 1.000
#> SRR1313189 2 0.0000 0.992 0.000 1.000
#> SRR1313190 2 0.0000 0.992 0.000 1.000
#> SRR1313191 2 0.0000 0.992 0.000 1.000
#> SRR1313192 2 0.0000 0.992 0.000 1.000
#> SRR1313193 2 0.0000 0.992 0.000 1.000
#> SRR1313194 2 0.0000 0.992 0.000 1.000
#> SRR1313195 2 0.0000 0.992 0.000 1.000
#> SRR1313196 2 0.0000 0.992 0.000 1.000
#> SRR1313197 2 0.0000 0.992 0.000 1.000
#> SRR1313198 2 0.0000 0.992 0.000 1.000
#> SRR1313199 2 0.0000 0.992 0.000 1.000
#> SRR1313200 2 0.0000 0.992 0.000 1.000
#> SRR1313201 2 0.0000 0.992 0.000 1.000
#> SRR1313202 2 0.0000 0.992 0.000 1.000
#> SRR1313203 1 0.0000 0.994 1.000 0.000
#> SRR1313204 2 0.0000 0.992 0.000 1.000
#> SRR1313205 2 0.0000 0.992 0.000 1.000
#> SRR1313207 2 0.0000 0.992 0.000 1.000
#> SRR1313208 2 0.0000 0.992 0.000 1.000
#> SRR1313206 2 0.0000 0.992 0.000 1.000
#> SRR1313210 2 0.0000 0.992 0.000 1.000
#> SRR1313209 2 0.0000 0.992 0.000 1.000
#> SRR1313211 2 0.0000 0.992 0.000 1.000
#> SRR1313212 2 0.0000 0.992 0.000 1.000
#> SRR1313214 2 0.0000 0.992 0.000 1.000
#> SRR1313215 2 0.0000 0.992 0.000 1.000
#> SRR1313213 2 0.0000 0.992 0.000 1.000
#> SRR1313216 2 0.0000 0.992 0.000 1.000
#> SRR1313217 2 0.0000 0.992 0.000 1.000
#> SRR1313219 2 0.0000 0.992 0.000 1.000
#> SRR1313220 2 0.0000 0.992 0.000 1.000
#> SRR1313218 2 0.0000 0.992 0.000 1.000
#> SRR1313222 2 0.0000 0.992 0.000 1.000
#> SRR1313221 2 0.0000 0.992 0.000 1.000
#> SRR1313223 2 0.0000 0.992 0.000 1.000
#> SRR1313224 2 0.0000 0.992 0.000 1.000
#> SRR1313225 2 0.0000 0.992 0.000 1.000
#> SRR1313226 2 0.0000 0.992 0.000 1.000
#> SRR1313227 2 0.0000 0.992 0.000 1.000
#> SRR1313228 2 0.0000 0.992 0.000 1.000
#> SRR1313229 2 0.0000 0.992 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313063 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313067 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313068 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313069 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313076 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313077 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313078 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313079 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313080 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313081 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313082 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313091 2 0.6140 0.3034 0.000 0.596 0.404
#> SRR1313093 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313096 3 0.4654 0.7328 0.208 0.000 0.792
#> SRR1313094 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313100 3 0.0237 0.9711 0.004 0.000 0.996
#> SRR1313105 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313109 3 0.4654 0.7234 0.000 0.208 0.792
#> SRR1313108 3 0.0592 0.9643 0.012 0.000 0.988
#> SRR1313111 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313116 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313128 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313126 3 0.1031 0.9532 0.024 0.000 0.976
#> SRR1313130 3 0.6308 0.0164 0.000 0.492 0.508
#> SRR1313132 1 0.3551 0.8444 0.868 0.000 0.132
#> SRR1313129 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313133 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313131 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313134 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313135 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313136 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313137 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313138 2 0.6307 0.0447 0.488 0.512 0.000
#> SRR1313140 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313141 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313139 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313143 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313142 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313144 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313145 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313146 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313147 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313149 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313152 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313151 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313154 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313153 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313156 1 0.4784 0.7439 0.796 0.200 0.004
#> SRR1313155 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313157 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313158 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313161 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313159 2 0.0237 0.9709 0.000 0.996 0.004
#> SRR1313160 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313162 1 0.2066 0.9312 0.940 0.000 0.060
#> SRR1313163 1 0.4555 0.7457 0.800 0.200 0.000
#> SRR1313165 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313166 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313164 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313167 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313170 3 0.0000 0.9747 0.000 0.000 1.000
#> SRR1313169 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313172 2 0.6244 0.1949 0.000 0.560 0.440
#> SRR1313171 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313174 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313173 1 0.0237 0.9874 0.996 0.000 0.004
#> SRR1313176 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313203 1 0.0000 0.9895 1.000 0.000 0.000
#> SRR1313204 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313226 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9750 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9750 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313067 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313068 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313078 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313079 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313082 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.4866 0.2844 0.000 0.596 0.404 0.000
#> SRR1313093 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313096 3 0.4248 0.7095 0.012 0.000 0.768 0.220
#> SRR1313094 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313101 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.4697 0.4411 0.000 0.000 0.644 0.356
#> SRR1313105 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.3649 0.7298 0.000 0.204 0.796 0.000
#> SRR1313108 3 0.3610 0.7482 0.000 0.000 0.800 0.200
#> SRR1313111 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313120 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.3528 0.7584 0.000 0.000 0.808 0.192
#> SRR1313124 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.3610 0.7482 0.000 0.000 0.800 0.200
#> SRR1313130 3 0.4981 0.1485 0.000 0.464 0.536 0.000
#> SRR1313132 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313131 4 0.1174 0.9271 0.012 0.000 0.020 0.968
#> SRR1313134 1 0.3219 0.7954 0.836 0.000 0.000 0.164
#> SRR1313135 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313140 1 0.0707 0.9643 0.980 0.000 0.000 0.020
#> SRR1313141 4 0.4790 0.3925 0.380 0.000 0.000 0.620
#> SRR1313139 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313143 4 0.3837 0.6951 0.224 0.000 0.000 0.776
#> SRR1313142 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313150 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313149 4 0.4790 0.3925 0.380 0.000 0.000 0.620
#> SRR1313152 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313158 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313159 1 0.3610 0.7331 0.800 0.200 0.000 0.000
#> SRR1313160 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313162 1 0.3486 0.7534 0.812 0.000 0.000 0.188
#> SRR1313163 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313167 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313168 1 0.0000 0.9790 1.000 0.000 0.000 0.000
#> SRR1313170 3 0.0000 0.9478 0.000 0.000 1.000 0.000
#> SRR1313169 1 0.0188 0.9771 0.996 0.000 0.000 0.004
#> SRR1313172 4 0.8279 0.0205 0.012 0.300 0.328 0.360
#> SRR1313171 1 0.1557 0.9278 0.944 0.000 0.000 0.056
#> SRR1313174 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313173 4 0.0469 0.9417 0.012 0.000 0.000 0.988
#> SRR1313176 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313203 4 0.0000 0.9508 0.000 0.000 0.000 1.000
#> SRR1313204 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.0188 0.9881 0.000 0.996 0.004 0.000
#> SRR1313227 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9922 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9922 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313063 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313064 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313066 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313067 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313068 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313069 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313074 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313077 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313078 4 0.4126 0.637 0.000 0.000 0.000 0.620 0.380
#> SRR1313079 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313081 4 0.0162 0.930 0.000 0.000 0.000 0.996 0.004
#> SRR1313082 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313084 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313085 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313087 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313092 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 5 0.4620 0.253 0.000 0.016 0.392 0.000 0.592
#> SRR1313093 3 0.4161 0.593 0.000 0.000 0.608 0.000 0.392
#> SRR1313095 3 0.0404 0.893 0.000 0.000 0.988 0.000 0.012
#> SRR1313096 3 0.6518 0.304 0.000 0.000 0.412 0.192 0.396
#> SRR1313094 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.1121 0.877 0.000 0.000 0.956 0.000 0.044
#> SRR1313098 3 0.1410 0.871 0.000 0.000 0.940 0.000 0.060
#> SRR1313101 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.4067 0.569 0.000 0.000 0.692 0.300 0.008
#> SRR1313105 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.3612 0.716 0.000 0.000 0.732 0.000 0.268
#> SRR1313106 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313109 3 0.4415 0.342 0.000 0.008 0.604 0.000 0.388
#> SRR1313108 3 0.6518 0.304 0.000 0.000 0.412 0.192 0.396
#> SRR1313111 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.4161 0.593 0.000 0.000 0.608 0.000 0.392
#> SRR1313114 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 5 0.4201 0.207 0.000 0.000 0.408 0.000 0.592
#> SRR1313120 3 0.3612 0.716 0.000 0.000 0.732 0.000 0.268
#> SRR1313119 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.3355 0.728 0.000 0.000 0.804 0.184 0.012
#> SRR1313124 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0290 0.894 0.000 0.000 0.992 0.000 0.008
#> SRR1313123 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.4150 0.676 0.612 0.000 0.000 0.000 0.388
#> SRR1313126 3 0.3427 0.718 0.000 0.000 0.796 0.192 0.012
#> SRR1313130 5 0.4331 0.229 0.000 0.004 0.400 0.000 0.596
#> SRR1313132 1 0.4138 0.679 0.616 0.000 0.000 0.000 0.384
#> SRR1313129 3 0.0000 0.897 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.4150 0.676 0.612 0.000 0.000 0.000 0.388
#> SRR1313131 4 0.4171 0.623 0.000 0.000 0.000 0.604 0.396
#> SRR1313134 1 0.5000 0.638 0.576 0.000 0.000 0.036 0.388
#> SRR1313135 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.0794 0.883 0.972 0.000 0.000 0.028 0.000
#> SRR1313141 4 0.5000 0.581 0.036 0.000 0.000 0.576 0.388
#> SRR1313139 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313143 4 0.4517 0.613 0.012 0.000 0.000 0.600 0.388
#> SRR1313142 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 4 0.5000 0.581 0.036 0.000 0.000 0.576 0.388
#> SRR1313152 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313154 1 0.4138 0.679 0.616 0.000 0.000 0.000 0.384
#> SRR1313153 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.3109 0.709 0.800 0.200 0.000 0.000 0.000
#> SRR1313160 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.5908 0.589 0.628 0.000 0.008 0.184 0.180
#> SRR1313163 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.4138 0.679 0.616 0.000 0.000 0.000 0.384
#> SRR1313164 1 0.4138 0.679 0.616 0.000 0.000 0.000 0.384
#> SRR1313167 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.2605 0.771 0.000 0.000 0.852 0.000 0.148
#> SRR1313169 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 2 0.4150 0.382 0.000 0.612 0.000 0.000 0.388
#> SRR1313171 1 0.4415 0.669 0.604 0.000 0.000 0.008 0.388
#> SRR1313174 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313173 4 0.4171 0.623 0.000 0.000 0.000 0.604 0.396
#> SRR1313176 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313178 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313180 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313181 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.0404 0.951 0.000 0.988 0.000 0.000 0.012
#> SRR1313184 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313185 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313188 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313187 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313186 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313189 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.2891 0.599 0.000 0.824 0.000 0.000 0.176
#> SRR1313192 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0162 0.962 0.000 0.996 0.000 0.000 0.004
#> SRR1313194 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313195 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313196 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313197 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313198 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313199 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313201 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313203 4 0.0000 0.931 0.000 0.000 0.000 1.000 0.000
#> SRR1313204 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313209 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313211 5 0.4307 0.699 0.000 0.496 0.000 0.000 0.504
#> SRR1313212 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313215 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313213 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313217 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313219 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313220 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.0510 0.945 0.000 0.984 0.000 0.000 0.016
#> SRR1313222 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0162 0.962 0.000 0.996 0.000 0.000 0.004
#> SRR1313225 5 0.4171 0.899 0.000 0.396 0.000 0.000 0.604
#> SRR1313226 5 0.4310 0.893 0.000 0.392 0.004 0.000 0.604
#> SRR1313227 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313063 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313064 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313066 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313067 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313068 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313069 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313070 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313071 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313072 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313073 4 0.0790 0.929 0.000 0.000 0.000 0.968 0.000 0.032
#> SRR1313074 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313075 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313077 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313078 6 0.3695 0.266 0.000 0.000 0.000 0.376 0.000 0.624
#> SRR1313079 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313081 4 0.2416 0.867 0.000 0.000 0.000 0.844 0.000 0.156
#> SRR1313082 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313083 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313084 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313085 4 0.0260 0.940 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313086 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313087 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0146 0.941 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313089 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 3 0.0713 0.887 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313090 3 0.0632 0.888 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313091 5 0.3109 0.685 0.000 0.000 0.224 0.000 0.772 0.004
#> SRR1313093 6 0.3515 0.434 0.000 0.000 0.324 0.000 0.000 0.676
#> SRR1313095 3 0.3076 0.734 0.000 0.000 0.760 0.000 0.000 0.240
#> SRR1313096 6 0.0806 0.746 0.000 0.000 0.008 0.020 0.000 0.972
#> SRR1313094 3 0.0891 0.886 0.000 0.000 0.968 0.000 0.024 0.008
#> SRR1313097 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313099 3 0.3483 0.659 0.000 0.000 0.764 0.000 0.024 0.212
#> SRR1313098 3 0.3126 0.727 0.000 0.000 0.752 0.000 0.000 0.248
#> SRR1313101 3 0.0000 0.888 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0146 0.889 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313103 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313100 3 0.5348 0.501 0.000 0.000 0.592 0.192 0.000 0.216
#> SRR1313105 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313104 3 0.0632 0.888 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313107 3 0.4230 0.339 0.000 0.000 0.612 0.000 0.024 0.364
#> SRR1313106 3 0.0891 0.886 0.000 0.000 0.968 0.000 0.024 0.008
#> SRR1313109 3 0.3923 0.413 0.000 0.000 0.620 0.000 0.372 0.008
#> SRR1313108 6 0.0806 0.746 0.000 0.000 0.008 0.020 0.000 0.972
#> SRR1313111 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313110 3 0.0713 0.887 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313112 3 0.0000 0.888 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313115 6 0.3607 0.379 0.000 0.000 0.348 0.000 0.000 0.652
#> SRR1313114 3 0.0713 0.887 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313117 3 0.0000 0.888 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.0713 0.887 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313116 5 0.3043 0.714 0.000 0.000 0.200 0.000 0.792 0.008
#> SRR1313120 3 0.4230 0.339 0.000 0.000 0.612 0.000 0.024 0.364
#> SRR1313119 3 0.0146 0.889 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313122 3 0.3592 0.713 0.000 0.000 0.740 0.020 0.000 0.240
#> SRR1313124 3 0.0632 0.888 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313121 3 0.0632 0.888 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313125 3 0.0146 0.889 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313127 3 0.1663 0.857 0.000 0.000 0.912 0.000 0.000 0.088
#> SRR1313123 3 0.0632 0.888 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313128 6 0.3050 0.714 0.236 0.000 0.000 0.000 0.000 0.764
#> SRR1313126 3 0.3592 0.713 0.000 0.000 0.740 0.020 0.000 0.240
#> SRR1313130 5 0.3271 0.673 0.000 0.000 0.232 0.000 0.760 0.008
#> SRR1313132 6 0.3531 0.613 0.328 0.000 0.000 0.000 0.000 0.672
#> SRR1313129 3 0.0632 0.884 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313133 6 0.3050 0.714 0.236 0.000 0.000 0.000 0.000 0.764
#> SRR1313131 6 0.1141 0.742 0.000 0.000 0.000 0.052 0.000 0.948
#> SRR1313134 6 0.3469 0.767 0.088 0.000 0.000 0.104 0.000 0.808
#> SRR1313135 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.2730 0.769 0.836 0.000 0.000 0.152 0.000 0.012
#> SRR1313141 6 0.2730 0.717 0.000 0.000 0.000 0.192 0.000 0.808
#> SRR1313139 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313143 6 0.2730 0.717 0.000 0.000 0.000 0.192 0.000 0.808
#> SRR1313142 1 0.0363 0.971 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313144 1 0.0363 0.971 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313145 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0146 0.976 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313147 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313149 6 0.2730 0.717 0.000 0.000 0.000 0.192 0.000 0.808
#> SRR1313152 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0363 0.971 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313154 6 0.3198 0.694 0.260 0.000 0.000 0.000 0.000 0.740
#> SRR1313153 1 0.0363 0.971 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313156 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.2902 0.689 0.800 0.196 0.000 0.000 0.004 0.000
#> SRR1313160 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313162 6 0.3555 0.517 0.280 0.000 0.000 0.008 0.000 0.712
#> SRR1313163 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 6 0.3774 0.485 0.408 0.000 0.000 0.000 0.000 0.592
#> SRR1313164 6 0.3151 0.701 0.252 0.000 0.000 0.000 0.000 0.748
#> SRR1313167 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.2553 0.786 0.000 0.000 0.848 0.000 0.144 0.008
#> SRR1313169 1 0.0000 0.979 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313172 6 0.3076 0.614 0.000 0.240 0.000 0.000 0.000 0.760
#> SRR1313171 6 0.3558 0.766 0.112 0.000 0.000 0.088 0.000 0.800
#> SRR1313174 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313173 6 0.1141 0.742 0.000 0.000 0.000 0.052 0.000 0.948
#> SRR1313176 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313178 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313180 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313181 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.2823 0.754 0.000 0.796 0.000 0.000 0.204 0.000
#> SRR1313184 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313185 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313188 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313187 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313186 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313189 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.3607 0.490 0.000 0.652 0.000 0.000 0.348 0.000
#> SRR1313192 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313193 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313194 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313195 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313196 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313197 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313198 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313199 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313201 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313203 4 0.1863 0.871 0.000 0.000 0.000 0.896 0.000 0.104
#> SRR1313204 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313207 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313206 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313210 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313209 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313211 5 0.2135 0.842 0.000 0.128 0.000 0.000 0.872 0.000
#> SRR1313212 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313215 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313213 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313217 5 0.0891 0.958 0.000 0.024 0.000 0.000 0.968 0.008
#> SRR1313219 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313220 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.2912 0.737 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313222 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0260 0.965 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313225 5 0.0632 0.959 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313226 5 0.0806 0.955 0.000 0.020 0.000 0.000 0.972 0.008
#> SRR1313227 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.970 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "pam"]
# you can also extract it by
# res = res_list["SD:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.963 0.970 0.986 0.4627 0.537 0.537
#> 3 3 0.699 0.872 0.925 0.4310 0.780 0.595
#> 4 4 0.861 0.825 0.911 0.1109 0.852 0.599
#> 5 5 0.795 0.722 0.824 0.0665 0.954 0.827
#> 6 6 0.867 0.804 0.896 0.0535 0.915 0.648
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.989 1.000 0.000
#> SRR1313063 1 0.0000 0.989 1.000 0.000
#> SRR1313064 1 0.0000 0.989 1.000 0.000
#> SRR1313065 1 0.0000 0.989 1.000 0.000
#> SRR1313066 1 0.4939 0.879 0.892 0.108
#> SRR1313067 1 0.0000 0.989 1.000 0.000
#> SRR1313068 1 0.0000 0.989 1.000 0.000
#> SRR1313069 1 0.0000 0.989 1.000 0.000
#> SRR1313070 1 0.4690 0.889 0.900 0.100
#> SRR1313071 1 0.0000 0.989 1.000 0.000
#> SRR1313072 1 0.2423 0.953 0.960 0.040
#> SRR1313073 1 0.0000 0.989 1.000 0.000
#> SRR1313074 1 0.0000 0.989 1.000 0.000
#> SRR1313075 1 0.0000 0.989 1.000 0.000
#> SRR1313076 1 0.0000 0.989 1.000 0.000
#> SRR1313077 1 0.0000 0.989 1.000 0.000
#> SRR1313078 1 0.0000 0.989 1.000 0.000
#> SRR1313079 1 0.0000 0.989 1.000 0.000
#> SRR1313080 1 0.0000 0.989 1.000 0.000
#> SRR1313081 1 0.0000 0.989 1.000 0.000
#> SRR1313082 1 0.0000 0.989 1.000 0.000
#> SRR1313083 1 0.0000 0.989 1.000 0.000
#> SRR1313084 1 0.5519 0.854 0.872 0.128
#> SRR1313085 1 0.5842 0.838 0.860 0.140
#> SRR1313086 1 0.0000 0.989 1.000 0.000
#> SRR1313087 1 0.0000 0.989 1.000 0.000
#> SRR1313088 1 0.0000 0.989 1.000 0.000
#> SRR1313089 1 0.0000 0.989 1.000 0.000
#> SRR1313092 1 0.0000 0.989 1.000 0.000
#> SRR1313090 1 0.0000 0.989 1.000 0.000
#> SRR1313091 2 0.0000 0.978 0.000 1.000
#> SRR1313093 1 0.0000 0.989 1.000 0.000
#> SRR1313095 1 0.0000 0.989 1.000 0.000
#> SRR1313096 1 0.0000 0.989 1.000 0.000
#> SRR1313094 1 0.0000 0.989 1.000 0.000
#> SRR1313097 1 0.0000 0.989 1.000 0.000
#> SRR1313099 1 0.0376 0.986 0.996 0.004
#> SRR1313098 1 0.0000 0.989 1.000 0.000
#> SRR1313101 1 0.0000 0.989 1.000 0.000
#> SRR1313102 1 0.0000 0.989 1.000 0.000
#> SRR1313103 1 0.0672 0.983 0.992 0.008
#> SRR1313100 1 0.0000 0.989 1.000 0.000
#> SRR1313105 1 0.0000 0.989 1.000 0.000
#> SRR1313104 1 0.0000 0.989 1.000 0.000
#> SRR1313107 1 0.0000 0.989 1.000 0.000
#> SRR1313106 1 0.1843 0.965 0.972 0.028
#> SRR1313109 1 0.8144 0.668 0.748 0.252
#> SRR1313108 1 0.0000 0.989 1.000 0.000
#> SRR1313111 1 0.0000 0.989 1.000 0.000
#> SRR1313110 1 0.0000 0.989 1.000 0.000
#> SRR1313112 1 0.6247 0.815 0.844 0.156
#> SRR1313113 1 0.0000 0.989 1.000 0.000
#> SRR1313115 1 0.0000 0.989 1.000 0.000
#> SRR1313114 1 0.0000 0.989 1.000 0.000
#> SRR1313117 1 0.0000 0.989 1.000 0.000
#> SRR1313118 1 0.0000 0.989 1.000 0.000
#> SRR1313116 1 0.3584 0.925 0.932 0.068
#> SRR1313120 1 0.0000 0.989 1.000 0.000
#> SRR1313119 1 0.0000 0.989 1.000 0.000
#> SRR1313122 1 0.0000 0.989 1.000 0.000
#> SRR1313124 1 0.0000 0.989 1.000 0.000
#> SRR1313121 1 0.0000 0.989 1.000 0.000
#> SRR1313125 1 0.0000 0.989 1.000 0.000
#> SRR1313127 1 0.0000 0.989 1.000 0.000
#> SRR1313123 1 0.0000 0.989 1.000 0.000
#> SRR1313128 1 0.0000 0.989 1.000 0.000
#> SRR1313126 1 0.0000 0.989 1.000 0.000
#> SRR1313130 2 0.0000 0.978 0.000 1.000
#> SRR1313132 1 0.0000 0.989 1.000 0.000
#> SRR1313129 1 0.0672 0.983 0.992 0.008
#> SRR1313133 1 0.0000 0.989 1.000 0.000
#> SRR1313131 1 0.0000 0.989 1.000 0.000
#> SRR1313134 1 0.0000 0.989 1.000 0.000
#> SRR1313135 1 0.0000 0.989 1.000 0.000
#> SRR1313136 1 0.0000 0.989 1.000 0.000
#> SRR1313137 1 0.0000 0.989 1.000 0.000
#> SRR1313138 2 0.7815 0.717 0.232 0.768
#> SRR1313140 1 0.0000 0.989 1.000 0.000
#> SRR1313141 1 0.0000 0.989 1.000 0.000
#> SRR1313139 1 0.0000 0.989 1.000 0.000
#> SRR1313143 1 0.0000 0.989 1.000 0.000
#> SRR1313142 1 0.0000 0.989 1.000 0.000
#> SRR1313144 1 0.0000 0.989 1.000 0.000
#> SRR1313145 1 0.0000 0.989 1.000 0.000
#> SRR1313146 1 0.0000 0.989 1.000 0.000
#> SRR1313147 1 0.0000 0.989 1.000 0.000
#> SRR1313150 1 0.0672 0.983 0.992 0.008
#> SRR1313149 1 0.0000 0.989 1.000 0.000
#> SRR1313152 1 0.0000 0.989 1.000 0.000
#> SRR1313151 1 0.0000 0.989 1.000 0.000
#> SRR1313154 1 0.0000 0.989 1.000 0.000
#> SRR1313153 1 0.0000 0.989 1.000 0.000
#> SRR1313156 1 0.1843 0.965 0.972 0.028
#> SRR1313155 1 0.0000 0.989 1.000 0.000
#> SRR1313157 1 0.0000 0.989 1.000 0.000
#> SRR1313158 1 0.0000 0.989 1.000 0.000
#> SRR1313161 1 0.0000 0.989 1.000 0.000
#> SRR1313159 2 0.7674 0.730 0.224 0.776
#> SRR1313160 1 0.0000 0.989 1.000 0.000
#> SRR1313162 1 0.0000 0.989 1.000 0.000
#> SRR1313163 1 0.0000 0.989 1.000 0.000
#> SRR1313165 1 0.0000 0.989 1.000 0.000
#> SRR1313166 1 0.0000 0.989 1.000 0.000
#> SRR1313164 1 0.0000 0.989 1.000 0.000
#> SRR1313167 1 0.0000 0.989 1.000 0.000
#> SRR1313168 1 0.0000 0.989 1.000 0.000
#> SRR1313170 1 0.0000 0.989 1.000 0.000
#> SRR1313169 1 0.0000 0.989 1.000 0.000
#> SRR1313172 2 0.8207 0.676 0.256 0.744
#> SRR1313171 1 0.0000 0.989 1.000 0.000
#> SRR1313174 2 0.0000 0.978 0.000 1.000
#> SRR1313173 1 0.0000 0.989 1.000 0.000
#> SRR1313176 2 0.0000 0.978 0.000 1.000
#> SRR1313175 2 0.0000 0.978 0.000 1.000
#> SRR1313178 2 0.0000 0.978 0.000 1.000
#> SRR1313177 2 0.0000 0.978 0.000 1.000
#> SRR1313179 2 0.6623 0.801 0.172 0.828
#> SRR1313180 2 0.6343 0.815 0.160 0.840
#> SRR1313181 2 0.0000 0.978 0.000 1.000
#> SRR1313183 2 0.0000 0.978 0.000 1.000
#> SRR1313182 2 0.0000 0.978 0.000 1.000
#> SRR1313184 2 0.0000 0.978 0.000 1.000
#> SRR1313185 2 0.0000 0.978 0.000 1.000
#> SRR1313188 2 0.0000 0.978 0.000 1.000
#> SRR1313187 2 0.0000 0.978 0.000 1.000
#> SRR1313186 2 0.0000 0.978 0.000 1.000
#> SRR1313189 2 0.0000 0.978 0.000 1.000
#> SRR1313190 2 0.0000 0.978 0.000 1.000
#> SRR1313191 2 0.0000 0.978 0.000 1.000
#> SRR1313192 2 0.0000 0.978 0.000 1.000
#> SRR1313193 2 0.0000 0.978 0.000 1.000
#> SRR1313194 2 0.0000 0.978 0.000 1.000
#> SRR1313195 2 0.0000 0.978 0.000 1.000
#> SRR1313196 2 0.0000 0.978 0.000 1.000
#> SRR1313197 2 0.0000 0.978 0.000 1.000
#> SRR1313198 2 0.0000 0.978 0.000 1.000
#> SRR1313199 2 0.0000 0.978 0.000 1.000
#> SRR1313200 2 0.0000 0.978 0.000 1.000
#> SRR1313201 2 0.0000 0.978 0.000 1.000
#> SRR1313202 2 0.0000 0.978 0.000 1.000
#> SRR1313203 1 0.1184 0.976 0.984 0.016
#> SRR1313204 2 0.0000 0.978 0.000 1.000
#> SRR1313205 2 0.0000 0.978 0.000 1.000
#> SRR1313207 2 0.0000 0.978 0.000 1.000
#> SRR1313208 2 0.0000 0.978 0.000 1.000
#> SRR1313206 2 0.0000 0.978 0.000 1.000
#> SRR1313210 2 0.0000 0.978 0.000 1.000
#> SRR1313209 2 0.0000 0.978 0.000 1.000
#> SRR1313211 2 0.0000 0.978 0.000 1.000
#> SRR1313212 2 0.0000 0.978 0.000 1.000
#> SRR1313214 2 0.0000 0.978 0.000 1.000
#> SRR1313215 2 0.0000 0.978 0.000 1.000
#> SRR1313213 2 0.0000 0.978 0.000 1.000
#> SRR1313216 2 0.0000 0.978 0.000 1.000
#> SRR1313217 2 0.0000 0.978 0.000 1.000
#> SRR1313219 2 0.0000 0.978 0.000 1.000
#> SRR1313220 2 0.0000 0.978 0.000 1.000
#> SRR1313218 2 0.0000 0.978 0.000 1.000
#> SRR1313222 2 0.0000 0.978 0.000 1.000
#> SRR1313221 2 0.0000 0.978 0.000 1.000
#> SRR1313223 2 0.0000 0.978 0.000 1.000
#> SRR1313224 2 0.0000 0.978 0.000 1.000
#> SRR1313225 2 0.0000 0.978 0.000 1.000
#> SRR1313226 2 0.7376 0.753 0.208 0.792
#> SRR1313227 2 0.0000 0.978 0.000 1.000
#> SRR1313228 2 0.0000 0.978 0.000 1.000
#> SRR1313229 2 0.0000 0.978 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.4931 0.784 0.232 0.000 0.768
#> SRR1313063 3 0.4974 0.781 0.236 0.000 0.764
#> SRR1313064 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313065 1 0.0892 0.887 0.980 0.000 0.020
#> SRR1313066 1 0.0237 0.883 0.996 0.000 0.004
#> SRR1313067 3 0.4887 0.787 0.228 0.000 0.772
#> SRR1313068 3 0.4931 0.784 0.232 0.000 0.768
#> SRR1313069 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313071 1 0.0237 0.883 0.996 0.000 0.004
#> SRR1313072 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313073 3 0.6235 0.455 0.436 0.000 0.564
#> SRR1313074 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313076 3 0.4931 0.784 0.232 0.000 0.768
#> SRR1313077 3 0.4974 0.781 0.236 0.000 0.764
#> SRR1313078 3 0.4974 0.781 0.236 0.000 0.764
#> SRR1313079 1 0.0424 0.878 0.992 0.000 0.008
#> SRR1313080 3 0.4931 0.784 0.232 0.000 0.768
#> SRR1313081 3 0.4931 0.784 0.232 0.000 0.768
#> SRR1313082 1 0.0424 0.884 0.992 0.000 0.008
#> SRR1313083 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313086 1 0.0237 0.883 0.996 0.000 0.004
#> SRR1313087 1 0.4605 0.645 0.796 0.000 0.204
#> SRR1313088 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.881 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313091 2 0.4452 0.745 0.000 0.808 0.192
#> SRR1313093 3 0.0747 0.891 0.016 0.000 0.984
#> SRR1313095 3 0.0747 0.891 0.016 0.000 0.984
#> SRR1313096 3 0.3482 0.831 0.128 0.000 0.872
#> SRR1313094 3 0.0237 0.895 0.004 0.000 0.996
#> SRR1313097 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313098 3 0.0237 0.894 0.004 0.000 0.996
#> SRR1313101 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313100 3 0.0892 0.889 0.020 0.000 0.980
#> SRR1313105 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313109 3 0.3686 0.776 0.000 0.140 0.860
#> SRR1313108 3 0.2711 0.860 0.088 0.000 0.912
#> SRR1313111 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313112 3 0.3038 0.809 0.000 0.104 0.896
#> SRR1313113 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313115 3 0.0747 0.891 0.016 0.000 0.984
#> SRR1313114 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313116 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313122 3 0.0892 0.889 0.020 0.000 0.980
#> SRR1313124 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313128 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313126 3 0.0892 0.889 0.020 0.000 0.980
#> SRR1313130 2 0.5529 0.600 0.000 0.704 0.296
#> SRR1313132 1 0.3816 0.904 0.852 0.000 0.148
#> SRR1313129 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313133 3 0.6274 0.104 0.456 0.000 0.544
#> SRR1313131 3 0.3551 0.831 0.132 0.000 0.868
#> SRR1313134 3 0.6204 0.228 0.424 0.000 0.576
#> SRR1313135 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313136 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313137 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313138 1 0.3686 0.910 0.860 0.000 0.140
#> SRR1313140 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313141 3 0.5529 0.616 0.296 0.000 0.704
#> SRR1313139 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313143 3 0.5529 0.623 0.296 0.000 0.704
#> SRR1313142 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313144 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313145 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313146 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313147 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313150 1 0.3482 0.919 0.872 0.000 0.128
#> SRR1313149 1 0.6062 0.432 0.616 0.000 0.384
#> SRR1313152 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313151 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313154 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313153 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313156 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313155 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313157 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313158 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313161 1 0.4504 0.852 0.804 0.000 0.196
#> SRR1313159 1 0.4891 0.891 0.836 0.040 0.124
#> SRR1313160 1 0.3551 0.916 0.868 0.000 0.132
#> SRR1313162 3 0.4887 0.701 0.228 0.000 0.772
#> SRR1313163 1 0.4887 0.811 0.772 0.000 0.228
#> SRR1313165 1 0.3482 0.919 0.872 0.000 0.128
#> SRR1313166 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313164 1 0.5621 0.655 0.692 0.000 0.308
#> SRR1313167 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313168 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313170 3 0.0000 0.896 0.000 0.000 1.000
#> SRR1313169 1 0.3412 0.921 0.876 0.000 0.124
#> SRR1313172 2 0.8185 0.107 0.072 0.500 0.428
#> SRR1313171 3 0.5431 0.606 0.284 0.000 0.716
#> SRR1313174 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313173 3 0.3551 0.831 0.132 0.000 0.868
#> SRR1313176 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313179 2 0.5307 0.765 0.056 0.820 0.124
#> SRR1313180 2 0.5016 0.698 0.000 0.760 0.240
#> SRR1313181 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313187 2 0.0424 0.960 0.000 0.992 0.008
#> SRR1313186 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313196 2 0.1289 0.939 0.000 0.968 0.032
#> SRR1313197 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313203 3 0.5363 0.652 0.276 0.000 0.724
#> SRR1313204 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313226 2 0.6280 0.225 0.000 0.540 0.460
#> SRR1313227 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.966 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.966 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.2281 0.8428 0.000 0.000 0.096 0.904
#> SRR1313063 4 0.2281 0.8428 0.000 0.000 0.096 0.904
#> SRR1313064 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313065 4 0.4155 0.7663 0.240 0.000 0.004 0.756
#> SRR1313066 4 0.2704 0.8795 0.124 0.000 0.000 0.876
#> SRR1313067 3 0.4967 0.1401 0.000 0.000 0.548 0.452
#> SRR1313068 4 0.3837 0.7094 0.000 0.000 0.224 0.776
#> SRR1313069 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313070 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313071 4 0.2760 0.8764 0.128 0.000 0.000 0.872
#> SRR1313072 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313073 4 0.2480 0.8495 0.008 0.000 0.088 0.904
#> SRR1313074 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313075 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313076 4 0.4382 0.5943 0.000 0.000 0.296 0.704
#> SRR1313077 4 0.2281 0.8428 0.000 0.000 0.096 0.904
#> SRR1313078 3 0.5663 0.1331 0.024 0.000 0.536 0.440
#> SRR1313079 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313080 4 0.2281 0.8428 0.000 0.000 0.096 0.904
#> SRR1313081 4 0.4454 0.5709 0.000 0.000 0.308 0.692
#> SRR1313082 4 0.3311 0.8394 0.172 0.000 0.000 0.828
#> SRR1313083 4 0.4500 0.6538 0.316 0.000 0.000 0.684
#> SRR1313084 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313085 4 0.2814 0.8739 0.132 0.000 0.000 0.868
#> SRR1313086 4 0.4679 0.5696 0.352 0.000 0.000 0.648
#> SRR1313087 4 0.2542 0.8899 0.084 0.000 0.012 0.904
#> SRR1313088 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313089 4 0.2281 0.8934 0.096 0.000 0.000 0.904
#> SRR1313092 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.6751 0.2229 0.000 0.508 0.396 0.096
#> SRR1313093 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.1118 0.8594 0.000 0.000 0.964 0.036
#> SRR1313096 3 0.5915 0.2051 0.400 0.000 0.560 0.040
#> SRR1313094 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.4008 0.6074 0.244 0.000 0.756 0.000
#> SRR1313101 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.1940 0.8267 0.000 0.000 0.924 0.076
#> SRR1313108 3 0.2048 0.8351 0.008 0.000 0.928 0.064
#> SRR1313111 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.1118 0.8594 0.000 0.000 0.964 0.036
#> SRR1313114 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.2281 0.8100 0.000 0.000 0.904 0.096
#> SRR1313120 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.1118 0.8594 0.000 0.000 0.964 0.036
#> SRR1313124 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.1302 0.8539 0.000 0.000 0.956 0.044
#> SRR1313130 3 0.5615 0.5929 0.000 0.188 0.716 0.096
#> SRR1313132 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.8819 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.3975 0.6487 0.760 0.000 0.240 0.000
#> SRR1313131 3 0.6347 0.2138 0.384 0.000 0.548 0.068
#> SRR1313134 1 0.5398 0.3248 0.580 0.000 0.404 0.016
#> SRR1313135 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313141 1 0.5873 0.2659 0.548 0.000 0.416 0.036
#> SRR1313139 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313143 1 0.6360 0.2128 0.516 0.000 0.420 0.064
#> SRR1313142 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313149 1 0.5837 0.3072 0.564 0.000 0.400 0.036
#> SRR1313152 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313159 1 0.0804 0.8709 0.980 0.012 0.000 0.008
#> SRR1313160 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313162 1 0.4741 0.6381 0.744 0.000 0.228 0.028
#> SRR1313163 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313167 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313170 3 0.4022 0.7741 0.096 0.000 0.836 0.068
#> SRR1313169 1 0.0000 0.8906 1.000 0.000 0.000 0.000
#> SRR1313172 3 0.8466 0.2393 0.248 0.280 0.440 0.032
#> SRR1313171 1 0.5888 0.2437 0.540 0.000 0.424 0.036
#> SRR1313174 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313173 3 0.6396 0.2198 0.380 0.000 0.548 0.072
#> SRR1313176 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313178 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.2469 0.8440 0.108 0.892 0.000 0.000
#> SRR1313180 3 0.6770 0.0246 0.000 0.408 0.496 0.096
#> SRR1313181 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313188 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313187 2 0.3716 0.8986 0.000 0.852 0.052 0.096
#> SRR1313186 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313189 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313192 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313195 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313196 2 0.5140 0.7974 0.000 0.760 0.144 0.096
#> SRR1313197 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313198 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313199 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313201 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313203 1 0.6207 0.1291 0.496 0.000 0.452 0.052
#> SRR1313204 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313209 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313211 2 0.2081 0.9386 0.000 0.916 0.000 0.084
#> SRR1313212 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313215 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313213 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313217 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313219 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313220 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313222 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.2281 0.9372 0.000 0.904 0.000 0.096
#> SRR1313226 3 0.5690 0.5837 0.000 0.196 0.708 0.096
#> SRR1313227 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9463 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9463 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.1197 0.8381 0.000 0.000 0.000 0.952 0.048
#> SRR1313063 4 0.1341 0.8353 0.000 0.000 0.000 0.944 0.056
#> SRR1313064 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.4066 0.5481 0.324 0.000 0.004 0.672 0.000
#> SRR1313066 4 0.4632 0.3365 0.012 0.000 0.000 0.540 0.448
#> SRR1313067 3 0.5605 0.0851 0.000 0.000 0.520 0.404 0.076
#> SRR1313068 4 0.3800 0.7072 0.000 0.000 0.108 0.812 0.080
#> SRR1313069 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.2074 0.8223 0.000 0.000 0.000 0.896 0.104
#> SRR1313071 4 0.2864 0.8114 0.024 0.000 0.000 0.864 0.112
#> SRR1313072 4 0.1851 0.8281 0.000 0.000 0.000 0.912 0.088
#> SRR1313073 4 0.0510 0.8441 0.000 0.000 0.000 0.984 0.016
#> SRR1313074 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.5498 0.2563 0.000 0.000 0.340 0.580 0.080
#> SRR1313077 4 0.1671 0.8298 0.000 0.000 0.000 0.924 0.076
#> SRR1313078 5 0.6653 0.3426 0.000 0.000 0.244 0.320 0.436
#> SRR1313079 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.1410 0.8341 0.000 0.000 0.000 0.940 0.060
#> SRR1313081 4 0.4854 0.4560 0.000 0.000 0.260 0.680 0.060
#> SRR1313082 4 0.2280 0.7904 0.120 0.000 0.000 0.880 0.000
#> SRR1313083 4 0.4906 0.6184 0.232 0.000 0.000 0.692 0.076
#> SRR1313084 4 0.2020 0.8266 0.000 0.000 0.000 0.900 0.100
#> SRR1313085 4 0.2873 0.8042 0.016 0.000 0.000 0.856 0.128
#> SRR1313086 4 0.3636 0.6228 0.272 0.000 0.000 0.728 0.000
#> SRR1313087 4 0.0000 0.8458 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.1732 0.8314 0.000 0.000 0.000 0.920 0.080
#> SRR1313089 4 0.0703 0.8455 0.000 0.000 0.000 0.976 0.024
#> SRR1313092 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 2 0.4074 0.1070 0.000 0.636 0.364 0.000 0.000
#> SRR1313093 3 0.0404 0.8877 0.000 0.000 0.988 0.000 0.012
#> SRR1313095 3 0.1764 0.8241 0.000 0.000 0.928 0.008 0.064
#> SRR1313096 5 0.5967 0.6292 0.072 0.000 0.384 0.016 0.528
#> SRR1313094 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313098 3 0.1121 0.8432 0.044 0.000 0.956 0.000 0.000
#> SRR1313101 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313105 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0162 0.8945 0.004 0.000 0.996 0.000 0.000
#> SRR1313106 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313109 3 0.3424 0.6006 0.000 0.240 0.760 0.000 0.000
#> SRR1313108 5 0.5126 0.5162 0.008 0.000 0.432 0.024 0.536
#> SRR1313111 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.1956 0.8111 0.000 0.000 0.916 0.008 0.076
#> SRR1313114 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 3 0.4249 0.3460 0.000 0.432 0.568 0.000 0.000
#> SRR1313120 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313119 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.1764 0.8241 0.000 0.000 0.928 0.008 0.064
#> SRR1313124 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313123 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.4283 0.2555 0.544 0.000 0.000 0.000 0.456
#> SRR1313126 3 0.2325 0.7972 0.000 0.000 0.904 0.028 0.068
#> SRR1313130 3 0.4101 0.4211 0.000 0.372 0.628 0.000 0.000
#> SRR1313132 1 0.4030 0.4610 0.648 0.000 0.000 0.000 0.352
#> SRR1313129 3 0.0000 0.8985 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.5039 0.1403 0.512 0.000 0.032 0.000 0.456
#> SRR1313131 5 0.6011 0.6339 0.064 0.000 0.376 0.024 0.536
#> SRR1313134 5 0.6447 0.3973 0.364 0.000 0.160 0.004 0.472
#> SRR1313135 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.1410 0.8217 0.940 0.000 0.000 0.000 0.060
#> SRR1313141 5 0.6529 0.5945 0.272 0.000 0.196 0.008 0.524
#> SRR1313139 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313143 5 0.7223 0.6422 0.196 0.000 0.196 0.072 0.536
#> SRR1313142 1 0.3424 0.6382 0.760 0.000 0.000 0.000 0.240
#> SRR1313144 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 5 0.6491 0.5313 0.300 0.000 0.160 0.012 0.528
#> SRR1313152 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0794 0.8444 0.972 0.000 0.000 0.000 0.028
#> SRR1313154 1 0.4283 0.2555 0.544 0.000 0.000 0.000 0.456
#> SRR1313153 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.1544 0.8128 0.932 0.000 0.000 0.000 0.068
#> SRR1313155 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.4291 0.6503 0.772 0.136 0.000 0.000 0.092
#> SRR1313160 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.6339 -0.1798 0.496 0.000 0.352 0.004 0.148
#> SRR1313163 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.4210 0.3465 0.588 0.000 0.000 0.000 0.412
#> SRR1313164 1 0.4283 0.2555 0.544 0.000 0.000 0.000 0.456
#> SRR1313167 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.4509 0.5500 0.048 0.236 0.716 0.000 0.000
#> SRR1313169 1 0.0000 0.8612 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 5 0.6138 0.6819 0.144 0.000 0.296 0.004 0.556
#> SRR1313171 5 0.6577 0.6195 0.256 0.000 0.216 0.008 0.520
#> SRR1313174 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313173 5 0.6011 0.6339 0.064 0.000 0.376 0.024 0.536
#> SRR1313176 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313175 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313178 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313177 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313179 5 0.5238 -0.6679 0.044 0.472 0.000 0.000 0.484
#> SRR1313180 2 0.3752 0.3184 0.000 0.708 0.292 0.000 0.000
#> SRR1313181 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313183 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313182 2 0.3876 0.7382 0.000 0.684 0.000 0.000 0.316
#> SRR1313184 2 0.4227 0.7357 0.000 0.580 0.000 0.000 0.420
#> SRR1313185 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313188 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313187 2 0.0880 0.6947 0.000 0.968 0.032 0.000 0.000
#> SRR1313186 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313189 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313190 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313191 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313192 2 0.4249 0.7350 0.000 0.568 0.000 0.000 0.432
#> SRR1313193 2 0.3876 0.7382 0.000 0.684 0.000 0.000 0.316
#> SRR1313194 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313195 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313196 2 0.1341 0.6710 0.000 0.944 0.056 0.000 0.000
#> SRR1313197 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313198 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313199 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313200 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313201 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313202 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313203 5 0.6507 0.6911 0.156 0.000 0.288 0.016 0.540
#> SRR1313204 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313205 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313207 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313208 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313206 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313210 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313209 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313211 2 0.2377 0.7319 0.000 0.872 0.000 0.000 0.128
#> SRR1313212 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313214 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313215 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313213 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313216 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313217 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313219 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313220 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313218 2 0.1851 0.7294 0.000 0.912 0.000 0.000 0.088
#> SRR1313222 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313221 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313223 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313224 2 0.3661 0.7378 0.000 0.724 0.000 0.000 0.276
#> SRR1313225 2 0.0000 0.7221 0.000 1.000 0.000 0.000 0.000
#> SRR1313226 3 0.4300 0.2875 0.000 0.476 0.524 0.000 0.000
#> SRR1313227 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313228 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
#> SRR1313229 2 0.4291 0.7329 0.000 0.536 0.000 0.000 0.464
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.1957 0.7529 0.000 0.000 0.000 0.888 0.000 0.112
#> SRR1313063 4 0.2092 0.7472 0.000 0.000 0.000 0.876 0.000 0.124
#> SRR1313064 4 0.0146 0.7809 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313065 4 0.4246 0.3917 0.400 0.000 0.020 0.580 0.000 0.000
#> SRR1313066 6 0.3766 0.3840 0.000 0.000 0.000 0.232 0.032 0.736
#> SRR1313067 3 0.5799 -0.0531 0.000 0.000 0.428 0.392 0.000 0.180
#> SRR1313068 4 0.3923 0.6653 0.000 0.000 0.060 0.748 0.000 0.192
#> SRR1313069 4 0.0260 0.7816 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313070 4 0.3956 0.6896 0.000 0.000 0.000 0.704 0.032 0.264
#> SRR1313071 4 0.4135 0.6623 0.000 0.000 0.000 0.668 0.032 0.300
#> SRR1313072 4 0.3686 0.7107 0.000 0.000 0.000 0.748 0.032 0.220
#> SRR1313073 4 0.1141 0.7715 0.000 0.000 0.000 0.948 0.000 0.052
#> SRR1313074 4 0.0547 0.7822 0.000 0.000 0.000 0.980 0.000 0.020
#> SRR1313075 4 0.2277 0.7699 0.000 0.000 0.000 0.892 0.032 0.076
#> SRR1313076 4 0.5202 0.5080 0.000 0.000 0.192 0.616 0.000 0.192
#> SRR1313077 4 0.2340 0.7378 0.000 0.000 0.000 0.852 0.000 0.148
#> SRR1313078 6 0.3221 0.4651 0.000 0.000 0.000 0.264 0.000 0.736
#> SRR1313079 4 0.0547 0.7822 0.000 0.000 0.000 0.980 0.020 0.000
#> SRR1313080 4 0.2300 0.7399 0.000 0.000 0.000 0.856 0.000 0.144
#> SRR1313081 4 0.4728 0.5719 0.000 0.000 0.176 0.680 0.000 0.144
#> SRR1313082 4 0.4120 0.6836 0.188 0.000 0.000 0.748 0.012 0.052
#> SRR1313083 4 0.5508 0.5352 0.200 0.000 0.004 0.584 0.000 0.212
#> SRR1313084 4 0.3934 0.6985 0.000 0.000 0.000 0.708 0.032 0.260
#> SRR1313085 4 0.4203 0.6452 0.000 0.000 0.000 0.652 0.032 0.316
#> SRR1313086 4 0.3853 0.5665 0.304 0.000 0.000 0.680 0.000 0.016
#> SRR1313087 4 0.0146 0.7809 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313088 4 0.3686 0.7107 0.000 0.000 0.000 0.748 0.032 0.220
#> SRR1313089 4 0.2858 0.7603 0.000 0.000 0.000 0.844 0.032 0.124
#> SRR1313092 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313090 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313091 5 0.4318 0.1245 0.000 0.020 0.448 0.000 0.532 0.000
#> SRR1313093 3 0.1501 0.8831 0.000 0.000 0.924 0.000 0.000 0.076
#> SRR1313095 3 0.2178 0.8314 0.000 0.000 0.868 0.000 0.000 0.132
#> SRR1313096 6 0.4459 0.6163 0.084 0.000 0.204 0.004 0.000 0.708
#> SRR1313094 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313097 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313099 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313098 3 0.1075 0.8960 0.048 0.000 0.952 0.000 0.000 0.000
#> SRR1313101 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313103 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313100 3 0.0790 0.9177 0.000 0.000 0.968 0.032 0.000 0.000
#> SRR1313105 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313104 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 3 0.0777 0.9234 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1313106 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313109 3 0.2454 0.7861 0.000 0.000 0.840 0.000 0.160 0.000
#> SRR1313108 6 0.3509 0.5281 0.000 0.000 0.240 0.016 0.000 0.744
#> SRR1313111 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313110 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313112 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313115 3 0.2964 0.7567 0.000 0.000 0.792 0.000 0.004 0.204
#> SRR1313114 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313117 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313116 5 0.3823 0.1712 0.000 0.000 0.436 0.000 0.564 0.000
#> SRR1313120 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313119 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313122 3 0.2219 0.8281 0.000 0.000 0.864 0.000 0.000 0.136
#> SRR1313124 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313121 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313125 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313127 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313123 3 0.0000 0.9385 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313128 6 0.3198 0.7313 0.260 0.000 0.000 0.000 0.000 0.740
#> SRR1313126 3 0.3416 0.7710 0.000 0.000 0.804 0.056 0.000 0.140
#> SRR1313130 3 0.3175 0.6417 0.000 0.000 0.744 0.000 0.256 0.000
#> SRR1313132 6 0.3847 0.3745 0.456 0.000 0.000 0.000 0.000 0.544
#> SRR1313129 3 0.0146 0.9378 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313133 6 0.3221 0.7274 0.264 0.000 0.000 0.000 0.000 0.736
#> SRR1313131 6 0.1668 0.7051 0.008 0.000 0.004 0.060 0.000 0.928
#> SRR1313134 6 0.3023 0.7524 0.232 0.000 0.000 0.000 0.000 0.768
#> SRR1313135 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.1501 0.8422 0.924 0.000 0.000 0.000 0.000 0.076
#> SRR1313141 6 0.2135 0.7843 0.128 0.000 0.000 0.000 0.000 0.872
#> SRR1313139 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313143 6 0.2112 0.7715 0.088 0.000 0.000 0.016 0.000 0.896
#> SRR1313142 1 0.3868 -0.2537 0.504 0.000 0.000 0.000 0.000 0.496
#> SRR1313144 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313149 6 0.2146 0.7821 0.116 0.000 0.000 0.004 0.000 0.880
#> SRR1313152 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.1610 0.8328 0.916 0.000 0.000 0.000 0.000 0.084
#> SRR1313154 6 0.3244 0.7239 0.268 0.000 0.000 0.000 0.000 0.732
#> SRR1313153 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.2454 0.7171 0.840 0.000 0.000 0.000 0.000 0.160
#> SRR1313155 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.4620 0.3423 0.584 0.000 0.000 0.000 0.368 0.048
#> SRR1313160 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.5787 0.0863 0.504 0.000 0.248 0.000 0.000 0.248
#> SRR1313163 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 6 0.3607 0.6172 0.348 0.000 0.000 0.000 0.000 0.652
#> SRR1313164 6 0.3244 0.7239 0.268 0.000 0.000 0.000 0.000 0.732
#> SRR1313167 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.3829 0.7087 0.060 0.000 0.760 0.000 0.180 0.000
#> SRR1313169 1 0.0000 0.9190 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313172 6 0.4065 0.7290 0.060 0.064 0.080 0.000 0.000 0.796
#> SRR1313171 6 0.2278 0.7849 0.128 0.000 0.004 0.000 0.000 0.868
#> SRR1313174 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313173 6 0.1444 0.6937 0.000 0.000 0.000 0.072 0.000 0.928
#> SRR1313176 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313178 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.1168 0.8925 0.016 0.956 0.000 0.000 0.000 0.028
#> SRR1313180 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313181 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3727 0.3648 0.000 0.612 0.000 0.000 0.388 0.000
#> SRR1313184 2 0.0790 0.9083 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313185 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313188 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313187 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313186 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313189 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313192 2 0.3371 0.5711 0.000 0.708 0.000 0.000 0.292 0.000
#> SRR1313193 2 0.3727 0.3648 0.000 0.612 0.000 0.000 0.388 0.000
#> SRR1313194 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313195 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313196 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313197 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313198 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313199 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313201 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0790 0.9224 0.000 0.032 0.000 0.000 0.968 0.000
#> SRR1313203 6 0.1897 0.7708 0.084 0.000 0.004 0.004 0.000 0.908
#> SRR1313204 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0363 0.9256 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313207 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313209 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313211 5 0.3620 0.4614 0.000 0.352 0.000 0.000 0.648 0.000
#> SRR1313212 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313215 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313213 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.1075 0.9202 0.000 0.048 0.000 0.000 0.952 0.000
#> SRR1313217 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313219 5 0.0865 0.9256 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313220 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 5 0.2969 0.7172 0.000 0.224 0.000 0.000 0.776 0.000
#> SRR1313222 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.3833 0.2038 0.000 0.556 0.000 0.000 0.444 0.000
#> SRR1313225 5 0.1387 0.9119 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313226 5 0.0790 0.8867 0.000 0.000 0.032 0.000 0.968 0.000
#> SRR1313227 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9341 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "mclust"]
# you can also extract it by
# res = res_list["SD:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.498 0.695 0.876 0.4623 0.508 0.508
#> 3 3 0.482 0.593 0.753 0.3559 0.795 0.610
#> 4 4 0.618 0.773 0.822 0.1476 0.820 0.536
#> 5 5 0.576 0.661 0.764 0.0716 0.915 0.689
#> 6 6 0.649 0.543 0.750 0.0521 0.933 0.703
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.7056 0.7202 0.808 0.192
#> SRR1313063 1 0.7056 0.7202 0.808 0.192
#> SRR1313064 1 0.0000 0.8268 1.000 0.000
#> SRR1313065 1 0.0000 0.8268 1.000 0.000
#> SRR1313066 1 0.0376 0.8254 0.996 0.004
#> SRR1313067 1 0.7056 0.7202 0.808 0.192
#> SRR1313068 1 0.7056 0.7202 0.808 0.192
#> SRR1313069 1 0.0000 0.8268 1.000 0.000
#> SRR1313070 1 0.0376 0.8254 0.996 0.004
#> SRR1313071 1 0.0376 0.8254 0.996 0.004
#> SRR1313072 1 0.0376 0.8254 0.996 0.004
#> SRR1313073 1 0.0000 0.8268 1.000 0.000
#> SRR1313074 1 0.0000 0.8268 1.000 0.000
#> SRR1313075 1 0.0000 0.8268 1.000 0.000
#> SRR1313076 1 0.7056 0.7202 0.808 0.192
#> SRR1313077 1 0.7056 0.7202 0.808 0.192
#> SRR1313078 1 0.7139 0.7179 0.804 0.196
#> SRR1313079 1 0.0000 0.8268 1.000 0.000
#> SRR1313080 1 0.7056 0.7202 0.808 0.192
#> SRR1313081 1 0.7056 0.7202 0.808 0.192
#> SRR1313082 1 0.0000 0.8268 1.000 0.000
#> SRR1313083 1 0.0000 0.8268 1.000 0.000
#> SRR1313084 1 0.0376 0.8254 0.996 0.004
#> SRR1313085 1 0.0376 0.8254 0.996 0.004
#> SRR1313086 1 0.0000 0.8268 1.000 0.000
#> SRR1313087 1 0.0000 0.8268 1.000 0.000
#> SRR1313088 1 0.0000 0.8268 1.000 0.000
#> SRR1313089 1 0.0000 0.8268 1.000 0.000
#> SRR1313092 1 0.9775 0.3885 0.588 0.412
#> SRR1313090 1 0.9833 0.3576 0.576 0.424
#> SRR1313091 2 0.9552 0.3450 0.376 0.624
#> SRR1313093 1 0.9795 0.3838 0.584 0.416
#> SRR1313095 1 0.9661 0.4341 0.608 0.392
#> SRR1313096 1 0.7219 0.7152 0.800 0.200
#> SRR1313094 1 0.9866 0.3407 0.568 0.432
#> SRR1313097 2 0.9833 0.2205 0.424 0.576
#> SRR1313099 2 0.9833 0.2143 0.424 0.576
#> SRR1313098 1 0.8016 0.6654 0.756 0.244
#> SRR1313101 2 0.9775 0.2543 0.412 0.588
#> SRR1313102 2 0.9754 0.2621 0.408 0.592
#> SRR1313103 2 0.9815 0.2277 0.420 0.580
#> SRR1313100 1 0.9661 0.4341 0.608 0.392
#> SRR1313105 2 0.9833 0.2143 0.424 0.576
#> SRR1313104 1 0.9983 0.1843 0.524 0.476
#> SRR1313107 2 0.9833 0.2143 0.424 0.576
#> SRR1313106 1 0.9922 0.2957 0.552 0.448
#> SRR1313109 2 0.9661 0.3064 0.392 0.608
#> SRR1313108 1 0.9710 0.4214 0.600 0.400
#> SRR1313111 2 0.9815 0.2274 0.420 0.580
#> SRR1313110 1 0.9732 0.4077 0.596 0.404
#> SRR1313112 2 0.9815 0.2288 0.420 0.580
#> SRR1313113 2 0.9815 0.2274 0.420 0.580
#> SRR1313115 1 0.9754 0.4033 0.592 0.408
#> SRR1313114 1 0.9661 0.4341 0.608 0.392
#> SRR1313117 1 0.9850 0.3463 0.572 0.428
#> SRR1313118 1 0.9661 0.4341 0.608 0.392
#> SRR1313116 2 0.9661 0.3064 0.392 0.608
#> SRR1313120 2 0.9833 0.2143 0.424 0.576
#> SRR1313119 1 0.9833 0.3576 0.576 0.424
#> SRR1313122 1 0.9686 0.4278 0.604 0.396
#> SRR1313124 1 0.9833 0.3576 0.576 0.424
#> SRR1313121 1 0.9833 0.3576 0.576 0.424
#> SRR1313125 2 0.9954 0.0774 0.460 0.540
#> SRR1313127 1 0.8713 0.6024 0.708 0.292
#> SRR1313123 1 0.9427 0.4941 0.640 0.360
#> SRR1313128 1 0.0672 0.8250 0.992 0.008
#> SRR1313126 1 0.7745 0.6837 0.772 0.228
#> SRR1313130 2 0.9552 0.3450 0.376 0.624
#> SRR1313132 1 0.0672 0.8250 0.992 0.008
#> SRR1313129 2 0.9661 0.3064 0.392 0.608
#> SRR1313133 1 0.0672 0.8250 0.992 0.008
#> SRR1313131 1 0.7219 0.7152 0.800 0.200
#> SRR1313134 1 0.0672 0.8250 0.992 0.008
#> SRR1313135 1 0.0000 0.8268 1.000 0.000
#> SRR1313136 1 0.0000 0.8268 1.000 0.000
#> SRR1313137 1 0.0000 0.8268 1.000 0.000
#> SRR1313138 1 0.0938 0.8213 0.988 0.012
#> SRR1313140 1 0.0000 0.8268 1.000 0.000
#> SRR1313141 1 0.0672 0.8250 0.992 0.008
#> SRR1313139 1 0.0000 0.8268 1.000 0.000
#> SRR1313143 1 0.0672 0.8250 0.992 0.008
#> SRR1313142 1 0.0000 0.8268 1.000 0.000
#> SRR1313144 1 0.0000 0.8268 1.000 0.000
#> SRR1313145 1 0.0376 0.8260 0.996 0.004
#> SRR1313146 1 0.0000 0.8268 1.000 0.000
#> SRR1313147 1 0.0000 0.8268 1.000 0.000
#> SRR1313150 1 0.0000 0.8268 1.000 0.000
#> SRR1313149 1 0.0672 0.8250 0.992 0.008
#> SRR1313152 1 0.0000 0.8268 1.000 0.000
#> SRR1313151 1 0.0000 0.8268 1.000 0.000
#> SRR1313154 1 0.0000 0.8268 1.000 0.000
#> SRR1313153 1 0.0000 0.8268 1.000 0.000
#> SRR1313156 1 0.0672 0.8250 0.992 0.008
#> SRR1313155 1 0.0000 0.8268 1.000 0.000
#> SRR1313157 1 0.0000 0.8268 1.000 0.000
#> SRR1313158 1 0.0672 0.8250 0.992 0.008
#> SRR1313161 1 0.0000 0.8268 1.000 0.000
#> SRR1313159 1 0.3879 0.7894 0.924 0.076
#> SRR1313160 1 0.0000 0.8268 1.000 0.000
#> SRR1313162 1 0.0000 0.8268 1.000 0.000
#> SRR1313163 1 0.0000 0.8268 1.000 0.000
#> SRR1313165 1 0.0000 0.8268 1.000 0.000
#> SRR1313166 1 0.0672 0.8250 0.992 0.008
#> SRR1313164 1 0.0672 0.8250 0.992 0.008
#> SRR1313167 1 0.0000 0.8268 1.000 0.000
#> SRR1313168 1 0.0000 0.8268 1.000 0.000
#> SRR1313170 1 0.9954 0.2557 0.540 0.460
#> SRR1313169 1 0.0000 0.8268 1.000 0.000
#> SRR1313172 1 0.9922 0.2974 0.552 0.448
#> SRR1313171 1 0.0672 0.8250 0.992 0.008
#> SRR1313174 2 0.0000 0.8519 0.000 1.000
#> SRR1313173 1 0.7219 0.7152 0.800 0.200
#> SRR1313176 2 0.0000 0.8519 0.000 1.000
#> SRR1313175 2 0.0000 0.8519 0.000 1.000
#> SRR1313178 2 0.0000 0.8519 0.000 1.000
#> SRR1313177 2 0.0000 0.8519 0.000 1.000
#> SRR1313179 1 0.9998 0.1490 0.508 0.492
#> SRR1313180 2 0.0000 0.8519 0.000 1.000
#> SRR1313181 2 0.0000 0.8519 0.000 1.000
#> SRR1313183 2 0.0000 0.8519 0.000 1.000
#> SRR1313182 2 0.0000 0.8519 0.000 1.000
#> SRR1313184 2 0.5946 0.7188 0.144 0.856
#> SRR1313185 2 0.0000 0.8519 0.000 1.000
#> SRR1313188 2 0.0000 0.8519 0.000 1.000
#> SRR1313187 2 0.0000 0.8519 0.000 1.000
#> SRR1313186 2 0.0000 0.8519 0.000 1.000
#> SRR1313189 2 0.0000 0.8519 0.000 1.000
#> SRR1313190 2 0.0000 0.8519 0.000 1.000
#> SRR1313191 2 0.0000 0.8519 0.000 1.000
#> SRR1313192 2 0.0000 0.8519 0.000 1.000
#> SRR1313193 2 0.0000 0.8519 0.000 1.000
#> SRR1313194 2 0.0000 0.8519 0.000 1.000
#> SRR1313195 2 0.0000 0.8519 0.000 1.000
#> SRR1313196 2 0.0000 0.8519 0.000 1.000
#> SRR1313197 2 0.0000 0.8519 0.000 1.000
#> SRR1313198 2 0.0000 0.8519 0.000 1.000
#> SRR1313199 2 0.0000 0.8519 0.000 1.000
#> SRR1313200 2 0.0000 0.8519 0.000 1.000
#> SRR1313201 2 0.0000 0.8519 0.000 1.000
#> SRR1313202 2 0.0938 0.8429 0.012 0.988
#> SRR1313203 1 0.9732 0.4159 0.596 0.404
#> SRR1313204 2 0.0000 0.8519 0.000 1.000
#> SRR1313205 2 0.0000 0.8519 0.000 1.000
#> SRR1313207 2 0.0000 0.8519 0.000 1.000
#> SRR1313208 2 0.0000 0.8519 0.000 1.000
#> SRR1313206 2 0.0000 0.8519 0.000 1.000
#> SRR1313210 2 0.0000 0.8519 0.000 1.000
#> SRR1313209 2 0.0000 0.8519 0.000 1.000
#> SRR1313211 2 0.0000 0.8519 0.000 1.000
#> SRR1313212 2 0.0000 0.8519 0.000 1.000
#> SRR1313214 2 0.0000 0.8519 0.000 1.000
#> SRR1313215 2 0.0000 0.8519 0.000 1.000
#> SRR1313213 2 0.0000 0.8519 0.000 1.000
#> SRR1313216 2 0.8661 0.5182 0.288 0.712
#> SRR1313217 2 0.0000 0.8519 0.000 1.000
#> SRR1313219 2 0.0000 0.8519 0.000 1.000
#> SRR1313220 2 0.0000 0.8519 0.000 1.000
#> SRR1313218 2 0.0000 0.8519 0.000 1.000
#> SRR1313222 2 0.0000 0.8519 0.000 1.000
#> SRR1313221 2 0.0000 0.8519 0.000 1.000
#> SRR1313223 2 0.0000 0.8519 0.000 1.000
#> SRR1313224 2 0.0000 0.8519 0.000 1.000
#> SRR1313225 2 0.0000 0.8519 0.000 1.000
#> SRR1313226 2 0.9209 0.4293 0.336 0.664
#> SRR1313227 2 0.0000 0.8519 0.000 1.000
#> SRR1313228 2 0.0000 0.8519 0.000 1.000
#> SRR1313229 2 0.0000 0.8519 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.6026 0.4547 0.376 0.000 0.624
#> SRR1313063 3 0.5905 0.4380 0.352 0.000 0.648
#> SRR1313064 1 0.5948 0.3244 0.640 0.000 0.360
#> SRR1313065 1 0.5431 0.5355 0.716 0.000 0.284
#> SRR1313066 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313067 3 0.5706 0.5320 0.320 0.000 0.680
#> SRR1313068 3 0.5733 0.4933 0.324 0.000 0.676
#> SRR1313069 1 0.5138 0.5319 0.748 0.000 0.252
#> SRR1313070 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313071 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313072 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313073 1 0.6299 -0.1288 0.524 0.000 0.476
#> SRR1313074 1 0.5138 0.5319 0.748 0.000 0.252
#> SRR1313075 1 0.5497 0.5157 0.708 0.000 0.292
#> SRR1313076 3 0.5785 0.4983 0.332 0.000 0.668
#> SRR1313077 3 0.4796 0.5580 0.220 0.000 0.780
#> SRR1313078 3 0.3551 0.5209 0.132 0.000 0.868
#> SRR1313079 1 0.5882 0.3869 0.652 0.000 0.348
#> SRR1313080 3 0.5948 0.4578 0.360 0.000 0.640
#> SRR1313081 3 0.4842 0.5524 0.224 0.000 0.776
#> SRR1313082 1 0.4887 0.5362 0.772 0.000 0.228
#> SRR1313083 1 0.5431 0.5367 0.716 0.000 0.284
#> SRR1313084 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313085 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313086 1 0.5178 0.5306 0.744 0.000 0.256
#> SRR1313087 1 0.6280 -0.0431 0.540 0.000 0.460
#> SRR1313088 1 0.5621 0.5154 0.692 0.000 0.308
#> SRR1313089 1 0.5431 0.5167 0.716 0.000 0.284
#> SRR1313092 3 0.7706 0.5883 0.264 0.088 0.648
#> SRR1313090 3 0.9212 0.5554 0.304 0.180 0.516
#> SRR1313091 2 0.8203 0.4686 0.116 0.616 0.268
#> SRR1313093 3 0.5573 0.5613 0.160 0.044 0.796
#> SRR1313095 3 0.5363 0.5820 0.276 0.000 0.724
#> SRR1313096 3 0.3879 0.5326 0.152 0.000 0.848
#> SRR1313094 3 0.8911 0.5583 0.260 0.176 0.564
#> SRR1313097 3 0.9193 0.2631 0.156 0.364 0.480
#> SRR1313099 2 0.9457 -0.2250 0.180 0.428 0.392
#> SRR1313098 3 0.5363 0.5820 0.276 0.000 0.724
#> SRR1313101 3 0.9336 0.1309 0.164 0.412 0.424
#> SRR1313102 2 0.9266 -0.1084 0.156 0.424 0.420
#> SRR1313103 2 0.9659 -0.2553 0.216 0.432 0.352
#> SRR1313100 3 0.5650 0.5653 0.312 0.000 0.688
#> SRR1313105 3 0.9626 0.3012 0.204 0.392 0.404
#> SRR1313104 3 0.8076 0.5509 0.168 0.180 0.652
#> SRR1313107 2 0.9541 -0.2430 0.192 0.424 0.384
#> SRR1313106 3 0.8076 0.5534 0.168 0.180 0.652
#> SRR1313109 2 0.9049 0.0459 0.136 0.464 0.400
#> SRR1313108 3 0.3879 0.5326 0.152 0.000 0.848
#> SRR1313111 2 0.9454 -0.1682 0.180 0.432 0.388
#> SRR1313110 3 0.9825 0.4916 0.308 0.268 0.424
#> SRR1313112 3 0.9247 0.1992 0.156 0.392 0.452
#> SRR1313113 2 0.9266 -0.1084 0.156 0.424 0.420
#> SRR1313115 3 0.5092 0.5598 0.176 0.020 0.804
#> SRR1313114 3 0.5621 0.5665 0.308 0.000 0.692
#> SRR1313117 3 0.8787 0.5427 0.228 0.188 0.584
#> SRR1313118 3 0.6018 0.5709 0.308 0.008 0.684
#> SRR1313116 2 0.9147 -0.0430 0.144 0.444 0.412
#> SRR1313120 2 0.9569 -0.2535 0.196 0.420 0.384
#> SRR1313119 3 0.9672 0.5200 0.304 0.240 0.456
#> SRR1313122 3 0.5692 0.5882 0.268 0.008 0.724
#> SRR1313124 3 0.8845 0.5533 0.240 0.184 0.576
#> SRR1313121 3 0.9173 0.5567 0.304 0.176 0.520
#> SRR1313125 3 0.8550 0.5310 0.176 0.216 0.608
#> SRR1313127 3 0.5363 0.5820 0.276 0.000 0.724
#> SRR1313123 3 0.5291 0.5847 0.268 0.000 0.732
#> SRR1313128 1 0.5363 0.6499 0.724 0.000 0.276
#> SRR1313126 3 0.5431 0.5788 0.284 0.000 0.716
#> SRR1313130 2 0.7884 0.5509 0.120 0.656 0.224
#> SRR1313132 1 0.4796 0.6704 0.780 0.000 0.220
#> SRR1313129 2 0.9069 -0.0391 0.136 0.440 0.424
#> SRR1313133 1 0.5363 0.6499 0.724 0.000 0.276
#> SRR1313131 3 0.3551 0.5251 0.132 0.000 0.868
#> SRR1313134 1 0.6168 0.5863 0.588 0.000 0.412
#> SRR1313135 1 0.3752 0.6987 0.856 0.000 0.144
#> SRR1313136 1 0.3941 0.6959 0.844 0.000 0.156
#> SRR1313137 1 0.2796 0.7071 0.908 0.000 0.092
#> SRR1313138 1 0.4002 0.6882 0.840 0.000 0.160
#> SRR1313140 1 0.2878 0.6917 0.904 0.000 0.096
#> SRR1313141 1 0.6079 0.6133 0.612 0.000 0.388
#> SRR1313139 1 0.2356 0.7080 0.928 0.000 0.072
#> SRR1313143 1 0.6252 0.5702 0.556 0.000 0.444
#> SRR1313142 1 0.4346 0.6955 0.816 0.000 0.184
#> SRR1313144 1 0.3267 0.7081 0.884 0.000 0.116
#> SRR1313145 1 0.4346 0.6891 0.816 0.000 0.184
#> SRR1313146 1 0.3879 0.7006 0.848 0.000 0.152
#> SRR1313147 1 0.2711 0.7082 0.912 0.000 0.088
#> SRR1313150 1 0.2878 0.7050 0.904 0.000 0.096
#> SRR1313149 1 0.6140 0.6103 0.596 0.000 0.404
#> SRR1313152 1 0.2796 0.7071 0.908 0.000 0.092
#> SRR1313151 1 0.4291 0.7034 0.820 0.000 0.180
#> SRR1313154 1 0.5016 0.6747 0.760 0.000 0.240
#> SRR1313153 1 0.4062 0.6981 0.836 0.000 0.164
#> SRR1313156 1 0.4796 0.6741 0.780 0.000 0.220
#> SRR1313155 1 0.3879 0.6984 0.848 0.000 0.152
#> SRR1313157 1 0.2796 0.7071 0.908 0.000 0.092
#> SRR1313158 1 0.4452 0.6846 0.808 0.000 0.192
#> SRR1313161 1 0.3038 0.7000 0.896 0.000 0.104
#> SRR1313159 1 0.6180 0.6564 0.716 0.024 0.260
#> SRR1313160 1 0.2959 0.7027 0.900 0.000 0.100
#> SRR1313162 3 0.5560 0.5547 0.300 0.000 0.700
#> SRR1313163 1 0.3879 0.6929 0.848 0.000 0.152
#> SRR1313165 1 0.3038 0.7000 0.896 0.000 0.104
#> SRR1313166 1 0.4702 0.6775 0.788 0.000 0.212
#> SRR1313164 1 0.4702 0.6732 0.788 0.000 0.212
#> SRR1313167 1 0.3192 0.7044 0.888 0.000 0.112
#> SRR1313168 1 0.2796 0.7071 0.908 0.000 0.092
#> SRR1313170 3 0.9421 0.2248 0.176 0.388 0.436
#> SRR1313169 1 0.2711 0.7088 0.912 0.000 0.088
#> SRR1313172 3 0.8826 0.2504 0.116 0.412 0.472
#> SRR1313171 1 0.6244 0.5494 0.560 0.000 0.440
#> SRR1313174 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313173 3 0.3551 0.5209 0.132 0.000 0.868
#> SRR1313176 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313175 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313178 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313177 2 0.1411 0.8226 0.000 0.964 0.036
#> SRR1313179 2 0.8655 0.0814 0.108 0.512 0.380
#> SRR1313180 2 0.2625 0.8294 0.000 0.916 0.084
#> SRR1313181 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313183 2 0.1411 0.8226 0.000 0.964 0.036
#> SRR1313182 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313184 2 0.6224 0.6702 0.032 0.728 0.240
#> SRR1313185 2 0.2165 0.8340 0.000 0.936 0.064
#> SRR1313188 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313187 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313186 2 0.2165 0.8340 0.000 0.936 0.064
#> SRR1313189 2 0.1411 0.8226 0.000 0.964 0.036
#> SRR1313190 2 0.0237 0.8354 0.000 0.996 0.004
#> SRR1313191 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313194 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313195 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313196 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313197 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313198 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313199 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313200 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313201 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313202 2 0.5012 0.7281 0.008 0.788 0.204
#> SRR1313203 3 0.6126 -0.0644 0.352 0.004 0.644
#> SRR1313204 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313210 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313209 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313211 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313214 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313215 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313213 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313216 2 0.6586 0.6614 0.056 0.728 0.216
#> SRR1313217 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313219 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313220 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313218 2 0.0237 0.8367 0.000 0.996 0.004
#> SRR1313222 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313223 2 0.1163 0.8264 0.000 0.972 0.028
#> SRR1313224 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313225 2 0.2448 0.8327 0.000 0.924 0.076
#> SRR1313226 2 0.5881 0.6441 0.016 0.728 0.256
#> SRR1313227 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.8365 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.8365 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.2760 0.7331 0.000 0.000 0.128 0.872
#> SRR1313063 4 0.1716 0.7576 0.000 0.000 0.064 0.936
#> SRR1313064 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313065 4 0.7365 -0.0541 0.400 0.000 0.160 0.440
#> SRR1313066 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313067 4 0.4797 0.6068 0.020 0.000 0.260 0.720
#> SRR1313068 4 0.3400 0.6990 0.000 0.000 0.180 0.820
#> SRR1313069 4 0.5793 0.2874 0.384 0.000 0.036 0.580
#> SRR1313070 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313071 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313072 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313073 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313074 4 0.5781 0.2970 0.380 0.000 0.036 0.584
#> SRR1313075 4 0.1452 0.7604 0.008 0.000 0.036 0.956
#> SRR1313076 4 0.4542 0.6618 0.020 0.000 0.228 0.752
#> SRR1313077 4 0.6371 0.4784 0.092 0.000 0.300 0.608
#> SRR1313078 4 0.6944 0.4613 0.216 0.000 0.196 0.588
#> SRR1313079 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313080 4 0.2530 0.7402 0.000 0.000 0.112 0.888
#> SRR1313081 4 0.6037 0.5023 0.068 0.000 0.304 0.628
#> SRR1313082 4 0.6938 0.1116 0.400 0.000 0.112 0.488
#> SRR1313083 4 0.7075 0.1186 0.384 0.000 0.128 0.488
#> SRR1313084 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313085 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313086 4 0.6635 0.2049 0.388 0.000 0.088 0.524
#> SRR1313087 4 0.1118 0.7621 0.000 0.000 0.036 0.964
#> SRR1313088 4 0.1389 0.7605 0.000 0.000 0.048 0.952
#> SRR1313089 4 0.1452 0.7604 0.008 0.000 0.036 0.956
#> SRR1313092 3 0.1474 0.8434 0.052 0.000 0.948 0.000
#> SRR1313090 3 0.1022 0.8551 0.000 0.000 0.968 0.032
#> SRR1313091 3 0.7131 0.0909 0.068 0.436 0.472 0.024
#> SRR1313093 3 0.3569 0.7411 0.196 0.000 0.804 0.000
#> SRR1313095 3 0.1716 0.8378 0.064 0.000 0.936 0.000
#> SRR1313096 3 0.4446 0.7221 0.196 0.000 0.776 0.028
#> SRR1313094 3 0.1474 0.8434 0.052 0.000 0.948 0.000
#> SRR1313097 3 0.0817 0.8598 0.000 0.000 0.976 0.024
#> SRR1313099 3 0.3479 0.7747 0.148 0.012 0.840 0.000
#> SRR1313098 3 0.1716 0.8378 0.064 0.000 0.936 0.000
#> SRR1313101 3 0.0921 0.8578 0.000 0.000 0.972 0.028
#> SRR1313102 3 0.1004 0.8597 0.004 0.000 0.972 0.024
#> SRR1313103 3 0.1716 0.8392 0.064 0.000 0.936 0.000
#> SRR1313100 3 0.2805 0.7787 0.012 0.000 0.888 0.100
#> SRR1313105 3 0.0000 0.8585 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0817 0.8598 0.000 0.000 0.976 0.024
#> SRR1313107 3 0.3074 0.7761 0.152 0.000 0.848 0.000
#> SRR1313106 3 0.0817 0.8598 0.000 0.000 0.976 0.024
#> SRR1313109 3 0.4920 0.6197 0.052 0.192 0.756 0.000
#> SRR1313108 3 0.4245 0.7281 0.196 0.000 0.784 0.020
#> SRR1313111 3 0.0592 0.8541 0.016 0.000 0.984 0.000
#> SRR1313110 3 0.1389 0.8390 0.000 0.000 0.952 0.048
#> SRR1313112 3 0.1004 0.8593 0.000 0.004 0.972 0.024
#> SRR1313113 3 0.0592 0.8604 0.000 0.000 0.984 0.016
#> SRR1313115 3 0.3444 0.7545 0.184 0.000 0.816 0.000
#> SRR1313114 3 0.1118 0.8516 0.000 0.000 0.964 0.036
#> SRR1313117 3 0.1022 0.8551 0.000 0.000 0.968 0.032
#> SRR1313118 3 0.1302 0.8445 0.000 0.000 0.956 0.044
#> SRR1313116 3 0.0817 0.8598 0.000 0.000 0.976 0.024
#> SRR1313120 3 0.3074 0.7761 0.152 0.000 0.848 0.000
#> SRR1313119 3 0.1022 0.8551 0.000 0.000 0.968 0.032
#> SRR1313122 3 0.2060 0.8403 0.052 0.000 0.932 0.016
#> SRR1313124 3 0.0921 0.8578 0.000 0.000 0.972 0.028
#> SRR1313121 3 0.1022 0.8551 0.000 0.000 0.968 0.032
#> SRR1313125 3 0.0817 0.8598 0.000 0.000 0.976 0.024
#> SRR1313127 3 0.1716 0.8378 0.064 0.000 0.936 0.000
#> SRR1313123 3 0.1557 0.8418 0.056 0.000 0.944 0.000
#> SRR1313128 1 0.3355 0.7900 0.836 0.000 0.160 0.004
#> SRR1313126 3 0.2546 0.8301 0.060 0.000 0.912 0.028
#> SRR1313130 3 0.6796 0.2914 0.052 0.380 0.544 0.024
#> SRR1313132 1 0.3764 0.8223 0.784 0.000 0.216 0.000
#> SRR1313129 3 0.1394 0.8587 0.012 0.008 0.964 0.016
#> SRR1313133 1 0.3306 0.7865 0.840 0.000 0.156 0.004
#> SRR1313131 4 0.7687 0.2518 0.240 0.000 0.312 0.448
#> SRR1313134 1 0.4418 0.7687 0.784 0.000 0.184 0.032
#> SRR1313135 1 0.4584 0.8356 0.696 0.000 0.300 0.004
#> SRR1313136 1 0.4406 0.8345 0.700 0.000 0.300 0.000
#> SRR1313137 1 0.6084 0.8057 0.660 0.000 0.244 0.096
#> SRR1313138 1 0.5690 0.8251 0.672 0.000 0.268 0.060
#> SRR1313140 1 0.6984 0.5916 0.580 0.000 0.184 0.236
#> SRR1313141 1 0.4511 0.7628 0.784 0.000 0.176 0.040
#> SRR1313139 1 0.6523 0.7564 0.628 0.000 0.236 0.136
#> SRR1313143 1 0.5159 0.7279 0.756 0.000 0.156 0.088
#> SRR1313142 1 0.3975 0.8368 0.760 0.000 0.240 0.000
#> SRR1313144 1 0.5687 0.8302 0.684 0.000 0.248 0.068
#> SRR1313145 1 0.4103 0.8403 0.744 0.000 0.256 0.000
#> SRR1313146 1 0.4406 0.8345 0.700 0.000 0.300 0.000
#> SRR1313147 1 0.6084 0.8057 0.660 0.000 0.244 0.096
#> SRR1313150 1 0.6124 0.7978 0.640 0.000 0.276 0.084
#> SRR1313149 1 0.4966 0.7406 0.768 0.000 0.156 0.076
#> SRR1313152 1 0.6084 0.8057 0.660 0.000 0.244 0.096
#> SRR1313151 1 0.4304 0.8398 0.716 0.000 0.284 0.000
#> SRR1313154 1 0.3764 0.8273 0.784 0.000 0.216 0.000
#> SRR1313153 1 0.4103 0.8405 0.744 0.000 0.256 0.000
#> SRR1313156 1 0.3801 0.8299 0.780 0.000 0.220 0.000
#> SRR1313155 1 0.4584 0.8356 0.696 0.000 0.300 0.004
#> SRR1313157 1 0.6167 0.7972 0.648 0.000 0.256 0.096
#> SRR1313158 1 0.4072 0.8393 0.748 0.000 0.252 0.000
#> SRR1313161 1 0.6124 0.7978 0.640 0.000 0.276 0.084
#> SRR1313159 1 0.4662 0.8249 0.768 0.016 0.204 0.012
#> SRR1313160 1 0.6100 0.8013 0.644 0.000 0.272 0.084
#> SRR1313162 3 0.3991 0.6910 0.172 0.000 0.808 0.020
#> SRR1313163 1 0.5678 0.8083 0.640 0.000 0.316 0.044
#> SRR1313165 1 0.6124 0.7978 0.640 0.000 0.276 0.084
#> SRR1313166 1 0.3837 0.8266 0.776 0.000 0.224 0.000
#> SRR1313164 1 0.3528 0.8116 0.808 0.000 0.192 0.000
#> SRR1313167 1 0.6084 0.8057 0.660 0.000 0.244 0.096
#> SRR1313168 1 0.6056 0.8085 0.660 0.000 0.248 0.092
#> SRR1313170 3 0.1004 0.8597 0.004 0.000 0.972 0.024
#> SRR1313169 1 0.6025 0.8084 0.668 0.000 0.236 0.096
#> SRR1313172 2 0.8429 -0.0216 0.252 0.400 0.324 0.024
#> SRR1313171 1 0.4365 0.7657 0.784 0.000 0.188 0.028
#> SRR1313174 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313173 4 0.7627 0.3023 0.240 0.000 0.292 0.468
#> SRR1313176 2 0.2480 0.9014 0.088 0.904 0.000 0.008
#> SRR1313175 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313178 2 0.3616 0.8892 0.112 0.852 0.000 0.036
#> SRR1313177 2 0.3731 0.8865 0.120 0.844 0.000 0.036
#> SRR1313179 2 0.7116 0.5193 0.196 0.608 0.184 0.012
#> SRR1313180 2 0.5188 0.6243 0.044 0.716 0.240 0.000
#> SRR1313181 2 0.3557 0.8905 0.108 0.856 0.000 0.036
#> SRR1313183 2 0.3731 0.8865 0.120 0.844 0.000 0.036
#> SRR1313182 2 0.1022 0.8999 0.032 0.968 0.000 0.000
#> SRR1313184 2 0.5984 0.7193 0.136 0.732 0.108 0.024
#> SRR1313185 2 0.0469 0.9042 0.012 0.988 0.000 0.000
#> SRR1313188 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313187 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313186 2 0.0188 0.9038 0.004 0.996 0.000 0.000
#> SRR1313189 2 0.3842 0.8829 0.128 0.836 0.000 0.036
#> SRR1313190 2 0.3674 0.8879 0.116 0.848 0.000 0.036
#> SRR1313191 2 0.0336 0.9029 0.008 0.992 0.000 0.000
#> SRR1313192 2 0.2412 0.9019 0.084 0.908 0.000 0.008
#> SRR1313193 2 0.1545 0.9045 0.040 0.952 0.000 0.008
#> SRR1313194 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313195 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313196 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313197 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313198 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313199 2 0.2412 0.9019 0.084 0.908 0.000 0.008
#> SRR1313200 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313201 2 0.2480 0.9016 0.088 0.904 0.000 0.008
#> SRR1313202 2 0.5539 0.7467 0.088 0.764 0.124 0.024
#> SRR1313203 4 0.6251 0.5524 0.196 0.000 0.140 0.664
#> SRR1313204 2 0.2480 0.9014 0.088 0.904 0.000 0.008
#> SRR1313205 2 0.2271 0.9024 0.076 0.916 0.000 0.008
#> SRR1313207 2 0.3674 0.8879 0.116 0.848 0.000 0.036
#> SRR1313208 2 0.2662 0.9011 0.084 0.900 0.000 0.016
#> SRR1313206 2 0.2342 0.9021 0.080 0.912 0.000 0.008
#> SRR1313210 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313209 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313211 2 0.0000 0.9034 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.3497 0.8921 0.104 0.860 0.000 0.036
#> SRR1313214 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313215 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313213 2 0.3674 0.8879 0.116 0.848 0.000 0.036
#> SRR1313216 2 0.6282 0.6878 0.116 0.712 0.144 0.028
#> SRR1313217 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313219 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313220 2 0.2412 0.9019 0.084 0.908 0.000 0.008
#> SRR1313218 2 0.0817 0.9014 0.024 0.976 0.000 0.000
#> SRR1313222 2 0.3616 0.8892 0.112 0.852 0.000 0.036
#> SRR1313221 2 0.3616 0.8892 0.112 0.852 0.000 0.036
#> SRR1313223 2 0.3674 0.8879 0.116 0.848 0.000 0.036
#> SRR1313224 2 0.1302 0.8982 0.044 0.956 0.000 0.000
#> SRR1313225 2 0.0592 0.9022 0.016 0.984 0.000 0.000
#> SRR1313226 3 0.5233 0.4825 0.020 0.332 0.648 0.000
#> SRR1313227 2 0.3279 0.8950 0.096 0.872 0.000 0.032
#> SRR1313228 2 0.3435 0.8927 0.100 0.864 0.000 0.036
#> SRR1313229 2 0.3435 0.8927 0.100 0.864 0.000 0.036
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.2791 0.7629 0.036 0.000 0.016 0.892 0.056
#> SRR1313063 4 0.2502 0.7659 0.024 0.000 0.012 0.904 0.060
#> SRR1313064 4 0.1043 0.7851 0.040 0.000 0.000 0.960 0.000
#> SRR1313065 1 0.4949 0.2223 0.572 0.000 0.032 0.396 0.000
#> SRR1313066 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313067 4 0.6214 0.4942 0.292 0.000 0.060 0.592 0.056
#> SRR1313068 4 0.4964 0.6613 0.192 0.000 0.024 0.728 0.056
#> SRR1313069 4 0.3707 0.5637 0.284 0.000 0.000 0.716 0.000
#> SRR1313070 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313071 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313072 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313073 4 0.0404 0.7824 0.012 0.000 0.000 0.988 0.000
#> SRR1313074 4 0.3508 0.6052 0.252 0.000 0.000 0.748 0.000
#> SRR1313075 4 0.1270 0.7807 0.052 0.000 0.000 0.948 0.000
#> SRR1313076 4 0.5830 0.5845 0.232 0.000 0.056 0.656 0.056
#> SRR1313077 4 0.6238 0.4613 0.312 0.000 0.056 0.576 0.056
#> SRR1313078 4 0.7016 0.4641 0.276 0.000 0.140 0.528 0.056
#> SRR1313079 4 0.1043 0.7851 0.040 0.000 0.000 0.960 0.000
#> SRR1313080 4 0.3763 0.7363 0.096 0.000 0.016 0.832 0.056
#> SRR1313081 4 0.6096 0.4933 0.292 0.000 0.052 0.600 0.056
#> SRR1313082 4 0.4582 0.3367 0.416 0.000 0.012 0.572 0.000
#> SRR1313083 4 0.4268 0.2884 0.444 0.000 0.000 0.556 0.000
#> SRR1313084 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313085 4 0.0963 0.7814 0.000 0.000 0.000 0.964 0.036
#> SRR1313086 4 0.3774 0.5480 0.296 0.000 0.000 0.704 0.000
#> SRR1313087 4 0.0703 0.7866 0.024 0.000 0.000 0.976 0.000
#> SRR1313088 4 0.2377 0.7574 0.128 0.000 0.000 0.872 0.000
#> SRR1313089 4 0.1270 0.7817 0.052 0.000 0.000 0.948 0.000
#> SRR1313092 3 0.5072 0.6454 0.340 0.000 0.620 0.028 0.012
#> SRR1313090 3 0.3141 0.7250 0.152 0.000 0.832 0.000 0.016
#> SRR1313091 3 0.8079 0.1326 0.220 0.104 0.360 0.000 0.316
#> SRR1313093 3 0.4896 0.5602 0.252 0.000 0.696 0.032 0.020
#> SRR1313095 3 0.5817 0.6254 0.328 0.000 0.588 0.060 0.024
#> SRR1313096 3 0.6012 0.5102 0.252 0.000 0.632 0.056 0.060
#> SRR1313094 3 0.4822 0.6628 0.344 0.000 0.628 0.008 0.020
#> SRR1313097 3 0.4437 0.7183 0.140 0.000 0.760 0.000 0.100
#> SRR1313099 3 0.6133 0.6015 0.300 0.000 0.540 0.000 0.160
#> SRR1313098 3 0.5692 0.6262 0.332 0.000 0.592 0.056 0.020
#> SRR1313101 3 0.5087 0.6970 0.148 0.000 0.700 0.000 0.152
#> SRR1313102 3 0.4113 0.7239 0.140 0.000 0.784 0.000 0.076
#> SRR1313103 3 0.5831 0.6453 0.236 0.000 0.604 0.000 0.160
#> SRR1313100 3 0.5933 0.6563 0.232 0.000 0.640 0.100 0.028
#> SRR1313105 3 0.3932 0.7257 0.140 0.000 0.796 0.000 0.064
#> SRR1313104 3 0.2798 0.7244 0.140 0.000 0.852 0.000 0.008
#> SRR1313107 3 0.6119 0.6005 0.296 0.000 0.544 0.000 0.160
#> SRR1313106 3 0.3489 0.7282 0.144 0.000 0.820 0.000 0.036
#> SRR1313109 3 0.6840 0.5675 0.212 0.040 0.556 0.000 0.192
#> SRR1313108 3 0.6335 0.4829 0.252 0.000 0.604 0.100 0.044
#> SRR1313111 3 0.4487 0.7171 0.140 0.000 0.756 0.000 0.104
#> SRR1313110 3 0.5065 0.7204 0.232 0.000 0.692 0.008 0.068
#> SRR1313112 3 0.5087 0.6970 0.148 0.000 0.700 0.000 0.152
#> SRR1313113 3 0.4535 0.7160 0.140 0.000 0.752 0.000 0.108
#> SRR1313115 3 0.5012 0.5615 0.244 0.000 0.696 0.032 0.028
#> SRR1313114 3 0.4376 0.7056 0.216 0.000 0.744 0.028 0.012
#> SRR1313117 3 0.3098 0.7240 0.148 0.000 0.836 0.000 0.016
#> SRR1313118 3 0.4248 0.7086 0.200 0.000 0.760 0.028 0.012
#> SRR1313116 3 0.4785 0.7135 0.140 0.004 0.740 0.000 0.116
#> SRR1313120 3 0.6133 0.6015 0.300 0.000 0.540 0.000 0.160
#> SRR1313119 3 0.3488 0.7281 0.168 0.000 0.808 0.000 0.024
#> SRR1313122 3 0.6161 0.6136 0.324 0.000 0.564 0.088 0.024
#> SRR1313124 3 0.3183 0.7252 0.156 0.000 0.828 0.000 0.016
#> SRR1313121 3 0.3399 0.7259 0.168 0.000 0.812 0.000 0.020
#> SRR1313125 3 0.3256 0.7244 0.148 0.000 0.832 0.004 0.016
#> SRR1313127 3 0.5692 0.6262 0.332 0.000 0.592 0.056 0.020
#> SRR1313123 3 0.4335 0.6594 0.324 0.000 0.664 0.008 0.004
#> SRR1313128 1 0.3197 0.7030 0.836 0.000 0.140 0.000 0.024
#> SRR1313126 3 0.6595 0.5820 0.332 0.000 0.532 0.088 0.048
#> SRR1313130 3 0.8496 0.1369 0.208 0.196 0.304 0.000 0.292
#> SRR1313132 1 0.2305 0.7789 0.896 0.000 0.092 0.000 0.012
#> SRR1313129 3 0.5555 0.6952 0.204 0.000 0.644 0.000 0.152
#> SRR1313133 1 0.3197 0.7030 0.836 0.000 0.140 0.000 0.024
#> SRR1313131 3 0.7981 0.0249 0.228 0.000 0.384 0.296 0.092
#> SRR1313134 1 0.5528 0.6225 0.700 0.000 0.184 0.068 0.048
#> SRR1313135 1 0.1836 0.8193 0.932 0.000 0.036 0.032 0.000
#> SRR1313136 1 0.1907 0.8200 0.928 0.000 0.044 0.028 0.000
#> SRR1313137 1 0.2491 0.8229 0.896 0.000 0.036 0.068 0.000
#> SRR1313138 1 0.1978 0.8296 0.928 0.000 0.024 0.044 0.004
#> SRR1313140 1 0.3246 0.7093 0.808 0.000 0.008 0.184 0.000
#> SRR1313141 1 0.5368 0.6026 0.708 0.000 0.168 0.100 0.024
#> SRR1313139 1 0.2769 0.8058 0.876 0.000 0.032 0.092 0.000
#> SRR1313143 1 0.6637 0.3162 0.564 0.000 0.140 0.260 0.036
#> SRR1313142 1 0.0963 0.8159 0.964 0.000 0.036 0.000 0.000
#> SRR1313144 1 0.2304 0.8245 0.908 0.000 0.044 0.048 0.000
#> SRR1313145 1 0.0963 0.8155 0.964 0.000 0.036 0.000 0.000
#> SRR1313146 1 0.1818 0.8157 0.932 0.000 0.044 0.024 0.000
#> SRR1313147 1 0.2409 0.8240 0.900 0.000 0.032 0.068 0.000
#> SRR1313150 1 0.2659 0.8161 0.888 0.000 0.060 0.052 0.000
#> SRR1313149 1 0.6000 0.5221 0.660 0.000 0.140 0.164 0.036
#> SRR1313152 1 0.2409 0.8245 0.900 0.000 0.032 0.068 0.000
#> SRR1313151 1 0.1661 0.8189 0.940 0.000 0.036 0.024 0.000
#> SRR1313154 1 0.1197 0.8119 0.952 0.000 0.048 0.000 0.000
#> SRR1313153 1 0.1124 0.8177 0.960 0.000 0.036 0.004 0.000
#> SRR1313156 1 0.2361 0.7791 0.892 0.000 0.096 0.000 0.012
#> SRR1313155 1 0.1915 0.8196 0.928 0.000 0.040 0.032 0.000
#> SRR1313157 1 0.2580 0.8210 0.892 0.000 0.044 0.064 0.000
#> SRR1313158 1 0.1544 0.8092 0.932 0.000 0.068 0.000 0.000
#> SRR1313161 1 0.2654 0.8151 0.888 0.000 0.064 0.048 0.000
#> SRR1313159 1 0.3209 0.7622 0.848 0.000 0.120 0.004 0.028
#> SRR1313160 1 0.2659 0.8161 0.888 0.000 0.060 0.052 0.000
#> SRR1313162 1 0.6155 -0.3430 0.476 0.000 0.428 0.076 0.020
#> SRR1313163 1 0.2390 0.8078 0.896 0.000 0.084 0.020 0.000
#> SRR1313165 1 0.2726 0.8128 0.884 0.000 0.064 0.052 0.000
#> SRR1313166 1 0.1764 0.7806 0.928 0.000 0.064 0.000 0.008
#> SRR1313164 1 0.2864 0.7612 0.864 0.000 0.112 0.000 0.024
#> SRR1313167 1 0.2409 0.8245 0.900 0.000 0.032 0.068 0.000
#> SRR1313168 1 0.2409 0.8245 0.900 0.000 0.032 0.068 0.000
#> SRR1313170 3 0.5327 0.7072 0.216 0.000 0.664 0.000 0.120
#> SRR1313169 1 0.2409 0.8245 0.900 0.000 0.032 0.068 0.000
#> SRR1313172 3 0.9151 0.2708 0.236 0.076 0.336 0.092 0.260
#> SRR1313171 1 0.5561 0.6195 0.696 0.000 0.188 0.068 0.048
#> SRR1313174 2 0.4294 0.2188 0.000 0.532 0.000 0.000 0.468
#> SRR1313173 3 0.8037 -0.1001 0.224 0.000 0.348 0.332 0.096
#> SRR1313176 2 0.2891 0.7824 0.000 0.824 0.000 0.000 0.176
#> SRR1313175 5 0.2813 0.7935 0.000 0.168 0.000 0.000 0.832
#> SRR1313178 2 0.1121 0.7984 0.000 0.956 0.000 0.000 0.044
#> SRR1313177 2 0.0404 0.7623 0.000 0.988 0.000 0.000 0.012
#> SRR1313179 5 0.9303 0.1613 0.156 0.300 0.152 0.076 0.316
#> SRR1313180 5 0.3427 0.7789 0.000 0.108 0.056 0.000 0.836
#> SRR1313181 2 0.1197 0.8000 0.000 0.952 0.000 0.000 0.048
#> SRR1313183 2 0.0162 0.7701 0.000 0.996 0.000 0.000 0.004
#> SRR1313182 2 0.4219 0.3887 0.000 0.584 0.000 0.000 0.416
#> SRR1313184 5 0.7053 0.4498 0.072 0.336 0.100 0.000 0.492
#> SRR1313185 2 0.4278 0.0625 0.000 0.548 0.000 0.000 0.452
#> SRR1313188 5 0.3339 0.7955 0.000 0.124 0.040 0.000 0.836
#> SRR1313187 5 0.3309 0.7987 0.000 0.128 0.036 0.000 0.836
#> SRR1313186 5 0.4227 0.3132 0.000 0.420 0.000 0.000 0.580
#> SRR1313189 2 0.1410 0.7993 0.000 0.940 0.000 0.000 0.060
#> SRR1313190 2 0.0162 0.7701 0.000 0.996 0.000 0.000 0.004
#> SRR1313191 2 0.4219 0.3887 0.000 0.584 0.000 0.000 0.416
#> SRR1313192 2 0.2516 0.7981 0.000 0.860 0.000 0.000 0.140
#> SRR1313193 2 0.3884 0.6535 0.000 0.708 0.004 0.000 0.288
#> SRR1313194 5 0.3309 0.7987 0.000 0.128 0.036 0.000 0.836
#> SRR1313195 5 0.3309 0.7987 0.000 0.128 0.036 0.000 0.836
#> SRR1313196 5 0.3309 0.7987 0.000 0.128 0.036 0.000 0.836
#> SRR1313197 5 0.3003 0.7827 0.000 0.188 0.000 0.000 0.812
#> SRR1313198 5 0.2891 0.7900 0.000 0.176 0.000 0.000 0.824
#> SRR1313199 2 0.2929 0.7803 0.000 0.820 0.000 0.000 0.180
#> SRR1313200 5 0.3309 0.7987 0.000 0.128 0.036 0.000 0.836
#> SRR1313201 2 0.2230 0.7980 0.000 0.884 0.000 0.000 0.116
#> SRR1313202 5 0.7217 0.4848 0.072 0.292 0.132 0.000 0.504
#> SRR1313203 4 0.8231 0.4638 0.216 0.040 0.132 0.496 0.116
#> SRR1313204 2 0.2424 0.8017 0.000 0.868 0.000 0.000 0.132
#> SRR1313205 2 0.3039 0.7731 0.000 0.808 0.000 0.000 0.192
#> SRR1313207 2 0.1043 0.7971 0.000 0.960 0.000 0.000 0.040
#> SRR1313208 2 0.4307 -0.2454 0.000 0.500 0.000 0.000 0.500
#> SRR1313206 2 0.3074 0.7704 0.000 0.804 0.000 0.000 0.196
#> SRR1313210 5 0.3327 0.8012 0.000 0.144 0.028 0.000 0.828
#> SRR1313209 5 0.2929 0.7867 0.000 0.180 0.000 0.000 0.820
#> SRR1313211 5 0.4192 0.3037 0.000 0.404 0.000 0.000 0.596
#> SRR1313212 2 0.3336 0.6554 0.000 0.772 0.000 0.000 0.228
#> SRR1313214 5 0.3039 0.7784 0.000 0.192 0.000 0.000 0.808
#> SRR1313215 5 0.2891 0.7900 0.000 0.176 0.000 0.000 0.824
#> SRR1313213 2 0.0000 0.7734 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.7572 0.4335 0.076 0.300 0.172 0.000 0.452
#> SRR1313217 5 0.3098 0.8001 0.000 0.148 0.016 0.000 0.836
#> SRR1313219 5 0.3327 0.8012 0.000 0.144 0.028 0.000 0.828
#> SRR1313220 2 0.2280 0.7974 0.000 0.880 0.000 0.000 0.120
#> SRR1313218 5 0.3210 0.7629 0.000 0.212 0.000 0.000 0.788
#> SRR1313222 2 0.0963 0.7954 0.000 0.964 0.000 0.000 0.036
#> SRR1313221 2 0.1410 0.8012 0.000 0.940 0.000 0.000 0.060
#> SRR1313223 2 0.0000 0.7734 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 5 0.3177 0.7650 0.000 0.208 0.000 0.000 0.792
#> SRR1313225 5 0.3752 0.6810 0.000 0.292 0.000 0.000 0.708
#> SRR1313226 5 0.7204 0.2704 0.100 0.100 0.284 0.000 0.516
#> SRR1313227 2 0.2852 0.7841 0.000 0.828 0.000 0.000 0.172
#> SRR1313228 2 0.2891 0.7816 0.000 0.824 0.000 0.000 0.176
#> SRR1313229 2 0.2732 0.7876 0.000 0.840 0.000 0.000 0.160
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0935 0.33382 0.032 0.000 0.004 0.964 0.000 0.000
#> SRR1313063 4 0.0603 0.31502 0.016 0.000 0.000 0.980 0.000 0.004
#> SRR1313064 4 0.4018 -0.18533 0.008 0.000 0.000 0.580 0.000 0.412
#> SRR1313065 1 0.5443 -0.27393 0.492 0.000 0.000 0.124 0.000 0.384
#> SRR1313066 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313067 4 0.5534 0.36976 0.124 0.000 0.104 0.672 0.000 0.100
#> SRR1313068 4 0.3376 0.35818 0.180 0.000 0.004 0.792 0.000 0.024
#> SRR1313069 6 0.5411 0.33928 0.116 0.000 0.000 0.412 0.000 0.472
#> SRR1313070 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313071 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313072 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313073 4 0.3595 -0.00405 0.008 0.000 0.000 0.704 0.000 0.288
#> SRR1313074 6 0.5113 0.32498 0.080 0.000 0.000 0.448 0.000 0.472
#> SRR1313075 4 0.4471 -0.31825 0.028 0.000 0.000 0.500 0.000 0.472
#> SRR1313076 4 0.4562 0.38286 0.108 0.000 0.068 0.756 0.000 0.068
#> SRR1313077 4 0.5858 0.33920 0.188 0.000 0.076 0.624 0.000 0.112
#> SRR1313078 4 0.5968 0.29955 0.116 0.000 0.052 0.600 0.004 0.228
#> SRR1313079 4 0.3915 -0.18528 0.004 0.000 0.000 0.584 0.000 0.412
#> SRR1313080 4 0.2092 0.34677 0.124 0.000 0.000 0.876 0.000 0.000
#> SRR1313081 4 0.5816 0.35513 0.116 0.000 0.124 0.644 0.000 0.116
#> SRR1313082 6 0.5911 0.28521 0.252 0.000 0.000 0.280 0.000 0.468
#> SRR1313083 6 0.5861 0.20957 0.220 0.000 0.000 0.308 0.000 0.472
#> SRR1313084 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313085 6 0.3756 0.38268 0.000 0.000 0.000 0.400 0.000 0.600
#> SRR1313086 6 0.5290 0.31455 0.100 0.000 0.000 0.428 0.000 0.472
#> SRR1313087 4 0.3907 -0.17991 0.004 0.000 0.000 0.588 0.000 0.408
#> SRR1313088 4 0.4592 -0.31487 0.036 0.000 0.000 0.496 0.000 0.468
#> SRR1313089 4 0.4471 -0.31825 0.028 0.000 0.000 0.500 0.000 0.472
#> SRR1313092 3 0.3626 0.72982 0.068 0.000 0.788 0.000 0.000 0.144
#> SRR1313090 3 0.0363 0.76912 0.012 0.000 0.988 0.000 0.000 0.000
#> SRR1313091 5 0.7108 -0.12401 0.040 0.020 0.256 0.000 0.416 0.268
#> SRR1313093 3 0.5236 0.58209 0.040 0.000 0.572 0.028 0.004 0.356
#> SRR1313095 3 0.4301 0.71791 0.068 0.000 0.760 0.028 0.000 0.144
#> SRR1313096 3 0.5349 0.57990 0.044 0.000 0.568 0.032 0.004 0.352
#> SRR1313094 3 0.3683 0.73172 0.052 0.000 0.784 0.000 0.004 0.160
#> SRR1313097 3 0.0632 0.77106 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313099 3 0.6563 0.52259 0.044 0.000 0.448 0.000 0.188 0.320
#> SRR1313098 3 0.4373 0.71295 0.068 0.000 0.752 0.028 0.000 0.152
#> SRR1313101 3 0.2346 0.72987 0.008 0.000 0.868 0.000 0.124 0.000
#> SRR1313102 3 0.0717 0.77331 0.000 0.000 0.976 0.000 0.016 0.008
#> SRR1313103 3 0.5749 0.64605 0.036 0.000 0.600 0.000 0.128 0.236
#> SRR1313100 3 0.3794 0.65658 0.216 0.000 0.744 0.040 0.000 0.000
#> SRR1313105 3 0.0508 0.77289 0.000 0.000 0.984 0.000 0.012 0.004
#> SRR1313104 3 0.0405 0.77025 0.004 0.000 0.988 0.000 0.008 0.000
#> SRR1313107 3 0.6669 0.50817 0.052 0.000 0.428 0.000 0.184 0.336
#> SRR1313106 3 0.1387 0.76117 0.000 0.000 0.932 0.000 0.068 0.000
#> SRR1313109 3 0.6242 0.43607 0.024 0.000 0.488 0.000 0.292 0.196
#> SRR1313108 3 0.6249 0.48563 0.040 0.000 0.484 0.116 0.004 0.356
#> SRR1313111 3 0.1152 0.76952 0.000 0.000 0.952 0.000 0.044 0.004
#> SRR1313110 3 0.1296 0.77233 0.032 0.000 0.952 0.004 0.012 0.000
#> SRR1313112 3 0.2664 0.68616 0.000 0.000 0.816 0.000 0.184 0.000
#> SRR1313113 3 0.1958 0.74750 0.000 0.000 0.896 0.000 0.100 0.004
#> SRR1313115 3 0.5329 0.58473 0.048 0.000 0.572 0.028 0.004 0.348
#> SRR1313114 3 0.1003 0.76825 0.028 0.000 0.964 0.004 0.000 0.004
#> SRR1313117 3 0.0508 0.76970 0.012 0.000 0.984 0.000 0.004 0.000
#> SRR1313118 3 0.0363 0.76912 0.012 0.000 0.988 0.000 0.000 0.000
#> SRR1313116 3 0.2494 0.74020 0.000 0.000 0.864 0.000 0.120 0.016
#> SRR1313120 3 0.6696 0.50453 0.056 0.000 0.428 0.000 0.180 0.336
#> SRR1313119 3 0.0622 0.77000 0.012 0.000 0.980 0.000 0.008 0.000
#> SRR1313122 3 0.5463 0.66061 0.068 0.000 0.672 0.116 0.000 0.144
#> SRR1313124 3 0.0603 0.77058 0.004 0.000 0.980 0.000 0.016 0.000
#> SRR1313121 3 0.0363 0.76912 0.012 0.000 0.988 0.000 0.000 0.000
#> SRR1313125 3 0.0405 0.77025 0.004 0.000 0.988 0.000 0.008 0.000
#> SRR1313127 3 0.4315 0.71530 0.072 0.000 0.756 0.024 0.000 0.148
#> SRR1313123 3 0.4286 0.71104 0.108 0.000 0.740 0.000 0.004 0.148
#> SRR1313128 1 0.3892 0.69094 0.640 0.000 0.004 0.000 0.004 0.352
#> SRR1313126 3 0.4649 0.70452 0.076 0.000 0.736 0.040 0.000 0.148
#> SRR1313130 5 0.7045 -0.10060 0.024 0.112 0.364 0.000 0.424 0.076
#> SRR1313132 1 0.4326 0.72429 0.656 0.000 0.044 0.000 0.000 0.300
#> SRR1313129 3 0.3695 0.68508 0.004 0.000 0.772 0.000 0.184 0.040
#> SRR1313133 1 0.3769 0.68762 0.640 0.000 0.000 0.000 0.004 0.356
#> SRR1313131 4 0.6352 0.19825 0.040 0.000 0.128 0.464 0.004 0.364
#> SRR1313134 1 0.4474 0.66335 0.608 0.000 0.012 0.020 0.000 0.360
#> SRR1313135 1 0.3514 0.77976 0.804 0.000 0.088 0.000 0.000 0.108
#> SRR1313136 1 0.3883 0.78035 0.768 0.000 0.088 0.000 0.000 0.144
#> SRR1313137 1 0.0508 0.75397 0.984 0.000 0.012 0.004 0.000 0.000
#> SRR1313138 1 0.3903 0.78813 0.764 0.000 0.060 0.004 0.000 0.172
#> SRR1313140 1 0.2595 0.62569 0.836 0.000 0.000 0.160 0.000 0.004
#> SRR1313141 6 0.4883 -0.24480 0.360 0.000 0.012 0.036 0.004 0.588
#> SRR1313139 1 0.0865 0.72311 0.964 0.000 0.000 0.036 0.000 0.000
#> SRR1313143 6 0.4339 0.07834 0.120 0.000 0.000 0.140 0.004 0.736
#> SRR1313142 1 0.4094 0.77629 0.740 0.000 0.080 0.000 0.000 0.180
#> SRR1313144 1 0.1615 0.76093 0.928 0.000 0.064 0.004 0.000 0.004
#> SRR1313145 1 0.4156 0.77404 0.732 0.000 0.080 0.000 0.000 0.188
#> SRR1313146 1 0.3907 0.77919 0.764 0.000 0.084 0.000 0.000 0.152
#> SRR1313147 1 0.0458 0.74685 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313150 1 0.0508 0.75397 0.984 0.000 0.012 0.004 0.000 0.000
#> SRR1313149 6 0.4790 0.02607 0.268 0.000 0.000 0.080 0.004 0.648
#> SRR1313152 1 0.0508 0.75397 0.984 0.000 0.012 0.004 0.000 0.000
#> SRR1313151 1 0.3746 0.78205 0.780 0.000 0.080 0.000 0.000 0.140
#> SRR1313154 1 0.4094 0.77629 0.740 0.000 0.080 0.000 0.000 0.180
#> SRR1313153 1 0.4156 0.77410 0.732 0.000 0.080 0.000 0.000 0.188
#> SRR1313156 1 0.4680 0.72962 0.648 0.004 0.052 0.000 0.004 0.292
#> SRR1313155 1 0.3602 0.78026 0.796 0.000 0.088 0.000 0.000 0.116
#> SRR1313157 1 0.0508 0.74984 0.984 0.000 0.004 0.012 0.000 0.000
#> SRR1313158 1 0.4428 0.76537 0.696 0.000 0.084 0.000 0.000 0.220
#> SRR1313161 1 0.0692 0.75215 0.976 0.000 0.020 0.004 0.000 0.000
#> SRR1313159 1 0.4819 0.71983 0.636 0.004 0.052 0.000 0.008 0.300
#> SRR1313160 1 0.0508 0.75397 0.984 0.000 0.012 0.004 0.000 0.000
#> SRR1313162 3 0.4970 0.67550 0.120 0.000 0.700 0.028 0.000 0.152
#> SRR1313163 1 0.4077 0.70228 0.724 0.000 0.228 0.004 0.000 0.044
#> SRR1313165 1 0.0603 0.75315 0.980 0.000 0.016 0.004 0.000 0.000
#> SRR1313166 1 0.4381 0.75774 0.692 0.000 0.072 0.000 0.000 0.236
#> SRR1313164 1 0.4186 0.71873 0.656 0.000 0.032 0.000 0.000 0.312
#> SRR1313167 1 0.0508 0.74984 0.984 0.000 0.004 0.012 0.000 0.000
#> SRR1313168 1 0.0508 0.75397 0.984 0.000 0.012 0.004 0.000 0.000
#> SRR1313170 3 0.2898 0.76611 0.020 0.000 0.868 0.000 0.072 0.040
#> SRR1313169 1 0.1296 0.76330 0.952 0.000 0.004 0.012 0.000 0.032
#> SRR1313172 6 0.7593 -0.12219 0.052 0.028 0.160 0.036 0.240 0.484
#> SRR1313171 1 0.4480 0.66414 0.608 0.000 0.016 0.016 0.000 0.360
#> SRR1313174 5 0.3867 0.36183 0.000 0.328 0.000 0.000 0.660 0.012
#> SRR1313173 4 0.6323 0.20042 0.040 0.000 0.124 0.468 0.004 0.364
#> SRR1313176 2 0.3014 0.76262 0.000 0.804 0.000 0.000 0.184 0.012
#> SRR1313175 5 0.0363 0.66268 0.000 0.012 0.000 0.000 0.988 0.000
#> SRR1313178 2 0.0713 0.79311 0.000 0.972 0.000 0.000 0.028 0.000
#> SRR1313177 2 0.0260 0.78134 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1313179 5 0.6942 0.27952 0.040 0.180 0.020 0.000 0.432 0.328
#> SRR1313180 5 0.2118 0.60353 0.000 0.008 0.104 0.000 0.888 0.000
#> SRR1313181 2 0.2019 0.79484 0.000 0.900 0.000 0.000 0.088 0.012
#> SRR1313183 2 0.0260 0.78134 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1313182 5 0.4399 -0.10139 0.000 0.460 0.000 0.000 0.516 0.024
#> SRR1313184 5 0.6145 0.41861 0.028 0.172 0.020 0.000 0.596 0.184
#> SRR1313185 5 0.4399 0.08261 0.000 0.460 0.000 0.000 0.516 0.024
#> SRR1313188 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313187 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313186 5 0.4273 0.29143 0.000 0.380 0.000 0.000 0.596 0.024
#> SRR1313189 2 0.2669 0.75017 0.000 0.836 0.000 0.000 0.156 0.008
#> SRR1313190 2 0.0260 0.78134 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1313191 5 0.4407 -0.17687 0.000 0.484 0.000 0.000 0.492 0.024
#> SRR1313192 2 0.3743 0.67818 0.000 0.724 0.000 0.000 0.252 0.024
#> SRR1313193 2 0.4273 0.47525 0.000 0.596 0.000 0.000 0.380 0.024
#> SRR1313194 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313195 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313196 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313197 5 0.3110 0.58205 0.000 0.196 0.000 0.000 0.792 0.012
#> SRR1313198 5 0.2912 0.60127 0.000 0.172 0.000 0.000 0.816 0.012
#> SRR1313199 2 0.2946 0.76591 0.000 0.812 0.000 0.000 0.176 0.012
#> SRR1313200 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313201 2 0.2915 0.73948 0.000 0.808 0.000 0.000 0.184 0.008
#> SRR1313202 5 0.5860 0.45231 0.024 0.160 0.024 0.000 0.636 0.156
#> SRR1313203 6 0.4531 -0.05580 0.040 0.032 0.000 0.216 0.000 0.712
#> SRR1313204 2 0.2877 0.77130 0.000 0.820 0.000 0.000 0.168 0.012
#> SRR1313205 2 0.4109 0.58631 0.000 0.648 0.000 0.000 0.328 0.024
#> SRR1313207 2 0.0622 0.78736 0.000 0.980 0.000 0.000 0.012 0.008
#> SRR1313208 2 0.4123 0.14207 0.000 0.568 0.000 0.000 0.420 0.012
#> SRR1313206 2 0.4153 0.56691 0.000 0.636 0.000 0.000 0.340 0.024
#> SRR1313210 5 0.0865 0.66039 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313209 5 0.3201 0.57064 0.000 0.208 0.000 0.000 0.780 0.012
#> SRR1313211 5 0.4396 -0.06510 0.000 0.456 0.000 0.000 0.520 0.024
#> SRR1313212 2 0.2980 0.72802 0.000 0.800 0.000 0.000 0.192 0.008
#> SRR1313214 5 0.3110 0.58205 0.000 0.196 0.000 0.000 0.792 0.012
#> SRR1313215 5 0.2562 0.60396 0.000 0.172 0.000 0.000 0.828 0.000
#> SRR1313213 2 0.0260 0.78134 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1313216 5 0.6001 0.43341 0.020 0.156 0.028 0.000 0.616 0.180
#> SRR1313217 5 0.0520 0.66295 0.000 0.008 0.000 0.000 0.984 0.008
#> SRR1313219 5 0.0713 0.66188 0.000 0.028 0.000 0.000 0.972 0.000
#> SRR1313220 2 0.2980 0.73674 0.000 0.800 0.000 0.000 0.192 0.008
#> SRR1313218 5 0.3645 0.53718 0.000 0.236 0.000 0.000 0.740 0.024
#> SRR1313222 2 0.0622 0.78736 0.000 0.980 0.000 0.000 0.012 0.008
#> SRR1313221 2 0.1049 0.79267 0.000 0.960 0.000 0.000 0.032 0.008
#> SRR1313223 2 0.0260 0.78134 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1313224 5 0.3593 0.54412 0.000 0.228 0.000 0.000 0.748 0.024
#> SRR1313225 5 0.3566 0.55881 0.000 0.224 0.000 0.000 0.752 0.024
#> SRR1313226 5 0.4675 0.31901 0.028 0.008 0.288 0.000 0.660 0.016
#> SRR1313227 2 0.2980 0.76262 0.000 0.808 0.000 0.000 0.180 0.012
#> SRR1313228 2 0.2946 0.76505 0.000 0.812 0.000 0.000 0.176 0.012
#> SRR1313229 2 0.2912 0.76784 0.000 0.816 0.000 0.000 0.172 0.012
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "NMF"]
# you can also extract it by
# res = res_list["SD:NMF"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.975 0.950 0.980 0.4914 0.510 0.510
#> 3 3 0.784 0.825 0.925 0.3549 0.744 0.534
#> 4 4 0.899 0.876 0.945 0.0936 0.835 0.570
#> 5 5 0.718 0.715 0.848 0.0804 0.874 0.578
#> 6 6 0.786 0.797 0.867 0.0431 0.897 0.572
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.976 1.000 0.000
#> SRR1313063 1 0.000 0.976 1.000 0.000
#> SRR1313064 1 0.000 0.976 1.000 0.000
#> SRR1313065 1 0.000 0.976 1.000 0.000
#> SRR1313066 1 0.163 0.955 0.976 0.024
#> SRR1313067 1 0.000 0.976 1.000 0.000
#> SRR1313068 1 0.000 0.976 1.000 0.000
#> SRR1313069 1 0.000 0.976 1.000 0.000
#> SRR1313070 1 0.000 0.976 1.000 0.000
#> SRR1313071 1 0.000 0.976 1.000 0.000
#> SRR1313072 1 0.000 0.976 1.000 0.000
#> SRR1313073 1 0.000 0.976 1.000 0.000
#> SRR1313074 1 0.000 0.976 1.000 0.000
#> SRR1313075 1 0.000 0.976 1.000 0.000
#> SRR1313076 1 0.000 0.976 1.000 0.000
#> SRR1313077 1 0.000 0.976 1.000 0.000
#> SRR1313078 1 0.000 0.976 1.000 0.000
#> SRR1313079 1 0.000 0.976 1.000 0.000
#> SRR1313080 1 0.000 0.976 1.000 0.000
#> SRR1313081 1 0.000 0.976 1.000 0.000
#> SRR1313082 1 0.000 0.976 1.000 0.000
#> SRR1313083 1 0.000 0.976 1.000 0.000
#> SRR1313084 1 0.000 0.976 1.000 0.000
#> SRR1313085 1 0.000 0.976 1.000 0.000
#> SRR1313086 1 0.000 0.976 1.000 0.000
#> SRR1313087 1 0.000 0.976 1.000 0.000
#> SRR1313088 1 0.000 0.976 1.000 0.000
#> SRR1313089 1 0.000 0.976 1.000 0.000
#> SRR1313092 1 0.000 0.976 1.000 0.000
#> SRR1313090 1 0.000 0.976 1.000 0.000
#> SRR1313091 2 0.000 0.983 0.000 1.000
#> SRR1313093 1 0.000 0.976 1.000 0.000
#> SRR1313095 1 0.000 0.976 1.000 0.000
#> SRR1313096 1 0.000 0.976 1.000 0.000
#> SRR1313094 1 0.000 0.976 1.000 0.000
#> SRR1313097 1 0.141 0.958 0.980 0.020
#> SRR1313099 2 0.000 0.983 0.000 1.000
#> SRR1313098 1 0.000 0.976 1.000 0.000
#> SRR1313101 1 0.850 0.629 0.724 0.276
#> SRR1313102 1 0.000 0.976 1.000 0.000
#> SRR1313103 2 0.981 0.254 0.420 0.580
#> SRR1313100 1 0.000 0.976 1.000 0.000
#> SRR1313105 1 0.861 0.615 0.716 0.284
#> SRR1313104 1 0.000 0.976 1.000 0.000
#> SRR1313107 2 0.000 0.983 0.000 1.000
#> SRR1313106 2 0.000 0.983 0.000 1.000
#> SRR1313109 2 0.000 0.983 0.000 1.000
#> SRR1313108 1 0.000 0.976 1.000 0.000
#> SRR1313111 1 0.482 0.872 0.896 0.104
#> SRR1313110 1 0.000 0.976 1.000 0.000
#> SRR1313112 1 0.961 0.394 0.616 0.384
#> SRR1313113 1 0.808 0.677 0.752 0.248
#> SRR1313115 1 0.000 0.976 1.000 0.000
#> SRR1313114 1 0.000 0.976 1.000 0.000
#> SRR1313117 1 0.000 0.976 1.000 0.000
#> SRR1313118 1 0.000 0.976 1.000 0.000
#> SRR1313116 2 0.000 0.983 0.000 1.000
#> SRR1313120 2 0.955 0.380 0.376 0.624
#> SRR1313119 1 0.000 0.976 1.000 0.000
#> SRR1313122 1 0.000 0.976 1.000 0.000
#> SRR1313124 1 0.000 0.976 1.000 0.000
#> SRR1313121 1 0.000 0.976 1.000 0.000
#> SRR1313125 1 0.000 0.976 1.000 0.000
#> SRR1313127 1 0.000 0.976 1.000 0.000
#> SRR1313123 1 0.000 0.976 1.000 0.000
#> SRR1313128 1 0.000 0.976 1.000 0.000
#> SRR1313126 1 0.000 0.976 1.000 0.000
#> SRR1313130 2 0.000 0.983 0.000 1.000
#> SRR1313132 1 0.000 0.976 1.000 0.000
#> SRR1313129 2 0.000 0.983 0.000 1.000
#> SRR1313133 1 0.000 0.976 1.000 0.000
#> SRR1313131 1 0.000 0.976 1.000 0.000
#> SRR1313134 1 0.714 0.757 0.804 0.196
#> SRR1313135 1 0.000 0.976 1.000 0.000
#> SRR1313136 1 0.000 0.976 1.000 0.000
#> SRR1313137 1 0.000 0.976 1.000 0.000
#> SRR1313138 1 0.909 0.534 0.676 0.324
#> SRR1313140 1 0.000 0.976 1.000 0.000
#> SRR1313141 1 0.000 0.976 1.000 0.000
#> SRR1313139 1 0.000 0.976 1.000 0.000
#> SRR1313143 1 0.000 0.976 1.000 0.000
#> SRR1313142 1 0.000 0.976 1.000 0.000
#> SRR1313144 1 0.000 0.976 1.000 0.000
#> SRR1313145 1 0.000 0.976 1.000 0.000
#> SRR1313146 1 0.000 0.976 1.000 0.000
#> SRR1313147 1 0.000 0.976 1.000 0.000
#> SRR1313150 1 0.000 0.976 1.000 0.000
#> SRR1313149 1 0.000 0.976 1.000 0.000
#> SRR1313152 1 0.000 0.976 1.000 0.000
#> SRR1313151 1 0.000 0.976 1.000 0.000
#> SRR1313154 1 0.000 0.976 1.000 0.000
#> SRR1313153 1 0.000 0.976 1.000 0.000
#> SRR1313156 1 0.966 0.373 0.608 0.392
#> SRR1313155 1 0.000 0.976 1.000 0.000
#> SRR1313157 1 0.000 0.976 1.000 0.000
#> SRR1313158 1 0.000 0.976 1.000 0.000
#> SRR1313161 1 0.000 0.976 1.000 0.000
#> SRR1313159 2 0.000 0.983 0.000 1.000
#> SRR1313160 1 0.000 0.976 1.000 0.000
#> SRR1313162 1 0.000 0.976 1.000 0.000
#> SRR1313163 1 0.000 0.976 1.000 0.000
#> SRR1313165 1 0.000 0.976 1.000 0.000
#> SRR1313166 1 0.000 0.976 1.000 0.000
#> SRR1313164 1 0.000 0.976 1.000 0.000
#> SRR1313167 1 0.000 0.976 1.000 0.000
#> SRR1313168 1 0.000 0.976 1.000 0.000
#> SRR1313170 2 0.839 0.621 0.268 0.732
#> SRR1313169 1 0.000 0.976 1.000 0.000
#> SRR1313172 2 0.000 0.983 0.000 1.000
#> SRR1313171 2 0.430 0.890 0.088 0.912
#> SRR1313174 2 0.000 0.983 0.000 1.000
#> SRR1313173 1 0.000 0.976 1.000 0.000
#> SRR1313176 2 0.000 0.983 0.000 1.000
#> SRR1313175 2 0.000 0.983 0.000 1.000
#> SRR1313178 2 0.000 0.983 0.000 1.000
#> SRR1313177 2 0.000 0.983 0.000 1.000
#> SRR1313179 2 0.000 0.983 0.000 1.000
#> SRR1313180 2 0.000 0.983 0.000 1.000
#> SRR1313181 2 0.000 0.983 0.000 1.000
#> SRR1313183 2 0.000 0.983 0.000 1.000
#> SRR1313182 2 0.000 0.983 0.000 1.000
#> SRR1313184 2 0.000 0.983 0.000 1.000
#> SRR1313185 2 0.000 0.983 0.000 1.000
#> SRR1313188 2 0.000 0.983 0.000 1.000
#> SRR1313187 2 0.000 0.983 0.000 1.000
#> SRR1313186 2 0.000 0.983 0.000 1.000
#> SRR1313189 2 0.000 0.983 0.000 1.000
#> SRR1313190 2 0.000 0.983 0.000 1.000
#> SRR1313191 2 0.000 0.983 0.000 1.000
#> SRR1313192 2 0.000 0.983 0.000 1.000
#> SRR1313193 2 0.000 0.983 0.000 1.000
#> SRR1313194 2 0.000 0.983 0.000 1.000
#> SRR1313195 2 0.000 0.983 0.000 1.000
#> SRR1313196 2 0.000 0.983 0.000 1.000
#> SRR1313197 2 0.000 0.983 0.000 1.000
#> SRR1313198 2 0.000 0.983 0.000 1.000
#> SRR1313199 2 0.000 0.983 0.000 1.000
#> SRR1313200 2 0.000 0.983 0.000 1.000
#> SRR1313201 2 0.000 0.983 0.000 1.000
#> SRR1313202 2 0.000 0.983 0.000 1.000
#> SRR1313203 2 0.000 0.983 0.000 1.000
#> SRR1313204 2 0.000 0.983 0.000 1.000
#> SRR1313205 2 0.000 0.983 0.000 1.000
#> SRR1313207 2 0.000 0.983 0.000 1.000
#> SRR1313208 2 0.000 0.983 0.000 1.000
#> SRR1313206 2 0.000 0.983 0.000 1.000
#> SRR1313210 2 0.000 0.983 0.000 1.000
#> SRR1313209 2 0.000 0.983 0.000 1.000
#> SRR1313211 2 0.000 0.983 0.000 1.000
#> SRR1313212 2 0.000 0.983 0.000 1.000
#> SRR1313214 2 0.000 0.983 0.000 1.000
#> SRR1313215 2 0.000 0.983 0.000 1.000
#> SRR1313213 2 0.000 0.983 0.000 1.000
#> SRR1313216 2 0.000 0.983 0.000 1.000
#> SRR1313217 2 0.000 0.983 0.000 1.000
#> SRR1313219 2 0.000 0.983 0.000 1.000
#> SRR1313220 2 0.000 0.983 0.000 1.000
#> SRR1313218 2 0.000 0.983 0.000 1.000
#> SRR1313222 2 0.000 0.983 0.000 1.000
#> SRR1313221 2 0.000 0.983 0.000 1.000
#> SRR1313223 2 0.000 0.983 0.000 1.000
#> SRR1313224 2 0.000 0.983 0.000 1.000
#> SRR1313225 2 0.000 0.983 0.000 1.000
#> SRR1313226 2 0.000 0.983 0.000 1.000
#> SRR1313227 2 0.000 0.983 0.000 1.000
#> SRR1313228 2 0.000 0.983 0.000 1.000
#> SRR1313229 2 0.000 0.983 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.4555 0.7074 0.800 0.000 0.200
#> SRR1313063 1 0.4654 0.6982 0.792 0.000 0.208
#> SRR1313064 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313067 1 0.5948 0.4872 0.640 0.000 0.360
#> SRR1313068 1 0.6126 0.4107 0.600 0.000 0.400
#> SRR1313069 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313073 1 0.2625 0.8234 0.916 0.000 0.084
#> SRR1313074 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313076 1 0.5905 0.5009 0.648 0.000 0.352
#> SRR1313077 1 0.6079 0.4355 0.612 0.000 0.388
#> SRR1313078 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313079 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313080 1 0.6062 0.4431 0.616 0.000 0.384
#> SRR1313081 1 0.5905 0.5008 0.648 0.000 0.352
#> SRR1313082 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313087 1 0.0237 0.8846 0.996 0.000 0.004
#> SRR1313088 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313091 2 0.2959 0.8719 0.000 0.900 0.100
#> SRR1313093 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313099 3 0.4504 0.7123 0.000 0.196 0.804
#> SRR1313098 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313102 3 0.0237 0.8523 0.000 0.004 0.996
#> SRR1313103 3 0.2066 0.8218 0.000 0.060 0.940
#> SRR1313100 3 0.6126 0.1574 0.400 0.000 0.600
#> SRR1313105 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313107 3 0.3116 0.7892 0.000 0.108 0.892
#> SRR1313106 3 0.0237 0.8516 0.000 0.004 0.996
#> SRR1313109 3 0.4555 0.7084 0.000 0.200 0.800
#> SRR1313108 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313114 3 0.0237 0.8524 0.004 0.000 0.996
#> SRR1313117 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313118 3 0.0592 0.8462 0.012 0.000 0.988
#> SRR1313116 3 0.0747 0.8467 0.000 0.016 0.984
#> SRR1313120 3 0.0237 0.8523 0.000 0.004 0.996
#> SRR1313119 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313123 3 0.0892 0.8459 0.020 0.000 0.980
#> SRR1313128 3 0.5948 0.5292 0.360 0.000 0.640
#> SRR1313126 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313130 2 0.5363 0.6023 0.000 0.724 0.276
#> SRR1313132 3 0.4931 0.6928 0.232 0.000 0.768
#> SRR1313129 3 0.2796 0.8008 0.000 0.092 0.908
#> SRR1313133 3 0.5397 0.6404 0.280 0.000 0.720
#> SRR1313131 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313134 3 0.6105 0.6599 0.252 0.024 0.724
#> SRR1313135 1 0.0237 0.8842 0.996 0.000 0.004
#> SRR1313136 1 0.6180 0.0921 0.584 0.000 0.416
#> SRR1313137 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313138 2 0.6603 0.4558 0.332 0.648 0.020
#> SRR1313140 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313141 3 0.6045 0.4968 0.380 0.000 0.620
#> SRR1313139 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313143 3 0.6126 0.4610 0.400 0.000 0.600
#> SRR1313142 3 0.6111 0.4690 0.396 0.000 0.604
#> SRR1313144 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313145 3 0.6244 0.3692 0.440 0.000 0.560
#> SRR1313146 1 0.6079 0.1907 0.612 0.000 0.388
#> SRR1313147 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313149 3 0.6126 0.4610 0.400 0.000 0.600
#> SRR1313152 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313151 1 0.3412 0.7624 0.876 0.000 0.124
#> SRR1313154 1 0.6286 -0.0974 0.536 0.000 0.464
#> SRR1313153 3 0.6305 0.2455 0.484 0.000 0.516
#> SRR1313156 3 0.8649 0.5417 0.196 0.204 0.600
#> SRR1313155 1 0.2959 0.7919 0.900 0.000 0.100
#> SRR1313157 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313158 3 0.6111 0.4690 0.396 0.000 0.604
#> SRR1313161 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313159 2 0.5882 0.4063 0.000 0.652 0.348
#> SRR1313160 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313162 3 0.4555 0.7225 0.200 0.000 0.800
#> SRR1313163 3 0.6111 0.4690 0.396 0.000 0.604
#> SRR1313165 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313166 3 0.6111 0.4690 0.396 0.000 0.604
#> SRR1313164 3 0.5291 0.6547 0.268 0.000 0.732
#> SRR1313167 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313170 3 0.3038 0.7923 0.000 0.104 0.896
#> SRR1313169 1 0.0000 0.8871 1.000 0.000 0.000
#> SRR1313172 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313171 3 0.7016 0.6846 0.116 0.156 0.728
#> SRR1313174 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.8536 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313203 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313204 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313226 2 0.2625 0.8949 0.000 0.916 0.084
#> SRR1313227 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9793 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9793 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.4955 0.28542 0.000 0.000 0.444 0.556
#> SRR1313063 4 0.4877 0.37876 0.000 0.000 0.408 0.592
#> SRR1313064 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313067 3 0.0336 0.85283 0.000 0.000 0.992 0.008
#> SRR1313068 3 0.3123 0.71547 0.000 0.000 0.844 0.156
#> SRR1313069 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313076 3 0.3123 0.71567 0.000 0.000 0.844 0.156
#> SRR1313077 3 0.0707 0.84579 0.000 0.000 0.980 0.020
#> SRR1313078 3 0.0000 0.85633 0.000 0.000 1.000 0.000
#> SRR1313079 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313080 3 0.3942 0.59071 0.000 0.000 0.764 0.236
#> SRR1313081 3 0.0188 0.85489 0.000 0.000 0.996 0.004
#> SRR1313082 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.4072 0.70327 0.252 0.000 0.748 0.000
#> SRR1313090 3 0.1211 0.85701 0.040 0.000 0.960 0.000
#> SRR1313091 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313093 1 0.2973 0.80717 0.856 0.000 0.144 0.000
#> SRR1313095 3 0.2868 0.81599 0.136 0.000 0.864 0.000
#> SRR1313096 1 0.0188 0.91789 0.996 0.000 0.004 0.000
#> SRR1313094 3 0.4008 0.71652 0.244 0.000 0.756 0.000
#> SRR1313097 3 0.3024 0.80943 0.148 0.000 0.852 0.000
#> SRR1313099 1 0.4388 0.76746 0.808 0.060 0.132 0.000
#> SRR1313098 1 0.1792 0.88041 0.932 0.000 0.068 0.000
#> SRR1313101 3 0.0336 0.85843 0.008 0.000 0.992 0.000
#> SRR1313102 1 0.4888 0.25153 0.588 0.000 0.412 0.000
#> SRR1313103 1 0.1867 0.87696 0.928 0.000 0.072 0.000
#> SRR1313100 3 0.0000 0.85633 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.4477 0.61236 0.312 0.000 0.688 0.000
#> SRR1313104 3 0.4277 0.66679 0.280 0.000 0.720 0.000
#> SRR1313107 1 0.2081 0.86627 0.916 0.000 0.084 0.000
#> SRR1313106 3 0.0000 0.85633 0.000 0.000 1.000 0.000
#> SRR1313109 2 0.6936 0.37602 0.188 0.588 0.224 0.000
#> SRR1313108 3 0.2011 0.83438 0.080 0.000 0.920 0.000
#> SRR1313111 1 0.4790 0.34682 0.620 0.000 0.380 0.000
#> SRR1313110 3 0.4040 0.70873 0.248 0.000 0.752 0.000
#> SRR1313112 3 0.0000 0.85633 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.1302 0.85640 0.044 0.000 0.956 0.000
#> SRR1313115 1 0.1557 0.89066 0.944 0.000 0.056 0.000
#> SRR1313114 1 0.4948 0.15286 0.560 0.000 0.440 0.000
#> SRR1313117 3 0.0000 0.85633 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.4564 0.58034 0.328 0.000 0.672 0.000
#> SRR1313116 3 0.0188 0.85784 0.004 0.000 0.996 0.000
#> SRR1313120 1 0.3688 0.73591 0.792 0.000 0.208 0.000
#> SRR1313119 3 0.3528 0.77470 0.192 0.000 0.808 0.000
#> SRR1313122 3 0.0188 0.85775 0.004 0.000 0.996 0.000
#> SRR1313124 3 0.1557 0.85340 0.056 0.000 0.944 0.000
#> SRR1313121 3 0.0336 0.85843 0.008 0.000 0.992 0.000
#> SRR1313125 3 0.4941 0.29538 0.436 0.000 0.564 0.000
#> SRR1313127 1 0.0707 0.91144 0.980 0.000 0.020 0.000
#> SRR1313123 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313128 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.0188 0.85775 0.004 0.000 0.996 0.000
#> SRR1313130 2 0.1388 0.94693 0.028 0.960 0.012 0.000
#> SRR1313132 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313129 1 0.4916 0.21102 0.576 0.000 0.424 0.000
#> SRR1313133 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313131 1 0.1557 0.88801 0.944 0.000 0.056 0.000
#> SRR1313134 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313135 1 0.1716 0.87721 0.936 0.000 0.000 0.064
#> SRR1313136 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0188 0.91798 0.996 0.000 0.000 0.004
#> SRR1313138 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313140 4 0.0592 0.91883 0.016 0.000 0.000 0.984
#> SRR1313141 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313139 4 0.0000 0.92862 0.000 0.000 0.000 1.000
#> SRR1313143 1 0.2149 0.85400 0.912 0.000 0.000 0.088
#> SRR1313142 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0817 0.90681 0.976 0.000 0.000 0.024
#> SRR1313145 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.1792 0.87387 0.932 0.000 0.000 0.068
#> SRR1313147 4 0.2149 0.86063 0.088 0.000 0.000 0.912
#> SRR1313150 4 0.2011 0.86528 0.080 0.000 0.000 0.920
#> SRR1313149 1 0.0336 0.91609 0.992 0.000 0.000 0.008
#> SRR1313152 1 0.0188 0.91798 0.996 0.000 0.000 0.004
#> SRR1313151 1 0.3074 0.78383 0.848 0.000 0.000 0.152
#> SRR1313154 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313157 4 0.2081 0.85974 0.084 0.000 0.000 0.916
#> SRR1313158 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313161 4 0.4999 0.00579 0.492 0.000 0.000 0.508
#> SRR1313159 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313160 1 0.2921 0.80157 0.860 0.000 0.000 0.140
#> SRR1313162 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313163 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.2281 0.84923 0.904 0.000 0.000 0.096
#> SRR1313166 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313167 4 0.0336 0.92379 0.008 0.000 0.000 0.992
#> SRR1313168 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313170 1 0.0921 0.90931 0.972 0.000 0.028 0.000
#> SRR1313169 4 0.3311 0.76907 0.172 0.000 0.000 0.828
#> SRR1313172 2 0.0188 0.98454 0.004 0.996 0.000 0.000
#> SRR1313171 1 0.0000 0.91929 1.000 0.000 0.000 0.000
#> SRR1313174 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.1211 0.90250 0.960 0.000 0.040 0.000
#> SRR1313176 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313203 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313204 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.3801 0.72049 0.000 0.780 0.220 0.000
#> SRR1313227 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.98855 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.98855 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.4907 0.0623 0.000 0.000 0.488 0.488 0.024
#> SRR1313063 4 0.5014 0.2233 0.000 0.000 0.432 0.536 0.032
#> SRR1313064 4 0.0693 0.8583 0.000 0.000 0.012 0.980 0.008
#> SRR1313065 4 0.0000 0.8662 0.000 0.000 0.000 1.000 0.000
#> SRR1313066 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313067 3 0.3002 0.6712 0.000 0.000 0.856 0.116 0.028
#> SRR1313068 3 0.4370 0.5031 0.000 0.000 0.724 0.236 0.040
#> SRR1313069 4 0.0404 0.8644 0.000 0.000 0.000 0.988 0.012
#> SRR1313070 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313071 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313072 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313073 4 0.2046 0.8056 0.000 0.000 0.068 0.916 0.016
#> SRR1313074 4 0.0162 0.8651 0.000 0.000 0.000 0.996 0.004
#> SRR1313075 4 0.0000 0.8662 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 3 0.4014 0.5115 0.000 0.000 0.728 0.256 0.016
#> SRR1313077 3 0.3146 0.6606 0.000 0.000 0.844 0.128 0.028
#> SRR1313078 3 0.0833 0.7568 0.004 0.000 0.976 0.004 0.016
#> SRR1313079 4 0.0451 0.8616 0.000 0.000 0.008 0.988 0.004
#> SRR1313080 3 0.4708 0.3925 0.000 0.000 0.668 0.292 0.040
#> SRR1313081 3 0.2293 0.7119 0.000 0.000 0.900 0.084 0.016
#> SRR1313082 4 0.0000 0.8662 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313084 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313085 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313086 4 0.0162 0.8657 0.000 0.000 0.000 0.996 0.004
#> SRR1313087 4 0.0807 0.8568 0.000 0.000 0.012 0.976 0.012
#> SRR1313088 4 0.0000 0.8662 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0162 0.8664 0.000 0.000 0.000 0.996 0.004
#> SRR1313092 3 0.2230 0.7457 0.116 0.000 0.884 0.000 0.000
#> SRR1313090 3 0.0566 0.7617 0.004 0.000 0.984 0.000 0.012
#> SRR1313091 2 0.4646 0.5014 0.000 0.712 0.228 0.000 0.060
#> SRR1313093 3 0.4305 0.2139 0.488 0.000 0.512 0.000 0.000
#> SRR1313095 3 0.2127 0.7486 0.108 0.000 0.892 0.000 0.000
#> SRR1313096 1 0.4278 0.0307 0.548 0.000 0.452 0.000 0.000
#> SRR1313094 3 0.3246 0.7143 0.184 0.000 0.808 0.000 0.008
#> SRR1313097 3 0.2069 0.7584 0.076 0.000 0.912 0.000 0.012
#> SRR1313099 1 0.5255 0.0754 0.560 0.052 0.388 0.000 0.000
#> SRR1313098 3 0.4653 0.2214 0.472 0.000 0.516 0.000 0.012
#> SRR1313101 3 0.0566 0.7617 0.004 0.000 0.984 0.000 0.012
#> SRR1313102 3 0.4622 0.3634 0.440 0.000 0.548 0.000 0.012
#> SRR1313103 1 0.3861 0.4433 0.712 0.000 0.284 0.000 0.004
#> SRR1313100 3 0.0898 0.7529 0.000 0.000 0.972 0.008 0.020
#> SRR1313105 3 0.5602 0.5976 0.164 0.000 0.640 0.000 0.196
#> SRR1313104 3 0.2006 0.7580 0.072 0.000 0.916 0.000 0.012
#> SRR1313107 1 0.4193 0.3849 0.684 0.000 0.304 0.000 0.012
#> SRR1313106 3 0.3999 0.3720 0.000 0.000 0.656 0.000 0.344
#> SRR1313109 3 0.7058 0.3733 0.248 0.252 0.476 0.000 0.024
#> SRR1313108 3 0.2127 0.7438 0.108 0.000 0.892 0.000 0.000
#> SRR1313111 3 0.4555 0.2905 0.472 0.000 0.520 0.000 0.008
#> SRR1313110 3 0.2144 0.7599 0.068 0.000 0.912 0.000 0.020
#> SRR1313112 3 0.0000 0.7599 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.3171 0.6582 0.008 0.000 0.816 0.000 0.176
#> SRR1313115 1 0.4192 0.1512 0.596 0.000 0.404 0.000 0.000
#> SRR1313114 3 0.4384 0.5691 0.324 0.000 0.660 0.000 0.016
#> SRR1313117 3 0.0510 0.7603 0.000 0.000 0.984 0.000 0.016
#> SRR1313118 3 0.3163 0.7202 0.164 0.000 0.824 0.000 0.012
#> SRR1313116 5 0.2074 0.6904 0.000 0.000 0.104 0.000 0.896
#> SRR1313120 3 0.4300 0.2398 0.476 0.000 0.524 0.000 0.000
#> SRR1313119 3 0.2674 0.7438 0.120 0.000 0.868 0.000 0.012
#> SRR1313122 3 0.0162 0.7605 0.000 0.000 0.996 0.000 0.004
#> SRR1313124 3 0.0671 0.7616 0.004 0.000 0.980 0.000 0.016
#> SRR1313121 3 0.0671 0.7616 0.004 0.000 0.980 0.000 0.016
#> SRR1313125 3 0.4108 0.5898 0.308 0.000 0.684 0.000 0.008
#> SRR1313127 3 0.4542 0.2755 0.456 0.000 0.536 0.000 0.008
#> SRR1313123 1 0.3209 0.6365 0.812 0.000 0.180 0.000 0.008
#> SRR1313128 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313126 3 0.0510 0.7566 0.000 0.000 0.984 0.000 0.016
#> SRR1313130 5 0.6449 0.6861 0.024 0.188 0.200 0.000 0.588
#> SRR1313132 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313129 3 0.4574 0.4247 0.412 0.000 0.576 0.000 0.012
#> SRR1313133 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313131 1 0.4030 0.3546 0.648 0.000 0.352 0.000 0.000
#> SRR1313134 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313135 1 0.2179 0.8049 0.888 0.000 0.000 0.112 0.000
#> SRR1313136 1 0.0609 0.8367 0.980 0.000 0.000 0.000 0.020
#> SRR1313137 1 0.2616 0.8106 0.888 0.000 0.000 0.076 0.036
#> SRR1313138 1 0.1892 0.8174 0.916 0.000 0.000 0.004 0.080
#> SRR1313140 4 0.3586 0.7072 0.188 0.000 0.000 0.792 0.020
#> SRR1313141 1 0.1787 0.8301 0.936 0.000 0.004 0.044 0.016
#> SRR1313139 4 0.2331 0.8117 0.080 0.000 0.000 0.900 0.020
#> SRR1313143 1 0.3918 0.7416 0.804 0.000 0.000 0.096 0.100
#> SRR1313142 1 0.0510 0.8370 0.984 0.000 0.000 0.000 0.016
#> SRR1313144 1 0.3151 0.7693 0.836 0.000 0.000 0.144 0.020
#> SRR1313145 1 0.0162 0.8367 0.996 0.000 0.000 0.000 0.004
#> SRR1313146 1 0.2416 0.8074 0.888 0.000 0.000 0.100 0.012
#> SRR1313147 4 0.4457 0.4211 0.368 0.000 0.000 0.620 0.012
#> SRR1313150 4 0.6326 0.4703 0.248 0.000 0.000 0.528 0.224
#> SRR1313149 1 0.1121 0.8321 0.956 0.000 0.000 0.044 0.000
#> SRR1313152 1 0.2482 0.8136 0.892 0.000 0.000 0.084 0.024
#> SRR1313151 1 0.3123 0.7554 0.828 0.000 0.000 0.160 0.012
#> SRR1313154 1 0.1628 0.8286 0.936 0.000 0.000 0.056 0.008
#> SRR1313153 1 0.0510 0.8370 0.984 0.000 0.000 0.000 0.016
#> SRR1313156 1 0.0510 0.8370 0.984 0.000 0.000 0.000 0.016
#> SRR1313155 1 0.2708 0.8144 0.884 0.000 0.000 0.072 0.044
#> SRR1313157 4 0.4419 0.5288 0.312 0.000 0.000 0.668 0.020
#> SRR1313158 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.4649 0.2412 0.580 0.000 0.000 0.404 0.016
#> SRR1313159 1 0.0693 0.8360 0.980 0.008 0.000 0.000 0.012
#> SRR1313160 1 0.3488 0.7223 0.808 0.000 0.000 0.168 0.024
#> SRR1313162 1 0.0794 0.8200 0.972 0.000 0.028 0.000 0.000
#> SRR1313163 1 0.1270 0.8283 0.948 0.000 0.000 0.000 0.052
#> SRR1313165 1 0.5653 0.5256 0.632 0.000 0.000 0.208 0.160
#> SRR1313166 1 0.0000 0.8360 1.000 0.000 0.000 0.000 0.000
#> SRR1313164 1 0.0162 0.8367 0.996 0.000 0.000 0.000 0.004
#> SRR1313167 4 0.5191 0.5815 0.252 0.000 0.000 0.660 0.088
#> SRR1313168 1 0.3437 0.7752 0.832 0.000 0.000 0.120 0.048
#> SRR1313170 5 0.5523 0.3829 0.320 0.000 0.088 0.000 0.592
#> SRR1313169 4 0.4689 0.2702 0.424 0.000 0.000 0.560 0.016
#> SRR1313172 2 0.0324 0.9209 0.004 0.992 0.004 0.000 0.000
#> SRR1313171 1 0.0290 0.8369 0.992 0.000 0.000 0.000 0.008
#> SRR1313174 5 0.4150 0.6968 0.000 0.388 0.000 0.000 0.612
#> SRR1313173 3 0.4302 0.2022 0.480 0.000 0.520 0.000 0.000
#> SRR1313176 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.3612 0.8252 0.000 0.268 0.000 0.000 0.732
#> SRR1313178 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313180 5 0.1579 0.7337 0.000 0.024 0.032 0.000 0.944
#> SRR1313181 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.3612 0.4341 0.000 0.732 0.000 0.000 0.268
#> SRR1313184 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313185 5 0.4201 0.6612 0.000 0.408 0.000 0.000 0.592
#> SRR1313188 5 0.1704 0.7656 0.000 0.068 0.004 0.000 0.928
#> SRR1313187 5 0.3409 0.8264 0.000 0.160 0.024 0.000 0.816
#> SRR1313186 5 0.4114 0.7162 0.000 0.376 0.000 0.000 0.624
#> SRR1313189 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 5 0.4287 0.5428 0.000 0.460 0.000 0.000 0.540
#> SRR1313192 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.2230 0.7741 0.000 0.884 0.000 0.000 0.116
#> SRR1313194 5 0.3863 0.8326 0.000 0.248 0.012 0.000 0.740
#> SRR1313195 5 0.4519 0.8272 0.000 0.228 0.052 0.000 0.720
#> SRR1313196 5 0.3535 0.8284 0.000 0.164 0.028 0.000 0.808
#> SRR1313197 5 0.3932 0.7784 0.000 0.328 0.000 0.000 0.672
#> SRR1313198 5 0.3480 0.8327 0.000 0.248 0.000 0.000 0.752
#> SRR1313199 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.3242 0.8314 0.000 0.172 0.012 0.000 0.816
#> SRR1313201 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.3636 0.8232 0.000 0.272 0.000 0.000 0.728
#> SRR1313203 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313204 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0162 0.9273 0.000 0.996 0.000 0.000 0.004
#> SRR1313207 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 5 0.2813 0.8273 0.000 0.168 0.000 0.000 0.832
#> SRR1313209 5 0.3837 0.7974 0.000 0.308 0.000 0.000 0.692
#> SRR1313211 2 0.4297 -0.3772 0.000 0.528 0.000 0.000 0.472
#> SRR1313212 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.3730 0.8130 0.000 0.288 0.000 0.000 0.712
#> SRR1313215 5 0.3395 0.8351 0.000 0.236 0.000 0.000 0.764
#> SRR1313213 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.3274 0.8361 0.000 0.220 0.000 0.000 0.780
#> SRR1313217 5 0.3093 0.8298 0.000 0.168 0.008 0.000 0.824
#> SRR1313219 5 0.3003 0.8332 0.000 0.188 0.000 0.000 0.812
#> SRR1313220 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.4273 -0.2936 0.000 0.552 0.000 0.000 0.448
#> SRR1313222 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 5 0.3999 0.7604 0.000 0.344 0.000 0.000 0.656
#> SRR1313226 5 0.1661 0.7338 0.000 0.024 0.036 0.000 0.940
#> SRR1313227 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9315 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 6 0.3254 0.7402 0.004 0.000 0.052 0.104 0.004 0.836
#> SRR1313063 6 0.3316 0.6989 0.000 0.000 0.028 0.152 0.008 0.812
#> SRR1313064 6 0.4931 0.2706 0.084 0.000 0.000 0.324 0.000 0.592
#> SRR1313065 4 0.0146 0.8762 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313066 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 6 0.3427 0.7548 0.000 0.000 0.156 0.032 0.008 0.804
#> SRR1313068 6 0.3752 0.7668 0.000 0.000 0.116 0.080 0.008 0.796
#> SRR1313069 6 0.5195 0.3548 0.208 0.000 0.000 0.176 0.000 0.616
#> SRR1313070 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 6 0.3566 0.5714 0.024 0.000 0.000 0.224 0.000 0.752
#> SRR1313074 4 0.4918 0.4683 0.088 0.000 0.000 0.604 0.000 0.308
#> SRR1313075 4 0.2164 0.8273 0.032 0.000 0.000 0.900 0.000 0.068
#> SRR1313076 6 0.3150 0.7704 0.000 0.000 0.104 0.064 0.000 0.832
#> SRR1313077 6 0.3090 0.7647 0.004 0.000 0.140 0.028 0.000 0.828
#> SRR1313078 6 0.2738 0.7413 0.004 0.000 0.176 0.000 0.000 0.820
#> SRR1313079 4 0.4534 0.0669 0.032 0.000 0.000 0.492 0.000 0.476
#> SRR1313080 6 0.3576 0.7640 0.000 0.000 0.096 0.084 0.008 0.812
#> SRR1313081 6 0.2971 0.7624 0.004 0.000 0.144 0.020 0.000 0.832
#> SRR1313082 4 0.1124 0.8598 0.008 0.000 0.000 0.956 0.000 0.036
#> SRR1313083 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313084 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 4 0.4159 0.6868 0.176 0.000 0.000 0.736 0.000 0.088
#> SRR1313087 6 0.4433 0.2999 0.040 0.000 0.000 0.344 0.000 0.616
#> SRR1313088 4 0.3819 0.7074 0.172 0.000 0.000 0.764 0.000 0.064
#> SRR1313089 4 0.0000 0.8776 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 3 0.3136 0.7579 0.016 0.000 0.796 0.000 0.000 0.188
#> SRR1313090 3 0.3109 0.7315 0.000 0.000 0.772 0.000 0.004 0.224
#> SRR1313091 3 0.4528 0.6126 0.000 0.148 0.716 0.000 0.132 0.004
#> SRR1313093 3 0.3196 0.7823 0.064 0.000 0.828 0.000 0.000 0.108
#> SRR1313095 3 0.3784 0.6536 0.012 0.000 0.680 0.000 0.000 0.308
#> SRR1313096 3 0.4520 0.7471 0.128 0.000 0.704 0.000 0.000 0.168
#> SRR1313094 3 0.1285 0.7840 0.004 0.000 0.944 0.000 0.000 0.052
#> SRR1313097 3 0.1753 0.7819 0.000 0.000 0.912 0.000 0.004 0.084
#> SRR1313099 3 0.2002 0.7470 0.076 0.004 0.908 0.000 0.000 0.012
#> SRR1313098 6 0.4798 0.4277 0.080 0.000 0.300 0.000 0.000 0.620
#> SRR1313101 3 0.3240 0.7379 0.000 0.000 0.752 0.000 0.004 0.244
#> SRR1313102 3 0.3092 0.7043 0.060 0.000 0.836 0.000 0.000 0.104
#> SRR1313103 3 0.3006 0.7098 0.092 0.000 0.844 0.000 0.000 0.064
#> SRR1313100 6 0.3881 0.6407 0.000 0.000 0.252 0.024 0.004 0.720
#> SRR1313105 3 0.2500 0.7355 0.004 0.000 0.868 0.000 0.116 0.012
#> SRR1313104 3 0.2979 0.7508 0.004 0.000 0.804 0.000 0.004 0.188
#> SRR1313107 3 0.3045 0.7067 0.100 0.000 0.840 0.000 0.000 0.060
#> SRR1313106 5 0.4189 0.3575 0.000 0.000 0.376 0.000 0.604 0.020
#> SRR1313109 3 0.3374 0.7427 0.024 0.052 0.848 0.000 0.068 0.008
#> SRR1313108 3 0.3279 0.7628 0.028 0.000 0.796 0.000 0.000 0.176
#> SRR1313111 3 0.1921 0.7490 0.052 0.000 0.916 0.000 0.000 0.032
#> SRR1313110 6 0.3253 0.6054 0.020 0.000 0.192 0.000 0.000 0.788
#> SRR1313112 3 0.3126 0.7131 0.000 0.000 0.752 0.000 0.000 0.248
#> SRR1313113 3 0.3248 0.6961 0.000 0.000 0.804 0.000 0.164 0.032
#> SRR1313115 3 0.3473 0.7710 0.096 0.000 0.808 0.000 0.000 0.096
#> SRR1313114 3 0.4903 0.2760 0.060 0.000 0.476 0.000 0.000 0.464
#> SRR1313117 3 0.4328 0.7012 0.000 0.000 0.720 0.000 0.100 0.180
#> SRR1313118 3 0.4315 0.5285 0.016 0.000 0.612 0.008 0.000 0.364
#> SRR1313116 5 0.0790 0.8752 0.000 0.000 0.032 0.000 0.968 0.000
#> SRR1313120 3 0.2744 0.7793 0.064 0.000 0.864 0.000 0.000 0.072
#> SRR1313119 3 0.3128 0.7442 0.012 0.000 0.812 0.000 0.008 0.168
#> SRR1313122 3 0.3023 0.7248 0.000 0.000 0.768 0.000 0.000 0.232
#> SRR1313124 3 0.3374 0.7375 0.000 0.000 0.772 0.000 0.020 0.208
#> SRR1313121 3 0.3468 0.6728 0.000 0.000 0.712 0.000 0.004 0.284
#> SRR1313125 3 0.2752 0.7759 0.036 0.000 0.856 0.000 0.000 0.108
#> SRR1313127 3 0.4686 0.7376 0.092 0.000 0.660 0.000 0.000 0.248
#> SRR1313123 3 0.3992 0.6521 0.104 0.000 0.760 0.000 0.000 0.136
#> SRR1313128 1 0.1524 0.8857 0.932 0.000 0.060 0.000 0.000 0.008
#> SRR1313126 6 0.3774 0.2289 0.000 0.000 0.408 0.000 0.000 0.592
#> SRR1313130 5 0.4310 0.0193 0.004 0.000 0.472 0.000 0.512 0.012
#> SRR1313132 1 0.2703 0.8352 0.824 0.000 0.172 0.000 0.000 0.004
#> SRR1313129 3 0.2908 0.7121 0.048 0.000 0.848 0.000 0.000 0.104
#> SRR1313133 1 0.1701 0.8835 0.920 0.000 0.072 0.000 0.000 0.008
#> SRR1313131 3 0.4045 0.7584 0.120 0.000 0.756 0.000 0.000 0.124
#> SRR1313134 1 0.2553 0.8528 0.848 0.000 0.144 0.000 0.000 0.008
#> SRR1313135 1 0.0951 0.8850 0.968 0.000 0.008 0.004 0.000 0.020
#> SRR1313136 1 0.1333 0.8884 0.944 0.000 0.048 0.000 0.000 0.008
#> SRR1313137 1 0.2102 0.8790 0.908 0.000 0.012 0.012 0.000 0.068
#> SRR1313138 1 0.4311 0.8304 0.756 0.000 0.108 0.000 0.016 0.120
#> SRR1313140 1 0.2966 0.8177 0.856 0.000 0.000 0.048 0.008 0.088
#> SRR1313141 1 0.0862 0.8851 0.972 0.000 0.008 0.000 0.004 0.016
#> SRR1313139 1 0.3979 0.7228 0.752 0.000 0.000 0.172 0.000 0.076
#> SRR1313143 1 0.1542 0.8721 0.936 0.000 0.008 0.000 0.004 0.052
#> SRR1313142 1 0.0713 0.8880 0.972 0.000 0.028 0.000 0.000 0.000
#> SRR1313144 1 0.1075 0.8756 0.952 0.000 0.000 0.000 0.000 0.048
#> SRR1313145 1 0.0790 0.8879 0.968 0.000 0.032 0.000 0.000 0.000
#> SRR1313146 1 0.1010 0.8753 0.960 0.000 0.004 0.000 0.000 0.036
#> SRR1313147 1 0.3118 0.8175 0.836 0.000 0.000 0.072 0.000 0.092
#> SRR1313150 1 0.3616 0.8187 0.828 0.000 0.000 0.056 0.056 0.060
#> SRR1313149 1 0.0806 0.8844 0.972 0.000 0.008 0.000 0.000 0.020
#> SRR1313152 1 0.2691 0.8758 0.872 0.000 0.032 0.008 0.000 0.088
#> SRR1313151 1 0.1152 0.8720 0.952 0.000 0.004 0.000 0.000 0.044
#> SRR1313154 1 0.0405 0.8849 0.988 0.000 0.008 0.000 0.000 0.004
#> SRR1313153 1 0.1349 0.8865 0.940 0.000 0.056 0.000 0.000 0.004
#> SRR1313156 1 0.1444 0.8825 0.928 0.000 0.072 0.000 0.000 0.000
#> SRR1313155 1 0.0363 0.8844 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313157 1 0.3469 0.8107 0.824 0.000 0.000 0.072 0.012 0.092
#> SRR1313158 1 0.3168 0.8317 0.804 0.000 0.172 0.000 0.000 0.024
#> SRR1313161 1 0.5464 0.7619 0.668 0.000 0.152 0.060 0.000 0.120
#> SRR1313159 1 0.2442 0.8538 0.852 0.000 0.144 0.000 0.000 0.004
#> SRR1313160 1 0.4204 0.8320 0.764 0.000 0.092 0.008 0.004 0.132
#> SRR1313162 1 0.4222 0.7929 0.728 0.000 0.184 0.000 0.000 0.088
#> SRR1313163 1 0.2872 0.8784 0.864 0.000 0.076 0.000 0.008 0.052
#> SRR1313165 1 0.2488 0.8603 0.880 0.000 0.000 0.000 0.044 0.076
#> SRR1313166 1 0.2257 0.8665 0.876 0.000 0.116 0.000 0.000 0.008
#> SRR1313164 1 0.2362 0.8570 0.860 0.000 0.136 0.000 0.000 0.004
#> SRR1313167 1 0.4476 0.6096 0.668 0.000 0.000 0.280 0.008 0.044
#> SRR1313168 1 0.1667 0.8842 0.936 0.000 0.008 0.008 0.004 0.044
#> SRR1313170 5 0.4630 0.5265 0.048 0.000 0.280 0.000 0.660 0.012
#> SRR1313169 1 0.3454 0.8085 0.812 0.000 0.004 0.124 0.000 0.060
#> SRR1313172 2 0.2932 0.7903 0.000 0.820 0.164 0.000 0.000 0.016
#> SRR1313171 1 0.3073 0.8095 0.788 0.000 0.204 0.000 0.000 0.008
#> SRR1313174 5 0.2260 0.8367 0.000 0.140 0.000 0.000 0.860 0.000
#> SRR1313173 3 0.4120 0.7624 0.096 0.000 0.744 0.000 0.000 0.160
#> SRR1313176 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.1141 0.8867 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313178 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.0146 0.9694 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1313180 5 0.0363 0.8798 0.000 0.000 0.012 0.000 0.988 0.000
#> SRR1313181 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.2912 0.7031 0.000 0.784 0.000 0.000 0.216 0.000
#> SRR1313184 2 0.0260 0.9638 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1313185 5 0.2300 0.8335 0.000 0.144 0.000 0.000 0.856 0.000
#> SRR1313188 5 0.0260 0.8794 0.000 0.000 0.008 0.000 0.992 0.000
#> SRR1313187 5 0.0363 0.8798 0.000 0.000 0.012 0.000 0.988 0.000
#> SRR1313186 5 0.2178 0.8436 0.000 0.132 0.000 0.000 0.868 0.000
#> SRR1313189 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.3221 0.6900 0.000 0.264 0.000 0.000 0.736 0.000
#> SRR1313192 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.2300 0.8156 0.000 0.856 0.000 0.000 0.144 0.000
#> SRR1313194 5 0.1196 0.8890 0.000 0.040 0.008 0.000 0.952 0.000
#> SRR1313195 5 0.1477 0.8876 0.000 0.048 0.008 0.000 0.940 0.004
#> SRR1313196 5 0.0363 0.8798 0.000 0.000 0.012 0.000 0.988 0.000
#> SRR1313197 5 0.1863 0.8629 0.000 0.104 0.000 0.000 0.896 0.000
#> SRR1313198 5 0.0865 0.8886 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313199 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0508 0.8819 0.000 0.004 0.012 0.000 0.984 0.000
#> SRR1313201 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.1196 0.8893 0.000 0.040 0.008 0.000 0.952 0.000
#> SRR1313203 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313204 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.0622 0.8833 0.008 0.012 0.000 0.000 0.980 0.000
#> SRR1313209 5 0.1610 0.8747 0.000 0.084 0.000 0.000 0.916 0.000
#> SRR1313211 5 0.3634 0.5191 0.000 0.356 0.000 0.000 0.644 0.000
#> SRR1313212 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.1267 0.8843 0.000 0.060 0.000 0.000 0.940 0.000
#> SRR1313215 5 0.0632 0.8870 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313213 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.1196 0.8882 0.008 0.040 0.000 0.000 0.952 0.000
#> SRR1313217 5 0.0520 0.8833 0.000 0.008 0.008 0.000 0.984 0.000
#> SRR1313219 5 0.0603 0.8853 0.004 0.016 0.000 0.000 0.980 0.000
#> SRR1313220 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.2793 0.7319 0.000 0.800 0.000 0.000 0.200 0.000
#> SRR1313222 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 5 0.1610 0.8752 0.000 0.084 0.000 0.000 0.916 0.000
#> SRR1313226 5 0.0363 0.8798 0.000 0.000 0.012 0.000 0.988 0.000
#> SRR1313227 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9726 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "hclust"]
# you can also extract it by
# res = res_list["CV:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.414 0.846 0.907 0.4717 0.508 0.508
#> 3 3 0.565 0.719 0.832 0.3515 0.827 0.666
#> 4 4 0.575 0.550 0.716 0.1193 0.846 0.604
#> 5 5 0.686 0.735 0.801 0.0893 0.874 0.584
#> 6 6 0.698 0.700 0.799 0.0163 0.998 0.990
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.8705 1.000 0.000
#> SRR1313063 1 0.0672 0.8718 0.992 0.008
#> SRR1313064 1 0.0000 0.8705 1.000 0.000
#> SRR1313065 1 0.0000 0.8705 1.000 0.000
#> SRR1313066 1 0.0000 0.8705 1.000 0.000
#> SRR1313067 1 0.0000 0.8705 1.000 0.000
#> SRR1313068 1 0.0672 0.8718 0.992 0.008
#> SRR1313069 1 0.0000 0.8705 1.000 0.000
#> SRR1313070 1 0.0000 0.8705 1.000 0.000
#> SRR1313071 1 0.0000 0.8705 1.000 0.000
#> SRR1313072 1 0.0000 0.8705 1.000 0.000
#> SRR1313073 1 0.0000 0.8705 1.000 0.000
#> SRR1313074 1 0.0000 0.8705 1.000 0.000
#> SRR1313075 1 0.0000 0.8705 1.000 0.000
#> SRR1313076 1 0.0000 0.8705 1.000 0.000
#> SRR1313077 1 0.0000 0.8705 1.000 0.000
#> SRR1313078 1 0.0000 0.8705 1.000 0.000
#> SRR1313079 1 0.0000 0.8705 1.000 0.000
#> SRR1313080 1 0.0672 0.8718 0.992 0.008
#> SRR1313081 1 0.0000 0.8705 1.000 0.000
#> SRR1313082 1 0.0000 0.8705 1.000 0.000
#> SRR1313083 1 0.0376 0.8717 0.996 0.004
#> SRR1313084 1 0.0000 0.8705 1.000 0.000
#> SRR1313085 1 0.0000 0.8705 1.000 0.000
#> SRR1313086 1 0.0000 0.8705 1.000 0.000
#> SRR1313087 1 0.0000 0.8705 1.000 0.000
#> SRR1313088 1 0.0000 0.8705 1.000 0.000
#> SRR1313089 1 0.0000 0.8705 1.000 0.000
#> SRR1313092 1 0.6148 0.8518 0.848 0.152
#> SRR1313090 1 0.5737 0.8611 0.864 0.136
#> SRR1313091 2 0.7139 0.7273 0.196 0.804
#> SRR1313093 1 0.5629 0.8607 0.868 0.132
#> SRR1313095 1 0.5178 0.8700 0.884 0.116
#> SRR1313096 1 0.4298 0.8781 0.912 0.088
#> SRR1313094 1 0.7139 0.8168 0.804 0.196
#> SRR1313097 2 0.9460 0.3350 0.364 0.636
#> SRR1313099 2 0.7219 0.7218 0.200 0.800
#> SRR1313098 1 0.3733 0.8835 0.928 0.072
#> SRR1313101 1 0.7219 0.8045 0.800 0.200
#> SRR1313102 1 0.6048 0.8555 0.852 0.148
#> SRR1313103 2 0.9427 0.3477 0.360 0.640
#> SRR1313100 1 0.4562 0.8777 0.904 0.096
#> SRR1313105 2 0.9993 -0.0787 0.484 0.516
#> SRR1313104 1 0.5737 0.8611 0.864 0.136
#> SRR1313107 2 0.9833 0.1108 0.424 0.576
#> SRR1313106 1 0.8443 0.6987 0.728 0.272
#> SRR1313109 2 0.7139 0.7273 0.196 0.804
#> SRR1313108 1 0.4939 0.8717 0.892 0.108
#> SRR1313111 1 0.9993 0.2098 0.516 0.484
#> SRR1313110 1 0.3733 0.8835 0.928 0.072
#> SRR1313112 1 0.6343 0.8455 0.840 0.160
#> SRR1313113 1 0.7745 0.7768 0.772 0.228
#> SRR1313115 1 0.5059 0.8698 0.888 0.112
#> SRR1313114 1 0.4690 0.8791 0.900 0.100
#> SRR1313117 1 0.6343 0.8446 0.840 0.160
#> SRR1313118 1 0.2778 0.8809 0.952 0.048
#> SRR1313116 2 0.1414 0.9188 0.020 0.980
#> SRR1313120 2 0.7219 0.7218 0.200 0.800
#> SRR1313119 1 0.5842 0.8588 0.860 0.140
#> SRR1313122 1 0.4815 0.8732 0.896 0.104
#> SRR1313124 1 0.5842 0.8588 0.860 0.140
#> SRR1313121 1 0.5737 0.8611 0.864 0.136
#> SRR1313125 1 0.6048 0.8555 0.852 0.148
#> SRR1313127 1 0.4431 0.8774 0.908 0.092
#> SRR1313123 1 0.6048 0.8555 0.852 0.148
#> SRR1313128 1 0.7219 0.8291 0.800 0.200
#> SRR1313126 1 0.4431 0.8774 0.908 0.092
#> SRR1313130 2 0.7139 0.7273 0.196 0.804
#> SRR1313132 2 0.7376 0.7118 0.208 0.792
#> SRR1313129 2 0.9460 0.3350 0.364 0.636
#> SRR1313133 1 0.7219 0.8315 0.800 0.200
#> SRR1313131 1 0.4562 0.8762 0.904 0.096
#> SRR1313134 1 0.4939 0.8832 0.892 0.108
#> SRR1313135 1 0.7602 0.8098 0.780 0.220
#> SRR1313136 1 0.6048 0.8643 0.852 0.148
#> SRR1313137 1 0.6048 0.8643 0.852 0.148
#> SRR1313138 1 0.7950 0.7890 0.760 0.240
#> SRR1313140 1 0.5629 0.8715 0.868 0.132
#> SRR1313141 1 0.4939 0.8770 0.892 0.108
#> SRR1313139 1 0.5737 0.8700 0.864 0.136
#> SRR1313143 1 0.4939 0.8770 0.892 0.108
#> SRR1313142 1 0.7376 0.8224 0.792 0.208
#> SRR1313144 1 0.7950 0.7890 0.760 0.240
#> SRR1313145 1 0.7528 0.8139 0.784 0.216
#> SRR1313146 1 0.7139 0.8327 0.804 0.196
#> SRR1313147 1 0.6887 0.8431 0.816 0.184
#> SRR1313150 1 0.6887 0.8456 0.816 0.184
#> SRR1313149 1 0.6887 0.8427 0.816 0.184
#> SRR1313152 1 0.7602 0.8098 0.780 0.220
#> SRR1313151 1 0.7139 0.8327 0.804 0.196
#> SRR1313154 1 0.7602 0.8098 0.780 0.220
#> SRR1313153 1 0.7950 0.7890 0.760 0.240
#> SRR1313156 1 0.8016 0.7860 0.756 0.244
#> SRR1313155 1 0.6048 0.8643 0.852 0.148
#> SRR1313157 1 0.6048 0.8643 0.852 0.148
#> SRR1313158 1 0.7528 0.8139 0.784 0.216
#> SRR1313161 1 0.6048 0.8643 0.852 0.148
#> SRR1313159 2 0.7376 0.7118 0.208 0.792
#> SRR1313160 1 0.6048 0.8643 0.852 0.148
#> SRR1313162 1 0.5294 0.8824 0.880 0.120
#> SRR1313163 1 0.7883 0.7944 0.764 0.236
#> SRR1313165 1 0.6973 0.8400 0.812 0.188
#> SRR1313166 1 0.7528 0.8139 0.784 0.216
#> SRR1313164 1 0.8267 0.7702 0.740 0.260
#> SRR1313167 1 0.5737 0.8693 0.864 0.136
#> SRR1313168 1 0.6887 0.8430 0.816 0.184
#> SRR1313170 2 0.7139 0.7281 0.196 0.804
#> SRR1313169 1 0.6048 0.8643 0.852 0.148
#> SRR1313172 2 0.7299 0.7155 0.204 0.796
#> SRR1313171 1 0.8267 0.7702 0.740 0.260
#> SRR1313174 2 0.0000 0.9256 0.000 1.000
#> SRR1313173 1 0.4161 0.8789 0.916 0.084
#> SRR1313176 2 0.0000 0.9256 0.000 1.000
#> SRR1313175 2 0.0672 0.9244 0.008 0.992
#> SRR1313178 2 0.0000 0.9256 0.000 1.000
#> SRR1313177 2 0.0000 0.9256 0.000 1.000
#> SRR1313179 2 0.4022 0.8664 0.080 0.920
#> SRR1313180 2 0.1414 0.9188 0.020 0.980
#> SRR1313181 2 0.0000 0.9256 0.000 1.000
#> SRR1313183 2 0.0000 0.9256 0.000 1.000
#> SRR1313182 2 0.0000 0.9256 0.000 1.000
#> SRR1313184 2 0.4022 0.8664 0.080 0.920
#> SRR1313185 2 0.0000 0.9256 0.000 1.000
#> SRR1313188 2 0.1414 0.9188 0.020 0.980
#> SRR1313187 2 0.1414 0.9188 0.020 0.980
#> SRR1313186 2 0.0376 0.9252 0.004 0.996
#> SRR1313189 2 0.0000 0.9256 0.000 1.000
#> SRR1313190 2 0.0000 0.9256 0.000 1.000
#> SRR1313191 2 0.0000 0.9256 0.000 1.000
#> SRR1313192 2 0.0000 0.9256 0.000 1.000
#> SRR1313193 2 0.0000 0.9256 0.000 1.000
#> SRR1313194 2 0.1184 0.9210 0.016 0.984
#> SRR1313195 2 0.1184 0.9210 0.016 0.984
#> SRR1313196 2 0.1414 0.9188 0.020 0.980
#> SRR1313197 2 0.0000 0.9256 0.000 1.000
#> SRR1313198 2 0.0376 0.9252 0.004 0.996
#> SRR1313199 2 0.0000 0.9256 0.000 1.000
#> SRR1313200 2 0.0938 0.9229 0.012 0.988
#> SRR1313201 2 0.0000 0.9256 0.000 1.000
#> SRR1313202 2 0.1184 0.9210 0.016 0.984
#> SRR1313203 2 0.0938 0.9211 0.012 0.988
#> SRR1313204 2 0.0000 0.9256 0.000 1.000
#> SRR1313205 2 0.0000 0.9256 0.000 1.000
#> SRR1313207 2 0.0000 0.9256 0.000 1.000
#> SRR1313208 2 0.0000 0.9256 0.000 1.000
#> SRR1313206 2 0.0000 0.9256 0.000 1.000
#> SRR1313210 2 0.0672 0.9244 0.008 0.992
#> SRR1313209 2 0.0000 0.9256 0.000 1.000
#> SRR1313211 2 0.0000 0.9256 0.000 1.000
#> SRR1313212 2 0.0000 0.9256 0.000 1.000
#> SRR1313214 2 0.0376 0.9252 0.004 0.996
#> SRR1313215 2 0.0938 0.9229 0.012 0.988
#> SRR1313213 2 0.0000 0.9256 0.000 1.000
#> SRR1313216 2 0.0672 0.9244 0.008 0.992
#> SRR1313217 2 0.0672 0.9244 0.008 0.992
#> SRR1313219 2 0.0672 0.9244 0.008 0.992
#> SRR1313220 2 0.0000 0.9256 0.000 1.000
#> SRR1313218 2 0.0000 0.9256 0.000 1.000
#> SRR1313222 2 0.0000 0.9256 0.000 1.000
#> SRR1313221 2 0.0000 0.9256 0.000 1.000
#> SRR1313223 2 0.0000 0.9256 0.000 1.000
#> SRR1313224 2 0.0000 0.9256 0.000 1.000
#> SRR1313225 2 0.0672 0.9244 0.008 0.992
#> SRR1313226 2 0.1414 0.9188 0.020 0.980
#> SRR1313227 2 0.0000 0.9256 0.000 1.000
#> SRR1313228 2 0.0000 0.9256 0.000 1.000
#> SRR1313229 2 0.0000 0.9256 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.3340 0.6908 0.120 0.000 0.880
#> SRR1313063 3 0.2537 0.7064 0.080 0.000 0.920
#> SRR1313064 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313065 3 0.6079 0.3656 0.388 0.000 0.612
#> SRR1313066 3 0.5905 0.4500 0.352 0.000 0.648
#> SRR1313067 3 0.3340 0.6908 0.120 0.000 0.880
#> SRR1313068 3 0.2356 0.7082 0.072 0.000 0.928
#> SRR1313069 3 0.6079 0.3657 0.388 0.000 0.612
#> SRR1313070 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313071 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313072 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313073 3 0.5529 0.5233 0.296 0.000 0.704
#> SRR1313074 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313075 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313076 3 0.3192 0.6980 0.112 0.000 0.888
#> SRR1313077 3 0.3340 0.6908 0.120 0.000 0.880
#> SRR1313078 3 0.3340 0.6908 0.120 0.000 0.880
#> SRR1313079 3 0.5905 0.4500 0.352 0.000 0.648
#> SRR1313080 3 0.2356 0.7082 0.072 0.000 0.928
#> SRR1313081 3 0.3267 0.6927 0.116 0.000 0.884
#> SRR1313082 3 0.5968 0.4154 0.364 0.000 0.636
#> SRR1313083 3 0.6154 0.3268 0.408 0.000 0.592
#> SRR1313084 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313085 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313086 3 0.6168 0.2984 0.412 0.000 0.588
#> SRR1313087 3 0.5882 0.4506 0.348 0.000 0.652
#> SRR1313088 3 0.6079 0.3657 0.388 0.000 0.612
#> SRR1313089 3 0.5905 0.4500 0.352 0.000 0.648
#> SRR1313092 3 0.3369 0.7030 0.052 0.040 0.908
#> SRR1313090 3 0.2903 0.7116 0.048 0.028 0.924
#> SRR1313091 2 0.8266 0.6590 0.136 0.624 0.240
#> SRR1313093 3 0.2806 0.7117 0.040 0.032 0.928
#> SRR1313095 3 0.2492 0.7158 0.048 0.016 0.936
#> SRR1313096 3 0.3091 0.7214 0.072 0.016 0.912
#> SRR1313094 3 0.4458 0.6659 0.056 0.080 0.864
#> SRR1313097 2 0.9140 0.3161 0.144 0.452 0.404
#> SRR1313099 2 0.8374 0.6481 0.144 0.616 0.240
#> SRR1313098 3 0.5366 0.6525 0.208 0.016 0.776
#> SRR1313101 3 0.4527 0.6654 0.052 0.088 0.860
#> SRR1313102 3 0.3263 0.7065 0.048 0.040 0.912
#> SRR1313103 2 0.9136 0.3270 0.144 0.456 0.400
#> SRR1313100 3 0.3445 0.7214 0.088 0.016 0.896
#> SRR1313105 3 0.8439 0.0700 0.096 0.368 0.536
#> SRR1313104 3 0.2903 0.7116 0.048 0.028 0.924
#> SRR1313107 3 0.9118 -0.1426 0.144 0.388 0.468
#> SRR1313106 3 0.5777 0.5834 0.052 0.160 0.788
#> SRR1313109 2 0.8266 0.6590 0.136 0.624 0.240
#> SRR1313108 3 0.2492 0.7173 0.048 0.016 0.936
#> SRR1313111 3 0.8395 0.1822 0.104 0.328 0.568
#> SRR1313110 3 0.5366 0.6525 0.208 0.016 0.776
#> SRR1313112 3 0.3589 0.6990 0.052 0.048 0.900
#> SRR1313113 3 0.5166 0.6313 0.056 0.116 0.828
#> SRR1313115 3 0.2383 0.7159 0.044 0.016 0.940
#> SRR1313114 3 0.3415 0.7203 0.080 0.020 0.900
#> SRR1313117 3 0.3589 0.6981 0.052 0.048 0.900
#> SRR1313118 3 0.4261 0.7070 0.140 0.012 0.848
#> SRR1313116 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313120 2 0.8374 0.6481 0.144 0.616 0.240
#> SRR1313119 3 0.3028 0.7102 0.048 0.032 0.920
#> SRR1313122 3 0.2703 0.7191 0.056 0.016 0.928
#> SRR1313124 3 0.3028 0.7102 0.048 0.032 0.920
#> SRR1313121 3 0.2903 0.7116 0.048 0.028 0.924
#> SRR1313125 3 0.3263 0.7065 0.048 0.040 0.912
#> SRR1313127 3 0.3528 0.7206 0.092 0.016 0.892
#> SRR1313123 3 0.3263 0.7065 0.048 0.040 0.912
#> SRR1313128 1 0.3412 0.8545 0.876 0.000 0.124
#> SRR1313126 3 0.3528 0.7206 0.092 0.016 0.892
#> SRR1313130 2 0.8266 0.6590 0.136 0.624 0.240
#> SRR1313132 2 0.8384 0.4790 0.392 0.520 0.088
#> SRR1313129 2 0.9140 0.3161 0.144 0.452 0.404
#> SRR1313133 1 0.3038 0.8559 0.896 0.000 0.104
#> SRR1313131 3 0.3445 0.7212 0.088 0.016 0.896
#> SRR1313134 3 0.6823 0.0913 0.484 0.012 0.504
#> SRR1313135 1 0.2711 0.8604 0.912 0.000 0.088
#> SRR1313136 1 0.4178 0.8320 0.828 0.000 0.172
#> SRR1313137 1 0.4121 0.8337 0.832 0.000 0.168
#> SRR1313138 1 0.1129 0.8206 0.976 0.004 0.020
#> SRR1313140 1 0.4931 0.7708 0.768 0.000 0.232
#> SRR1313141 1 0.5882 0.5394 0.652 0.000 0.348
#> SRR1313139 1 0.4750 0.7937 0.784 0.000 0.216
#> SRR1313143 1 0.5882 0.5394 0.652 0.000 0.348
#> SRR1313142 1 0.3038 0.8571 0.896 0.000 0.104
#> SRR1313144 1 0.1129 0.8206 0.976 0.004 0.020
#> SRR1313145 1 0.2537 0.8594 0.920 0.000 0.080
#> SRR1313146 1 0.3551 0.8563 0.868 0.000 0.132
#> SRR1313147 1 0.3482 0.8583 0.872 0.000 0.128
#> SRR1313150 1 0.2356 0.8495 0.928 0.000 0.072
#> SRR1313149 1 0.4974 0.7559 0.764 0.000 0.236
#> SRR1313152 1 0.2448 0.8583 0.924 0.000 0.076
#> SRR1313151 1 0.3551 0.8563 0.868 0.000 0.132
#> SRR1313154 1 0.1643 0.8398 0.956 0.000 0.044
#> SRR1313153 1 0.1129 0.8206 0.976 0.004 0.020
#> SRR1313156 1 0.1267 0.8186 0.972 0.004 0.024
#> SRR1313155 1 0.4750 0.7917 0.784 0.000 0.216
#> SRR1313157 1 0.4750 0.7917 0.784 0.000 0.216
#> SRR1313158 1 0.2537 0.8594 0.920 0.000 0.080
#> SRR1313161 1 0.4931 0.7707 0.768 0.000 0.232
#> SRR1313159 2 0.8384 0.4790 0.392 0.520 0.088
#> SRR1313160 1 0.4842 0.7818 0.776 0.000 0.224
#> SRR1313162 3 0.6498 0.3136 0.396 0.008 0.596
#> SRR1313163 1 0.1399 0.8272 0.968 0.004 0.028
#> SRR1313165 1 0.3267 0.8603 0.884 0.000 0.116
#> SRR1313166 1 0.2711 0.8609 0.912 0.000 0.088
#> SRR1313164 1 0.2773 0.8046 0.928 0.024 0.048
#> SRR1313167 1 0.5363 0.6981 0.724 0.000 0.276
#> SRR1313168 1 0.3412 0.8582 0.876 0.000 0.124
#> SRR1313170 2 0.8346 0.5374 0.360 0.548 0.092
#> SRR1313169 1 0.5058 0.7546 0.756 0.000 0.244
#> SRR1313172 2 0.8355 0.6446 0.140 0.616 0.244
#> SRR1313171 1 0.2773 0.8046 0.928 0.024 0.048
#> SRR1313174 2 0.2680 0.8856 0.068 0.924 0.008
#> SRR1313173 3 0.3183 0.7216 0.076 0.016 0.908
#> SRR1313176 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313175 2 0.3183 0.8837 0.076 0.908 0.016
#> SRR1313178 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313177 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313179 2 0.7545 0.6941 0.272 0.652 0.076
#> SRR1313180 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313181 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313183 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313182 2 0.2680 0.8856 0.068 0.924 0.008
#> SRR1313184 2 0.7545 0.6941 0.272 0.652 0.076
#> SRR1313185 2 0.2774 0.8851 0.072 0.920 0.008
#> SRR1313188 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313187 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313186 2 0.2939 0.8851 0.072 0.916 0.012
#> SRR1313189 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313190 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313191 2 0.2680 0.8856 0.068 0.924 0.008
#> SRR1313192 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313193 2 0.0424 0.8778 0.008 0.992 0.000
#> SRR1313194 2 0.3995 0.8690 0.116 0.868 0.016
#> SRR1313195 2 0.3995 0.8690 0.116 0.868 0.016
#> SRR1313196 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313197 2 0.2680 0.8856 0.068 0.924 0.008
#> SRR1313198 2 0.3031 0.8843 0.076 0.912 0.012
#> SRR1313199 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313200 2 0.3921 0.8709 0.112 0.872 0.016
#> SRR1313201 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313202 2 0.3769 0.8746 0.104 0.880 0.016
#> SRR1313203 2 0.2550 0.8564 0.012 0.932 0.056
#> SRR1313204 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313205 2 0.1860 0.8843 0.052 0.948 0.000
#> SRR1313207 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313208 2 0.1860 0.8843 0.052 0.948 0.000
#> SRR1313206 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313210 2 0.3091 0.8848 0.072 0.912 0.016
#> SRR1313209 2 0.2680 0.8856 0.068 0.924 0.008
#> SRR1313211 2 0.2400 0.8856 0.064 0.932 0.004
#> SRR1313212 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313214 2 0.3031 0.8843 0.076 0.912 0.012
#> SRR1313215 2 0.3769 0.8745 0.104 0.880 0.016
#> SRR1313213 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313216 2 0.3091 0.8845 0.072 0.912 0.016
#> SRR1313217 2 0.3183 0.8837 0.076 0.908 0.016
#> SRR1313219 2 0.3183 0.8837 0.076 0.908 0.016
#> SRR1313220 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313218 2 0.2486 0.8860 0.060 0.932 0.008
#> SRR1313222 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313221 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313223 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313224 2 0.2486 0.8860 0.060 0.932 0.008
#> SRR1313225 2 0.2902 0.8859 0.064 0.920 0.016
#> SRR1313226 2 0.4136 0.8679 0.116 0.864 0.020
#> SRR1313227 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313228 2 0.0237 0.8772 0.004 0.996 0.000
#> SRR1313229 2 0.0237 0.8772 0.004 0.996 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 3 0.4088 0.621716 0.004 0.000 0.764 0.232
#> SRR1313063 3 0.3710 0.670878 0.004 0.000 0.804 0.192
#> SRR1313064 4 0.3942 0.607725 0.000 0.000 0.236 0.764
#> SRR1313065 4 0.5397 0.604546 0.064 0.000 0.220 0.716
#> SRR1313066 4 0.4122 0.604446 0.004 0.000 0.236 0.760
#> SRR1313067 3 0.4088 0.621716 0.004 0.000 0.764 0.232
#> SRR1313068 3 0.3626 0.679261 0.004 0.000 0.812 0.184
#> SRR1313069 4 0.5466 0.603193 0.068 0.000 0.220 0.712
#> SRR1313070 4 0.4122 0.609637 0.004 0.000 0.236 0.760
#> SRR1313071 4 0.4122 0.609637 0.004 0.000 0.236 0.760
#> SRR1313072 4 0.3942 0.607725 0.000 0.000 0.236 0.764
#> SRR1313073 4 0.4746 0.391814 0.000 0.000 0.368 0.632
#> SRR1313074 4 0.3942 0.607725 0.000 0.000 0.236 0.764
#> SRR1313075 4 0.3942 0.607725 0.000 0.000 0.236 0.764
#> SRR1313076 3 0.3402 0.691002 0.004 0.000 0.832 0.164
#> SRR1313077 3 0.4088 0.621716 0.004 0.000 0.764 0.232
#> SRR1313078 3 0.4088 0.621716 0.004 0.000 0.764 0.232
#> SRR1313079 4 0.4155 0.600308 0.004 0.000 0.240 0.756
#> SRR1313080 3 0.3626 0.679261 0.004 0.000 0.812 0.184
#> SRR1313081 3 0.4053 0.626398 0.004 0.000 0.768 0.228
#> SRR1313082 4 0.4922 0.615286 0.036 0.000 0.228 0.736
#> SRR1313083 4 0.5184 0.596882 0.060 0.000 0.204 0.736
#> SRR1313084 4 0.3942 0.607725 0.000 0.000 0.236 0.764
#> SRR1313085 4 0.4122 0.609637 0.004 0.000 0.236 0.760
#> SRR1313086 4 0.5620 0.587062 0.084 0.000 0.208 0.708
#> SRR1313087 4 0.4040 0.596195 0.000 0.000 0.248 0.752
#> SRR1313088 4 0.5466 0.603193 0.068 0.000 0.220 0.712
#> SRR1313089 4 0.4122 0.604446 0.004 0.000 0.236 0.760
#> SRR1313092 3 0.1118 0.783234 0.036 0.000 0.964 0.000
#> SRR1313090 3 0.0804 0.787858 0.012 0.008 0.980 0.000
#> SRR1313091 2 0.7831 0.467084 0.312 0.408 0.280 0.000
#> SRR1313093 3 0.0895 0.787077 0.020 0.000 0.976 0.004
#> SRR1313095 3 0.0937 0.786315 0.012 0.000 0.976 0.012
#> SRR1313096 3 0.1209 0.779575 0.004 0.000 0.964 0.032
#> SRR1313094 3 0.2300 0.760649 0.064 0.016 0.920 0.000
#> SRR1313097 3 0.7707 -0.016672 0.276 0.272 0.452 0.000
#> SRR1313099 2 0.7844 0.455500 0.308 0.404 0.288 0.000
#> SRR1313098 3 0.4483 0.671495 0.104 0.000 0.808 0.088
#> SRR1313101 3 0.2494 0.759163 0.048 0.036 0.916 0.000
#> SRR1313102 3 0.1174 0.786802 0.020 0.012 0.968 0.000
#> SRR1313103 3 0.7721 -0.031963 0.276 0.276 0.448 0.000
#> SRR1313100 3 0.1576 0.774109 0.004 0.000 0.948 0.048
#> SRR1313105 3 0.6975 0.348604 0.216 0.200 0.584 0.000
#> SRR1313104 3 0.0804 0.787858 0.012 0.008 0.980 0.000
#> SRR1313107 3 0.7533 0.211368 0.272 0.208 0.516 0.004
#> SRR1313106 3 0.3903 0.698946 0.076 0.080 0.844 0.000
#> SRR1313109 2 0.7831 0.467084 0.312 0.408 0.280 0.000
#> SRR1313108 3 0.0524 0.785050 0.004 0.000 0.988 0.008
#> SRR1313111 3 0.6675 0.426150 0.228 0.156 0.616 0.000
#> SRR1313110 3 0.4483 0.671495 0.104 0.000 0.808 0.088
#> SRR1313112 3 0.1488 0.781900 0.032 0.012 0.956 0.000
#> SRR1313113 3 0.3156 0.736207 0.068 0.048 0.884 0.000
#> SRR1313115 3 0.0188 0.785161 0.000 0.000 0.996 0.004
#> SRR1313114 3 0.1543 0.782608 0.008 0.004 0.956 0.032
#> SRR1313117 3 0.1452 0.780566 0.036 0.008 0.956 0.000
#> SRR1313118 3 0.3489 0.728721 0.012 0.008 0.856 0.124
#> SRR1313116 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313120 2 0.7844 0.455500 0.308 0.404 0.288 0.000
#> SRR1313119 3 0.0927 0.787516 0.016 0.008 0.976 0.000
#> SRR1313122 3 0.0779 0.783602 0.004 0.000 0.980 0.016
#> SRR1313124 3 0.0927 0.787516 0.016 0.008 0.976 0.000
#> SRR1313121 3 0.0804 0.787858 0.012 0.008 0.980 0.000
#> SRR1313125 3 0.1174 0.786802 0.020 0.012 0.968 0.000
#> SRR1313127 3 0.1474 0.769782 0.000 0.000 0.948 0.052
#> SRR1313123 3 0.1174 0.786802 0.020 0.012 0.968 0.000
#> SRR1313128 1 0.6867 0.470345 0.508 0.000 0.108 0.384
#> SRR1313126 3 0.1557 0.768076 0.000 0.000 0.944 0.056
#> SRR1313130 2 0.7831 0.467084 0.312 0.408 0.280 0.000
#> SRR1313132 1 0.7745 -0.239736 0.540 0.316 0.084 0.060
#> SRR1313129 3 0.7707 -0.016672 0.276 0.272 0.452 0.000
#> SRR1313133 1 0.6626 0.523165 0.544 0.000 0.092 0.364
#> SRR1313131 3 0.1389 0.772425 0.000 0.000 0.952 0.048
#> SRR1313134 3 0.7468 -0.191268 0.228 0.000 0.504 0.268
#> SRR1313135 1 0.5764 0.513310 0.520 0.000 0.028 0.452
#> SRR1313136 4 0.6438 -0.350404 0.436 0.000 0.068 0.496
#> SRR1313137 4 0.6442 -0.355868 0.440 0.000 0.068 0.492
#> SRR1313138 1 0.5007 0.558243 0.636 0.000 0.008 0.356
#> SRR1313140 4 0.6980 -0.176957 0.400 0.000 0.116 0.484
#> SRR1313141 4 0.7620 0.119605 0.316 0.000 0.224 0.460
#> SRR1313139 4 0.6659 -0.235259 0.400 0.000 0.088 0.512
#> SRR1313143 4 0.7620 0.119605 0.316 0.000 0.224 0.460
#> SRR1313142 1 0.6658 0.500726 0.532 0.000 0.092 0.376
#> SRR1313144 1 0.4872 0.555664 0.640 0.000 0.004 0.356
#> SRR1313145 1 0.6000 0.522084 0.508 0.000 0.040 0.452
#> SRR1313146 1 0.6745 0.458427 0.480 0.000 0.092 0.428
#> SRR1313147 4 0.6081 -0.466936 0.472 0.000 0.044 0.484
#> SRR1313150 1 0.5856 0.522122 0.556 0.000 0.036 0.408
#> SRR1313149 1 0.7545 0.124332 0.416 0.000 0.188 0.396
#> SRR1313152 1 0.5755 0.526732 0.528 0.000 0.028 0.444
#> SRR1313151 1 0.6745 0.458427 0.480 0.000 0.092 0.428
#> SRR1313154 1 0.5872 0.560902 0.576 0.000 0.040 0.384
#> SRR1313153 1 0.4872 0.555664 0.640 0.000 0.004 0.356
#> SRR1313156 1 0.5110 0.557853 0.636 0.000 0.012 0.352
#> SRR1313155 4 0.6709 -0.197870 0.400 0.000 0.092 0.508
#> SRR1313157 4 0.6709 -0.197870 0.400 0.000 0.092 0.508
#> SRR1313158 1 0.6000 0.522084 0.508 0.000 0.040 0.452
#> SRR1313161 4 0.6718 -0.134668 0.380 0.000 0.096 0.524
#> SRR1313159 1 0.7745 -0.239736 0.540 0.316 0.084 0.060
#> SRR1313160 4 0.6751 -0.170303 0.396 0.000 0.096 0.508
#> SRR1313162 3 0.6805 0.259143 0.260 0.000 0.592 0.148
#> SRR1313163 1 0.5085 0.555215 0.616 0.000 0.008 0.376
#> SRR1313165 1 0.6011 0.451410 0.484 0.000 0.040 0.476
#> SRR1313166 1 0.6005 0.513064 0.500 0.000 0.040 0.460
#> SRR1313164 1 0.6314 0.554860 0.596 0.008 0.056 0.340
#> SRR1313167 4 0.6894 -0.000839 0.344 0.000 0.120 0.536
#> SRR1313168 4 0.6011 -0.471680 0.476 0.000 0.040 0.484
#> SRR1313170 1 0.7890 -0.315636 0.508 0.344 0.088 0.060
#> SRR1313169 4 0.6757 -0.123244 0.376 0.000 0.100 0.524
#> SRR1313172 2 0.7989 0.453243 0.300 0.408 0.288 0.004
#> SRR1313171 1 0.6314 0.554860 0.596 0.008 0.056 0.340
#> SRR1313174 2 0.4795 0.776734 0.292 0.696 0.012 0.000
#> SRR1313173 3 0.1305 0.778164 0.004 0.000 0.960 0.036
#> SRR1313176 2 0.0376 0.763258 0.004 0.992 0.000 0.004
#> SRR1313175 2 0.5108 0.770914 0.308 0.672 0.020 0.000
#> SRR1313178 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313177 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313179 1 0.6495 -0.490294 0.492 0.436 0.072 0.000
#> SRR1313180 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313181 2 0.0524 0.761946 0.008 0.988 0.000 0.004
#> SRR1313183 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313182 2 0.4422 0.781263 0.256 0.736 0.008 0.000
#> SRR1313184 1 0.6495 -0.490294 0.492 0.436 0.072 0.000
#> SRR1313185 2 0.4820 0.777150 0.296 0.692 0.012 0.000
#> SRR1313188 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313187 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313186 2 0.4933 0.776501 0.296 0.688 0.016 0.000
#> SRR1313189 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313190 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313191 2 0.4744 0.778400 0.284 0.704 0.012 0.000
#> SRR1313192 2 0.0188 0.767056 0.004 0.996 0.000 0.000
#> SRR1313193 2 0.0707 0.771021 0.020 0.980 0.000 0.000
#> SRR1313194 2 0.5681 0.718649 0.404 0.568 0.028 0.000
#> SRR1313195 2 0.5681 0.718649 0.404 0.568 0.028 0.000
#> SRR1313196 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313197 2 0.4795 0.776734 0.292 0.696 0.012 0.000
#> SRR1313198 2 0.4980 0.773628 0.304 0.680 0.016 0.000
#> SRR1313199 2 0.0188 0.767244 0.004 0.996 0.000 0.000
#> SRR1313200 2 0.5671 0.721755 0.400 0.572 0.028 0.000
#> SRR1313201 2 0.0336 0.763950 0.008 0.992 0.000 0.000
#> SRR1313202 2 0.5571 0.727107 0.396 0.580 0.024 0.000
#> SRR1313203 2 0.4086 0.731479 0.080 0.840 0.076 0.004
#> SRR1313204 2 0.0188 0.767056 0.004 0.996 0.000 0.000
#> SRR1313205 2 0.2654 0.779652 0.108 0.888 0.004 0.000
#> SRR1313207 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313208 2 0.2654 0.779652 0.108 0.888 0.004 0.000
#> SRR1313206 2 0.0188 0.767056 0.004 0.996 0.000 0.000
#> SRR1313210 2 0.5152 0.768876 0.316 0.664 0.020 0.000
#> SRR1313209 2 0.4718 0.779102 0.280 0.708 0.012 0.000
#> SRR1313211 2 0.3768 0.784098 0.184 0.808 0.008 0.000
#> SRR1313212 2 0.0000 0.765975 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.4957 0.774832 0.300 0.684 0.016 0.000
#> SRR1313215 2 0.5465 0.731462 0.392 0.588 0.020 0.000
#> SRR1313213 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313216 2 0.5184 0.771661 0.304 0.672 0.024 0.000
#> SRR1313217 2 0.5213 0.763492 0.328 0.652 0.020 0.000
#> SRR1313219 2 0.5085 0.772302 0.304 0.676 0.020 0.000
#> SRR1313220 2 0.0000 0.765975 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.3972 0.784000 0.204 0.788 0.008 0.000
#> SRR1313222 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313221 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313223 2 0.0657 0.760722 0.012 0.984 0.000 0.004
#> SRR1313224 2 0.3351 0.782796 0.148 0.844 0.008 0.000
#> SRR1313225 2 0.4776 0.780476 0.272 0.712 0.016 0.000
#> SRR1313226 2 0.5766 0.716338 0.404 0.564 0.032 0.000
#> SRR1313227 2 0.0188 0.767244 0.004 0.996 0.000 0.000
#> SRR1313228 2 0.0188 0.767244 0.004 0.996 0.000 0.000
#> SRR1313229 2 0.0524 0.761946 0.008 0.988 0.000 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 3 0.3826 0.6846 0.008 0.000 0.752 0.236 0.004
#> SRR1313063 3 0.3578 0.7216 0.004 0.000 0.784 0.204 0.008
#> SRR1313064 4 0.0880 0.9242 0.032 0.000 0.000 0.968 0.000
#> SRR1313065 4 0.2732 0.8346 0.160 0.000 0.000 0.840 0.000
#> SRR1313066 4 0.0794 0.9217 0.028 0.000 0.000 0.972 0.000
#> SRR1313067 3 0.3826 0.6846 0.008 0.000 0.752 0.236 0.004
#> SRR1313068 3 0.3509 0.7290 0.004 0.000 0.792 0.196 0.008
#> SRR1313069 4 0.2891 0.8133 0.176 0.000 0.000 0.824 0.000
#> SRR1313070 4 0.1197 0.9225 0.048 0.000 0.000 0.952 0.000
#> SRR1313071 4 0.1270 0.9217 0.052 0.000 0.000 0.948 0.000
#> SRR1313072 4 0.0880 0.9242 0.032 0.000 0.000 0.968 0.000
#> SRR1313073 4 0.3655 0.7341 0.036 0.000 0.160 0.804 0.000
#> SRR1313074 4 0.0880 0.9242 0.032 0.000 0.000 0.968 0.000
#> SRR1313075 4 0.0880 0.9242 0.032 0.000 0.000 0.968 0.000
#> SRR1313076 3 0.3205 0.7429 0.004 0.000 0.816 0.176 0.004
#> SRR1313077 3 0.3826 0.6846 0.008 0.000 0.752 0.236 0.004
#> SRR1313078 3 0.3826 0.6846 0.008 0.000 0.752 0.236 0.004
#> SRR1313079 4 0.0955 0.9195 0.028 0.000 0.004 0.968 0.000
#> SRR1313080 3 0.3509 0.7290 0.004 0.000 0.792 0.196 0.008
#> SRR1313081 3 0.3797 0.6887 0.008 0.000 0.756 0.232 0.004
#> SRR1313082 4 0.1908 0.8974 0.092 0.000 0.000 0.908 0.000
#> SRR1313083 4 0.2690 0.8402 0.156 0.000 0.000 0.844 0.000
#> SRR1313084 4 0.0880 0.9242 0.032 0.000 0.000 0.968 0.000
#> SRR1313085 4 0.1270 0.9217 0.052 0.000 0.000 0.948 0.000
#> SRR1313086 4 0.2891 0.8084 0.176 0.000 0.000 0.824 0.000
#> SRR1313087 4 0.1281 0.9170 0.032 0.000 0.012 0.956 0.000
#> SRR1313088 4 0.2891 0.8133 0.176 0.000 0.000 0.824 0.000
#> SRR1313089 4 0.0794 0.9217 0.028 0.000 0.000 0.972 0.000
#> SRR1313092 3 0.1168 0.8212 0.008 0.000 0.960 0.000 0.032
#> SRR1313090 3 0.0798 0.8232 0.008 0.000 0.976 0.000 0.016
#> SRR1313091 5 0.6023 0.5719 0.008 0.128 0.276 0.000 0.588
#> SRR1313093 3 0.0771 0.8238 0.000 0.000 0.976 0.004 0.020
#> SRR1313095 3 0.0854 0.8230 0.004 0.000 0.976 0.012 0.008
#> SRR1313096 3 0.1412 0.8176 0.004 0.000 0.952 0.036 0.008
#> SRR1313094 3 0.2115 0.7995 0.008 0.008 0.916 0.000 0.068
#> SRR1313097 3 0.6316 -0.1773 0.008 0.120 0.448 0.000 0.424
#> SRR1313099 5 0.6021 0.5613 0.008 0.124 0.284 0.000 0.584
#> SRR1313098 3 0.4166 0.7346 0.144 0.000 0.792 0.052 0.012
#> SRR1313101 3 0.2017 0.7967 0.008 0.000 0.912 0.000 0.080
#> SRR1313102 3 0.1153 0.8227 0.008 0.004 0.964 0.000 0.024
#> SRR1313103 3 0.6318 -0.1905 0.008 0.120 0.444 0.000 0.428
#> SRR1313100 3 0.1408 0.8163 0.008 0.000 0.948 0.044 0.000
#> SRR1313105 3 0.5733 0.2776 0.008 0.080 0.580 0.000 0.332
#> SRR1313104 3 0.0798 0.8232 0.008 0.000 0.976 0.000 0.016
#> SRR1313107 3 0.6316 0.0614 0.008 0.112 0.512 0.004 0.364
#> SRR1313106 3 0.3124 0.7364 0.008 0.008 0.840 0.000 0.144
#> SRR1313109 5 0.6023 0.5719 0.008 0.128 0.276 0.000 0.588
#> SRR1313108 3 0.0693 0.8217 0.000 0.000 0.980 0.012 0.008
#> SRR1313111 3 0.5573 0.3535 0.008 0.076 0.612 0.000 0.304
#> SRR1313110 3 0.4166 0.7346 0.144 0.000 0.792 0.052 0.012
#> SRR1313112 3 0.1331 0.8197 0.008 0.000 0.952 0.000 0.040
#> SRR1313113 3 0.2642 0.7733 0.008 0.008 0.880 0.000 0.104
#> SRR1313115 3 0.0451 0.8217 0.000 0.000 0.988 0.008 0.004
#> SRR1313114 3 0.1603 0.8219 0.012 0.004 0.948 0.032 0.004
#> SRR1313117 3 0.1331 0.8187 0.008 0.000 0.952 0.000 0.040
#> SRR1313118 3 0.3163 0.7791 0.012 0.000 0.848 0.128 0.012
#> SRR1313116 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313120 5 0.6021 0.5613 0.008 0.124 0.284 0.000 0.584
#> SRR1313119 3 0.0898 0.8231 0.008 0.000 0.972 0.000 0.020
#> SRR1313122 3 0.0898 0.8209 0.000 0.000 0.972 0.020 0.008
#> SRR1313124 3 0.0898 0.8231 0.008 0.000 0.972 0.000 0.020
#> SRR1313121 3 0.0798 0.8232 0.008 0.000 0.976 0.000 0.016
#> SRR1313125 3 0.1153 0.8227 0.008 0.004 0.964 0.000 0.024
#> SRR1313127 3 0.1341 0.8126 0.000 0.000 0.944 0.056 0.000
#> SRR1313123 3 0.1153 0.8227 0.008 0.004 0.964 0.000 0.024
#> SRR1313128 1 0.3683 0.8064 0.828 0.000 0.072 0.096 0.004
#> SRR1313126 3 0.1410 0.8112 0.000 0.000 0.940 0.060 0.000
#> SRR1313130 5 0.6023 0.5719 0.008 0.128 0.276 0.000 0.588
#> SRR1313132 5 0.4374 0.5567 0.144 0.000 0.072 0.008 0.776
#> SRR1313129 3 0.6316 -0.1773 0.008 0.120 0.448 0.000 0.424
#> SRR1313133 1 0.1502 0.7994 0.940 0.000 0.056 0.004 0.000
#> SRR1313131 3 0.1270 0.8139 0.000 0.000 0.948 0.052 0.000
#> SRR1313134 3 0.6294 -0.1016 0.376 0.000 0.468 0.156 0.000
#> SRR1313135 1 0.3193 0.8339 0.852 0.000 0.004 0.112 0.032
#> SRR1313136 1 0.3318 0.8082 0.800 0.000 0.008 0.192 0.000
#> SRR1313137 1 0.3209 0.8137 0.812 0.000 0.008 0.180 0.000
#> SRR1313138 1 0.2280 0.7565 0.880 0.000 0.000 0.000 0.120
#> SRR1313140 1 0.4181 0.7356 0.712 0.000 0.020 0.268 0.000
#> SRR1313141 1 0.5905 0.5542 0.572 0.000 0.136 0.292 0.000
#> SRR1313139 1 0.3607 0.7754 0.752 0.000 0.004 0.244 0.000
#> SRR1313143 1 0.5905 0.5542 0.572 0.000 0.136 0.292 0.000
#> SRR1313142 1 0.3985 0.8127 0.828 0.000 0.064 0.072 0.036
#> SRR1313144 1 0.2516 0.7436 0.860 0.000 0.000 0.000 0.140
#> SRR1313145 1 0.2445 0.8343 0.884 0.000 0.004 0.108 0.004
#> SRR1313146 1 0.3359 0.8265 0.840 0.000 0.052 0.108 0.000
#> SRR1313147 1 0.3154 0.8305 0.836 0.000 0.004 0.148 0.012
#> SRR1313150 1 0.2075 0.8125 0.924 0.000 0.004 0.040 0.032
#> SRR1313149 1 0.5107 0.6991 0.688 0.000 0.108 0.204 0.000
#> SRR1313152 1 0.3117 0.8339 0.860 0.000 0.004 0.100 0.036
#> SRR1313151 1 0.3359 0.8265 0.840 0.000 0.052 0.108 0.000
#> SRR1313154 1 0.1059 0.8048 0.968 0.000 0.004 0.008 0.020
#> SRR1313153 1 0.2516 0.7436 0.860 0.000 0.000 0.000 0.140
#> SRR1313156 1 0.2439 0.7547 0.876 0.000 0.004 0.000 0.120
#> SRR1313155 1 0.3756 0.7677 0.744 0.000 0.008 0.248 0.000
#> SRR1313157 1 0.3756 0.7677 0.744 0.000 0.008 0.248 0.000
#> SRR1313158 1 0.2392 0.8332 0.888 0.000 0.004 0.104 0.004
#> SRR1313161 1 0.3957 0.7364 0.712 0.000 0.008 0.280 0.000
#> SRR1313159 5 0.4374 0.5567 0.144 0.000 0.072 0.008 0.776
#> SRR1313160 1 0.3835 0.7572 0.732 0.000 0.008 0.260 0.000
#> SRR1313162 3 0.5787 0.3791 0.344 0.000 0.580 0.040 0.036
#> SRR1313163 1 0.3507 0.7894 0.828 0.000 0.000 0.052 0.120
#> SRR1313165 1 0.2976 0.8324 0.852 0.000 0.004 0.132 0.012
#> SRR1313166 1 0.2445 0.8329 0.884 0.000 0.004 0.108 0.004
#> SRR1313164 1 0.2110 0.7789 0.912 0.000 0.016 0.000 0.072
#> SRR1313167 1 0.4268 0.6457 0.648 0.000 0.008 0.344 0.000
#> SRR1313168 1 0.3067 0.8311 0.844 0.000 0.004 0.140 0.012
#> SRR1313170 5 0.4926 0.5825 0.128 0.024 0.076 0.008 0.764
#> SRR1313169 1 0.4003 0.7259 0.704 0.000 0.008 0.288 0.000
#> SRR1313172 5 0.6245 0.5559 0.008 0.132 0.284 0.004 0.572
#> SRR1313171 1 0.2110 0.7789 0.912 0.000 0.016 0.000 0.072
#> SRR1313174 5 0.3999 0.6642 0.000 0.344 0.000 0.000 0.656
#> SRR1313173 3 0.1492 0.8167 0.004 0.000 0.948 0.040 0.008
#> SRR1313176 2 0.0290 0.9044 0.000 0.992 0.000 0.000 0.008
#> SRR1313175 5 0.3969 0.7049 0.000 0.304 0.004 0.000 0.692
#> SRR1313178 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 5 0.4639 0.5838 0.024 0.124 0.060 0.008 0.784
#> SRR1313180 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313181 2 0.0162 0.9044 0.000 0.996 0.000 0.000 0.004
#> SRR1313183 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 5 0.4291 0.4095 0.000 0.464 0.000 0.000 0.536
#> SRR1313184 5 0.4639 0.5838 0.024 0.124 0.060 0.008 0.784
#> SRR1313185 5 0.4238 0.6336 0.000 0.368 0.004 0.000 0.628
#> SRR1313188 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313187 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313186 5 0.4354 0.6335 0.000 0.368 0.008 0.000 0.624
#> SRR1313189 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 5 0.4030 0.6572 0.000 0.352 0.000 0.000 0.648
#> SRR1313192 2 0.0880 0.8999 0.000 0.968 0.000 0.000 0.032
#> SRR1313193 2 0.1410 0.8737 0.000 0.940 0.000 0.000 0.060
#> SRR1313194 5 0.3320 0.7583 0.004 0.164 0.012 0.000 0.820
#> SRR1313195 5 0.3320 0.7583 0.004 0.164 0.012 0.000 0.820
#> SRR1313196 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313197 5 0.3999 0.6642 0.000 0.344 0.000 0.000 0.656
#> SRR1313198 5 0.3966 0.6802 0.000 0.336 0.000 0.000 0.664
#> SRR1313199 2 0.0880 0.8998 0.000 0.968 0.000 0.000 0.032
#> SRR1313200 5 0.3360 0.7583 0.004 0.168 0.012 0.000 0.816
#> SRR1313201 2 0.0404 0.9041 0.000 0.988 0.000 0.000 0.012
#> SRR1313202 5 0.3171 0.7564 0.000 0.176 0.008 0.000 0.816
#> SRR1313203 2 0.4732 0.6400 0.000 0.744 0.068 0.012 0.176
#> SRR1313204 2 0.0880 0.8999 0.000 0.968 0.000 0.000 0.032
#> SRR1313205 2 0.2891 0.7220 0.000 0.824 0.000 0.000 0.176
#> SRR1313207 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.2891 0.7220 0.000 0.824 0.000 0.000 0.176
#> SRR1313206 2 0.0880 0.8999 0.000 0.968 0.000 0.000 0.032
#> SRR1313210 5 0.3949 0.7085 0.000 0.300 0.004 0.000 0.696
#> SRR1313209 5 0.4045 0.6533 0.000 0.356 0.000 0.000 0.644
#> SRR1313211 2 0.4182 0.0344 0.000 0.600 0.000 0.000 0.400
#> SRR1313212 2 0.0703 0.9026 0.000 0.976 0.000 0.000 0.024
#> SRR1313214 5 0.3999 0.6734 0.000 0.344 0.000 0.000 0.656
#> SRR1313215 5 0.3160 0.7538 0.000 0.188 0.004 0.000 0.808
#> SRR1313213 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.4088 0.7055 0.000 0.304 0.008 0.000 0.688
#> SRR1313217 5 0.3838 0.7197 0.000 0.280 0.004 0.000 0.716
#> SRR1313219 5 0.4009 0.6982 0.000 0.312 0.004 0.000 0.684
#> SRR1313220 2 0.0703 0.9026 0.000 0.976 0.000 0.000 0.024
#> SRR1313218 2 0.4182 0.0621 0.000 0.600 0.000 0.000 0.400
#> SRR1313222 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9038 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.3612 0.5185 0.000 0.732 0.000 0.000 0.268
#> SRR1313225 5 0.4238 0.6316 0.000 0.368 0.004 0.000 0.628
#> SRR1313226 5 0.3381 0.7585 0.004 0.160 0.016 0.000 0.820
#> SRR1313227 2 0.0880 0.8998 0.000 0.968 0.000 0.000 0.032
#> SRR1313228 2 0.0880 0.8998 0.000 0.968 0.000 0.000 0.032
#> SRR1313229 2 0.0162 0.9044 0.000 0.996 0.000 0.000 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 3 0.4565 0.6418 0.008 0.000 0.716 0.108 0.000 0.168
#> SRR1313063 3 0.4195 0.6744 0.008 0.000 0.756 0.100 0.000 0.136
#> SRR1313064 4 0.0146 0.8882 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313065 4 0.3130 0.7989 0.144 0.000 0.000 0.824 0.004 0.028
#> SRR1313066 4 0.0146 0.8878 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313067 3 0.4565 0.6418 0.008 0.000 0.716 0.108 0.000 0.168
#> SRR1313068 3 0.4103 0.6817 0.008 0.000 0.764 0.092 0.000 0.136
#> SRR1313069 4 0.3959 0.7369 0.172 0.000 0.000 0.760 0.004 0.064
#> SRR1313070 4 0.0777 0.8882 0.024 0.000 0.000 0.972 0.000 0.004
#> SRR1313071 4 0.0858 0.8877 0.028 0.000 0.000 0.968 0.000 0.004
#> SRR1313072 4 0.0000 0.8880 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.3728 0.6228 0.004 0.000 0.152 0.784 0.000 0.060
#> SRR1313074 4 0.0146 0.8882 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313075 4 0.0146 0.8882 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313076 3 0.3812 0.6920 0.008 0.000 0.776 0.036 0.004 0.176
#> SRR1313077 3 0.4565 0.6418 0.008 0.000 0.716 0.108 0.000 0.168
#> SRR1313078 3 0.4565 0.6418 0.008 0.000 0.716 0.108 0.000 0.168
#> SRR1313079 4 0.0603 0.8830 0.000 0.000 0.004 0.980 0.000 0.016
#> SRR1313080 3 0.4103 0.6817 0.008 0.000 0.764 0.092 0.000 0.136
#> SRR1313081 3 0.4522 0.6457 0.008 0.000 0.720 0.104 0.000 0.168
#> SRR1313082 4 0.1812 0.8594 0.080 0.000 0.000 0.912 0.000 0.008
#> SRR1313083 4 0.2909 0.8043 0.136 0.000 0.000 0.836 0.000 0.028
#> SRR1313084 4 0.0000 0.8880 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0858 0.8877 0.028 0.000 0.000 0.968 0.000 0.004
#> SRR1313086 4 0.3840 0.7540 0.152 0.000 0.000 0.776 0.004 0.068
#> SRR1313087 4 0.0993 0.8724 0.000 0.000 0.012 0.964 0.000 0.024
#> SRR1313088 4 0.3959 0.7369 0.172 0.000 0.000 0.760 0.004 0.064
#> SRR1313089 4 0.0260 0.8875 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313092 3 0.0972 0.7759 0.008 0.000 0.964 0.000 0.028 0.000
#> SRR1313090 3 0.0665 0.7796 0.008 0.000 0.980 0.000 0.008 0.004
#> SRR1313091 5 0.5418 0.4964 0.008 0.112 0.280 0.000 0.596 0.004
#> SRR1313093 3 0.0820 0.7814 0.000 0.000 0.972 0.000 0.016 0.012
#> SRR1313095 3 0.0692 0.7817 0.004 0.000 0.976 0.000 0.000 0.020
#> SRR1313096 3 0.1285 0.7742 0.004 0.000 0.944 0.000 0.000 0.052
#> SRR1313094 3 0.1841 0.7500 0.008 0.008 0.920 0.000 0.064 0.000
#> SRR1313097 3 0.5711 -0.1705 0.008 0.108 0.452 0.000 0.428 0.004
#> SRR1313099 5 0.5413 0.4882 0.008 0.108 0.288 0.000 0.592 0.004
#> SRR1313098 3 0.3808 0.6745 0.132 0.000 0.784 0.000 0.004 0.080
#> SRR1313101 3 0.1845 0.7488 0.008 0.000 0.916 0.000 0.072 0.004
#> SRR1313102 3 0.1007 0.7783 0.008 0.004 0.968 0.000 0.016 0.004
#> SRR1313103 3 0.5712 -0.1838 0.008 0.108 0.448 0.000 0.432 0.004
#> SRR1313100 3 0.1333 0.7768 0.008 0.000 0.944 0.000 0.000 0.048
#> SRR1313105 3 0.5192 0.2813 0.008 0.072 0.584 0.000 0.332 0.004
#> SRR1313104 3 0.0665 0.7796 0.008 0.000 0.980 0.000 0.008 0.004
#> SRR1313107 3 0.5731 0.0648 0.008 0.108 0.516 0.000 0.360 0.008
#> SRR1313106 3 0.2695 0.6815 0.008 0.000 0.844 0.000 0.144 0.004
#> SRR1313109 5 0.5418 0.4964 0.008 0.112 0.280 0.000 0.596 0.004
#> SRR1313108 3 0.0632 0.7799 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313111 3 0.5109 0.3507 0.008 0.076 0.616 0.000 0.296 0.004
#> SRR1313110 3 0.3808 0.6745 0.132 0.000 0.784 0.000 0.004 0.080
#> SRR1313112 3 0.1194 0.7739 0.008 0.000 0.956 0.000 0.032 0.004
#> SRR1313113 3 0.2418 0.7231 0.008 0.008 0.884 0.000 0.096 0.004
#> SRR1313115 3 0.0458 0.7800 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313114 3 0.1442 0.7804 0.012 0.004 0.944 0.000 0.000 0.040
#> SRR1313117 3 0.1194 0.7728 0.008 0.000 0.956 0.000 0.032 0.004
#> SRR1313118 3 0.3288 0.7350 0.016 0.000 0.824 0.016 0.004 0.140
#> SRR1313116 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313120 5 0.5413 0.4882 0.008 0.108 0.288 0.000 0.592 0.004
#> SRR1313119 3 0.0767 0.7792 0.008 0.000 0.976 0.000 0.012 0.004
#> SRR1313122 3 0.0713 0.7795 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313124 3 0.0767 0.7792 0.008 0.000 0.976 0.000 0.012 0.004
#> SRR1313121 3 0.0665 0.7796 0.008 0.000 0.980 0.000 0.008 0.004
#> SRR1313125 3 0.1007 0.7783 0.008 0.004 0.968 0.000 0.016 0.004
#> SRR1313127 3 0.1471 0.7701 0.000 0.000 0.932 0.004 0.000 0.064
#> SRR1313123 3 0.1007 0.7783 0.008 0.004 0.968 0.000 0.016 0.004
#> SRR1313128 1 0.3984 0.7956 0.804 0.000 0.068 0.088 0.004 0.036
#> SRR1313126 3 0.1531 0.7688 0.000 0.000 0.928 0.004 0.000 0.068
#> SRR1313130 5 0.5418 0.4964 0.008 0.112 0.280 0.000 0.596 0.004
#> SRR1313132 5 0.4467 0.3609 0.088 0.000 0.056 0.000 0.764 0.092
#> SRR1313129 3 0.5711 -0.1705 0.008 0.108 0.452 0.000 0.428 0.004
#> SRR1313133 1 0.2421 0.7711 0.896 0.000 0.052 0.004 0.004 0.044
#> SRR1313131 3 0.1387 0.7702 0.000 0.000 0.932 0.000 0.000 0.068
#> SRR1313134 3 0.6366 -0.1204 0.372 0.000 0.448 0.132 0.000 0.048
#> SRR1313135 1 0.3117 0.8227 0.848 0.000 0.000 0.100 0.032 0.020
#> SRR1313136 1 0.3610 0.7989 0.792 0.000 0.004 0.152 0.000 0.052
#> SRR1313137 1 0.3249 0.8110 0.824 0.000 0.004 0.128 0.000 0.044
#> SRR1313138 1 0.3285 0.7023 0.820 0.000 0.000 0.000 0.116 0.064
#> SRR1313140 1 0.4550 0.7428 0.704 0.000 0.016 0.220 0.000 0.060
#> SRR1313141 1 0.6419 0.5811 0.556 0.000 0.124 0.236 0.004 0.080
#> SRR1313139 1 0.3744 0.7758 0.756 0.000 0.000 0.200 0.000 0.044
#> SRR1313143 1 0.6419 0.5811 0.556 0.000 0.124 0.236 0.004 0.080
#> SRR1313142 1 0.4362 0.7952 0.796 0.000 0.060 0.068 0.036 0.040
#> SRR1313144 1 0.3570 0.6814 0.792 0.000 0.000 0.000 0.144 0.064
#> SRR1313145 1 0.2476 0.8256 0.880 0.000 0.000 0.092 0.004 0.024
#> SRR1313146 1 0.3389 0.8164 0.832 0.000 0.048 0.100 0.000 0.020
#> SRR1313147 1 0.3123 0.8235 0.840 0.000 0.000 0.116 0.012 0.032
#> SRR1313150 1 0.2628 0.7832 0.884 0.000 0.000 0.024 0.024 0.068
#> SRR1313149 1 0.5367 0.7026 0.672 0.000 0.100 0.172 0.000 0.056
#> SRR1313152 1 0.2883 0.8218 0.868 0.000 0.000 0.076 0.036 0.020
#> SRR1313151 1 0.3389 0.8164 0.832 0.000 0.048 0.100 0.000 0.020
#> SRR1313154 1 0.1769 0.7745 0.924 0.000 0.000 0.004 0.012 0.060
#> SRR1313153 1 0.3493 0.6851 0.800 0.000 0.000 0.000 0.136 0.064
#> SRR1313156 1 0.3426 0.6994 0.816 0.000 0.004 0.000 0.116 0.064
#> SRR1313155 1 0.4064 0.7644 0.740 0.000 0.004 0.200 0.000 0.056
#> SRR1313157 1 0.4064 0.7644 0.740 0.000 0.004 0.200 0.000 0.056
#> SRR1313158 1 0.2476 0.8252 0.880 0.000 0.000 0.092 0.004 0.024
#> SRR1313161 1 0.4361 0.7321 0.700 0.000 0.004 0.236 0.000 0.060
#> SRR1313159 5 0.4467 0.3609 0.088 0.000 0.056 0.000 0.764 0.092
#> SRR1313160 1 0.4206 0.7530 0.724 0.000 0.004 0.212 0.000 0.060
#> SRR1313162 3 0.5848 0.2804 0.288 0.000 0.560 0.000 0.032 0.120
#> SRR1313163 1 0.4077 0.7517 0.788 0.000 0.000 0.040 0.112 0.060
#> SRR1313165 1 0.2766 0.8259 0.868 0.000 0.000 0.092 0.012 0.028
#> SRR1313166 1 0.2527 0.8241 0.880 0.000 0.000 0.084 0.004 0.032
#> SRR1313164 1 0.2987 0.7289 0.856 0.000 0.008 0.000 0.056 0.080
#> SRR1313167 1 0.4688 0.6471 0.636 0.000 0.004 0.300 0.000 0.060
#> SRR1313168 1 0.2890 0.8257 0.860 0.000 0.000 0.096 0.012 0.032
#> SRR1313170 5 0.4925 0.4182 0.076 0.024 0.060 0.000 0.752 0.088
#> SRR1313169 1 0.4385 0.7254 0.696 0.000 0.004 0.240 0.000 0.060
#> SRR1313172 5 0.5590 0.4808 0.008 0.116 0.288 0.000 0.580 0.008
#> SRR1313171 1 0.2987 0.7289 0.856 0.000 0.008 0.000 0.056 0.080
#> SRR1313174 5 0.3499 0.6815 0.000 0.320 0.000 0.000 0.680 0.000
#> SRR1313173 3 0.1462 0.7723 0.008 0.000 0.936 0.000 0.000 0.056
#> SRR1313176 2 0.0260 0.8844 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313175 5 0.3448 0.7173 0.000 0.280 0.004 0.000 0.716 0.000
#> SRR1313178 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 5 0.4325 0.4389 0.000 0.124 0.044 0.000 0.768 0.064
#> SRR1313180 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313181 2 0.0146 0.8841 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313183 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 5 0.3838 0.4223 0.000 0.448 0.000 0.000 0.552 0.000
#> SRR1313184 5 0.4325 0.4389 0.000 0.124 0.044 0.000 0.768 0.064
#> SRR1313185 5 0.3728 0.6528 0.000 0.344 0.004 0.000 0.652 0.000
#> SRR1313188 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313187 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313186 5 0.3833 0.6526 0.000 0.344 0.008 0.000 0.648 0.000
#> SRR1313189 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.3531 0.6747 0.000 0.328 0.000 0.000 0.672 0.000
#> SRR1313192 2 0.0790 0.8810 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313193 2 0.1267 0.8517 0.000 0.940 0.000 0.000 0.060 0.000
#> SRR1313194 5 0.2755 0.7385 0.004 0.140 0.012 0.000 0.844 0.000
#> SRR1313195 5 0.2755 0.7385 0.004 0.140 0.012 0.000 0.844 0.000
#> SRR1313196 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313197 5 0.3499 0.6815 0.000 0.320 0.000 0.000 0.680 0.000
#> SRR1313198 5 0.3464 0.6941 0.000 0.312 0.000 0.000 0.688 0.000
#> SRR1313199 2 0.0865 0.8784 0.000 0.964 0.000 0.000 0.036 0.000
#> SRR1313200 5 0.2794 0.7394 0.004 0.144 0.012 0.000 0.840 0.000
#> SRR1313201 2 0.0363 0.8845 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313202 5 0.2631 0.7391 0.000 0.152 0.008 0.000 0.840 0.000
#> SRR1313203 6 0.5662 0.0000 0.000 0.204 0.068 0.000 0.092 0.636
#> SRR1313204 2 0.0790 0.8810 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313205 2 0.2697 0.6891 0.000 0.812 0.000 0.000 0.188 0.000
#> SRR1313207 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.2697 0.6891 0.000 0.812 0.000 0.000 0.188 0.000
#> SRR1313206 2 0.0790 0.8810 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313210 5 0.3426 0.7207 0.000 0.276 0.004 0.000 0.720 0.000
#> SRR1313209 5 0.3547 0.6709 0.000 0.332 0.000 0.000 0.668 0.000
#> SRR1313211 2 0.3804 -0.0321 0.000 0.576 0.000 0.000 0.424 0.000
#> SRR1313212 2 0.0632 0.8836 0.000 0.976 0.000 0.000 0.024 0.000
#> SRR1313214 5 0.3499 0.6878 0.000 0.320 0.000 0.000 0.680 0.000
#> SRR1313215 5 0.2632 0.7394 0.000 0.164 0.004 0.000 0.832 0.000
#> SRR1313213 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.3555 0.7180 0.000 0.280 0.008 0.000 0.712 0.000
#> SRR1313217 5 0.3314 0.7284 0.000 0.256 0.004 0.000 0.740 0.000
#> SRR1313219 5 0.3489 0.7111 0.000 0.288 0.004 0.000 0.708 0.000
#> SRR1313220 2 0.0632 0.8836 0.000 0.976 0.000 0.000 0.024 0.000
#> SRR1313218 2 0.3789 0.0306 0.000 0.584 0.000 0.000 0.416 0.000
#> SRR1313222 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.8829 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.3330 0.4941 0.000 0.716 0.000 0.000 0.284 0.000
#> SRR1313225 5 0.3728 0.6485 0.000 0.344 0.004 0.000 0.652 0.000
#> SRR1313226 5 0.2806 0.7376 0.004 0.136 0.016 0.000 0.844 0.000
#> SRR1313227 2 0.0865 0.8784 0.000 0.964 0.000 0.000 0.036 0.000
#> SRR1313228 2 0.0865 0.8784 0.000 0.964 0.000 0.000 0.036 0.000
#> SRR1313229 2 0.0146 0.8841 0.000 0.996 0.000 0.000 0.004 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "kmeans"]
# you can also extract it by
# res = res_list["CV:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.980 0.992 0.4597 0.540 0.540
#> 3 3 0.744 0.865 0.900 0.4312 0.759 0.566
#> 4 4 0.826 0.853 0.858 0.1168 0.898 0.704
#> 5 5 0.824 0.809 0.842 0.0689 0.934 0.751
#> 6 6 0.777 0.651 0.753 0.0386 0.972 0.868
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.994 1.000 0.000
#> SRR1313063 1 0.000 0.994 1.000 0.000
#> SRR1313064 1 0.000 0.994 1.000 0.000
#> SRR1313065 1 0.000 0.994 1.000 0.000
#> SRR1313066 1 0.000 0.994 1.000 0.000
#> SRR1313067 1 0.000 0.994 1.000 0.000
#> SRR1313068 1 0.000 0.994 1.000 0.000
#> SRR1313069 1 0.000 0.994 1.000 0.000
#> SRR1313070 1 0.000 0.994 1.000 0.000
#> SRR1313071 1 0.000 0.994 1.000 0.000
#> SRR1313072 1 0.000 0.994 1.000 0.000
#> SRR1313073 1 0.000 0.994 1.000 0.000
#> SRR1313074 1 0.000 0.994 1.000 0.000
#> SRR1313075 1 0.000 0.994 1.000 0.000
#> SRR1313076 1 0.000 0.994 1.000 0.000
#> SRR1313077 1 0.000 0.994 1.000 0.000
#> SRR1313078 1 0.000 0.994 1.000 0.000
#> SRR1313079 1 0.000 0.994 1.000 0.000
#> SRR1313080 1 0.000 0.994 1.000 0.000
#> SRR1313081 1 0.000 0.994 1.000 0.000
#> SRR1313082 1 0.000 0.994 1.000 0.000
#> SRR1313083 1 0.000 0.994 1.000 0.000
#> SRR1313084 1 0.000 0.994 1.000 0.000
#> SRR1313085 1 0.000 0.994 1.000 0.000
#> SRR1313086 1 0.000 0.994 1.000 0.000
#> SRR1313087 1 0.000 0.994 1.000 0.000
#> SRR1313088 1 0.000 0.994 1.000 0.000
#> SRR1313089 1 0.000 0.994 1.000 0.000
#> SRR1313092 1 0.000 0.994 1.000 0.000
#> SRR1313090 1 0.000 0.994 1.000 0.000
#> SRR1313091 2 0.000 0.988 0.000 1.000
#> SRR1313093 1 0.000 0.994 1.000 0.000
#> SRR1313095 1 0.000 0.994 1.000 0.000
#> SRR1313096 1 0.000 0.994 1.000 0.000
#> SRR1313094 1 0.000 0.994 1.000 0.000
#> SRR1313097 1 0.000 0.994 1.000 0.000
#> SRR1313099 1 0.242 0.954 0.960 0.040
#> SRR1313098 1 0.000 0.994 1.000 0.000
#> SRR1313101 1 0.000 0.994 1.000 0.000
#> SRR1313102 1 0.000 0.994 1.000 0.000
#> SRR1313103 1 0.000 0.994 1.000 0.000
#> SRR1313100 1 0.000 0.994 1.000 0.000
#> SRR1313105 1 0.000 0.994 1.000 0.000
#> SRR1313104 1 0.000 0.994 1.000 0.000
#> SRR1313107 1 0.000 0.994 1.000 0.000
#> SRR1313106 1 0.000 0.994 1.000 0.000
#> SRR1313109 2 0.518 0.869 0.116 0.884
#> SRR1313108 1 0.000 0.994 1.000 0.000
#> SRR1313111 1 0.000 0.994 1.000 0.000
#> SRR1313110 1 0.000 0.994 1.000 0.000
#> SRR1313112 1 0.000 0.994 1.000 0.000
#> SRR1313113 1 0.000 0.994 1.000 0.000
#> SRR1313115 1 0.000 0.994 1.000 0.000
#> SRR1313114 1 0.000 0.994 1.000 0.000
#> SRR1313117 1 0.000 0.994 1.000 0.000
#> SRR1313118 1 0.000 0.994 1.000 0.000
#> SRR1313116 1 0.327 0.933 0.940 0.060
#> SRR1313120 1 0.000 0.994 1.000 0.000
#> SRR1313119 1 0.000 0.994 1.000 0.000
#> SRR1313122 1 0.000 0.994 1.000 0.000
#> SRR1313124 1 0.000 0.994 1.000 0.000
#> SRR1313121 1 0.000 0.994 1.000 0.000
#> SRR1313125 1 0.000 0.994 1.000 0.000
#> SRR1313127 1 0.000 0.994 1.000 0.000
#> SRR1313123 1 0.000 0.994 1.000 0.000
#> SRR1313128 1 0.000 0.994 1.000 0.000
#> SRR1313126 1 0.000 0.994 1.000 0.000
#> SRR1313130 2 0.605 0.829 0.148 0.852
#> SRR1313132 1 0.000 0.994 1.000 0.000
#> SRR1313129 1 0.000 0.994 1.000 0.000
#> SRR1313133 1 0.000 0.994 1.000 0.000
#> SRR1313131 1 0.000 0.994 1.000 0.000
#> SRR1313134 1 0.000 0.994 1.000 0.000
#> SRR1313135 1 0.000 0.994 1.000 0.000
#> SRR1313136 1 0.000 0.994 1.000 0.000
#> SRR1313137 1 0.000 0.994 1.000 0.000
#> SRR1313138 1 0.000 0.994 1.000 0.000
#> SRR1313140 1 0.000 0.994 1.000 0.000
#> SRR1313141 1 0.000 0.994 1.000 0.000
#> SRR1313139 1 0.000 0.994 1.000 0.000
#> SRR1313143 1 0.000 0.994 1.000 0.000
#> SRR1313142 1 0.000 0.994 1.000 0.000
#> SRR1313144 1 0.000 0.994 1.000 0.000
#> SRR1313145 1 0.000 0.994 1.000 0.000
#> SRR1313146 1 0.000 0.994 1.000 0.000
#> SRR1313147 1 0.000 0.994 1.000 0.000
#> SRR1313150 1 0.000 0.994 1.000 0.000
#> SRR1313149 1 0.000 0.994 1.000 0.000
#> SRR1313152 1 0.000 0.994 1.000 0.000
#> SRR1313151 1 0.000 0.994 1.000 0.000
#> SRR1313154 1 0.000 0.994 1.000 0.000
#> SRR1313153 1 0.000 0.994 1.000 0.000
#> SRR1313156 1 0.000 0.994 1.000 0.000
#> SRR1313155 1 0.000 0.994 1.000 0.000
#> SRR1313157 1 0.000 0.994 1.000 0.000
#> SRR1313158 1 0.000 0.994 1.000 0.000
#> SRR1313161 1 0.000 0.994 1.000 0.000
#> SRR1313159 2 0.904 0.538 0.320 0.680
#> SRR1313160 1 0.000 0.994 1.000 0.000
#> SRR1313162 1 0.000 0.994 1.000 0.000
#> SRR1313163 1 0.000 0.994 1.000 0.000
#> SRR1313165 1 0.000 0.994 1.000 0.000
#> SRR1313166 1 0.000 0.994 1.000 0.000
#> SRR1313164 1 0.000 0.994 1.000 0.000
#> SRR1313167 1 0.000 0.994 1.000 0.000
#> SRR1313168 1 0.000 0.994 1.000 0.000
#> SRR1313170 1 0.242 0.954 0.960 0.040
#> SRR1313169 1 0.000 0.994 1.000 0.000
#> SRR1313172 1 0.995 0.126 0.540 0.460
#> SRR1313171 1 0.000 0.994 1.000 0.000
#> SRR1313174 2 0.000 0.988 0.000 1.000
#> SRR1313173 1 0.000 0.994 1.000 0.000
#> SRR1313176 2 0.000 0.988 0.000 1.000
#> SRR1313175 2 0.000 0.988 0.000 1.000
#> SRR1313178 2 0.000 0.988 0.000 1.000
#> SRR1313177 2 0.000 0.988 0.000 1.000
#> SRR1313179 2 0.000 0.988 0.000 1.000
#> SRR1313180 2 0.000 0.988 0.000 1.000
#> SRR1313181 2 0.000 0.988 0.000 1.000
#> SRR1313183 2 0.000 0.988 0.000 1.000
#> SRR1313182 2 0.000 0.988 0.000 1.000
#> SRR1313184 2 0.000 0.988 0.000 1.000
#> SRR1313185 2 0.000 0.988 0.000 1.000
#> SRR1313188 2 0.000 0.988 0.000 1.000
#> SRR1313187 2 0.000 0.988 0.000 1.000
#> SRR1313186 2 0.000 0.988 0.000 1.000
#> SRR1313189 2 0.000 0.988 0.000 1.000
#> SRR1313190 2 0.000 0.988 0.000 1.000
#> SRR1313191 2 0.000 0.988 0.000 1.000
#> SRR1313192 2 0.000 0.988 0.000 1.000
#> SRR1313193 2 0.000 0.988 0.000 1.000
#> SRR1313194 2 0.000 0.988 0.000 1.000
#> SRR1313195 2 0.000 0.988 0.000 1.000
#> SRR1313196 2 0.000 0.988 0.000 1.000
#> SRR1313197 2 0.000 0.988 0.000 1.000
#> SRR1313198 2 0.000 0.988 0.000 1.000
#> SRR1313199 2 0.000 0.988 0.000 1.000
#> SRR1313200 2 0.000 0.988 0.000 1.000
#> SRR1313201 2 0.000 0.988 0.000 1.000
#> SRR1313202 2 0.000 0.988 0.000 1.000
#> SRR1313203 1 0.184 0.967 0.972 0.028
#> SRR1313204 2 0.000 0.988 0.000 1.000
#> SRR1313205 2 0.000 0.988 0.000 1.000
#> SRR1313207 2 0.000 0.988 0.000 1.000
#> SRR1313208 2 0.000 0.988 0.000 1.000
#> SRR1313206 2 0.000 0.988 0.000 1.000
#> SRR1313210 2 0.000 0.988 0.000 1.000
#> SRR1313209 2 0.000 0.988 0.000 1.000
#> SRR1313211 2 0.000 0.988 0.000 1.000
#> SRR1313212 2 0.000 0.988 0.000 1.000
#> SRR1313214 2 0.000 0.988 0.000 1.000
#> SRR1313215 2 0.000 0.988 0.000 1.000
#> SRR1313213 2 0.000 0.988 0.000 1.000
#> SRR1313216 2 0.000 0.988 0.000 1.000
#> SRR1313217 2 0.000 0.988 0.000 1.000
#> SRR1313219 2 0.000 0.988 0.000 1.000
#> SRR1313220 2 0.000 0.988 0.000 1.000
#> SRR1313218 2 0.000 0.988 0.000 1.000
#> SRR1313222 2 0.000 0.988 0.000 1.000
#> SRR1313221 2 0.000 0.988 0.000 1.000
#> SRR1313223 2 0.000 0.988 0.000 1.000
#> SRR1313224 2 0.000 0.988 0.000 1.000
#> SRR1313225 2 0.000 0.988 0.000 1.000
#> SRR1313226 2 0.552 0.855 0.128 0.872
#> SRR1313227 2 0.000 0.988 0.000 1.000
#> SRR1313228 2 0.000 0.988 0.000 1.000
#> SRR1313229 2 0.000 0.988 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.6062 0.556 0.384 0.000 0.616
#> SRR1313063 3 0.6062 0.556 0.384 0.000 0.616
#> SRR1313064 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313065 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313066 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313067 3 0.5948 0.589 0.360 0.000 0.640
#> SRR1313068 3 0.5859 0.607 0.344 0.000 0.656
#> SRR1313069 1 0.0892 0.800 0.980 0.000 0.020
#> SRR1313070 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313071 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313072 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313073 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313074 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313075 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313076 3 0.5948 0.589 0.360 0.000 0.640
#> SRR1313077 3 0.6062 0.556 0.384 0.000 0.616
#> SRR1313078 3 0.6062 0.556 0.384 0.000 0.616
#> SRR1313079 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313080 3 0.5905 0.599 0.352 0.000 0.648
#> SRR1313081 3 0.6062 0.556 0.384 0.000 0.616
#> SRR1313082 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313083 1 0.0892 0.800 0.980 0.000 0.020
#> SRR1313084 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313085 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313086 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313087 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313088 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313089 1 0.1163 0.801 0.972 0.000 0.028
#> SRR1313092 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313090 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313091 2 0.4605 0.774 0.000 0.796 0.204
#> SRR1313093 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313095 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313096 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313094 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313097 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313099 3 0.1525 0.894 0.032 0.004 0.964
#> SRR1313098 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313101 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313102 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313103 3 0.1411 0.892 0.036 0.000 0.964
#> SRR1313100 3 0.1163 0.903 0.028 0.000 0.972
#> SRR1313105 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313104 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313107 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313106 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313109 3 0.1163 0.864 0.000 0.028 0.972
#> SRR1313108 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313111 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313110 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313112 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313113 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313115 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313114 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313117 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313118 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313116 3 0.0747 0.875 0.000 0.016 0.984
#> SRR1313120 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313119 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313122 3 0.1163 0.903 0.028 0.000 0.972
#> SRR1313124 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313121 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313125 3 0.0892 0.904 0.020 0.000 0.980
#> SRR1313127 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313123 3 0.1031 0.905 0.024 0.000 0.976
#> SRR1313128 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313126 3 0.2448 0.868 0.076 0.000 0.924
#> SRR1313130 3 0.5327 0.572 0.000 0.272 0.728
#> SRR1313132 1 0.5706 0.732 0.680 0.000 0.320
#> SRR1313129 3 0.1267 0.900 0.024 0.004 0.972
#> SRR1313133 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313131 3 0.1411 0.899 0.036 0.000 0.964
#> SRR1313134 1 0.4842 0.843 0.776 0.000 0.224
#> SRR1313135 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313136 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313137 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313138 1 0.5706 0.732 0.680 0.000 0.320
#> SRR1313140 1 0.0424 0.803 0.992 0.000 0.008
#> SRR1313141 1 0.4887 0.837 0.772 0.000 0.228
#> SRR1313139 1 0.1289 0.813 0.968 0.000 0.032
#> SRR1313143 1 0.2796 0.817 0.908 0.000 0.092
#> SRR1313142 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313144 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313145 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313146 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313147 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313150 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313149 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313152 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313151 1 0.4654 0.847 0.792 0.000 0.208
#> SRR1313154 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313153 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313156 1 0.5706 0.732 0.680 0.000 0.320
#> SRR1313155 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313157 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313158 1 0.5254 0.801 0.736 0.000 0.264
#> SRR1313161 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313159 1 0.9738 0.382 0.424 0.232 0.344
#> SRR1313160 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313162 1 0.5926 0.679 0.644 0.000 0.356
#> SRR1313163 1 0.5621 0.748 0.692 0.000 0.308
#> SRR1313165 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313166 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313164 1 0.5706 0.732 0.680 0.000 0.320
#> SRR1313167 1 0.1289 0.813 0.968 0.000 0.032
#> SRR1313168 1 0.4750 0.847 0.784 0.000 0.216
#> SRR1313170 3 0.1289 0.873 0.032 0.000 0.968
#> SRR1313169 1 0.4702 0.847 0.788 0.000 0.212
#> SRR1313172 3 0.1781 0.889 0.020 0.020 0.960
#> SRR1313171 1 0.5733 0.727 0.676 0.000 0.324
#> SRR1313174 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313173 3 0.1411 0.899 0.036 0.000 0.964
#> SRR1313176 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313175 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313178 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313179 2 0.5461 0.657 0.008 0.748 0.244
#> SRR1313180 2 0.1163 0.974 0.000 0.972 0.028
#> SRR1313181 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313182 2 0.0592 0.978 0.000 0.988 0.012
#> SRR1313184 2 0.5178 0.646 0.000 0.744 0.256
#> SRR1313185 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313188 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313187 2 0.1163 0.974 0.000 0.972 0.028
#> SRR1313186 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313189 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313191 2 0.0424 0.978 0.000 0.992 0.008
#> SRR1313192 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313194 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313195 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313196 2 0.1163 0.974 0.000 0.972 0.028
#> SRR1313197 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313198 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313199 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313200 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313201 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313202 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313203 3 0.2772 0.864 0.080 0.004 0.916
#> SRR1313204 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313210 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313209 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313211 2 0.0892 0.977 0.000 0.980 0.020
#> SRR1313212 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313214 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313215 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313213 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313216 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313217 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313219 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313220 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313218 2 0.0424 0.978 0.000 0.992 0.008
#> SRR1313222 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313225 2 0.1031 0.977 0.000 0.976 0.024
#> SRR1313226 3 0.5760 0.459 0.000 0.328 0.672
#> SRR1313227 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.978 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.978 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.5925 0.619 0.068 0.000 0.284 0.648
#> SRR1313063 4 0.6187 0.566 0.068 0.000 0.336 0.596
#> SRR1313064 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313065 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313066 4 0.4973 0.791 0.348 0.000 0.008 0.644
#> SRR1313067 4 0.6187 0.566 0.068 0.000 0.336 0.596
#> SRR1313068 4 0.6452 0.298 0.068 0.000 0.464 0.468
#> SRR1313069 4 0.5004 0.741 0.392 0.000 0.004 0.604
#> SRR1313070 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313071 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313072 4 0.4973 0.791 0.348 0.000 0.008 0.644
#> SRR1313073 4 0.4955 0.790 0.344 0.000 0.008 0.648
#> SRR1313074 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313075 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313076 4 0.6249 0.540 0.068 0.000 0.352 0.580
#> SRR1313077 4 0.6187 0.566 0.068 0.000 0.336 0.596
#> SRR1313078 4 0.6187 0.566 0.068 0.000 0.336 0.596
#> SRR1313079 4 0.4973 0.791 0.348 0.000 0.008 0.644
#> SRR1313080 4 0.6452 0.298 0.068 0.000 0.464 0.468
#> SRR1313081 4 0.5994 0.608 0.068 0.000 0.296 0.636
#> SRR1313082 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313083 4 0.4889 0.784 0.360 0.000 0.004 0.636
#> SRR1313084 4 0.4973 0.791 0.348 0.000 0.008 0.644
#> SRR1313085 4 0.5007 0.789 0.356 0.000 0.008 0.636
#> SRR1313086 4 0.4889 0.784 0.360 0.000 0.004 0.636
#> SRR1313087 4 0.4955 0.790 0.344 0.000 0.008 0.648
#> SRR1313088 4 0.4905 0.780 0.364 0.000 0.004 0.632
#> SRR1313089 4 0.4990 0.791 0.352 0.000 0.008 0.640
#> SRR1313092 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.5320 0.448 0.000 0.416 0.572 0.012
#> SRR1313093 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313096 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313094 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313099 3 0.0804 0.936 0.000 0.008 0.980 0.012
#> SRR1313098 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313101 3 0.0188 0.942 0.000 0.000 0.996 0.004
#> SRR1313102 3 0.0469 0.939 0.000 0.000 0.988 0.012
#> SRR1313103 3 0.0844 0.936 0.004 0.004 0.980 0.012
#> SRR1313100 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313105 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313104 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313106 3 0.0376 0.941 0.000 0.004 0.992 0.004
#> SRR1313109 3 0.4098 0.738 0.000 0.204 0.784 0.012
#> SRR1313108 3 0.0336 0.941 0.000 0.000 0.992 0.008
#> SRR1313111 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313110 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313112 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313115 3 0.0336 0.941 0.000 0.000 0.992 0.008
#> SRR1313114 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313117 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313116 3 0.5093 0.566 0.000 0.348 0.640 0.012
#> SRR1313120 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313119 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313124 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0188 0.942 0.000 0.000 0.996 0.004
#> SRR1313127 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313123 3 0.0000 0.943 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.1716 0.967 0.936 0.000 0.064 0.000
#> SRR1313126 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313130 3 0.4453 0.693 0.000 0.244 0.744 0.012
#> SRR1313132 1 0.2593 0.943 0.904 0.000 0.080 0.016
#> SRR1313129 3 0.0804 0.936 0.000 0.008 0.980 0.012
#> SRR1313133 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313131 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313134 1 0.1716 0.967 0.936 0.000 0.064 0.000
#> SRR1313135 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313136 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313137 1 0.1716 0.967 0.936 0.000 0.064 0.000
#> SRR1313138 1 0.2593 0.943 0.904 0.000 0.080 0.016
#> SRR1313140 1 0.0657 0.895 0.984 0.000 0.012 0.004
#> SRR1313141 1 0.1978 0.964 0.928 0.000 0.068 0.004
#> SRR1313139 1 0.0657 0.895 0.984 0.000 0.012 0.004
#> SRR1313143 1 0.2500 0.882 0.916 0.000 0.040 0.044
#> SRR1313142 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313144 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313145 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313146 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313147 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313150 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313149 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313152 1 0.1716 0.967 0.936 0.000 0.064 0.000
#> SRR1313151 1 0.1743 0.959 0.940 0.000 0.056 0.004
#> SRR1313154 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313153 1 0.1902 0.966 0.932 0.000 0.064 0.004
#> SRR1313156 1 0.2593 0.943 0.904 0.000 0.080 0.016
#> SRR1313155 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313157 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313158 1 0.2053 0.963 0.924 0.000 0.072 0.004
#> SRR1313161 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313159 1 0.6117 0.612 0.688 0.224 0.072 0.016
#> SRR1313160 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313162 1 0.3047 0.899 0.872 0.000 0.116 0.012
#> SRR1313163 1 0.2402 0.950 0.912 0.000 0.076 0.012
#> SRR1313165 1 0.1716 0.967 0.936 0.000 0.064 0.000
#> SRR1313166 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313164 1 0.2593 0.943 0.904 0.000 0.080 0.016
#> SRR1313167 1 0.0657 0.895 0.984 0.000 0.012 0.004
#> SRR1313168 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313170 3 0.4377 0.745 0.008 0.188 0.788 0.016
#> SRR1313169 1 0.1902 0.967 0.932 0.000 0.064 0.004
#> SRR1313172 3 0.0657 0.938 0.000 0.004 0.984 0.012
#> SRR1313171 1 0.2593 0.943 0.904 0.000 0.080 0.016
#> SRR1313174 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313173 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313176 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313175 2 0.0336 0.814 0.000 0.992 0.000 0.008
#> SRR1313178 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313177 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313179 2 0.5722 0.806 0.012 0.724 0.072 0.192
#> SRR1313180 2 0.1767 0.781 0.000 0.944 0.044 0.012
#> SRR1313181 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313183 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313182 2 0.3808 0.838 0.012 0.812 0.000 0.176
#> SRR1313184 2 0.6363 0.769 0.012 0.680 0.116 0.192
#> SRR1313185 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0804 0.808 0.000 0.980 0.008 0.012
#> SRR1313187 2 0.1767 0.781 0.000 0.944 0.044 0.012
#> SRR1313186 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313190 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313191 2 0.3105 0.836 0.004 0.856 0.000 0.140
#> SRR1313192 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313193 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313194 2 0.0524 0.813 0.000 0.988 0.004 0.008
#> SRR1313195 2 0.0524 0.813 0.000 0.988 0.004 0.008
#> SRR1313196 2 0.1767 0.781 0.000 0.944 0.044 0.012
#> SRR1313197 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313200 2 0.0524 0.813 0.000 0.988 0.004 0.008
#> SRR1313201 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313202 2 0.0657 0.810 0.000 0.984 0.004 0.012
#> SRR1313203 3 0.0469 0.940 0.000 0.000 0.988 0.012
#> SRR1313204 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313205 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313207 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313208 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313206 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313210 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0188 0.818 0.000 0.996 0.000 0.004
#> SRR1313212 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313214 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313216 2 0.0336 0.814 0.000 0.992 0.000 0.008
#> SRR1313217 2 0.0336 0.814 0.000 0.992 0.000 0.008
#> SRR1313219 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313218 2 0.3545 0.838 0.008 0.828 0.000 0.164
#> SRR1313222 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313221 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313223 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313224 2 0.4999 0.842 0.012 0.660 0.000 0.328
#> SRR1313225 2 0.0000 0.818 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.5093 0.566 0.000 0.348 0.640 0.012
#> SRR1313227 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313228 2 0.5038 0.842 0.012 0.652 0.000 0.336
#> SRR1313229 2 0.5038 0.842 0.012 0.652 0.000 0.336
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.4898 0.7140 0.000 0.000 0.068 0.684 0.248
#> SRR1313063 4 0.5447 0.6764 0.000 0.000 0.112 0.640 0.248
#> SRR1313064 4 0.1830 0.8584 0.068 0.000 0.000 0.924 0.008
#> SRR1313065 4 0.1851 0.8511 0.088 0.000 0.000 0.912 0.000
#> SRR1313066 4 0.1697 0.8592 0.060 0.000 0.000 0.932 0.008
#> SRR1313067 4 0.5612 0.6567 0.000 0.000 0.128 0.624 0.248
#> SRR1313068 4 0.6623 0.3254 0.000 0.000 0.300 0.452 0.248
#> SRR1313069 4 0.2471 0.8112 0.136 0.000 0.000 0.864 0.000
#> SRR1313070 4 0.1830 0.8582 0.068 0.000 0.000 0.924 0.008
#> SRR1313071 4 0.1830 0.8582 0.068 0.000 0.000 0.924 0.008
#> SRR1313072 4 0.1697 0.8592 0.060 0.000 0.000 0.932 0.008
#> SRR1313073 4 0.1862 0.8540 0.048 0.000 0.004 0.932 0.016
#> SRR1313074 4 0.1830 0.8584 0.068 0.000 0.000 0.924 0.008
#> SRR1313075 4 0.1830 0.8584 0.068 0.000 0.000 0.924 0.008
#> SRR1313076 4 0.5931 0.6058 0.000 0.000 0.164 0.588 0.248
#> SRR1313077 4 0.5447 0.6764 0.000 0.000 0.112 0.640 0.248
#> SRR1313078 4 0.5447 0.6764 0.000 0.000 0.112 0.640 0.248
#> SRR1313079 4 0.1697 0.8592 0.060 0.000 0.000 0.932 0.008
#> SRR1313080 4 0.6633 0.3143 0.000 0.000 0.304 0.448 0.248
#> SRR1313081 4 0.5010 0.7082 0.000 0.000 0.076 0.676 0.248
#> SRR1313082 4 0.1894 0.8573 0.072 0.000 0.000 0.920 0.008
#> SRR1313083 4 0.1894 0.8573 0.072 0.000 0.000 0.920 0.008
#> SRR1313084 4 0.1697 0.8592 0.060 0.000 0.000 0.932 0.008
#> SRR1313085 4 0.1830 0.8582 0.068 0.000 0.000 0.924 0.008
#> SRR1313086 4 0.1732 0.8550 0.080 0.000 0.000 0.920 0.000
#> SRR1313087 4 0.1557 0.8578 0.052 0.000 0.000 0.940 0.008
#> SRR1313088 4 0.1851 0.8510 0.088 0.000 0.000 0.912 0.000
#> SRR1313089 4 0.2046 0.8574 0.068 0.000 0.000 0.916 0.016
#> SRR1313092 3 0.0162 0.8852 0.000 0.000 0.996 0.000 0.004
#> SRR1313090 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 5 0.5489 0.1785 0.000 0.028 0.448 0.020 0.504
#> SRR1313093 3 0.0404 0.8842 0.000 0.000 0.988 0.000 0.012
#> SRR1313095 3 0.3579 0.7778 0.000 0.000 0.756 0.004 0.240
#> SRR1313096 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313094 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313099 3 0.0404 0.8813 0.000 0.000 0.988 0.012 0.000
#> SRR1313098 3 0.4106 0.7530 0.000 0.000 0.724 0.020 0.256
#> SRR1313101 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313103 3 0.0404 0.8813 0.000 0.000 0.988 0.012 0.000
#> SRR1313100 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313105 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313104 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313106 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313109 3 0.3882 0.6247 0.000 0.000 0.756 0.020 0.224
#> SRR1313108 3 0.3274 0.7930 0.000 0.000 0.780 0.000 0.220
#> SRR1313111 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313110 3 0.2464 0.8482 0.000 0.000 0.888 0.016 0.096
#> SRR1313112 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.1792 0.8598 0.000 0.000 0.916 0.000 0.084
#> SRR1313114 3 0.3098 0.8250 0.000 0.000 0.836 0.016 0.148
#> SRR1313117 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.3011 0.8279 0.000 0.000 0.844 0.016 0.140
#> SRR1313116 5 0.4481 0.2640 0.000 0.000 0.416 0.008 0.576
#> SRR1313120 3 0.0404 0.8813 0.000 0.000 0.988 0.012 0.000
#> SRR1313119 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313124 3 0.0000 0.8856 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0404 0.8838 0.000 0.000 0.988 0.000 0.012
#> SRR1313125 3 0.0162 0.8847 0.000 0.000 0.996 0.004 0.000
#> SRR1313127 3 0.3819 0.7780 0.000 0.000 0.756 0.016 0.228
#> SRR1313123 3 0.0404 0.8838 0.000 0.000 0.988 0.000 0.012
#> SRR1313128 1 0.0671 0.9480 0.980 0.000 0.000 0.004 0.016
#> SRR1313126 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313130 3 0.4697 0.2695 0.000 0.000 0.592 0.020 0.388
#> SRR1313132 1 0.2953 0.8767 0.844 0.000 0.000 0.012 0.144
#> SRR1313129 3 0.0290 0.8831 0.000 0.000 0.992 0.008 0.000
#> SRR1313133 1 0.1341 0.9329 0.944 0.000 0.000 0.000 0.056
#> SRR1313131 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313134 1 0.1300 0.9471 0.956 0.000 0.000 0.016 0.028
#> SRR1313135 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313136 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313137 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313138 1 0.2798 0.8818 0.852 0.000 0.000 0.008 0.140
#> SRR1313140 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313141 1 0.2920 0.8602 0.852 0.000 0.000 0.016 0.132
#> SRR1313139 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313143 1 0.4078 0.7789 0.784 0.000 0.000 0.068 0.148
#> SRR1313142 1 0.0609 0.9456 0.980 0.000 0.000 0.000 0.020
#> SRR1313144 1 0.2516 0.8868 0.860 0.000 0.000 0.000 0.140
#> SRR1313145 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313146 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313147 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313150 1 0.0963 0.9398 0.964 0.000 0.000 0.000 0.036
#> SRR1313149 1 0.0794 0.9444 0.972 0.000 0.000 0.000 0.028
#> SRR1313152 1 0.0290 0.9509 0.992 0.000 0.000 0.008 0.000
#> SRR1313151 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313154 1 0.0290 0.9479 0.992 0.000 0.000 0.000 0.008
#> SRR1313153 1 0.2516 0.8868 0.860 0.000 0.000 0.000 0.140
#> SRR1313156 1 0.2249 0.9096 0.896 0.000 0.000 0.008 0.096
#> SRR1313155 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313157 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313158 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313161 1 0.0671 0.9504 0.980 0.000 0.000 0.016 0.004
#> SRR1313159 1 0.3456 0.8392 0.800 0.000 0.000 0.016 0.184
#> SRR1313160 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313162 1 0.4166 0.8129 0.772 0.000 0.020 0.020 0.188
#> SRR1313163 1 0.0451 0.9470 0.988 0.000 0.000 0.004 0.008
#> SRR1313165 1 0.0290 0.9509 0.992 0.000 0.000 0.008 0.000
#> SRR1313166 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313164 1 0.2843 0.8797 0.848 0.000 0.000 0.008 0.144
#> SRR1313167 1 0.0865 0.9465 0.972 0.000 0.000 0.024 0.004
#> SRR1313168 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313170 3 0.5334 0.4179 0.028 0.000 0.588 0.020 0.364
#> SRR1313169 1 0.0510 0.9517 0.984 0.000 0.000 0.016 0.000
#> SRR1313172 3 0.0807 0.8801 0.000 0.000 0.976 0.012 0.012
#> SRR1313171 1 0.1082 0.9413 0.964 0.000 0.000 0.008 0.028
#> SRR1313174 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313173 3 0.4014 0.7572 0.000 0.000 0.728 0.016 0.256
#> SRR1313176 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313175 5 0.4219 0.8278 0.000 0.416 0.000 0.000 0.584
#> SRR1313178 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313177 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313179 2 0.7713 0.2297 0.144 0.504 0.080 0.016 0.256
#> SRR1313180 5 0.6115 0.6915 0.000 0.280 0.136 0.008 0.576
#> SRR1313181 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313183 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313182 2 0.4366 -0.0319 0.000 0.664 0.000 0.016 0.320
#> SRR1313184 2 0.7352 0.1553 0.016 0.464 0.252 0.016 0.252
#> SRR1313185 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313188 5 0.5182 0.8045 0.000 0.384 0.032 0.008 0.576
#> SRR1313187 5 0.6034 0.7113 0.000 0.296 0.120 0.008 0.576
#> SRR1313186 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313189 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313190 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313191 2 0.4702 -0.5160 0.000 0.552 0.000 0.016 0.432
#> SRR1313192 2 0.0404 0.8744 0.000 0.988 0.000 0.012 0.000
#> SRR1313193 2 0.0510 0.8718 0.000 0.984 0.000 0.016 0.000
#> SRR1313194 5 0.4727 0.8251 0.000 0.408 0.008 0.008 0.576
#> SRR1313195 5 0.4727 0.8251 0.000 0.408 0.008 0.008 0.576
#> SRR1313196 5 0.6034 0.7113 0.000 0.296 0.120 0.008 0.576
#> SRR1313197 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313198 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313199 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.4727 0.8251 0.000 0.408 0.008 0.008 0.576
#> SRR1313201 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.4613 0.8266 0.000 0.408 0.008 0.004 0.580
#> SRR1313203 3 0.4132 0.7541 0.000 0.000 0.720 0.020 0.260
#> SRR1313204 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0798 0.8656 0.000 0.976 0.000 0.016 0.008
#> SRR1313207 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313208 2 0.0671 0.8689 0.000 0.980 0.000 0.016 0.004
#> SRR1313206 2 0.0671 0.8689 0.000 0.980 0.000 0.016 0.004
#> SRR1313210 5 0.4367 0.8280 0.000 0.416 0.000 0.004 0.580
#> SRR1313209 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313211 5 0.4702 0.8024 0.000 0.432 0.000 0.016 0.552
#> SRR1313212 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.4674 0.8243 0.000 0.416 0.000 0.016 0.568
#> SRR1313215 5 0.4481 0.8278 0.000 0.416 0.000 0.008 0.576
#> SRR1313213 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313216 5 0.4367 0.8280 0.000 0.416 0.000 0.004 0.580
#> SRR1313217 5 0.4481 0.8255 0.000 0.416 0.000 0.008 0.576
#> SRR1313219 5 0.4367 0.8280 0.000 0.416 0.000 0.004 0.580
#> SRR1313220 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.4114 0.2140 0.000 0.712 0.000 0.016 0.272
#> SRR1313222 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313221 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
#> SRR1313223 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.1386 0.8367 0.000 0.952 0.000 0.016 0.032
#> SRR1313225 5 0.4481 0.8272 0.000 0.416 0.000 0.008 0.576
#> SRR1313226 5 0.4481 0.2640 0.000 0.000 0.416 0.008 0.576
#> SRR1313227 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.8801 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0510 0.8804 0.000 0.984 0.000 0.016 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0458 0.3196 0.000 0.000 0.016 0.984 0.000 0.000
#> SRR1313063 4 0.1444 0.3710 0.000 0.000 0.072 0.928 0.000 0.000
#> SRR1313064 4 0.4563 -0.7782 0.020 0.008 0.000 0.504 0.000 0.468
#> SRR1313065 4 0.4984 -0.8031 0.048 0.008 0.000 0.476 0.000 0.468
#> SRR1313066 6 0.4579 0.8836 0.012 0.016 0.000 0.476 0.000 0.496
#> SRR1313067 4 0.1957 0.3701 0.000 0.000 0.112 0.888 0.000 0.000
#> SRR1313068 4 0.2980 0.3344 0.000 0.000 0.192 0.800 0.000 0.008
#> SRR1313069 6 0.5452 0.6901 0.092 0.008 0.000 0.448 0.000 0.452
#> SRR1313070 6 0.4795 0.8931 0.024 0.016 0.000 0.456 0.000 0.504
#> SRR1313071 6 0.4795 0.8931 0.024 0.016 0.000 0.456 0.000 0.504
#> SRR1313072 6 0.4579 0.8836 0.012 0.016 0.000 0.476 0.000 0.496
#> SRR1313073 4 0.4135 -0.6804 0.008 0.004 0.000 0.584 0.000 0.404
#> SRR1313074 4 0.4563 -0.7782 0.020 0.008 0.000 0.504 0.000 0.468
#> SRR1313075 4 0.4564 -0.7843 0.020 0.008 0.000 0.500 0.000 0.472
#> SRR1313076 4 0.2362 0.3629 0.000 0.004 0.136 0.860 0.000 0.000
#> SRR1313077 4 0.1501 0.3725 0.000 0.000 0.076 0.924 0.000 0.000
#> SRR1313078 4 0.1501 0.3725 0.000 0.000 0.076 0.924 0.000 0.000
#> SRR1313079 4 0.4488 -0.7747 0.016 0.008 0.000 0.508 0.000 0.468
#> SRR1313080 4 0.3078 0.3330 0.000 0.000 0.192 0.796 0.000 0.012
#> SRR1313081 4 0.1075 0.3535 0.000 0.000 0.048 0.952 0.000 0.000
#> SRR1313082 4 0.4634 -0.8049 0.024 0.008 0.000 0.496 0.000 0.472
#> SRR1313083 4 0.4634 -0.8049 0.024 0.008 0.000 0.496 0.000 0.472
#> SRR1313084 6 0.4579 0.8836 0.012 0.016 0.000 0.476 0.000 0.496
#> SRR1313085 6 0.4795 0.8931 0.024 0.016 0.000 0.456 0.000 0.504
#> SRR1313086 4 0.4822 -0.8097 0.036 0.008 0.000 0.480 0.000 0.476
#> SRR1313087 4 0.4320 -0.7657 0.008 0.008 0.000 0.516 0.000 0.468
#> SRR1313088 6 0.4985 0.7667 0.048 0.008 0.000 0.472 0.000 0.472
#> SRR1313089 4 0.4492 -0.7975 0.016 0.008 0.000 0.496 0.000 0.480
#> SRR1313092 3 0.0146 0.8004 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313090 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313091 3 0.5573 0.0404 0.000 0.004 0.488 0.000 0.384 0.124
#> SRR1313093 3 0.0405 0.7993 0.000 0.000 0.988 0.008 0.000 0.004
#> SRR1313095 3 0.4114 0.5931 0.000 0.008 0.628 0.356 0.000 0.008
#> SRR1313096 3 0.4462 0.5067 0.000 0.008 0.540 0.436 0.000 0.016
#> SRR1313094 3 0.0146 0.8004 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313097 3 0.0547 0.7964 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313099 3 0.2094 0.7592 0.000 0.020 0.900 0.000 0.000 0.080
#> SRR1313098 3 0.4617 0.4913 0.000 0.008 0.524 0.444 0.000 0.024
#> SRR1313101 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0806 0.7983 0.000 0.000 0.972 0.008 0.000 0.020
#> SRR1313103 3 0.1983 0.7639 0.000 0.020 0.908 0.000 0.000 0.072
#> SRR1313100 3 0.4291 0.5129 0.000 0.008 0.548 0.436 0.000 0.008
#> SRR1313105 3 0.0632 0.7956 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313104 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 3 0.0547 0.7964 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313106 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313109 3 0.4419 0.6301 0.000 0.020 0.748 0.000 0.096 0.136
#> SRR1313108 3 0.4113 0.6281 0.000 0.008 0.668 0.308 0.000 0.016
#> SRR1313111 3 0.0547 0.7964 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313110 3 0.3043 0.7133 0.000 0.000 0.792 0.200 0.000 0.008
#> SRR1313112 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0146 0.8000 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313115 3 0.1700 0.7735 0.000 0.000 0.916 0.080 0.000 0.004
#> SRR1313114 3 0.3840 0.6498 0.000 0.008 0.696 0.288 0.000 0.008
#> SRR1313117 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.3489 0.6562 0.000 0.004 0.708 0.288 0.000 0.000
#> SRR1313116 5 0.4718 0.4534 0.000 0.000 0.316 0.000 0.616 0.068
#> SRR1313120 3 0.1204 0.7818 0.000 0.000 0.944 0.000 0.000 0.056
#> SRR1313119 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313122 3 0.4462 0.5067 0.000 0.008 0.540 0.436 0.000 0.016
#> SRR1313124 3 0.0000 0.8006 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313121 3 0.0547 0.7974 0.000 0.000 0.980 0.020 0.000 0.000
#> SRR1313125 3 0.0146 0.8000 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313127 3 0.4088 0.6007 0.000 0.008 0.636 0.348 0.000 0.008
#> SRR1313123 3 0.0692 0.7965 0.000 0.000 0.976 0.020 0.000 0.004
#> SRR1313128 1 0.1930 0.8868 0.916 0.036 0.000 0.000 0.000 0.048
#> SRR1313126 3 0.4556 0.4779 0.000 0.008 0.516 0.456 0.000 0.020
#> SRR1313130 3 0.5661 0.3439 0.000 0.020 0.580 0.000 0.268 0.132
#> SRR1313132 1 0.5202 0.7060 0.616 0.196 0.000 0.000 0.000 0.188
#> SRR1313129 3 0.0865 0.7909 0.000 0.000 0.964 0.000 0.000 0.036
#> SRR1313133 1 0.2997 0.8571 0.844 0.096 0.000 0.000 0.000 0.060
#> SRR1313131 3 0.4621 0.4837 0.000 0.008 0.520 0.448 0.000 0.024
#> SRR1313134 1 0.2908 0.8717 0.864 0.048 0.000 0.012 0.000 0.076
#> SRR1313135 1 0.0363 0.8997 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313136 1 0.0508 0.8984 0.984 0.004 0.000 0.000 0.000 0.012
#> SRR1313137 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.4980 0.7314 0.648 0.184 0.000 0.000 0.000 0.168
#> SRR1313140 1 0.1124 0.8918 0.956 0.008 0.000 0.000 0.000 0.036
#> SRR1313141 1 0.4715 0.7648 0.736 0.048 0.000 0.136 0.000 0.080
#> SRR1313139 1 0.0891 0.8935 0.968 0.008 0.000 0.000 0.000 0.024
#> SRR1313143 1 0.4859 0.7474 0.720 0.048 0.000 0.152 0.000 0.080
#> SRR1313142 1 0.2328 0.8800 0.892 0.056 0.000 0.000 0.000 0.052
#> SRR1313144 1 0.4950 0.7342 0.652 0.184 0.000 0.000 0.000 0.164
#> SRR1313145 1 0.0146 0.8996 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313146 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.1341 0.8910 0.948 0.028 0.000 0.000 0.000 0.024
#> SRR1313149 1 0.2846 0.8729 0.856 0.060 0.000 0.000 0.000 0.084
#> SRR1313152 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0891 0.8943 0.968 0.008 0.000 0.000 0.000 0.024
#> SRR1313154 1 0.0820 0.8983 0.972 0.012 0.000 0.000 0.000 0.016
#> SRR1313153 1 0.4921 0.7373 0.656 0.180 0.000 0.000 0.000 0.164
#> SRR1313156 1 0.4074 0.8057 0.752 0.140 0.000 0.000 0.000 0.108
#> SRR1313155 1 0.0291 0.8991 0.992 0.004 0.000 0.000 0.000 0.004
#> SRR1313157 1 0.0146 0.8997 0.996 0.004 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0363 0.8991 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313161 1 0.0508 0.8994 0.984 0.004 0.000 0.000 0.000 0.012
#> SRR1313159 1 0.5740 0.6249 0.536 0.200 0.000 0.000 0.004 0.260
#> SRR1313160 1 0.0146 0.8997 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313162 1 0.6603 0.6453 0.552 0.188 0.020 0.048 0.000 0.192
#> SRR1313163 1 0.0363 0.8994 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313165 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0146 0.8996 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313164 1 0.5065 0.7227 0.636 0.192 0.000 0.000 0.000 0.172
#> SRR1313167 1 0.1297 0.8865 0.948 0.012 0.000 0.000 0.000 0.040
#> SRR1313168 1 0.0000 0.8997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.7470 0.2538 0.012 0.168 0.400 0.000 0.124 0.296
#> SRR1313169 1 0.0972 0.8931 0.964 0.008 0.000 0.000 0.000 0.028
#> SRR1313172 3 0.1845 0.7798 0.000 0.008 0.916 0.004 0.000 0.072
#> SRR1313171 1 0.2948 0.8685 0.848 0.060 0.000 0.000 0.000 0.092
#> SRR1313174 5 0.0935 0.8616 0.000 0.000 0.000 0.004 0.964 0.032
#> SRR1313173 3 0.4687 0.4823 0.000 0.008 0.516 0.448 0.000 0.028
#> SRR1313176 2 0.4615 0.8686 0.000 0.676 0.000 0.004 0.244 0.076
#> SRR1313175 5 0.0547 0.8675 0.000 0.000 0.000 0.000 0.980 0.020
#> SRR1313178 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313177 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313179 2 0.7911 0.0860 0.092 0.400 0.112 0.000 0.096 0.300
#> SRR1313180 5 0.2852 0.8015 0.000 0.000 0.080 0.000 0.856 0.064
#> SRR1313181 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313183 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313182 5 0.3621 0.6014 0.000 0.192 0.000 0.004 0.772 0.032
#> SRR1313184 2 0.7330 0.0483 0.012 0.396 0.216 0.000 0.080 0.296
#> SRR1313185 5 0.0935 0.8616 0.000 0.000 0.000 0.004 0.964 0.032
#> SRR1313188 5 0.2318 0.8327 0.000 0.000 0.044 0.000 0.892 0.064
#> SRR1313187 5 0.2852 0.8015 0.000 0.000 0.080 0.000 0.856 0.064
#> SRR1313186 5 0.0935 0.8616 0.000 0.000 0.000 0.004 0.964 0.032
#> SRR1313189 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313190 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313191 5 0.3351 0.6745 0.000 0.152 0.000 0.004 0.808 0.036
#> SRR1313192 2 0.4071 0.8459 0.000 0.712 0.000 0.004 0.248 0.036
#> SRR1313193 2 0.4355 0.8019 0.000 0.656 0.000 0.004 0.304 0.036
#> SRR1313194 5 0.1686 0.8529 0.000 0.000 0.012 0.000 0.924 0.064
#> SRR1313195 5 0.1686 0.8529 0.000 0.000 0.012 0.000 0.924 0.064
#> SRR1313196 5 0.2852 0.8015 0.000 0.000 0.080 0.000 0.856 0.064
#> SRR1313197 5 0.0935 0.8616 0.000 0.000 0.000 0.004 0.964 0.032
#> SRR1313198 5 0.0146 0.8688 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1313199 2 0.3101 0.8670 0.000 0.756 0.000 0.000 0.244 0.000
#> SRR1313200 5 0.1686 0.8529 0.000 0.000 0.012 0.000 0.924 0.064
#> SRR1313201 2 0.3240 0.8676 0.000 0.752 0.000 0.000 0.244 0.004
#> SRR1313202 5 0.1625 0.8545 0.000 0.000 0.012 0.000 0.928 0.060
#> SRR1313203 3 0.5163 0.4650 0.000 0.012 0.488 0.444 0.000 0.056
#> SRR1313204 2 0.3240 0.8660 0.000 0.752 0.000 0.000 0.244 0.004
#> SRR1313205 2 0.4355 0.8019 0.000 0.656 0.000 0.004 0.304 0.036
#> SRR1313207 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313208 2 0.4355 0.8019 0.000 0.656 0.000 0.004 0.304 0.036
#> SRR1313206 2 0.4355 0.8019 0.000 0.656 0.000 0.004 0.304 0.036
#> SRR1313210 5 0.0000 0.8689 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.0935 0.8616 0.000 0.000 0.000 0.004 0.964 0.032
#> SRR1313211 5 0.2600 0.7788 0.000 0.084 0.000 0.004 0.876 0.036
#> SRR1313212 2 0.3240 0.8660 0.000 0.752 0.000 0.000 0.244 0.004
#> SRR1313214 5 0.0777 0.8640 0.000 0.000 0.000 0.004 0.972 0.024
#> SRR1313215 5 0.0260 0.8693 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1313213 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313216 5 0.0260 0.8692 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1313217 5 0.0790 0.8649 0.000 0.000 0.000 0.000 0.968 0.032
#> SRR1313219 5 0.0260 0.8683 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1313220 2 0.3240 0.8660 0.000 0.752 0.000 0.000 0.244 0.004
#> SRR1313218 5 0.4244 0.3500 0.000 0.280 0.000 0.004 0.680 0.036
#> SRR1313222 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313221 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
#> SRR1313223 2 0.3349 0.8670 0.000 0.748 0.000 0.000 0.244 0.008
#> SRR1313224 2 0.4450 0.7707 0.000 0.632 0.000 0.004 0.328 0.036
#> SRR1313225 5 0.0777 0.8640 0.000 0.000 0.000 0.004 0.972 0.024
#> SRR1313226 5 0.4365 0.6087 0.000 0.004 0.228 0.000 0.704 0.064
#> SRR1313227 2 0.3240 0.8678 0.000 0.752 0.000 0.004 0.244 0.000
#> SRR1313228 2 0.3101 0.8670 0.000 0.756 0.000 0.000 0.244 0.000
#> SRR1313229 2 0.4663 0.8687 0.000 0.672 0.000 0.004 0.244 0.080
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "skmeans"]
# you can also extract it by
# res = res_list["CV:skmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 5.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.955 0.983 0.4846 0.519 0.519
#> 3 3 1.000 0.980 0.991 0.3795 0.781 0.591
#> 4 4 0.827 0.902 0.911 0.1100 0.865 0.627
#> 5 5 0.982 0.943 0.968 0.0804 0.915 0.686
#> 6 6 0.876 0.702 0.864 0.0347 0.970 0.854
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.978 1.000 0.000
#> SRR1313063 1 0.0000 0.978 1.000 0.000
#> SRR1313064 1 0.0000 0.978 1.000 0.000
#> SRR1313065 1 0.0000 0.978 1.000 0.000
#> SRR1313066 1 0.0000 0.978 1.000 0.000
#> SRR1313067 1 0.0000 0.978 1.000 0.000
#> SRR1313068 1 0.0000 0.978 1.000 0.000
#> SRR1313069 1 0.0000 0.978 1.000 0.000
#> SRR1313070 1 0.0000 0.978 1.000 0.000
#> SRR1313071 1 0.0000 0.978 1.000 0.000
#> SRR1313072 1 0.0000 0.978 1.000 0.000
#> SRR1313073 1 0.0000 0.978 1.000 0.000
#> SRR1313074 1 0.0000 0.978 1.000 0.000
#> SRR1313075 1 0.0000 0.978 1.000 0.000
#> SRR1313076 1 0.0000 0.978 1.000 0.000
#> SRR1313077 1 0.0000 0.978 1.000 0.000
#> SRR1313078 1 0.0000 0.978 1.000 0.000
#> SRR1313079 1 0.0000 0.978 1.000 0.000
#> SRR1313080 1 0.0000 0.978 1.000 0.000
#> SRR1313081 1 0.0000 0.978 1.000 0.000
#> SRR1313082 1 0.0000 0.978 1.000 0.000
#> SRR1313083 1 0.0000 0.978 1.000 0.000
#> SRR1313084 1 0.0000 0.978 1.000 0.000
#> SRR1313085 1 0.0000 0.978 1.000 0.000
#> SRR1313086 1 0.0000 0.978 1.000 0.000
#> SRR1313087 1 0.0000 0.978 1.000 0.000
#> SRR1313088 1 0.0000 0.978 1.000 0.000
#> SRR1313089 1 0.0000 0.978 1.000 0.000
#> SRR1313092 1 0.0000 0.978 1.000 0.000
#> SRR1313090 1 0.0000 0.978 1.000 0.000
#> SRR1313091 2 0.0000 0.989 0.000 1.000
#> SRR1313093 1 0.0000 0.978 1.000 0.000
#> SRR1313095 1 0.0000 0.978 1.000 0.000
#> SRR1313096 1 0.0000 0.978 1.000 0.000
#> SRR1313094 1 0.0000 0.978 1.000 0.000
#> SRR1313097 1 0.3733 0.909 0.928 0.072
#> SRR1313099 2 0.0000 0.989 0.000 1.000
#> SRR1313098 1 0.0000 0.978 1.000 0.000
#> SRR1313101 1 0.0376 0.975 0.996 0.004
#> SRR1313102 1 0.0000 0.978 1.000 0.000
#> SRR1313103 2 0.6887 0.766 0.184 0.816
#> SRR1313100 1 0.0000 0.978 1.000 0.000
#> SRR1313105 1 0.2603 0.938 0.956 0.044
#> SRR1313104 1 0.0000 0.978 1.000 0.000
#> SRR1313107 1 0.2423 0.941 0.960 0.040
#> SRR1313106 1 0.9983 0.104 0.524 0.476
#> SRR1313109 2 0.0000 0.989 0.000 1.000
#> SRR1313108 1 0.0000 0.978 1.000 0.000
#> SRR1313111 1 0.0938 0.968 0.988 0.012
#> SRR1313110 1 0.0000 0.978 1.000 0.000
#> SRR1313112 1 0.9833 0.278 0.576 0.424
#> SRR1313113 1 0.6623 0.785 0.828 0.172
#> SRR1313115 1 0.0000 0.978 1.000 0.000
#> SRR1313114 1 0.0000 0.978 1.000 0.000
#> SRR1313117 1 0.0000 0.978 1.000 0.000
#> SRR1313118 1 0.0000 0.978 1.000 0.000
#> SRR1313116 2 0.0000 0.989 0.000 1.000
#> SRR1313120 2 0.9922 0.156 0.448 0.552
#> SRR1313119 1 0.0000 0.978 1.000 0.000
#> SRR1313122 1 0.0000 0.978 1.000 0.000
#> SRR1313124 1 0.0000 0.978 1.000 0.000
#> SRR1313121 1 0.0000 0.978 1.000 0.000
#> SRR1313125 1 0.0000 0.978 1.000 0.000
#> SRR1313127 1 0.0000 0.978 1.000 0.000
#> SRR1313123 1 0.0000 0.978 1.000 0.000
#> SRR1313128 1 0.0000 0.978 1.000 0.000
#> SRR1313126 1 0.0000 0.978 1.000 0.000
#> SRR1313130 2 0.0000 0.989 0.000 1.000
#> SRR1313132 1 0.0000 0.978 1.000 0.000
#> SRR1313129 2 0.3733 0.913 0.072 0.928
#> SRR1313133 1 0.0000 0.978 1.000 0.000
#> SRR1313131 1 0.0000 0.978 1.000 0.000
#> SRR1313134 1 0.0000 0.978 1.000 0.000
#> SRR1313135 1 0.0000 0.978 1.000 0.000
#> SRR1313136 1 0.0000 0.978 1.000 0.000
#> SRR1313137 1 0.0000 0.978 1.000 0.000
#> SRR1313138 1 0.9710 0.331 0.600 0.400
#> SRR1313140 1 0.0000 0.978 1.000 0.000
#> SRR1313141 1 0.0000 0.978 1.000 0.000
#> SRR1313139 1 0.0000 0.978 1.000 0.000
#> SRR1313143 1 0.0000 0.978 1.000 0.000
#> SRR1313142 1 0.0000 0.978 1.000 0.000
#> SRR1313144 1 0.0000 0.978 1.000 0.000
#> SRR1313145 1 0.0000 0.978 1.000 0.000
#> SRR1313146 1 0.0000 0.978 1.000 0.000
#> SRR1313147 1 0.0000 0.978 1.000 0.000
#> SRR1313150 1 0.0000 0.978 1.000 0.000
#> SRR1313149 1 0.0000 0.978 1.000 0.000
#> SRR1313152 1 0.0000 0.978 1.000 0.000
#> SRR1313151 1 0.0000 0.978 1.000 0.000
#> SRR1313154 1 0.0000 0.978 1.000 0.000
#> SRR1313153 1 0.0000 0.978 1.000 0.000
#> SRR1313156 1 0.0000 0.978 1.000 0.000
#> SRR1313155 1 0.0000 0.978 1.000 0.000
#> SRR1313157 1 0.0000 0.978 1.000 0.000
#> SRR1313158 1 0.0000 0.978 1.000 0.000
#> SRR1313161 1 0.0000 0.978 1.000 0.000
#> SRR1313159 2 0.0000 0.989 0.000 1.000
#> SRR1313160 1 0.0000 0.978 1.000 0.000
#> SRR1313162 1 0.0000 0.978 1.000 0.000
#> SRR1313163 1 0.0000 0.978 1.000 0.000
#> SRR1313165 1 0.0000 0.978 1.000 0.000
#> SRR1313166 1 0.0000 0.978 1.000 0.000
#> SRR1313164 1 0.0000 0.978 1.000 0.000
#> SRR1313167 1 0.0000 0.978 1.000 0.000
#> SRR1313168 1 0.0000 0.978 1.000 0.000
#> SRR1313170 2 0.0000 0.989 0.000 1.000
#> SRR1313169 1 0.0000 0.978 1.000 0.000
#> SRR1313172 2 0.0000 0.989 0.000 1.000
#> SRR1313171 1 0.0000 0.978 1.000 0.000
#> SRR1313174 2 0.0000 0.989 0.000 1.000
#> SRR1313173 1 0.0000 0.978 1.000 0.000
#> SRR1313176 2 0.0000 0.989 0.000 1.000
#> SRR1313175 2 0.0000 0.989 0.000 1.000
#> SRR1313178 2 0.0000 0.989 0.000 1.000
#> SRR1313177 2 0.0000 0.989 0.000 1.000
#> SRR1313179 2 0.0000 0.989 0.000 1.000
#> SRR1313180 2 0.0000 0.989 0.000 1.000
#> SRR1313181 2 0.0000 0.989 0.000 1.000
#> SRR1313183 2 0.0000 0.989 0.000 1.000
#> SRR1313182 2 0.0000 0.989 0.000 1.000
#> SRR1313184 2 0.0000 0.989 0.000 1.000
#> SRR1313185 2 0.0000 0.989 0.000 1.000
#> SRR1313188 2 0.0000 0.989 0.000 1.000
#> SRR1313187 2 0.0000 0.989 0.000 1.000
#> SRR1313186 2 0.0000 0.989 0.000 1.000
#> SRR1313189 2 0.0000 0.989 0.000 1.000
#> SRR1313190 2 0.0000 0.989 0.000 1.000
#> SRR1313191 2 0.0000 0.989 0.000 1.000
#> SRR1313192 2 0.0000 0.989 0.000 1.000
#> SRR1313193 2 0.0000 0.989 0.000 1.000
#> SRR1313194 2 0.0000 0.989 0.000 1.000
#> SRR1313195 2 0.0000 0.989 0.000 1.000
#> SRR1313196 2 0.0000 0.989 0.000 1.000
#> SRR1313197 2 0.0000 0.989 0.000 1.000
#> SRR1313198 2 0.0000 0.989 0.000 1.000
#> SRR1313199 2 0.0000 0.989 0.000 1.000
#> SRR1313200 2 0.0000 0.989 0.000 1.000
#> SRR1313201 2 0.0000 0.989 0.000 1.000
#> SRR1313202 2 0.0000 0.989 0.000 1.000
#> SRR1313203 1 0.9977 0.119 0.528 0.472
#> SRR1313204 2 0.0000 0.989 0.000 1.000
#> SRR1313205 2 0.0000 0.989 0.000 1.000
#> SRR1313207 2 0.0000 0.989 0.000 1.000
#> SRR1313208 2 0.0000 0.989 0.000 1.000
#> SRR1313206 2 0.0000 0.989 0.000 1.000
#> SRR1313210 2 0.0000 0.989 0.000 1.000
#> SRR1313209 2 0.0000 0.989 0.000 1.000
#> SRR1313211 2 0.0000 0.989 0.000 1.000
#> SRR1313212 2 0.0000 0.989 0.000 1.000
#> SRR1313214 2 0.0000 0.989 0.000 1.000
#> SRR1313215 2 0.0000 0.989 0.000 1.000
#> SRR1313213 2 0.0000 0.989 0.000 1.000
#> SRR1313216 2 0.0000 0.989 0.000 1.000
#> SRR1313217 2 0.0000 0.989 0.000 1.000
#> SRR1313219 2 0.0000 0.989 0.000 1.000
#> SRR1313220 2 0.0000 0.989 0.000 1.000
#> SRR1313218 2 0.0000 0.989 0.000 1.000
#> SRR1313222 2 0.0000 0.989 0.000 1.000
#> SRR1313221 2 0.0000 0.989 0.000 1.000
#> SRR1313223 2 0.0000 0.989 0.000 1.000
#> SRR1313224 2 0.0000 0.989 0.000 1.000
#> SRR1313225 2 0.0000 0.989 0.000 1.000
#> SRR1313226 2 0.0000 0.989 0.000 1.000
#> SRR1313227 2 0.0000 0.989 0.000 1.000
#> SRR1313228 2 0.0000 0.989 0.000 1.000
#> SRR1313229 2 0.0000 0.989 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.000 0.989 0 0.000 1.000
#> SRR1313063 3 0.000 0.989 0 0.000 1.000
#> SRR1313064 1 0.000 1.000 1 0.000 0.000
#> SRR1313065 1 0.000 1.000 1 0.000 0.000
#> SRR1313066 1 0.000 1.000 1 0.000 0.000
#> SRR1313067 3 0.000 0.989 0 0.000 1.000
#> SRR1313068 3 0.000 0.989 0 0.000 1.000
#> SRR1313069 1 0.000 1.000 1 0.000 0.000
#> SRR1313070 1 0.000 1.000 1 0.000 0.000
#> SRR1313071 1 0.000 1.000 1 0.000 0.000
#> SRR1313072 1 0.000 1.000 1 0.000 0.000
#> SRR1313073 1 0.000 1.000 1 0.000 0.000
#> SRR1313074 1 0.000 1.000 1 0.000 0.000
#> SRR1313075 1 0.000 1.000 1 0.000 0.000
#> SRR1313076 3 0.000 0.989 0 0.000 1.000
#> SRR1313077 3 0.000 0.989 0 0.000 1.000
#> SRR1313078 3 0.000 0.989 0 0.000 1.000
#> SRR1313079 1 0.000 1.000 1 0.000 0.000
#> SRR1313080 3 0.000 0.989 0 0.000 1.000
#> SRR1313081 3 0.000 0.989 0 0.000 1.000
#> SRR1313082 1 0.000 1.000 1 0.000 0.000
#> SRR1313083 1 0.000 1.000 1 0.000 0.000
#> SRR1313084 1 0.000 1.000 1 0.000 0.000
#> SRR1313085 1 0.000 1.000 1 0.000 0.000
#> SRR1313086 1 0.000 1.000 1 0.000 0.000
#> SRR1313087 1 0.000 1.000 1 0.000 0.000
#> SRR1313088 1 0.000 1.000 1 0.000 0.000
#> SRR1313089 1 0.000 1.000 1 0.000 0.000
#> SRR1313092 3 0.000 0.989 0 0.000 1.000
#> SRR1313090 3 0.000 0.989 0 0.000 1.000
#> SRR1313091 2 0.000 0.984 0 1.000 0.000
#> SRR1313093 3 0.000 0.989 0 0.000 1.000
#> SRR1313095 3 0.000 0.989 0 0.000 1.000
#> SRR1313096 3 0.000 0.989 0 0.000 1.000
#> SRR1313094 3 0.000 0.989 0 0.000 1.000
#> SRR1313097 3 0.000 0.989 0 0.000 1.000
#> SRR1313099 3 0.000 0.989 0 0.000 1.000
#> SRR1313098 3 0.000 0.989 0 0.000 1.000
#> SRR1313101 3 0.000 0.989 0 0.000 1.000
#> SRR1313102 3 0.000 0.989 0 0.000 1.000
#> SRR1313103 3 0.000 0.989 0 0.000 1.000
#> SRR1313100 3 0.000 0.989 0 0.000 1.000
#> SRR1313105 3 0.000 0.989 0 0.000 1.000
#> SRR1313104 3 0.000 0.989 0 0.000 1.000
#> SRR1313107 3 0.000 0.989 0 0.000 1.000
#> SRR1313106 3 0.000 0.989 0 0.000 1.000
#> SRR1313109 2 0.445 0.768 0 0.808 0.192
#> SRR1313108 3 0.000 0.989 0 0.000 1.000
#> SRR1313111 3 0.000 0.989 0 0.000 1.000
#> SRR1313110 3 0.000 0.989 0 0.000 1.000
#> SRR1313112 3 0.000 0.989 0 0.000 1.000
#> SRR1313113 3 0.000 0.989 0 0.000 1.000
#> SRR1313115 3 0.000 0.989 0 0.000 1.000
#> SRR1313114 3 0.000 0.989 0 0.000 1.000
#> SRR1313117 3 0.000 0.989 0 0.000 1.000
#> SRR1313118 3 0.000 0.989 0 0.000 1.000
#> SRR1313116 3 0.565 0.533 0 0.312 0.688
#> SRR1313120 3 0.000 0.989 0 0.000 1.000
#> SRR1313119 3 0.000 0.989 0 0.000 1.000
#> SRR1313122 3 0.000 0.989 0 0.000 1.000
#> SRR1313124 3 0.000 0.989 0 0.000 1.000
#> SRR1313121 3 0.000 0.989 0 0.000 1.000
#> SRR1313125 3 0.000 0.989 0 0.000 1.000
#> SRR1313127 3 0.000 0.989 0 0.000 1.000
#> SRR1313123 3 0.000 0.989 0 0.000 1.000
#> SRR1313128 1 0.000 1.000 1 0.000 0.000
#> SRR1313126 3 0.000 0.989 0 0.000 1.000
#> SRR1313130 2 0.455 0.756 0 0.800 0.200
#> SRR1313132 1 0.000 1.000 1 0.000 0.000
#> SRR1313129 3 0.000 0.989 0 0.000 1.000
#> SRR1313133 1 0.000 1.000 1 0.000 0.000
#> SRR1313131 3 0.000 0.989 0 0.000 1.000
#> SRR1313134 1 0.000 1.000 1 0.000 0.000
#> SRR1313135 1 0.000 1.000 1 0.000 0.000
#> SRR1313136 1 0.000 1.000 1 0.000 0.000
#> SRR1313137 1 0.000 1.000 1 0.000 0.000
#> SRR1313138 1 0.000 1.000 1 0.000 0.000
#> SRR1313140 1 0.000 1.000 1 0.000 0.000
#> SRR1313141 1 0.000 1.000 1 0.000 0.000
#> SRR1313139 1 0.000 1.000 1 0.000 0.000
#> SRR1313143 1 0.000 1.000 1 0.000 0.000
#> SRR1313142 1 0.000 1.000 1 0.000 0.000
#> SRR1313144 1 0.000 1.000 1 0.000 0.000
#> SRR1313145 1 0.000 1.000 1 0.000 0.000
#> SRR1313146 1 0.000 1.000 1 0.000 0.000
#> SRR1313147 1 0.000 1.000 1 0.000 0.000
#> SRR1313150 1 0.000 1.000 1 0.000 0.000
#> SRR1313149 1 0.000 1.000 1 0.000 0.000
#> SRR1313152 1 0.000 1.000 1 0.000 0.000
#> SRR1313151 1 0.000 1.000 1 0.000 0.000
#> SRR1313154 1 0.000 1.000 1 0.000 0.000
#> SRR1313153 1 0.000 1.000 1 0.000 0.000
#> SRR1313156 1 0.000 1.000 1 0.000 0.000
#> SRR1313155 1 0.000 1.000 1 0.000 0.000
#> SRR1313157 1 0.000 1.000 1 0.000 0.000
#> SRR1313158 1 0.000 1.000 1 0.000 0.000
#> SRR1313161 1 0.000 1.000 1 0.000 0.000
#> SRR1313159 2 0.000 0.984 0 1.000 0.000
#> SRR1313160 1 0.000 1.000 1 0.000 0.000
#> SRR1313162 1 0.000 1.000 1 0.000 0.000
#> SRR1313163 1 0.000 1.000 1 0.000 0.000
#> SRR1313165 1 0.000 1.000 1 0.000 0.000
#> SRR1313166 1 0.000 1.000 1 0.000 0.000
#> SRR1313164 1 0.000 1.000 1 0.000 0.000
#> SRR1313167 1 0.000 1.000 1 0.000 0.000
#> SRR1313168 1 0.000 1.000 1 0.000 0.000
#> SRR1313170 2 0.573 0.535 0 0.676 0.324
#> SRR1313169 1 0.000 1.000 1 0.000 0.000
#> SRR1313172 2 0.418 0.795 0 0.828 0.172
#> SRR1313171 1 0.000 1.000 1 0.000 0.000
#> SRR1313174 2 0.000 0.984 0 1.000 0.000
#> SRR1313173 3 0.000 0.989 0 0.000 1.000
#> SRR1313176 2 0.000 0.984 0 1.000 0.000
#> SRR1313175 2 0.000 0.984 0 1.000 0.000
#> SRR1313178 2 0.000 0.984 0 1.000 0.000
#> SRR1313177 2 0.000 0.984 0 1.000 0.000
#> SRR1313179 2 0.000 0.984 0 1.000 0.000
#> SRR1313180 2 0.000 0.984 0 1.000 0.000
#> SRR1313181 2 0.000 0.984 0 1.000 0.000
#> SRR1313183 2 0.000 0.984 0 1.000 0.000
#> SRR1313182 2 0.000 0.984 0 1.000 0.000
#> SRR1313184 2 0.000 0.984 0 1.000 0.000
#> SRR1313185 2 0.000 0.984 0 1.000 0.000
#> SRR1313188 2 0.000 0.984 0 1.000 0.000
#> SRR1313187 2 0.000 0.984 0 1.000 0.000
#> SRR1313186 2 0.000 0.984 0 1.000 0.000
#> SRR1313189 2 0.000 0.984 0 1.000 0.000
#> SRR1313190 2 0.000 0.984 0 1.000 0.000
#> SRR1313191 2 0.000 0.984 0 1.000 0.000
#> SRR1313192 2 0.000 0.984 0 1.000 0.000
#> SRR1313193 2 0.000 0.984 0 1.000 0.000
#> SRR1313194 2 0.000 0.984 0 1.000 0.000
#> SRR1313195 2 0.000 0.984 0 1.000 0.000
#> SRR1313196 2 0.000 0.984 0 1.000 0.000
#> SRR1313197 2 0.000 0.984 0 1.000 0.000
#> SRR1313198 2 0.000 0.984 0 1.000 0.000
#> SRR1313199 2 0.000 0.984 0 1.000 0.000
#> SRR1313200 2 0.000 0.984 0 1.000 0.000
#> SRR1313201 2 0.000 0.984 0 1.000 0.000
#> SRR1313202 2 0.000 0.984 0 1.000 0.000
#> SRR1313203 3 0.475 0.722 0 0.216 0.784
#> SRR1313204 2 0.000 0.984 0 1.000 0.000
#> SRR1313205 2 0.000 0.984 0 1.000 0.000
#> SRR1313207 2 0.000 0.984 0 1.000 0.000
#> SRR1313208 2 0.000 0.984 0 1.000 0.000
#> SRR1313206 2 0.000 0.984 0 1.000 0.000
#> SRR1313210 2 0.000 0.984 0 1.000 0.000
#> SRR1313209 2 0.000 0.984 0 1.000 0.000
#> SRR1313211 2 0.000 0.984 0 1.000 0.000
#> SRR1313212 2 0.000 0.984 0 1.000 0.000
#> SRR1313214 2 0.000 0.984 0 1.000 0.000
#> SRR1313215 2 0.000 0.984 0 1.000 0.000
#> SRR1313213 2 0.000 0.984 0 1.000 0.000
#> SRR1313216 2 0.000 0.984 0 1.000 0.000
#> SRR1313217 2 0.000 0.984 0 1.000 0.000
#> SRR1313219 2 0.000 0.984 0 1.000 0.000
#> SRR1313220 2 0.000 0.984 0 1.000 0.000
#> SRR1313218 2 0.000 0.984 0 1.000 0.000
#> SRR1313222 2 0.000 0.984 0 1.000 0.000
#> SRR1313221 2 0.000 0.984 0 1.000 0.000
#> SRR1313223 2 0.000 0.984 0 1.000 0.000
#> SRR1313224 2 0.000 0.984 0 1.000 0.000
#> SRR1313225 2 0.000 0.984 0 1.000 0.000
#> SRR1313226 2 0.103 0.963 0 0.976 0.024
#> SRR1313227 2 0.000 0.984 0 1.000 0.000
#> SRR1313228 2 0.000 0.984 0 1.000 0.000
#> SRR1313229 2 0.000 0.984 0 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313063 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313064 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313067 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313068 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313069 4 0.0336 0.8542 0.008 0.000 0.000 0.992
#> SRR1313070 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313077 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313078 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313079 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313081 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313082 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313093 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313096 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313094 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.4941 0.0602 0.000 0.000 0.564 0.436
#> SRR1313101 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.3726 0.7513 0.212 0.000 0.788 0.000
#> SRR1313108 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313111 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.3764 0.7470 0.216 0.000 0.784 0.000
#> SRR1313120 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313126 4 0.3975 0.7460 0.000 0.000 0.240 0.760
#> SRR1313130 3 0.4086 0.7389 0.216 0.008 0.776 0.000
#> SRR1313132 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313129 3 0.0000 0.9601 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313131 4 0.4134 0.7207 0.000 0.000 0.260 0.740
#> SRR1313134 1 0.3801 0.9795 0.780 0.000 0.000 0.220
#> SRR1313135 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313136 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313137 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313138 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313140 1 0.3907 0.9661 0.768 0.000 0.000 0.232
#> SRR1313141 4 0.2011 0.7619 0.080 0.000 0.000 0.920
#> SRR1313139 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313143 4 0.0000 0.8624 0.000 0.000 0.000 1.000
#> SRR1313142 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313144 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313145 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313146 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313147 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313150 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313149 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313152 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313151 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313154 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313153 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313156 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313155 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313157 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313158 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313161 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313159 1 0.0000 0.6986 1.000 0.000 0.000 0.000
#> SRR1313160 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313162 1 0.3908 0.9786 0.784 0.000 0.004 0.212
#> SRR1313163 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313165 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313166 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313164 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313167 1 0.4941 0.6373 0.564 0.000 0.000 0.436
#> SRR1313168 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313170 3 0.3764 0.7470 0.216 0.000 0.784 0.000
#> SRR1313169 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313172 2 0.1940 0.8735 0.000 0.924 0.076 0.000
#> SRR1313171 1 0.3764 0.9836 0.784 0.000 0.000 0.216
#> SRR1313174 2 0.3649 0.8898 0.204 0.796 0.000 0.000
#> SRR1313173 4 0.3764 0.7721 0.000 0.000 0.216 0.784
#> SRR1313176 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313178 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313181 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.1716 0.9057 0.064 0.936 0.000 0.000
#> SRR1313184 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.3688 0.8892 0.208 0.792 0.000 0.000
#> SRR1313188 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313187 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313186 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313189 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313195 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313196 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313197 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313198 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313199 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313201 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313203 4 0.4011 0.7261 0.000 0.208 0.008 0.784
#> SRR1313204 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313209 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313211 2 0.3688 0.8892 0.208 0.792 0.000 0.000
#> SRR1313212 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313215 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313213 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313217 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313219 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313220 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.3764 0.8878 0.216 0.784 0.000 0.000
#> SRR1313226 2 0.4818 0.8622 0.216 0.748 0.036 0.000
#> SRR1313227 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9111 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9111 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0898 0.946 0.000 0.000 0.008 0.972 0.020
#> SRR1313063 4 0.0898 0.946 0.000 0.000 0.008 0.972 0.020
#> SRR1313064 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313065 4 0.0609 0.952 0.020 0.000 0.000 0.980 0.000
#> SRR1313066 4 0.0290 0.953 0.008 0.000 0.000 0.992 0.000
#> SRR1313067 4 0.1012 0.945 0.000 0.000 0.012 0.968 0.020
#> SRR1313068 4 0.2144 0.903 0.000 0.000 0.068 0.912 0.020
#> SRR1313069 4 0.2280 0.870 0.120 0.000 0.000 0.880 0.000
#> SRR1313070 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313071 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313072 4 0.0290 0.953 0.008 0.000 0.000 0.992 0.000
#> SRR1313073 4 0.0162 0.952 0.004 0.000 0.000 0.996 0.000
#> SRR1313074 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313075 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313076 4 0.1117 0.943 0.000 0.000 0.016 0.964 0.020
#> SRR1313077 4 0.1012 0.945 0.000 0.000 0.012 0.968 0.020
#> SRR1313078 4 0.1012 0.945 0.000 0.000 0.012 0.968 0.020
#> SRR1313079 4 0.0290 0.953 0.008 0.000 0.000 0.992 0.000
#> SRR1313080 4 0.1943 0.914 0.000 0.000 0.056 0.924 0.020
#> SRR1313081 4 0.0898 0.946 0.000 0.000 0.008 0.972 0.020
#> SRR1313082 4 0.0609 0.952 0.020 0.000 0.000 0.980 0.000
#> SRR1313083 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313084 4 0.0290 0.953 0.008 0.000 0.000 0.992 0.000
#> SRR1313085 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313086 4 0.0703 0.950 0.024 0.000 0.000 0.976 0.000
#> SRR1313087 4 0.0162 0.952 0.004 0.000 0.000 0.996 0.000
#> SRR1313088 4 0.1043 0.940 0.040 0.000 0.000 0.960 0.000
#> SRR1313089 4 0.0510 0.953 0.016 0.000 0.000 0.984 0.000
#> SRR1313092 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313090 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313091 5 0.1026 0.948 0.000 0.004 0.024 0.004 0.968
#> SRR1313093 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313095 3 0.0771 0.945 0.000 0.000 0.976 0.004 0.020
#> SRR1313096 3 0.1012 0.942 0.000 0.000 0.968 0.012 0.020
#> SRR1313094 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313097 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313099 3 0.0566 0.949 0.000 0.000 0.984 0.004 0.012
#> SRR1313098 3 0.4821 0.125 0.000 0.000 0.516 0.464 0.020
#> SRR1313101 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313102 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0451 0.951 0.000 0.000 0.988 0.004 0.008
#> SRR1313100 3 0.1012 0.942 0.000 0.000 0.968 0.012 0.020
#> SRR1313105 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313104 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313106 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313109 5 0.3266 0.759 0.000 0.000 0.200 0.004 0.796
#> SRR1313108 3 0.0671 0.947 0.000 0.000 0.980 0.004 0.016
#> SRR1313111 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313110 3 0.1018 0.942 0.000 0.000 0.968 0.016 0.016
#> SRR1313112 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313113 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313115 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000
#> SRR1313114 3 0.1117 0.939 0.000 0.000 0.964 0.016 0.020
#> SRR1313117 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313118 3 0.1012 0.942 0.000 0.000 0.968 0.012 0.020
#> SRR1313116 5 0.0703 0.948 0.000 0.000 0.024 0.000 0.976
#> SRR1313120 3 0.0451 0.951 0.000 0.000 0.988 0.004 0.008
#> SRR1313119 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313122 3 0.1012 0.942 0.000 0.000 0.968 0.012 0.020
#> SRR1313124 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313121 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0162 0.955 0.000 0.000 0.996 0.000 0.004
#> SRR1313127 3 0.1117 0.939 0.000 0.000 0.964 0.016 0.020
#> SRR1313123 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313126 3 0.4651 0.393 0.000 0.000 0.608 0.372 0.020
#> SRR1313130 5 0.3333 0.747 0.000 0.000 0.208 0.004 0.788
#> SRR1313132 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313129 3 0.0290 0.953 0.000 0.000 0.992 0.000 0.008
#> SRR1313133 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313131 3 0.4639 0.403 0.000 0.000 0.612 0.368 0.020
#> SRR1313134 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313135 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313140 1 0.1043 0.950 0.960 0.000 0.000 0.040 0.000
#> SRR1313141 4 0.4211 0.478 0.360 0.000 0.000 0.636 0.004
#> SRR1313139 1 0.0162 0.984 0.996 0.000 0.000 0.004 0.000
#> SRR1313143 4 0.2338 0.882 0.112 0.000 0.000 0.884 0.004
#> SRR1313142 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313144 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313145 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313152 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313155 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0162 0.984 0.996 0.000 0.000 0.004 0.000
#> SRR1313159 1 0.0671 0.973 0.980 0.000 0.000 0.004 0.016
#> SRR1313160 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.2069 0.906 0.912 0.000 0.000 0.076 0.012
#> SRR1313163 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313164 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313167 1 0.3774 0.561 0.704 0.000 0.000 0.296 0.000
#> SRR1313168 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 5 0.3123 0.781 0.000 0.000 0.184 0.004 0.812
#> SRR1313169 1 0.0000 0.987 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 2 0.2054 0.907 0.000 0.916 0.072 0.008 0.004
#> SRR1313171 1 0.0162 0.985 0.996 0.000 0.000 0.000 0.004
#> SRR1313174 5 0.1043 0.966 0.000 0.040 0.000 0.000 0.960
#> SRR1313173 4 0.2144 0.903 0.000 0.000 0.068 0.912 0.020
#> SRR1313176 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313178 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0451 0.983 0.000 0.988 0.000 0.004 0.008
#> SRR1313180 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313181 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.2424 0.845 0.000 0.868 0.000 0.000 0.132
#> SRR1313184 2 0.0451 0.983 0.000 0.988 0.000 0.004 0.008
#> SRR1313185 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313188 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313187 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313186 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313189 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.0290 0.985 0.000 0.992 0.000 0.000 0.008
#> SRR1313192 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313195 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313196 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313197 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313198 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313199 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313201 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313203 4 0.4208 0.678 0.000 0.248 0.004 0.728 0.020
#> SRR1313204 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313209 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313211 5 0.0963 0.969 0.000 0.036 0.000 0.000 0.964
#> SRR1313212 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313215 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313213 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313217 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313219 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313220 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313222 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 5 0.0880 0.972 0.000 0.032 0.000 0.000 0.968
#> SRR1313226 5 0.0771 0.951 0.000 0.004 0.020 0.000 0.976
#> SRR1313227 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.992 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.3860 0.3281 0.000 0.000 0.000 0.528 0.000 0.472
#> SRR1313063 4 0.3862 0.3227 0.000 0.000 0.000 0.524 0.000 0.476
#> SRR1313064 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 4 0.0790 0.7458 0.032 0.000 0.000 0.968 0.000 0.000
#> SRR1313066 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 4 0.3860 0.3281 0.000 0.000 0.000 0.528 0.000 0.472
#> SRR1313068 4 0.4594 0.2298 0.000 0.000 0.036 0.488 0.000 0.476
#> SRR1313069 4 0.1501 0.7129 0.076 0.000 0.000 0.924 0.000 0.000
#> SRR1313070 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.0260 0.7577 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313074 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313075 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.4471 0.2606 0.000 0.000 0.028 0.500 0.000 0.472
#> SRR1313077 4 0.3860 0.3281 0.000 0.000 0.000 0.528 0.000 0.472
#> SRR1313078 4 0.3860 0.3281 0.000 0.000 0.000 0.528 0.000 0.472
#> SRR1313079 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.4534 0.2415 0.000 0.000 0.032 0.492 0.000 0.476
#> SRR1313081 4 0.3860 0.3281 0.000 0.000 0.000 0.528 0.000 0.472
#> SRR1313082 4 0.0547 0.7524 0.020 0.000 0.000 0.980 0.000 0.000
#> SRR1313083 4 0.0260 0.7580 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1313084 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 4 0.0790 0.7458 0.032 0.000 0.000 0.968 0.000 0.000
#> SRR1313087 4 0.0146 0.7590 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313088 4 0.0790 0.7458 0.032 0.000 0.000 0.968 0.000 0.000
#> SRR1313089 4 0.0000 0.7610 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313090 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313091 5 0.5699 0.3066 0.000 0.000 0.172 0.000 0.484 0.344
#> SRR1313093 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313095 3 0.3765 -0.1759 0.000 0.000 0.596 0.000 0.000 0.404
#> SRR1313096 3 0.3864 -0.3519 0.000 0.000 0.520 0.000 0.000 0.480
#> SRR1313094 3 0.0146 0.6552 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313097 3 0.2454 0.5827 0.000 0.000 0.840 0.000 0.000 0.160
#> SRR1313099 3 0.3620 0.4083 0.000 0.000 0.648 0.000 0.000 0.352
#> SRR1313098 6 0.5532 0.4681 0.000 0.000 0.384 0.136 0.000 0.480
#> SRR1313101 3 0.0146 0.6551 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313102 3 0.1610 0.6261 0.000 0.000 0.916 0.000 0.000 0.084
#> SRR1313103 3 0.3592 0.4172 0.000 0.000 0.656 0.000 0.000 0.344
#> SRR1313100 3 0.4091 -0.3574 0.000 0.000 0.520 0.008 0.000 0.472
#> SRR1313105 3 0.2048 0.6095 0.000 0.000 0.880 0.000 0.000 0.120
#> SRR1313104 3 0.0632 0.6401 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313107 3 0.2664 0.5644 0.000 0.000 0.816 0.000 0.000 0.184
#> SRR1313106 3 0.0458 0.6528 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313109 3 0.5523 0.2393 0.000 0.000 0.500 0.000 0.140 0.360
#> SRR1313108 3 0.3309 0.1984 0.000 0.000 0.720 0.000 0.000 0.280
#> SRR1313111 3 0.2048 0.6095 0.000 0.000 0.880 0.000 0.000 0.120
#> SRR1313110 3 0.4136 -0.2709 0.000 0.000 0.560 0.012 0.000 0.428
#> SRR1313112 3 0.0146 0.6551 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313113 3 0.1075 0.6425 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1313115 3 0.0632 0.6401 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313114 3 0.4089 -0.3478 0.000 0.000 0.524 0.008 0.000 0.468
#> SRR1313117 3 0.0146 0.6551 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313118 3 0.3989 -0.3374 0.000 0.000 0.528 0.004 0.000 0.468
#> SRR1313116 5 0.0937 0.9532 0.000 0.000 0.000 0.000 0.960 0.040
#> SRR1313120 3 0.3515 0.4380 0.000 0.000 0.676 0.000 0.000 0.324
#> SRR1313119 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313122 3 0.3862 -0.3443 0.000 0.000 0.524 0.000 0.000 0.476
#> SRR1313124 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313121 3 0.0363 0.6493 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313125 3 0.0000 0.6547 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313127 3 0.4089 -0.3478 0.000 0.000 0.524 0.008 0.000 0.468
#> SRR1313123 3 0.0146 0.6542 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313128 1 0.1124 0.9059 0.956 0.000 0.000 0.008 0.000 0.036
#> SRR1313126 6 0.4947 0.4105 0.000 0.000 0.456 0.064 0.000 0.480
#> SRR1313130 3 0.5659 0.2275 0.000 0.000 0.488 0.000 0.164 0.348
#> SRR1313132 1 0.3266 0.7644 0.728 0.000 0.000 0.000 0.000 0.272
#> SRR1313129 3 0.3409 0.4610 0.000 0.000 0.700 0.000 0.000 0.300
#> SRR1313133 1 0.2300 0.8622 0.856 0.000 0.000 0.000 0.000 0.144
#> SRR1313131 6 0.4990 0.4191 0.000 0.000 0.452 0.068 0.000 0.480
#> SRR1313134 1 0.1657 0.8889 0.928 0.000 0.000 0.056 0.000 0.016
#> SRR1313135 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313136 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313137 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313138 1 0.2454 0.8526 0.840 0.000 0.000 0.000 0.000 0.160
#> SRR1313140 1 0.3052 0.7202 0.780 0.000 0.000 0.216 0.000 0.004
#> SRR1313141 1 0.4646 0.0984 0.500 0.000 0.000 0.460 0.000 0.040
#> SRR1313139 1 0.1910 0.8502 0.892 0.000 0.000 0.108 0.000 0.000
#> SRR1313143 4 0.3351 0.6238 0.160 0.000 0.000 0.800 0.000 0.040
#> SRR1313142 1 0.1471 0.8972 0.932 0.000 0.000 0.004 0.000 0.064
#> SRR1313144 1 0.2454 0.8526 0.840 0.000 0.000 0.000 0.000 0.160
#> SRR1313145 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313146 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313147 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313150 1 0.0713 0.9047 0.972 0.000 0.000 0.000 0.000 0.028
#> SRR1313149 1 0.1444 0.8945 0.928 0.000 0.000 0.000 0.000 0.072
#> SRR1313152 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313151 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313154 1 0.0146 0.9099 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313153 1 0.2491 0.8511 0.836 0.000 0.000 0.000 0.000 0.164
#> SRR1313156 1 0.2454 0.8526 0.840 0.000 0.000 0.000 0.000 0.160
#> SRR1313155 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313157 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313158 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313161 1 0.1327 0.8887 0.936 0.000 0.000 0.064 0.000 0.000
#> SRR1313159 1 0.3979 0.5270 0.540 0.000 0.000 0.000 0.004 0.456
#> SRR1313160 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313162 1 0.3766 0.7055 0.684 0.000 0.000 0.012 0.000 0.304
#> SRR1313163 1 0.0000 0.9090 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313166 1 0.0458 0.9112 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313164 1 0.2527 0.8483 0.832 0.000 0.000 0.000 0.000 0.168
#> SRR1313167 4 0.3838 0.0498 0.448 0.000 0.000 0.552 0.000 0.000
#> SRR1313168 1 0.0363 0.9113 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313170 6 0.4789 -0.3297 0.016 0.000 0.448 0.000 0.024 0.512
#> SRR1313169 1 0.1007 0.8992 0.956 0.000 0.000 0.044 0.000 0.000
#> SRR1313172 2 0.1921 0.8793 0.000 0.916 0.052 0.000 0.000 0.032
#> SRR1313171 1 0.2260 0.8655 0.860 0.000 0.000 0.000 0.000 0.140
#> SRR1313174 5 0.0363 0.9641 0.000 0.012 0.000 0.000 0.988 0.000
#> SRR1313173 6 0.5750 0.1497 0.000 0.000 0.184 0.336 0.000 0.480
#> SRR1313176 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.4076 0.4654 0.008 0.540 0.000 0.000 0.000 0.452
#> SRR1313180 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313181 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.2941 0.7236 0.000 0.780 0.000 0.000 0.220 0.000
#> SRR1313184 2 0.3833 0.4867 0.000 0.556 0.000 0.000 0.000 0.444
#> SRR1313185 5 0.0363 0.9641 0.000 0.012 0.000 0.000 0.988 0.000
#> SRR1313188 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313187 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313186 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.3198 0.6626 0.000 0.740 0.000 0.000 0.260 0.000
#> SRR1313192 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313194 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313195 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313196 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313197 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313198 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313201 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0146 0.9717 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1313203 4 0.5951 0.2384 0.000 0.192 0.004 0.448 0.000 0.356
#> SRR1313204 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0363 0.9445 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313207 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0260 0.9472 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1313206 2 0.0146 0.9496 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313210 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313211 5 0.0632 0.9526 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313212 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313215 5 0.0260 0.9714 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1313213 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313217 5 0.0260 0.9714 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1313219 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.0790 0.9295 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313222 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 5 0.0000 0.9719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313226 5 0.0458 0.9701 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1313227 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9519 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "pam"]
# you can also extract it by
# res = res_list["CV:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 5.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.951 0.980 0.4485 0.544 0.544
#> 3 3 0.884 0.855 0.944 0.4841 0.734 0.534
#> 4 4 0.757 0.650 0.801 0.0978 0.903 0.721
#> 5 5 0.915 0.884 0.950 0.0878 0.887 0.615
#> 6 6 0.836 0.689 0.864 0.0277 0.986 0.934
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
#> attr(,"optional")
#> [1] 2
There is also optional best \(k\) = 2 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.993 1.000 0.000
#> SRR1313063 1 0.0000 0.993 1.000 0.000
#> SRR1313064 1 0.0000 0.993 1.000 0.000
#> SRR1313065 1 0.0000 0.993 1.000 0.000
#> SRR1313066 1 0.0000 0.993 1.000 0.000
#> SRR1313067 1 0.0000 0.993 1.000 0.000
#> SRR1313068 1 0.0000 0.993 1.000 0.000
#> SRR1313069 1 0.0000 0.993 1.000 0.000
#> SRR1313070 1 0.0000 0.993 1.000 0.000
#> SRR1313071 1 0.0000 0.993 1.000 0.000
#> SRR1313072 1 0.0000 0.993 1.000 0.000
#> SRR1313073 1 0.0000 0.993 1.000 0.000
#> SRR1313074 1 0.0000 0.993 1.000 0.000
#> SRR1313075 1 0.0000 0.993 1.000 0.000
#> SRR1313076 1 0.0000 0.993 1.000 0.000
#> SRR1313077 1 0.0000 0.993 1.000 0.000
#> SRR1313078 1 0.0000 0.993 1.000 0.000
#> SRR1313079 1 0.0000 0.993 1.000 0.000
#> SRR1313080 1 0.0000 0.993 1.000 0.000
#> SRR1313081 1 0.0000 0.993 1.000 0.000
#> SRR1313082 1 0.0000 0.993 1.000 0.000
#> SRR1313083 1 0.0000 0.993 1.000 0.000
#> SRR1313084 1 0.0000 0.993 1.000 0.000
#> SRR1313085 1 0.0000 0.993 1.000 0.000
#> SRR1313086 1 0.0000 0.993 1.000 0.000
#> SRR1313087 1 0.0000 0.993 1.000 0.000
#> SRR1313088 1 0.0000 0.993 1.000 0.000
#> SRR1313089 1 0.0000 0.993 1.000 0.000
#> SRR1313092 1 0.0000 0.993 1.000 0.000
#> SRR1313090 1 0.0000 0.993 1.000 0.000
#> SRR1313091 2 0.9522 0.453 0.372 0.628
#> SRR1313093 1 0.0000 0.993 1.000 0.000
#> SRR1313095 1 0.0000 0.993 1.000 0.000
#> SRR1313096 1 0.0000 0.993 1.000 0.000
#> SRR1313094 1 0.0000 0.993 1.000 0.000
#> SRR1313097 1 0.0000 0.993 1.000 0.000
#> SRR1313099 1 0.0000 0.993 1.000 0.000
#> SRR1313098 1 0.0000 0.993 1.000 0.000
#> SRR1313101 1 0.0000 0.993 1.000 0.000
#> SRR1313102 1 0.0000 0.993 1.000 0.000
#> SRR1313103 1 0.0000 0.993 1.000 0.000
#> SRR1313100 1 0.0000 0.993 1.000 0.000
#> SRR1313105 1 0.0000 0.993 1.000 0.000
#> SRR1313104 1 0.0000 0.993 1.000 0.000
#> SRR1313107 1 0.0000 0.993 1.000 0.000
#> SRR1313106 1 0.0000 0.993 1.000 0.000
#> SRR1313109 2 0.9954 0.222 0.460 0.540
#> SRR1313108 1 0.0000 0.993 1.000 0.000
#> SRR1313111 1 0.0000 0.993 1.000 0.000
#> SRR1313110 1 0.0000 0.993 1.000 0.000
#> SRR1313112 1 0.1184 0.977 0.984 0.016
#> SRR1313113 1 0.0000 0.993 1.000 0.000
#> SRR1313115 1 0.0000 0.993 1.000 0.000
#> SRR1313114 1 0.0000 0.993 1.000 0.000
#> SRR1313117 1 0.0000 0.993 1.000 0.000
#> SRR1313118 1 0.0000 0.993 1.000 0.000
#> SRR1313116 1 0.2948 0.937 0.948 0.052
#> SRR1313120 1 0.0000 0.993 1.000 0.000
#> SRR1313119 1 0.0000 0.993 1.000 0.000
#> SRR1313122 1 0.0000 0.993 1.000 0.000
#> SRR1313124 1 0.0000 0.993 1.000 0.000
#> SRR1313121 1 0.0000 0.993 1.000 0.000
#> SRR1313125 1 0.0000 0.993 1.000 0.000
#> SRR1313127 1 0.0000 0.993 1.000 0.000
#> SRR1313123 1 0.0000 0.993 1.000 0.000
#> SRR1313128 1 0.0000 0.993 1.000 0.000
#> SRR1313126 1 0.0000 0.993 1.000 0.000
#> SRR1313130 2 0.9954 0.222 0.460 0.540
#> SRR1313132 1 0.0000 0.993 1.000 0.000
#> SRR1313129 1 0.0000 0.993 1.000 0.000
#> SRR1313133 1 0.0000 0.993 1.000 0.000
#> SRR1313131 1 0.0000 0.993 1.000 0.000
#> SRR1313134 1 0.0000 0.993 1.000 0.000
#> SRR1313135 1 0.0000 0.993 1.000 0.000
#> SRR1313136 1 0.0000 0.993 1.000 0.000
#> SRR1313137 1 0.0000 0.993 1.000 0.000
#> SRR1313138 1 0.0000 0.993 1.000 0.000
#> SRR1313140 1 0.0000 0.993 1.000 0.000
#> SRR1313141 1 0.0000 0.993 1.000 0.000
#> SRR1313139 1 0.0000 0.993 1.000 0.000
#> SRR1313143 1 0.0000 0.993 1.000 0.000
#> SRR1313142 1 0.0000 0.993 1.000 0.000
#> SRR1313144 1 0.0000 0.993 1.000 0.000
#> SRR1313145 1 0.0000 0.993 1.000 0.000
#> SRR1313146 1 0.0000 0.993 1.000 0.000
#> SRR1313147 1 0.0000 0.993 1.000 0.000
#> SRR1313150 1 0.0000 0.993 1.000 0.000
#> SRR1313149 1 0.0000 0.993 1.000 0.000
#> SRR1313152 1 0.0000 0.993 1.000 0.000
#> SRR1313151 1 0.0000 0.993 1.000 0.000
#> SRR1313154 1 0.0000 0.993 1.000 0.000
#> SRR1313153 1 0.0000 0.993 1.000 0.000
#> SRR1313156 1 0.0000 0.993 1.000 0.000
#> SRR1313155 1 0.0000 0.993 1.000 0.000
#> SRR1313157 1 0.0000 0.993 1.000 0.000
#> SRR1313158 1 0.0000 0.993 1.000 0.000
#> SRR1313161 1 0.0000 0.993 1.000 0.000
#> SRR1313159 1 0.9044 0.503 0.680 0.320
#> SRR1313160 1 0.0000 0.993 1.000 0.000
#> SRR1313162 1 0.0000 0.993 1.000 0.000
#> SRR1313163 1 0.0000 0.993 1.000 0.000
#> SRR1313165 1 0.0000 0.993 1.000 0.000
#> SRR1313166 1 0.0000 0.993 1.000 0.000
#> SRR1313164 1 0.0000 0.993 1.000 0.000
#> SRR1313167 1 0.0000 0.993 1.000 0.000
#> SRR1313168 1 0.0000 0.993 1.000 0.000
#> SRR1313170 1 0.0672 0.985 0.992 0.008
#> SRR1313169 1 0.0000 0.993 1.000 0.000
#> SRR1313172 1 0.8386 0.613 0.732 0.268
#> SRR1313171 1 0.0000 0.993 1.000 0.000
#> SRR1313174 2 0.0000 0.953 0.000 1.000
#> SRR1313173 1 0.0000 0.993 1.000 0.000
#> SRR1313176 2 0.0000 0.953 0.000 1.000
#> SRR1313175 2 0.0000 0.953 0.000 1.000
#> SRR1313178 2 0.0000 0.953 0.000 1.000
#> SRR1313177 2 0.0000 0.953 0.000 1.000
#> SRR1313179 2 0.0938 0.943 0.012 0.988
#> SRR1313180 2 0.8861 0.588 0.304 0.696
#> SRR1313181 2 0.0000 0.953 0.000 1.000
#> SRR1313183 2 0.0000 0.953 0.000 1.000
#> SRR1313182 2 0.0000 0.953 0.000 1.000
#> SRR1313184 2 0.8081 0.679 0.248 0.752
#> SRR1313185 2 0.0000 0.953 0.000 1.000
#> SRR1313188 2 0.0000 0.953 0.000 1.000
#> SRR1313187 2 0.9248 0.521 0.340 0.660
#> SRR1313186 2 0.0000 0.953 0.000 1.000
#> SRR1313189 2 0.0000 0.953 0.000 1.000
#> SRR1313190 2 0.0000 0.953 0.000 1.000
#> SRR1313191 2 0.0000 0.953 0.000 1.000
#> SRR1313192 2 0.0000 0.953 0.000 1.000
#> SRR1313193 2 0.0000 0.953 0.000 1.000
#> SRR1313194 2 0.0000 0.953 0.000 1.000
#> SRR1313195 2 0.0000 0.953 0.000 1.000
#> SRR1313196 2 0.0000 0.953 0.000 1.000
#> SRR1313197 2 0.0000 0.953 0.000 1.000
#> SRR1313198 2 0.0000 0.953 0.000 1.000
#> SRR1313199 2 0.0000 0.953 0.000 1.000
#> SRR1313200 2 0.0000 0.953 0.000 1.000
#> SRR1313201 2 0.0000 0.953 0.000 1.000
#> SRR1313202 2 0.0000 0.953 0.000 1.000
#> SRR1313203 1 0.0376 0.990 0.996 0.004
#> SRR1313204 2 0.0000 0.953 0.000 1.000
#> SRR1313205 2 0.0000 0.953 0.000 1.000
#> SRR1313207 2 0.0000 0.953 0.000 1.000
#> SRR1313208 2 0.0000 0.953 0.000 1.000
#> SRR1313206 2 0.0000 0.953 0.000 1.000
#> SRR1313210 2 0.0000 0.953 0.000 1.000
#> SRR1313209 2 0.0000 0.953 0.000 1.000
#> SRR1313211 2 0.0000 0.953 0.000 1.000
#> SRR1313212 2 0.0000 0.953 0.000 1.000
#> SRR1313214 2 0.0000 0.953 0.000 1.000
#> SRR1313215 2 0.0000 0.953 0.000 1.000
#> SRR1313213 2 0.0000 0.953 0.000 1.000
#> SRR1313216 2 0.0000 0.953 0.000 1.000
#> SRR1313217 2 0.0000 0.953 0.000 1.000
#> SRR1313219 2 0.0000 0.953 0.000 1.000
#> SRR1313220 2 0.0000 0.953 0.000 1.000
#> SRR1313218 2 0.0000 0.953 0.000 1.000
#> SRR1313222 2 0.0000 0.953 0.000 1.000
#> SRR1313221 2 0.0000 0.953 0.000 1.000
#> SRR1313223 2 0.0000 0.953 0.000 1.000
#> SRR1313224 2 0.0000 0.953 0.000 1.000
#> SRR1313225 2 0.0000 0.953 0.000 1.000
#> SRR1313226 2 0.9954 0.222 0.460 0.540
#> SRR1313227 2 0.0000 0.953 0.000 1.000
#> SRR1313228 2 0.0000 0.953 0.000 1.000
#> SRR1313229 2 0.0000 0.953 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.6225 0.256 0.432 0.000 0.568
#> SRR1313063 3 0.6168 0.310 0.412 0.000 0.588
#> SRR1313064 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313066 1 0.6280 0.103 0.540 0.000 0.460
#> SRR1313067 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313068 3 0.0424 0.887 0.008 0.000 0.992
#> SRR1313069 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313072 1 0.1163 0.908 0.972 0.000 0.028
#> SRR1313073 1 0.6244 0.169 0.560 0.000 0.440
#> SRR1313074 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313076 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313077 3 0.6225 0.256 0.432 0.000 0.568
#> SRR1313078 3 0.6215 0.268 0.428 0.000 0.572
#> SRR1313079 1 0.6192 0.229 0.580 0.000 0.420
#> SRR1313080 3 0.0892 0.878 0.020 0.000 0.980
#> SRR1313081 3 0.6267 0.194 0.452 0.000 0.548
#> SRR1313082 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313084 1 0.6260 0.145 0.552 0.000 0.448
#> SRR1313085 1 0.0592 0.920 0.988 0.000 0.012
#> SRR1313086 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313087 1 0.6260 0.145 0.552 0.000 0.448
#> SRR1313088 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313089 1 0.2165 0.874 0.936 0.000 0.064
#> SRR1313092 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313091 3 0.4121 0.747 0.000 0.168 0.832
#> SRR1313093 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313096 3 0.1289 0.869 0.032 0.000 0.968
#> SRR1313094 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313098 3 0.6192 0.289 0.420 0.000 0.580
#> SRR1313101 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313100 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313105 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313109 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313108 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313116 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313128 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313126 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313130 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313132 1 0.0237 0.926 0.996 0.000 0.004
#> SRR1313129 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313133 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313131 3 0.6140 0.330 0.404 0.000 0.596
#> SRR1313134 1 0.6260 0.145 0.552 0.000 0.448
#> SRR1313135 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313136 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313137 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313138 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313140 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313141 1 0.0424 0.923 0.992 0.000 0.008
#> SRR1313139 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313143 1 0.1860 0.886 0.948 0.000 0.052
#> SRR1313142 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313144 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313145 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313146 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313147 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313149 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313152 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313151 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313154 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313153 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313156 1 0.0237 0.926 0.996 0.000 0.004
#> SRR1313155 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313157 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313158 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313161 1 0.1289 0.904 0.968 0.000 0.032
#> SRR1313159 1 0.2280 0.882 0.940 0.008 0.052
#> SRR1313160 1 0.1964 0.880 0.944 0.000 0.056
#> SRR1313162 3 0.6291 0.140 0.468 0.000 0.532
#> SRR1313163 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313165 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313166 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313164 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313167 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313170 3 0.0000 0.892 0.000 0.000 1.000
#> SRR1313169 1 0.0000 0.928 1.000 0.000 0.000
#> SRR1313172 3 0.9738 0.251 0.304 0.252 0.444
#> SRR1313171 1 0.6274 0.117 0.544 0.000 0.456
#> SRR1313174 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313173 3 0.6192 0.289 0.420 0.000 0.580
#> SRR1313176 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313179 2 0.5874 0.700 0.032 0.760 0.208
#> SRR1313180 3 0.5327 0.594 0.000 0.272 0.728
#> SRR1313181 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313184 3 0.5178 0.610 0.000 0.256 0.744
#> SRR1313185 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313187 3 0.4062 0.745 0.000 0.164 0.836
#> SRR1313186 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313203 3 0.6183 0.631 0.236 0.032 0.732
#> SRR1313204 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313226 3 0.0424 0.887 0.000 0.008 0.992
#> SRR1313227 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.995 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.995 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.6371 0.6455 0.428 0.000 0.064 0.508
#> SRR1313063 4 0.6709 0.6273 0.400 0.000 0.092 0.508
#> SRR1313064 4 0.4999 0.6238 0.492 0.000 0.000 0.508
#> SRR1313065 1 0.5713 -0.2873 0.604 0.000 0.036 0.360
#> SRR1313066 1 0.6795 -0.5733 0.472 0.000 0.096 0.432
#> SRR1313067 4 0.4999 0.0419 0.000 0.000 0.492 0.508
#> SRR1313068 4 0.5406 0.0807 0.012 0.000 0.480 0.508
#> SRR1313069 1 0.4989 -0.5626 0.528 0.000 0.000 0.472
#> SRR1313070 4 0.5000 0.6158 0.496 0.000 0.000 0.504
#> SRR1313071 1 0.4994 -0.5838 0.520 0.000 0.000 0.480
#> SRR1313072 4 0.5294 0.6352 0.484 0.000 0.008 0.508
#> SRR1313073 4 0.5406 0.6391 0.480 0.000 0.012 0.508
#> SRR1313074 4 0.4999 0.6238 0.492 0.000 0.000 0.508
#> SRR1313075 4 0.4999 0.6238 0.492 0.000 0.000 0.508
#> SRR1313076 4 0.4999 0.0419 0.000 0.000 0.492 0.508
#> SRR1313077 4 0.6575 0.6384 0.412 0.000 0.080 0.508
#> SRR1313078 4 0.6575 0.6384 0.412 0.000 0.080 0.508
#> SRR1313079 4 0.5294 0.6355 0.484 0.000 0.008 0.508
#> SRR1313080 4 0.5602 0.1035 0.020 0.000 0.472 0.508
#> SRR1313081 4 0.6425 0.6441 0.424 0.000 0.068 0.508
#> SRR1313082 1 0.4790 -0.2662 0.620 0.000 0.000 0.380
#> SRR1313083 1 0.1302 0.7445 0.956 0.000 0.000 0.044
#> SRR1313084 4 0.5691 0.6435 0.468 0.000 0.024 0.508
#> SRR1313085 4 0.5000 0.6158 0.496 0.000 0.000 0.504
#> SRR1313086 1 0.4888 -0.3832 0.588 0.000 0.000 0.412
#> SRR1313087 4 0.5508 0.6412 0.476 0.000 0.016 0.508
#> SRR1313088 1 0.4925 -0.4333 0.572 0.000 0.000 0.428
#> SRR1313089 4 0.4999 0.6238 0.492 0.000 0.000 0.508
#> SRR1313092 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.4843 0.4331 0.000 0.396 0.604 0.000
#> SRR1313093 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313096 3 0.0817 0.8641 0.024 0.000 0.976 0.000
#> SRR1313094 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.6672 -0.1229 0.408 0.000 0.504 0.088
#> SRR1313101 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313108 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313111 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0817 0.8674 0.000 0.000 0.976 0.024
#> SRR1313112 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.1211 0.8525 0.000 0.000 0.960 0.040
#> SRR1313116 3 0.4999 0.2750 0.000 0.492 0.508 0.000
#> SRR1313120 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0188 0.8823 0.000 0.000 0.996 0.004
#> SRR1313123 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.0592 0.8735 0.000 0.000 0.984 0.016
#> SRR1313130 3 0.2345 0.8059 0.000 0.100 0.900 0.000
#> SRR1313132 1 0.0336 0.7846 0.992 0.000 0.008 0.000
#> SRR1313129 3 0.0000 0.8852 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313131 3 0.4804 0.1805 0.384 0.000 0.616 0.000
#> SRR1313134 1 0.4996 -0.0256 0.516 0.000 0.484 0.000
#> SRR1313135 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313141 1 0.1488 0.7485 0.956 0.000 0.012 0.032
#> SRR1313139 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313143 1 0.6764 -0.3438 0.556 0.000 0.112 0.332
#> SRR1313142 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313149 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313152 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0188 0.7885 0.996 0.000 0.004 0.000
#> SRR1313155 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0937 0.7717 0.976 0.000 0.012 0.012
#> SRR1313159 1 0.6323 0.1433 0.500 0.440 0.060 0.000
#> SRR1313160 1 0.0817 0.7607 0.976 0.000 0.024 0.000
#> SRR1313162 3 0.6148 -0.1263 0.468 0.000 0.484 0.048
#> SRR1313163 1 0.0188 0.7885 0.996 0.004 0.000 0.000
#> SRR1313165 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313167 1 0.0188 0.7892 0.996 0.000 0.000 0.004
#> SRR1313168 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313170 3 0.3157 0.7388 0.144 0.004 0.852 0.000
#> SRR1313169 1 0.0000 0.7929 1.000 0.000 0.000 0.000
#> SRR1313172 3 0.8625 0.0526 0.280 0.252 0.428 0.040
#> SRR1313171 1 0.4134 0.3496 0.740 0.000 0.260 0.000
#> SRR1313174 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.7803 -0.3180 0.404 0.000 0.340 0.256
#> SRR1313176 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313175 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313177 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313179 2 0.8273 0.5997 0.032 0.468 0.196 0.304
#> SRR1313180 2 0.4543 0.2400 0.000 0.676 0.324 0.000
#> SRR1313181 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313183 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313182 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313184 3 0.6788 0.3983 0.004 0.200 0.624 0.172
#> SRR1313185 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.4843 0.0241 0.000 0.604 0.396 0.000
#> SRR1313186 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313190 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313191 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.4967 0.7542 0.000 0.548 0.000 0.452
#> SRR1313193 2 0.3975 0.7619 0.000 0.760 0.000 0.240
#> SRR1313194 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313200 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313202 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313203 3 0.4464 0.5578 0.224 0.012 0.760 0.004
#> SRR1313204 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313205 2 0.4955 0.7545 0.000 0.556 0.000 0.444
#> SRR1313207 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313208 2 0.4994 0.7517 0.000 0.520 0.000 0.480
#> SRR1313206 2 0.4998 0.7510 0.000 0.512 0.000 0.488
#> SRR1313210 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.2281 0.7630 0.000 0.904 0.000 0.096
#> SRR1313212 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313214 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313216 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313218 2 0.2760 0.7640 0.000 0.872 0.000 0.128
#> SRR1313222 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313221 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313223 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313224 2 0.2408 0.7634 0.000 0.896 0.000 0.104
#> SRR1313225 2 0.0000 0.7587 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.4999 0.2750 0.000 0.492 0.508 0.000
#> SRR1313227 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313228 2 0.4999 0.7505 0.000 0.508 0.000 0.492
#> SRR1313229 2 0.4999 0.7505 0.000 0.508 0.000 0.492
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0162 0.9122 0.000 0.000 0.004 0.996 0.000
#> SRR1313063 4 0.0290 0.9124 0.000 0.000 0.008 0.992 0.000
#> SRR1313064 4 0.0000 0.9114 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 1 0.5157 0.0260 0.520 0.000 0.040 0.440 0.000
#> SRR1313066 4 0.2922 0.8616 0.056 0.000 0.072 0.872 0.000
#> SRR1313067 4 0.0404 0.9107 0.000 0.000 0.012 0.988 0.000
#> SRR1313068 4 0.0609 0.9081 0.000 0.000 0.020 0.980 0.000
#> SRR1313069 4 0.2852 0.7894 0.172 0.000 0.000 0.828 0.000
#> SRR1313070 4 0.1341 0.9015 0.056 0.000 0.000 0.944 0.000
#> SRR1313071 4 0.2424 0.8445 0.132 0.000 0.000 0.868 0.000
#> SRR1313072 4 0.1197 0.9053 0.048 0.000 0.000 0.952 0.000
#> SRR1313073 4 0.0162 0.9123 0.004 0.000 0.000 0.996 0.000
#> SRR1313074 4 0.0794 0.9108 0.028 0.000 0.000 0.972 0.000
#> SRR1313075 4 0.0703 0.9120 0.024 0.000 0.000 0.976 0.000
#> SRR1313076 4 0.0404 0.9107 0.000 0.000 0.012 0.988 0.000
#> SRR1313077 4 0.0290 0.9124 0.000 0.000 0.008 0.992 0.000
#> SRR1313078 4 0.0290 0.9124 0.000 0.000 0.008 0.992 0.000
#> SRR1313079 4 0.0000 0.9114 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.0290 0.9124 0.000 0.000 0.008 0.992 0.000
#> SRR1313081 4 0.0290 0.9124 0.000 0.000 0.008 0.992 0.000
#> SRR1313082 1 0.4150 0.3035 0.612 0.000 0.000 0.388 0.000
#> SRR1313083 1 0.1671 0.8967 0.924 0.000 0.000 0.076 0.000
#> SRR1313084 4 0.1270 0.9039 0.052 0.000 0.000 0.948 0.000
#> SRR1313085 4 0.1270 0.9037 0.052 0.000 0.000 0.948 0.000
#> SRR1313086 4 0.3932 0.5609 0.328 0.000 0.000 0.672 0.000
#> SRR1313087 4 0.0000 0.9114 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.4242 0.3058 0.428 0.000 0.000 0.572 0.000
#> SRR1313089 4 0.1043 0.9084 0.040 0.000 0.000 0.960 0.000
#> SRR1313092 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 3 0.4088 0.4366 0.000 0.000 0.632 0.000 0.368
#> SRR1313093 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313095 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313096 3 0.0609 0.9200 0.020 0.000 0.980 0.000 0.000
#> SRR1313094 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313098 3 0.4305 0.0801 0.000 0.000 0.512 0.488 0.000
#> SRR1313101 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.0404 0.9268 0.000 0.000 0.988 0.012 0.000
#> SRR1313105 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313106 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313109 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313108 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313111 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.1908 0.8627 0.000 0.000 0.908 0.092 0.000
#> SRR1313112 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313114 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.1671 0.8770 0.000 0.000 0.924 0.076 0.000
#> SRR1313116 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313119 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313124 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0290 0.9285 0.000 0.000 0.992 0.008 0.000
#> SRR1313123 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313126 3 0.2605 0.7977 0.000 0.000 0.852 0.148 0.000
#> SRR1313130 3 0.4306 0.0578 0.000 0.000 0.508 0.000 0.492
#> SRR1313132 1 0.0771 0.9448 0.976 0.000 0.020 0.004 0.000
#> SRR1313129 3 0.0000 0.9329 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313131 3 0.1124 0.9036 0.036 0.000 0.960 0.004 0.000
#> SRR1313134 3 0.2536 0.8184 0.128 0.000 0.868 0.004 0.000
#> SRR1313135 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313141 1 0.3141 0.8152 0.852 0.000 0.040 0.108 0.000
#> SRR1313139 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313143 4 0.5076 0.6976 0.200 0.000 0.108 0.692 0.000
#> SRR1313142 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313144 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313152 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313154 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313153 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0324 0.9604 0.992 0.000 0.004 0.004 0.000
#> SRR1313155 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313161 1 0.0510 0.9524 0.984 0.000 0.000 0.016 0.000
#> SRR1313159 5 0.3913 0.5189 0.324 0.000 0.000 0.000 0.676
#> SRR1313160 1 0.0579 0.9549 0.984 0.000 0.008 0.008 0.000
#> SRR1313162 3 0.4761 0.6756 0.124 0.000 0.732 0.144 0.000
#> SRR1313163 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313164 1 0.0162 0.9628 0.996 0.000 0.000 0.004 0.000
#> SRR1313167 1 0.0290 0.9593 0.992 0.000 0.000 0.008 0.000
#> SRR1313168 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.4157 0.6169 0.020 0.000 0.716 0.000 0.264
#> SRR1313169 1 0.0000 0.9643 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 3 0.2285 0.8785 0.024 0.052 0.916 0.004 0.004
#> SRR1313171 3 0.3906 0.5926 0.292 0.000 0.704 0.004 0.000
#> SRR1313174 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313173 4 0.4550 0.5861 0.036 0.000 0.276 0.688 0.000
#> SRR1313176 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313178 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.5268 0.6712 0.024 0.704 0.200 0.000 0.072
#> SRR1313180 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313181 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 5 0.0162 0.9618 0.000 0.004 0.000 0.000 0.996
#> SRR1313184 2 0.4415 0.2064 0.004 0.552 0.444 0.000 0.000
#> SRR1313185 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313188 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313187 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313186 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313189 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313192 2 0.1270 0.9098 0.000 0.948 0.000 0.000 0.052
#> SRR1313193 2 0.3932 0.4878 0.000 0.672 0.000 0.000 0.328
#> SRR1313194 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313195 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313196 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313197 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313198 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313199 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313201 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313203 3 0.0981 0.9189 0.012 0.000 0.972 0.008 0.008
#> SRR1313204 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.1732 0.8830 0.000 0.920 0.000 0.000 0.080
#> SRR1313207 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0510 0.9382 0.000 0.984 0.000 0.000 0.016
#> SRR1313206 2 0.0162 0.9464 0.000 0.996 0.000 0.000 0.004
#> SRR1313210 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313209 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313211 5 0.2179 0.8549 0.000 0.112 0.000 0.000 0.888
#> SRR1313212 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313215 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313213 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313217 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313219 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313220 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 5 0.2773 0.7929 0.000 0.164 0.000 0.000 0.836
#> SRR1313222 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 5 0.3949 0.4935 0.000 0.332 0.000 0.000 0.668
#> SRR1313225 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313226 5 0.0000 0.9650 0.000 0.000 0.000 0.000 1.000
#> SRR1313227 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9489 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0146 0.5249 0.000 0.000 0.004 0.996 0.000 0.000
#> SRR1313063 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313064 4 0.1327 0.4778 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1313065 1 0.6579 -0.0877 0.476 0.000 0.096 0.324 0.000 0.104
#> SRR1313066 4 0.3971 -0.3373 0.000 0.000 0.004 0.548 0.000 0.448
#> SRR1313067 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313068 4 0.0547 0.5189 0.000 0.000 0.020 0.980 0.000 0.000
#> SRR1313069 4 0.3718 0.1973 0.084 0.000 0.000 0.784 0.000 0.132
#> SRR1313070 4 0.3864 -0.4672 0.000 0.000 0.000 0.520 0.000 0.480
#> SRR1313071 6 0.4335 0.2753 0.020 0.000 0.000 0.472 0.000 0.508
#> SRR1313072 4 0.3833 -0.3180 0.000 0.000 0.000 0.556 0.000 0.444
#> SRR1313073 4 0.0363 0.5179 0.000 0.000 0.000 0.988 0.000 0.012
#> SRR1313074 4 0.3531 -0.0171 0.000 0.000 0.000 0.672 0.000 0.328
#> SRR1313075 4 0.4168 -0.2283 0.016 0.000 0.000 0.584 0.000 0.400
#> SRR1313076 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313077 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313078 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313079 4 0.2491 0.3502 0.000 0.000 0.000 0.836 0.000 0.164
#> SRR1313080 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313081 4 0.0260 0.5277 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1313082 1 0.5709 -0.4313 0.452 0.000 0.000 0.164 0.000 0.384
#> SRR1313083 1 0.4125 0.5808 0.736 0.000 0.000 0.080 0.000 0.184
#> SRR1313084 4 0.3838 -0.3325 0.000 0.000 0.000 0.552 0.000 0.448
#> SRR1313085 4 0.3864 -0.4635 0.000 0.000 0.000 0.520 0.000 0.480
#> SRR1313086 4 0.5984 -0.3896 0.280 0.000 0.000 0.444 0.000 0.276
#> SRR1313087 4 0.0547 0.5122 0.000 0.000 0.000 0.980 0.000 0.020
#> SRR1313088 6 0.5714 0.4756 0.196 0.000 0.000 0.296 0.000 0.508
#> SRR1313089 4 0.4109 -0.2542 0.012 0.000 0.000 0.576 0.000 0.412
#> SRR1313092 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313090 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313091 3 0.3992 0.4225 0.000 0.000 0.624 0.000 0.364 0.012
#> SRR1313093 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313095 3 0.0146 0.9113 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1313096 3 0.1010 0.8891 0.000 0.000 0.960 0.004 0.000 0.036
#> SRR1313094 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313097 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313099 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313098 4 0.3851 0.0874 0.000 0.000 0.460 0.540 0.000 0.000
#> SRR1313101 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313103 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313100 3 0.0363 0.9071 0.000 0.000 0.988 0.012 0.000 0.000
#> SRR1313105 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313104 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313106 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313109 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313108 3 0.0146 0.9113 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1313111 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313110 3 0.1663 0.8435 0.000 0.000 0.912 0.088 0.000 0.000
#> SRR1313112 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313115 3 0.0146 0.9113 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1313114 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313117 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.1663 0.8441 0.000 0.000 0.912 0.088 0.000 0.000
#> SRR1313116 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313120 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313119 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313122 3 0.0146 0.9113 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1313124 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313121 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313125 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313127 3 0.0458 0.9048 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1313123 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313128 1 0.3390 0.7359 0.704 0.000 0.000 0.000 0.000 0.296
#> SRR1313126 3 0.2048 0.8088 0.000 0.000 0.880 0.120 0.000 0.000
#> SRR1313130 3 0.3868 0.0617 0.000 0.000 0.508 0.000 0.492 0.000
#> SRR1313132 1 0.3774 0.6632 0.592 0.000 0.000 0.000 0.000 0.408
#> SRR1313129 3 0.0000 0.9130 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313133 1 0.3634 0.7032 0.644 0.000 0.000 0.000 0.000 0.356
#> SRR1313131 3 0.1082 0.8850 0.000 0.000 0.956 0.004 0.000 0.040
#> SRR1313134 3 0.4064 0.6421 0.040 0.000 0.720 0.004 0.000 0.236
#> SRR1313135 1 0.2048 0.8090 0.880 0.000 0.000 0.000 0.000 0.120
#> SRR1313136 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.3198 0.7296 0.740 0.000 0.000 0.000 0.000 0.260
#> SRR1313140 1 0.2260 0.7892 0.860 0.000 0.000 0.000 0.000 0.140
#> SRR1313141 1 0.3915 0.7282 0.696 0.000 0.012 0.008 0.000 0.284
#> SRR1313139 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313143 4 0.7545 -0.1969 0.172 0.000 0.212 0.348 0.000 0.268
#> SRR1313142 1 0.3774 0.6632 0.592 0.000 0.000 0.000 0.000 0.408
#> SRR1313144 1 0.3647 0.6919 0.640 0.000 0.000 0.000 0.000 0.360
#> SRR1313145 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.1007 0.8158 0.956 0.000 0.000 0.000 0.000 0.044
#> SRR1313147 1 0.0632 0.8188 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313150 1 0.1267 0.8148 0.940 0.000 0.000 0.000 0.000 0.060
#> SRR1313149 1 0.3742 0.7060 0.648 0.000 0.000 0.004 0.000 0.348
#> SRR1313152 1 0.0937 0.8174 0.960 0.000 0.000 0.000 0.000 0.040
#> SRR1313151 1 0.2178 0.7935 0.868 0.000 0.000 0.000 0.000 0.132
#> SRR1313154 1 0.2697 0.7820 0.812 0.000 0.000 0.000 0.000 0.188
#> SRR1313153 1 0.3464 0.7126 0.688 0.000 0.000 0.000 0.000 0.312
#> SRR1313156 1 0.3852 0.6777 0.612 0.000 0.004 0.000 0.000 0.384
#> SRR1313155 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.2048 0.8032 0.880 0.000 0.000 0.000 0.000 0.120
#> SRR1313161 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313159 5 0.6029 -0.0398 0.256 0.000 0.000 0.000 0.412 0.332
#> SRR1313160 1 0.1007 0.8134 0.956 0.000 0.000 0.000 0.000 0.044
#> SRR1313162 3 0.4884 0.4130 0.048 0.000 0.564 0.008 0.000 0.380
#> SRR1313163 1 0.0547 0.8200 0.980 0.000 0.000 0.000 0.000 0.020
#> SRR1313165 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0865 0.8137 0.964 0.000 0.000 0.000 0.000 0.036
#> SRR1313164 1 0.3774 0.6632 0.592 0.000 0.000 0.000 0.000 0.408
#> SRR1313167 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.8174 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.5962 0.3067 0.004 0.000 0.488 0.000 0.248 0.260
#> SRR1313169 1 0.0363 0.8191 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313172 3 0.3114 0.7778 0.000 0.036 0.832 0.000 0.004 0.128
#> SRR1313171 3 0.5619 0.3649 0.188 0.000 0.560 0.004 0.000 0.248
#> SRR1313174 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313173 4 0.4493 0.1056 0.000 0.000 0.364 0.596 0.000 0.040
#> SRR1313176 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.6866 0.3793 0.000 0.416 0.080 0.000 0.164 0.340
#> SRR1313180 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 5 0.2854 0.7683 0.000 0.000 0.000 0.000 0.792 0.208
#> SRR1313184 3 0.5565 0.1750 0.000 0.340 0.508 0.000 0.000 0.152
#> SRR1313185 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313188 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313187 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313186 5 0.2823 0.7719 0.000 0.000 0.000 0.000 0.796 0.204
#> SRR1313189 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.0713 0.8998 0.000 0.000 0.000 0.000 0.972 0.028
#> SRR1313192 2 0.3924 0.8297 0.000 0.740 0.000 0.000 0.052 0.208
#> SRR1313193 2 0.5651 0.5323 0.000 0.532 0.000 0.000 0.260 0.208
#> SRR1313194 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313195 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313196 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313197 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313198 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313199 2 0.2762 0.8622 0.000 0.804 0.000 0.000 0.000 0.196
#> SRR1313200 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313201 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313202 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313203 3 0.1036 0.8940 0.000 0.000 0.964 0.004 0.008 0.024
#> SRR1313204 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313205 2 0.4300 0.8060 0.000 0.712 0.000 0.000 0.080 0.208
#> SRR1313207 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.3290 0.8536 0.000 0.776 0.000 0.000 0.016 0.208
#> SRR1313206 2 0.2994 0.8593 0.000 0.788 0.000 0.000 0.004 0.208
#> SRR1313210 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313211 5 0.4349 0.6627 0.000 0.084 0.000 0.000 0.708 0.208
#> SRR1313212 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313214 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313215 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313217 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313219 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313220 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313218 5 0.4734 0.6070 0.000 0.120 0.000 0.000 0.672 0.208
#> SRR1313222 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313224 5 0.5486 0.3803 0.000 0.224 0.000 0.000 0.568 0.208
#> SRR1313225 5 0.2854 0.7683 0.000 0.000 0.000 0.000 0.792 0.208
#> SRR1313226 5 0.0000 0.9167 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313227 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313228 2 0.2854 0.8609 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1313229 2 0.0000 0.8611 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "mclust"]
# you can also extract it by
# res = res_list["CV:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.369 0.789 0.848 0.4672 0.537 0.537
#> 3 3 1.000 0.964 0.985 0.4295 0.757 0.563
#> 4 4 0.871 0.910 0.910 0.0849 0.950 0.848
#> 5 5 0.810 0.815 0.887 0.0561 0.953 0.837
#> 6 6 0.777 0.686 0.825 0.0470 0.928 0.721
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.7733 1.000 0.000
#> SRR1313063 1 0.0000 0.7733 1.000 0.000
#> SRR1313064 1 0.7883 0.7966 0.764 0.236
#> SRR1313065 1 0.7883 0.7966 0.764 0.236
#> SRR1313066 1 0.7883 0.7966 0.764 0.236
#> SRR1313067 1 0.0000 0.7733 1.000 0.000
#> SRR1313068 1 0.0000 0.7733 1.000 0.000
#> SRR1313069 1 0.9044 0.7633 0.680 0.320
#> SRR1313070 1 0.7883 0.7966 0.764 0.236
#> SRR1313071 1 0.7883 0.7966 0.764 0.236
#> SRR1313072 1 0.7883 0.7966 0.764 0.236
#> SRR1313073 1 0.7745 0.7966 0.772 0.228
#> SRR1313074 1 0.7883 0.7966 0.764 0.236
#> SRR1313075 1 0.7883 0.7966 0.764 0.236
#> SRR1313076 1 0.0000 0.7733 1.000 0.000
#> SRR1313077 1 0.0000 0.7733 1.000 0.000
#> SRR1313078 1 0.0000 0.7733 1.000 0.000
#> SRR1313079 1 0.7883 0.7966 0.764 0.236
#> SRR1313080 1 0.0000 0.7733 1.000 0.000
#> SRR1313081 1 0.0000 0.7733 1.000 0.000
#> SRR1313082 1 0.7883 0.7966 0.764 0.236
#> SRR1313083 1 0.8267 0.7893 0.740 0.260
#> SRR1313084 1 0.7745 0.7966 0.772 0.228
#> SRR1313085 1 0.7883 0.7966 0.764 0.236
#> SRR1313086 1 0.7883 0.7966 0.764 0.236
#> SRR1313087 1 0.7745 0.7966 0.772 0.228
#> SRR1313088 1 0.7883 0.7966 0.764 0.236
#> SRR1313089 1 0.7883 0.7966 0.764 0.236
#> SRR1313092 1 0.1633 0.7657 0.976 0.024
#> SRR1313090 1 0.1843 0.7637 0.972 0.028
#> SRR1313091 2 0.7602 0.7821 0.220 0.780
#> SRR1313093 1 0.1633 0.7657 0.976 0.024
#> SRR1313095 1 0.0000 0.7733 1.000 0.000
#> SRR1313096 1 0.0000 0.7733 1.000 0.000
#> SRR1313094 1 0.1633 0.7657 0.976 0.024
#> SRR1313097 1 0.2778 0.7513 0.952 0.048
#> SRR1313099 2 0.9323 0.6190 0.348 0.652
#> SRR1313098 1 0.0376 0.7745 0.996 0.004
#> SRR1313101 1 0.2778 0.7513 0.952 0.048
#> SRR1313102 1 0.1414 0.7673 0.980 0.020
#> SRR1313103 1 0.9522 0.0565 0.628 0.372
#> SRR1313100 1 0.0000 0.7733 1.000 0.000
#> SRR1313105 1 0.2603 0.7541 0.956 0.044
#> SRR1313104 1 0.1414 0.7673 0.980 0.020
#> SRR1313107 1 0.2948 0.7484 0.948 0.052
#> SRR1313106 1 0.2236 0.7592 0.964 0.036
#> SRR1313109 2 0.8207 0.7409 0.256 0.744
#> SRR1313108 1 0.0938 0.7700 0.988 0.012
#> SRR1313111 1 0.2423 0.7568 0.960 0.040
#> SRR1313110 1 0.0000 0.7733 1.000 0.000
#> SRR1313112 1 0.4022 0.7482 0.920 0.080
#> SRR1313113 1 0.2778 0.7513 0.952 0.048
#> SRR1313115 1 0.1633 0.7657 0.976 0.024
#> SRR1313114 1 0.0000 0.7733 1.000 0.000
#> SRR1313117 1 0.2043 0.7616 0.968 0.032
#> SRR1313118 1 0.0000 0.7733 1.000 0.000
#> SRR1313116 2 0.9460 0.5673 0.364 0.636
#> SRR1313120 1 0.3584 0.7345 0.932 0.068
#> SRR1313119 1 0.1414 0.7673 0.980 0.020
#> SRR1313122 1 0.0000 0.7733 1.000 0.000
#> SRR1313124 1 0.2043 0.7616 0.968 0.032
#> SRR1313121 1 0.1414 0.7673 0.980 0.020
#> SRR1313125 1 0.2043 0.7616 0.968 0.032
#> SRR1313127 1 0.0000 0.7733 1.000 0.000
#> SRR1313123 1 0.0000 0.7733 1.000 0.000
#> SRR1313128 1 0.9393 0.7438 0.644 0.356
#> SRR1313126 1 0.0000 0.7733 1.000 0.000
#> SRR1313130 2 0.8386 0.7267 0.268 0.732
#> SRR1313132 1 0.9393 0.7438 0.644 0.356
#> SRR1313129 2 0.9998 0.3792 0.492 0.508
#> SRR1313133 1 0.9393 0.7438 0.644 0.356
#> SRR1313131 1 0.0000 0.7733 1.000 0.000
#> SRR1313134 1 0.7883 0.7966 0.764 0.236
#> SRR1313135 1 0.9393 0.7438 0.644 0.356
#> SRR1313136 1 0.9393 0.7438 0.644 0.356
#> SRR1313137 1 0.9393 0.7438 0.644 0.356
#> SRR1313138 1 0.9393 0.7438 0.644 0.356
#> SRR1313140 1 0.9286 0.7504 0.656 0.344
#> SRR1313141 1 0.7883 0.7966 0.764 0.236
#> SRR1313139 1 0.9393 0.7438 0.644 0.356
#> SRR1313143 1 0.7883 0.7966 0.764 0.236
#> SRR1313142 1 0.9393 0.7438 0.644 0.356
#> SRR1313144 1 0.9393 0.7438 0.644 0.356
#> SRR1313145 1 0.9393 0.7438 0.644 0.356
#> SRR1313146 1 0.9393 0.7438 0.644 0.356
#> SRR1313147 1 0.9393 0.7438 0.644 0.356
#> SRR1313150 1 0.9393 0.7438 0.644 0.356
#> SRR1313149 1 0.9170 0.7574 0.668 0.332
#> SRR1313152 1 0.9393 0.7438 0.644 0.356
#> SRR1313151 1 0.9393 0.7438 0.644 0.356
#> SRR1313154 1 0.9393 0.7438 0.644 0.356
#> SRR1313153 1 0.9393 0.7438 0.644 0.356
#> SRR1313156 1 0.9393 0.7438 0.644 0.356
#> SRR1313155 1 0.9393 0.7438 0.644 0.356
#> SRR1313157 1 0.9393 0.7438 0.644 0.356
#> SRR1313158 1 0.9393 0.7438 0.644 0.356
#> SRR1313161 1 0.9393 0.7438 0.644 0.356
#> SRR1313159 1 0.9393 0.7438 0.644 0.356
#> SRR1313160 1 0.9393 0.7438 0.644 0.356
#> SRR1313162 1 0.8016 0.7924 0.756 0.244
#> SRR1313163 1 0.9393 0.7438 0.644 0.356
#> SRR1313165 1 0.9393 0.7438 0.644 0.356
#> SRR1313166 1 0.9393 0.7438 0.644 0.356
#> SRR1313164 1 0.9393 0.7438 0.644 0.356
#> SRR1313167 1 0.9209 0.7544 0.664 0.336
#> SRR1313168 1 0.9393 0.7438 0.644 0.356
#> SRR1313170 1 0.7815 0.7493 0.768 0.232
#> SRR1313169 1 0.9393 0.7438 0.644 0.356
#> SRR1313172 1 0.8763 0.6435 0.704 0.296
#> SRR1313171 1 0.8207 0.7892 0.744 0.256
#> SRR1313174 2 0.3274 0.8892 0.060 0.940
#> SRR1313173 1 0.0000 0.7733 1.000 0.000
#> SRR1313176 2 0.0000 0.8880 0.000 1.000
#> SRR1313175 2 0.3584 0.8874 0.068 0.932
#> SRR1313178 2 0.0000 0.8880 0.000 1.000
#> SRR1313177 2 0.0000 0.8880 0.000 1.000
#> SRR1313179 1 0.9866 0.6525 0.568 0.432
#> SRR1313180 2 0.7602 0.7821 0.220 0.780
#> SRR1313181 2 0.0000 0.8880 0.000 1.000
#> SRR1313183 2 0.0000 0.8880 0.000 1.000
#> SRR1313182 2 0.3114 0.8896 0.056 0.944
#> SRR1313184 2 0.0938 0.8871 0.012 0.988
#> SRR1313185 2 0.3274 0.8892 0.060 0.940
#> SRR1313188 2 0.7602 0.7821 0.220 0.780
#> SRR1313187 2 0.7602 0.7821 0.220 0.780
#> SRR1313186 2 0.3584 0.8874 0.068 0.932
#> SRR1313189 2 0.0000 0.8880 0.000 1.000
#> SRR1313190 2 0.0000 0.8880 0.000 1.000
#> SRR1313191 2 0.2236 0.8905 0.036 0.964
#> SRR1313192 2 0.0000 0.8880 0.000 1.000
#> SRR1313193 2 0.2603 0.8904 0.044 0.956
#> SRR1313194 2 0.7602 0.7821 0.220 0.780
#> SRR1313195 2 0.7602 0.7821 0.220 0.780
#> SRR1313196 2 0.7602 0.7821 0.220 0.780
#> SRR1313197 2 0.3584 0.8874 0.068 0.932
#> SRR1313198 2 0.3584 0.8874 0.068 0.932
#> SRR1313199 2 0.0000 0.8880 0.000 1.000
#> SRR1313200 2 0.7602 0.7821 0.220 0.780
#> SRR1313201 2 0.0000 0.8880 0.000 1.000
#> SRR1313202 2 0.7602 0.7821 0.220 0.780
#> SRR1313203 1 0.8327 0.7576 0.736 0.264
#> SRR1313204 2 0.0000 0.8880 0.000 1.000
#> SRR1313205 2 0.0000 0.8880 0.000 1.000
#> SRR1313207 2 0.0000 0.8880 0.000 1.000
#> SRR1313208 2 0.0000 0.8880 0.000 1.000
#> SRR1313206 2 0.0672 0.8892 0.008 0.992
#> SRR1313210 2 0.3584 0.8874 0.068 0.932
#> SRR1313209 2 0.3431 0.8884 0.064 0.936
#> SRR1313211 2 0.3274 0.8892 0.060 0.940
#> SRR1313212 2 0.0000 0.8880 0.000 1.000
#> SRR1313214 2 0.3584 0.8874 0.068 0.932
#> SRR1313215 2 0.3584 0.8874 0.068 0.932
#> SRR1313213 2 0.0000 0.8880 0.000 1.000
#> SRR1313216 2 0.3584 0.8874 0.068 0.932
#> SRR1313217 2 0.6887 0.8108 0.184 0.816
#> SRR1313219 2 0.3584 0.8874 0.068 0.932
#> SRR1313220 2 0.0000 0.8880 0.000 1.000
#> SRR1313218 2 0.0376 0.8887 0.004 0.996
#> SRR1313222 2 0.0000 0.8880 0.000 1.000
#> SRR1313221 2 0.0000 0.8880 0.000 1.000
#> SRR1313223 2 0.0000 0.8880 0.000 1.000
#> SRR1313224 2 0.0000 0.8880 0.000 1.000
#> SRR1313225 2 0.3584 0.8874 0.068 0.932
#> SRR1313226 2 0.7950 0.7583 0.240 0.760
#> SRR1313227 2 0.0000 0.8880 0.000 1.000
#> SRR1313228 2 0.0000 0.8880 0.000 1.000
#> SRR1313229 2 0.0000 0.8880 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313063 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313064 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313067 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313068 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313069 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313076 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313077 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313078 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313079 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313080 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313081 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313082 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313091 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313093 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313099 3 0.5363 0.628 0.000 0.276 0.724
#> SRR1313098 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313101 3 0.0424 0.959 0.000 0.008 0.992
#> SRR1313102 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313103 3 0.0424 0.959 0.000 0.008 0.992
#> SRR1313100 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313105 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313109 2 0.2261 0.918 0.000 0.932 0.068
#> SRR1313108 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313112 3 0.1753 0.924 0.000 0.048 0.952
#> SRR1313113 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313116 3 0.4887 0.705 0.000 0.228 0.772
#> SRR1313120 3 0.0424 0.959 0.000 0.008 0.992
#> SRR1313119 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313128 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313126 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313130 2 0.2959 0.879 0.000 0.900 0.100
#> SRR1313132 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313129 3 0.3879 0.812 0.000 0.152 0.848
#> SRR1313133 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313131 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313134 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313135 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313136 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313137 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313138 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313140 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313141 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313139 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313143 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313142 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313144 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313145 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313146 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313147 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313149 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313152 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313151 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313154 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313153 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313156 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313155 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313157 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313158 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313161 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313159 1 0.2796 0.895 0.908 0.092 0.000
#> SRR1313160 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313162 1 0.1163 0.970 0.972 0.000 0.028
#> SRR1313163 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313165 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313166 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313164 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313167 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313170 2 0.4015 0.865 0.096 0.876 0.028
#> SRR1313169 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313172 3 0.6286 0.168 0.000 0.464 0.536
#> SRR1313171 1 0.0000 0.998 1.000 0.000 0.000
#> SRR1313174 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.965 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313179 2 0.6008 0.410 0.372 0.628 0.000
#> SRR1313180 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313203 3 0.9638 0.146 0.372 0.208 0.420
#> SRR1313204 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313226 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.988 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.988 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 3 0.2814 0.869 0.000 0.000 0.868 0.132
#> SRR1313063 3 0.1940 0.922 0.000 0.000 0.924 0.076
#> SRR1313064 4 0.4222 0.967 0.272 0.000 0.000 0.728
#> SRR1313065 4 0.4624 0.890 0.340 0.000 0.000 0.660
#> SRR1313066 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313067 3 0.1867 0.925 0.000 0.000 0.928 0.072
#> SRR1313068 3 0.1792 0.928 0.000 0.000 0.932 0.068
#> SRR1313069 1 0.4961 -0.381 0.552 0.000 0.000 0.448
#> SRR1313070 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313071 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313072 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313073 4 0.4164 0.970 0.264 0.000 0.000 0.736
#> SRR1313074 4 0.4193 0.969 0.268 0.000 0.000 0.732
#> SRR1313075 4 0.4134 0.970 0.260 0.000 0.000 0.740
#> SRR1313076 3 0.0817 0.955 0.000 0.000 0.976 0.024
#> SRR1313077 3 0.1867 0.925 0.000 0.000 0.928 0.072
#> SRR1313078 3 0.1716 0.931 0.000 0.000 0.936 0.064
#> SRR1313079 4 0.4193 0.969 0.268 0.000 0.000 0.732
#> SRR1313080 3 0.1792 0.928 0.000 0.000 0.932 0.068
#> SRR1313081 3 0.1792 0.928 0.000 0.000 0.932 0.068
#> SRR1313082 4 0.4406 0.942 0.300 0.000 0.000 0.700
#> SRR1313083 1 0.2973 0.743 0.856 0.000 0.000 0.144
#> SRR1313084 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313085 4 0.4072 0.967 0.252 0.000 0.000 0.748
#> SRR1313086 4 0.4585 0.903 0.332 0.000 0.000 0.668
#> SRR1313087 4 0.4193 0.969 0.268 0.000 0.000 0.732
#> SRR1313088 4 0.4522 0.920 0.320 0.000 0.000 0.680
#> SRR1313089 4 0.4134 0.970 0.260 0.000 0.000 0.740
#> SRR1313092 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.1398 0.868 0.000 0.956 0.040 0.004
#> SRR1313093 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313096 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313094 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.2466 0.872 0.000 0.096 0.900 0.004
#> SRR1313098 3 0.0188 0.965 0.000 0.000 0.996 0.004
#> SRR1313101 3 0.0188 0.965 0.000 0.004 0.996 0.000
#> SRR1313102 3 0.0188 0.965 0.000 0.004 0.996 0.000
#> SRR1313103 3 0.0817 0.952 0.000 0.024 0.976 0.000
#> SRR1313100 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0336 0.963 0.000 0.008 0.992 0.000
#> SRR1313104 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313109 2 0.4088 0.709 0.000 0.764 0.232 0.004
#> SRR1313108 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313111 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0376 0.964 0.000 0.004 0.992 0.004
#> SRR1313113 3 0.0188 0.965 0.000 0.004 0.996 0.000
#> SRR1313115 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.4483 0.647 0.000 0.284 0.712 0.004
#> SRR1313120 3 0.0469 0.960 0.000 0.012 0.988 0.000
#> SRR1313119 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313130 2 0.1661 0.857 0.000 0.944 0.052 0.004
#> SRR1313132 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313129 3 0.1211 0.938 0.000 0.040 0.960 0.000
#> SRR1313133 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313131 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313134 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313135 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313140 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313141 1 0.0188 0.972 0.996 0.000 0.000 0.004
#> SRR1313139 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313143 1 0.0336 0.966 0.992 0.000 0.000 0.008
#> SRR1313142 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313149 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313152 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313155 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313159 1 0.0657 0.959 0.984 0.004 0.000 0.012
#> SRR1313160 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313162 1 0.1635 0.900 0.948 0.000 0.044 0.008
#> SRR1313163 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313165 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0188 0.972 0.996 0.000 0.000 0.004
#> SRR1313167 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313170 2 0.6369 0.424 0.260 0.640 0.096 0.004
#> SRR1313169 1 0.0000 0.974 1.000 0.000 0.000 0.000
#> SRR1313172 3 0.4464 0.710 0.000 0.208 0.768 0.024
#> SRR1313171 1 0.0336 0.969 0.992 0.000 0.000 0.008
#> SRR1313174 2 0.2647 0.886 0.000 0.880 0.000 0.120
#> SRR1313173 3 0.0000 0.966 0.000 0.000 1.000 0.000
#> SRR1313176 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313175 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313177 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313179 2 0.7663 0.362 0.340 0.528 0.060 0.072
#> SRR1313180 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313181 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313183 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313182 2 0.3688 0.881 0.000 0.792 0.000 0.208
#> SRR1313184 2 0.4570 0.825 0.008 0.812 0.116 0.064
#> SRR1313185 2 0.2469 0.886 0.000 0.892 0.000 0.108
#> SRR1313188 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313187 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313186 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313190 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313191 2 0.3356 0.885 0.000 0.824 0.000 0.176
#> SRR1313192 2 0.3837 0.879 0.000 0.776 0.000 0.224
#> SRR1313193 2 0.3356 0.882 0.000 0.824 0.000 0.176
#> SRR1313194 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313195 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313196 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313197 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313200 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313201 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313202 2 0.0188 0.876 0.000 0.996 0.000 0.004
#> SRR1313203 3 0.4754 0.737 0.008 0.016 0.748 0.228
#> SRR1313204 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313205 2 0.3801 0.879 0.000 0.780 0.000 0.220
#> SRR1313207 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313208 2 0.2149 0.885 0.000 0.912 0.000 0.088
#> SRR1313206 2 0.3764 0.880 0.000 0.784 0.000 0.216
#> SRR1313210 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.2408 0.886 0.000 0.896 0.000 0.104
#> SRR1313212 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313214 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313216 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313218 2 0.1557 0.883 0.000 0.944 0.000 0.056
#> SRR1313222 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313221 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313223 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313224 2 0.1792 0.883 0.000 0.932 0.000 0.068
#> SRR1313225 2 0.0000 0.877 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.0657 0.870 0.000 0.984 0.012 0.004
#> SRR1313227 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313228 2 0.3975 0.876 0.000 0.760 0.000 0.240
#> SRR1313229 2 0.3975 0.876 0.000 0.760 0.000 0.240
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 3 0.2416 0.882 0.000 0.100 0.888 0.012 0.000
#> SRR1313063 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313064 4 0.2773 0.929 0.164 0.000 0.000 0.836 0.000
#> SRR1313065 4 0.4171 0.617 0.396 0.000 0.000 0.604 0.000
#> SRR1313066 4 0.2377 0.912 0.128 0.000 0.000 0.872 0.000
#> SRR1313067 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313068 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313069 4 0.4302 0.397 0.480 0.000 0.000 0.520 0.000
#> SRR1313070 4 0.2377 0.912 0.128 0.000 0.000 0.872 0.000
#> SRR1313071 4 0.2424 0.916 0.132 0.000 0.000 0.868 0.000
#> SRR1313072 4 0.2648 0.930 0.152 0.000 0.000 0.848 0.000
#> SRR1313073 4 0.2516 0.923 0.140 0.000 0.000 0.860 0.000
#> SRR1313074 4 0.2732 0.930 0.160 0.000 0.000 0.840 0.000
#> SRR1313075 4 0.2690 0.930 0.156 0.000 0.000 0.844 0.000
#> SRR1313076 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313077 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313078 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313079 4 0.2690 0.930 0.156 0.000 0.000 0.844 0.000
#> SRR1313080 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313081 3 0.2304 0.884 0.000 0.100 0.892 0.008 0.000
#> SRR1313082 4 0.2966 0.917 0.184 0.000 0.000 0.816 0.000
#> SRR1313083 1 0.2230 0.852 0.884 0.000 0.000 0.116 0.000
#> SRR1313084 4 0.2605 0.929 0.148 0.000 0.000 0.852 0.000
#> SRR1313085 4 0.2605 0.929 0.148 0.000 0.000 0.852 0.000
#> SRR1313086 4 0.3707 0.809 0.284 0.000 0.000 0.716 0.000
#> SRR1313087 4 0.2605 0.929 0.148 0.000 0.000 0.852 0.000
#> SRR1313088 4 0.2966 0.917 0.184 0.000 0.000 0.816 0.000
#> SRR1313089 4 0.2773 0.929 0.164 0.000 0.000 0.836 0.000
#> SRR1313092 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 5 0.1405 0.771 0.000 0.008 0.016 0.020 0.956
#> SRR1313093 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313095 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313096 3 0.0162 0.924 0.000 0.004 0.996 0.000 0.000
#> SRR1313094 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 5 0.5750 0.174 0.000 0.008 0.436 0.064 0.492
#> SRR1313098 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313101 3 0.0807 0.914 0.000 0.000 0.976 0.012 0.012
#> SRR1313102 3 0.0162 0.923 0.000 0.000 0.996 0.000 0.004
#> SRR1313103 3 0.4491 0.443 0.000 0.000 0.652 0.020 0.328
#> SRR1313100 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313105 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313106 3 0.0162 0.924 0.000 0.000 0.996 0.004 0.000
#> SRR1313109 5 0.2661 0.738 0.000 0.008 0.044 0.052 0.896
#> SRR1313108 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313111 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.2037 0.881 0.000 0.004 0.920 0.064 0.012
#> SRR1313113 3 0.0162 0.924 0.000 0.000 0.996 0.004 0.000
#> SRR1313115 3 0.0963 0.908 0.000 0.036 0.964 0.000 0.000
#> SRR1313114 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 3 0.4825 0.345 0.000 0.024 0.568 0.000 0.408
#> SRR1313120 3 0.1809 0.887 0.000 0.000 0.928 0.060 0.012
#> SRR1313119 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313124 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313123 3 0.0000 0.925 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.0510 0.963 0.984 0.000 0.000 0.016 0.000
#> SRR1313126 3 0.1671 0.898 0.000 0.076 0.924 0.000 0.000
#> SRR1313130 5 0.1299 0.772 0.000 0.008 0.012 0.020 0.960
#> SRR1313132 1 0.1671 0.907 0.924 0.000 0.000 0.076 0.000
#> SRR1313129 3 0.4506 0.500 0.000 0.000 0.676 0.028 0.296
#> SRR1313133 1 0.0290 0.964 0.992 0.000 0.000 0.008 0.000
#> SRR1313131 3 0.1608 0.900 0.000 0.072 0.928 0.000 0.000
#> SRR1313134 1 0.1410 0.922 0.940 0.000 0.000 0.060 0.000
#> SRR1313135 1 0.0794 0.957 0.972 0.000 0.000 0.028 0.000
#> SRR1313136 1 0.0290 0.964 0.992 0.000 0.000 0.008 0.000
#> SRR1313137 1 0.0290 0.964 0.992 0.000 0.000 0.008 0.000
#> SRR1313138 1 0.1732 0.903 0.920 0.000 0.000 0.080 0.000
#> SRR1313140 1 0.0794 0.957 0.972 0.000 0.000 0.028 0.000
#> SRR1313141 1 0.0404 0.963 0.988 0.000 0.000 0.012 0.000
#> SRR1313139 1 0.0510 0.963 0.984 0.000 0.000 0.016 0.000
#> SRR1313143 1 0.0609 0.962 0.980 0.000 0.000 0.020 0.000
#> SRR1313142 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313144 1 0.0404 0.964 0.988 0.000 0.000 0.012 0.000
#> SRR1313145 1 0.0510 0.963 0.984 0.000 0.000 0.016 0.000
#> SRR1313146 1 0.0510 0.963 0.984 0.000 0.000 0.016 0.000
#> SRR1313147 1 0.0510 0.963 0.984 0.000 0.000 0.016 0.000
#> SRR1313150 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.0794 0.957 0.972 0.000 0.000 0.028 0.000
#> SRR1313152 1 0.0404 0.964 0.988 0.000 0.000 0.012 0.000
#> SRR1313151 1 0.0794 0.957 0.972 0.000 0.000 0.028 0.000
#> SRR1313154 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.2179 0.871 0.888 0.000 0.000 0.112 0.000
#> SRR1313155 1 0.0162 0.960 0.996 0.000 0.000 0.004 0.000
#> SRR1313157 1 0.0162 0.963 0.996 0.000 0.000 0.004 0.000
#> SRR1313158 1 0.0880 0.955 0.968 0.000 0.000 0.032 0.000
#> SRR1313161 1 0.0703 0.960 0.976 0.000 0.000 0.024 0.000
#> SRR1313159 1 0.2877 0.819 0.848 0.004 0.000 0.144 0.004
#> SRR1313160 1 0.0290 0.964 0.992 0.000 0.000 0.008 0.000
#> SRR1313162 1 0.2139 0.911 0.916 0.000 0.032 0.052 0.000
#> SRR1313163 1 0.1732 0.903 0.920 0.000 0.000 0.080 0.000
#> SRR1313165 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0703 0.960 0.976 0.000 0.000 0.024 0.000
#> SRR1313164 1 0.0609 0.953 0.980 0.000 0.000 0.020 0.000
#> SRR1313167 1 0.0703 0.961 0.976 0.000 0.000 0.024 0.000
#> SRR1313168 1 0.0000 0.962 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 5 0.5878 0.409 0.208 0.004 0.060 0.056 0.672
#> SRR1313169 1 0.0880 0.955 0.968 0.000 0.000 0.032 0.000
#> SRR1313172 3 0.7698 0.173 0.020 0.352 0.440 0.128 0.060
#> SRR1313171 1 0.1544 0.914 0.932 0.000 0.000 0.068 0.000
#> SRR1313174 5 0.4182 0.249 0.000 0.400 0.000 0.000 0.600
#> SRR1313173 3 0.1671 0.898 0.000 0.076 0.924 0.000 0.000
#> SRR1313176 2 0.2329 0.926 0.000 0.876 0.000 0.000 0.124
#> SRR1313175 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313178 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313177 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313179 5 0.6848 0.249 0.280 0.048 0.000 0.132 0.540
#> SRR1313180 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313181 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313183 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313182 5 0.3210 0.676 0.000 0.212 0.000 0.000 0.788
#> SRR1313184 5 0.4052 0.699 0.004 0.044 0.012 0.132 0.808
#> SRR1313185 5 0.2127 0.750 0.000 0.108 0.000 0.000 0.892
#> SRR1313188 5 0.0000 0.783 0.000 0.000 0.000 0.000 1.000
#> SRR1313187 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313186 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313189 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313190 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313191 5 0.2516 0.733 0.000 0.140 0.000 0.000 0.860
#> SRR1313192 5 0.3983 0.519 0.000 0.340 0.000 0.000 0.660
#> SRR1313193 5 0.3774 0.574 0.000 0.296 0.000 0.000 0.704
#> SRR1313194 5 0.1908 0.715 0.000 0.092 0.000 0.000 0.908
#> SRR1313195 5 0.0794 0.770 0.000 0.028 0.000 0.000 0.972
#> SRR1313196 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313197 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313198 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313199 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313200 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313201 5 0.4192 0.416 0.000 0.404 0.000 0.000 0.596
#> SRR1313202 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313203 3 0.7174 0.198 0.028 0.396 0.428 0.136 0.012
#> SRR1313204 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313205 5 0.3366 0.658 0.000 0.232 0.000 0.000 0.768
#> SRR1313207 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313208 5 0.2020 0.758 0.000 0.100 0.000 0.000 0.900
#> SRR1313206 5 0.3424 0.650 0.000 0.240 0.000 0.000 0.760
#> SRR1313210 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313209 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313211 5 0.2230 0.746 0.000 0.116 0.000 0.000 0.884
#> SRR1313212 5 0.4171 0.432 0.000 0.396 0.000 0.000 0.604
#> SRR1313214 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313215 5 0.0290 0.783 0.000 0.008 0.000 0.000 0.992
#> SRR1313213 2 0.2074 0.950 0.000 0.896 0.000 0.000 0.104
#> SRR1313216 5 0.0000 0.783 0.000 0.000 0.000 0.000 1.000
#> SRR1313217 5 0.0000 0.783 0.000 0.000 0.000 0.000 1.000
#> SRR1313219 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313220 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313218 5 0.1197 0.776 0.000 0.048 0.000 0.000 0.952
#> SRR1313222 2 0.4101 0.366 0.000 0.628 0.000 0.000 0.372
#> SRR1313221 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313223 5 0.4287 0.255 0.000 0.460 0.000 0.000 0.540
#> SRR1313224 5 0.1740 0.771 0.000 0.056 0.000 0.012 0.932
#> SRR1313225 5 0.0162 0.784 0.000 0.004 0.000 0.000 0.996
#> SRR1313226 5 0.0162 0.782 0.000 0.004 0.000 0.000 0.996
#> SRR1313227 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313228 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
#> SRR1313229 5 0.4201 0.409 0.000 0.408 0.000 0.000 0.592
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 6 0.3518 0.92984 0.000 0.000 0.256 0.012 0.000 0.732
#> SRR1313063 6 0.3314 0.93711 0.000 0.000 0.256 0.004 0.000 0.740
#> SRR1313064 4 0.2340 0.96519 0.148 0.000 0.000 0.852 0.000 0.000
#> SRR1313065 1 0.3843 -0.08921 0.548 0.000 0.000 0.452 0.000 0.000
#> SRR1313066 4 0.1714 0.92134 0.092 0.000 0.000 0.908 0.000 0.000
#> SRR1313067 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313068 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313069 1 0.3647 0.29089 0.640 0.000 0.000 0.360 0.000 0.000
#> SRR1313070 4 0.2048 0.95441 0.120 0.000 0.000 0.880 0.000 0.000
#> SRR1313071 4 0.2219 0.96779 0.136 0.000 0.000 0.864 0.000 0.000
#> SRR1313072 4 0.2219 0.96779 0.136 0.000 0.000 0.864 0.000 0.000
#> SRR1313073 4 0.2699 0.94817 0.124 0.000 0.012 0.856 0.000 0.008
#> SRR1313074 4 0.2300 0.96736 0.144 0.000 0.000 0.856 0.000 0.000
#> SRR1313075 4 0.2300 0.96736 0.144 0.000 0.000 0.856 0.000 0.000
#> SRR1313076 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313077 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313078 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313079 4 0.2219 0.96779 0.136 0.000 0.000 0.864 0.000 0.000
#> SRR1313080 6 0.3198 0.94113 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1313081 6 0.3421 0.93470 0.000 0.000 0.256 0.008 0.000 0.736
#> SRR1313082 4 0.2664 0.93541 0.184 0.000 0.000 0.816 0.000 0.000
#> SRR1313083 1 0.1327 0.89366 0.936 0.000 0.000 0.064 0.000 0.000
#> SRR1313084 4 0.2219 0.96779 0.136 0.000 0.000 0.864 0.000 0.000
#> SRR1313085 4 0.2219 0.96779 0.136 0.000 0.000 0.864 0.000 0.000
#> SRR1313086 4 0.3390 0.76679 0.296 0.000 0.000 0.704 0.000 0.000
#> SRR1313087 4 0.2260 0.96798 0.140 0.000 0.000 0.860 0.000 0.000
#> SRR1313088 4 0.2597 0.94250 0.176 0.000 0.000 0.824 0.000 0.000
#> SRR1313089 4 0.2300 0.96729 0.144 0.000 0.000 0.856 0.000 0.000
#> SRR1313092 3 0.1075 0.66543 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1313090 3 0.0363 0.66958 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313091 5 0.2706 0.76102 0.000 0.028 0.024 0.000 0.880 0.068
#> SRR1313093 3 0.3266 0.51924 0.000 0.000 0.728 0.000 0.000 0.272
#> SRR1313095 3 0.3695 0.17403 0.000 0.000 0.624 0.000 0.000 0.376
#> SRR1313096 3 0.3607 0.25516 0.000 0.000 0.652 0.000 0.000 0.348
#> SRR1313094 3 0.1204 0.65458 0.000 0.000 0.944 0.000 0.000 0.056
#> SRR1313097 3 0.0363 0.66923 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313099 5 0.6182 0.37571 0.000 0.028 0.296 0.016 0.544 0.116
#> SRR1313098 3 0.3390 0.37830 0.000 0.000 0.704 0.000 0.000 0.296
#> SRR1313101 3 0.1814 0.61178 0.000 0.000 0.900 0.000 0.000 0.100
#> SRR1313102 3 0.2092 0.61555 0.000 0.000 0.876 0.000 0.000 0.124
#> SRR1313103 3 0.5404 0.07739 0.000 0.016 0.524 0.000 0.384 0.076
#> SRR1313100 3 0.3789 0.00828 0.000 0.000 0.584 0.000 0.000 0.416
#> SRR1313105 3 0.0458 0.66608 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313104 3 0.0458 0.66973 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313107 3 0.0520 0.66898 0.000 0.008 0.984 0.000 0.000 0.008
#> SRR1313106 3 0.0260 0.66944 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1313109 5 0.4423 0.69945 0.000 0.024 0.056 0.048 0.788 0.084
#> SRR1313108 3 0.3482 0.47871 0.000 0.000 0.684 0.000 0.000 0.316
#> SRR1313111 3 0.0508 0.66674 0.000 0.004 0.984 0.000 0.000 0.012
#> SRR1313110 3 0.3288 0.41065 0.000 0.000 0.724 0.000 0.000 0.276
#> SRR1313112 3 0.3978 0.51528 0.000 0.000 0.744 0.064 0.000 0.192
#> SRR1313113 3 0.0547 0.66772 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313115 3 0.3515 0.47857 0.000 0.000 0.676 0.000 0.000 0.324
#> SRR1313114 3 0.3390 0.37481 0.000 0.000 0.704 0.000 0.000 0.296
#> SRR1313117 3 0.0146 0.66937 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313118 3 0.3464 0.34550 0.000 0.000 0.688 0.000 0.000 0.312
#> SRR1313116 5 0.5456 0.18650 0.000 0.032 0.388 0.000 0.524 0.056
#> SRR1313120 3 0.2070 0.61145 0.000 0.012 0.896 0.000 0.000 0.092
#> SRR1313119 3 0.0547 0.66809 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313122 3 0.2854 0.52744 0.000 0.000 0.792 0.000 0.000 0.208
#> SRR1313124 3 0.0458 0.66796 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313121 3 0.1714 0.63953 0.000 0.000 0.908 0.000 0.000 0.092
#> SRR1313125 3 0.0260 0.66969 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1313127 3 0.3464 0.34161 0.000 0.000 0.688 0.000 0.000 0.312
#> SRR1313123 3 0.3309 0.40617 0.000 0.000 0.720 0.000 0.000 0.280
#> SRR1313128 1 0.0363 0.93446 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313126 6 0.3869 0.25033 0.000 0.000 0.500 0.000 0.000 0.500
#> SRR1313130 5 0.2681 0.76091 0.000 0.020 0.028 0.000 0.880 0.072
#> SRR1313132 1 0.1267 0.90062 0.940 0.000 0.000 0.060 0.000 0.000
#> SRR1313129 3 0.5664 0.02463 0.000 0.028 0.504 0.000 0.388 0.080
#> SRR1313133 1 0.0000 0.93598 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313131 3 0.3868 -0.31065 0.000 0.000 0.508 0.000 0.000 0.492
#> SRR1313134 1 0.2213 0.86191 0.888 0.000 0.004 0.100 0.000 0.008
#> SRR1313135 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313136 1 0.0000 0.93598 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313138 1 0.2121 0.86625 0.892 0.000 0.000 0.096 0.000 0.012
#> SRR1313140 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313141 1 0.0858 0.92045 0.968 0.000 0.004 0.028 0.000 0.000
#> SRR1313139 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313143 1 0.1152 0.92145 0.952 0.000 0.004 0.044 0.000 0.000
#> SRR1313142 1 0.0146 0.93491 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313144 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313145 1 0.0260 0.93591 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1313146 1 0.0363 0.93496 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313147 1 0.0260 0.93591 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1313150 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313149 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313152 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313151 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313154 1 0.0000 0.93598 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313153 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313156 1 0.2706 0.82856 0.852 0.000 0.000 0.124 0.000 0.024
#> SRR1313155 1 0.0260 0.93598 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1313157 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313158 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313161 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313159 1 0.3142 0.80884 0.832 0.000 0.000 0.132 0.012 0.024
#> SRR1313160 1 0.0146 0.93491 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313162 1 0.5114 0.61827 0.692 0.000 0.052 0.080 0.000 0.176
#> SRR1313163 1 0.2070 0.86981 0.896 0.000 0.000 0.092 0.000 0.012
#> SRR1313165 1 0.0146 0.93491 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313166 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313164 1 0.0547 0.92721 0.980 0.000 0.000 0.020 0.000 0.000
#> SRR1313167 1 0.0363 0.93496 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1313168 1 0.0146 0.93647 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313170 5 0.6628 0.28139 0.324 0.000 0.040 0.052 0.508 0.076
#> SRR1313169 1 0.0458 0.93343 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313172 3 0.7720 0.10669 0.040 0.132 0.380 0.100 0.004 0.344
#> SRR1313171 1 0.2001 0.87170 0.900 0.000 0.004 0.092 0.000 0.004
#> SRR1313174 5 0.3854 0.12571 0.000 0.464 0.000 0.000 0.536 0.000
#> SRR1313173 3 0.3866 -0.28365 0.000 0.000 0.516 0.000 0.000 0.484
#> SRR1313176 2 0.0790 0.75311 0.000 0.968 0.000 0.000 0.032 0.000
#> SRR1313175 5 0.0146 0.78866 0.000 0.004 0.000 0.000 0.996 0.000
#> SRR1313178 2 0.0146 0.75586 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313177 2 0.0000 0.75378 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 5 0.7435 0.21106 0.316 0.032 0.024 0.104 0.460 0.064
#> SRR1313180 5 0.1700 0.77776 0.000 0.024 0.000 0.000 0.928 0.048
#> SRR1313181 2 0.0632 0.75474 0.000 0.976 0.000 0.000 0.024 0.000
#> SRR1313183 2 0.0146 0.75586 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313182 5 0.2664 0.64227 0.000 0.184 0.000 0.000 0.816 0.000
#> SRR1313184 5 0.5269 0.63620 0.028 0.036 0.028 0.104 0.744 0.060
#> SRR1313185 5 0.1556 0.76828 0.000 0.080 0.000 0.000 0.920 0.000
#> SRR1313188 5 0.1010 0.78535 0.000 0.004 0.000 0.000 0.960 0.036
#> SRR1313187 5 0.2101 0.77348 0.000 0.028 0.008 0.000 0.912 0.052
#> SRR1313186 5 0.0547 0.78630 0.000 0.020 0.000 0.000 0.980 0.000
#> SRR1313189 2 0.0000 0.75378 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.75378 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.2762 0.63600 0.000 0.196 0.000 0.000 0.804 0.000
#> SRR1313192 5 0.3857 -0.16165 0.000 0.468 0.000 0.000 0.532 0.000
#> SRR1313193 5 0.3847 -0.14391 0.000 0.456 0.000 0.000 0.544 0.000
#> SRR1313194 5 0.2197 0.76443 0.000 0.056 0.000 0.000 0.900 0.044
#> SRR1313195 5 0.1921 0.77546 0.000 0.032 0.000 0.000 0.916 0.052
#> SRR1313196 5 0.1780 0.77626 0.000 0.028 0.000 0.000 0.924 0.048
#> SRR1313197 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313198 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313199 2 0.3659 0.57393 0.000 0.636 0.000 0.000 0.364 0.000
#> SRR1313200 5 0.1320 0.78207 0.000 0.016 0.000 0.000 0.948 0.036
#> SRR1313201 2 0.3659 0.57661 0.000 0.636 0.000 0.000 0.364 0.000
#> SRR1313202 5 0.1633 0.77918 0.000 0.024 0.000 0.000 0.932 0.044
#> SRR1313203 3 0.7318 0.08460 0.028 0.108 0.384 0.104 0.000 0.376
#> SRR1313204 2 0.3607 0.59104 0.000 0.652 0.000 0.000 0.348 0.000
#> SRR1313205 5 0.2664 0.64402 0.000 0.184 0.000 0.000 0.816 0.000
#> SRR1313207 2 0.0146 0.75586 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313208 5 0.1327 0.76504 0.000 0.064 0.000 0.000 0.936 0.000
#> SRR1313206 5 0.3804 0.01248 0.000 0.424 0.000 0.000 0.576 0.000
#> SRR1313210 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313209 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313211 5 0.1765 0.73921 0.000 0.096 0.000 0.000 0.904 0.000
#> SRR1313212 5 0.3782 0.06689 0.000 0.412 0.000 0.000 0.588 0.000
#> SRR1313214 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313215 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313213 2 0.0146 0.75564 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313216 5 0.0146 0.78866 0.000 0.004 0.000 0.000 0.996 0.000
#> SRR1313217 5 0.1176 0.78575 0.000 0.020 0.000 0.000 0.956 0.024
#> SRR1313219 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313220 2 0.3756 0.50243 0.000 0.600 0.000 0.000 0.400 0.000
#> SRR1313218 5 0.0632 0.78455 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1313222 2 0.2378 0.71510 0.000 0.848 0.000 0.000 0.152 0.000
#> SRR1313221 2 0.3868 0.24682 0.000 0.508 0.000 0.000 0.492 0.000
#> SRR1313223 2 0.3244 0.65277 0.000 0.732 0.000 0.000 0.268 0.000
#> SRR1313224 5 0.1124 0.78019 0.000 0.036 0.000 0.008 0.956 0.000
#> SRR1313225 5 0.0260 0.78872 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313226 5 0.2036 0.77438 0.000 0.028 0.008 0.000 0.916 0.048
#> SRR1313227 2 0.3864 0.28902 0.000 0.520 0.000 0.000 0.480 0.000
#> SRR1313228 5 0.3854 -0.14759 0.000 0.464 0.000 0.000 0.536 0.000
#> SRR1313229 2 0.3659 0.57380 0.000 0.636 0.000 0.000 0.364 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "NMF"]
# you can also extract it by
# res = res_list["CV:NMF"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 6.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.969 0.987 0.4927 0.505 0.505
#> 3 3 0.886 0.911 0.960 0.3598 0.742 0.528
#> 4 4 0.842 0.891 0.911 0.1021 0.894 0.696
#> 5 5 1.000 0.960 0.982 0.0782 0.926 0.726
#> 6 6 0.903 0.800 0.900 0.0344 0.965 0.833
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 6
#> attr(,"optional")
#> [1] 2 5
There is also optional best \(k\) = 2 5 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.996 1.000 0.000
#> SRR1313063 1 0.0000 0.996 1.000 0.000
#> SRR1313064 1 0.0000 0.996 1.000 0.000
#> SRR1313065 1 0.0000 0.996 1.000 0.000
#> SRR1313066 1 0.0000 0.996 1.000 0.000
#> SRR1313067 1 0.0000 0.996 1.000 0.000
#> SRR1313068 1 0.0000 0.996 1.000 0.000
#> SRR1313069 1 0.0000 0.996 1.000 0.000
#> SRR1313070 1 0.0000 0.996 1.000 0.000
#> SRR1313071 1 0.0000 0.996 1.000 0.000
#> SRR1313072 1 0.0000 0.996 1.000 0.000
#> SRR1313073 1 0.0000 0.996 1.000 0.000
#> SRR1313074 1 0.0000 0.996 1.000 0.000
#> SRR1313075 1 0.0000 0.996 1.000 0.000
#> SRR1313076 1 0.0000 0.996 1.000 0.000
#> SRR1313077 1 0.0000 0.996 1.000 0.000
#> SRR1313078 1 0.0000 0.996 1.000 0.000
#> SRR1313079 1 0.0000 0.996 1.000 0.000
#> SRR1313080 1 0.0000 0.996 1.000 0.000
#> SRR1313081 1 0.0000 0.996 1.000 0.000
#> SRR1313082 1 0.0000 0.996 1.000 0.000
#> SRR1313083 1 0.0000 0.996 1.000 0.000
#> SRR1313084 1 0.0000 0.996 1.000 0.000
#> SRR1313085 1 0.0000 0.996 1.000 0.000
#> SRR1313086 1 0.0000 0.996 1.000 0.000
#> SRR1313087 1 0.0000 0.996 1.000 0.000
#> SRR1313088 1 0.0000 0.996 1.000 0.000
#> SRR1313089 1 0.0000 0.996 1.000 0.000
#> SRR1313092 1 0.0000 0.996 1.000 0.000
#> SRR1313090 1 0.0000 0.996 1.000 0.000
#> SRR1313091 2 0.0000 0.975 0.000 1.000
#> SRR1313093 1 0.0000 0.996 1.000 0.000
#> SRR1313095 1 0.0000 0.996 1.000 0.000
#> SRR1313096 1 0.0000 0.996 1.000 0.000
#> SRR1313094 1 0.0000 0.996 1.000 0.000
#> SRR1313097 1 0.7674 0.699 0.776 0.224
#> SRR1313099 2 0.0000 0.975 0.000 1.000
#> SRR1313098 1 0.0000 0.996 1.000 0.000
#> SRR1313101 2 0.0672 0.968 0.008 0.992
#> SRR1313102 1 0.0000 0.996 1.000 0.000
#> SRR1313103 2 0.9608 0.404 0.384 0.616
#> SRR1313100 1 0.0000 0.996 1.000 0.000
#> SRR1313105 2 0.8713 0.605 0.292 0.708
#> SRR1313104 1 0.0000 0.996 1.000 0.000
#> SRR1313107 1 0.4161 0.904 0.916 0.084
#> SRR1313106 2 0.0000 0.975 0.000 1.000
#> SRR1313109 2 0.0000 0.975 0.000 1.000
#> SRR1313108 1 0.0000 0.996 1.000 0.000
#> SRR1313111 1 0.0376 0.993 0.996 0.004
#> SRR1313110 1 0.0000 0.996 1.000 0.000
#> SRR1313112 2 0.4298 0.892 0.088 0.912
#> SRR1313113 2 0.3431 0.916 0.064 0.936
#> SRR1313115 1 0.0000 0.996 1.000 0.000
#> SRR1313114 1 0.0000 0.996 1.000 0.000
#> SRR1313117 2 0.9988 0.112 0.480 0.520
#> SRR1313118 1 0.0000 0.996 1.000 0.000
#> SRR1313116 2 0.0000 0.975 0.000 1.000
#> SRR1313120 2 0.7139 0.760 0.196 0.804
#> SRR1313119 1 0.0000 0.996 1.000 0.000
#> SRR1313122 1 0.0000 0.996 1.000 0.000
#> SRR1313124 1 0.0000 0.996 1.000 0.000
#> SRR1313121 1 0.0000 0.996 1.000 0.000
#> SRR1313125 1 0.0000 0.996 1.000 0.000
#> SRR1313127 1 0.0000 0.996 1.000 0.000
#> SRR1313123 1 0.0000 0.996 1.000 0.000
#> SRR1313128 1 0.0000 0.996 1.000 0.000
#> SRR1313126 1 0.0000 0.996 1.000 0.000
#> SRR1313130 2 0.0000 0.975 0.000 1.000
#> SRR1313132 1 0.0000 0.996 1.000 0.000
#> SRR1313129 2 0.0376 0.971 0.004 0.996
#> SRR1313133 1 0.0000 0.996 1.000 0.000
#> SRR1313131 1 0.0000 0.996 1.000 0.000
#> SRR1313134 1 0.0000 0.996 1.000 0.000
#> SRR1313135 1 0.0000 0.996 1.000 0.000
#> SRR1313136 1 0.0000 0.996 1.000 0.000
#> SRR1313137 1 0.0000 0.996 1.000 0.000
#> SRR1313138 1 0.0376 0.993 0.996 0.004
#> SRR1313140 1 0.0000 0.996 1.000 0.000
#> SRR1313141 1 0.0000 0.996 1.000 0.000
#> SRR1313139 1 0.0000 0.996 1.000 0.000
#> SRR1313143 1 0.0000 0.996 1.000 0.000
#> SRR1313142 1 0.0000 0.996 1.000 0.000
#> SRR1313144 1 0.0000 0.996 1.000 0.000
#> SRR1313145 1 0.0000 0.996 1.000 0.000
#> SRR1313146 1 0.0000 0.996 1.000 0.000
#> SRR1313147 1 0.0000 0.996 1.000 0.000
#> SRR1313150 1 0.0000 0.996 1.000 0.000
#> SRR1313149 1 0.0000 0.996 1.000 0.000
#> SRR1313152 1 0.0000 0.996 1.000 0.000
#> SRR1313151 1 0.0000 0.996 1.000 0.000
#> SRR1313154 1 0.0000 0.996 1.000 0.000
#> SRR1313153 1 0.0000 0.996 1.000 0.000
#> SRR1313156 1 0.0000 0.996 1.000 0.000
#> SRR1313155 1 0.0000 0.996 1.000 0.000
#> SRR1313157 1 0.0000 0.996 1.000 0.000
#> SRR1313158 1 0.0000 0.996 1.000 0.000
#> SRR1313161 1 0.0000 0.996 1.000 0.000
#> SRR1313159 2 0.0000 0.975 0.000 1.000
#> SRR1313160 1 0.0000 0.996 1.000 0.000
#> SRR1313162 1 0.0000 0.996 1.000 0.000
#> SRR1313163 1 0.0000 0.996 1.000 0.000
#> SRR1313165 1 0.0000 0.996 1.000 0.000
#> SRR1313166 1 0.0000 0.996 1.000 0.000
#> SRR1313164 1 0.0000 0.996 1.000 0.000
#> SRR1313167 1 0.0000 0.996 1.000 0.000
#> SRR1313168 1 0.0000 0.996 1.000 0.000
#> SRR1313170 2 0.8813 0.590 0.300 0.700
#> SRR1313169 1 0.0000 0.996 1.000 0.000
#> SRR1313172 2 0.0000 0.975 0.000 1.000
#> SRR1313171 1 0.0000 0.996 1.000 0.000
#> SRR1313174 2 0.0000 0.975 0.000 1.000
#> SRR1313173 1 0.0000 0.996 1.000 0.000
#> SRR1313176 2 0.0000 0.975 0.000 1.000
#> SRR1313175 2 0.0000 0.975 0.000 1.000
#> SRR1313178 2 0.0000 0.975 0.000 1.000
#> SRR1313177 2 0.0000 0.975 0.000 1.000
#> SRR1313179 2 0.0000 0.975 0.000 1.000
#> SRR1313180 2 0.0000 0.975 0.000 1.000
#> SRR1313181 2 0.0000 0.975 0.000 1.000
#> SRR1313183 2 0.0000 0.975 0.000 1.000
#> SRR1313182 2 0.0000 0.975 0.000 1.000
#> SRR1313184 2 0.0000 0.975 0.000 1.000
#> SRR1313185 2 0.0000 0.975 0.000 1.000
#> SRR1313188 2 0.0000 0.975 0.000 1.000
#> SRR1313187 2 0.0000 0.975 0.000 1.000
#> SRR1313186 2 0.0000 0.975 0.000 1.000
#> SRR1313189 2 0.0000 0.975 0.000 1.000
#> SRR1313190 2 0.0000 0.975 0.000 1.000
#> SRR1313191 2 0.0000 0.975 0.000 1.000
#> SRR1313192 2 0.0000 0.975 0.000 1.000
#> SRR1313193 2 0.0000 0.975 0.000 1.000
#> SRR1313194 2 0.0000 0.975 0.000 1.000
#> SRR1313195 2 0.0000 0.975 0.000 1.000
#> SRR1313196 2 0.0000 0.975 0.000 1.000
#> SRR1313197 2 0.0000 0.975 0.000 1.000
#> SRR1313198 2 0.0000 0.975 0.000 1.000
#> SRR1313199 2 0.0000 0.975 0.000 1.000
#> SRR1313200 2 0.0000 0.975 0.000 1.000
#> SRR1313201 2 0.0000 0.975 0.000 1.000
#> SRR1313202 2 0.0000 0.975 0.000 1.000
#> SRR1313203 2 0.0000 0.975 0.000 1.000
#> SRR1313204 2 0.0000 0.975 0.000 1.000
#> SRR1313205 2 0.0000 0.975 0.000 1.000
#> SRR1313207 2 0.0000 0.975 0.000 1.000
#> SRR1313208 2 0.0000 0.975 0.000 1.000
#> SRR1313206 2 0.0000 0.975 0.000 1.000
#> SRR1313210 2 0.0000 0.975 0.000 1.000
#> SRR1313209 2 0.0000 0.975 0.000 1.000
#> SRR1313211 2 0.0000 0.975 0.000 1.000
#> SRR1313212 2 0.0000 0.975 0.000 1.000
#> SRR1313214 2 0.0000 0.975 0.000 1.000
#> SRR1313215 2 0.0000 0.975 0.000 1.000
#> SRR1313213 2 0.0000 0.975 0.000 1.000
#> SRR1313216 2 0.0000 0.975 0.000 1.000
#> SRR1313217 2 0.0000 0.975 0.000 1.000
#> SRR1313219 2 0.0000 0.975 0.000 1.000
#> SRR1313220 2 0.0000 0.975 0.000 1.000
#> SRR1313218 2 0.0000 0.975 0.000 1.000
#> SRR1313222 2 0.0000 0.975 0.000 1.000
#> SRR1313221 2 0.0000 0.975 0.000 1.000
#> SRR1313223 2 0.0000 0.975 0.000 1.000
#> SRR1313224 2 0.0000 0.975 0.000 1.000
#> SRR1313225 2 0.0000 0.975 0.000 1.000
#> SRR1313226 2 0.0000 0.975 0.000 1.000
#> SRR1313227 2 0.0000 0.975 0.000 1.000
#> SRR1313228 2 0.0000 0.975 0.000 1.000
#> SRR1313229 2 0.0000 0.975 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.5905 0.402 0.648 0.000 0.352
#> SRR1313063 3 0.5835 0.532 0.340 0.000 0.660
#> SRR1313064 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313067 3 0.5138 0.678 0.252 0.000 0.748
#> SRR1313068 3 0.2625 0.867 0.084 0.000 0.916
#> SRR1313069 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313076 3 0.5016 0.694 0.240 0.000 0.760
#> SRR1313077 3 0.5178 0.673 0.256 0.000 0.744
#> SRR1313078 3 0.5138 0.678 0.252 0.000 0.748
#> SRR1313079 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313080 3 0.4702 0.730 0.212 0.000 0.788
#> SRR1313081 3 0.6180 0.355 0.416 0.000 0.584
#> SRR1313082 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313091 3 0.6252 0.196 0.000 0.444 0.556
#> SRR1313093 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313100 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313105 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313109 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313108 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313116 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313128 1 0.4750 0.759 0.784 0.000 0.216
#> SRR1313126 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313130 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313132 1 0.5178 0.708 0.744 0.000 0.256
#> SRR1313129 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313133 1 0.5058 0.724 0.756 0.000 0.244
#> SRR1313131 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313134 1 0.4796 0.754 0.780 0.000 0.220
#> SRR1313135 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313136 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313137 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313138 1 0.6372 0.747 0.756 0.068 0.176
#> SRR1313140 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313141 1 0.3038 0.865 0.896 0.000 0.104
#> SRR1313139 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313143 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313142 1 0.4702 0.763 0.788 0.000 0.212
#> SRR1313144 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313145 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313146 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313147 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313149 1 0.1289 0.919 0.968 0.000 0.032
#> SRR1313152 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313151 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313154 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313153 1 0.1964 0.902 0.944 0.000 0.056
#> SRR1313156 1 0.5681 0.722 0.748 0.016 0.236
#> SRR1313155 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313157 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313158 1 0.4796 0.754 0.780 0.000 0.220
#> SRR1313161 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313159 2 0.8835 0.412 0.180 0.576 0.244
#> SRR1313160 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313162 1 0.5650 0.620 0.688 0.000 0.312
#> SRR1313163 1 0.1031 0.924 0.976 0.000 0.024
#> SRR1313165 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313166 1 0.0424 0.933 0.992 0.000 0.008
#> SRR1313164 1 0.5178 0.708 0.744 0.000 0.256
#> SRR1313167 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313170 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313169 1 0.0000 0.938 1.000 0.000 0.000
#> SRR1313172 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313171 1 0.5291 0.691 0.732 0.000 0.268
#> SRR1313174 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.938 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313184 2 0.4002 0.798 0.000 0.840 0.160
#> SRR1313185 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313203 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313204 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313226 3 0.6111 0.355 0.000 0.396 0.604
#> SRR1313227 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.990 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.990 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.3726 0.702 0.000 0.000 0.212 0.788
#> SRR1313063 4 0.3764 0.697 0.000 0.000 0.216 0.784
#> SRR1313064 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313067 4 0.4072 0.655 0.000 0.000 0.252 0.748
#> SRR1313068 3 0.1302 0.928 0.000 0.000 0.956 0.044
#> SRR1313069 4 0.0817 0.840 0.024 0.000 0.000 0.976
#> SRR1313070 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.4898 0.333 0.000 0.000 0.416 0.584
#> SRR1313077 4 0.3764 0.697 0.000 0.000 0.216 0.784
#> SRR1313078 4 0.4103 0.650 0.000 0.000 0.256 0.744
#> SRR1313079 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313080 3 0.3400 0.751 0.000 0.000 0.820 0.180
#> SRR1313081 4 0.3764 0.697 0.000 0.000 0.216 0.784
#> SRR1313082 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.865 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.4477 0.577 0.000 0.312 0.688 0.000
#> SRR1313093 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313096 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313094 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.1022 0.940 0.032 0.000 0.968 0.000
#> SRR1313098 3 0.0921 0.944 0.028 0.000 0.972 0.000
#> SRR1313101 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.1211 0.932 0.040 0.000 0.960 0.000
#> SRR1313100 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0921 0.945 0.000 0.028 0.972 0.000
#> SRR1313104 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313108 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313111 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.3764 0.736 0.000 0.216 0.784 0.000
#> SRR1313120 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313126 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313130 3 0.1557 0.919 0.000 0.056 0.944 0.000
#> SRR1313132 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313129 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313131 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313134 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313135 1 0.3801 0.960 0.780 0.000 0.000 0.220
#> SRR1313136 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313137 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313138 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313140 1 0.4304 0.885 0.716 0.000 0.000 0.284
#> SRR1313141 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313139 1 0.4543 0.827 0.676 0.000 0.000 0.324
#> SRR1313143 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313142 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313144 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313145 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313146 1 0.3801 0.960 0.780 0.000 0.000 0.220
#> SRR1313147 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313150 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313149 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313152 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313151 1 0.3873 0.952 0.772 0.000 0.000 0.228
#> SRR1313154 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313153 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313156 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313155 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313157 1 0.3837 0.956 0.776 0.000 0.000 0.224
#> SRR1313158 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313161 4 0.4972 -0.337 0.456 0.000 0.000 0.544
#> SRR1313159 1 0.4775 0.868 0.784 0.076 0.000 0.140
#> SRR1313160 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313162 1 0.4406 0.925 0.780 0.000 0.028 0.192
#> SRR1313163 1 0.3908 0.959 0.784 0.004 0.000 0.212
#> SRR1313165 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313166 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313164 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313167 4 0.3219 0.633 0.164 0.000 0.000 0.836
#> SRR1313168 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313170 1 0.6764 0.417 0.596 0.144 0.260 0.000
#> SRR1313169 1 0.3873 0.953 0.772 0.000 0.000 0.228
#> SRR1313172 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313171 1 0.3764 0.963 0.784 0.000 0.000 0.216
#> SRR1313174 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313173 3 0.0000 0.967 0.000 0.000 1.000 0.000
#> SRR1313176 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313175 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313177 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313179 1 0.2345 0.531 0.900 0.100 0.000 0.000
#> SRR1313180 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313183 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313182 2 0.0469 0.891 0.012 0.988 0.000 0.000
#> SRR1313184 2 0.4679 0.778 0.352 0.648 0.000 0.000
#> SRR1313185 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313190 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313191 2 0.0921 0.893 0.028 0.972 0.000 0.000
#> SRR1313192 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313193 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313194 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313200 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313202 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313203 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313204 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313205 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313207 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313208 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313206 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313210 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313214 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313216 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313218 2 0.2469 0.899 0.108 0.892 0.000 0.000
#> SRR1313222 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313221 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313223 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313224 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313225 2 0.0000 0.890 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.4477 0.615 0.000 0.312 0.688 0.000
#> SRR1313227 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313228 2 0.3764 0.905 0.216 0.784 0.000 0.000
#> SRR1313229 2 0.3764 0.905 0.216 0.784 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313063 4 0.0290 0.965 0.000 0.000 0.008 0.992 0.000
#> SRR1313064 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313066 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313067 4 0.1410 0.921 0.000 0.000 0.060 0.940 0.000
#> SRR1313068 3 0.0794 0.960 0.000 0.000 0.972 0.028 0.000
#> SRR1313069 4 0.2074 0.874 0.104 0.000 0.000 0.896 0.000
#> SRR1313070 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 3 0.3661 0.619 0.000 0.000 0.724 0.276 0.000
#> SRR1313077 4 0.1043 0.940 0.000 0.000 0.040 0.960 0.000
#> SRR1313078 4 0.2377 0.848 0.000 0.000 0.128 0.872 0.000
#> SRR1313079 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 3 0.3242 0.724 0.000 0.000 0.784 0.216 0.000
#> SRR1313081 4 0.0963 0.944 0.000 0.000 0.036 0.964 0.000
#> SRR1313082 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313084 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313085 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313087 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0000 0.970 0.000 0.000 0.000 1.000 0.000
#> SRR1313092 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 3 0.0510 0.972 0.000 0.000 0.984 0.000 0.016
#> SRR1313093 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313095 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313096 3 0.0162 0.982 0.000 0.000 0.996 0.000 0.004
#> SRR1313094 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.0324 0.979 0.004 0.000 0.992 0.000 0.004
#> SRR1313098 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313101 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313105 3 0.0404 0.976 0.000 0.000 0.988 0.000 0.012
#> SRR1313104 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313106 3 0.0404 0.976 0.000 0.000 0.988 0.000 0.012
#> SRR1313109 3 0.0162 0.982 0.000 0.000 0.996 0.000 0.004
#> SRR1313108 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313111 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0162 0.982 0.000 0.000 0.996 0.000 0.004
#> SRR1313115 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313114 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0162 0.982 0.000 0.000 0.996 0.000 0.004
#> SRR1313118 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 5 0.0162 0.993 0.000 0.000 0.004 0.000 0.996
#> SRR1313120 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313119 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313124 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313123 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313126 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313130 3 0.1732 0.909 0.000 0.000 0.920 0.000 0.080
#> SRR1313132 1 0.0162 0.965 0.996 0.000 0.000 0.000 0.004
#> SRR1313129 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313131 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313134 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313135 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.1544 0.908 0.932 0.000 0.000 0.068 0.000
#> SRR1313141 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313139 1 0.1792 0.891 0.916 0.000 0.000 0.084 0.000
#> SRR1313143 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313142 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313144 1 0.0162 0.965 0.996 0.000 0.000 0.000 0.004
#> SRR1313145 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313152 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0162 0.965 0.996 0.000 0.000 0.000 0.004
#> SRR1313155 1 0.0290 0.961 0.992 0.000 0.000 0.008 0.000
#> SRR1313157 1 0.0510 0.955 0.984 0.000 0.000 0.016 0.000
#> SRR1313158 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.3612 0.628 0.732 0.000 0.000 0.268 0.000
#> SRR1313159 1 0.0162 0.965 0.996 0.000 0.000 0.000 0.004
#> SRR1313160 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.0566 0.955 0.984 0.000 0.012 0.000 0.004
#> SRR1313163 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313164 1 0.0162 0.965 0.996 0.000 0.000 0.000 0.004
#> SRR1313167 4 0.3796 0.571 0.300 0.000 0.000 0.700 0.000
#> SRR1313168 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 1 0.5590 0.555 0.640 0.000 0.204 0.000 0.156
#> SRR1313169 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 2 0.0162 0.987 0.000 0.996 0.004 0.000 0.000
#> SRR1313171 1 0.0000 0.966 1.000 0.000 0.000 0.000 0.000
#> SRR1313174 5 0.0290 0.995 0.000 0.008 0.000 0.000 0.992
#> SRR1313173 3 0.0000 0.984 0.000 0.000 1.000 0.000 0.000
#> SRR1313176 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313178 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 1 0.4397 0.239 0.564 0.432 0.000 0.000 0.004
#> SRR1313180 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313181 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 5 0.0609 0.984 0.000 0.020 0.000 0.000 0.980
#> SRR1313184 2 0.0162 0.987 0.000 0.996 0.000 0.000 0.004
#> SRR1313185 5 0.0290 0.995 0.000 0.008 0.000 0.000 0.992
#> SRR1313188 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313187 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313186 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313189 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 5 0.0510 0.988 0.000 0.016 0.000 0.000 0.984
#> SRR1313192 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313195 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313196 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313197 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313198 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313199 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313201 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313203 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313204 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0162 0.987 0.000 0.996 0.000 0.000 0.004
#> SRR1313210 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313209 5 0.0290 0.995 0.000 0.008 0.000 0.000 0.992
#> SRR1313211 5 0.0290 0.995 0.000 0.008 0.000 0.000 0.992
#> SRR1313212 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313215 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313213 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313217 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313219 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313220 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.3508 0.661 0.000 0.748 0.000 0.000 0.252
#> SRR1313222 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 5 0.0162 0.998 0.000 0.004 0.000 0.000 0.996
#> SRR1313226 5 0.0162 0.993 0.000 0.000 0.004 0.000 0.996
#> SRR1313227 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.991 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 6 0.4168 0.3435 0.000 0.000 0.016 0.400 0.000 0.584
#> SRR1313063 6 0.4301 0.3636 0.000 0.000 0.024 0.392 0.000 0.584
#> SRR1313064 4 0.2340 0.6937 0.000 0.000 0.000 0.852 0.000 0.148
#> SRR1313065 4 0.2178 0.7360 0.132 0.000 0.000 0.868 0.000 0.000
#> SRR1313066 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 6 0.4786 0.4468 0.000 0.000 0.064 0.352 0.000 0.584
#> SRR1313068 6 0.4926 0.4954 0.000 0.000 0.336 0.080 0.000 0.584
#> SRR1313069 4 0.3743 0.6081 0.252 0.000 0.000 0.724 0.000 0.024
#> SRR1313070 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.3868 -0.1410 0.000 0.000 0.000 0.504 0.000 0.496
#> SRR1313074 4 0.0260 0.8253 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313075 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 6 0.4846 0.4704 0.000 0.000 0.356 0.068 0.000 0.576
#> SRR1313077 6 0.4786 0.4468 0.000 0.000 0.064 0.352 0.000 0.584
#> SRR1313078 6 0.4823 0.4505 0.000 0.000 0.068 0.348 0.000 0.584
#> SRR1313079 4 0.1501 0.7731 0.000 0.000 0.000 0.924 0.000 0.076
#> SRR1313080 6 0.5388 0.5471 0.000 0.000 0.228 0.188 0.000 0.584
#> SRR1313081 6 0.4786 0.4468 0.000 0.000 0.064 0.352 0.000 0.584
#> SRR1313082 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313083 4 0.0146 0.8273 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313084 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 4 0.2597 0.7007 0.176 0.000 0.000 0.824 0.000 0.000
#> SRR1313087 4 0.3727 0.2123 0.000 0.000 0.000 0.612 0.000 0.388
#> SRR1313088 4 0.2823 0.6705 0.204 0.000 0.000 0.796 0.000 0.000
#> SRR1313089 4 0.0000 0.8290 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313090 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313091 3 0.1141 0.8536 0.000 0.000 0.948 0.000 0.052 0.000
#> SRR1313093 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313095 3 0.0547 0.8839 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313096 3 0.3810 0.2010 0.000 0.000 0.572 0.000 0.000 0.428
#> SRR1313094 3 0.0000 0.8859 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313097 3 0.0000 0.8859 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313099 3 0.3151 0.6092 0.000 0.000 0.748 0.000 0.000 0.252
#> SRR1313098 6 0.3915 0.3598 0.000 0.000 0.412 0.004 0.000 0.584
#> SRR1313101 3 0.0713 0.8789 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313102 3 0.1267 0.8619 0.000 0.000 0.940 0.000 0.000 0.060
#> SRR1313103 3 0.1444 0.8534 0.000 0.000 0.928 0.000 0.000 0.072
#> SRR1313100 6 0.3838 0.2711 0.000 0.000 0.448 0.000 0.000 0.552
#> SRR1313105 3 0.0790 0.8713 0.000 0.000 0.968 0.000 0.032 0.000
#> SRR1313104 3 0.0458 0.8855 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313107 3 0.0547 0.8822 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313106 3 0.0972 0.8766 0.000 0.000 0.964 0.000 0.028 0.008
#> SRR1313109 3 0.1327 0.8564 0.000 0.000 0.936 0.000 0.000 0.064
#> SRR1313108 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313111 3 0.0790 0.8777 0.000 0.000 0.968 0.000 0.000 0.032
#> SRR1313110 3 0.3833 0.1785 0.000 0.000 0.556 0.000 0.000 0.444
#> SRR1313112 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313113 3 0.0000 0.8859 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313115 3 0.0458 0.8855 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313114 3 0.2340 0.7791 0.000 0.000 0.852 0.000 0.000 0.148
#> SRR1313117 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313118 3 0.1714 0.8431 0.000 0.000 0.908 0.000 0.000 0.092
#> SRR1313116 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313120 3 0.0632 0.8830 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313119 3 0.0713 0.8789 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313122 3 0.0547 0.8839 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313124 3 0.0363 0.8864 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1313121 3 0.0458 0.8855 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313125 3 0.0713 0.8817 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1313127 3 0.3659 0.3227 0.000 0.000 0.636 0.000 0.000 0.364
#> SRR1313123 3 0.1007 0.8716 0.000 0.000 0.956 0.000 0.000 0.044
#> SRR1313128 1 0.1075 0.8875 0.952 0.000 0.000 0.000 0.000 0.048
#> SRR1313126 6 0.3789 0.3503 0.000 0.000 0.416 0.000 0.000 0.584
#> SRR1313130 3 0.2527 0.7053 0.000 0.000 0.832 0.000 0.168 0.000
#> SRR1313132 1 0.3727 0.6037 0.612 0.000 0.000 0.000 0.000 0.388
#> SRR1313129 3 0.1267 0.8619 0.000 0.000 0.940 0.000 0.000 0.060
#> SRR1313133 1 0.0865 0.8919 0.964 0.000 0.000 0.000 0.000 0.036
#> SRR1313131 3 0.3076 0.6055 0.000 0.000 0.760 0.000 0.000 0.240
#> SRR1313134 1 0.0146 0.8975 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313135 1 0.0632 0.8951 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313136 1 0.0603 0.8934 0.980 0.000 0.004 0.000 0.000 0.016
#> SRR1313137 1 0.0632 0.8917 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313138 1 0.1204 0.8833 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1313140 1 0.0260 0.8963 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1313141 1 0.0632 0.8948 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313139 1 0.3563 0.4275 0.664 0.000 0.000 0.336 0.000 0.000
#> SRR1313143 1 0.0632 0.8948 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313142 1 0.1556 0.8717 0.920 0.000 0.000 0.000 0.000 0.080
#> SRR1313144 1 0.3607 0.6460 0.652 0.000 0.000 0.000 0.000 0.348
#> SRR1313145 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0146 0.8975 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313150 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.1075 0.8876 0.952 0.000 0.000 0.000 0.000 0.048
#> SRR1313152 1 0.0146 0.8975 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313151 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313153 1 0.1714 0.8640 0.908 0.000 0.000 0.000 0.000 0.092
#> SRR1313156 1 0.0632 0.8953 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313155 1 0.1082 0.8789 0.956 0.000 0.000 0.040 0.000 0.004
#> SRR1313157 1 0.0935 0.8839 0.964 0.000 0.000 0.032 0.000 0.004
#> SRR1313158 1 0.1225 0.8893 0.952 0.000 0.012 0.000 0.000 0.036
#> SRR1313161 1 0.4908 -0.0841 0.476 0.000 0.012 0.476 0.000 0.036
#> SRR1313159 1 0.3727 0.6037 0.612 0.000 0.000 0.000 0.000 0.388
#> SRR1313160 1 0.1367 0.8825 0.944 0.000 0.012 0.000 0.000 0.044
#> SRR1313162 1 0.3828 0.5311 0.560 0.000 0.000 0.000 0.000 0.440
#> SRR1313163 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.8971 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.0146 0.8971 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313164 1 0.3706 0.6130 0.620 0.000 0.000 0.000 0.000 0.380
#> SRR1313167 4 0.3634 0.4408 0.356 0.000 0.000 0.644 0.000 0.000
#> SRR1313168 1 0.0632 0.8917 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313170 6 0.6063 -0.1854 0.348 0.000 0.264 0.000 0.000 0.388
#> SRR1313169 1 0.1713 0.8635 0.928 0.000 0.000 0.044 0.000 0.028
#> SRR1313172 2 0.1858 0.8571 0.000 0.904 0.092 0.000 0.000 0.004
#> SRR1313171 1 0.2941 0.7732 0.780 0.000 0.000 0.000 0.000 0.220
#> SRR1313174 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313173 3 0.3866 -0.1078 0.000 0.000 0.516 0.000 0.000 0.484
#> SRR1313176 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 6 0.6041 -0.2663 0.360 0.252 0.000 0.000 0.000 0.388
#> SRR1313180 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 5 0.1141 0.9371 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313184 2 0.3862 0.5249 0.000 0.608 0.004 0.000 0.000 0.388
#> SRR1313185 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313188 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313187 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313186 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.0363 0.9843 0.000 0.012 0.000 0.000 0.988 0.000
#> SRR1313192 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313194 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313195 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313196 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313197 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313198 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313203 2 0.2996 0.7004 0.000 0.772 0.000 0.000 0.000 0.228
#> SRR1313204 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313211 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313215 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313217 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313219 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.2730 0.7470 0.000 0.808 0.000 0.000 0.192 0.000
#> SRR1313222 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313226 5 0.0000 0.9971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9670 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "hclust"]
# you can also extract it by
# res = res_list["MAD:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.450 0.857 0.876 0.4309 0.540 0.540
#> 3 3 0.573 0.799 0.879 0.4647 0.796 0.634
#> 4 4 0.570 0.615 0.791 0.1004 0.972 0.924
#> 5 5 0.611 0.534 0.731 0.0508 0.934 0.816
#> 6 6 0.656 0.481 0.682 0.0347 0.908 0.730
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0376 0.807 0.996 0.004
#> SRR1313063 1 0.0376 0.807 0.996 0.004
#> SRR1313064 1 0.0000 0.806 1.000 0.000
#> SRR1313065 1 0.1843 0.823 0.972 0.028
#> SRR1313066 1 0.0000 0.806 1.000 0.000
#> SRR1313067 1 0.1633 0.820 0.976 0.024
#> SRR1313068 1 0.0376 0.807 0.996 0.004
#> SRR1313069 1 0.0000 0.806 1.000 0.000
#> SRR1313070 1 0.0000 0.806 1.000 0.000
#> SRR1313071 1 0.0000 0.806 1.000 0.000
#> SRR1313072 1 0.0000 0.806 1.000 0.000
#> SRR1313073 1 0.0376 0.807 0.996 0.004
#> SRR1313074 1 0.0000 0.806 1.000 0.000
#> SRR1313075 1 0.0000 0.806 1.000 0.000
#> SRR1313076 1 0.0376 0.807 0.996 0.004
#> SRR1313077 1 0.0376 0.807 0.996 0.004
#> SRR1313078 1 0.0376 0.807 0.996 0.004
#> SRR1313079 1 0.0000 0.806 1.000 0.000
#> SRR1313080 1 0.0376 0.807 0.996 0.004
#> SRR1313081 1 0.0376 0.807 0.996 0.004
#> SRR1313082 1 0.1843 0.823 0.972 0.028
#> SRR1313083 1 0.1843 0.823 0.972 0.028
#> SRR1313084 1 0.0000 0.806 1.000 0.000
#> SRR1313085 1 0.0000 0.806 1.000 0.000
#> SRR1313086 1 0.5178 0.869 0.884 0.116
#> SRR1313087 1 0.0000 0.806 1.000 0.000
#> SRR1313088 1 0.0000 0.806 1.000 0.000
#> SRR1313089 1 0.0000 0.806 1.000 0.000
#> SRR1313092 1 0.7602 0.877 0.780 0.220
#> SRR1313090 1 0.8081 0.859 0.752 0.248
#> SRR1313091 1 0.9963 0.477 0.536 0.464
#> SRR1313093 1 0.6531 0.885 0.832 0.168
#> SRR1313095 1 0.6712 0.886 0.824 0.176
#> SRR1313096 1 0.6531 0.885 0.832 0.168
#> SRR1313094 1 0.7602 0.877 0.780 0.220
#> SRR1313097 1 0.8267 0.848 0.740 0.260
#> SRR1313099 1 0.9087 0.775 0.676 0.324
#> SRR1313098 1 0.6531 0.885 0.832 0.168
#> SRR1313101 1 0.8081 0.858 0.752 0.248
#> SRR1313102 1 0.8081 0.859 0.752 0.248
#> SRR1313103 1 0.8861 0.802 0.696 0.304
#> SRR1313100 1 0.6801 0.887 0.820 0.180
#> SRR1313105 1 0.9460 0.710 0.636 0.364
#> SRR1313104 1 0.8081 0.859 0.752 0.248
#> SRR1313107 1 0.9087 0.775 0.676 0.324
#> SRR1313106 2 0.9933 -0.215 0.452 0.548
#> SRR1313109 1 0.9970 0.466 0.532 0.468
#> SRR1313108 1 0.6531 0.885 0.832 0.168
#> SRR1313111 1 0.8861 0.802 0.696 0.304
#> SRR1313110 1 0.8016 0.861 0.756 0.244
#> SRR1313112 1 0.8327 0.844 0.736 0.264
#> SRR1313113 1 0.8763 0.809 0.704 0.296
#> SRR1313115 1 0.6531 0.885 0.832 0.168
#> SRR1313114 1 0.7815 0.868 0.768 0.232
#> SRR1313117 1 0.8081 0.858 0.752 0.248
#> SRR1313118 1 0.7950 0.863 0.760 0.240
#> SRR1313116 2 0.8608 0.476 0.284 0.716
#> SRR1313120 1 0.9087 0.775 0.676 0.324
#> SRR1313119 1 0.8081 0.859 0.752 0.248
#> SRR1313122 1 0.6712 0.886 0.824 0.176
#> SRR1313124 1 0.8081 0.859 0.752 0.248
#> SRR1313121 1 0.8081 0.859 0.752 0.248
#> SRR1313125 1 0.8081 0.858 0.752 0.248
#> SRR1313127 1 0.6623 0.886 0.828 0.172
#> SRR1313123 1 0.7815 0.868 0.768 0.232
#> SRR1313128 1 0.7139 0.885 0.804 0.196
#> SRR1313126 1 0.6531 0.885 0.832 0.168
#> SRR1313130 1 0.9963 0.477 0.536 0.464
#> SRR1313132 1 0.8661 0.823 0.712 0.288
#> SRR1313129 1 0.8955 0.790 0.688 0.312
#> SRR1313133 1 0.7139 0.885 0.804 0.196
#> SRR1313131 1 0.6531 0.885 0.832 0.168
#> SRR1313134 1 0.7139 0.885 0.804 0.196
#> SRR1313135 1 0.7139 0.885 0.804 0.196
#> SRR1313136 1 0.7139 0.885 0.804 0.196
#> SRR1313137 1 0.6973 0.886 0.812 0.188
#> SRR1313138 1 0.7056 0.886 0.808 0.192
#> SRR1313140 1 0.5629 0.876 0.868 0.132
#> SRR1313141 1 0.6531 0.885 0.832 0.168
#> SRR1313139 1 0.5629 0.876 0.868 0.132
#> SRR1313143 1 0.6531 0.885 0.832 0.168
#> SRR1313142 1 0.7056 0.886 0.808 0.192
#> SRR1313144 1 0.7528 0.879 0.784 0.216
#> SRR1313145 1 0.7139 0.885 0.804 0.196
#> SRR1313146 1 0.7139 0.885 0.804 0.196
#> SRR1313147 1 0.6973 0.886 0.812 0.188
#> SRR1313150 1 0.6973 0.886 0.812 0.188
#> SRR1313149 1 0.6531 0.885 0.832 0.168
#> SRR1313152 1 0.6973 0.886 0.812 0.188
#> SRR1313151 1 0.7139 0.885 0.804 0.196
#> SRR1313154 1 0.7453 0.881 0.788 0.212
#> SRR1313153 1 0.7056 0.886 0.808 0.192
#> SRR1313156 1 0.7056 0.886 0.808 0.192
#> SRR1313155 1 0.7139 0.885 0.804 0.196
#> SRR1313157 1 0.6973 0.886 0.812 0.188
#> SRR1313158 1 0.7139 0.885 0.804 0.196
#> SRR1313161 1 0.6973 0.886 0.812 0.188
#> SRR1313159 1 0.9977 0.441 0.528 0.472
#> SRR1313160 1 0.6973 0.886 0.812 0.188
#> SRR1313162 1 0.6531 0.886 0.832 0.168
#> SRR1313163 1 0.7056 0.886 0.808 0.192
#> SRR1313165 1 0.6973 0.886 0.812 0.188
#> SRR1313166 1 0.7139 0.885 0.804 0.196
#> SRR1313164 1 0.7883 0.870 0.764 0.236
#> SRR1313167 1 0.6973 0.886 0.812 0.188
#> SRR1313168 1 0.6973 0.886 0.812 0.188
#> SRR1313170 2 0.7056 0.703 0.192 0.808
#> SRR1313169 1 0.6973 0.886 0.812 0.188
#> SRR1313172 2 0.9427 0.218 0.360 0.640
#> SRR1313171 1 0.7883 0.870 0.764 0.236
#> SRR1313174 2 0.0000 0.950 0.000 1.000
#> SRR1313173 1 0.6531 0.885 0.832 0.168
#> SRR1313176 2 0.0376 0.951 0.004 0.996
#> SRR1313175 2 0.0000 0.950 0.000 1.000
#> SRR1313178 2 0.0376 0.951 0.004 0.996
#> SRR1313177 2 0.0376 0.951 0.004 0.996
#> SRR1313179 2 0.2043 0.930 0.032 0.968
#> SRR1313180 2 0.4161 0.880 0.084 0.916
#> SRR1313181 2 0.0376 0.951 0.004 0.996
#> SRR1313183 2 0.0376 0.951 0.004 0.996
#> SRR1313182 2 0.0000 0.950 0.000 1.000
#> SRR1313184 2 0.2043 0.930 0.032 0.968
#> SRR1313185 2 0.0000 0.950 0.000 1.000
#> SRR1313188 2 0.4161 0.880 0.084 0.916
#> SRR1313187 2 0.4161 0.880 0.084 0.916
#> SRR1313186 2 0.0000 0.950 0.000 1.000
#> SRR1313189 2 0.0376 0.951 0.004 0.996
#> SRR1313190 2 0.0376 0.951 0.004 0.996
#> SRR1313191 2 0.0000 0.950 0.000 1.000
#> SRR1313192 2 0.0000 0.950 0.000 1.000
#> SRR1313193 2 0.0376 0.951 0.004 0.996
#> SRR1313194 2 0.4161 0.880 0.084 0.916
#> SRR1313195 2 0.4161 0.880 0.084 0.916
#> SRR1313196 2 0.4161 0.880 0.084 0.916
#> SRR1313197 2 0.0000 0.950 0.000 1.000
#> SRR1313198 2 0.0000 0.950 0.000 1.000
#> SRR1313199 2 0.0376 0.951 0.004 0.996
#> SRR1313200 2 0.4161 0.880 0.084 0.916
#> SRR1313201 2 0.0376 0.951 0.004 0.996
#> SRR1313202 2 0.4161 0.880 0.084 0.916
#> SRR1313203 1 0.8443 0.721 0.728 0.272
#> SRR1313204 2 0.0376 0.951 0.004 0.996
#> SRR1313205 2 0.0376 0.951 0.004 0.996
#> SRR1313207 2 0.0376 0.951 0.004 0.996
#> SRR1313208 2 0.0376 0.951 0.004 0.996
#> SRR1313206 2 0.0376 0.951 0.004 0.996
#> SRR1313210 2 0.0000 0.950 0.000 1.000
#> SRR1313209 2 0.0000 0.950 0.000 1.000
#> SRR1313211 2 0.0000 0.950 0.000 1.000
#> SRR1313212 2 0.0376 0.951 0.004 0.996
#> SRR1313214 2 0.0000 0.950 0.000 1.000
#> SRR1313215 2 0.0000 0.950 0.000 1.000
#> SRR1313213 2 0.0376 0.951 0.004 0.996
#> SRR1313216 2 0.0376 0.949 0.004 0.996
#> SRR1313217 2 0.0000 0.950 0.000 1.000
#> SRR1313219 2 0.0000 0.950 0.000 1.000
#> SRR1313220 2 0.0376 0.951 0.004 0.996
#> SRR1313218 2 0.0000 0.950 0.000 1.000
#> SRR1313222 2 0.0376 0.951 0.004 0.996
#> SRR1313221 2 0.0376 0.951 0.004 0.996
#> SRR1313223 2 0.0376 0.951 0.004 0.996
#> SRR1313224 2 0.0000 0.950 0.000 1.000
#> SRR1313225 2 0.0000 0.950 0.000 1.000
#> SRR1313226 2 0.4298 0.874 0.088 0.912
#> SRR1313227 2 0.0376 0.951 0.004 0.996
#> SRR1313228 2 0.0376 0.951 0.004 0.996
#> SRR1313229 2 0.0376 0.951 0.004 0.996
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.2625 0.8649 0.916 0.000 0.084
#> SRR1313063 1 0.2625 0.8649 0.916 0.000 0.084
#> SRR1313064 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313065 1 0.2772 0.8578 0.916 0.004 0.080
#> SRR1313066 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313067 1 0.3116 0.8442 0.892 0.000 0.108
#> SRR1313068 1 0.2625 0.8649 0.916 0.000 0.084
#> SRR1313069 1 0.1129 0.8781 0.976 0.004 0.020
#> SRR1313070 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313071 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313072 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313073 1 0.2625 0.8649 0.916 0.000 0.084
#> SRR1313074 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313075 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313076 1 0.2711 0.8625 0.912 0.000 0.088
#> SRR1313077 1 0.2711 0.8625 0.912 0.000 0.088
#> SRR1313078 1 0.2711 0.8625 0.912 0.000 0.088
#> SRR1313079 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313080 1 0.2625 0.8649 0.916 0.000 0.084
#> SRR1313081 1 0.2711 0.8625 0.912 0.000 0.088
#> SRR1313082 1 0.2772 0.8578 0.916 0.004 0.080
#> SRR1313083 1 0.2772 0.8578 0.916 0.004 0.080
#> SRR1313084 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313085 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313086 1 0.4805 0.7431 0.812 0.012 0.176
#> SRR1313087 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313088 1 0.1129 0.8781 0.976 0.004 0.020
#> SRR1313089 1 0.0983 0.8780 0.980 0.004 0.016
#> SRR1313092 3 0.3623 0.8088 0.072 0.032 0.896
#> SRR1313090 3 0.2806 0.8031 0.040 0.032 0.928
#> SRR1313091 3 0.6200 0.5253 0.012 0.312 0.676
#> SRR1313093 3 0.5016 0.6510 0.240 0.000 0.760
#> SRR1313095 3 0.5247 0.6823 0.224 0.008 0.768
#> SRR1313096 3 0.5465 0.5738 0.288 0.000 0.712
#> SRR1313094 3 0.3337 0.8107 0.060 0.032 0.908
#> SRR1313097 3 0.2229 0.8025 0.012 0.044 0.944
#> SRR1313099 3 0.3213 0.7740 0.008 0.092 0.900
#> SRR1313098 3 0.4755 0.7244 0.184 0.008 0.808
#> SRR1313101 3 0.1877 0.8044 0.012 0.032 0.956
#> SRR1313102 3 0.2031 0.8044 0.016 0.032 0.952
#> SRR1313103 3 0.2866 0.7869 0.008 0.076 0.916
#> SRR1313100 3 0.5122 0.7126 0.200 0.012 0.788
#> SRR1313105 3 0.3851 0.7448 0.004 0.136 0.860
#> SRR1313104 3 0.2806 0.8031 0.040 0.032 0.928
#> SRR1313107 3 0.3213 0.7740 0.008 0.092 0.900
#> SRR1313106 3 0.6688 0.2807 0.012 0.408 0.580
#> SRR1313109 3 0.6255 0.5095 0.012 0.320 0.668
#> SRR1313108 3 0.5465 0.5738 0.288 0.000 0.712
#> SRR1313111 3 0.2866 0.7869 0.008 0.076 0.916
#> SRR1313110 3 0.3112 0.7989 0.056 0.028 0.916
#> SRR1313112 3 0.2339 0.8021 0.012 0.048 0.940
#> SRR1313113 3 0.3120 0.7877 0.012 0.080 0.908
#> SRR1313115 3 0.5016 0.6510 0.240 0.000 0.760
#> SRR1313114 3 0.3181 0.7965 0.064 0.024 0.912
#> SRR1313117 3 0.1877 0.8044 0.012 0.032 0.956
#> SRR1313118 3 0.2903 0.8017 0.048 0.028 0.924
#> SRR1313116 3 0.6683 -0.0416 0.008 0.496 0.496
#> SRR1313120 3 0.3213 0.7740 0.008 0.092 0.900
#> SRR1313119 3 0.1877 0.8040 0.012 0.032 0.956
#> SRR1313122 3 0.5656 0.6239 0.264 0.008 0.728
#> SRR1313124 3 0.2806 0.8031 0.040 0.032 0.928
#> SRR1313121 3 0.1905 0.8041 0.016 0.028 0.956
#> SRR1313125 3 0.1877 0.8044 0.012 0.032 0.956
#> SRR1313127 3 0.4531 0.7424 0.168 0.008 0.824
#> SRR1313123 3 0.3083 0.7979 0.060 0.024 0.916
#> SRR1313128 3 0.4521 0.7761 0.180 0.004 0.816
#> SRR1313126 3 0.5335 0.6702 0.232 0.008 0.760
#> SRR1313130 3 0.6200 0.5253 0.012 0.312 0.676
#> SRR1313132 3 0.4745 0.8027 0.068 0.080 0.852
#> SRR1313129 3 0.4575 0.7262 0.012 0.160 0.828
#> SRR1313133 3 0.4047 0.7950 0.148 0.004 0.848
#> SRR1313131 3 0.5859 0.4797 0.344 0.000 0.656
#> SRR1313134 3 0.3551 0.7923 0.132 0.000 0.868
#> SRR1313135 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313136 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313137 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313138 3 0.4349 0.8045 0.128 0.020 0.852
#> SRR1313140 3 0.6754 0.2912 0.432 0.012 0.556
#> SRR1313141 1 0.6309 0.0135 0.504 0.000 0.496
#> SRR1313139 3 0.6754 0.2912 0.432 0.012 0.556
#> SRR1313143 1 0.6309 0.0135 0.504 0.000 0.496
#> SRR1313142 3 0.4349 0.8045 0.128 0.020 0.852
#> SRR1313144 3 0.4891 0.8021 0.124 0.040 0.836
#> SRR1313145 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313146 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313147 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313150 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313149 1 0.6309 0.0135 0.504 0.000 0.496
#> SRR1313152 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313151 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313154 3 0.3295 0.8100 0.096 0.008 0.896
#> SRR1313153 3 0.4349 0.8045 0.128 0.020 0.852
#> SRR1313156 3 0.4349 0.8045 0.128 0.020 0.852
#> SRR1313155 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313157 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313158 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313161 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313159 3 0.7406 0.4519 0.044 0.360 0.596
#> SRR1313160 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313162 3 0.5122 0.7369 0.200 0.012 0.788
#> SRR1313163 3 0.4349 0.8045 0.128 0.020 0.852
#> SRR1313165 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313166 3 0.4280 0.8059 0.124 0.020 0.856
#> SRR1313164 3 0.3765 0.8131 0.084 0.028 0.888
#> SRR1313167 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313168 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313170 2 0.6341 0.5743 0.016 0.672 0.312
#> SRR1313169 3 0.4418 0.8027 0.132 0.020 0.848
#> SRR1313172 3 0.7274 0.2157 0.028 0.452 0.520
#> SRR1313171 3 0.3765 0.8131 0.084 0.028 0.888
#> SRR1313174 2 0.1643 0.9483 0.000 0.956 0.044
#> SRR1313173 3 0.5859 0.4797 0.344 0.000 0.656
#> SRR1313176 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313175 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313178 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313179 2 0.2486 0.9259 0.008 0.932 0.060
#> SRR1313180 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313181 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313182 2 0.1411 0.9494 0.000 0.964 0.036
#> SRR1313184 2 0.2486 0.9259 0.008 0.932 0.060
#> SRR1313185 2 0.1529 0.9487 0.000 0.960 0.040
#> SRR1313188 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313187 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313186 2 0.1529 0.9487 0.000 0.960 0.040
#> SRR1313189 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313191 2 0.1643 0.9483 0.000 0.956 0.044
#> SRR1313192 2 0.0747 0.9477 0.000 0.984 0.016
#> SRR1313193 2 0.1289 0.9492 0.000 0.968 0.032
#> SRR1313194 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313195 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313196 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313197 2 0.1643 0.9483 0.000 0.956 0.044
#> SRR1313198 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313199 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313200 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313201 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313202 2 0.4514 0.8592 0.012 0.832 0.156
#> SRR1313203 1 0.8536 0.5180 0.596 0.260 0.144
#> SRR1313204 2 0.0424 0.9463 0.000 0.992 0.008
#> SRR1313205 2 0.1289 0.9492 0.000 0.968 0.032
#> SRR1313207 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313208 2 0.1289 0.9492 0.000 0.968 0.032
#> SRR1313206 2 0.1031 0.9488 0.000 0.976 0.024
#> SRR1313210 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313209 2 0.1643 0.9483 0.000 0.956 0.044
#> SRR1313211 2 0.1411 0.9487 0.000 0.964 0.036
#> SRR1313212 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313214 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313215 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313213 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313216 2 0.3193 0.9087 0.004 0.896 0.100
#> SRR1313217 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313219 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313220 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313218 2 0.1411 0.9487 0.000 0.964 0.036
#> SRR1313222 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313224 2 0.1411 0.9487 0.000 0.964 0.036
#> SRR1313225 2 0.1753 0.9474 0.000 0.952 0.048
#> SRR1313226 2 0.4575 0.8541 0.012 0.828 0.160
#> SRR1313227 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9446 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9446 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.4872 0.6643 0.244 0.000 0.028 0.728
#> SRR1313063 4 0.4872 0.6643 0.244 0.000 0.028 0.728
#> SRR1313064 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313065 4 0.2742 0.7171 0.024 0.000 0.076 0.900
#> SRR1313066 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313067 4 0.5328 0.6423 0.248 0.000 0.048 0.704
#> SRR1313068 4 0.4903 0.6620 0.248 0.000 0.028 0.724
#> SRR1313069 4 0.1406 0.7685 0.016 0.000 0.024 0.960
#> SRR1313070 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313071 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313072 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313073 4 0.4974 0.6814 0.224 0.000 0.040 0.736
#> SRR1313074 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313075 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313076 4 0.4903 0.6621 0.248 0.000 0.028 0.724
#> SRR1313077 4 0.4903 0.6621 0.248 0.000 0.028 0.724
#> SRR1313078 4 0.4903 0.6621 0.248 0.000 0.028 0.724
#> SRR1313079 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313080 4 0.4903 0.6620 0.248 0.000 0.028 0.724
#> SRR1313081 4 0.4903 0.6621 0.248 0.000 0.028 0.724
#> SRR1313082 4 0.2742 0.7171 0.024 0.000 0.076 0.900
#> SRR1313083 4 0.2742 0.7171 0.024 0.000 0.076 0.900
#> SRR1313084 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313085 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313086 4 0.4771 0.5642 0.060 0.004 0.148 0.788
#> SRR1313087 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313088 4 0.1406 0.7685 0.016 0.000 0.024 0.960
#> SRR1313089 4 0.0707 0.7770 0.000 0.000 0.020 0.980
#> SRR1313092 3 0.2650 0.6549 0.036 0.008 0.916 0.040
#> SRR1313090 3 0.2594 0.6575 0.044 0.036 0.916 0.004
#> SRR1313091 3 0.4936 0.3153 0.012 0.316 0.672 0.000
#> SRR1313093 3 0.6659 -0.3072 0.400 0.000 0.512 0.088
#> SRR1313095 3 0.5396 0.3756 0.156 0.000 0.740 0.104
#> SRR1313096 3 0.7073 -0.4453 0.412 0.000 0.464 0.124
#> SRR1313094 3 0.2364 0.6624 0.036 0.008 0.928 0.028
#> SRR1313097 3 0.1854 0.6677 0.012 0.048 0.940 0.000
#> SRR1313099 3 0.4786 0.5513 0.104 0.108 0.788 0.000
#> SRR1313098 3 0.4656 0.5041 0.136 0.000 0.792 0.072
#> SRR1313101 3 0.1798 0.6688 0.016 0.040 0.944 0.000
#> SRR1313102 3 0.2007 0.6681 0.020 0.036 0.940 0.004
#> SRR1313103 3 0.2984 0.6410 0.028 0.084 0.888 0.000
#> SRR1313100 3 0.5212 0.4437 0.140 0.004 0.764 0.092
#> SRR1313105 3 0.3763 0.5898 0.024 0.144 0.832 0.000
#> SRR1313104 3 0.2594 0.6575 0.044 0.036 0.916 0.004
#> SRR1313107 3 0.4844 0.5467 0.108 0.108 0.784 0.000
#> SRR1313106 3 0.5775 0.1376 0.032 0.408 0.560 0.000
#> SRR1313109 3 0.5193 0.2893 0.020 0.324 0.656 0.000
#> SRR1313108 3 0.7073 -0.4453 0.412 0.000 0.464 0.124
#> SRR1313111 3 0.2984 0.6410 0.028 0.084 0.888 0.000
#> SRR1313110 3 0.2814 0.6493 0.052 0.032 0.908 0.008
#> SRR1313112 3 0.2142 0.6631 0.016 0.056 0.928 0.000
#> SRR1313113 3 0.2542 0.6475 0.012 0.084 0.904 0.000
#> SRR1313115 3 0.6659 -0.3072 0.400 0.000 0.512 0.088
#> SRR1313114 3 0.3052 0.6415 0.064 0.032 0.896 0.008
#> SRR1313117 3 0.1798 0.6688 0.016 0.040 0.944 0.000
#> SRR1313118 3 0.2731 0.6553 0.048 0.032 0.912 0.008
#> SRR1313116 2 0.5780 -0.0708 0.028 0.496 0.476 0.000
#> SRR1313120 3 0.4786 0.5513 0.104 0.108 0.788 0.000
#> SRR1313119 3 0.2007 0.6679 0.020 0.036 0.940 0.004
#> SRR1313122 3 0.6027 0.2304 0.192 0.000 0.684 0.124
#> SRR1313124 3 0.2594 0.6575 0.044 0.036 0.916 0.004
#> SRR1313121 3 0.2019 0.6663 0.024 0.032 0.940 0.004
#> SRR1313125 3 0.1677 0.6694 0.012 0.040 0.948 0.000
#> SRR1313127 3 0.4301 0.5293 0.120 0.000 0.816 0.064
#> SRR1313123 3 0.2907 0.6445 0.064 0.032 0.900 0.004
#> SRR1313128 3 0.5696 0.5164 0.232 0.000 0.692 0.076
#> SRR1313126 3 0.5484 0.3541 0.164 0.000 0.732 0.104
#> SRR1313130 3 0.4936 0.3153 0.012 0.316 0.672 0.000
#> SRR1313132 3 0.5446 0.6285 0.164 0.060 0.756 0.020
#> SRR1313129 3 0.3672 0.5658 0.012 0.164 0.824 0.000
#> SRR1313133 3 0.5123 0.5637 0.232 0.000 0.724 0.044
#> SRR1313131 1 0.7249 0.4167 0.444 0.000 0.412 0.144
#> SRR1313134 3 0.5272 0.3500 0.288 0.000 0.680 0.032
#> SRR1313135 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313136 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313137 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313138 3 0.4687 0.6872 0.096 0.008 0.808 0.088
#> SRR1313140 3 0.6612 0.2187 0.072 0.004 0.524 0.400
#> SRR1313141 4 0.7883 -0.2909 0.316 0.000 0.300 0.384
#> SRR1313139 3 0.6612 0.2187 0.072 0.004 0.524 0.400
#> SRR1313143 4 0.7883 -0.2909 0.316 0.000 0.300 0.384
#> SRR1313142 3 0.4687 0.6872 0.096 0.008 0.808 0.088
#> SRR1313144 3 0.5083 0.6828 0.088 0.032 0.800 0.080
#> SRR1313145 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313146 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313147 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313150 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313149 4 0.7883 -0.2909 0.316 0.000 0.300 0.384
#> SRR1313152 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313151 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313154 3 0.4882 0.6552 0.164 0.004 0.776 0.056
#> SRR1313153 3 0.4687 0.6872 0.096 0.008 0.808 0.088
#> SRR1313156 3 0.4687 0.6872 0.096 0.008 0.808 0.088
#> SRR1313155 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313157 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313158 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313161 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313159 3 0.6538 0.2533 0.072 0.332 0.588 0.008
#> SRR1313160 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313162 3 0.5596 0.5498 0.180 0.004 0.728 0.088
#> SRR1313163 3 0.4687 0.6872 0.096 0.008 0.808 0.088
#> SRR1313165 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313166 3 0.4683 0.6880 0.100 0.008 0.808 0.084
#> SRR1313164 3 0.5735 0.5417 0.208 0.020 0.720 0.052
#> SRR1313167 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313168 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313170 2 0.5921 0.4272 0.068 0.672 0.256 0.004
#> SRR1313169 3 0.4750 0.6854 0.096 0.008 0.804 0.092
#> SRR1313172 1 0.7844 0.2870 0.444 0.236 0.316 0.004
#> SRR1313171 3 0.5735 0.5417 0.208 0.020 0.720 0.052
#> SRR1313174 2 0.0921 0.8079 0.000 0.972 0.028 0.000
#> SRR1313173 1 0.7249 0.4167 0.444 0.000 0.412 0.144
#> SRR1313176 2 0.4040 0.7541 0.248 0.752 0.000 0.000
#> SRR1313175 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313178 2 0.4072 0.7520 0.252 0.748 0.000 0.000
#> SRR1313177 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313179 2 0.5845 0.7411 0.252 0.672 0.076 0.000
#> SRR1313180 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313181 2 0.4072 0.7520 0.252 0.748 0.000 0.000
#> SRR1313183 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313182 2 0.1510 0.8111 0.016 0.956 0.028 0.000
#> SRR1313184 2 0.5845 0.7411 0.252 0.672 0.076 0.000
#> SRR1313185 2 0.1388 0.8099 0.012 0.960 0.028 0.000
#> SRR1313188 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313187 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313186 2 0.1388 0.8099 0.012 0.960 0.028 0.000
#> SRR1313189 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313190 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313191 2 0.0921 0.8079 0.000 0.972 0.028 0.000
#> SRR1313192 2 0.2915 0.8082 0.080 0.892 0.028 0.000
#> SRR1313193 2 0.1584 0.8092 0.036 0.952 0.012 0.000
#> SRR1313194 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313195 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313196 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313197 2 0.0921 0.8079 0.000 0.972 0.028 0.000
#> SRR1313198 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313199 2 0.4040 0.7541 0.248 0.752 0.000 0.000
#> SRR1313200 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313201 2 0.4040 0.7541 0.248 0.752 0.000 0.000
#> SRR1313202 2 0.3812 0.7042 0.028 0.832 0.140 0.000
#> SRR1313203 1 0.8497 -0.1616 0.412 0.116 0.076 0.396
#> SRR1313204 2 0.3893 0.7756 0.196 0.796 0.008 0.000
#> SRR1313205 2 0.1388 0.8101 0.028 0.960 0.012 0.000
#> SRR1313207 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313208 2 0.1388 0.8101 0.028 0.960 0.012 0.000
#> SRR1313206 2 0.2737 0.7991 0.104 0.888 0.008 0.000
#> SRR1313210 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313209 2 0.0921 0.8079 0.000 0.972 0.028 0.000
#> SRR1313211 2 0.1833 0.8115 0.032 0.944 0.024 0.000
#> SRR1313212 2 0.4040 0.7541 0.248 0.752 0.000 0.000
#> SRR1313214 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313215 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313213 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313216 2 0.2266 0.7739 0.004 0.912 0.084 0.000
#> SRR1313217 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313219 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313220 2 0.4040 0.7541 0.248 0.752 0.000 0.000
#> SRR1313218 2 0.1733 0.8110 0.024 0.948 0.028 0.000
#> SRR1313222 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313221 2 0.4543 0.7082 0.324 0.676 0.000 0.000
#> SRR1313223 2 0.4564 0.7055 0.328 0.672 0.000 0.000
#> SRR1313224 2 0.1733 0.8115 0.028 0.948 0.024 0.000
#> SRR1313225 2 0.1022 0.8072 0.000 0.968 0.032 0.000
#> SRR1313226 2 0.3863 0.6985 0.028 0.828 0.144 0.000
#> SRR1313227 2 0.4072 0.7520 0.252 0.748 0.000 0.000
#> SRR1313228 2 0.4072 0.7520 0.252 0.748 0.000 0.000
#> SRR1313229 2 0.4072 0.7520 0.252 0.748 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0162 0.40950 0.004 0.000 0.000 0.996 0.000
#> SRR1313063 4 0.0162 0.40950 0.004 0.000 0.000 0.996 0.000
#> SRR1313064 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313065 4 0.6146 0.54840 0.376 0.000 0.136 0.488 0.000
#> SRR1313066 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313067 4 0.0798 0.38168 0.000 0.008 0.016 0.976 0.000
#> SRR1313068 4 0.0794 0.38247 0.028 0.000 0.000 0.972 0.000
#> SRR1313069 4 0.5559 0.61269 0.380 0.000 0.076 0.544 0.000
#> SRR1313070 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313071 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313072 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313073 4 0.1410 0.43006 0.060 0.000 0.000 0.940 0.000
#> SRR1313074 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313075 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313076 4 0.0162 0.40705 0.000 0.004 0.000 0.996 0.000
#> SRR1313077 4 0.0162 0.40705 0.000 0.004 0.000 0.996 0.000
#> SRR1313078 4 0.0162 0.40705 0.000 0.004 0.000 0.996 0.000
#> SRR1313079 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313080 4 0.0794 0.38247 0.028 0.000 0.000 0.972 0.000
#> SRR1313081 4 0.0162 0.40705 0.000 0.004 0.000 0.996 0.000
#> SRR1313082 4 0.6146 0.54840 0.376 0.000 0.136 0.488 0.000
#> SRR1313083 4 0.6146 0.54840 0.376 0.000 0.136 0.488 0.000
#> SRR1313084 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313085 4 0.5415 0.62519 0.384 0.000 0.064 0.552 0.000
#> SRR1313086 4 0.6824 0.37049 0.352 0.000 0.240 0.404 0.004
#> SRR1313087 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313088 4 0.5559 0.61269 0.380 0.000 0.076 0.544 0.000
#> SRR1313089 4 0.5396 0.62617 0.376 0.000 0.064 0.560 0.000
#> SRR1313092 3 0.5623 0.71617 0.036 0.140 0.728 0.072 0.024
#> SRR1313090 3 0.5732 0.71701 0.032 0.144 0.724 0.048 0.052
#> SRR1313091 3 0.6649 0.46442 0.016 0.136 0.508 0.004 0.336
#> SRR1313093 2 0.8418 -0.33122 0.160 0.324 0.232 0.284 0.000
#> SRR1313095 3 0.6872 0.52647 0.052 0.128 0.568 0.248 0.004
#> SRR1313096 2 0.8393 -0.35854 0.184 0.324 0.184 0.308 0.000
#> SRR1313094 3 0.5443 0.72143 0.036 0.140 0.740 0.060 0.024
#> SRR1313097 3 0.5084 0.72364 0.028 0.152 0.748 0.008 0.064
#> SRR1313099 3 0.6732 0.64062 0.092 0.184 0.608 0.000 0.116
#> SRR1313098 3 0.6326 0.60921 0.048 0.112 0.640 0.196 0.004
#> SRR1313101 3 0.5217 0.72441 0.028 0.148 0.748 0.020 0.056
#> SRR1313102 3 0.5272 0.72383 0.032 0.152 0.744 0.020 0.052
#> SRR1313103 3 0.5519 0.70613 0.036 0.164 0.704 0.000 0.096
#> SRR1313100 3 0.6906 0.56936 0.048 0.132 0.588 0.220 0.012
#> SRR1313105 3 0.6119 0.66941 0.036 0.144 0.660 0.004 0.156
#> SRR1313104 3 0.5732 0.71701 0.032 0.144 0.724 0.048 0.052
#> SRR1313107 3 0.6935 0.61888 0.100 0.200 0.584 0.000 0.116
#> SRR1313106 3 0.6506 0.25637 0.024 0.088 0.448 0.004 0.436
#> SRR1313109 3 0.6587 0.44783 0.016 0.144 0.496 0.000 0.344
#> SRR1313108 2 0.8393 -0.35854 0.184 0.324 0.184 0.308 0.000
#> SRR1313111 3 0.5519 0.70613 0.036 0.164 0.704 0.000 0.096
#> SRR1313110 3 0.5899 0.71170 0.040 0.140 0.716 0.060 0.044
#> SRR1313112 3 0.5461 0.71978 0.028 0.148 0.732 0.020 0.072
#> SRR1313113 3 0.5455 0.70871 0.028 0.152 0.716 0.004 0.100
#> SRR1313115 2 0.8418 -0.33122 0.160 0.324 0.232 0.284 0.000
#> SRR1313114 3 0.5994 0.70691 0.040 0.132 0.712 0.072 0.044
#> SRR1313117 3 0.5217 0.72441 0.028 0.148 0.748 0.020 0.056
#> SRR1313118 3 0.5832 0.71535 0.036 0.140 0.720 0.056 0.048
#> SRR1313116 5 0.6345 -0.00549 0.016 0.096 0.364 0.004 0.520
#> SRR1313120 3 0.6732 0.64062 0.092 0.184 0.608 0.000 0.116
#> SRR1313119 3 0.5272 0.72360 0.032 0.152 0.744 0.020 0.052
#> SRR1313122 3 0.7527 0.43733 0.080 0.136 0.504 0.272 0.008
#> SRR1313124 3 0.5732 0.71701 0.032 0.144 0.724 0.048 0.052
#> SRR1313121 3 0.5369 0.72247 0.036 0.152 0.740 0.024 0.048
#> SRR1313125 3 0.5125 0.72489 0.028 0.148 0.752 0.016 0.056
#> SRR1313127 3 0.6401 0.61758 0.048 0.128 0.636 0.184 0.004
#> SRR1313123 3 0.5937 0.70908 0.040 0.132 0.716 0.068 0.044
#> SRR1313128 3 0.5967 0.48177 0.124 0.124 0.684 0.068 0.000
#> SRR1313126 3 0.6931 0.50773 0.052 0.128 0.556 0.260 0.004
#> SRR1313130 3 0.6649 0.46442 0.016 0.136 0.508 0.004 0.336
#> SRR1313132 3 0.4852 0.63324 0.056 0.100 0.772 0.000 0.072
#> SRR1313129 3 0.6166 0.65144 0.028 0.140 0.644 0.004 0.184
#> SRR1313133 3 0.5543 0.52997 0.108 0.124 0.716 0.052 0.000
#> SRR1313131 4 0.8419 -0.45347 0.280 0.256 0.152 0.312 0.000
#> SRR1313134 3 0.7318 0.19210 0.208 0.252 0.488 0.052 0.000
#> SRR1313135 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313136 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313137 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313138 3 0.1331 0.73314 0.040 0.000 0.952 0.000 0.008
#> SRR1313140 3 0.5568 0.34180 0.116 0.000 0.644 0.236 0.004
#> SRR1313141 1 0.7352 0.73726 0.464 0.256 0.044 0.236 0.000
#> SRR1313139 3 0.5568 0.34180 0.116 0.000 0.644 0.236 0.004
#> SRR1313143 1 0.7352 0.73726 0.464 0.256 0.044 0.236 0.000
#> SRR1313142 3 0.1331 0.73314 0.040 0.000 0.952 0.000 0.008
#> SRR1313144 3 0.1997 0.73119 0.036 0.000 0.924 0.000 0.040
#> SRR1313145 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313146 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313147 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313150 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313149 1 0.7352 0.73726 0.464 0.256 0.044 0.236 0.000
#> SRR1313152 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313151 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313154 3 0.3392 0.66008 0.064 0.084 0.848 0.000 0.004
#> SRR1313153 3 0.1331 0.73314 0.040 0.000 0.952 0.000 0.008
#> SRR1313156 3 0.1331 0.73314 0.040 0.000 0.952 0.000 0.008
#> SRR1313155 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313157 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313158 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313161 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313159 3 0.4682 0.38625 0.000 0.024 0.620 0.000 0.356
#> SRR1313160 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313162 3 0.5453 0.63485 0.052 0.044 0.716 0.180 0.008
#> SRR1313163 3 0.1331 0.73314 0.040 0.000 0.952 0.000 0.008
#> SRR1313165 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313166 3 0.1331 0.73382 0.040 0.000 0.952 0.000 0.008
#> SRR1313164 3 0.6023 0.49112 0.128 0.212 0.636 0.000 0.024
#> SRR1313167 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313168 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313170 5 0.4479 0.39894 0.000 0.036 0.264 0.000 0.700
#> SRR1313169 3 0.1408 0.73156 0.044 0.000 0.948 0.000 0.008
#> SRR1313172 2 0.7598 -0.14080 0.188 0.524 0.112 0.004 0.172
#> SRR1313171 3 0.6023 0.49112 0.128 0.212 0.636 0.000 0.024
#> SRR1313174 5 0.0162 0.72508 0.000 0.004 0.000 0.000 0.996
#> SRR1313173 4 0.8419 -0.45347 0.280 0.256 0.152 0.312 0.000
#> SRR1313176 5 0.4171 0.20416 0.000 0.396 0.000 0.000 0.604
#> SRR1313175 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313178 5 0.4192 0.18320 0.000 0.404 0.000 0.000 0.596
#> SRR1313177 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313179 5 0.5168 0.31956 0.000 0.356 0.052 0.000 0.592
#> SRR1313180 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313181 5 0.4192 0.18320 0.000 0.404 0.000 0.000 0.596
#> SRR1313183 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313182 5 0.0609 0.72268 0.000 0.020 0.000 0.000 0.980
#> SRR1313184 5 0.5168 0.31956 0.000 0.356 0.052 0.000 0.592
#> SRR1313185 5 0.0510 0.72323 0.000 0.016 0.000 0.000 0.984
#> SRR1313188 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313187 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313186 5 0.0510 0.72323 0.000 0.016 0.000 0.000 0.984
#> SRR1313189 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313190 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313191 5 0.0162 0.72508 0.000 0.004 0.000 0.000 0.996
#> SRR1313192 5 0.1965 0.67667 0.000 0.096 0.000 0.000 0.904
#> SRR1313193 5 0.1608 0.69607 0.000 0.072 0.000 0.000 0.928
#> SRR1313194 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313195 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313196 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313197 5 0.0162 0.72508 0.000 0.004 0.000 0.000 0.996
#> SRR1313198 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313199 5 0.4182 0.19394 0.000 0.400 0.000 0.000 0.600
#> SRR1313200 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313201 5 0.4150 0.22482 0.000 0.388 0.000 0.000 0.612
#> SRR1313202 5 0.2984 0.63417 0.000 0.032 0.108 0.000 0.860
#> SRR1313203 1 0.5658 0.35294 0.572 0.332 0.000 0.096 0.000
#> SRR1313204 5 0.3857 0.38353 0.000 0.312 0.000 0.000 0.688
#> SRR1313205 5 0.1410 0.70432 0.000 0.060 0.000 0.000 0.940
#> SRR1313207 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313208 5 0.1410 0.70432 0.000 0.060 0.000 0.000 0.940
#> SRR1313206 5 0.2929 0.58940 0.000 0.180 0.000 0.000 0.820
#> SRR1313210 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313209 5 0.0162 0.72508 0.000 0.004 0.000 0.000 0.996
#> SRR1313211 5 0.1341 0.70773 0.000 0.056 0.000 0.000 0.944
#> SRR1313212 5 0.4150 0.22482 0.000 0.388 0.000 0.000 0.612
#> SRR1313214 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313215 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313213 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313216 5 0.1648 0.68903 0.000 0.020 0.040 0.000 0.940
#> SRR1313217 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313219 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313220 5 0.4150 0.22482 0.000 0.388 0.000 0.000 0.612
#> SRR1313218 5 0.0880 0.71849 0.000 0.032 0.000 0.000 0.968
#> SRR1313222 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313221 2 0.4294 0.23470 0.000 0.532 0.000 0.000 0.468
#> SRR1313223 2 0.4291 0.24686 0.000 0.536 0.000 0.000 0.464
#> SRR1313224 5 0.1197 0.71185 0.000 0.048 0.000 0.000 0.952
#> SRR1313225 5 0.0162 0.72526 0.000 0.000 0.004 0.000 0.996
#> SRR1313226 5 0.3035 0.62832 0.000 0.032 0.112 0.000 0.856
#> SRR1313227 5 0.4192 0.18320 0.000 0.404 0.000 0.000 0.596
#> SRR1313228 5 0.4192 0.18320 0.000 0.404 0.000 0.000 0.596
#> SRR1313229 5 0.4192 0.18320 0.000 0.404 0.000 0.000 0.596
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0291 0.966 0.004 0.000 0.000 0.992 0.000 0.004
#> SRR1313063 4 0.0291 0.966 0.004 0.000 0.000 0.992 0.000 0.004
#> SRR1313064 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313065 5 0.7397 0.296 0.028 0.000 0.132 0.096 0.404 0.340
#> SRR1313066 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313067 4 0.0603 0.941 0.000 0.000 0.016 0.980 0.000 0.004
#> SRR1313068 4 0.0914 0.952 0.016 0.000 0.000 0.968 0.000 0.016
#> SRR1313069 5 0.7109 0.326 0.028 0.000 0.072 0.124 0.448 0.328
#> SRR1313070 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313071 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313072 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313073 4 0.2036 0.847 0.008 0.000 0.000 0.912 0.016 0.064
#> SRR1313074 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313075 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313076 4 0.0000 0.969 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313077 4 0.0000 0.969 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313078 4 0.0000 0.969 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313079 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313080 4 0.0914 0.952 0.016 0.000 0.000 0.968 0.000 0.016
#> SRR1313081 4 0.0000 0.969 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313082 5 0.7397 0.296 0.028 0.000 0.132 0.096 0.404 0.340
#> SRR1313083 5 0.7397 0.296 0.028 0.000 0.132 0.096 0.404 0.340
#> SRR1313084 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313085 5 0.6846 0.343 0.036 0.000 0.048 0.108 0.472 0.336
#> SRR1313086 5 0.7495 0.145 0.020 0.000 0.264 0.068 0.324 0.324
#> SRR1313087 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313088 5 0.7109 0.326 0.028 0.000 0.072 0.124 0.448 0.328
#> SRR1313089 5 0.6766 0.345 0.028 0.000 0.048 0.112 0.472 0.340
#> SRR1313092 3 0.5506 0.594 0.004 0.000 0.588 0.072 0.028 0.308
#> SRR1313090 3 0.5461 0.608 0.004 0.000 0.604 0.048 0.048 0.296
#> SRR1313091 3 0.7359 0.347 0.000 0.104 0.388 0.004 0.236 0.268
#> SRR1313093 6 0.7049 0.584 0.044 0.000 0.144 0.268 0.048 0.496
#> SRR1313095 3 0.6211 0.377 0.016 0.000 0.480 0.244 0.000 0.260
#> SRR1313096 6 0.6933 0.598 0.056 0.000 0.100 0.292 0.048 0.504
#> SRR1313094 3 0.5359 0.603 0.004 0.000 0.600 0.060 0.028 0.308
#> SRR1313097 3 0.5122 0.609 0.000 0.008 0.600 0.008 0.060 0.324
#> SRR1313099 3 0.6090 0.487 0.008 0.032 0.460 0.000 0.092 0.408
#> SRR1313098 3 0.5816 0.484 0.012 0.000 0.552 0.192 0.000 0.244
#> SRR1313101 3 0.5124 0.609 0.000 0.000 0.600 0.020 0.060 0.320
#> SRR1313102 3 0.5206 0.610 0.004 0.000 0.600 0.020 0.056 0.320
#> SRR1313103 3 0.5486 0.583 0.000 0.028 0.556 0.000 0.072 0.344
#> SRR1313100 3 0.6274 0.429 0.012 0.000 0.496 0.220 0.008 0.264
#> SRR1313105 3 0.6114 0.542 0.000 0.028 0.516 0.004 0.132 0.320
#> SRR1313104 3 0.5516 0.607 0.004 0.000 0.600 0.048 0.052 0.296
#> SRR1313107 3 0.6099 0.455 0.008 0.032 0.436 0.000 0.092 0.432
#> SRR1313106 3 0.7486 0.212 0.000 0.124 0.336 0.004 0.324 0.212
#> SRR1313109 3 0.7306 0.329 0.000 0.112 0.376 0.000 0.236 0.276
#> SRR1313108 6 0.6933 0.598 0.056 0.000 0.100 0.292 0.048 0.504
#> SRR1313111 3 0.5486 0.583 0.000 0.028 0.556 0.000 0.072 0.344
#> SRR1313110 3 0.5543 0.606 0.008 0.000 0.612 0.060 0.040 0.280
#> SRR1313112 3 0.5318 0.602 0.000 0.000 0.584 0.020 0.076 0.320
#> SRR1313113 3 0.5582 0.589 0.000 0.024 0.568 0.004 0.080 0.324
#> SRR1313115 6 0.7049 0.584 0.044 0.000 0.144 0.268 0.048 0.496
#> SRR1313114 3 0.5643 0.599 0.008 0.000 0.604 0.068 0.040 0.280
#> SRR1313117 3 0.5124 0.609 0.000 0.000 0.600 0.020 0.060 0.320
#> SRR1313118 3 0.5497 0.606 0.004 0.000 0.604 0.056 0.044 0.292
#> SRR1313116 5 0.6992 -0.144 0.000 0.076 0.264 0.004 0.452 0.204
#> SRR1313120 3 0.6090 0.487 0.008 0.032 0.460 0.000 0.092 0.408
#> SRR1313119 3 0.5166 0.610 0.004 0.000 0.600 0.020 0.052 0.324
#> SRR1313122 3 0.6734 0.256 0.032 0.000 0.416 0.272 0.004 0.276
#> SRR1313124 3 0.5461 0.608 0.004 0.000 0.604 0.048 0.048 0.296
#> SRR1313121 3 0.5185 0.609 0.004 0.000 0.600 0.024 0.048 0.324
#> SRR1313125 3 0.5046 0.611 0.000 0.000 0.604 0.016 0.060 0.320
#> SRR1313127 3 0.5805 0.496 0.012 0.000 0.548 0.176 0.000 0.264
#> SRR1313123 3 0.5594 0.601 0.008 0.000 0.608 0.064 0.040 0.280
#> SRR1313128 3 0.5695 0.287 0.084 0.000 0.644 0.036 0.020 0.216
#> SRR1313126 3 0.6254 0.352 0.016 0.000 0.468 0.256 0.000 0.260
#> SRR1313130 3 0.7359 0.347 0.000 0.104 0.388 0.004 0.236 0.268
#> SRR1313132 3 0.4874 0.486 0.020 0.020 0.728 0.000 0.076 0.156
#> SRR1313129 3 0.6550 0.523 0.000 0.100 0.504 0.004 0.088 0.304
#> SRR1313133 3 0.5383 0.345 0.080 0.000 0.676 0.028 0.020 0.196
#> SRR1313131 6 0.7836 0.554 0.176 0.000 0.088 0.280 0.056 0.400
#> SRR1313134 3 0.6989 -0.199 0.128 0.000 0.444 0.028 0.056 0.344
#> SRR1313135 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313136 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313137 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313138 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313140 3 0.4878 0.295 0.008 0.000 0.680 0.028 0.244 0.040
#> SRR1313141 6 0.6030 0.273 0.164 0.000 0.000 0.112 0.108 0.616
#> SRR1313139 3 0.4878 0.295 0.008 0.000 0.680 0.028 0.244 0.040
#> SRR1313143 6 0.6030 0.273 0.164 0.000 0.000 0.112 0.108 0.616
#> SRR1313142 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313144 3 0.0993 0.645 0.000 0.012 0.964 0.000 0.024 0.000
#> SRR1313145 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313146 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313147 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313150 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313149 6 0.6030 0.273 0.164 0.000 0.000 0.112 0.108 0.616
#> SRR1313152 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313151 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313154 3 0.3359 0.521 0.024 0.000 0.820 0.000 0.020 0.136
#> SRR1313153 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313156 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313155 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313157 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313158 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313161 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313159 3 0.5477 0.320 0.000 0.252 0.616 0.000 0.104 0.028
#> SRR1313160 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313162 3 0.4805 0.516 0.012 0.000 0.696 0.176 0.000 0.116
#> SRR1313163 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313165 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313166 3 0.0146 0.649 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313164 3 0.5691 0.236 0.040 0.008 0.600 0.000 0.072 0.280
#> SRR1313167 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313168 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313170 5 0.6963 -0.272 0.000 0.260 0.212 0.000 0.444 0.084
#> SRR1313169 3 0.0260 0.648 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313172 2 0.7902 -0.396 0.112 0.356 0.060 0.000 0.132 0.340
#> SRR1313171 3 0.5691 0.236 0.040 0.008 0.600 0.000 0.072 0.280
#> SRR1313174 2 0.3966 0.638 0.000 0.552 0.004 0.000 0.444 0.000
#> SRR1313173 6 0.7836 0.554 0.176 0.000 0.088 0.280 0.056 0.400
#> SRR1313176 2 0.0520 0.617 0.008 0.984 0.000 0.000 0.008 0.000
#> SRR1313175 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313178 2 0.0260 0.612 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.4003 0.593 0.016 0.804 0.048 0.000 0.108 0.024
#> SRR1313180 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313181 2 0.0260 0.612 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3944 0.646 0.000 0.568 0.004 0.000 0.428 0.000
#> SRR1313184 2 0.4003 0.593 0.016 0.804 0.048 0.000 0.108 0.024
#> SRR1313185 2 0.3950 0.644 0.000 0.564 0.004 0.000 0.432 0.000
#> SRR1313188 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313187 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313186 2 0.3950 0.644 0.000 0.564 0.004 0.000 0.432 0.000
#> SRR1313189 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.3966 0.638 0.000 0.552 0.004 0.000 0.444 0.000
#> SRR1313192 2 0.3756 0.664 0.000 0.644 0.004 0.000 0.352 0.000
#> SRR1313193 2 0.3659 0.664 0.000 0.636 0.000 0.000 0.364 0.000
#> SRR1313194 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313195 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313196 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313197 2 0.3966 0.638 0.000 0.552 0.004 0.000 0.444 0.000
#> SRR1313198 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313199 2 0.0405 0.615 0.008 0.988 0.000 0.000 0.004 0.000
#> SRR1313200 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313201 2 0.0777 0.627 0.004 0.972 0.000 0.000 0.024 0.000
#> SRR1313202 5 0.6011 -0.434 0.000 0.396 0.052 0.000 0.472 0.080
#> SRR1313203 1 0.1464 0.000 0.944 0.036 0.000 0.000 0.004 0.016
#> SRR1313204 2 0.1765 0.650 0.000 0.904 0.000 0.000 0.096 0.000
#> SRR1313205 2 0.3706 0.662 0.000 0.620 0.000 0.000 0.380 0.000
#> SRR1313207 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.3706 0.662 0.000 0.620 0.000 0.000 0.380 0.000
#> SRR1313206 2 0.3023 0.670 0.000 0.768 0.000 0.000 0.232 0.000
#> SRR1313210 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313209 2 0.3966 0.638 0.000 0.552 0.004 0.000 0.444 0.000
#> SRR1313211 2 0.3830 0.662 0.000 0.620 0.004 0.000 0.376 0.000
#> SRR1313212 2 0.0777 0.627 0.004 0.972 0.000 0.000 0.024 0.000
#> SRR1313214 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313215 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313213 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313216 2 0.5126 0.562 0.000 0.484 0.024 0.000 0.456 0.036
#> SRR1313217 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313219 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313220 2 0.0777 0.627 0.004 0.972 0.000 0.000 0.024 0.000
#> SRR1313218 2 0.3923 0.650 0.000 0.580 0.004 0.000 0.416 0.000
#> SRR1313222 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.2219 0.483 0.136 0.864 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.2260 0.479 0.140 0.860 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.3852 0.660 0.000 0.612 0.004 0.000 0.384 0.000
#> SRR1313225 2 0.4072 0.632 0.000 0.544 0.008 0.000 0.448 0.000
#> SRR1313226 5 0.6055 -0.429 0.000 0.392 0.056 0.000 0.472 0.080
#> SRR1313227 2 0.0260 0.612 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0260 0.612 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0260 0.612 0.008 0.992 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "kmeans"]
# you can also extract it by
# res = res_list["MAD:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.972 0.987 0.4591 0.544 0.544
#> 3 3 0.726 0.804 0.886 0.3951 0.785 0.616
#> 4 4 0.708 0.800 0.813 0.1347 0.878 0.669
#> 5 5 0.779 0.700 0.752 0.0743 0.910 0.669
#> 6 6 0.822 0.797 0.830 0.0418 0.937 0.707
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.9849 1.000 0.000
#> SRR1313063 1 0.000 0.9849 1.000 0.000
#> SRR1313064 1 0.000 0.9849 1.000 0.000
#> SRR1313065 1 0.000 0.9849 1.000 0.000
#> SRR1313066 1 0.000 0.9849 1.000 0.000
#> SRR1313067 1 0.000 0.9849 1.000 0.000
#> SRR1313068 1 0.000 0.9849 1.000 0.000
#> SRR1313069 1 0.000 0.9849 1.000 0.000
#> SRR1313070 1 0.000 0.9849 1.000 0.000
#> SRR1313071 1 0.000 0.9849 1.000 0.000
#> SRR1313072 1 0.000 0.9849 1.000 0.000
#> SRR1313073 1 0.000 0.9849 1.000 0.000
#> SRR1313074 1 0.000 0.9849 1.000 0.000
#> SRR1313075 1 0.000 0.9849 1.000 0.000
#> SRR1313076 1 0.000 0.9849 1.000 0.000
#> SRR1313077 1 0.000 0.9849 1.000 0.000
#> SRR1313078 1 0.000 0.9849 1.000 0.000
#> SRR1313079 1 0.000 0.9849 1.000 0.000
#> SRR1313080 1 0.000 0.9849 1.000 0.000
#> SRR1313081 1 0.000 0.9849 1.000 0.000
#> SRR1313082 1 0.000 0.9849 1.000 0.000
#> SRR1313083 1 0.000 0.9849 1.000 0.000
#> SRR1313084 1 0.000 0.9849 1.000 0.000
#> SRR1313085 1 0.000 0.9849 1.000 0.000
#> SRR1313086 1 0.000 0.9849 1.000 0.000
#> SRR1313087 1 0.000 0.9849 1.000 0.000
#> SRR1313088 1 0.000 0.9849 1.000 0.000
#> SRR1313089 1 0.000 0.9849 1.000 0.000
#> SRR1313092 1 0.000 0.9849 1.000 0.000
#> SRR1313090 1 0.000 0.9849 1.000 0.000
#> SRR1313091 2 0.000 0.9910 0.000 1.000
#> SRR1313093 1 0.000 0.9849 1.000 0.000
#> SRR1313095 1 0.000 0.9849 1.000 0.000
#> SRR1313096 1 0.000 0.9849 1.000 0.000
#> SRR1313094 1 0.000 0.9849 1.000 0.000
#> SRR1313097 1 0.311 0.9448 0.944 0.056
#> SRR1313099 1 0.469 0.8999 0.900 0.100
#> SRR1313098 1 0.000 0.9849 1.000 0.000
#> SRR1313101 1 0.311 0.9448 0.944 0.056
#> SRR1313102 1 0.278 0.9511 0.952 0.048
#> SRR1313103 1 0.311 0.9448 0.944 0.056
#> SRR1313100 1 0.000 0.9849 1.000 0.000
#> SRR1313105 1 0.311 0.9448 0.944 0.056
#> SRR1313104 1 0.000 0.9849 1.000 0.000
#> SRR1313107 1 0.311 0.9448 0.944 0.056
#> SRR1313106 1 0.311 0.9448 0.944 0.056
#> SRR1313109 2 1.000 -0.0396 0.496 0.504
#> SRR1313108 1 0.000 0.9849 1.000 0.000
#> SRR1313111 1 0.311 0.9448 0.944 0.056
#> SRR1313110 1 0.000 0.9849 1.000 0.000
#> SRR1313112 1 0.311 0.9448 0.944 0.056
#> SRR1313113 1 0.311 0.9448 0.944 0.056
#> SRR1313115 1 0.000 0.9849 1.000 0.000
#> SRR1313114 1 0.000 0.9849 1.000 0.000
#> SRR1313117 1 0.000 0.9849 1.000 0.000
#> SRR1313118 1 0.000 0.9849 1.000 0.000
#> SRR1313116 1 0.833 0.6656 0.736 0.264
#> SRR1313120 1 0.311 0.9448 0.944 0.056
#> SRR1313119 1 0.000 0.9849 1.000 0.000
#> SRR1313122 1 0.000 0.9849 1.000 0.000
#> SRR1313124 1 0.000 0.9849 1.000 0.000
#> SRR1313121 1 0.000 0.9849 1.000 0.000
#> SRR1313125 1 0.000 0.9849 1.000 0.000
#> SRR1313127 1 0.000 0.9849 1.000 0.000
#> SRR1313123 1 0.000 0.9849 1.000 0.000
#> SRR1313128 1 0.000 0.9849 1.000 0.000
#> SRR1313126 1 0.000 0.9849 1.000 0.000
#> SRR1313130 2 0.000 0.9910 0.000 1.000
#> SRR1313132 1 0.000 0.9849 1.000 0.000
#> SRR1313129 1 0.722 0.7704 0.800 0.200
#> SRR1313133 1 0.000 0.9849 1.000 0.000
#> SRR1313131 1 0.000 0.9849 1.000 0.000
#> SRR1313134 1 0.000 0.9849 1.000 0.000
#> SRR1313135 1 0.000 0.9849 1.000 0.000
#> SRR1313136 1 0.000 0.9849 1.000 0.000
#> SRR1313137 1 0.000 0.9849 1.000 0.000
#> SRR1313138 1 0.295 0.9480 0.948 0.052
#> SRR1313140 1 0.000 0.9849 1.000 0.000
#> SRR1313141 1 0.000 0.9849 1.000 0.000
#> SRR1313139 1 0.000 0.9849 1.000 0.000
#> SRR1313143 1 0.000 0.9849 1.000 0.000
#> SRR1313142 1 0.000 0.9849 1.000 0.000
#> SRR1313144 1 0.000 0.9849 1.000 0.000
#> SRR1313145 1 0.000 0.9849 1.000 0.000
#> SRR1313146 1 0.000 0.9849 1.000 0.000
#> SRR1313147 1 0.000 0.9849 1.000 0.000
#> SRR1313150 1 0.000 0.9849 1.000 0.000
#> SRR1313149 1 0.000 0.9849 1.000 0.000
#> SRR1313152 1 0.000 0.9849 1.000 0.000
#> SRR1313151 1 0.000 0.9849 1.000 0.000
#> SRR1313154 1 0.000 0.9849 1.000 0.000
#> SRR1313153 1 0.000 0.9849 1.000 0.000
#> SRR1313156 1 0.278 0.9511 0.952 0.048
#> SRR1313155 1 0.000 0.9849 1.000 0.000
#> SRR1313157 1 0.000 0.9849 1.000 0.000
#> SRR1313158 1 0.000 0.9849 1.000 0.000
#> SRR1313161 1 0.000 0.9849 1.000 0.000
#> SRR1313159 1 0.722 0.7704 0.800 0.200
#> SRR1313160 1 0.000 0.9849 1.000 0.000
#> SRR1313162 1 0.000 0.9849 1.000 0.000
#> SRR1313163 1 0.242 0.9570 0.960 0.040
#> SRR1313165 1 0.000 0.9849 1.000 0.000
#> SRR1313166 1 0.000 0.9849 1.000 0.000
#> SRR1313164 1 0.000 0.9849 1.000 0.000
#> SRR1313167 1 0.000 0.9849 1.000 0.000
#> SRR1313168 1 0.000 0.9849 1.000 0.000
#> SRR1313170 1 0.311 0.9448 0.944 0.056
#> SRR1313169 1 0.000 0.9849 1.000 0.000
#> SRR1313172 1 0.311 0.9448 0.944 0.056
#> SRR1313171 1 0.000 0.9849 1.000 0.000
#> SRR1313174 2 0.000 0.9910 0.000 1.000
#> SRR1313173 1 0.000 0.9849 1.000 0.000
#> SRR1313176 2 0.000 0.9910 0.000 1.000
#> SRR1313175 2 0.000 0.9910 0.000 1.000
#> SRR1313178 2 0.000 0.9910 0.000 1.000
#> SRR1313177 2 0.000 0.9910 0.000 1.000
#> SRR1313179 2 0.000 0.9910 0.000 1.000
#> SRR1313180 2 0.000 0.9910 0.000 1.000
#> SRR1313181 2 0.000 0.9910 0.000 1.000
#> SRR1313183 2 0.000 0.9910 0.000 1.000
#> SRR1313182 2 0.000 0.9910 0.000 1.000
#> SRR1313184 2 0.000 0.9910 0.000 1.000
#> SRR1313185 2 0.000 0.9910 0.000 1.000
#> SRR1313188 2 0.000 0.9910 0.000 1.000
#> SRR1313187 2 0.000 0.9910 0.000 1.000
#> SRR1313186 2 0.000 0.9910 0.000 1.000
#> SRR1313189 2 0.000 0.9910 0.000 1.000
#> SRR1313190 2 0.000 0.9910 0.000 1.000
#> SRR1313191 2 0.000 0.9910 0.000 1.000
#> SRR1313192 2 0.000 0.9910 0.000 1.000
#> SRR1313193 2 0.000 0.9910 0.000 1.000
#> SRR1313194 2 0.000 0.9910 0.000 1.000
#> SRR1313195 2 0.000 0.9910 0.000 1.000
#> SRR1313196 2 0.000 0.9910 0.000 1.000
#> SRR1313197 2 0.000 0.9910 0.000 1.000
#> SRR1313198 2 0.000 0.9910 0.000 1.000
#> SRR1313199 2 0.000 0.9910 0.000 1.000
#> SRR1313200 2 0.000 0.9910 0.000 1.000
#> SRR1313201 2 0.000 0.9910 0.000 1.000
#> SRR1313202 2 0.000 0.9910 0.000 1.000
#> SRR1313203 1 0.000 0.9849 1.000 0.000
#> SRR1313204 2 0.000 0.9910 0.000 1.000
#> SRR1313205 2 0.000 0.9910 0.000 1.000
#> SRR1313207 2 0.000 0.9910 0.000 1.000
#> SRR1313208 2 0.000 0.9910 0.000 1.000
#> SRR1313206 2 0.000 0.9910 0.000 1.000
#> SRR1313210 2 0.000 0.9910 0.000 1.000
#> SRR1313209 2 0.000 0.9910 0.000 1.000
#> SRR1313211 2 0.000 0.9910 0.000 1.000
#> SRR1313212 2 0.000 0.9910 0.000 1.000
#> SRR1313214 2 0.000 0.9910 0.000 1.000
#> SRR1313215 2 0.000 0.9910 0.000 1.000
#> SRR1313213 2 0.000 0.9910 0.000 1.000
#> SRR1313216 2 0.000 0.9910 0.000 1.000
#> SRR1313217 2 0.000 0.9910 0.000 1.000
#> SRR1313219 2 0.000 0.9910 0.000 1.000
#> SRR1313220 2 0.000 0.9910 0.000 1.000
#> SRR1313218 2 0.000 0.9910 0.000 1.000
#> SRR1313222 2 0.000 0.9910 0.000 1.000
#> SRR1313221 2 0.000 0.9910 0.000 1.000
#> SRR1313223 2 0.000 0.9910 0.000 1.000
#> SRR1313224 2 0.000 0.9910 0.000 1.000
#> SRR1313225 2 0.000 0.9910 0.000 1.000
#> SRR1313226 2 0.000 0.9910 0.000 1.000
#> SRR1313227 2 0.000 0.9910 0.000 1.000
#> SRR1313228 2 0.000 0.9910 0.000 1.000
#> SRR1313229 2 0.000 0.9910 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.3267 0.8883 0.884 0.000 0.116
#> SRR1313063 1 0.2625 0.9076 0.916 0.000 0.084
#> SRR1313064 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313065 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313066 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313067 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313068 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313069 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313070 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313071 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313072 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313073 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313074 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313075 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313076 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313077 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313078 1 0.3482 0.8801 0.872 0.000 0.128
#> SRR1313079 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313080 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313081 1 0.3412 0.8825 0.876 0.000 0.124
#> SRR1313082 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313083 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313084 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313085 1 0.2066 0.9134 0.940 0.000 0.060
#> SRR1313086 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313087 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313088 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313089 1 0.2165 0.9152 0.936 0.000 0.064
#> SRR1313092 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313091 3 0.5859 0.4337 0.000 0.344 0.656
#> SRR1313093 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313096 3 0.5138 0.6178 0.252 0.000 0.748
#> SRR1313094 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313100 3 0.3879 0.6369 0.152 0.000 0.848
#> SRR1313105 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313106 3 0.1964 0.7313 0.000 0.056 0.944
#> SRR1313109 3 0.4178 0.6251 0.000 0.172 0.828
#> SRR1313108 3 0.5254 0.5993 0.264 0.000 0.736
#> SRR1313111 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313116 3 0.2066 0.7275 0.000 0.060 0.940
#> SRR1313120 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313122 3 0.0747 0.7706 0.016 0.000 0.984
#> SRR1313124 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313128 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313126 3 0.4796 0.6593 0.220 0.000 0.780
#> SRR1313130 3 0.6267 0.0932 0.000 0.452 0.548
#> SRR1313132 3 0.2066 0.7632 0.060 0.000 0.940
#> SRR1313129 3 0.0000 0.7787 0.000 0.000 1.000
#> SRR1313133 3 0.6026 0.5518 0.376 0.000 0.624
#> SRR1313131 1 0.6026 0.4578 0.624 0.000 0.376
#> SRR1313134 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313135 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313136 3 0.6026 0.5518 0.376 0.000 0.624
#> SRR1313137 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313138 3 0.3686 0.7374 0.140 0.000 0.860
#> SRR1313140 1 0.4346 0.7777 0.816 0.000 0.184
#> SRR1313141 1 0.5810 0.4532 0.664 0.000 0.336
#> SRR1313139 3 0.6309 0.2385 0.496 0.000 0.504
#> SRR1313143 1 0.5560 0.5545 0.700 0.000 0.300
#> SRR1313142 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313144 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313145 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313146 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313147 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313150 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313149 1 0.5591 0.5444 0.696 0.000 0.304
#> SRR1313152 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313151 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313154 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313153 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313156 3 0.3686 0.7374 0.140 0.000 0.860
#> SRR1313155 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313157 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313158 3 0.3686 0.7374 0.140 0.000 0.860
#> SRR1313161 3 0.3879 0.7317 0.152 0.000 0.848
#> SRR1313159 3 0.2383 0.7642 0.044 0.016 0.940
#> SRR1313160 3 0.4605 0.6989 0.204 0.000 0.796
#> SRR1313162 3 0.4121 0.7042 0.168 0.000 0.832
#> SRR1313163 3 0.3116 0.7503 0.108 0.000 0.892
#> SRR1313165 3 0.5650 0.6170 0.312 0.000 0.688
#> SRR1313166 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313164 3 0.5733 0.6080 0.324 0.000 0.676
#> SRR1313167 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313168 3 0.6045 0.5463 0.380 0.000 0.620
#> SRR1313170 3 0.0424 0.7730 0.000 0.008 0.992
#> SRR1313169 3 0.6062 0.5402 0.384 0.000 0.616
#> SRR1313172 3 0.0237 0.7763 0.004 0.000 0.996
#> SRR1313171 3 0.6026 0.5518 0.376 0.000 0.624
#> SRR1313174 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313173 1 0.5968 0.4932 0.636 0.000 0.364
#> SRR1313176 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313175 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313178 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313177 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313179 2 0.2066 0.9708 0.060 0.940 0.000
#> SRR1313180 2 0.1031 0.9556 0.000 0.976 0.024
#> SRR1313181 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313183 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313182 2 0.0237 0.9719 0.004 0.996 0.000
#> SRR1313184 2 0.1964 0.9714 0.056 0.944 0.000
#> SRR1313185 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313189 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313190 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313191 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313192 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313193 2 0.1643 0.9718 0.044 0.956 0.000
#> SRR1313194 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313199 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313200 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313201 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313202 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313203 1 0.2448 0.9090 0.924 0.000 0.076
#> SRR1313204 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313205 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313207 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313208 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313206 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313210 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313212 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313214 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313213 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313216 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313220 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313218 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313222 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313221 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313223 2 0.2165 0.9697 0.064 0.936 0.000
#> SRR1313224 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9718 0.000 1.000 0.000
#> SRR1313226 2 0.4235 0.7869 0.000 0.824 0.176
#> SRR1313227 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313228 2 0.2066 0.9710 0.060 0.940 0.000
#> SRR1313229 2 0.2066 0.9710 0.060 0.940 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313063 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313064 4 0.0188 0.920 0.004 0.000 0.000 0.996
#> SRR1313065 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313066 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313067 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313068 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313069 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313070 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313071 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313072 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313073 4 0.0592 0.917 0.016 0.000 0.000 0.984
#> SRR1313074 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313075 4 0.0592 0.919 0.016 0.000 0.000 0.984
#> SRR1313076 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313077 4 0.1661 0.905 0.052 0.000 0.004 0.944
#> SRR1313078 4 0.3636 0.807 0.172 0.000 0.008 0.820
#> SRR1313079 4 0.0188 0.920 0.004 0.000 0.000 0.996
#> SRR1313080 4 0.1398 0.910 0.040 0.000 0.004 0.956
#> SRR1313081 4 0.1661 0.905 0.052 0.000 0.004 0.944
#> SRR1313082 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313083 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313084 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313085 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313086 4 0.0336 0.920 0.008 0.000 0.000 0.992
#> SRR1313087 4 0.0188 0.920 0.004 0.000 0.000 0.996
#> SRR1313088 4 0.0469 0.919 0.012 0.000 0.000 0.988
#> SRR1313089 4 0.0707 0.918 0.020 0.000 0.000 0.980
#> SRR1313092 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.6397 0.452 0.208 0.144 0.648 0.000
#> SRR1313093 3 0.3306 0.707 0.156 0.000 0.840 0.004
#> SRR1313095 3 0.1576 0.809 0.048 0.000 0.948 0.004
#> SRR1313096 3 0.7006 0.320 0.204 0.000 0.580 0.216
#> SRR1313094 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.1716 0.794 0.064 0.000 0.936 0.000
#> SRR1313098 3 0.0188 0.838 0.000 0.000 0.996 0.004
#> SRR1313101 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.2060 0.789 0.016 0.000 0.932 0.052
#> SRR1313105 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.2469 0.751 0.108 0.000 0.892 0.000
#> SRR1313106 3 0.2216 0.752 0.092 0.000 0.908 0.000
#> SRR1313109 3 0.1888 0.795 0.044 0.016 0.940 0.000
#> SRR1313108 3 0.6714 0.394 0.176 0.000 0.616 0.208
#> SRR1313111 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.3257 0.711 0.152 0.000 0.844 0.004
#> SRR1313114 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.3975 0.585 0.240 0.000 0.760 0.000
#> SRR1313120 3 0.2469 0.751 0.108 0.000 0.892 0.000
#> SRR1313119 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.1854 0.803 0.048 0.000 0.940 0.012
#> SRR1313124 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0188 0.838 0.000 0.000 0.996 0.004
#> SRR1313123 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.6373 0.807 0.636 0.000 0.248 0.116
#> SRR1313126 3 0.4624 0.600 0.052 0.000 0.784 0.164
#> SRR1313130 3 0.5143 0.527 0.256 0.036 0.708 0.000
#> SRR1313132 1 0.4950 0.737 0.620 0.000 0.376 0.004
#> SRR1313129 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.6350 0.810 0.636 0.000 0.252 0.112
#> SRR1313131 4 0.7023 0.342 0.312 0.000 0.144 0.544
#> SRR1313134 1 0.6350 0.810 0.636 0.000 0.252 0.112
#> SRR1313135 1 0.6865 0.862 0.524 0.000 0.364 0.112
#> SRR1313136 1 0.6750 0.863 0.540 0.000 0.356 0.104
#> SRR1313137 1 0.6954 0.855 0.500 0.000 0.384 0.116
#> SRR1313138 1 0.5606 0.730 0.500 0.000 0.480 0.020
#> SRR1313140 1 0.6988 0.472 0.500 0.000 0.120 0.380
#> SRR1313141 1 0.6949 0.168 0.480 0.000 0.112 0.408
#> SRR1313139 1 0.7321 0.822 0.500 0.000 0.328 0.172
#> SRR1313143 4 0.6561 0.340 0.344 0.000 0.092 0.564
#> SRR1313142 1 0.6733 0.860 0.564 0.000 0.324 0.112
#> SRR1313144 1 0.6954 0.856 0.500 0.000 0.384 0.116
#> SRR1313145 1 0.6669 0.861 0.564 0.000 0.332 0.104
#> SRR1313146 1 0.6748 0.861 0.560 0.000 0.328 0.112
#> SRR1313147 1 0.6988 0.856 0.500 0.000 0.380 0.120
#> SRR1313150 1 0.6988 0.856 0.500 0.000 0.380 0.120
#> SRR1313149 4 0.6694 0.197 0.392 0.000 0.092 0.516
#> SRR1313152 1 0.6954 0.855 0.500 0.000 0.384 0.116
#> SRR1313151 1 0.6711 0.853 0.576 0.000 0.308 0.116
#> SRR1313154 1 0.6350 0.813 0.636 0.000 0.252 0.112
#> SRR1313153 1 0.6748 0.861 0.560 0.000 0.328 0.112
#> SRR1313156 1 0.5478 0.765 0.540 0.000 0.444 0.016
#> SRR1313155 1 0.6748 0.861 0.560 0.000 0.328 0.112
#> SRR1313157 1 0.6988 0.856 0.500 0.000 0.380 0.120
#> SRR1313158 1 0.5478 0.765 0.540 0.000 0.444 0.016
#> SRR1313161 1 0.5778 0.740 0.500 0.000 0.472 0.028
#> SRR1313159 3 0.5168 -0.701 0.496 0.000 0.500 0.004
#> SRR1313160 1 0.6140 0.775 0.500 0.000 0.452 0.048
#> SRR1313162 1 0.6315 0.823 0.540 0.000 0.396 0.064
#> SRR1313163 1 0.5511 0.724 0.500 0.000 0.484 0.016
#> SRR1313165 1 0.6722 0.835 0.500 0.000 0.408 0.092
#> SRR1313166 1 0.6347 0.823 0.624 0.000 0.276 0.100
#> SRR1313164 1 0.6252 0.822 0.624 0.000 0.288 0.088
#> SRR1313167 1 0.6988 0.856 0.500 0.000 0.380 0.120
#> SRR1313168 1 0.6954 0.856 0.500 0.000 0.384 0.116
#> SRR1313170 3 0.0000 0.841 0.000 0.000 1.000 0.000
#> SRR1313169 1 0.6988 0.856 0.500 0.000 0.380 0.120
#> SRR1313172 3 0.4401 0.468 0.272 0.000 0.724 0.004
#> SRR1313171 1 0.6350 0.810 0.636 0.000 0.252 0.112
#> SRR1313174 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313173 4 0.6945 0.367 0.312 0.000 0.136 0.552
#> SRR1313176 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313178 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0188 0.853 0.004 0.996 0.000 0.000
#> SRR1313180 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313181 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.4164 0.862 0.264 0.736 0.000 0.000
#> SRR1313184 2 0.0188 0.853 0.004 0.996 0.000 0.000
#> SRR1313185 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313188 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313187 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313186 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313189 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313192 2 0.0336 0.853 0.008 0.992 0.000 0.000
#> SRR1313193 2 0.3907 0.861 0.232 0.768 0.000 0.000
#> SRR1313194 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313195 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313196 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313197 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313198 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313199 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313201 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313203 4 0.1637 0.907 0.060 0.000 0.000 0.940
#> SRR1313204 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.1118 0.855 0.036 0.964 0.000 0.000
#> SRR1313207 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0336 0.853 0.008 0.992 0.000 0.000
#> SRR1313206 2 0.0336 0.853 0.008 0.992 0.000 0.000
#> SRR1313210 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313209 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313211 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313212 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313215 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313213 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313217 2 0.4655 0.860 0.312 0.684 0.004 0.000
#> SRR1313219 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313220 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.4454 0.862 0.308 0.692 0.000 0.000
#> SRR1313222 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.4454 0.862 0.308 0.692 0.000 0.000
#> SRR1313225 2 0.4477 0.861 0.312 0.688 0.000 0.000
#> SRR1313226 3 0.7917 -0.334 0.312 0.344 0.344 0.000
#> SRR1313227 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.852 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.852 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313063 4 0.3599 0.8614 0.008 0.000 0.020 0.812 0.160
#> SRR1313064 4 0.1041 0.9144 0.032 0.000 0.000 0.964 0.004
#> SRR1313065 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313066 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313067 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313068 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313069 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313070 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313071 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313072 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313073 4 0.1701 0.9031 0.016 0.000 0.000 0.936 0.048
#> SRR1313074 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313075 4 0.1041 0.9142 0.032 0.000 0.000 0.964 0.004
#> SRR1313076 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313077 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313078 4 0.6244 0.5625 0.080 0.000 0.024 0.500 0.396
#> SRR1313079 4 0.1041 0.9144 0.032 0.000 0.000 0.964 0.004
#> SRR1313080 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313081 4 0.3566 0.8603 0.004 0.000 0.024 0.812 0.160
#> SRR1313082 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313083 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313084 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313085 4 0.2153 0.9044 0.040 0.000 0.000 0.916 0.044
#> SRR1313086 4 0.0880 0.9145 0.032 0.000 0.000 0.968 0.000
#> SRR1313087 4 0.1041 0.9144 0.032 0.000 0.000 0.964 0.004
#> SRR1313088 4 0.1485 0.9120 0.032 0.000 0.000 0.948 0.020
#> SRR1313089 4 0.1168 0.9134 0.032 0.000 0.000 0.960 0.008
#> SRR1313092 3 0.0798 0.9056 0.016 0.000 0.976 0.000 0.008
#> SRR1313090 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313091 3 0.4676 0.6029 0.004 0.028 0.708 0.008 0.252
#> SRR1313093 3 0.5400 0.6077 0.096 0.000 0.632 0.000 0.272
#> SRR1313095 3 0.1908 0.8610 0.000 0.000 0.908 0.000 0.092
#> SRR1313096 5 0.7605 -0.3196 0.108 0.000 0.368 0.116 0.408
#> SRR1313094 3 0.0798 0.9056 0.016 0.000 0.976 0.000 0.008
#> SRR1313097 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313099 3 0.1502 0.8853 0.056 0.000 0.940 0.000 0.004
#> SRR1313098 3 0.2110 0.8777 0.016 0.000 0.912 0.000 0.072
#> SRR1313101 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313102 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313103 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313100 3 0.1331 0.8877 0.000 0.000 0.952 0.008 0.040
#> SRR1313105 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313104 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313107 3 0.2959 0.8386 0.100 0.000 0.864 0.000 0.036
#> SRR1313106 3 0.1990 0.8594 0.008 0.000 0.920 0.004 0.068
#> SRR1313109 3 0.2959 0.8214 0.016 0.000 0.864 0.008 0.112
#> SRR1313108 5 0.7478 -0.3390 0.096 0.000 0.384 0.112 0.408
#> SRR1313111 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313110 3 0.0671 0.9067 0.016 0.000 0.980 0.000 0.004
#> SRR1313112 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313113 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313115 3 0.5400 0.6077 0.096 0.000 0.632 0.000 0.272
#> SRR1313114 3 0.0671 0.9067 0.016 0.000 0.980 0.000 0.004
#> SRR1313117 3 0.0404 0.9073 0.012 0.000 0.988 0.000 0.000
#> SRR1313118 3 0.0671 0.9067 0.016 0.000 0.980 0.000 0.004
#> SRR1313116 3 0.4178 0.5869 0.004 0.000 0.696 0.008 0.292
#> SRR1313120 3 0.2959 0.8386 0.100 0.000 0.864 0.000 0.036
#> SRR1313119 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313122 3 0.1908 0.8610 0.000 0.000 0.908 0.000 0.092
#> SRR1313124 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313121 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313125 3 0.0510 0.9072 0.016 0.000 0.984 0.000 0.000
#> SRR1313127 3 0.1386 0.8971 0.016 0.000 0.952 0.000 0.032
#> SRR1313123 3 0.0771 0.9051 0.020 0.000 0.976 0.000 0.004
#> SRR1313128 1 0.5141 0.6705 0.684 0.000 0.032 0.032 0.252
#> SRR1313126 3 0.3841 0.7513 0.000 0.000 0.780 0.032 0.188
#> SRR1313130 3 0.4613 0.3615 0.004 0.000 0.580 0.008 0.408
#> SRR1313132 1 0.2740 0.8536 0.888 0.000 0.064 0.004 0.044
#> SRR1313129 3 0.0566 0.9060 0.012 0.000 0.984 0.004 0.000
#> SRR1313133 1 0.5116 0.6742 0.688 0.000 0.032 0.032 0.248
#> SRR1313131 5 0.7661 -0.3777 0.180 0.000 0.076 0.320 0.424
#> SRR1313134 1 0.5236 0.6548 0.668 0.000 0.032 0.032 0.268
#> SRR1313135 1 0.2677 0.9251 0.872 0.000 0.112 0.016 0.000
#> SRR1313136 1 0.2574 0.9247 0.876 0.000 0.112 0.012 0.000
#> SRR1313137 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313138 1 0.2818 0.9163 0.860 0.000 0.128 0.004 0.008
#> SRR1313140 1 0.3242 0.8921 0.852 0.000 0.076 0.072 0.000
#> SRR1313141 5 0.7266 -0.3064 0.320 0.000 0.024 0.256 0.400
#> SRR1313139 1 0.3035 0.9228 0.856 0.000 0.112 0.032 0.000
#> SRR1313143 5 0.7220 -0.3985 0.232 0.000 0.024 0.344 0.400
#> SRR1313142 1 0.2464 0.9225 0.888 0.000 0.096 0.016 0.000
#> SRR1313144 1 0.2873 0.9246 0.860 0.000 0.120 0.020 0.000
#> SRR1313145 1 0.2416 0.9226 0.888 0.000 0.100 0.012 0.000
#> SRR1313146 1 0.2464 0.9225 0.888 0.000 0.096 0.016 0.000
#> SRR1313147 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313150 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313149 5 0.7266 -0.3715 0.256 0.000 0.024 0.320 0.400
#> SRR1313152 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313151 1 0.2464 0.9225 0.888 0.000 0.096 0.016 0.000
#> SRR1313154 1 0.2417 0.8577 0.912 0.000 0.032 0.016 0.040
#> SRR1313153 1 0.2464 0.9225 0.888 0.000 0.096 0.016 0.000
#> SRR1313156 1 0.2439 0.9206 0.876 0.000 0.120 0.000 0.004
#> SRR1313155 1 0.2464 0.9225 0.888 0.000 0.096 0.016 0.000
#> SRR1313157 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313158 1 0.2439 0.9220 0.876 0.000 0.120 0.004 0.000
#> SRR1313161 1 0.2753 0.9155 0.856 0.000 0.136 0.008 0.000
#> SRR1313159 1 0.3379 0.8900 0.828 0.000 0.148 0.008 0.016
#> SRR1313160 1 0.2873 0.9210 0.856 0.000 0.128 0.016 0.000
#> SRR1313162 1 0.4934 0.7949 0.720 0.000 0.192 0.008 0.080
#> SRR1313163 1 0.2629 0.9146 0.860 0.000 0.136 0.000 0.004
#> SRR1313165 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313166 1 0.2472 0.8572 0.908 0.000 0.036 0.012 0.044
#> SRR1313164 1 0.2513 0.8566 0.904 0.000 0.040 0.008 0.048
#> SRR1313167 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313168 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313170 3 0.1087 0.8987 0.016 0.000 0.968 0.008 0.008
#> SRR1313169 1 0.2964 0.9242 0.856 0.000 0.120 0.024 0.000
#> SRR1313172 3 0.6919 0.4010 0.200 0.000 0.480 0.020 0.300
#> SRR1313171 1 0.5236 0.6548 0.668 0.000 0.032 0.032 0.268
#> SRR1313174 5 0.4449 0.3797 0.000 0.484 0.004 0.000 0.512
#> SRR1313173 5 0.7624 -0.3821 0.180 0.000 0.072 0.324 0.424
#> SRR1313176 2 0.0000 0.8338 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.4446 0.3900 0.000 0.476 0.004 0.000 0.520
#> SRR1313178 2 0.0609 0.8331 0.020 0.980 0.000 0.000 0.000
#> SRR1313177 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313179 2 0.1673 0.8254 0.032 0.944 0.000 0.008 0.016
#> SRR1313180 5 0.5673 0.3786 0.004 0.432 0.048 0.008 0.508
#> SRR1313181 2 0.0162 0.8339 0.004 0.996 0.000 0.000 0.000
#> SRR1313183 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313182 2 0.4402 0.0492 0.004 0.620 0.000 0.004 0.372
#> SRR1313184 2 0.1569 0.8279 0.032 0.948 0.000 0.008 0.012
#> SRR1313185 5 0.4449 0.3797 0.000 0.484 0.004 0.000 0.512
#> SRR1313188 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313187 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313186 5 0.4449 0.3797 0.000 0.484 0.004 0.000 0.512
#> SRR1313189 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313190 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313191 2 0.4448 -0.3341 0.004 0.516 0.000 0.000 0.480
#> SRR1313192 2 0.0932 0.8222 0.004 0.972 0.000 0.004 0.020
#> SRR1313193 2 0.4389 0.0644 0.004 0.624 0.000 0.004 0.368
#> SRR1313194 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313195 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313196 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313197 5 0.4449 0.3797 0.000 0.484 0.004 0.000 0.512
#> SRR1313198 5 0.4446 0.3900 0.000 0.476 0.004 0.000 0.520
#> SRR1313199 2 0.0000 0.8338 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313201 2 0.0324 0.8323 0.004 0.992 0.000 0.004 0.000
#> SRR1313202 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313203 4 0.4910 0.7403 0.020 0.000 0.012 0.628 0.340
#> SRR1313204 2 0.0324 0.8323 0.004 0.992 0.000 0.004 0.000
#> SRR1313205 2 0.2597 0.6949 0.004 0.872 0.000 0.004 0.120
#> SRR1313207 2 0.0880 0.8306 0.032 0.968 0.000 0.000 0.000
#> SRR1313208 2 0.0932 0.8222 0.004 0.972 0.000 0.004 0.020
#> SRR1313206 2 0.0932 0.8222 0.004 0.972 0.000 0.004 0.020
#> SRR1313210 5 0.4446 0.3900 0.000 0.476 0.004 0.000 0.520
#> SRR1313209 5 0.4449 0.3797 0.000 0.484 0.004 0.000 0.512
#> SRR1313211 2 0.4591 -0.3266 0.004 0.516 0.000 0.004 0.476
#> SRR1313212 2 0.0324 0.8323 0.004 0.992 0.000 0.004 0.000
#> SRR1313214 5 0.4448 0.3851 0.000 0.480 0.004 0.000 0.516
#> SRR1313215 5 0.4446 0.3900 0.000 0.476 0.004 0.000 0.520
#> SRR1313213 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313216 5 0.5140 0.4021 0.004 0.464 0.016 0.008 0.508
#> SRR1313217 5 0.5221 0.4049 0.004 0.460 0.020 0.008 0.508
#> SRR1313219 5 0.4446 0.3900 0.000 0.476 0.004 0.000 0.520
#> SRR1313220 2 0.0324 0.8323 0.004 0.992 0.000 0.004 0.000
#> SRR1313218 2 0.4583 -0.2921 0.004 0.528 0.000 0.004 0.464
#> SRR1313222 2 0.0880 0.8306 0.032 0.968 0.000 0.000 0.000
#> SRR1313221 2 0.0794 0.8316 0.028 0.972 0.000 0.000 0.000
#> SRR1313223 2 0.1041 0.8293 0.032 0.964 0.000 0.004 0.000
#> SRR1313224 2 0.4591 -0.3266 0.004 0.516 0.000 0.004 0.476
#> SRR1313225 5 0.4737 0.3800 0.004 0.476 0.004 0.004 0.512
#> SRR1313226 5 0.5498 -0.0479 0.004 0.036 0.444 0.008 0.508
#> SRR1313227 2 0.0000 0.8338 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.8338 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0162 0.8339 0.004 0.996 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.5775 0.6339 0.016 0.180 0.008 0.604 0.000 0.192
#> SRR1313063 4 0.5546 0.6283 0.004 0.180 0.008 0.608 0.000 0.200
#> SRR1313064 4 0.0748 0.8297 0.016 0.004 0.000 0.976 0.000 0.004
#> SRR1313065 4 0.0603 0.8297 0.016 0.004 0.000 0.980 0.000 0.000
#> SRR1313066 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313067 4 0.5871 0.6043 0.004 0.180 0.020 0.584 0.000 0.212
#> SRR1313068 4 0.5595 0.6211 0.004 0.180 0.008 0.600 0.000 0.208
#> SRR1313069 4 0.0717 0.8297 0.016 0.008 0.000 0.976 0.000 0.000
#> SRR1313070 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313071 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313072 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313073 4 0.4268 0.7330 0.016 0.172 0.008 0.756 0.000 0.048
#> SRR1313074 4 0.0717 0.8297 0.016 0.008 0.000 0.976 0.000 0.000
#> SRR1313075 4 0.1275 0.8255 0.016 0.016 0.000 0.956 0.000 0.012
#> SRR1313076 4 0.5618 0.6169 0.004 0.180 0.008 0.596 0.000 0.212
#> SRR1313077 4 0.5618 0.6169 0.004 0.180 0.008 0.596 0.000 0.212
#> SRR1313078 6 0.6161 0.0698 0.012 0.176 0.008 0.300 0.000 0.504
#> SRR1313079 4 0.0748 0.8297 0.016 0.004 0.000 0.976 0.000 0.004
#> SRR1313080 4 0.5571 0.6242 0.004 0.180 0.008 0.604 0.000 0.204
#> SRR1313081 4 0.5871 0.6043 0.004 0.180 0.020 0.584 0.000 0.212
#> SRR1313082 4 0.0603 0.8297 0.016 0.004 0.000 0.980 0.000 0.000
#> SRR1313083 4 0.0603 0.8297 0.016 0.004 0.000 0.980 0.000 0.000
#> SRR1313084 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313085 4 0.2680 0.8037 0.016 0.068 0.004 0.884 0.000 0.028
#> SRR1313086 4 0.0603 0.8297 0.016 0.004 0.000 0.980 0.000 0.000
#> SRR1313087 4 0.0748 0.8297 0.016 0.004 0.000 0.976 0.000 0.004
#> SRR1313088 4 0.1448 0.8236 0.016 0.024 0.000 0.948 0.000 0.012
#> SRR1313089 4 0.1275 0.8253 0.016 0.012 0.000 0.956 0.000 0.016
#> SRR1313092 3 0.0806 0.9100 0.020 0.008 0.972 0.000 0.000 0.000
#> SRR1313090 3 0.0777 0.9106 0.024 0.004 0.972 0.000 0.000 0.000
#> SRR1313091 3 0.4962 0.5263 0.000 0.020 0.640 0.000 0.280 0.060
#> SRR1313093 6 0.4627 0.2234 0.020 0.012 0.436 0.000 0.000 0.532
#> SRR1313095 3 0.3280 0.7554 0.004 0.032 0.812 0.000 0.000 0.152
#> SRR1313096 6 0.4811 0.6161 0.036 0.024 0.144 0.052 0.000 0.744
#> SRR1313094 3 0.0909 0.9105 0.020 0.012 0.968 0.000 0.000 0.000
#> SRR1313097 3 0.1003 0.9091 0.020 0.016 0.964 0.000 0.000 0.000
#> SRR1313099 3 0.1679 0.8911 0.008 0.028 0.936 0.000 0.000 0.028
#> SRR1313098 3 0.2734 0.8415 0.020 0.020 0.872 0.000 0.000 0.088
#> SRR1313101 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313102 3 0.1138 0.9091 0.024 0.012 0.960 0.000 0.000 0.004
#> SRR1313103 3 0.1237 0.9073 0.020 0.020 0.956 0.000 0.000 0.004
#> SRR1313100 3 0.2263 0.8471 0.004 0.060 0.900 0.000 0.000 0.036
#> SRR1313105 3 0.1148 0.9082 0.020 0.016 0.960 0.000 0.000 0.004
#> SRR1313104 3 0.0692 0.9105 0.020 0.004 0.976 0.000 0.000 0.000
#> SRR1313107 3 0.2036 0.8777 0.008 0.028 0.916 0.000 0.000 0.048
#> SRR1313106 3 0.1296 0.8893 0.000 0.012 0.952 0.000 0.032 0.004
#> SRR1313109 3 0.3188 0.8401 0.020 0.020 0.864 0.000 0.060 0.036
#> SRR1313108 6 0.4703 0.6074 0.024 0.024 0.156 0.052 0.000 0.744
#> SRR1313111 3 0.1148 0.9082 0.020 0.016 0.960 0.000 0.000 0.004
#> SRR1313110 3 0.0777 0.9106 0.024 0.004 0.972 0.000 0.000 0.000
#> SRR1313112 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313113 3 0.1003 0.9091 0.020 0.016 0.964 0.000 0.000 0.000
#> SRR1313115 6 0.4644 0.1619 0.020 0.012 0.456 0.000 0.000 0.512
#> SRR1313114 3 0.0777 0.9106 0.024 0.004 0.972 0.000 0.000 0.000
#> SRR1313117 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313118 3 0.0777 0.9106 0.024 0.004 0.972 0.000 0.000 0.000
#> SRR1313116 3 0.4980 0.5334 0.000 0.016 0.648 0.004 0.272 0.060
#> SRR1313120 3 0.2036 0.8777 0.008 0.028 0.916 0.000 0.000 0.048
#> SRR1313119 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313122 3 0.3317 0.7510 0.004 0.032 0.808 0.000 0.000 0.156
#> SRR1313124 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313121 3 0.0777 0.9106 0.024 0.004 0.972 0.000 0.000 0.000
#> SRR1313125 3 0.0632 0.9111 0.024 0.000 0.976 0.000 0.000 0.000
#> SRR1313127 3 0.2036 0.8822 0.028 0.008 0.916 0.000 0.000 0.048
#> SRR1313123 3 0.0935 0.9067 0.032 0.004 0.964 0.000 0.000 0.000
#> SRR1313128 6 0.4214 0.2706 0.460 0.008 0.004 0.000 0.000 0.528
#> SRR1313126 3 0.5665 0.3339 0.008 0.152 0.576 0.004 0.000 0.260
#> SRR1313130 3 0.5065 0.4914 0.000 0.020 0.616 0.000 0.304 0.060
#> SRR1313132 1 0.2752 0.8179 0.864 0.012 0.020 0.000 0.000 0.104
#> SRR1313129 3 0.1321 0.9076 0.024 0.020 0.952 0.000 0.000 0.004
#> SRR1313133 6 0.4227 0.1745 0.492 0.008 0.004 0.000 0.000 0.496
#> SRR1313131 6 0.4516 0.6065 0.056 0.012 0.044 0.120 0.000 0.768
#> SRR1313134 6 0.4242 0.3549 0.412 0.012 0.004 0.000 0.000 0.572
#> SRR1313135 1 0.0547 0.9440 0.980 0.000 0.020 0.000 0.000 0.000
#> SRR1313136 1 0.0547 0.9440 0.980 0.000 0.020 0.000 0.000 0.000
#> SRR1313137 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313138 1 0.1663 0.9427 0.940 0.024 0.024 0.004 0.000 0.008
#> SRR1313140 1 0.2058 0.9338 0.924 0.028 0.012 0.024 0.000 0.012
#> SRR1313141 6 0.4593 0.6026 0.128 0.004 0.004 0.144 0.000 0.720
#> SRR1313139 1 0.1700 0.9368 0.936 0.028 0.012 0.024 0.000 0.000
#> SRR1313143 6 0.4541 0.5846 0.100 0.004 0.004 0.172 0.000 0.720
#> SRR1313142 1 0.0508 0.9403 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313144 1 0.1262 0.9470 0.956 0.016 0.020 0.008 0.000 0.000
#> SRR1313145 1 0.0508 0.9403 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313146 1 0.0508 0.9403 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313147 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313150 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313149 6 0.4563 0.5919 0.108 0.004 0.004 0.164 0.000 0.720
#> SRR1313152 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313151 1 0.0870 0.9352 0.972 0.004 0.012 0.000 0.000 0.012
#> SRR1313154 1 0.2420 0.8081 0.864 0.004 0.004 0.000 0.000 0.128
#> SRR1313153 1 0.0508 0.9403 0.984 0.004 0.012 0.000 0.000 0.000
#> SRR1313156 1 0.0777 0.9419 0.972 0.004 0.024 0.000 0.000 0.000
#> SRR1313155 1 0.0458 0.9432 0.984 0.000 0.016 0.000 0.000 0.000
#> SRR1313157 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313158 1 0.0777 0.9419 0.972 0.004 0.024 0.000 0.000 0.000
#> SRR1313161 1 0.1620 0.9441 0.940 0.024 0.024 0.012 0.000 0.000
#> SRR1313159 1 0.1837 0.9206 0.932 0.012 0.032 0.000 0.004 0.020
#> SRR1313160 1 0.1620 0.9441 0.940 0.024 0.024 0.012 0.000 0.000
#> SRR1313162 1 0.3879 0.7146 0.788 0.020 0.052 0.000 0.000 0.140
#> SRR1313163 1 0.1341 0.9436 0.948 0.024 0.028 0.000 0.000 0.000
#> SRR1313165 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313166 1 0.2400 0.8155 0.872 0.008 0.004 0.000 0.000 0.116
#> SRR1313164 1 0.2631 0.7999 0.856 0.012 0.004 0.000 0.000 0.128
#> SRR1313167 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313168 1 0.1434 0.9464 0.948 0.024 0.020 0.008 0.000 0.000
#> SRR1313170 3 0.2303 0.8801 0.024 0.020 0.904 0.000 0.000 0.052
#> SRR1313169 1 0.1536 0.9458 0.944 0.024 0.020 0.012 0.000 0.000
#> SRR1313172 6 0.4871 0.5151 0.052 0.024 0.268 0.000 0.000 0.656
#> SRR1313171 6 0.4242 0.3549 0.412 0.012 0.004 0.000 0.000 0.572
#> SRR1313174 5 0.0622 0.8610 0.000 0.008 0.000 0.000 0.980 0.012
#> SRR1313173 6 0.4516 0.6065 0.056 0.012 0.044 0.120 0.000 0.768
#> SRR1313176 2 0.4578 0.9227 0.012 0.640 0.000 0.008 0.320 0.020
#> SRR1313175 5 0.0692 0.8627 0.000 0.000 0.004 0.000 0.976 0.020
#> SRR1313178 2 0.4927 0.9223 0.012 0.624 0.004 0.008 0.320 0.032
#> SRR1313177 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313179 2 0.5161 0.8796 0.000 0.592 0.000 0.004 0.304 0.100
#> SRR1313180 5 0.2457 0.8187 0.000 0.008 0.036 0.004 0.896 0.056
#> SRR1313181 2 0.4788 0.9225 0.012 0.632 0.004 0.008 0.320 0.024
#> SRR1313183 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313182 5 0.3376 0.6238 0.000 0.180 0.000 0.004 0.792 0.024
#> SRR1313184 2 0.5164 0.8833 0.000 0.584 0.000 0.004 0.316 0.096
#> SRR1313185 5 0.0767 0.8598 0.000 0.008 0.000 0.004 0.976 0.012
#> SRR1313188 5 0.1644 0.8521 0.000 0.000 0.012 0.004 0.932 0.052
#> SRR1313187 5 0.1644 0.8521 0.000 0.000 0.012 0.004 0.932 0.052
#> SRR1313186 5 0.0767 0.8598 0.000 0.008 0.000 0.004 0.976 0.012
#> SRR1313189 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313190 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313191 5 0.1982 0.8117 0.000 0.068 0.000 0.004 0.912 0.016
#> SRR1313192 2 0.4553 0.8258 0.000 0.580 0.000 0.004 0.384 0.032
#> SRR1313193 5 0.3492 0.6254 0.000 0.176 0.000 0.004 0.788 0.032
#> SRR1313194 5 0.1644 0.8521 0.000 0.000 0.012 0.004 0.932 0.052
#> SRR1313195 5 0.1964 0.8450 0.000 0.008 0.012 0.004 0.920 0.056
#> SRR1313196 5 0.1964 0.8450 0.000 0.008 0.012 0.004 0.920 0.056
#> SRR1313197 5 0.0622 0.8610 0.000 0.008 0.000 0.000 0.980 0.012
#> SRR1313198 5 0.0000 0.8643 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313199 2 0.3499 0.9173 0.000 0.680 0.000 0.000 0.320 0.000
#> SRR1313200 5 0.1644 0.8521 0.000 0.000 0.012 0.004 0.932 0.052
#> SRR1313201 2 0.4058 0.9087 0.000 0.660 0.000 0.004 0.320 0.016
#> SRR1313202 5 0.1964 0.8450 0.000 0.008 0.012 0.004 0.920 0.056
#> SRR1313203 6 0.4897 0.1325 0.008 0.056 0.000 0.344 0.000 0.592
#> SRR1313204 2 0.3835 0.9126 0.000 0.668 0.000 0.000 0.320 0.012
#> SRR1313205 5 0.4640 -0.4725 0.000 0.436 0.000 0.004 0.528 0.032
#> SRR1313207 2 0.5384 0.9171 0.012 0.592 0.004 0.008 0.320 0.064
#> SRR1313208 2 0.4553 0.8258 0.000 0.580 0.000 0.004 0.384 0.032
#> SRR1313206 2 0.4553 0.8258 0.000 0.580 0.000 0.004 0.384 0.032
#> SRR1313210 5 0.0146 0.8644 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1313209 5 0.0767 0.8608 0.000 0.008 0.004 0.000 0.976 0.012
#> SRR1313211 5 0.2870 0.7656 0.000 0.100 0.004 0.004 0.860 0.032
#> SRR1313212 2 0.4138 0.9065 0.000 0.656 0.000 0.004 0.320 0.020
#> SRR1313214 5 0.0405 0.8634 0.000 0.000 0.004 0.000 0.988 0.008
#> SRR1313215 5 0.0146 0.8644 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1313213 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313216 5 0.2015 0.8481 0.000 0.012 0.016 0.000 0.916 0.056
#> SRR1313217 5 0.1738 0.8520 0.000 0.000 0.016 0.004 0.928 0.052
#> SRR1313219 5 0.0146 0.8644 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1313220 2 0.4138 0.9065 0.000 0.656 0.000 0.004 0.320 0.020
#> SRR1313218 5 0.2964 0.7541 0.000 0.108 0.004 0.004 0.852 0.032
#> SRR1313222 2 0.5384 0.9171 0.012 0.592 0.004 0.008 0.320 0.064
#> SRR1313221 2 0.5114 0.9212 0.012 0.612 0.004 0.008 0.320 0.044
#> SRR1313223 2 0.5571 0.9114 0.012 0.576 0.004 0.008 0.320 0.080
#> SRR1313224 5 0.2870 0.7656 0.000 0.100 0.004 0.004 0.860 0.032
#> SRR1313225 5 0.2008 0.8269 0.000 0.040 0.004 0.004 0.920 0.032
#> SRR1313226 5 0.4967 0.3839 0.000 0.012 0.300 0.004 0.628 0.056
#> SRR1313227 2 0.3499 0.9173 0.000 0.680 0.000 0.000 0.320 0.000
#> SRR1313228 2 0.3499 0.9173 0.000 0.680 0.000 0.000 0.320 0.000
#> SRR1313229 2 0.4788 0.9225 0.012 0.632 0.004 0.008 0.320 0.024
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "skmeans"]
# you can also extract it by
# res = res_list["MAD:skmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 6.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.925 0.927 0.969 0.4909 0.502 0.502
#> 3 3 1.000 0.957 0.982 0.3330 0.796 0.612
#> 4 4 0.959 0.935 0.973 0.1355 0.889 0.690
#> 5 5 0.865 0.823 0.854 0.0689 0.923 0.708
#> 6 6 0.906 0.875 0.926 0.0490 0.945 0.737
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4
There is also optional best \(k\) = 2 3 4 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.988 1.000 0.000
#> SRR1313063 1 0.000 0.988 1.000 0.000
#> SRR1313064 1 0.000 0.988 1.000 0.000
#> SRR1313065 1 0.000 0.988 1.000 0.000
#> SRR1313066 1 0.000 0.988 1.000 0.000
#> SRR1313067 1 0.000 0.988 1.000 0.000
#> SRR1313068 1 0.000 0.988 1.000 0.000
#> SRR1313069 1 0.000 0.988 1.000 0.000
#> SRR1313070 1 0.000 0.988 1.000 0.000
#> SRR1313071 1 0.000 0.988 1.000 0.000
#> SRR1313072 1 0.000 0.988 1.000 0.000
#> SRR1313073 1 0.000 0.988 1.000 0.000
#> SRR1313074 1 0.000 0.988 1.000 0.000
#> SRR1313075 1 0.000 0.988 1.000 0.000
#> SRR1313076 1 0.000 0.988 1.000 0.000
#> SRR1313077 1 0.000 0.988 1.000 0.000
#> SRR1313078 1 0.000 0.988 1.000 0.000
#> SRR1313079 1 0.000 0.988 1.000 0.000
#> SRR1313080 1 0.000 0.988 1.000 0.000
#> SRR1313081 1 0.000 0.988 1.000 0.000
#> SRR1313082 1 0.000 0.988 1.000 0.000
#> SRR1313083 1 0.000 0.988 1.000 0.000
#> SRR1313084 1 0.000 0.988 1.000 0.000
#> SRR1313085 1 0.000 0.988 1.000 0.000
#> SRR1313086 1 0.000 0.988 1.000 0.000
#> SRR1313087 1 0.000 0.988 1.000 0.000
#> SRR1313088 1 0.000 0.988 1.000 0.000
#> SRR1313089 1 0.000 0.988 1.000 0.000
#> SRR1313092 1 0.000 0.988 1.000 0.000
#> SRR1313090 1 0.000 0.988 1.000 0.000
#> SRR1313091 2 0.000 0.941 0.000 1.000
#> SRR1313093 1 0.000 0.988 1.000 0.000
#> SRR1313095 1 0.000 0.988 1.000 0.000
#> SRR1313096 1 0.000 0.988 1.000 0.000
#> SRR1313094 1 0.000 0.988 1.000 0.000
#> SRR1313097 2 0.966 0.426 0.392 0.608
#> SRR1313099 2 0.961 0.444 0.384 0.616
#> SRR1313098 1 0.000 0.988 1.000 0.000
#> SRR1313101 2 0.966 0.426 0.392 0.608
#> SRR1313102 2 0.895 0.580 0.312 0.688
#> SRR1313103 2 0.966 0.426 0.392 0.608
#> SRR1313100 1 0.000 0.988 1.000 0.000
#> SRR1313105 2 0.966 0.426 0.392 0.608
#> SRR1313104 1 0.000 0.988 1.000 0.000
#> SRR1313107 2 0.966 0.426 0.392 0.608
#> SRR1313106 2 0.000 0.941 0.000 1.000
#> SRR1313109 2 0.000 0.941 0.000 1.000
#> SRR1313108 1 0.000 0.988 1.000 0.000
#> SRR1313111 2 0.966 0.426 0.392 0.608
#> SRR1313110 1 0.000 0.988 1.000 0.000
#> SRR1313112 2 0.966 0.426 0.392 0.608
#> SRR1313113 2 0.966 0.426 0.392 0.608
#> SRR1313115 1 0.000 0.988 1.000 0.000
#> SRR1313114 1 0.000 0.988 1.000 0.000
#> SRR1313117 1 0.722 0.729 0.800 0.200
#> SRR1313118 1 0.000 0.988 1.000 0.000
#> SRR1313116 2 0.000 0.941 0.000 1.000
#> SRR1313120 1 0.929 0.425 0.656 0.344
#> SRR1313119 1 0.184 0.959 0.972 0.028
#> SRR1313122 1 0.000 0.988 1.000 0.000
#> SRR1313124 1 0.000 0.988 1.000 0.000
#> SRR1313121 1 0.000 0.988 1.000 0.000
#> SRR1313125 1 0.000 0.988 1.000 0.000
#> SRR1313127 1 0.000 0.988 1.000 0.000
#> SRR1313123 1 0.000 0.988 1.000 0.000
#> SRR1313128 1 0.000 0.988 1.000 0.000
#> SRR1313126 1 0.000 0.988 1.000 0.000
#> SRR1313130 2 0.000 0.941 0.000 1.000
#> SRR1313132 1 0.000 0.988 1.000 0.000
#> SRR1313129 2 0.311 0.894 0.056 0.944
#> SRR1313133 1 0.000 0.988 1.000 0.000
#> SRR1313131 1 0.000 0.988 1.000 0.000
#> SRR1313134 1 0.000 0.988 1.000 0.000
#> SRR1313135 1 0.000 0.988 1.000 0.000
#> SRR1313136 1 0.000 0.988 1.000 0.000
#> SRR1313137 1 0.000 0.988 1.000 0.000
#> SRR1313138 2 0.000 0.941 0.000 1.000
#> SRR1313140 1 0.000 0.988 1.000 0.000
#> SRR1313141 1 0.000 0.988 1.000 0.000
#> SRR1313139 1 0.000 0.988 1.000 0.000
#> SRR1313143 1 0.000 0.988 1.000 0.000
#> SRR1313142 1 0.000 0.988 1.000 0.000
#> SRR1313144 1 0.000 0.988 1.000 0.000
#> SRR1313145 1 0.000 0.988 1.000 0.000
#> SRR1313146 1 0.000 0.988 1.000 0.000
#> SRR1313147 1 0.000 0.988 1.000 0.000
#> SRR1313150 1 0.000 0.988 1.000 0.000
#> SRR1313149 1 0.000 0.988 1.000 0.000
#> SRR1313152 1 0.000 0.988 1.000 0.000
#> SRR1313151 1 0.000 0.988 1.000 0.000
#> SRR1313154 1 0.000 0.988 1.000 0.000
#> SRR1313153 1 0.000 0.988 1.000 0.000
#> SRR1313156 1 0.722 0.729 0.800 0.200
#> SRR1313155 1 0.000 0.988 1.000 0.000
#> SRR1313157 1 0.000 0.988 1.000 0.000
#> SRR1313158 1 0.000 0.988 1.000 0.000
#> SRR1313161 1 0.000 0.988 1.000 0.000
#> SRR1313159 2 0.000 0.941 0.000 1.000
#> SRR1313160 1 0.000 0.988 1.000 0.000
#> SRR1313162 1 0.000 0.988 1.000 0.000
#> SRR1313163 1 0.722 0.729 0.800 0.200
#> SRR1313165 1 0.000 0.988 1.000 0.000
#> SRR1313166 1 0.000 0.988 1.000 0.000
#> SRR1313164 1 0.000 0.988 1.000 0.000
#> SRR1313167 1 0.000 0.988 1.000 0.000
#> SRR1313168 1 0.000 0.988 1.000 0.000
#> SRR1313170 2 0.000 0.941 0.000 1.000
#> SRR1313169 1 0.000 0.988 1.000 0.000
#> SRR1313172 2 0.886 0.594 0.304 0.696
#> SRR1313171 1 0.000 0.988 1.000 0.000
#> SRR1313174 2 0.000 0.941 0.000 1.000
#> SRR1313173 1 0.000 0.988 1.000 0.000
#> SRR1313176 2 0.000 0.941 0.000 1.000
#> SRR1313175 2 0.000 0.941 0.000 1.000
#> SRR1313178 2 0.000 0.941 0.000 1.000
#> SRR1313177 2 0.000 0.941 0.000 1.000
#> SRR1313179 2 0.000 0.941 0.000 1.000
#> SRR1313180 2 0.000 0.941 0.000 1.000
#> SRR1313181 2 0.000 0.941 0.000 1.000
#> SRR1313183 2 0.000 0.941 0.000 1.000
#> SRR1313182 2 0.000 0.941 0.000 1.000
#> SRR1313184 2 0.000 0.941 0.000 1.000
#> SRR1313185 2 0.000 0.941 0.000 1.000
#> SRR1313188 2 0.000 0.941 0.000 1.000
#> SRR1313187 2 0.000 0.941 0.000 1.000
#> SRR1313186 2 0.000 0.941 0.000 1.000
#> SRR1313189 2 0.000 0.941 0.000 1.000
#> SRR1313190 2 0.000 0.941 0.000 1.000
#> SRR1313191 2 0.000 0.941 0.000 1.000
#> SRR1313192 2 0.000 0.941 0.000 1.000
#> SRR1313193 2 0.000 0.941 0.000 1.000
#> SRR1313194 2 0.000 0.941 0.000 1.000
#> SRR1313195 2 0.000 0.941 0.000 1.000
#> SRR1313196 2 0.000 0.941 0.000 1.000
#> SRR1313197 2 0.000 0.941 0.000 1.000
#> SRR1313198 2 0.000 0.941 0.000 1.000
#> SRR1313199 2 0.000 0.941 0.000 1.000
#> SRR1313200 2 0.000 0.941 0.000 1.000
#> SRR1313201 2 0.000 0.941 0.000 1.000
#> SRR1313202 2 0.000 0.941 0.000 1.000
#> SRR1313203 1 0.000 0.988 1.000 0.000
#> SRR1313204 2 0.000 0.941 0.000 1.000
#> SRR1313205 2 0.000 0.941 0.000 1.000
#> SRR1313207 2 0.000 0.941 0.000 1.000
#> SRR1313208 2 0.000 0.941 0.000 1.000
#> SRR1313206 2 0.000 0.941 0.000 1.000
#> SRR1313210 2 0.000 0.941 0.000 1.000
#> SRR1313209 2 0.000 0.941 0.000 1.000
#> SRR1313211 2 0.000 0.941 0.000 1.000
#> SRR1313212 2 0.000 0.941 0.000 1.000
#> SRR1313214 2 0.000 0.941 0.000 1.000
#> SRR1313215 2 0.000 0.941 0.000 1.000
#> SRR1313213 2 0.000 0.941 0.000 1.000
#> SRR1313216 2 0.000 0.941 0.000 1.000
#> SRR1313217 2 0.000 0.941 0.000 1.000
#> SRR1313219 2 0.000 0.941 0.000 1.000
#> SRR1313220 2 0.000 0.941 0.000 1.000
#> SRR1313218 2 0.000 0.941 0.000 1.000
#> SRR1313222 2 0.000 0.941 0.000 1.000
#> SRR1313221 2 0.000 0.941 0.000 1.000
#> SRR1313223 2 0.000 0.941 0.000 1.000
#> SRR1313224 2 0.000 0.941 0.000 1.000
#> SRR1313225 2 0.000 0.941 0.000 1.000
#> SRR1313226 2 0.000 0.941 0.000 1.000
#> SRR1313227 2 0.000 0.941 0.000 1.000
#> SRR1313228 2 0.000 0.941 0.000 1.000
#> SRR1313229 2 0.000 0.941 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313063 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313067 1 0.1289 0.956 0.968 0.000 0.032
#> SRR1313068 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313069 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313076 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313077 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313078 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313079 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313080 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313081 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313082 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313091 2 0.6140 0.329 0.000 0.596 0.404
#> SRR1313093 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313096 1 0.5835 0.493 0.660 0.000 0.340
#> SRR1313094 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313098 3 0.0747 0.976 0.016 0.000 0.984
#> SRR1313101 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313100 3 0.0424 0.983 0.008 0.000 0.992
#> SRR1313105 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313109 3 0.4555 0.742 0.000 0.200 0.800
#> SRR1313108 3 0.1289 0.961 0.032 0.000 0.968
#> SRR1313111 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313116 3 0.2261 0.922 0.000 0.068 0.932
#> SRR1313120 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313128 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313126 3 0.1163 0.965 0.028 0.000 0.972
#> SRR1313130 2 0.6111 0.350 0.000 0.604 0.396
#> SRR1313132 1 0.3941 0.815 0.844 0.000 0.156
#> SRR1313129 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313133 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313131 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313134 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313135 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313136 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313137 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313138 2 0.4452 0.751 0.192 0.808 0.000
#> SRR1313140 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313141 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313139 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313143 1 0.0237 0.981 0.996 0.000 0.004
#> SRR1313142 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313144 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313145 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313146 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313147 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313149 1 0.0237 0.981 0.996 0.000 0.004
#> SRR1313152 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313151 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313154 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313153 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313156 1 0.4589 0.783 0.820 0.172 0.008
#> SRR1313155 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313157 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313158 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313161 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313159 2 0.2550 0.910 0.012 0.932 0.056
#> SRR1313160 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313162 1 0.2625 0.904 0.916 0.000 0.084
#> SRR1313163 1 0.4452 0.756 0.808 0.192 0.000
#> SRR1313165 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313166 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313164 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313167 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313170 3 0.0000 0.990 0.000 0.000 1.000
#> SRR1313169 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313172 2 0.9129 0.200 0.372 0.480 0.148
#> SRR1313171 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313174 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313173 1 0.0424 0.979 0.992 0.000 0.008
#> SRR1313176 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313203 1 0.0000 0.983 1.000 0.000 0.000
#> SRR1313204 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313226 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.972 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.972 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313067 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313068 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313078 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313079 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313082 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.4866 0.310 0.000 0.596 0.404 0.000
#> SRR1313093 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.1302 0.916 0.000 0.000 0.956 0.044
#> SRR1313096 3 0.4817 0.418 0.000 0.000 0.612 0.388
#> SRR1313094 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.2011 0.885 0.000 0.000 0.920 0.080
#> SRR1313101 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.4406 0.574 0.000 0.000 0.700 0.300
#> SRR1313105 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.3610 0.734 0.000 0.200 0.800 0.000
#> SRR1313108 3 0.4746 0.465 0.000 0.000 0.632 0.368
#> SRR1313111 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.0188 0.945 0.000 0.004 0.996 0.000
#> SRR1313120 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.3123 0.806 0.000 0.000 0.844 0.156
#> SRR1313124 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.4585 0.540 0.000 0.000 0.668 0.332
#> SRR1313130 2 0.4855 0.321 0.000 0.600 0.400 0.000
#> SRR1313132 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313131 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313134 1 0.3074 0.815 0.848 0.000 0.000 0.152
#> SRR1313135 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313141 4 0.4790 0.392 0.380 0.000 0.000 0.620
#> SRR1313139 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313143 4 0.3688 0.727 0.208 0.000 0.000 0.792
#> SRR1313142 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313149 4 0.4543 0.523 0.324 0.000 0.000 0.676
#> SRR1313152 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313159 1 0.3610 0.736 0.800 0.200 0.000 0.000
#> SRR1313160 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313162 1 0.3610 0.739 0.800 0.000 0.000 0.200
#> SRR1313163 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313167 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313170 3 0.0000 0.948 0.000 0.000 1.000 0.000
#> SRR1313169 1 0.0000 0.978 1.000 0.000 0.000 0.000
#> SRR1313172 4 0.3791 0.717 0.000 0.200 0.004 0.796
#> SRR1313171 1 0.2814 0.841 0.868 0.000 0.000 0.132
#> SRR1313174 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313173 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313203 4 0.0000 0.964 0.000 0.000 0.000 1.000
#> SRR1313204 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313227 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.985 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.985 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313063 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313064 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313066 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313067 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313068 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313069 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313077 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313078 4 0.4161 0.625 0.000 0.392 0.000 0.608 0.000
#> SRR1313079 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313081 4 0.0162 0.929 0.000 0.004 0.000 0.996 0.000
#> SRR1313082 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313084 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313085 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313087 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313092 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 5 0.4210 0.188 0.000 0.000 0.412 0.000 0.588
#> SRR1313093 3 0.4161 0.594 0.000 0.392 0.608 0.000 0.000
#> SRR1313095 3 0.0798 0.908 0.000 0.016 0.976 0.008 0.000
#> SRR1313096 2 0.6759 -0.378 0.000 0.396 0.328 0.276 0.000
#> SRR1313094 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.0404 0.913 0.000 0.012 0.988 0.000 0.000
#> SRR1313098 3 0.4054 0.761 0.000 0.204 0.760 0.036 0.000
#> SRR1313101 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.3662 0.656 0.000 0.004 0.744 0.252 0.000
#> SRR1313105 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.3452 0.745 0.000 0.244 0.756 0.000 0.000
#> SRR1313106 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313109 3 0.4126 0.400 0.000 0.000 0.620 0.000 0.380
#> SRR1313108 2 0.6671 -0.425 0.000 0.396 0.372 0.232 0.000
#> SRR1313111 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.4161 0.594 0.000 0.392 0.608 0.000 0.000
#> SRR1313114 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 5 0.4235 0.148 0.000 0.000 0.424 0.000 0.576
#> SRR1313120 3 0.3452 0.745 0.000 0.244 0.756 0.000 0.000
#> SRR1313119 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.2727 0.819 0.000 0.016 0.868 0.116 0.000
#> SRR1313124 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.1197 0.895 0.000 0.048 0.952 0.000 0.000
#> SRR1313123 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.4161 0.672 0.608 0.392 0.000 0.000 0.000
#> SRR1313126 3 0.4302 0.678 0.000 0.048 0.744 0.208 0.000
#> SRR1313130 5 0.4138 0.256 0.000 0.000 0.384 0.000 0.616
#> SRR1313132 1 0.4114 0.685 0.624 0.376 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.918 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.4161 0.672 0.608 0.392 0.000 0.000 0.000
#> SRR1313131 4 0.4171 0.622 0.000 0.396 0.000 0.604 0.000
#> SRR1313134 1 0.4310 0.669 0.604 0.392 0.000 0.004 0.000
#> SRR1313135 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313141 4 0.5204 0.561 0.048 0.392 0.000 0.560 0.000
#> SRR1313139 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313143 4 0.4866 0.589 0.028 0.392 0.000 0.580 0.000
#> SRR1313142 1 0.0162 0.901 0.996 0.004 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 4 0.5077 0.573 0.040 0.392 0.000 0.568 0.000
#> SRR1313152 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0162 0.901 0.996 0.004 0.000 0.000 0.000
#> SRR1313154 1 0.4126 0.682 0.620 0.380 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.3231 0.707 0.800 0.196 0.000 0.000 0.004
#> SRR1313160 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.5956 0.544 0.592 0.212 0.000 0.196 0.000
#> SRR1313163 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.4114 0.685 0.624 0.376 0.000 0.000 0.000
#> SRR1313164 1 0.4126 0.682 0.620 0.380 0.000 0.000 0.000
#> SRR1313167 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.3534 0.641 0.000 0.000 0.744 0.000 0.256
#> SRR1313169 1 0.0000 0.903 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 2 0.0162 0.373 0.000 0.996 0.000 0.000 0.004
#> SRR1313171 1 0.4866 0.641 0.580 0.392 0.000 0.028 0.000
#> SRR1313174 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313173 4 0.4171 0.622 0.000 0.396 0.000 0.604 0.000
#> SRR1313176 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313175 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313178 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313177 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313179 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313180 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313181 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313183 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313182 2 0.4291 0.759 0.000 0.536 0.000 0.000 0.464
#> SRR1313184 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313185 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313188 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313187 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313186 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313189 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313190 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313191 5 0.0609 0.860 0.000 0.020 0.000 0.000 0.980
#> SRR1313192 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313193 2 0.4192 0.865 0.000 0.596 0.000 0.000 0.404
#> SRR1313194 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313195 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313196 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313197 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313198 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313199 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313200 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313201 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313202 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313203 4 0.0000 0.930 0.000 0.000 0.000 1.000 0.000
#> SRR1313204 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313205 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313207 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313208 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313206 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313210 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313209 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313211 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313212 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313214 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313215 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313213 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313216 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313217 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313219 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313220 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313218 5 0.4171 -0.411 0.000 0.396 0.000 0.000 0.604
#> SRR1313222 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313221 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313223 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313224 2 0.4192 0.865 0.000 0.596 0.000 0.000 0.404
#> SRR1313225 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313226 5 0.0000 0.891 0.000 0.000 0.000 0.000 1.000
#> SRR1313227 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313228 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
#> SRR1313229 2 0.4171 0.877 0.000 0.604 0.000 0.000 0.396
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.2178 0.884 0.000 0.000 0.000 0.868 0.000 0.132
#> SRR1313063 4 0.2003 0.894 0.000 0.000 0.000 0.884 0.000 0.116
#> SRR1313064 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313066 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 4 0.2178 0.884 0.000 0.000 0.000 0.868 0.000 0.132
#> SRR1313068 4 0.2178 0.884 0.000 0.000 0.000 0.868 0.000 0.132
#> SRR1313069 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313070 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313074 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313075 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.2178 0.884 0.000 0.000 0.000 0.868 0.000 0.132
#> SRR1313077 4 0.2219 0.881 0.000 0.000 0.000 0.864 0.000 0.136
#> SRR1313078 6 0.3198 0.578 0.000 0.000 0.000 0.260 0.000 0.740
#> SRR1313079 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.2178 0.884 0.000 0.000 0.000 0.868 0.000 0.132
#> SRR1313081 4 0.2219 0.881 0.000 0.000 0.000 0.864 0.000 0.136
#> SRR1313082 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313083 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313084 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313087 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313089 4 0.0000 0.957 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 3 0.0632 0.878 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313090 3 0.0458 0.880 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313091 5 0.4493 0.332 0.000 0.000 0.344 0.000 0.612 0.044
#> SRR1313093 6 0.2562 0.629 0.000 0.000 0.172 0.000 0.000 0.828
#> SRR1313095 3 0.3050 0.729 0.000 0.000 0.764 0.000 0.000 0.236
#> SRR1313096 6 0.1418 0.766 0.000 0.000 0.024 0.032 0.000 0.944
#> SRR1313094 3 0.1320 0.871 0.000 0.000 0.948 0.000 0.036 0.016
#> SRR1313097 3 0.1408 0.869 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1313099 3 0.2457 0.837 0.000 0.000 0.880 0.000 0.036 0.084
#> SRR1313098 3 0.3737 0.491 0.000 0.000 0.608 0.000 0.000 0.392
#> SRR1313101 3 0.0000 0.880 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0458 0.879 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313103 3 0.1649 0.866 0.000 0.000 0.932 0.000 0.036 0.032
#> SRR1313100 3 0.5039 0.568 0.000 0.000 0.640 0.184 0.000 0.176
#> SRR1313105 3 0.1649 0.866 0.000 0.000 0.932 0.000 0.036 0.032
#> SRR1313104 3 0.0458 0.880 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313107 3 0.4219 0.541 0.000 0.000 0.660 0.000 0.036 0.304
#> SRR1313106 3 0.1003 0.874 0.000 0.000 0.964 0.000 0.020 0.016
#> SRR1313109 3 0.4493 0.480 0.000 0.000 0.612 0.000 0.344 0.044
#> SRR1313108 6 0.1418 0.766 0.000 0.000 0.024 0.032 0.000 0.944
#> SRR1313111 3 0.1649 0.866 0.000 0.000 0.932 0.000 0.036 0.032
#> SRR1313110 3 0.0547 0.879 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1313112 3 0.0000 0.880 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.1649 0.866 0.000 0.000 0.932 0.000 0.036 0.032
#> SRR1313115 6 0.2730 0.598 0.000 0.000 0.192 0.000 0.000 0.808
#> SRR1313114 3 0.0632 0.878 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313117 3 0.0000 0.880 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.0632 0.878 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313116 5 0.4165 0.472 0.000 0.000 0.292 0.000 0.672 0.036
#> SRR1313120 3 0.4219 0.541 0.000 0.000 0.660 0.000 0.036 0.304
#> SRR1313119 3 0.0146 0.880 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313122 3 0.3645 0.708 0.000 0.000 0.740 0.024 0.000 0.236
#> SRR1313124 3 0.0458 0.880 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313121 3 0.0458 0.880 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1313125 3 0.0146 0.880 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313127 3 0.3151 0.711 0.000 0.000 0.748 0.000 0.000 0.252
#> SRR1313123 3 0.0632 0.878 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1313128 6 0.2996 0.749 0.228 0.000 0.000 0.000 0.000 0.772
#> SRR1313126 3 0.3950 0.653 0.000 0.000 0.696 0.028 0.000 0.276
#> SRR1313130 5 0.3500 0.660 0.000 0.000 0.204 0.000 0.768 0.028
#> SRR1313132 6 0.3309 0.701 0.280 0.000 0.000 0.000 0.000 0.720
#> SRR1313129 3 0.1649 0.866 0.000 0.000 0.932 0.000 0.036 0.032
#> SRR1313133 6 0.3023 0.746 0.232 0.000 0.000 0.000 0.000 0.768
#> SRR1313131 6 0.1444 0.768 0.000 0.000 0.000 0.072 0.000 0.928
#> SRR1313134 6 0.3103 0.761 0.208 0.000 0.000 0.008 0.000 0.784
#> SRR1313135 1 0.0146 0.973 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1313136 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.0891 0.955 0.968 0.000 0.000 0.008 0.000 0.024
#> SRR1313141 6 0.3136 0.746 0.016 0.000 0.000 0.188 0.000 0.796
#> SRR1313139 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313143 6 0.3012 0.738 0.008 0.000 0.000 0.196 0.000 0.796
#> SRR1313142 1 0.1765 0.882 0.904 0.000 0.000 0.000 0.000 0.096
#> SRR1313144 1 0.0632 0.960 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313145 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0632 0.960 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313147 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313149 6 0.3136 0.746 0.016 0.000 0.000 0.188 0.000 0.796
#> SRR1313152 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.2003 0.855 0.884 0.000 0.000 0.000 0.000 0.116
#> SRR1313154 6 0.3309 0.701 0.280 0.000 0.000 0.000 0.000 0.720
#> SRR1313153 1 0.0632 0.960 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1313156 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.2902 0.691 0.800 0.196 0.000 0.000 0.004 0.000
#> SRR1313160 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313162 6 0.3651 0.650 0.224 0.000 0.016 0.008 0.000 0.752
#> SRR1313163 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 6 0.3515 0.641 0.324 0.000 0.000 0.000 0.000 0.676
#> SRR1313164 6 0.3288 0.706 0.276 0.000 0.000 0.000 0.000 0.724
#> SRR1313167 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.3938 0.692 0.000 0.000 0.728 0.000 0.228 0.044
#> SRR1313169 1 0.0000 0.975 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313172 6 0.3050 0.640 0.000 0.236 0.000 0.000 0.000 0.764
#> SRR1313171 6 0.3202 0.773 0.176 0.000 0.000 0.024 0.000 0.800
#> SRR1313174 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313173 6 0.1444 0.768 0.000 0.000 0.000 0.072 0.000 0.928
#> SRR1313176 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313178 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313180 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313181 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3592 0.483 0.000 0.656 0.000 0.000 0.344 0.000
#> SRR1313184 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313185 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313188 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313187 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313186 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313189 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.1444 0.916 0.000 0.072 0.000 0.000 0.928 0.000
#> SRR1313192 2 0.0363 0.959 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313193 2 0.0937 0.935 0.000 0.960 0.000 0.000 0.040 0.000
#> SRR1313194 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313195 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313196 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313197 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313198 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313199 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313201 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313203 4 0.0458 0.947 0.000 0.000 0.000 0.984 0.000 0.016
#> SRR1313204 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0363 0.959 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313207 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0363 0.959 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313206 2 0.0363 0.959 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313210 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313209 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313211 5 0.1007 0.944 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313212 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313215 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313213 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.0790 0.948 0.000 0.032 0.000 0.000 0.968 0.000
#> SRR1313217 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313219 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313220 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.3765 0.332 0.000 0.596 0.000 0.000 0.404 0.000
#> SRR1313222 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0865 0.939 0.000 0.964 0.000 0.000 0.036 0.000
#> SRR1313225 5 0.0865 0.950 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313226 5 0.1225 0.949 0.000 0.036 0.000 0.000 0.952 0.012
#> SRR1313227 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.966 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "pam"]
# you can also extract it by
# res = res_list["MAD:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.962 0.962 0.983 0.4639 0.537 0.537
#> 3 3 0.902 0.897 0.955 0.4403 0.769 0.580
#> 4 4 0.925 0.895 0.957 0.1039 0.853 0.601
#> 5 5 0.840 0.793 0.852 0.0664 0.910 0.674
#> 6 6 0.879 0.814 0.893 0.0448 0.948 0.758
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.985 1.000 0.000
#> SRR1313063 1 0.0000 0.985 1.000 0.000
#> SRR1313064 1 0.0000 0.985 1.000 0.000
#> SRR1313065 1 0.0000 0.985 1.000 0.000
#> SRR1313066 1 0.6887 0.779 0.816 0.184
#> SRR1313067 1 0.0000 0.985 1.000 0.000
#> SRR1313068 1 0.0000 0.985 1.000 0.000
#> SRR1313069 1 0.0000 0.985 1.000 0.000
#> SRR1313070 1 0.7056 0.767 0.808 0.192
#> SRR1313071 1 0.0938 0.975 0.988 0.012
#> SRR1313072 1 0.6887 0.779 0.816 0.184
#> SRR1313073 1 0.0000 0.985 1.000 0.000
#> SRR1313074 1 0.0000 0.985 1.000 0.000
#> SRR1313075 1 0.0000 0.985 1.000 0.000
#> SRR1313076 1 0.0000 0.985 1.000 0.000
#> SRR1313077 1 0.0000 0.985 1.000 0.000
#> SRR1313078 1 0.0000 0.985 1.000 0.000
#> SRR1313079 1 0.0000 0.985 1.000 0.000
#> SRR1313080 1 0.0000 0.985 1.000 0.000
#> SRR1313081 1 0.0000 0.985 1.000 0.000
#> SRR1313082 1 0.0000 0.985 1.000 0.000
#> SRR1313083 1 0.0000 0.985 1.000 0.000
#> SRR1313084 1 0.7139 0.761 0.804 0.196
#> SRR1313085 1 0.9393 0.450 0.644 0.356
#> SRR1313086 1 0.0000 0.985 1.000 0.000
#> SRR1313087 1 0.0000 0.985 1.000 0.000
#> SRR1313088 1 0.0000 0.985 1.000 0.000
#> SRR1313089 1 0.4815 0.881 0.896 0.104
#> SRR1313092 1 0.0000 0.985 1.000 0.000
#> SRR1313090 1 0.0000 0.985 1.000 0.000
#> SRR1313091 2 0.0000 0.979 0.000 1.000
#> SRR1313093 1 0.0000 0.985 1.000 0.000
#> SRR1313095 1 0.0000 0.985 1.000 0.000
#> SRR1313096 1 0.0000 0.985 1.000 0.000
#> SRR1313094 1 0.0000 0.985 1.000 0.000
#> SRR1313097 1 0.0000 0.985 1.000 0.000
#> SRR1313099 1 0.0000 0.985 1.000 0.000
#> SRR1313098 1 0.0000 0.985 1.000 0.000
#> SRR1313101 1 0.0000 0.985 1.000 0.000
#> SRR1313102 1 0.0000 0.985 1.000 0.000
#> SRR1313103 1 0.0000 0.985 1.000 0.000
#> SRR1313100 1 0.0000 0.985 1.000 0.000
#> SRR1313105 1 0.0000 0.985 1.000 0.000
#> SRR1313104 1 0.0000 0.985 1.000 0.000
#> SRR1313107 1 0.0000 0.985 1.000 0.000
#> SRR1313106 1 0.1414 0.967 0.980 0.020
#> SRR1313109 1 0.2603 0.945 0.956 0.044
#> SRR1313108 1 0.0000 0.985 1.000 0.000
#> SRR1313111 1 0.0000 0.985 1.000 0.000
#> SRR1313110 1 0.0000 0.985 1.000 0.000
#> SRR1313112 1 0.0000 0.985 1.000 0.000
#> SRR1313113 1 0.0000 0.985 1.000 0.000
#> SRR1313115 1 0.0000 0.985 1.000 0.000
#> SRR1313114 1 0.0000 0.985 1.000 0.000
#> SRR1313117 1 0.0000 0.985 1.000 0.000
#> SRR1313118 1 0.0000 0.985 1.000 0.000
#> SRR1313116 1 0.1843 0.960 0.972 0.028
#> SRR1313120 1 0.0000 0.985 1.000 0.000
#> SRR1313119 1 0.0000 0.985 1.000 0.000
#> SRR1313122 1 0.0000 0.985 1.000 0.000
#> SRR1313124 1 0.0000 0.985 1.000 0.000
#> SRR1313121 1 0.0000 0.985 1.000 0.000
#> SRR1313125 1 0.0000 0.985 1.000 0.000
#> SRR1313127 1 0.0000 0.985 1.000 0.000
#> SRR1313123 1 0.0000 0.985 1.000 0.000
#> SRR1313128 1 0.0000 0.985 1.000 0.000
#> SRR1313126 1 0.0000 0.985 1.000 0.000
#> SRR1313130 2 0.0000 0.979 0.000 1.000
#> SRR1313132 1 0.0000 0.985 1.000 0.000
#> SRR1313129 1 0.0376 0.982 0.996 0.004
#> SRR1313133 1 0.0000 0.985 1.000 0.000
#> SRR1313131 1 0.0000 0.985 1.000 0.000
#> SRR1313134 1 0.0000 0.985 1.000 0.000
#> SRR1313135 1 0.0000 0.985 1.000 0.000
#> SRR1313136 1 0.0000 0.985 1.000 0.000
#> SRR1313137 1 0.0000 0.985 1.000 0.000
#> SRR1313138 2 0.7219 0.752 0.200 0.800
#> SRR1313140 1 0.0000 0.985 1.000 0.000
#> SRR1313141 1 0.0000 0.985 1.000 0.000
#> SRR1313139 1 0.0000 0.985 1.000 0.000
#> SRR1313143 1 0.0000 0.985 1.000 0.000
#> SRR1313142 1 0.0000 0.985 1.000 0.000
#> SRR1313144 1 0.0000 0.985 1.000 0.000
#> SRR1313145 1 0.0000 0.985 1.000 0.000
#> SRR1313146 1 0.0000 0.985 1.000 0.000
#> SRR1313147 1 0.0000 0.985 1.000 0.000
#> SRR1313150 1 0.3879 0.912 0.924 0.076
#> SRR1313149 1 0.0000 0.985 1.000 0.000
#> SRR1313152 1 0.0000 0.985 1.000 0.000
#> SRR1313151 1 0.0000 0.985 1.000 0.000
#> SRR1313154 1 0.0000 0.985 1.000 0.000
#> SRR1313153 1 0.0000 0.985 1.000 0.000
#> SRR1313156 1 0.0000 0.985 1.000 0.000
#> SRR1313155 1 0.0000 0.985 1.000 0.000
#> SRR1313157 1 0.0000 0.985 1.000 0.000
#> SRR1313158 1 0.0000 0.985 1.000 0.000
#> SRR1313161 1 0.0000 0.985 1.000 0.000
#> SRR1313159 2 0.7674 0.716 0.224 0.776
#> SRR1313160 1 0.0000 0.985 1.000 0.000
#> SRR1313162 1 0.0000 0.985 1.000 0.000
#> SRR1313163 1 0.0000 0.985 1.000 0.000
#> SRR1313165 1 0.0000 0.985 1.000 0.000
#> SRR1313166 1 0.0000 0.985 1.000 0.000
#> SRR1313164 1 0.0000 0.985 1.000 0.000
#> SRR1313167 1 0.0000 0.985 1.000 0.000
#> SRR1313168 1 0.0000 0.985 1.000 0.000
#> SRR1313170 1 0.0000 0.985 1.000 0.000
#> SRR1313169 1 0.0000 0.985 1.000 0.000
#> SRR1313172 2 0.9833 0.262 0.424 0.576
#> SRR1313171 1 0.0000 0.985 1.000 0.000
#> SRR1313174 2 0.0000 0.979 0.000 1.000
#> SRR1313173 1 0.0000 0.985 1.000 0.000
#> SRR1313176 2 0.0000 0.979 0.000 1.000
#> SRR1313175 2 0.0000 0.979 0.000 1.000
#> SRR1313178 2 0.0000 0.979 0.000 1.000
#> SRR1313177 2 0.0000 0.979 0.000 1.000
#> SRR1313179 2 0.7139 0.758 0.196 0.804
#> SRR1313180 2 0.0000 0.979 0.000 1.000
#> SRR1313181 2 0.0000 0.979 0.000 1.000
#> SRR1313183 2 0.0000 0.979 0.000 1.000
#> SRR1313182 2 0.0000 0.979 0.000 1.000
#> SRR1313184 2 0.0000 0.979 0.000 1.000
#> SRR1313185 2 0.0000 0.979 0.000 1.000
#> SRR1313188 2 0.0000 0.979 0.000 1.000
#> SRR1313187 2 0.0000 0.979 0.000 1.000
#> SRR1313186 2 0.0000 0.979 0.000 1.000
#> SRR1313189 2 0.0000 0.979 0.000 1.000
#> SRR1313190 2 0.0000 0.979 0.000 1.000
#> SRR1313191 2 0.0000 0.979 0.000 1.000
#> SRR1313192 2 0.0000 0.979 0.000 1.000
#> SRR1313193 2 0.0000 0.979 0.000 1.000
#> SRR1313194 2 0.0000 0.979 0.000 1.000
#> SRR1313195 2 0.0000 0.979 0.000 1.000
#> SRR1313196 2 0.0000 0.979 0.000 1.000
#> SRR1313197 2 0.0000 0.979 0.000 1.000
#> SRR1313198 2 0.0000 0.979 0.000 1.000
#> SRR1313199 2 0.0000 0.979 0.000 1.000
#> SRR1313200 2 0.0000 0.979 0.000 1.000
#> SRR1313201 2 0.0000 0.979 0.000 1.000
#> SRR1313202 2 0.0000 0.979 0.000 1.000
#> SRR1313203 1 0.6148 0.822 0.848 0.152
#> SRR1313204 2 0.0000 0.979 0.000 1.000
#> SRR1313205 2 0.0000 0.979 0.000 1.000
#> SRR1313207 2 0.0000 0.979 0.000 1.000
#> SRR1313208 2 0.0000 0.979 0.000 1.000
#> SRR1313206 2 0.0000 0.979 0.000 1.000
#> SRR1313210 2 0.0000 0.979 0.000 1.000
#> SRR1313209 2 0.0000 0.979 0.000 1.000
#> SRR1313211 2 0.0000 0.979 0.000 1.000
#> SRR1313212 2 0.0000 0.979 0.000 1.000
#> SRR1313214 2 0.0000 0.979 0.000 1.000
#> SRR1313215 2 0.0000 0.979 0.000 1.000
#> SRR1313213 2 0.0000 0.979 0.000 1.000
#> SRR1313216 2 0.0000 0.979 0.000 1.000
#> SRR1313217 2 0.0000 0.979 0.000 1.000
#> SRR1313219 2 0.0000 0.979 0.000 1.000
#> SRR1313220 2 0.0000 0.979 0.000 1.000
#> SRR1313218 2 0.0000 0.979 0.000 1.000
#> SRR1313222 2 0.0000 0.979 0.000 1.000
#> SRR1313221 2 0.0000 0.979 0.000 1.000
#> SRR1313223 2 0.0000 0.979 0.000 1.000
#> SRR1313224 2 0.0000 0.979 0.000 1.000
#> SRR1313225 2 0.0000 0.979 0.000 1.000
#> SRR1313226 2 0.6343 0.807 0.160 0.840
#> SRR1313227 2 0.0000 0.979 0.000 1.000
#> SRR1313228 2 0.0000 0.979 0.000 1.000
#> SRR1313229 2 0.0000 0.979 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.3116 0.8711 0.108 0.000 0.892
#> SRR1313063 3 0.3816 0.8327 0.148 0.000 0.852
#> SRR1313064 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313065 1 0.0237 0.9470 0.996 0.000 0.004
#> SRR1313066 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313067 3 0.1964 0.9102 0.056 0.000 0.944
#> SRR1313068 3 0.1860 0.9125 0.052 0.000 0.948
#> SRR1313069 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313073 1 0.5905 0.4275 0.648 0.000 0.352
#> SRR1313074 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313076 3 0.2711 0.8878 0.088 0.000 0.912
#> SRR1313077 3 0.3752 0.8370 0.144 0.000 0.856
#> SRR1313078 3 0.3879 0.8282 0.152 0.000 0.848
#> SRR1313079 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313080 3 0.1529 0.9188 0.040 0.000 0.960
#> SRR1313081 3 0.2537 0.8938 0.080 0.000 0.920
#> SRR1313082 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313087 1 0.1289 0.9251 0.968 0.000 0.032
#> SRR1313088 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.9460 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313091 2 0.6062 0.3821 0.000 0.616 0.384
#> SRR1313093 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313096 3 0.3752 0.8296 0.144 0.000 0.856
#> SRR1313094 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313098 3 0.1964 0.9058 0.056 0.000 0.944
#> SRR1313101 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313100 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313105 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313106 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313109 3 0.1878 0.9011 0.004 0.044 0.952
#> SRR1313108 3 0.1031 0.9254 0.024 0.000 0.976
#> SRR1313111 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313118 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313116 3 0.0237 0.9330 0.004 0.000 0.996
#> SRR1313120 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313122 3 0.0237 0.9324 0.004 0.000 0.996
#> SRR1313124 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313128 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313126 3 0.0747 0.9286 0.016 0.000 0.984
#> SRR1313130 2 0.6225 0.2698 0.000 0.568 0.432
#> SRR1313132 1 0.3412 0.8410 0.876 0.000 0.124
#> SRR1313129 3 0.0000 0.9347 0.000 0.000 1.000
#> SRR1313133 1 0.5968 0.4166 0.636 0.000 0.364
#> SRR1313131 3 0.3816 0.8292 0.148 0.000 0.852
#> SRR1313134 1 0.5363 0.6081 0.724 0.000 0.276
#> SRR1313135 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313136 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313137 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313138 1 0.1031 0.9379 0.976 0.000 0.024
#> SRR1313140 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313141 1 0.6244 0.1889 0.560 0.000 0.440
#> SRR1313139 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313143 1 0.6008 0.3885 0.628 0.000 0.372
#> SRR1313142 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313144 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313145 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313146 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313147 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313150 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313149 1 0.4062 0.7866 0.836 0.000 0.164
#> SRR1313152 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313151 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313154 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313153 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313156 1 0.0892 0.9408 0.980 0.000 0.020
#> SRR1313155 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313157 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313158 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313161 1 0.1289 0.9317 0.968 0.000 0.032
#> SRR1313159 1 0.1337 0.9356 0.972 0.012 0.016
#> SRR1313160 1 0.0892 0.9408 0.980 0.000 0.020
#> SRR1313162 3 0.6140 0.3559 0.404 0.000 0.596
#> SRR1313163 1 0.1289 0.9317 0.968 0.000 0.032
#> SRR1313165 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313166 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313164 1 0.5098 0.6557 0.752 0.000 0.248
#> SRR1313167 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313168 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313170 3 0.0237 0.9330 0.004 0.000 0.996
#> SRR1313169 1 0.0424 0.9479 0.992 0.000 0.008
#> SRR1313172 3 0.8967 0.1745 0.380 0.132 0.488
#> SRR1313171 3 0.6308 0.0512 0.492 0.000 0.508
#> SRR1313174 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313173 3 0.4178 0.8007 0.172 0.000 0.828
#> SRR1313176 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313179 2 0.0661 0.9638 0.004 0.988 0.008
#> SRR1313180 2 0.2165 0.9163 0.000 0.936 0.064
#> SRR1313181 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313203 3 0.6225 0.2638 0.432 0.000 0.568
#> SRR1313204 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313226 2 0.6489 0.1917 0.004 0.540 0.456
#> SRR1313227 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9753 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9753 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0336 0.8985 0.000 0.000 0.008 0.992
#> SRR1313063 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.2760 0.7973 0.128 0.000 0.000 0.872
#> SRR1313066 4 0.0469 0.8976 0.012 0.000 0.000 0.988
#> SRR1313067 4 0.4992 0.0794 0.000 0.000 0.476 0.524
#> SRR1313068 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0592 0.8955 0.016 0.000 0.000 0.984
#> SRR1313072 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313076 3 0.5564 0.1428 0.020 0.000 0.544 0.436
#> SRR1313077 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313078 4 0.7365 0.1346 0.160 0.000 0.400 0.440
#> SRR1313079 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.4624 0.4533 0.000 0.000 0.340 0.660
#> SRR1313082 4 0.1474 0.8705 0.052 0.000 0.000 0.948
#> SRR1313083 4 0.4605 0.5011 0.336 0.000 0.000 0.664
#> SRR1313084 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.1302 0.8763 0.044 0.000 0.000 0.956
#> SRR1313086 4 0.4948 0.1853 0.440 0.000 0.000 0.560
#> SRR1313087 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0707 0.8930 0.020 0.000 0.000 0.980
#> SRR1313089 4 0.0000 0.9025 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.3873 0.6687 0.000 0.228 0.772 0.000
#> SRR1313093 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313095 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313096 1 0.5161 0.3827 0.592 0.000 0.400 0.008
#> SRR1313094 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313097 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313099 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313098 3 0.4866 0.2429 0.404 0.000 0.596 0.000
#> SRR1313101 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313103 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313100 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313107 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313106 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313108 3 0.3970 0.8047 0.076 0.000 0.840 0.084
#> SRR1313111 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313114 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313120 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313119 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.0336 0.9545 0.008 0.000 0.992 0.000
#> SRR1313123 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.0657 0.9492 0.004 0.000 0.984 0.012
#> SRR1313130 3 0.0336 0.9532 0.000 0.008 0.992 0.000
#> SRR1313132 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.9615 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.2149 0.8582 0.912 0.000 0.088 0.000
#> SRR1313131 1 0.6564 0.3314 0.536 0.000 0.380 0.084
#> SRR1313134 1 0.3219 0.7962 0.836 0.000 0.164 0.000
#> SRR1313135 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313140 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313141 1 0.3266 0.7925 0.832 0.000 0.168 0.000
#> SRR1313139 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313143 1 0.3836 0.7820 0.816 0.000 0.168 0.016
#> SRR1313142 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313149 1 0.3266 0.7925 0.832 0.000 0.168 0.000
#> SRR1313152 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313151 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313161 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313159 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313160 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313162 1 0.0336 0.9170 0.992 0.000 0.008 0.000
#> SRR1313163 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313166 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313167 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313170 3 0.2149 0.8705 0.088 0.000 0.912 0.000
#> SRR1313169 1 0.0000 0.9222 1.000 0.000 0.000 0.000
#> SRR1313172 1 0.5295 0.1120 0.504 0.008 0.488 0.000
#> SRR1313171 1 0.3266 0.7925 0.832 0.000 0.168 0.000
#> SRR1313174 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.6049 0.5912 0.652 0.000 0.264 0.084
#> SRR1313176 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.2647 0.8461 0.120 0.880 0.000 0.000
#> SRR1313180 2 0.4746 0.4315 0.000 0.632 0.368 0.000
#> SRR1313181 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313203 1 0.4057 0.7868 0.816 0.000 0.152 0.032
#> SRR1313204 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.0336 0.9532 0.000 0.008 0.992 0.000
#> SRR1313227 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9897 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9897 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0963 0.925 0.000 0.000 0.036 0.964 0.000
#> SRR1313063 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313064 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.2763 0.813 0.148 0.000 0.004 0.848 0.000
#> SRR1313066 4 0.1549 0.929 0.016 0.040 0.000 0.944 0.000
#> SRR1313067 3 0.3983 0.508 0.000 0.000 0.660 0.340 0.000
#> SRR1313068 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313069 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0290 0.950 0.000 0.008 0.000 0.992 0.000
#> SRR1313071 4 0.0798 0.944 0.016 0.008 0.000 0.976 0.000
#> SRR1313072 4 0.0290 0.950 0.000 0.008 0.000 0.992 0.000
#> SRR1313073 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0162 0.950 0.000 0.004 0.000 0.996 0.000
#> SRR1313076 3 0.4235 0.505 0.008 0.000 0.656 0.336 0.000
#> SRR1313077 4 0.0510 0.946 0.000 0.016 0.000 0.984 0.000
#> SRR1313078 2 0.7143 -0.329 0.012 0.348 0.320 0.320 0.000
#> SRR1313079 4 0.0162 0.950 0.000 0.004 0.000 0.996 0.000
#> SRR1313080 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313081 3 0.4192 0.363 0.000 0.000 0.596 0.404 0.000
#> SRR1313082 4 0.1341 0.916 0.056 0.000 0.000 0.944 0.000
#> SRR1313083 4 0.5819 0.558 0.232 0.144 0.004 0.620 0.000
#> SRR1313084 4 0.0290 0.950 0.000 0.008 0.000 0.992 0.000
#> SRR1313085 4 0.1740 0.911 0.056 0.012 0.000 0.932 0.000
#> SRR1313086 4 0.3752 0.565 0.292 0.000 0.000 0.708 0.000
#> SRR1313087 4 0.0000 0.951 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0912 0.943 0.016 0.012 0.000 0.972 0.000
#> SRR1313089 4 0.0162 0.950 0.000 0.004 0.000 0.996 0.000
#> SRR1313092 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313090 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313091 3 0.4305 0.132 0.000 0.000 0.512 0.000 0.488
#> SRR1313093 3 0.0162 0.911 0.000 0.004 0.996 0.000 0.000
#> SRR1313095 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313096 2 0.7137 -0.416 0.304 0.352 0.332 0.012 0.000
#> SRR1313094 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313097 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313099 3 0.0162 0.911 0.000 0.004 0.996 0.000 0.000
#> SRR1313098 3 0.3661 0.547 0.276 0.000 0.724 0.000 0.000
#> SRR1313101 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313102 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313103 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313100 3 0.0162 0.910 0.000 0.000 0.996 0.004 0.000
#> SRR1313105 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313104 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313107 3 0.0162 0.911 0.000 0.004 0.996 0.000 0.000
#> SRR1313106 3 0.0703 0.895 0.000 0.000 0.976 0.000 0.024
#> SRR1313109 3 0.3661 0.591 0.000 0.000 0.724 0.000 0.276
#> SRR1313108 3 0.6714 0.432 0.064 0.300 0.548 0.088 0.000
#> SRR1313111 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313110 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313112 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313113 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313115 3 0.0162 0.911 0.000 0.004 0.996 0.000 0.000
#> SRR1313114 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313117 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313118 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313116 5 0.4304 -0.102 0.000 0.000 0.484 0.000 0.516
#> SRR1313120 3 0.0162 0.911 0.000 0.004 0.996 0.000 0.000
#> SRR1313119 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313122 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313124 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313121 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313127 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313123 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313128 1 0.4030 0.700 0.648 0.352 0.000 0.000 0.000
#> SRR1313126 3 0.1197 0.878 0.000 0.000 0.952 0.048 0.000
#> SRR1313130 3 0.4045 0.449 0.000 0.000 0.644 0.000 0.356
#> SRR1313132 1 0.1965 0.829 0.904 0.096 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.913 0.000 0.000 1.000 0.000 0.000
#> SRR1313133 1 0.4298 0.696 0.640 0.352 0.008 0.000 0.000
#> SRR1313131 2 0.7999 -0.351 0.236 0.352 0.324 0.088 0.000
#> SRR1313134 1 0.5583 0.643 0.564 0.352 0.084 0.000 0.000
#> SRR1313135 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.0290 0.863 0.992 0.008 0.000 0.000 0.000
#> SRR1313141 1 0.6224 0.584 0.496 0.352 0.152 0.000 0.000
#> SRR1313139 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313143 1 0.6603 0.568 0.480 0.352 0.156 0.012 0.000
#> SRR1313142 1 0.1478 0.843 0.936 0.064 0.000 0.000 0.000
#> SRR1313144 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 1 0.6224 0.584 0.496 0.352 0.152 0.000 0.000
#> SRR1313152 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0162 0.864 0.996 0.004 0.000 0.000 0.000
#> SRR1313154 1 0.4015 0.702 0.652 0.348 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0162 0.864 0.996 0.004 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0290 0.860 0.992 0.000 0.008 0.000 0.000
#> SRR1313159 1 0.0324 0.863 0.992 0.004 0.000 0.000 0.004
#> SRR1313160 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.3741 0.611 0.732 0.004 0.264 0.000 0.000
#> SRR1313163 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.3796 0.730 0.700 0.300 0.000 0.000 0.000
#> SRR1313164 1 0.4015 0.702 0.652 0.348 0.000 0.000 0.000
#> SRR1313167 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.5304 0.494 0.080 0.000 0.628 0.000 0.292
#> SRR1313169 1 0.0000 0.865 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 1 0.6814 0.450 0.404 0.356 0.236 0.000 0.004
#> SRR1313171 1 0.6132 0.596 0.508 0.352 0.140 0.000 0.000
#> SRR1313174 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313173 2 0.8039 -0.389 0.268 0.352 0.292 0.088 0.000
#> SRR1313176 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313175 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313178 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313177 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313179 2 0.5730 0.668 0.096 0.548 0.000 0.000 0.356
#> SRR1313180 5 0.0162 0.920 0.000 0.000 0.004 0.000 0.996
#> SRR1313181 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313183 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313182 2 0.4219 0.730 0.000 0.584 0.000 0.000 0.416
#> SRR1313184 2 0.4171 0.756 0.000 0.604 0.000 0.000 0.396
#> SRR1313185 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313188 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313187 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313186 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313189 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313190 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313191 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313192 2 0.4114 0.783 0.000 0.624 0.000 0.000 0.376
#> SRR1313193 2 0.4219 0.730 0.000 0.584 0.000 0.000 0.416
#> SRR1313194 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313195 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313196 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313197 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313198 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313199 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313200 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313201 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313202 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313203 1 0.6847 0.544 0.452 0.380 0.140 0.028 0.000
#> SRR1313204 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313205 2 0.4114 0.783 0.000 0.624 0.000 0.000 0.376
#> SRR1313207 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313208 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313206 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313210 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313209 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313211 5 0.3143 0.521 0.000 0.204 0.000 0.000 0.796
#> SRR1313212 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313214 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313215 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313213 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313216 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313217 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313219 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313220 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313218 5 0.0290 0.915 0.000 0.008 0.000 0.000 0.992
#> SRR1313222 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313221 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313223 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313224 2 0.4219 0.730 0.000 0.584 0.000 0.000 0.416
#> SRR1313225 5 0.0000 0.926 0.000 0.000 0.000 0.000 1.000
#> SRR1313226 5 0.4045 0.276 0.000 0.000 0.356 0.000 0.644
#> SRR1313227 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313228 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
#> SRR1313229 2 0.4045 0.804 0.000 0.644 0.000 0.000 0.356
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.4026 0.681 0.000 0.000 0.012 0.612 0.000 0.376
#> SRR1313063 4 0.3695 0.687 0.000 0.000 0.000 0.624 0.000 0.376
#> SRR1313064 4 0.2664 0.786 0.000 0.000 0.000 0.816 0.000 0.184
#> SRR1313065 4 0.3133 0.635 0.212 0.000 0.008 0.780 0.000 0.000
#> SRR1313066 4 0.2509 0.767 0.000 0.000 0.000 0.876 0.036 0.088
#> SRR1313067 3 0.5309 0.239 0.000 0.000 0.488 0.104 0.000 0.408
#> SRR1313068 4 0.3774 0.662 0.000 0.000 0.000 0.592 0.000 0.408
#> SRR1313069 4 0.2664 0.788 0.000 0.000 0.000 0.816 0.000 0.184
#> SRR1313070 4 0.1320 0.795 0.000 0.000 0.000 0.948 0.036 0.016
#> SRR1313071 4 0.1320 0.795 0.000 0.000 0.000 0.948 0.036 0.016
#> SRR1313072 4 0.1225 0.796 0.000 0.000 0.000 0.952 0.036 0.012
#> SRR1313073 4 0.3547 0.715 0.000 0.000 0.000 0.668 0.000 0.332
#> SRR1313074 4 0.3211 0.780 0.056 0.000 0.000 0.824 0.000 0.120
#> SRR1313075 4 0.1010 0.797 0.000 0.000 0.000 0.960 0.036 0.004
#> SRR1313076 6 0.5324 -0.170 0.000 0.000 0.428 0.104 0.000 0.468
#> SRR1313077 4 0.3857 0.596 0.000 0.000 0.000 0.532 0.000 0.468
#> SRR1313078 6 0.1141 0.377 0.000 0.000 0.000 0.052 0.000 0.948
#> SRR1313079 4 0.3248 0.795 0.000 0.000 0.000 0.804 0.032 0.164
#> SRR1313080 4 0.3756 0.669 0.000 0.000 0.000 0.600 0.000 0.400
#> SRR1313081 6 0.5987 -0.205 0.000 0.000 0.312 0.252 0.000 0.436
#> SRR1313082 4 0.0547 0.798 0.020 0.000 0.000 0.980 0.000 0.000
#> SRR1313083 4 0.5187 0.436 0.160 0.000 0.008 0.644 0.000 0.188
#> SRR1313084 4 0.1225 0.796 0.000 0.000 0.000 0.952 0.036 0.012
#> SRR1313085 4 0.2074 0.782 0.004 0.000 0.000 0.912 0.036 0.048
#> SRR1313086 4 0.3189 0.591 0.236 0.000 0.000 0.760 0.000 0.004
#> SRR1313087 4 0.2664 0.786 0.000 0.000 0.000 0.816 0.000 0.184
#> SRR1313088 4 0.1906 0.793 0.008 0.000 0.000 0.924 0.036 0.032
#> SRR1313089 4 0.1124 0.797 0.000 0.000 0.000 0.956 0.036 0.008
#> SRR1313092 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313090 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313091 3 0.3428 0.608 0.000 0.000 0.696 0.000 0.304 0.000
#> SRR1313093 3 0.2092 0.831 0.000 0.000 0.876 0.000 0.000 0.124
#> SRR1313095 3 0.0790 0.905 0.000 0.000 0.968 0.000 0.000 0.032
#> SRR1313096 6 0.3704 0.618 0.232 0.000 0.016 0.008 0.000 0.744
#> SRR1313094 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313097 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313099 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313098 3 0.3912 0.345 0.340 0.000 0.648 0.000 0.000 0.012
#> SRR1313101 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313103 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313100 3 0.0865 0.900 0.000 0.000 0.964 0.036 0.000 0.000
#> SRR1313105 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313104 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313106 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313109 3 0.1501 0.872 0.000 0.000 0.924 0.000 0.076 0.000
#> SRR1313108 6 0.2020 0.386 0.000 0.000 0.096 0.008 0.000 0.896
#> SRR1313111 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313110 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313112 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313115 3 0.2389 0.827 0.000 0.000 0.864 0.000 0.008 0.128
#> SRR1313114 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313117 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313116 3 0.3765 0.408 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1313120 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313119 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313122 3 0.1349 0.887 0.000 0.000 0.940 0.004 0.000 0.056
#> SRR1313124 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313121 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313125 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313127 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313123 3 0.0000 0.923 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313128 6 0.3881 0.578 0.396 0.000 0.000 0.004 0.000 0.600
#> SRR1313126 3 0.4000 0.652 0.000 0.000 0.724 0.048 0.000 0.228
#> SRR1313130 3 0.2793 0.743 0.000 0.000 0.800 0.000 0.200 0.000
#> SRR1313132 1 0.2302 0.786 0.872 0.000 0.000 0.000 0.008 0.120
#> SRR1313129 3 0.0260 0.922 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1313133 6 0.3899 0.567 0.404 0.000 0.000 0.004 0.000 0.592
#> SRR1313131 6 0.0146 0.428 0.000 0.000 0.000 0.004 0.000 0.996
#> SRR1313134 6 0.3890 0.573 0.400 0.000 0.000 0.004 0.000 0.596
#> SRR1313135 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313136 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313140 1 0.2178 0.775 0.868 0.000 0.000 0.000 0.000 0.132
#> SRR1313141 6 0.3819 0.602 0.372 0.000 0.000 0.004 0.000 0.624
#> SRR1313139 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313143 6 0.3584 0.620 0.308 0.000 0.000 0.004 0.000 0.688
#> SRR1313142 1 0.2912 0.607 0.784 0.000 0.000 0.000 0.000 0.216
#> SRR1313144 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313147 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313150 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313149 6 0.3807 0.605 0.368 0.000 0.000 0.004 0.000 0.628
#> SRR1313152 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.0603 0.930 0.980 0.000 0.000 0.004 0.000 0.016
#> SRR1313154 6 0.3971 0.482 0.448 0.000 0.000 0.004 0.000 0.548
#> SRR1313153 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313156 1 0.0363 0.937 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1313155 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313157 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313161 1 0.0632 0.916 0.976 0.000 0.024 0.000 0.000 0.000
#> SRR1313159 1 0.0891 0.917 0.968 0.000 0.000 0.000 0.024 0.008
#> SRR1313160 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.1390 0.899 0.948 0.000 0.016 0.004 0.000 0.032
#> SRR1313163 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313165 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313166 1 0.3847 -0.267 0.544 0.000 0.000 0.000 0.000 0.456
#> SRR1313164 6 0.3843 0.474 0.452 0.000 0.000 0.000 0.000 0.548
#> SRR1313167 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313168 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313170 3 0.2786 0.816 0.084 0.000 0.860 0.000 0.056 0.000
#> SRR1313169 1 0.0000 0.948 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313172 6 0.5117 0.575 0.288 0.000 0.116 0.000 0.000 0.596
#> SRR1313171 6 0.3862 0.587 0.388 0.000 0.000 0.004 0.000 0.608
#> SRR1313174 5 0.1141 0.974 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313173 6 0.0146 0.428 0.000 0.000 0.000 0.004 0.000 0.996
#> SRR1313176 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313178 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.1908 0.819 0.096 0.900 0.000 0.000 0.000 0.004
#> SRR1313180 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313181 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3563 0.524 0.000 0.664 0.000 0.000 0.336 0.000
#> SRR1313184 2 0.1863 0.849 0.000 0.896 0.000 0.000 0.104 0.000
#> SRR1313185 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313188 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313187 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313186 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313189 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.1141 0.974 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313192 2 0.3050 0.694 0.000 0.764 0.000 0.000 0.236 0.000
#> SRR1313193 2 0.3563 0.524 0.000 0.664 0.000 0.000 0.336 0.000
#> SRR1313194 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313195 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313196 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313197 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313198 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313199 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313201 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0865 0.971 0.000 0.036 0.000 0.000 0.964 0.000
#> SRR1313203 6 0.3911 0.604 0.368 0.000 0.000 0.008 0.000 0.624
#> SRR1313204 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.2823 0.738 0.000 0.796 0.000 0.000 0.204 0.000
#> SRR1313207 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313209 5 0.1141 0.974 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313211 5 0.3717 0.374 0.000 0.384 0.000 0.000 0.616 0.000
#> SRR1313212 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.1141 0.974 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313215 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313213 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.1007 0.972 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313217 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313219 5 0.1007 0.978 0.000 0.044 0.000 0.000 0.956 0.000
#> SRR1313220 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 5 0.1204 0.971 0.000 0.056 0.000 0.000 0.944 0.000
#> SRR1313222 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.3563 0.524 0.000 0.664 0.000 0.000 0.336 0.000
#> SRR1313225 5 0.1141 0.974 0.000 0.052 0.000 0.000 0.948 0.000
#> SRR1313226 5 0.0865 0.921 0.000 0.000 0.036 0.000 0.964 0.000
#> SRR1313227 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.932 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "mclust"]
# you can also extract it by
# res = res_list["MAD:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.505 0.748 0.861 0.4540 0.560 0.560
#> 3 3 0.617 0.655 0.794 0.4004 0.770 0.589
#> 4 4 0.718 0.842 0.862 0.1348 0.875 0.648
#> 5 5 0.649 0.738 0.822 0.0755 0.940 0.771
#> 6 6 0.718 0.597 0.773 0.0430 0.952 0.785
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.6973 0.730 0.812 0.188
#> SRR1313063 1 0.6887 0.732 0.816 0.184
#> SRR1313064 1 0.0000 0.773 1.000 0.000
#> SRR1313065 1 0.0000 0.773 1.000 0.000
#> SRR1313066 1 0.0000 0.773 1.000 0.000
#> SRR1313067 1 0.6973 0.730 0.812 0.188
#> SRR1313068 1 0.6973 0.730 0.812 0.188
#> SRR1313069 1 0.0000 0.773 1.000 0.000
#> SRR1313070 1 0.0000 0.773 1.000 0.000
#> SRR1313071 1 0.0000 0.773 1.000 0.000
#> SRR1313072 1 0.0000 0.773 1.000 0.000
#> SRR1313073 1 0.0000 0.773 1.000 0.000
#> SRR1313074 1 0.0000 0.773 1.000 0.000
#> SRR1313075 1 0.0000 0.773 1.000 0.000
#> SRR1313076 1 0.6973 0.730 0.812 0.188
#> SRR1313077 1 0.6973 0.730 0.812 0.188
#> SRR1313078 1 0.6973 0.730 0.812 0.188
#> SRR1313079 1 0.0000 0.773 1.000 0.000
#> SRR1313080 1 0.6973 0.730 0.812 0.188
#> SRR1313081 1 0.6973 0.730 0.812 0.188
#> SRR1313082 1 0.0000 0.773 1.000 0.000
#> SRR1313083 1 0.0000 0.773 1.000 0.000
#> SRR1313084 1 0.0000 0.773 1.000 0.000
#> SRR1313085 1 0.0000 0.773 1.000 0.000
#> SRR1313086 1 0.0000 0.773 1.000 0.000
#> SRR1313087 1 0.0000 0.773 1.000 0.000
#> SRR1313088 1 0.0000 0.773 1.000 0.000
#> SRR1313089 1 0.0000 0.773 1.000 0.000
#> SRR1313092 1 0.9944 0.498 0.544 0.456
#> SRR1313090 1 0.9993 0.452 0.516 0.484
#> SRR1313091 1 1.0000 0.413 0.500 0.500
#> SRR1313093 1 0.9933 0.503 0.548 0.452
#> SRR1313095 1 0.9896 0.518 0.560 0.440
#> SRR1313096 1 0.7219 0.728 0.800 0.200
#> SRR1313094 1 0.9988 0.459 0.520 0.480
#> SRR1313097 1 0.9993 0.452 0.516 0.484
#> SRR1313099 1 0.9970 0.466 0.532 0.468
#> SRR1313098 1 0.8016 0.704 0.756 0.244
#> SRR1313101 1 0.9993 0.452 0.516 0.484
#> SRR1313102 1 0.9993 0.452 0.516 0.484
#> SRR1313103 1 0.9970 0.466 0.532 0.468
#> SRR1313100 1 0.9795 0.537 0.584 0.416
#> SRR1313105 1 0.9993 0.452 0.516 0.484
#> SRR1313104 1 0.9993 0.452 0.516 0.484
#> SRR1313107 1 0.9970 0.466 0.532 0.468
#> SRR1313106 1 0.9977 0.473 0.528 0.472
#> SRR1313109 1 0.9998 0.433 0.508 0.492
#> SRR1313108 1 0.7602 0.717 0.780 0.220
#> SRR1313111 1 0.9988 0.459 0.520 0.480
#> SRR1313110 1 0.9944 0.498 0.544 0.456
#> SRR1313112 1 0.9993 0.452 0.516 0.484
#> SRR1313113 1 0.9993 0.452 0.516 0.484
#> SRR1313115 1 0.9933 0.503 0.548 0.452
#> SRR1313114 1 0.9933 0.503 0.548 0.452
#> SRR1313117 1 0.9993 0.452 0.516 0.484
#> SRR1313118 1 0.9944 0.498 0.544 0.456
#> SRR1313116 1 0.9993 0.452 0.516 0.484
#> SRR1313120 1 0.9970 0.466 0.532 0.468
#> SRR1313119 1 0.9993 0.452 0.516 0.484
#> SRR1313122 1 0.9922 0.506 0.552 0.448
#> SRR1313124 1 0.9993 0.452 0.516 0.484
#> SRR1313121 1 0.9993 0.452 0.516 0.484
#> SRR1313125 1 0.9993 0.452 0.516 0.484
#> SRR1313127 1 0.8144 0.698 0.748 0.252
#> SRR1313123 1 0.9129 0.637 0.672 0.328
#> SRR1313128 1 0.0938 0.776 0.988 0.012
#> SRR1313126 1 0.6973 0.730 0.812 0.188
#> SRR1313130 1 1.0000 0.413 0.500 0.500
#> SRR1313132 1 0.0938 0.776 0.988 0.012
#> SRR1313129 1 0.9993 0.452 0.516 0.484
#> SRR1313133 1 0.0938 0.776 0.988 0.012
#> SRR1313131 1 0.7219 0.728 0.800 0.200
#> SRR1313134 1 0.0938 0.776 0.988 0.012
#> SRR1313135 1 0.0938 0.776 0.988 0.012
#> SRR1313136 1 0.0938 0.776 0.988 0.012
#> SRR1313137 1 0.0938 0.776 0.988 0.012
#> SRR1313138 1 0.4431 0.758 0.908 0.092
#> SRR1313140 1 0.0000 0.773 1.000 0.000
#> SRR1313141 1 0.0938 0.776 0.988 0.012
#> SRR1313139 1 0.0000 0.773 1.000 0.000
#> SRR1313143 1 0.0938 0.776 0.988 0.012
#> SRR1313142 1 0.0938 0.776 0.988 0.012
#> SRR1313144 1 0.0938 0.776 0.988 0.012
#> SRR1313145 1 0.0938 0.776 0.988 0.012
#> SRR1313146 1 0.0938 0.776 0.988 0.012
#> SRR1313147 1 0.0000 0.773 1.000 0.000
#> SRR1313150 1 0.1184 0.774 0.984 0.016
#> SRR1313149 1 0.0938 0.776 0.988 0.012
#> SRR1313152 1 0.0938 0.776 0.988 0.012
#> SRR1313151 1 0.0938 0.776 0.988 0.012
#> SRR1313154 1 0.0938 0.776 0.988 0.012
#> SRR1313153 1 0.0938 0.776 0.988 0.012
#> SRR1313156 1 0.3431 0.767 0.936 0.064
#> SRR1313155 1 0.0938 0.776 0.988 0.012
#> SRR1313157 1 0.0000 0.773 1.000 0.000
#> SRR1313158 1 0.0938 0.776 0.988 0.012
#> SRR1313161 1 0.4298 0.759 0.912 0.088
#> SRR1313159 1 0.4690 0.755 0.900 0.100
#> SRR1313160 1 0.3274 0.768 0.940 0.060
#> SRR1313162 1 0.1633 0.776 0.976 0.024
#> SRR1313163 1 0.4298 0.759 0.912 0.088
#> SRR1313165 1 0.3114 0.769 0.944 0.056
#> SRR1313166 1 0.0938 0.776 0.988 0.012
#> SRR1313164 1 0.0938 0.776 0.988 0.012
#> SRR1313167 1 0.0000 0.773 1.000 0.000
#> SRR1313168 1 0.0938 0.776 0.988 0.012
#> SRR1313170 1 0.9993 0.452 0.516 0.484
#> SRR1313169 1 0.0938 0.776 0.988 0.012
#> SRR1313172 1 0.9881 0.523 0.564 0.436
#> SRR1313171 1 0.0938 0.776 0.988 0.012
#> SRR1313174 2 0.0000 0.971 0.000 1.000
#> SRR1313173 1 0.7219 0.728 0.800 0.200
#> SRR1313176 2 0.0000 0.971 0.000 1.000
#> SRR1313175 2 0.0000 0.971 0.000 1.000
#> SRR1313178 2 0.0000 0.971 0.000 1.000
#> SRR1313177 2 0.0000 0.971 0.000 1.000
#> SRR1313179 1 0.9963 0.486 0.536 0.464
#> SRR1313180 2 0.0000 0.971 0.000 1.000
#> SRR1313181 2 0.0000 0.971 0.000 1.000
#> SRR1313183 2 0.0000 0.971 0.000 1.000
#> SRR1313182 2 0.0000 0.971 0.000 1.000
#> SRR1313184 2 0.8661 0.362 0.288 0.712
#> SRR1313185 2 0.0000 0.971 0.000 1.000
#> SRR1313188 2 0.0000 0.971 0.000 1.000
#> SRR1313187 2 0.0000 0.971 0.000 1.000
#> SRR1313186 2 0.0000 0.971 0.000 1.000
#> SRR1313189 2 0.0000 0.971 0.000 1.000
#> SRR1313190 2 0.0000 0.971 0.000 1.000
#> SRR1313191 2 0.0000 0.971 0.000 1.000
#> SRR1313192 2 0.0000 0.971 0.000 1.000
#> SRR1313193 2 0.0000 0.971 0.000 1.000
#> SRR1313194 2 0.0000 0.971 0.000 1.000
#> SRR1313195 2 0.0000 0.971 0.000 1.000
#> SRR1313196 2 0.0000 0.971 0.000 1.000
#> SRR1313197 2 0.0000 0.971 0.000 1.000
#> SRR1313198 2 0.0000 0.971 0.000 1.000
#> SRR1313199 2 0.0000 0.971 0.000 1.000
#> SRR1313200 2 0.0000 0.971 0.000 1.000
#> SRR1313201 2 0.0000 0.971 0.000 1.000
#> SRR1313202 2 0.0000 0.971 0.000 1.000
#> SRR1313203 1 0.7453 0.717 0.788 0.212
#> SRR1313204 2 0.0000 0.971 0.000 1.000
#> SRR1313205 2 0.0000 0.971 0.000 1.000
#> SRR1313207 2 0.0000 0.971 0.000 1.000
#> SRR1313208 2 0.0000 0.971 0.000 1.000
#> SRR1313206 2 0.0000 0.971 0.000 1.000
#> SRR1313210 2 0.0000 0.971 0.000 1.000
#> SRR1313209 2 0.0000 0.971 0.000 1.000
#> SRR1313211 2 0.0000 0.971 0.000 1.000
#> SRR1313212 2 0.0000 0.971 0.000 1.000
#> SRR1313214 2 0.0000 0.971 0.000 1.000
#> SRR1313215 2 0.0000 0.971 0.000 1.000
#> SRR1313213 2 0.0000 0.971 0.000 1.000
#> SRR1313216 2 1.0000 -0.429 0.500 0.500
#> SRR1313217 2 0.0000 0.971 0.000 1.000
#> SRR1313219 2 0.0000 0.971 0.000 1.000
#> SRR1313220 2 0.0000 0.971 0.000 1.000
#> SRR1313218 2 0.0000 0.971 0.000 1.000
#> SRR1313222 2 0.0000 0.971 0.000 1.000
#> SRR1313221 2 0.0000 0.971 0.000 1.000
#> SRR1313223 2 0.0000 0.971 0.000 1.000
#> SRR1313224 2 0.0000 0.971 0.000 1.000
#> SRR1313225 2 0.0000 0.971 0.000 1.000
#> SRR1313226 2 0.8499 0.402 0.276 0.724
#> SRR1313227 2 0.0000 0.971 0.000 1.000
#> SRR1313228 2 0.0000 0.971 0.000 1.000
#> SRR1313229 2 0.0000 0.971 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 3 0.6274 0.2614 0.456 0.000 0.544
#> SRR1313063 3 0.6274 0.2614 0.456 0.000 0.544
#> SRR1313064 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313065 1 0.5760 0.2791 0.672 0.000 0.328
#> SRR1313066 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313067 3 0.6079 0.3567 0.388 0.000 0.612
#> SRR1313068 3 0.6235 0.2881 0.436 0.000 0.564
#> SRR1313069 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313070 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313071 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313072 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313073 1 0.6291 -0.1152 0.532 0.000 0.468
#> SRR1313074 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313075 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313076 3 0.6192 0.3097 0.420 0.000 0.580
#> SRR1313077 3 0.5465 0.5031 0.288 0.000 0.712
#> SRR1313078 3 0.4235 0.6521 0.176 0.000 0.824
#> SRR1313079 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313080 3 0.6274 0.2614 0.456 0.000 0.544
#> SRR1313081 3 0.5497 0.4969 0.292 0.000 0.708
#> SRR1313082 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313083 1 0.5905 0.2604 0.648 0.000 0.352
#> SRR1313084 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313085 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313086 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313087 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313088 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313089 1 0.5733 0.2817 0.676 0.000 0.324
#> SRR1313092 3 0.1860 0.7492 0.052 0.000 0.948
#> SRR1313090 3 0.1411 0.7444 0.036 0.000 0.964
#> SRR1313091 3 0.7901 0.1546 0.060 0.400 0.540
#> SRR1313093 3 0.4062 0.6648 0.164 0.000 0.836
#> SRR1313095 3 0.1964 0.7467 0.056 0.000 0.944
#> SRR1313096 3 0.4062 0.6648 0.164 0.000 0.836
#> SRR1313094 3 0.1964 0.7467 0.056 0.000 0.944
#> SRR1313097 3 0.0475 0.7462 0.004 0.004 0.992
#> SRR1313099 3 0.2998 0.7434 0.068 0.016 0.916
#> SRR1313098 3 0.2165 0.7446 0.064 0.000 0.936
#> SRR1313101 3 0.0237 0.7489 0.000 0.004 0.996
#> SRR1313102 3 0.2383 0.7499 0.044 0.016 0.940
#> SRR1313103 3 0.2749 0.7462 0.064 0.012 0.924
#> SRR1313100 3 0.1753 0.7465 0.048 0.000 0.952
#> SRR1313105 3 0.0475 0.7462 0.004 0.004 0.992
#> SRR1313104 3 0.0000 0.7483 0.000 0.000 1.000
#> SRR1313107 3 0.2680 0.7461 0.068 0.008 0.924
#> SRR1313106 3 0.0661 0.7448 0.004 0.008 0.988
#> SRR1313109 3 0.6678 0.4314 0.060 0.216 0.724
#> SRR1313108 3 0.4062 0.6648 0.164 0.000 0.836
#> SRR1313111 3 0.1878 0.7536 0.044 0.004 0.952
#> SRR1313110 3 0.1411 0.7444 0.036 0.000 0.964
#> SRR1313112 3 0.0237 0.7489 0.000 0.004 0.996
#> SRR1313113 3 0.0237 0.7489 0.000 0.004 0.996
#> SRR1313115 3 0.4002 0.6687 0.160 0.000 0.840
#> SRR1313114 3 0.1411 0.7444 0.036 0.000 0.964
#> SRR1313117 3 0.1289 0.7466 0.032 0.000 0.968
#> SRR1313118 3 0.1411 0.7444 0.036 0.000 0.964
#> SRR1313116 3 0.2096 0.7086 0.004 0.052 0.944
#> SRR1313120 3 0.2261 0.7440 0.068 0.000 0.932
#> SRR1313119 3 0.1411 0.7444 0.036 0.000 0.964
#> SRR1313122 3 0.1860 0.7492 0.052 0.000 0.948
#> SRR1313124 3 0.1289 0.7466 0.032 0.000 0.968
#> SRR1313121 3 0.1163 0.7483 0.028 0.000 0.972
#> SRR1313125 3 0.0237 0.7489 0.000 0.004 0.996
#> SRR1313127 3 0.2165 0.7446 0.064 0.000 0.936
#> SRR1313123 3 0.2066 0.7453 0.060 0.000 0.940
#> SRR1313128 1 0.5621 0.5695 0.692 0.000 0.308
#> SRR1313126 3 0.2448 0.7391 0.076 0.000 0.924
#> SRR1313130 3 0.7915 0.1179 0.056 0.456 0.488
#> SRR1313132 1 0.6140 0.5326 0.596 0.000 0.404
#> SRR1313129 3 0.3253 0.7321 0.052 0.036 0.912
#> SRR1313133 1 0.5621 0.5695 0.692 0.000 0.308
#> SRR1313131 3 0.5016 0.5708 0.240 0.000 0.760
#> SRR1313134 1 0.5810 0.5573 0.664 0.000 0.336
#> SRR1313135 1 0.6126 0.5437 0.600 0.000 0.400
#> SRR1313136 1 0.6126 0.5404 0.600 0.000 0.400
#> SRR1313137 1 0.6062 0.5463 0.616 0.000 0.384
#> SRR1313138 1 0.6373 0.5342 0.588 0.004 0.408
#> SRR1313140 1 0.4002 0.4550 0.840 0.000 0.160
#> SRR1313141 1 0.5835 0.5546 0.660 0.000 0.340
#> SRR1313139 1 0.4931 0.4811 0.768 0.000 0.232
#> SRR1313143 1 0.6295 0.3489 0.528 0.000 0.472
#> SRR1313142 1 0.5650 0.5701 0.688 0.000 0.312
#> SRR1313144 1 0.6062 0.5485 0.616 0.000 0.384
#> SRR1313145 1 0.6095 0.5426 0.608 0.000 0.392
#> SRR1313146 1 0.5733 0.5711 0.676 0.000 0.324
#> SRR1313147 1 0.6026 0.5565 0.624 0.000 0.376
#> SRR1313150 1 0.6295 0.4604 0.528 0.000 0.472
#> SRR1313149 1 0.5905 0.5405 0.648 0.000 0.352
#> SRR1313152 1 0.6062 0.5463 0.616 0.000 0.384
#> SRR1313151 1 0.5650 0.5706 0.688 0.000 0.312
#> SRR1313154 1 0.5621 0.5695 0.692 0.000 0.308
#> SRR1313153 1 0.5706 0.5702 0.680 0.000 0.320
#> SRR1313156 1 0.6140 0.5326 0.596 0.000 0.404
#> SRR1313155 1 0.5948 0.5645 0.640 0.000 0.360
#> SRR1313157 1 0.6267 0.4879 0.548 0.000 0.452
#> SRR1313158 1 0.6140 0.5326 0.596 0.000 0.404
#> SRR1313161 1 0.6180 0.5286 0.584 0.000 0.416
#> SRR1313159 1 0.6498 0.5339 0.596 0.008 0.396
#> SRR1313160 1 0.6111 0.5428 0.604 0.000 0.396
#> SRR1313162 3 0.2448 0.7409 0.076 0.000 0.924
#> SRR1313163 1 0.6168 0.5327 0.588 0.000 0.412
#> SRR1313165 1 0.6111 0.5428 0.604 0.000 0.396
#> SRR1313166 1 0.5650 0.5701 0.688 0.000 0.312
#> SRR1313164 1 0.5706 0.5702 0.680 0.000 0.320
#> SRR1313167 1 0.6280 0.4712 0.540 0.000 0.460
#> SRR1313168 1 0.6045 0.5495 0.620 0.000 0.380
#> SRR1313170 3 0.2918 0.7367 0.044 0.032 0.924
#> SRR1313169 1 0.5905 0.5651 0.648 0.000 0.352
#> SRR1313172 3 0.9474 0.1115 0.272 0.232 0.496
#> SRR1313171 1 0.6291 0.3675 0.532 0.000 0.468
#> SRR1313174 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313173 3 0.4291 0.6545 0.180 0.000 0.820
#> SRR1313176 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313175 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313178 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313177 2 0.0237 0.9641 0.004 0.996 0.000
#> SRR1313179 3 0.9058 0.1637 0.180 0.276 0.544
#> SRR1313180 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313181 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313183 2 0.0237 0.9641 0.004 0.996 0.000
#> SRR1313182 2 0.0237 0.9656 0.004 0.996 0.000
#> SRR1313184 2 0.8058 0.1878 0.072 0.552 0.376
#> SRR1313185 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313188 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313187 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313186 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313189 2 0.0237 0.9641 0.004 0.996 0.000
#> SRR1313190 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313191 2 0.0237 0.9656 0.004 0.996 0.000
#> SRR1313192 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313194 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313195 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313196 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313197 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313198 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313199 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313200 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313201 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313202 2 0.5024 0.6979 0.004 0.776 0.220
#> SRR1313203 1 0.6274 0.1567 0.544 0.000 0.456
#> SRR1313204 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313210 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313209 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313211 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313214 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313215 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313213 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313216 2 0.7987 -0.0427 0.060 0.492 0.448
#> SRR1313217 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313219 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313220 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313218 2 0.0475 0.9652 0.004 0.992 0.004
#> SRR1313222 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313224 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313225 2 0.0661 0.9645 0.004 0.988 0.008
#> SRR1313226 2 0.5404 0.6357 0.004 0.740 0.256
#> SRR1313227 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9659 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9659 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.2149 0.79503 0.000 0.000 0.088 0.912
#> SRR1313063 4 0.0707 0.81141 0.000 0.000 0.020 0.980
#> SRR1313064 4 0.1398 0.80953 0.040 0.000 0.004 0.956
#> SRR1313065 4 0.6170 0.46538 0.332 0.000 0.068 0.600
#> SRR1313066 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313067 4 0.3306 0.74806 0.004 0.000 0.156 0.840
#> SRR1313068 4 0.2216 0.79363 0.000 0.000 0.092 0.908
#> SRR1313069 4 0.4761 0.52133 0.332 0.000 0.004 0.664
#> SRR1313070 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313071 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313072 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313073 4 0.0779 0.81499 0.016 0.000 0.004 0.980
#> SRR1313074 4 0.3908 0.68554 0.212 0.000 0.004 0.784
#> SRR1313075 4 0.0895 0.81485 0.020 0.000 0.004 0.976
#> SRR1313076 4 0.2999 0.76889 0.004 0.000 0.132 0.864
#> SRR1313077 4 0.4914 0.67388 0.044 0.000 0.208 0.748
#> SRR1313078 4 0.7017 0.38366 0.188 0.000 0.236 0.576
#> SRR1313079 4 0.0779 0.81499 0.016 0.000 0.004 0.980
#> SRR1313080 4 0.1792 0.80252 0.000 0.000 0.068 0.932
#> SRR1313081 4 0.4579 0.69422 0.032 0.000 0.200 0.768
#> SRR1313082 4 0.5677 0.49595 0.332 0.000 0.040 0.628
#> SRR1313083 4 0.6221 0.48450 0.316 0.000 0.076 0.608
#> SRR1313084 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313085 4 0.0188 0.81238 0.000 0.000 0.004 0.996
#> SRR1313086 4 0.6041 0.47611 0.332 0.000 0.060 0.608
#> SRR1313087 4 0.0779 0.81499 0.016 0.000 0.004 0.980
#> SRR1313088 4 0.1004 0.81429 0.024 0.000 0.004 0.972
#> SRR1313089 4 0.0895 0.81499 0.020 0.000 0.004 0.976
#> SRR1313092 3 0.0524 0.93253 0.008 0.000 0.988 0.004
#> SRR1313090 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313091 3 0.5125 0.37441 0.004 0.376 0.616 0.004
#> SRR1313093 3 0.1867 0.88056 0.072 0.000 0.928 0.000
#> SRR1313095 3 0.0524 0.93253 0.008 0.000 0.988 0.004
#> SRR1313096 3 0.1940 0.87897 0.076 0.000 0.924 0.000
#> SRR1313094 3 0.0336 0.93235 0.008 0.000 0.992 0.000
#> SRR1313097 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313099 3 0.1474 0.89704 0.052 0.000 0.948 0.000
#> SRR1313098 3 0.0524 0.93253 0.008 0.000 0.988 0.004
#> SRR1313101 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313102 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313103 3 0.0188 0.93277 0.004 0.000 0.996 0.000
#> SRR1313100 3 0.2450 0.85250 0.016 0.000 0.912 0.072
#> SRR1313105 3 0.0000 0.93413 0.000 0.000 1.000 0.000
#> SRR1313104 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313107 3 0.1716 0.88643 0.064 0.000 0.936 0.000
#> SRR1313106 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313109 3 0.0817 0.91761 0.000 0.024 0.976 0.000
#> SRR1313108 3 0.2125 0.87744 0.076 0.000 0.920 0.004
#> SRR1313111 3 0.0000 0.93413 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.1716 0.87410 0.000 0.000 0.936 0.064
#> SRR1313112 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313113 3 0.0000 0.93413 0.000 0.000 1.000 0.000
#> SRR1313115 3 0.1867 0.88056 0.072 0.000 0.928 0.000
#> SRR1313114 3 0.0469 0.93032 0.000 0.000 0.988 0.012
#> SRR1313117 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313118 3 0.0817 0.91872 0.000 0.000 0.976 0.024
#> SRR1313116 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313120 3 0.1792 0.88247 0.068 0.000 0.932 0.000
#> SRR1313119 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313122 3 0.0672 0.93195 0.008 0.000 0.984 0.008
#> SRR1313124 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313121 3 0.0376 0.93426 0.004 0.000 0.992 0.004
#> SRR1313125 3 0.0336 0.93244 0.000 0.000 0.992 0.008
#> SRR1313127 3 0.0657 0.93123 0.012 0.000 0.984 0.004
#> SRR1313123 3 0.1637 0.89239 0.060 0.000 0.940 0.000
#> SRR1313128 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313126 3 0.1256 0.91807 0.028 0.000 0.964 0.008
#> SRR1313130 3 0.4607 0.54576 0.004 0.276 0.716 0.004
#> SRR1313132 1 0.3726 0.88709 0.788 0.000 0.212 0.000
#> SRR1313129 3 0.0000 0.93413 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313131 4 0.7717 -0.02476 0.344 0.000 0.232 0.424
#> SRR1313134 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313135 1 0.4428 0.87695 0.720 0.000 0.276 0.004
#> SRR1313136 1 0.4134 0.88384 0.740 0.000 0.260 0.000
#> SRR1313137 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313138 1 0.5550 0.87096 0.692 0.000 0.248 0.060
#> SRR1313140 1 0.6412 0.38095 0.592 0.000 0.088 0.320
#> SRR1313141 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313139 1 0.6805 0.54829 0.592 0.000 0.148 0.260
#> SRR1313143 1 0.5392 0.83146 0.724 0.000 0.204 0.072
#> SRR1313142 1 0.3726 0.88860 0.788 0.000 0.212 0.000
#> SRR1313144 1 0.5693 0.86843 0.688 0.000 0.240 0.072
#> SRR1313145 1 0.3764 0.88973 0.784 0.000 0.216 0.000
#> SRR1313146 1 0.4283 0.88501 0.740 0.000 0.256 0.004
#> SRR1313147 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313150 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313149 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313152 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313151 1 0.3801 0.88954 0.780 0.000 0.220 0.000
#> SRR1313154 1 0.3688 0.88692 0.792 0.000 0.208 0.000
#> SRR1313153 1 0.3726 0.88860 0.788 0.000 0.212 0.000
#> SRR1313156 1 0.3801 0.89000 0.780 0.000 0.220 0.000
#> SRR1313155 1 0.4372 0.88067 0.728 0.000 0.268 0.004
#> SRR1313157 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313158 1 0.3764 0.88973 0.784 0.000 0.216 0.000
#> SRR1313161 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313159 1 0.3764 0.88975 0.784 0.000 0.216 0.000
#> SRR1313160 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313162 3 0.1109 0.92236 0.028 0.000 0.968 0.004
#> SRR1313163 1 0.4993 0.87760 0.712 0.000 0.260 0.028
#> SRR1313165 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313166 1 0.3688 0.88692 0.792 0.000 0.208 0.000
#> SRR1313164 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313167 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313168 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313170 3 0.0188 0.93374 0.000 0.000 0.996 0.004
#> SRR1313169 1 0.5723 0.86665 0.684 0.000 0.244 0.072
#> SRR1313172 1 0.8066 0.39323 0.448 0.328 0.208 0.016
#> SRR1313171 1 0.3649 0.88541 0.796 0.000 0.204 0.000
#> SRR1313174 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313173 4 0.7681 -0.00922 0.344 0.000 0.224 0.432
#> SRR1313176 2 0.0376 0.92292 0.004 0.992 0.000 0.004
#> SRR1313175 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313178 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313177 2 0.0779 0.92025 0.016 0.980 0.000 0.004
#> SRR1313179 2 0.6263 0.56465 0.272 0.656 0.028 0.044
#> SRR1313180 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313181 2 0.0524 0.92231 0.008 0.988 0.000 0.004
#> SRR1313183 2 0.0779 0.92025 0.016 0.980 0.000 0.004
#> SRR1313182 2 0.3123 0.89921 0.156 0.844 0.000 0.000
#> SRR1313184 2 0.2742 0.89821 0.032 0.916 0.024 0.028
#> SRR1313185 2 0.1022 0.92274 0.032 0.968 0.000 0.000
#> SRR1313188 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313187 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313186 2 0.1474 0.92165 0.052 0.948 0.000 0.000
#> SRR1313189 2 0.0779 0.92025 0.016 0.980 0.000 0.004
#> SRR1313190 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313191 2 0.2868 0.90468 0.136 0.864 0.000 0.000
#> SRR1313192 2 0.0000 0.92341 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0188 0.92368 0.004 0.996 0.000 0.000
#> SRR1313194 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313195 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313196 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313197 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313198 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313199 2 0.0524 0.92231 0.008 0.988 0.000 0.004
#> SRR1313200 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313201 2 0.0336 0.92294 0.008 0.992 0.000 0.000
#> SRR1313202 2 0.2565 0.90788 0.056 0.912 0.032 0.000
#> SRR1313203 4 0.5352 0.64959 0.168 0.000 0.092 0.740
#> SRR1313204 2 0.0524 0.92231 0.008 0.988 0.000 0.004
#> SRR1313205 2 0.0000 0.92341 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313208 2 0.0336 0.92294 0.008 0.992 0.000 0.000
#> SRR1313206 2 0.0000 0.92341 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313209 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313211 2 0.1118 0.92243 0.036 0.964 0.000 0.000
#> SRR1313212 2 0.0657 0.92162 0.012 0.984 0.000 0.004
#> SRR1313214 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313215 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313213 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313216 2 0.4413 0.80840 0.032 0.828 0.112 0.028
#> SRR1313217 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313219 2 0.3528 0.89018 0.192 0.808 0.000 0.000
#> SRR1313220 2 0.0336 0.92294 0.008 0.992 0.000 0.000
#> SRR1313218 2 0.1792 0.91947 0.068 0.932 0.000 0.000
#> SRR1313222 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313221 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313223 2 0.0657 0.92143 0.012 0.984 0.000 0.004
#> SRR1313224 2 0.2216 0.91664 0.092 0.908 0.000 0.000
#> SRR1313225 2 0.1557 0.92136 0.056 0.944 0.000 0.000
#> SRR1313226 3 0.5678 0.46983 0.044 0.316 0.640 0.000
#> SRR1313227 2 0.0376 0.92292 0.004 0.992 0.000 0.004
#> SRR1313228 2 0.0376 0.92292 0.004 0.992 0.000 0.004
#> SRR1313229 2 0.0657 0.92143 0.012 0.984 0.000 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0566 0.86731 0.000 0.000 0.012 0.984 0.004
#> SRR1313063 4 0.0566 0.86818 0.000 0.000 0.012 0.984 0.004
#> SRR1313064 4 0.0404 0.87021 0.012 0.000 0.000 0.988 0.000
#> SRR1313065 4 0.4519 0.67335 0.228 0.000 0.052 0.720 0.000
#> SRR1313066 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313067 4 0.3950 0.75779 0.068 0.000 0.112 0.812 0.008
#> SRR1313068 4 0.1831 0.83901 0.000 0.000 0.076 0.920 0.004
#> SRR1313069 4 0.3109 0.74118 0.200 0.000 0.000 0.800 0.000
#> SRR1313070 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313071 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313072 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313073 4 0.0162 0.86990 0.004 0.000 0.000 0.996 0.000
#> SRR1313074 4 0.3109 0.74118 0.200 0.000 0.000 0.800 0.000
#> SRR1313075 4 0.0290 0.87046 0.008 0.000 0.000 0.992 0.000
#> SRR1313076 4 0.2953 0.80386 0.028 0.000 0.100 0.868 0.004
#> SRR1313077 4 0.4863 0.66346 0.136 0.000 0.116 0.740 0.008
#> SRR1313078 4 0.6381 0.45742 0.260 0.000 0.136 0.580 0.024
#> SRR1313079 4 0.0290 0.87046 0.008 0.000 0.000 0.992 0.000
#> SRR1313080 4 0.0865 0.86550 0.000 0.000 0.024 0.972 0.004
#> SRR1313081 4 0.4519 0.69899 0.120 0.000 0.112 0.764 0.004
#> SRR1313082 4 0.3897 0.72254 0.204 0.000 0.028 0.768 0.000
#> SRR1313083 4 0.4800 0.66236 0.196 0.000 0.088 0.716 0.000
#> SRR1313084 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313085 4 0.0290 0.86867 0.000 0.000 0.000 0.992 0.008
#> SRR1313086 4 0.3496 0.73662 0.200 0.000 0.012 0.788 0.000
#> SRR1313087 4 0.0290 0.87046 0.008 0.000 0.000 0.992 0.000
#> SRR1313088 4 0.0992 0.86672 0.008 0.000 0.024 0.968 0.000
#> SRR1313089 4 0.0404 0.87018 0.012 0.000 0.000 0.988 0.000
#> SRR1313092 3 0.2930 0.81458 0.164 0.000 0.832 0.000 0.004
#> SRR1313090 3 0.0162 0.84194 0.004 0.000 0.996 0.000 0.000
#> SRR1313091 3 0.7197 0.30181 0.136 0.056 0.456 0.000 0.352
#> SRR1313093 3 0.4122 0.73389 0.304 0.000 0.688 0.004 0.004
#> SRR1313095 3 0.3365 0.80307 0.180 0.000 0.808 0.008 0.004
#> SRR1313096 3 0.5411 0.67492 0.304 0.000 0.624 0.064 0.008
#> SRR1313094 3 0.3093 0.81350 0.168 0.000 0.824 0.000 0.008
#> SRR1313097 3 0.0162 0.84323 0.000 0.000 0.996 0.000 0.004
#> SRR1313099 3 0.3621 0.80296 0.192 0.000 0.788 0.000 0.020
#> SRR1313098 3 0.3266 0.78809 0.200 0.000 0.796 0.000 0.004
#> SRR1313101 3 0.0324 0.84187 0.004 0.000 0.992 0.000 0.004
#> SRR1313102 3 0.0865 0.84569 0.024 0.000 0.972 0.000 0.004
#> SRR1313103 3 0.2439 0.83389 0.120 0.000 0.876 0.000 0.004
#> SRR1313100 3 0.3262 0.81912 0.124 0.000 0.840 0.036 0.000
#> SRR1313105 3 0.0162 0.84323 0.000 0.000 0.996 0.000 0.004
#> SRR1313104 3 0.0162 0.84301 0.000 0.000 0.996 0.000 0.004
#> SRR1313107 3 0.3527 0.80414 0.192 0.000 0.792 0.000 0.016
#> SRR1313106 3 0.0162 0.84323 0.000 0.000 0.996 0.000 0.004
#> SRR1313109 3 0.5472 0.60406 0.108 0.000 0.632 0.000 0.260
#> SRR1313108 3 0.6066 0.60541 0.304 0.000 0.568 0.120 0.008
#> SRR1313111 3 0.0451 0.84436 0.008 0.000 0.988 0.000 0.004
#> SRR1313110 3 0.1908 0.83892 0.092 0.000 0.908 0.000 0.000
#> SRR1313112 3 0.0324 0.84187 0.004 0.000 0.992 0.000 0.004
#> SRR1313113 3 0.0162 0.84323 0.000 0.000 0.996 0.000 0.004
#> SRR1313115 3 0.4122 0.73389 0.304 0.000 0.688 0.004 0.004
#> SRR1313114 3 0.1792 0.84123 0.084 0.000 0.916 0.000 0.000
#> SRR1313117 3 0.0324 0.84187 0.004 0.000 0.992 0.000 0.004
#> SRR1313118 3 0.1041 0.84493 0.032 0.000 0.964 0.000 0.004
#> SRR1313116 3 0.0451 0.84412 0.004 0.000 0.988 0.000 0.008
#> SRR1313120 3 0.3123 0.81149 0.184 0.000 0.812 0.000 0.004
#> SRR1313119 3 0.0324 0.84187 0.004 0.000 0.992 0.000 0.004
#> SRR1313122 3 0.3688 0.81194 0.148 0.000 0.812 0.036 0.004
#> SRR1313124 3 0.0162 0.84323 0.000 0.000 0.996 0.000 0.004
#> SRR1313121 3 0.0162 0.84194 0.004 0.000 0.996 0.000 0.000
#> SRR1313125 3 0.0290 0.84266 0.000 0.000 0.992 0.000 0.008
#> SRR1313127 3 0.3300 0.78424 0.204 0.000 0.792 0.000 0.004
#> SRR1313123 3 0.3461 0.76269 0.224 0.000 0.772 0.000 0.004
#> SRR1313128 1 0.0693 0.81574 0.980 0.000 0.008 0.000 0.012
#> SRR1313126 3 0.4656 0.75335 0.180 0.000 0.740 0.076 0.004
#> SRR1313130 3 0.6976 0.35269 0.088 0.076 0.500 0.000 0.336
#> SRR1313132 1 0.2389 0.85451 0.880 0.000 0.116 0.000 0.004
#> SRR1313129 3 0.2653 0.83416 0.096 0.000 0.880 0.000 0.024
#> SRR1313133 1 0.0807 0.81703 0.976 0.000 0.012 0.000 0.012
#> SRR1313131 1 0.5404 0.00582 0.520 0.000 0.024 0.436 0.020
#> SRR1313134 1 0.1799 0.80347 0.940 0.000 0.012 0.028 0.020
#> SRR1313135 1 0.2439 0.85953 0.876 0.000 0.120 0.000 0.004
#> SRR1313136 1 0.2074 0.86306 0.896 0.000 0.104 0.000 0.000
#> SRR1313137 1 0.2953 0.85521 0.844 0.000 0.144 0.012 0.000
#> SRR1313138 1 0.3163 0.85078 0.824 0.000 0.164 0.012 0.000
#> SRR1313140 1 0.5312 0.59500 0.648 0.000 0.096 0.256 0.000
#> SRR1313141 1 0.3360 0.65696 0.816 0.000 0.004 0.168 0.012
#> SRR1313139 1 0.5210 0.66561 0.680 0.000 0.120 0.200 0.000
#> SRR1313143 1 0.4512 0.42868 0.676 0.000 0.004 0.300 0.020
#> SRR1313142 1 0.1671 0.85922 0.924 0.000 0.076 0.000 0.000
#> SRR1313144 1 0.2771 0.86080 0.860 0.000 0.128 0.012 0.000
#> SRR1313145 1 0.1965 0.86103 0.904 0.000 0.096 0.000 0.000
#> SRR1313146 1 0.2583 0.85468 0.864 0.000 0.132 0.000 0.004
#> SRR1313147 1 0.2997 0.85466 0.840 0.000 0.148 0.012 0.000
#> SRR1313150 1 0.2997 0.85466 0.840 0.000 0.148 0.012 0.000
#> SRR1313149 1 0.3846 0.60948 0.776 0.000 0.004 0.200 0.020
#> SRR1313152 1 0.2909 0.85731 0.848 0.000 0.140 0.012 0.000
#> SRR1313151 1 0.2286 0.86167 0.888 0.000 0.108 0.000 0.004
#> SRR1313154 1 0.1041 0.84066 0.964 0.000 0.032 0.000 0.004
#> SRR1313153 1 0.1851 0.86219 0.912 0.000 0.088 0.000 0.000
#> SRR1313156 1 0.2338 0.85590 0.884 0.000 0.112 0.000 0.004
#> SRR1313155 1 0.2286 0.86167 0.888 0.000 0.108 0.000 0.004
#> SRR1313157 1 0.3039 0.85273 0.836 0.000 0.152 0.012 0.000
#> SRR1313158 1 0.2286 0.85687 0.888 0.000 0.108 0.000 0.004
#> SRR1313161 1 0.3039 0.85335 0.836 0.000 0.152 0.012 0.000
#> SRR1313159 1 0.2389 0.85367 0.880 0.004 0.116 0.000 0.000
#> SRR1313160 1 0.3039 0.85335 0.836 0.000 0.152 0.012 0.000
#> SRR1313162 3 0.4457 0.74990 0.208 0.000 0.740 0.048 0.004
#> SRR1313163 1 0.2773 0.84888 0.836 0.000 0.164 0.000 0.000
#> SRR1313165 1 0.3039 0.85335 0.836 0.000 0.152 0.012 0.000
#> SRR1313166 1 0.1205 0.84166 0.956 0.000 0.040 0.000 0.004
#> SRR1313164 1 0.1485 0.83146 0.948 0.000 0.032 0.000 0.020
#> SRR1313167 1 0.2818 0.86022 0.856 0.000 0.132 0.012 0.000
#> SRR1313168 1 0.2818 0.86022 0.856 0.000 0.132 0.012 0.000
#> SRR1313170 3 0.2843 0.83279 0.076 0.000 0.876 0.000 0.048
#> SRR1313169 1 0.2818 0.86033 0.856 0.000 0.132 0.012 0.000
#> SRR1313172 1 0.7229 0.43632 0.552 0.180 0.036 0.020 0.212
#> SRR1313171 1 0.2002 0.80882 0.932 0.000 0.020 0.028 0.020
#> SRR1313174 5 0.3242 0.75780 0.000 0.216 0.000 0.000 0.784
#> SRR1313173 1 0.5249 -0.05282 0.508 0.000 0.012 0.456 0.024
#> SRR1313176 2 0.3274 0.75901 0.000 0.780 0.000 0.000 0.220
#> SRR1313175 5 0.2377 0.80947 0.000 0.128 0.000 0.000 0.872
#> SRR1313178 2 0.2732 0.76965 0.000 0.840 0.000 0.000 0.160
#> SRR1313177 2 0.0000 0.68041 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.6734 0.12696 0.276 0.500 0.012 0.000 0.212
#> SRR1313180 5 0.1106 0.78020 0.000 0.024 0.012 0.000 0.964
#> SRR1313181 2 0.2773 0.77062 0.000 0.836 0.000 0.000 0.164
#> SRR1313183 2 0.0000 0.68041 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 5 0.3816 0.61832 0.000 0.304 0.000 0.000 0.696
#> SRR1313184 2 0.6495 0.26157 0.148 0.464 0.008 0.000 0.380
#> SRR1313185 2 0.4300 0.21545 0.000 0.524 0.000 0.000 0.476
#> SRR1313188 5 0.1282 0.79824 0.000 0.044 0.004 0.000 0.952
#> SRR1313187 5 0.1041 0.78961 0.000 0.032 0.004 0.000 0.964
#> SRR1313186 5 0.4302 -0.10183 0.000 0.480 0.000 0.000 0.520
#> SRR1313189 2 0.0609 0.69074 0.000 0.980 0.000 0.000 0.020
#> SRR1313190 2 0.0000 0.68041 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 5 0.3913 0.57125 0.000 0.324 0.000 0.000 0.676
#> SRR1313192 2 0.3366 0.75438 0.000 0.768 0.000 0.000 0.232
#> SRR1313193 2 0.3895 0.64765 0.000 0.680 0.000 0.000 0.320
#> SRR1313194 5 0.1205 0.79633 0.000 0.040 0.004 0.000 0.956
#> SRR1313195 5 0.1124 0.79355 0.000 0.036 0.004 0.000 0.960
#> SRR1313196 5 0.1124 0.79355 0.000 0.036 0.004 0.000 0.960
#> SRR1313197 5 0.2891 0.79789 0.000 0.176 0.000 0.000 0.824
#> SRR1313198 5 0.2852 0.80033 0.000 0.172 0.000 0.000 0.828
#> SRR1313199 2 0.3242 0.76082 0.000 0.784 0.000 0.000 0.216
#> SRR1313200 5 0.1121 0.79827 0.000 0.044 0.000 0.000 0.956
#> SRR1313201 2 0.3039 0.76907 0.000 0.808 0.000 0.000 0.192
#> SRR1313202 5 0.5216 0.10673 0.032 0.360 0.012 0.000 0.596
#> SRR1313203 4 0.6720 0.51323 0.276 0.160 0.004 0.540 0.020
#> SRR1313204 2 0.3003 0.77084 0.000 0.812 0.000 0.000 0.188
#> SRR1313205 2 0.3424 0.75094 0.000 0.760 0.000 0.000 0.240
#> SRR1313207 2 0.2561 0.76530 0.000 0.856 0.000 0.000 0.144
#> SRR1313208 2 0.3586 0.71854 0.000 0.736 0.000 0.000 0.264
#> SRR1313206 2 0.3336 0.75827 0.000 0.772 0.000 0.000 0.228
#> SRR1313210 5 0.2648 0.80762 0.000 0.152 0.000 0.000 0.848
#> SRR1313209 5 0.2891 0.79789 0.000 0.176 0.000 0.000 0.824
#> SRR1313211 2 0.4219 0.46075 0.000 0.584 0.000 0.000 0.416
#> SRR1313212 2 0.3242 0.76031 0.000 0.784 0.000 0.000 0.216
#> SRR1313214 5 0.3143 0.76901 0.000 0.204 0.000 0.000 0.796
#> SRR1313215 5 0.2891 0.79789 0.000 0.176 0.000 0.000 0.824
#> SRR1313213 2 0.0000 0.68041 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 2 0.7228 0.20181 0.080 0.416 0.100 0.000 0.404
#> SRR1313217 5 0.1121 0.79827 0.000 0.044 0.000 0.000 0.956
#> SRR1313219 5 0.2773 0.80414 0.000 0.164 0.000 0.000 0.836
#> SRR1313220 2 0.3074 0.76840 0.000 0.804 0.000 0.000 0.196
#> SRR1313218 2 0.4182 0.50700 0.000 0.600 0.000 0.000 0.400
#> SRR1313222 2 0.0963 0.70589 0.000 0.964 0.000 0.000 0.036
#> SRR1313221 2 0.2773 0.77057 0.000 0.836 0.000 0.000 0.164
#> SRR1313223 2 0.0000 0.68041 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.4287 0.33474 0.000 0.540 0.000 0.000 0.460
#> SRR1313225 2 0.3932 0.63165 0.000 0.672 0.000 0.000 0.328
#> SRR1313226 3 0.6315 0.34184 0.084 0.024 0.472 0.000 0.420
#> SRR1313227 2 0.3274 0.75901 0.000 0.780 0.000 0.000 0.220
#> SRR1313228 2 0.3274 0.75901 0.000 0.780 0.000 0.000 0.220
#> SRR1313229 2 0.3039 0.76899 0.000 0.808 0.000 0.000 0.192
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.4250 0.3514 0.016 0.000 0.000 0.528 0.000 0.456
#> SRR1313063 4 0.3804 0.4184 0.000 0.000 0.000 0.576 0.000 0.424
#> SRR1313064 4 0.1007 0.7584 0.000 0.000 0.000 0.956 0.000 0.044
#> SRR1313065 4 0.3448 0.4619 0.280 0.000 0.000 0.716 0.000 0.004
#> SRR1313066 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313067 6 0.5439 0.2670 0.072 0.000 0.032 0.308 0.000 0.588
#> SRR1313068 4 0.4990 0.2763 0.068 0.000 0.000 0.480 0.000 0.452
#> SRR1313069 4 0.1082 0.7513 0.040 0.000 0.000 0.956 0.000 0.004
#> SRR1313070 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313071 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313072 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313073 4 0.3175 0.6110 0.000 0.000 0.000 0.744 0.000 0.256
#> SRR1313074 4 0.0363 0.7647 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1313075 4 0.0146 0.7653 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313076 4 0.5120 0.2478 0.068 0.000 0.004 0.468 0.000 0.460
#> SRR1313077 6 0.5406 0.3621 0.088 0.000 0.028 0.272 0.000 0.612
#> SRR1313078 6 0.5361 0.5237 0.096 0.000 0.092 0.124 0.000 0.688
#> SRR1313079 4 0.1075 0.7570 0.000 0.000 0.000 0.952 0.000 0.048
#> SRR1313080 4 0.3975 0.3766 0.004 0.000 0.000 0.544 0.000 0.452
#> SRR1313081 6 0.5429 0.3791 0.068 0.000 0.044 0.272 0.000 0.616
#> SRR1313082 4 0.2146 0.6820 0.116 0.000 0.000 0.880 0.000 0.004
#> SRR1313083 4 0.2020 0.7130 0.096 0.000 0.000 0.896 0.000 0.008
#> SRR1313084 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313085 4 0.0713 0.7643 0.000 0.000 0.000 0.972 0.000 0.028
#> SRR1313086 4 0.0508 0.7639 0.012 0.000 0.000 0.984 0.000 0.004
#> SRR1313087 4 0.2048 0.7210 0.000 0.000 0.000 0.880 0.000 0.120
#> SRR1313088 4 0.0405 0.7660 0.004 0.000 0.000 0.988 0.000 0.008
#> SRR1313089 4 0.0146 0.7653 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313092 3 0.3842 0.6483 0.076 0.000 0.768 0.000 0.000 0.156
#> SRR1313090 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313091 3 0.8213 0.1061 0.048 0.184 0.360 0.000 0.224 0.184
#> SRR1313093 3 0.4868 0.5052 0.076 0.000 0.592 0.000 0.000 0.332
#> SRR1313095 3 0.4617 0.5233 0.084 0.000 0.664 0.000 0.000 0.252
#> SRR1313096 6 0.5203 -0.2938 0.076 0.000 0.456 0.004 0.000 0.464
#> SRR1313094 3 0.3683 0.6497 0.048 0.000 0.768 0.000 0.000 0.184
#> SRR1313097 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313099 3 0.4668 0.5831 0.064 0.000 0.620 0.000 0.000 0.316
#> SRR1313098 3 0.4618 0.6123 0.092 0.000 0.672 0.000 0.000 0.236
#> SRR1313101 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313102 3 0.3235 0.7180 0.032 0.000 0.824 0.000 0.008 0.136
#> SRR1313103 3 0.4173 0.6465 0.044 0.000 0.688 0.000 0.000 0.268
#> SRR1313100 3 0.2631 0.6916 0.152 0.000 0.840 0.000 0.000 0.008
#> SRR1313105 3 0.0146 0.7569 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1313104 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 3 0.4895 0.5565 0.068 0.000 0.600 0.000 0.004 0.328
#> SRR1313106 3 0.0146 0.7575 0.004 0.000 0.996 0.000 0.000 0.000
#> SRR1313109 3 0.4808 0.6619 0.040 0.008 0.736 0.000 0.072 0.144
#> SRR1313108 6 0.5110 -0.1198 0.072 0.000 0.396 0.004 0.000 0.528
#> SRR1313111 3 0.2135 0.7300 0.000 0.000 0.872 0.000 0.000 0.128
#> SRR1313110 3 0.1995 0.7512 0.052 0.000 0.912 0.000 0.000 0.036
#> SRR1313112 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313113 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313115 3 0.4900 0.5066 0.080 0.000 0.592 0.000 0.000 0.328
#> SRR1313114 3 0.1500 0.7495 0.052 0.000 0.936 0.000 0.000 0.012
#> SRR1313117 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313118 3 0.0146 0.7575 0.004 0.000 0.996 0.000 0.000 0.000
#> SRR1313116 3 0.0405 0.7574 0.004 0.000 0.988 0.000 0.000 0.008
#> SRR1313120 3 0.4747 0.5684 0.068 0.000 0.608 0.000 0.000 0.324
#> SRR1313119 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313122 3 0.4948 0.3956 0.076 0.000 0.604 0.004 0.000 0.316
#> SRR1313124 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313121 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313125 3 0.0000 0.7568 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313127 3 0.4685 0.6062 0.096 0.000 0.664 0.000 0.000 0.240
#> SRR1313123 3 0.5238 0.5014 0.128 0.000 0.580 0.000 0.000 0.292
#> SRR1313128 1 0.3390 0.7542 0.704 0.000 0.000 0.000 0.000 0.296
#> SRR1313126 3 0.5030 0.4552 0.104 0.000 0.628 0.004 0.000 0.264
#> SRR1313130 3 0.7846 0.2101 0.028 0.180 0.400 0.000 0.236 0.156
#> SRR1313132 1 0.3670 0.7677 0.704 0.000 0.012 0.000 0.000 0.284
#> SRR1313129 3 0.3275 0.7160 0.036 0.000 0.816 0.000 0.004 0.144
#> SRR1313133 1 0.3409 0.7528 0.700 0.000 0.000 0.000 0.000 0.300
#> SRR1313131 6 0.4976 0.3487 0.248 0.000 0.012 0.088 0.000 0.652
#> SRR1313134 1 0.3547 0.7520 0.696 0.000 0.000 0.004 0.000 0.300
#> SRR1313135 1 0.3110 0.7916 0.792 0.000 0.012 0.000 0.000 0.196
#> SRR1313136 1 0.3110 0.7940 0.792 0.000 0.012 0.000 0.000 0.196
#> SRR1313137 1 0.0713 0.7510 0.972 0.000 0.028 0.000 0.000 0.000
#> SRR1313138 1 0.3974 0.7873 0.744 0.000 0.032 0.000 0.012 0.212
#> SRR1313140 1 0.3516 0.5396 0.760 0.000 0.004 0.220 0.000 0.016
#> SRR1313141 1 0.5051 0.6282 0.596 0.000 0.000 0.104 0.000 0.300
#> SRR1313139 1 0.2573 0.6250 0.856 0.000 0.004 0.132 0.000 0.008
#> SRR1313143 4 0.6100 -0.2391 0.312 0.000 0.000 0.384 0.000 0.304
#> SRR1313142 1 0.3109 0.7911 0.772 0.000 0.004 0.000 0.000 0.224
#> SRR1313144 1 0.0858 0.7527 0.968 0.000 0.028 0.000 0.000 0.004
#> SRR1313145 1 0.3189 0.7883 0.760 0.000 0.004 0.000 0.000 0.236
#> SRR1313146 1 0.3586 0.7828 0.756 0.000 0.028 0.000 0.000 0.216
#> SRR1313147 1 0.1053 0.7390 0.964 0.000 0.012 0.020 0.000 0.004
#> SRR1313150 1 0.0935 0.7470 0.964 0.000 0.032 0.000 0.000 0.004
#> SRR1313149 1 0.6037 0.2579 0.420 0.000 0.000 0.276 0.000 0.304
#> SRR1313152 1 0.0713 0.7510 0.972 0.000 0.028 0.000 0.000 0.000
#> SRR1313151 1 0.3141 0.7937 0.788 0.000 0.012 0.000 0.000 0.200
#> SRR1313154 1 0.3163 0.7900 0.764 0.000 0.004 0.000 0.000 0.232
#> SRR1313153 1 0.3163 0.7899 0.764 0.000 0.004 0.000 0.000 0.232
#> SRR1313156 1 0.3855 0.7795 0.704 0.000 0.024 0.000 0.000 0.272
#> SRR1313155 1 0.3014 0.7938 0.804 0.000 0.012 0.000 0.000 0.184
#> SRR1313157 1 0.1116 0.7433 0.960 0.000 0.028 0.008 0.000 0.004
#> SRR1313158 1 0.3494 0.7855 0.736 0.000 0.012 0.000 0.000 0.252
#> SRR1313161 1 0.0935 0.7470 0.964 0.000 0.032 0.000 0.000 0.004
#> SRR1313159 1 0.4160 0.7711 0.684 0.008 0.024 0.000 0.000 0.284
#> SRR1313160 1 0.0935 0.7470 0.964 0.000 0.032 0.000 0.000 0.004
#> SRR1313162 3 0.5030 0.5639 0.108 0.000 0.632 0.004 0.000 0.256
#> SRR1313163 1 0.4111 0.6894 0.740 0.000 0.176 0.000 0.000 0.084
#> SRR1313165 1 0.0935 0.7470 0.964 0.000 0.032 0.000 0.000 0.004
#> SRR1313166 1 0.3330 0.7647 0.716 0.000 0.000 0.000 0.000 0.284
#> SRR1313164 1 0.3409 0.7530 0.700 0.000 0.000 0.000 0.000 0.300
#> SRR1313167 1 0.1116 0.7455 0.960 0.000 0.028 0.004 0.000 0.008
#> SRR1313168 1 0.0713 0.7510 0.972 0.000 0.028 0.000 0.000 0.000
#> SRR1313170 3 0.3658 0.7085 0.048 0.000 0.792 0.000 0.008 0.152
#> SRR1313169 1 0.1168 0.7543 0.956 0.000 0.028 0.000 0.000 0.016
#> SRR1313172 5 0.6889 -0.4096 0.288 0.016 0.008 0.008 0.360 0.320
#> SRR1313171 1 0.3684 0.7538 0.692 0.000 0.004 0.004 0.000 0.300
#> SRR1313174 5 0.4084 0.5323 0.000 0.400 0.000 0.000 0.588 0.012
#> SRR1313173 6 0.4976 0.3487 0.248 0.000 0.012 0.088 0.000 0.652
#> SRR1313176 2 0.1757 0.7071 0.000 0.916 0.000 0.000 0.076 0.008
#> SRR1313175 5 0.2912 0.6623 0.000 0.216 0.000 0.000 0.784 0.000
#> SRR1313178 2 0.0806 0.7131 0.000 0.972 0.000 0.000 0.008 0.020
#> SRR1313177 2 0.3620 0.6131 0.000 0.772 0.000 0.000 0.184 0.044
#> SRR1313179 5 0.7876 -0.1038 0.228 0.236 0.024 0.004 0.388 0.120
#> SRR1313180 5 0.4040 0.5793 0.000 0.104 0.092 0.000 0.784 0.020
#> SRR1313181 2 0.0972 0.7161 0.000 0.964 0.000 0.000 0.028 0.008
#> SRR1313183 2 0.3620 0.6131 0.000 0.772 0.000 0.000 0.184 0.044
#> SRR1313182 5 0.4177 0.3873 0.000 0.468 0.000 0.000 0.520 0.012
#> SRR1313184 2 0.7472 0.1100 0.124 0.392 0.032 0.000 0.348 0.104
#> SRR1313185 2 0.3867 0.2765 0.000 0.660 0.000 0.000 0.328 0.012
#> SRR1313188 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313187 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313186 2 0.3992 0.1971 0.000 0.624 0.000 0.000 0.364 0.012
#> SRR1313189 2 0.3806 0.6181 0.000 0.752 0.000 0.000 0.200 0.048
#> SRR1313190 2 0.3453 0.6271 0.000 0.792 0.000 0.000 0.164 0.044
#> SRR1313191 2 0.4172 -0.2354 0.000 0.528 0.000 0.000 0.460 0.012
#> SRR1313192 2 0.2613 0.6625 0.000 0.848 0.000 0.000 0.140 0.012
#> SRR1313193 2 0.3078 0.6041 0.000 0.796 0.000 0.000 0.192 0.012
#> SRR1313194 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313195 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313196 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313197 5 0.4015 0.5721 0.000 0.372 0.000 0.000 0.616 0.012
#> SRR1313198 5 0.4015 0.5721 0.000 0.372 0.000 0.000 0.616 0.012
#> SRR1313199 2 0.1588 0.7083 0.000 0.924 0.000 0.000 0.072 0.004
#> SRR1313200 5 0.3253 0.6673 0.000 0.192 0.000 0.000 0.788 0.020
#> SRR1313201 2 0.1723 0.7126 0.000 0.928 0.000 0.000 0.036 0.036
#> SRR1313202 2 0.6040 -0.1513 0.020 0.452 0.048 0.000 0.436 0.044
#> SRR1313203 4 0.6696 -0.0434 0.068 0.000 0.004 0.488 0.152 0.288
#> SRR1313204 2 0.1531 0.7100 0.000 0.928 0.000 0.000 0.068 0.004
#> SRR1313205 2 0.2572 0.6680 0.000 0.852 0.000 0.000 0.136 0.012
#> SRR1313207 2 0.2647 0.6715 0.000 0.868 0.000 0.000 0.088 0.044
#> SRR1313208 2 0.2164 0.7033 0.000 0.900 0.000 0.000 0.068 0.032
#> SRR1313206 2 0.2446 0.6768 0.000 0.864 0.000 0.000 0.124 0.012
#> SRR1313210 5 0.3620 0.5960 0.000 0.352 0.000 0.000 0.648 0.000
#> SRR1313209 5 0.4057 0.5466 0.000 0.388 0.000 0.000 0.600 0.012
#> SRR1313211 2 0.3171 0.5905 0.000 0.784 0.000 0.000 0.204 0.012
#> SRR1313212 2 0.2404 0.7040 0.000 0.884 0.000 0.000 0.080 0.036
#> SRR1313214 5 0.4066 0.5395 0.000 0.392 0.000 0.000 0.596 0.012
#> SRR1313215 5 0.3684 0.5784 0.000 0.372 0.000 0.000 0.628 0.000
#> SRR1313213 2 0.3487 0.6245 0.000 0.788 0.000 0.000 0.168 0.044
#> SRR1313216 2 0.7025 0.1384 0.032 0.488 0.044 0.000 0.244 0.192
#> SRR1313217 5 0.3374 0.6657 0.000 0.208 0.000 0.000 0.772 0.020
#> SRR1313219 5 0.3672 0.5828 0.000 0.368 0.000 0.000 0.632 0.000
#> SRR1313220 2 0.1649 0.7130 0.000 0.932 0.000 0.000 0.032 0.036
#> SRR1313218 2 0.3518 0.4958 0.000 0.732 0.000 0.000 0.256 0.012
#> SRR1313222 2 0.3453 0.6315 0.000 0.792 0.000 0.000 0.164 0.044
#> SRR1313221 2 0.1297 0.7103 0.000 0.948 0.000 0.000 0.012 0.040
#> SRR1313223 2 0.3620 0.6131 0.000 0.772 0.000 0.000 0.184 0.044
#> SRR1313224 2 0.3748 0.3850 0.000 0.688 0.000 0.000 0.300 0.012
#> SRR1313225 2 0.2790 0.6594 0.000 0.840 0.000 0.000 0.140 0.020
#> SRR1313226 5 0.4858 0.0928 0.032 0.020 0.364 0.000 0.584 0.000
#> SRR1313227 2 0.1812 0.7055 0.000 0.912 0.000 0.000 0.080 0.008
#> SRR1313228 2 0.1812 0.7055 0.000 0.912 0.000 0.000 0.080 0.008
#> SRR1313229 2 0.1524 0.7115 0.000 0.932 0.000 0.000 0.060 0.008
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "NMF"]
# you can also extract it by
# res = res_list["MAD:NMF"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.878 0.917 0.965 0.4896 0.510 0.510
#> 3 3 0.810 0.831 0.925 0.3566 0.758 0.556
#> 4 4 0.886 0.867 0.933 0.0979 0.842 0.586
#> 5 5 0.746 0.655 0.853 0.0628 0.903 0.671
#> 6 6 0.718 0.705 0.809 0.0485 0.850 0.458
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.960 1.000 0.000
#> SRR1313063 1 0.0000 0.960 1.000 0.000
#> SRR1313064 1 0.0000 0.960 1.000 0.000
#> SRR1313065 1 0.0000 0.960 1.000 0.000
#> SRR1313066 2 0.7139 0.742 0.196 0.804
#> SRR1313067 1 0.0000 0.960 1.000 0.000
#> SRR1313068 1 0.0000 0.960 1.000 0.000
#> SRR1313069 1 0.0000 0.960 1.000 0.000
#> SRR1313070 1 0.0000 0.960 1.000 0.000
#> SRR1313071 1 0.0000 0.960 1.000 0.000
#> SRR1313072 1 0.0000 0.960 1.000 0.000
#> SRR1313073 1 0.0000 0.960 1.000 0.000
#> SRR1313074 1 0.0000 0.960 1.000 0.000
#> SRR1313075 1 0.0000 0.960 1.000 0.000
#> SRR1313076 1 0.0000 0.960 1.000 0.000
#> SRR1313077 1 0.0000 0.960 1.000 0.000
#> SRR1313078 1 0.0000 0.960 1.000 0.000
#> SRR1313079 1 0.0000 0.960 1.000 0.000
#> SRR1313080 1 0.0000 0.960 1.000 0.000
#> SRR1313081 1 0.0000 0.960 1.000 0.000
#> SRR1313082 1 0.0000 0.960 1.000 0.000
#> SRR1313083 1 0.0000 0.960 1.000 0.000
#> SRR1313084 1 0.0938 0.951 0.988 0.012
#> SRR1313085 1 0.0000 0.960 1.000 0.000
#> SRR1313086 1 0.0000 0.960 1.000 0.000
#> SRR1313087 1 0.0000 0.960 1.000 0.000
#> SRR1313088 1 0.0000 0.960 1.000 0.000
#> SRR1313089 1 0.0000 0.960 1.000 0.000
#> SRR1313092 1 0.0000 0.960 1.000 0.000
#> SRR1313090 1 0.0000 0.960 1.000 0.000
#> SRR1313091 2 0.0000 0.965 0.000 1.000
#> SRR1313093 1 0.0000 0.960 1.000 0.000
#> SRR1313095 1 0.0000 0.960 1.000 0.000
#> SRR1313096 1 0.0000 0.960 1.000 0.000
#> SRR1313094 1 0.0000 0.960 1.000 0.000
#> SRR1313097 1 0.6887 0.775 0.816 0.184
#> SRR1313099 2 0.9323 0.456 0.348 0.652
#> SRR1313098 1 0.0000 0.960 1.000 0.000
#> SRR1313101 1 0.9209 0.520 0.664 0.336
#> SRR1313102 1 0.5629 0.839 0.868 0.132
#> SRR1313103 1 0.9170 0.529 0.668 0.332
#> SRR1313100 1 0.0000 0.960 1.000 0.000
#> SRR1313105 1 0.9000 0.562 0.684 0.316
#> SRR1313104 1 0.0000 0.960 1.000 0.000
#> SRR1313107 2 0.8081 0.661 0.248 0.752
#> SRR1313106 2 0.2236 0.934 0.036 0.964
#> SRR1313109 2 0.0672 0.958 0.008 0.992
#> SRR1313108 1 0.0000 0.960 1.000 0.000
#> SRR1313111 1 0.7674 0.720 0.776 0.224
#> SRR1313110 1 0.0000 0.960 1.000 0.000
#> SRR1313112 1 0.8555 0.629 0.720 0.280
#> SRR1313113 1 0.8955 0.570 0.688 0.312
#> SRR1313115 1 0.0000 0.960 1.000 0.000
#> SRR1313114 1 0.0000 0.960 1.000 0.000
#> SRR1313117 1 0.4431 0.880 0.908 0.092
#> SRR1313118 1 0.0000 0.960 1.000 0.000
#> SRR1313116 2 0.9608 0.362 0.384 0.616
#> SRR1313120 1 0.9393 0.475 0.644 0.356
#> SRR1313119 1 0.0000 0.960 1.000 0.000
#> SRR1313122 1 0.0000 0.960 1.000 0.000
#> SRR1313124 1 0.0000 0.960 1.000 0.000
#> SRR1313121 1 0.0000 0.960 1.000 0.000
#> SRR1313125 1 0.0000 0.960 1.000 0.000
#> SRR1313127 1 0.0000 0.960 1.000 0.000
#> SRR1313123 1 0.0000 0.960 1.000 0.000
#> SRR1313128 1 0.0000 0.960 1.000 0.000
#> SRR1313126 1 0.0000 0.960 1.000 0.000
#> SRR1313130 2 0.0000 0.965 0.000 1.000
#> SRR1313132 1 0.6887 0.775 0.816 0.184
#> SRR1313129 2 0.8813 0.563 0.300 0.700
#> SRR1313133 1 0.0000 0.960 1.000 0.000
#> SRR1313131 1 0.0000 0.960 1.000 0.000
#> SRR1313134 1 0.7376 0.743 0.792 0.208
#> SRR1313135 1 0.0000 0.960 1.000 0.000
#> SRR1313136 1 0.0000 0.960 1.000 0.000
#> SRR1313137 1 0.0000 0.960 1.000 0.000
#> SRR1313138 2 0.6712 0.773 0.176 0.824
#> SRR1313140 1 0.0000 0.960 1.000 0.000
#> SRR1313141 1 0.0000 0.960 1.000 0.000
#> SRR1313139 1 0.0000 0.960 1.000 0.000
#> SRR1313143 1 0.0000 0.960 1.000 0.000
#> SRR1313142 1 0.0000 0.960 1.000 0.000
#> SRR1313144 1 0.0000 0.960 1.000 0.000
#> SRR1313145 1 0.0000 0.960 1.000 0.000
#> SRR1313146 1 0.0000 0.960 1.000 0.000
#> SRR1313147 1 0.0000 0.960 1.000 0.000
#> SRR1313150 1 0.0000 0.960 1.000 0.000
#> SRR1313149 1 0.0000 0.960 1.000 0.000
#> SRR1313152 1 0.0000 0.960 1.000 0.000
#> SRR1313151 1 0.0000 0.960 1.000 0.000
#> SRR1313154 1 0.0000 0.960 1.000 0.000
#> SRR1313153 1 0.0000 0.960 1.000 0.000
#> SRR1313156 1 0.9933 0.202 0.548 0.452
#> SRR1313155 1 0.0000 0.960 1.000 0.000
#> SRR1313157 1 0.0000 0.960 1.000 0.000
#> SRR1313158 1 0.0672 0.954 0.992 0.008
#> SRR1313161 1 0.0000 0.960 1.000 0.000
#> SRR1313159 2 0.3114 0.915 0.056 0.944
#> SRR1313160 1 0.0000 0.960 1.000 0.000
#> SRR1313162 1 0.0000 0.960 1.000 0.000
#> SRR1313163 1 0.3879 0.896 0.924 0.076
#> SRR1313165 1 0.0000 0.960 1.000 0.000
#> SRR1313166 1 0.0000 0.960 1.000 0.000
#> SRR1313164 1 0.4161 0.888 0.916 0.084
#> SRR1313167 1 0.0000 0.960 1.000 0.000
#> SRR1313168 1 0.0000 0.960 1.000 0.000
#> SRR1313170 2 0.9909 0.175 0.444 0.556
#> SRR1313169 1 0.0000 0.960 1.000 0.000
#> SRR1313172 2 0.0000 0.965 0.000 1.000
#> SRR1313171 2 0.3879 0.895 0.076 0.924
#> SRR1313174 2 0.0000 0.965 0.000 1.000
#> SRR1313173 1 0.0000 0.960 1.000 0.000
#> SRR1313176 2 0.0000 0.965 0.000 1.000
#> SRR1313175 2 0.0000 0.965 0.000 1.000
#> SRR1313178 2 0.0000 0.965 0.000 1.000
#> SRR1313177 2 0.0000 0.965 0.000 1.000
#> SRR1313179 2 0.0000 0.965 0.000 1.000
#> SRR1313180 2 0.0000 0.965 0.000 1.000
#> SRR1313181 2 0.0000 0.965 0.000 1.000
#> SRR1313183 2 0.0000 0.965 0.000 1.000
#> SRR1313182 2 0.0000 0.965 0.000 1.000
#> SRR1313184 2 0.0000 0.965 0.000 1.000
#> SRR1313185 2 0.0000 0.965 0.000 1.000
#> SRR1313188 2 0.0000 0.965 0.000 1.000
#> SRR1313187 2 0.0000 0.965 0.000 1.000
#> SRR1313186 2 0.0000 0.965 0.000 1.000
#> SRR1313189 2 0.0000 0.965 0.000 1.000
#> SRR1313190 2 0.0000 0.965 0.000 1.000
#> SRR1313191 2 0.0000 0.965 0.000 1.000
#> SRR1313192 2 0.0000 0.965 0.000 1.000
#> SRR1313193 2 0.0000 0.965 0.000 1.000
#> SRR1313194 2 0.0000 0.965 0.000 1.000
#> SRR1313195 2 0.0000 0.965 0.000 1.000
#> SRR1313196 2 0.0000 0.965 0.000 1.000
#> SRR1313197 2 0.0000 0.965 0.000 1.000
#> SRR1313198 2 0.0000 0.965 0.000 1.000
#> SRR1313199 2 0.0000 0.965 0.000 1.000
#> SRR1313200 2 0.0000 0.965 0.000 1.000
#> SRR1313201 2 0.0000 0.965 0.000 1.000
#> SRR1313202 2 0.0000 0.965 0.000 1.000
#> SRR1313203 2 0.0000 0.965 0.000 1.000
#> SRR1313204 2 0.0000 0.965 0.000 1.000
#> SRR1313205 2 0.0000 0.965 0.000 1.000
#> SRR1313207 2 0.0000 0.965 0.000 1.000
#> SRR1313208 2 0.0000 0.965 0.000 1.000
#> SRR1313206 2 0.0000 0.965 0.000 1.000
#> SRR1313210 2 0.0000 0.965 0.000 1.000
#> SRR1313209 2 0.0000 0.965 0.000 1.000
#> SRR1313211 2 0.0000 0.965 0.000 1.000
#> SRR1313212 2 0.0000 0.965 0.000 1.000
#> SRR1313214 2 0.0000 0.965 0.000 1.000
#> SRR1313215 2 0.0000 0.965 0.000 1.000
#> SRR1313213 2 0.0000 0.965 0.000 1.000
#> SRR1313216 2 0.0000 0.965 0.000 1.000
#> SRR1313217 2 0.0000 0.965 0.000 1.000
#> SRR1313219 2 0.0000 0.965 0.000 1.000
#> SRR1313220 2 0.0000 0.965 0.000 1.000
#> SRR1313218 2 0.0000 0.965 0.000 1.000
#> SRR1313222 2 0.0000 0.965 0.000 1.000
#> SRR1313221 2 0.0000 0.965 0.000 1.000
#> SRR1313223 2 0.0000 0.965 0.000 1.000
#> SRR1313224 2 0.0000 0.965 0.000 1.000
#> SRR1313225 2 0.0000 0.965 0.000 1.000
#> SRR1313226 2 0.0000 0.965 0.000 1.000
#> SRR1313227 2 0.0000 0.965 0.000 1.000
#> SRR1313228 2 0.0000 0.965 0.000 1.000
#> SRR1313229 2 0.0000 0.965 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.4291 0.7320 0.820 0.000 0.180
#> SRR1313063 1 0.4555 0.7093 0.800 0.000 0.200
#> SRR1313064 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313067 1 0.5810 0.5249 0.664 0.000 0.336
#> SRR1313068 1 0.6126 0.4095 0.600 0.000 0.400
#> SRR1313069 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313076 1 0.5835 0.5182 0.660 0.000 0.340
#> SRR1313077 1 0.6126 0.4095 0.600 0.000 0.400
#> SRR1313078 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313079 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313080 1 0.5905 0.4983 0.648 0.000 0.352
#> SRR1313081 1 0.6095 0.4254 0.608 0.000 0.392
#> SRR1313082 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313090 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313091 2 0.2796 0.8819 0.000 0.908 0.092
#> SRR1313093 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313099 3 0.2448 0.7951 0.000 0.076 0.924
#> SRR1313098 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313100 3 0.6126 0.1554 0.400 0.000 0.600
#> SRR1313105 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313107 3 0.0424 0.8344 0.000 0.008 0.992
#> SRR1313106 3 0.2625 0.7727 0.000 0.084 0.916
#> SRR1313109 3 0.4974 0.6603 0.000 0.236 0.764
#> SRR1313108 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313110 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313112 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313114 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313117 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313118 3 0.0237 0.8356 0.004 0.000 0.996
#> SRR1313116 3 0.2066 0.8054 0.000 0.060 0.940
#> SRR1313120 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313119 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313122 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313121 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313125 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313128 3 0.5968 0.5334 0.364 0.000 0.636
#> SRR1313126 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313130 2 0.0424 0.9802 0.000 0.992 0.008
#> SRR1313132 3 0.6264 0.7064 0.168 0.068 0.764
#> SRR1313129 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313133 3 0.5178 0.6614 0.256 0.000 0.744
#> SRR1313131 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313134 3 0.7918 0.6136 0.204 0.136 0.660
#> SRR1313135 1 0.4399 0.6643 0.812 0.000 0.188
#> SRR1313136 3 0.6295 0.3166 0.472 0.000 0.528
#> SRR1313137 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313138 2 0.4346 0.7535 0.184 0.816 0.000
#> SRR1313140 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313141 3 0.6062 0.5048 0.384 0.000 0.616
#> SRR1313139 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313143 3 0.6126 0.4783 0.400 0.000 0.600
#> SRR1313142 3 0.6111 0.4855 0.396 0.000 0.604
#> SRR1313144 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313145 3 0.6126 0.4783 0.400 0.000 0.600
#> SRR1313146 3 0.6295 0.3166 0.472 0.000 0.528
#> SRR1313147 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313149 3 0.6079 0.4986 0.388 0.000 0.612
#> SRR1313152 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313151 1 0.6140 0.0936 0.596 0.000 0.404
#> SRR1313154 3 0.6267 0.3680 0.452 0.000 0.548
#> SRR1313153 3 0.6235 0.4050 0.436 0.000 0.564
#> SRR1313156 3 0.7600 0.4777 0.056 0.344 0.600
#> SRR1313155 1 0.5363 0.4843 0.724 0.000 0.276
#> SRR1313157 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313158 3 0.6111 0.4855 0.396 0.000 0.604
#> SRR1313161 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313159 2 0.5859 0.4085 0.000 0.656 0.344
#> SRR1313160 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313162 3 0.4504 0.7153 0.196 0.000 0.804
#> SRR1313163 3 0.6111 0.4855 0.396 0.000 0.604
#> SRR1313165 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313166 3 0.6026 0.5166 0.376 0.000 0.624
#> SRR1313164 3 0.5178 0.6614 0.256 0.000 0.744
#> SRR1313167 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313170 3 0.3686 0.7473 0.000 0.140 0.860
#> SRR1313169 1 0.0000 0.8999 1.000 0.000 0.000
#> SRR1313172 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313171 3 0.5988 0.4582 0.000 0.368 0.632
#> SRR1313174 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.8381 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313203 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313204 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313226 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9884 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9884 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.4277 0.583 0.000 0.000 0.280 0.720
#> SRR1313063 4 0.4008 0.652 0.000 0.000 0.244 0.756
#> SRR1313064 4 0.0921 0.886 0.028 0.000 0.000 0.972
#> SRR1313065 4 0.1716 0.899 0.064 0.000 0.000 0.936
#> SRR1313066 4 0.0592 0.879 0.016 0.000 0.000 0.984
#> SRR1313067 3 0.0817 0.913 0.000 0.000 0.976 0.024
#> SRR1313068 3 0.1716 0.883 0.000 0.000 0.936 0.064
#> SRR1313069 4 0.1792 0.899 0.068 0.000 0.000 0.932
#> SRR1313070 4 0.1637 0.899 0.060 0.000 0.000 0.940
#> SRR1313071 4 0.1716 0.899 0.064 0.000 0.000 0.936
#> SRR1313072 4 0.1389 0.896 0.048 0.000 0.000 0.952
#> SRR1313073 4 0.1792 0.899 0.068 0.000 0.000 0.932
#> SRR1313074 4 0.1557 0.898 0.056 0.000 0.000 0.944
#> SRR1313075 4 0.1389 0.895 0.048 0.000 0.000 0.952
#> SRR1313076 3 0.2081 0.869 0.000 0.000 0.916 0.084
#> SRR1313077 3 0.0469 0.921 0.000 0.000 0.988 0.012
#> SRR1313078 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313079 4 0.0592 0.879 0.016 0.000 0.000 0.984
#> SRR1313080 3 0.4040 0.641 0.000 0.000 0.752 0.248
#> SRR1313081 3 0.0336 0.923 0.000 0.000 0.992 0.008
#> SRR1313082 4 0.1792 0.899 0.068 0.000 0.000 0.932
#> SRR1313083 4 0.1792 0.899 0.068 0.000 0.000 0.932
#> SRR1313084 4 0.0817 0.884 0.024 0.000 0.000 0.976
#> SRR1313085 4 0.1792 0.899 0.068 0.000 0.000 0.932
#> SRR1313086 4 0.1940 0.897 0.076 0.000 0.000 0.924
#> SRR1313087 4 0.1118 0.890 0.036 0.000 0.000 0.964
#> SRR1313088 4 0.1940 0.897 0.076 0.000 0.000 0.924
#> SRR1313089 4 0.0336 0.872 0.008 0.000 0.000 0.992
#> SRR1313092 3 0.1389 0.903 0.048 0.000 0.952 0.000
#> SRR1313090 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313091 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313093 1 0.3610 0.753 0.800 0.000 0.200 0.000
#> SRR1313095 3 0.1302 0.904 0.044 0.000 0.956 0.000
#> SRR1313096 1 0.2408 0.845 0.896 0.000 0.104 0.000
#> SRR1313094 3 0.0336 0.924 0.008 0.000 0.992 0.000
#> SRR1313097 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313099 1 0.6027 0.633 0.684 0.124 0.192 0.000
#> SRR1313098 1 0.2469 0.842 0.892 0.000 0.108 0.000
#> SRR1313101 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.5119 0.119 0.440 0.004 0.556 0.000
#> SRR1313103 1 0.2859 0.836 0.880 0.008 0.112 0.000
#> SRR1313100 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313105 3 0.0188 0.925 0.004 0.000 0.996 0.000
#> SRR1313104 3 0.1792 0.886 0.068 0.000 0.932 0.000
#> SRR1313107 1 0.3606 0.805 0.840 0.020 0.140 0.000
#> SRR1313106 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313109 2 0.6396 0.259 0.360 0.564 0.076 0.000
#> SRR1313108 3 0.4382 0.531 0.296 0.000 0.704 0.000
#> SRR1313111 1 0.4877 0.370 0.592 0.000 0.408 0.000
#> SRR1313110 3 0.1637 0.893 0.060 0.000 0.940 0.000
#> SRR1313112 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313115 1 0.2589 0.835 0.884 0.000 0.116 0.000
#> SRR1313114 1 0.4972 0.231 0.544 0.000 0.456 0.000
#> SRR1313117 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.2589 0.835 0.116 0.000 0.884 0.000
#> SRR1313116 3 0.1510 0.900 0.000 0.016 0.956 0.028
#> SRR1313120 1 0.4382 0.617 0.704 0.000 0.296 0.000
#> SRR1313119 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.4477 0.507 0.312 0.000 0.688 0.000
#> SRR1313127 1 0.2081 0.856 0.916 0.000 0.084 0.000
#> SRR1313123 1 0.1978 0.863 0.928 0.004 0.068 0.000
#> SRR1313128 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.0000 0.927 0.000 0.000 1.000 0.000
#> SRR1313130 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313132 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313129 1 0.6275 0.121 0.484 0.056 0.460 0.000
#> SRR1313133 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313131 1 0.2216 0.851 0.908 0.000 0.092 0.000
#> SRR1313134 1 0.0188 0.885 0.996 0.004 0.000 0.000
#> SRR1313135 1 0.0336 0.883 0.992 0.000 0.000 0.008
#> SRR1313136 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313137 1 0.0707 0.874 0.980 0.000 0.000 0.020
#> SRR1313138 1 0.0188 0.885 0.996 0.004 0.000 0.000
#> SRR1313140 4 0.3486 0.823 0.188 0.000 0.000 0.812
#> SRR1313141 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313139 4 0.2814 0.870 0.132 0.000 0.000 0.868
#> SRR1313143 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313142 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313144 1 0.0469 0.880 0.988 0.000 0.000 0.012
#> SRR1313145 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0188 0.885 0.996 0.000 0.000 0.004
#> SRR1313147 4 0.4661 0.599 0.348 0.000 0.000 0.652
#> SRR1313150 4 0.3356 0.835 0.176 0.000 0.000 0.824
#> SRR1313149 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313152 1 0.0707 0.874 0.980 0.000 0.000 0.020
#> SRR1313151 1 0.0336 0.883 0.992 0.000 0.000 0.008
#> SRR1313154 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313156 1 0.0592 0.880 0.984 0.016 0.000 0.000
#> SRR1313155 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313157 4 0.4134 0.742 0.260 0.000 0.000 0.740
#> SRR1313158 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313161 4 0.5000 0.219 0.500 0.000 0.000 0.500
#> SRR1313159 1 0.1940 0.841 0.924 0.076 0.000 0.000
#> SRR1313160 1 0.4454 0.407 0.692 0.000 0.000 0.308
#> SRR1313162 1 0.1022 0.878 0.968 0.000 0.032 0.000
#> SRR1313163 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313165 1 0.4830 0.142 0.608 0.000 0.000 0.392
#> SRR1313166 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.886 1.000 0.000 0.000 0.000
#> SRR1313167 4 0.2530 0.882 0.112 0.000 0.000 0.888
#> SRR1313168 1 0.0336 0.882 0.992 0.000 0.000 0.008
#> SRR1313170 1 0.6620 0.539 0.628 0.192 0.180 0.000
#> SRR1313169 4 0.4998 0.262 0.488 0.000 0.000 0.512
#> SRR1313172 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313171 1 0.1867 0.844 0.928 0.072 0.000 0.000
#> SRR1313174 2 0.0921 0.971 0.000 0.972 0.000 0.028
#> SRR1313173 1 0.2469 0.841 0.892 0.000 0.108 0.000
#> SRR1313176 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0707 0.975 0.000 0.980 0.000 0.020
#> SRR1313178 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.1792 0.943 0.000 0.932 0.000 0.068
#> SRR1313181 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0336 0.980 0.000 0.992 0.000 0.008
#> SRR1313188 2 0.1716 0.946 0.000 0.936 0.000 0.064
#> SRR1313187 2 0.1637 0.949 0.000 0.940 0.000 0.060
#> SRR1313186 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0188 0.981 0.000 0.996 0.000 0.004
#> SRR1313192 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.1022 0.969 0.000 0.968 0.000 0.032
#> SRR1313195 2 0.0469 0.979 0.000 0.988 0.000 0.012
#> SRR1313196 2 0.0921 0.971 0.000 0.972 0.000 0.028
#> SRR1313197 2 0.0188 0.981 0.000 0.996 0.000 0.004
#> SRR1313198 2 0.1022 0.969 0.000 0.968 0.000 0.032
#> SRR1313199 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.1211 0.964 0.000 0.960 0.000 0.040
#> SRR1313201 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0469 0.979 0.000 0.988 0.000 0.012
#> SRR1313203 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313204 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0921 0.971 0.000 0.972 0.000 0.028
#> SRR1313209 2 0.0469 0.979 0.000 0.988 0.000 0.012
#> SRR1313211 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0592 0.977 0.000 0.984 0.000 0.016
#> SRR1313215 2 0.0592 0.977 0.000 0.984 0.000 0.016
#> SRR1313213 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.1118 0.966 0.000 0.964 0.000 0.036
#> SRR1313219 2 0.0921 0.971 0.000 0.972 0.000 0.028
#> SRR1313220 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.3245 0.893 0.000 0.880 0.056 0.064
#> SRR1313227 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.983 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.983 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.3081 0.7699 0.000 0.000 0.156 0.832 0.012
#> SRR1313063 4 0.3812 0.7080 0.000 0.000 0.204 0.772 0.024
#> SRR1313064 4 0.0162 0.9310 0.000 0.000 0.004 0.996 0.000
#> SRR1313065 4 0.0162 0.9317 0.000 0.000 0.000 0.996 0.004
#> SRR1313066 4 0.0290 0.9298 0.000 0.000 0.000 0.992 0.008
#> SRR1313067 3 0.2595 0.7699 0.000 0.000 0.888 0.080 0.032
#> SRR1313068 3 0.4302 0.5585 0.000 0.000 0.720 0.248 0.032
#> SRR1313069 4 0.0162 0.9312 0.000 0.000 0.000 0.996 0.004
#> SRR1313070 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0162 0.9317 0.000 0.000 0.000 0.996 0.004
#> SRR1313073 4 0.0579 0.9243 0.000 0.000 0.008 0.984 0.008
#> SRR1313074 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 3 0.4218 0.4874 0.000 0.000 0.660 0.332 0.008
#> SRR1313077 3 0.2522 0.7622 0.000 0.000 0.880 0.108 0.012
#> SRR1313078 3 0.0932 0.8209 0.004 0.000 0.972 0.004 0.020
#> SRR1313079 4 0.0162 0.9310 0.000 0.000 0.004 0.996 0.000
#> SRR1313080 3 0.5008 0.4278 0.000 0.000 0.644 0.300 0.056
#> SRR1313081 3 0.1628 0.8062 0.000 0.000 0.936 0.056 0.008
#> SRR1313082 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313084 4 0.0162 0.9317 0.000 0.000 0.000 0.996 0.004
#> SRR1313085 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0162 0.9312 0.000 0.000 0.000 0.996 0.004
#> SRR1313087 4 0.0162 0.9310 0.000 0.000 0.004 0.996 0.000
#> SRR1313088 4 0.0000 0.9325 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0162 0.9317 0.000 0.000 0.000 0.996 0.004
#> SRR1313092 3 0.2864 0.7669 0.136 0.000 0.852 0.000 0.012
#> SRR1313090 3 0.0404 0.8193 0.000 0.000 0.988 0.000 0.012
#> SRR1313091 2 0.3194 0.5776 0.020 0.832 0.148 0.000 0.000
#> SRR1313093 3 0.4653 0.1297 0.472 0.000 0.516 0.000 0.012
#> SRR1313095 3 0.2583 0.7666 0.132 0.000 0.864 0.000 0.004
#> SRR1313096 1 0.4339 0.4353 0.652 0.000 0.336 0.000 0.012
#> SRR1313094 3 0.1597 0.8131 0.048 0.000 0.940 0.000 0.012
#> SRR1313097 3 0.0451 0.8203 0.004 0.000 0.988 0.000 0.008
#> SRR1313099 3 0.6367 0.3255 0.344 0.128 0.516 0.000 0.012
#> SRR1313098 1 0.4517 0.3179 0.600 0.000 0.388 0.000 0.012
#> SRR1313101 3 0.0510 0.8186 0.000 0.000 0.984 0.000 0.016
#> SRR1313102 3 0.4402 0.4507 0.352 0.000 0.636 0.000 0.012
#> SRR1313103 1 0.4323 0.4363 0.656 0.000 0.332 0.000 0.012
#> SRR1313100 3 0.1082 0.8130 0.000 0.000 0.964 0.008 0.028
#> SRR1313105 3 0.1557 0.8073 0.008 0.000 0.940 0.000 0.052
#> SRR1313104 3 0.0807 0.8220 0.012 0.000 0.976 0.000 0.012
#> SRR1313107 1 0.4444 0.3592 0.624 0.000 0.364 0.000 0.012
#> SRR1313106 3 0.2929 0.6707 0.000 0.000 0.820 0.000 0.180
#> SRR1313109 2 0.7006 -0.1574 0.232 0.380 0.376 0.000 0.012
#> SRR1313108 3 0.3163 0.7356 0.164 0.000 0.824 0.000 0.012
#> SRR1313111 3 0.4547 0.3540 0.400 0.000 0.588 0.000 0.012
#> SRR1313110 3 0.2260 0.8127 0.064 0.000 0.908 0.000 0.028
#> SRR1313112 3 0.0324 0.8206 0.004 0.000 0.992 0.000 0.004
#> SRR1313113 3 0.1124 0.8153 0.004 0.000 0.960 0.000 0.036
#> SRR1313115 1 0.4505 0.3121 0.604 0.000 0.384 0.000 0.012
#> SRR1313114 3 0.4620 0.3598 0.392 0.000 0.592 0.000 0.016
#> SRR1313117 3 0.0609 0.8183 0.000 0.000 0.980 0.000 0.020
#> SRR1313118 3 0.3061 0.7631 0.136 0.000 0.844 0.000 0.020
#> SRR1313116 5 0.3480 0.4225 0.000 0.000 0.248 0.000 0.752
#> SRR1313120 3 0.4288 0.5130 0.324 0.000 0.664 0.000 0.012
#> SRR1313119 3 0.0566 0.8208 0.004 0.000 0.984 0.000 0.012
#> SRR1313122 3 0.0290 0.8197 0.000 0.000 0.992 0.000 0.008
#> SRR1313124 3 0.0609 0.8183 0.000 0.000 0.980 0.000 0.020
#> SRR1313121 3 0.0510 0.8186 0.000 0.000 0.984 0.000 0.016
#> SRR1313125 3 0.3550 0.6642 0.236 0.000 0.760 0.000 0.004
#> SRR1313127 1 0.4538 0.3799 0.620 0.000 0.364 0.000 0.016
#> SRR1313123 1 0.2971 0.7187 0.836 0.000 0.156 0.000 0.008
#> SRR1313128 1 0.0451 0.8377 0.988 0.000 0.004 0.000 0.008
#> SRR1313126 3 0.0566 0.8207 0.004 0.000 0.984 0.000 0.012
#> SRR1313130 2 0.5355 0.2772 0.000 0.624 0.084 0.000 0.292
#> SRR1313132 1 0.0693 0.8356 0.980 0.000 0.008 0.000 0.012
#> SRR1313129 3 0.4402 0.5709 0.292 0.008 0.688 0.000 0.012
#> SRR1313133 1 0.0693 0.8356 0.980 0.000 0.008 0.000 0.012
#> SRR1313131 1 0.3916 0.5782 0.732 0.000 0.256 0.000 0.012
#> SRR1313134 1 0.0290 0.8384 0.992 0.000 0.000 0.000 0.008
#> SRR1313135 1 0.0671 0.8392 0.980 0.000 0.000 0.016 0.004
#> SRR1313136 1 0.0290 0.8392 0.992 0.000 0.000 0.000 0.008
#> SRR1313137 1 0.2079 0.8081 0.916 0.000 0.000 0.064 0.020
#> SRR1313138 1 0.1831 0.8118 0.920 0.000 0.000 0.004 0.076
#> SRR1313140 4 0.4484 0.5319 0.308 0.000 0.000 0.668 0.024
#> SRR1313141 1 0.0693 0.8356 0.980 0.000 0.008 0.000 0.012
#> SRR1313139 4 0.3203 0.7652 0.168 0.000 0.000 0.820 0.012
#> SRR1313143 1 0.1357 0.8266 0.948 0.000 0.004 0.000 0.048
#> SRR1313142 1 0.0290 0.8392 0.992 0.000 0.000 0.000 0.008
#> SRR1313144 1 0.1597 0.8213 0.940 0.000 0.000 0.048 0.012
#> SRR1313145 1 0.0000 0.8392 1.000 0.000 0.000 0.000 0.000
#> SRR1313146 1 0.0162 0.8394 0.996 0.000 0.000 0.000 0.004
#> SRR1313147 1 0.4127 0.5052 0.680 0.000 0.000 0.312 0.008
#> SRR1313150 5 0.6369 -0.1132 0.244 0.000 0.000 0.236 0.520
#> SRR1313149 1 0.0579 0.8368 0.984 0.000 0.008 0.000 0.008
#> SRR1313152 1 0.1740 0.8166 0.932 0.000 0.000 0.056 0.012
#> SRR1313151 1 0.0290 0.8392 0.992 0.000 0.000 0.000 0.008
#> SRR1313154 1 0.0162 0.8394 0.996 0.000 0.000 0.000 0.004
#> SRR1313153 1 0.0566 0.8379 0.984 0.000 0.000 0.004 0.012
#> SRR1313156 1 0.0404 0.8385 0.988 0.000 0.000 0.000 0.012
#> SRR1313155 1 0.0671 0.8372 0.980 0.000 0.000 0.004 0.016
#> SRR1313157 1 0.5386 0.2066 0.544 0.000 0.000 0.396 0.060
#> SRR1313158 1 0.0162 0.8393 0.996 0.000 0.000 0.000 0.004
#> SRR1313161 1 0.4046 0.5518 0.696 0.000 0.000 0.296 0.008
#> SRR1313159 1 0.0566 0.8362 0.984 0.012 0.000 0.000 0.004
#> SRR1313160 1 0.2248 0.7948 0.900 0.000 0.000 0.088 0.012
#> SRR1313162 1 0.1670 0.8099 0.936 0.000 0.052 0.000 0.012
#> SRR1313163 1 0.0671 0.8372 0.980 0.000 0.000 0.004 0.016
#> SRR1313165 1 0.4940 0.4404 0.576 0.000 0.000 0.032 0.392
#> SRR1313166 1 0.0579 0.8368 0.984 0.000 0.008 0.000 0.008
#> SRR1313164 1 0.0000 0.8392 1.000 0.000 0.000 0.000 0.000
#> SRR1313167 4 0.6068 0.4202 0.308 0.000 0.000 0.544 0.148
#> SRR1313168 1 0.1774 0.8169 0.932 0.000 0.000 0.052 0.016
#> SRR1313170 1 0.6903 0.0637 0.416 0.008 0.236 0.000 0.340
#> SRR1313169 1 0.3455 0.6769 0.784 0.000 0.000 0.208 0.008
#> SRR1313172 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313171 1 0.0865 0.8371 0.972 0.000 0.004 0.000 0.024
#> SRR1313174 2 0.4138 0.2104 0.000 0.616 0.000 0.000 0.384
#> SRR1313173 1 0.4251 0.4702 0.672 0.000 0.316 0.000 0.012
#> SRR1313176 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 2 0.4304 -0.1902 0.000 0.516 0.000 0.000 0.484
#> SRR1313178 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313180 5 0.1399 0.5790 0.000 0.020 0.028 0.000 0.952
#> SRR1313181 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.3003 0.6047 0.000 0.812 0.000 0.000 0.188
#> SRR1313184 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313185 2 0.4015 0.3156 0.000 0.652 0.000 0.000 0.348
#> SRR1313188 5 0.1830 0.5930 0.000 0.068 0.008 0.000 0.924
#> SRR1313187 5 0.4419 0.5816 0.000 0.312 0.020 0.000 0.668
#> SRR1313186 2 0.3913 0.3724 0.000 0.676 0.000 0.000 0.324
#> SRR1313189 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.4015 0.3156 0.000 0.652 0.000 0.000 0.348
#> SRR1313192 2 0.0290 0.7697 0.000 0.992 0.000 0.000 0.008
#> SRR1313193 2 0.1732 0.7183 0.000 0.920 0.000 0.000 0.080
#> SRR1313194 5 0.4655 0.2616 0.000 0.476 0.012 0.000 0.512
#> SRR1313195 2 0.5238 -0.2761 0.000 0.484 0.044 0.000 0.472
#> SRR1313196 5 0.4902 0.4382 0.000 0.408 0.028 0.000 0.564
#> SRR1313197 2 0.4182 0.1547 0.000 0.600 0.000 0.000 0.400
#> SRR1313198 5 0.4302 0.2609 0.000 0.480 0.000 0.000 0.520
#> SRR1313199 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.4387 0.5475 0.000 0.348 0.012 0.000 0.640
#> SRR1313201 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 2 0.4655 -0.2001 0.000 0.512 0.012 0.000 0.476
#> SRR1313203 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313204 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.1544 0.7282 0.000 0.932 0.000 0.000 0.068
#> SRR1313207 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0162 0.7720 0.000 0.996 0.000 0.000 0.004
#> SRR1313210 5 0.3242 0.6030 0.000 0.216 0.000 0.000 0.784
#> SRR1313209 2 0.4268 -0.0248 0.000 0.556 0.000 0.000 0.444
#> SRR1313211 2 0.3366 0.5437 0.000 0.768 0.000 0.000 0.232
#> SRR1313212 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 2 0.4291 -0.1088 0.000 0.536 0.000 0.000 0.464
#> SRR1313215 5 0.4302 0.2602 0.000 0.480 0.000 0.000 0.520
#> SRR1313213 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 2 0.4440 -0.1354 0.004 0.528 0.000 0.000 0.468
#> SRR1313217 5 0.4101 0.5667 0.000 0.332 0.004 0.000 0.664
#> SRR1313219 5 0.3895 0.5710 0.000 0.320 0.000 0.000 0.680
#> SRR1313220 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.3366 0.5437 0.000 0.768 0.000 0.000 0.232
#> SRR1313222 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 2 0.4015 0.3152 0.000 0.652 0.000 0.000 0.348
#> SRR1313226 5 0.1522 0.5751 0.000 0.012 0.044 0.000 0.944
#> SRR1313227 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.7740 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 6 0.4021 0.6519 0.032 0.000 0.076 0.088 0.004 0.800
#> SRR1313063 6 0.4578 0.6317 0.008 0.000 0.076 0.136 0.028 0.752
#> SRR1313064 6 0.3996 -0.1635 0.004 0.000 0.000 0.484 0.000 0.512
#> SRR1313065 4 0.0692 0.8900 0.004 0.000 0.000 0.976 0.000 0.020
#> SRR1313066 4 0.0000 0.8909 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 6 0.4251 0.6239 0.000 0.000 0.256 0.012 0.032 0.700
#> SRR1313068 6 0.4873 0.6104 0.000 0.000 0.276 0.032 0.040 0.652
#> SRR1313069 6 0.5012 0.1956 0.100 0.000 0.000 0.300 0.000 0.600
#> SRR1313070 4 0.0000 0.8909 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.8909 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.8909 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 6 0.3738 0.4854 0.040 0.000 0.000 0.208 0.000 0.752
#> SRR1313074 4 0.4078 0.5401 0.020 0.000 0.000 0.640 0.000 0.340
#> SRR1313075 4 0.1285 0.8783 0.004 0.000 0.000 0.944 0.000 0.052
#> SRR1313076 6 0.3892 0.6987 0.016 0.000 0.144 0.040 0.008 0.792
#> SRR1313077 6 0.3357 0.6943 0.020 0.000 0.144 0.020 0.000 0.816
#> SRR1313078 6 0.3520 0.6645 0.036 0.000 0.188 0.000 0.000 0.776
#> SRR1313079 4 0.3426 0.6377 0.004 0.000 0.000 0.720 0.000 0.276
#> SRR1313080 6 0.5100 0.6381 0.000 0.000 0.228 0.056 0.048 0.668
#> SRR1313081 6 0.3412 0.6899 0.032 0.000 0.144 0.012 0.000 0.812
#> SRR1313082 4 0.1082 0.8850 0.004 0.000 0.000 0.956 0.000 0.040
#> SRR1313083 4 0.0935 0.8876 0.004 0.000 0.000 0.964 0.000 0.032
#> SRR1313084 4 0.0000 0.8909 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0146 0.8913 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1313086 4 0.4407 0.6521 0.076 0.000 0.000 0.692 0.000 0.232
#> SRR1313087 6 0.3971 -0.0253 0.004 0.000 0.000 0.448 0.000 0.548
#> SRR1313088 4 0.4172 0.6935 0.072 0.000 0.000 0.724 0.000 0.204
#> SRR1313089 4 0.0260 0.8914 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1313092 3 0.3612 0.6423 0.092 0.000 0.804 0.000 0.004 0.100
#> SRR1313090 3 0.3860 0.4551 0.000 0.000 0.728 0.000 0.036 0.236
#> SRR1313091 3 0.4809 0.4132 0.020 0.300 0.644 0.000 0.028 0.008
#> SRR1313093 3 0.3511 0.6448 0.216 0.000 0.760 0.000 0.000 0.024
#> SRR1313095 3 0.4881 0.4747 0.088 0.000 0.640 0.000 0.004 0.268
#> SRR1313096 3 0.4587 0.5863 0.296 0.000 0.640 0.000 0.000 0.064
#> SRR1313094 3 0.1644 0.6454 0.040 0.000 0.932 0.000 0.000 0.028
#> SRR1313097 3 0.1976 0.6207 0.008 0.000 0.916 0.000 0.016 0.060
#> SRR1313099 3 0.3492 0.6579 0.176 0.004 0.788 0.000 0.000 0.032
#> SRR1313098 3 0.6015 0.2139 0.240 0.000 0.384 0.000 0.000 0.376
#> SRR1313101 3 0.3860 0.4637 0.000 0.000 0.728 0.000 0.036 0.236
#> SRR1313102 3 0.4738 0.6485 0.200 0.000 0.684 0.000 0.004 0.112
#> SRR1313103 3 0.4122 0.6232 0.248 0.000 0.704 0.000 0.000 0.048
#> SRR1313100 6 0.4570 0.4765 0.000 0.000 0.368 0.012 0.024 0.596
#> SRR1313105 3 0.1890 0.6291 0.008 0.000 0.924 0.000 0.044 0.024
#> SRR1313104 3 0.3141 0.5675 0.004 0.000 0.832 0.000 0.040 0.124
#> SRR1313107 3 0.4000 0.6352 0.228 0.000 0.724 0.000 0.000 0.048
#> SRR1313106 5 0.5071 0.1316 0.000 0.000 0.444 0.000 0.480 0.076
#> SRR1313109 3 0.4227 0.6024 0.092 0.116 0.772 0.000 0.004 0.016
#> SRR1313108 3 0.3092 0.6508 0.104 0.000 0.836 0.000 0.000 0.060
#> SRR1313111 3 0.3621 0.6604 0.192 0.000 0.772 0.000 0.004 0.032
#> SRR1313110 6 0.4710 0.5649 0.072 0.000 0.208 0.000 0.020 0.700
#> SRR1313112 3 0.3688 0.4432 0.000 0.000 0.724 0.000 0.020 0.256
#> SRR1313113 3 0.2058 0.6113 0.000 0.000 0.908 0.000 0.056 0.036
#> SRR1313115 3 0.3863 0.6165 0.260 0.000 0.712 0.000 0.000 0.028
#> SRR1313114 6 0.6008 -0.0628 0.284 0.000 0.240 0.000 0.004 0.472
#> SRR1313117 3 0.4079 0.5002 0.000 0.000 0.744 0.000 0.084 0.172
#> SRR1313118 3 0.5883 0.1578 0.088 0.000 0.484 0.004 0.028 0.396
#> SRR1313116 5 0.2615 0.6555 0.004 0.000 0.136 0.000 0.852 0.008
#> SRR1313120 3 0.3098 0.6592 0.164 0.000 0.812 0.000 0.000 0.024
#> SRR1313119 3 0.4671 0.5514 0.044 0.000 0.696 0.000 0.032 0.228
#> SRR1313122 3 0.3670 0.4612 0.000 0.000 0.736 0.000 0.024 0.240
#> SRR1313124 3 0.3857 0.5129 0.000 0.000 0.768 0.000 0.080 0.152
#> SRR1313121 3 0.4183 0.3489 0.000 0.000 0.668 0.000 0.036 0.296
#> SRR1313125 3 0.4457 0.6514 0.168 0.000 0.720 0.000 0.004 0.108
#> SRR1313127 3 0.5600 0.5492 0.296 0.000 0.528 0.000 0.000 0.176
#> SRR1313123 3 0.5442 0.3385 0.412 0.000 0.468 0.000 0.000 0.120
#> SRR1313128 1 0.2622 0.8121 0.868 0.000 0.104 0.000 0.004 0.024
#> SRR1313126 6 0.4453 0.4618 0.032 0.000 0.400 0.000 0.000 0.568
#> SRR1313130 3 0.5895 -0.0469 0.008 0.088 0.500 0.000 0.380 0.024
#> SRR1313132 1 0.3053 0.7626 0.812 0.000 0.168 0.000 0.000 0.020
#> SRR1313129 3 0.4233 0.6583 0.180 0.000 0.736 0.000 0.004 0.080
#> SRR1313133 1 0.2750 0.7930 0.844 0.000 0.136 0.000 0.000 0.020
#> SRR1313131 3 0.4361 0.5668 0.308 0.000 0.648 0.000 0.000 0.044
#> SRR1313134 1 0.2581 0.8035 0.860 0.000 0.120 0.000 0.000 0.020
#> SRR1313135 1 0.1500 0.8447 0.936 0.000 0.000 0.012 0.000 0.052
#> SRR1313136 1 0.1138 0.8449 0.960 0.000 0.012 0.004 0.000 0.024
#> SRR1313137 1 0.2356 0.8346 0.884 0.000 0.000 0.004 0.016 0.096
#> SRR1313138 1 0.3418 0.8072 0.820 0.000 0.004 0.000 0.092 0.084
#> SRR1313140 1 0.4550 0.6679 0.704 0.000 0.000 0.060 0.016 0.220
#> SRR1313141 1 0.3845 0.7992 0.788 0.000 0.120 0.000 0.008 0.084
#> SRR1313139 1 0.5672 0.6008 0.628 0.000 0.000 0.196 0.044 0.132
#> SRR1313143 1 0.4247 0.7799 0.740 0.000 0.092 0.000 0.004 0.164
#> SRR1313142 1 0.0924 0.8451 0.972 0.000 0.008 0.004 0.008 0.008
#> SRR1313144 1 0.2955 0.7768 0.816 0.000 0.000 0.008 0.004 0.172
#> SRR1313145 1 0.2255 0.8217 0.892 0.000 0.088 0.004 0.000 0.016
#> SRR1313146 1 0.2655 0.8109 0.848 0.000 0.004 0.008 0.000 0.140
#> SRR1313147 1 0.3983 0.7217 0.736 0.000 0.000 0.056 0.000 0.208
#> SRR1313150 1 0.5297 0.6214 0.624 0.000 0.000 0.048 0.276 0.052
#> SRR1313149 1 0.3464 0.8105 0.808 0.000 0.108 0.000 0.000 0.084
#> SRR1313152 1 0.2306 0.8334 0.888 0.000 0.004 0.004 0.008 0.096
#> SRR1313151 1 0.2948 0.7697 0.804 0.000 0.000 0.008 0.000 0.188
#> SRR1313154 1 0.2401 0.8320 0.892 0.000 0.072 0.008 0.000 0.028
#> SRR1313153 1 0.0912 0.8448 0.972 0.000 0.004 0.004 0.012 0.008
#> SRR1313156 1 0.1232 0.8413 0.956 0.000 0.024 0.000 0.016 0.004
#> SRR1313155 1 0.1262 0.8466 0.956 0.000 0.000 0.008 0.016 0.020
#> SRR1313157 1 0.4531 0.7629 0.752 0.000 0.000 0.056 0.060 0.132
#> SRR1313158 1 0.2364 0.8220 0.892 0.000 0.072 0.000 0.004 0.032
#> SRR1313161 1 0.3399 0.8185 0.816 0.000 0.020 0.024 0.000 0.140
#> SRR1313159 1 0.3104 0.8256 0.872 0.036 0.040 0.000 0.032 0.020
#> SRR1313160 1 0.2887 0.8274 0.856 0.000 0.004 0.008 0.020 0.112
#> SRR1313162 1 0.3501 0.7812 0.804 0.000 0.116 0.000 0.000 0.080
#> SRR1313163 1 0.2011 0.8366 0.912 0.000 0.004 0.000 0.020 0.064
#> SRR1313165 1 0.4499 0.7123 0.704 0.000 0.000 0.008 0.216 0.072
#> SRR1313166 1 0.2581 0.8003 0.856 0.000 0.128 0.000 0.000 0.016
#> SRR1313164 1 0.2604 0.8148 0.872 0.000 0.100 0.000 0.008 0.020
#> SRR1313167 1 0.5346 0.5065 0.588 0.000 0.000 0.320 0.036 0.056
#> SRR1313168 1 0.2146 0.8401 0.908 0.000 0.000 0.008 0.024 0.060
#> SRR1313170 5 0.5387 0.1956 0.088 0.000 0.404 0.000 0.500 0.008
#> SRR1313169 1 0.3078 0.8192 0.836 0.000 0.000 0.056 0.000 0.108
#> SRR1313172 2 0.1398 0.8992 0.000 0.940 0.052 0.000 0.000 0.008
#> SRR1313171 1 0.3975 0.7401 0.764 0.000 0.180 0.000 0.020 0.036
#> SRR1313174 5 0.3774 0.5974 0.000 0.408 0.000 0.000 0.592 0.000
#> SRR1313173 3 0.4313 0.5914 0.284 0.000 0.668 0.000 0.000 0.048
#> SRR1313176 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.3675 0.7590 0.008 0.252 0.004 0.000 0.732 0.004
#> SRR1313178 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313180 5 0.1334 0.6816 0.000 0.000 0.032 0.000 0.948 0.020
#> SRR1313181 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.2697 0.6805 0.000 0.812 0.000 0.000 0.188 0.000
#> SRR1313184 2 0.0260 0.9519 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1313185 5 0.3915 0.5899 0.000 0.412 0.004 0.000 0.584 0.000
#> SRR1313188 5 0.0777 0.6776 0.024 0.000 0.004 0.000 0.972 0.000
#> SRR1313187 5 0.3078 0.7386 0.000 0.064 0.048 0.000 0.860 0.028
#> SRR1313186 5 0.3937 0.5683 0.000 0.424 0.004 0.000 0.572 0.000
#> SRR1313189 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.3860 0.4601 0.000 0.472 0.000 0.000 0.528 0.000
#> SRR1313192 2 0.0458 0.9469 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1313193 2 0.2048 0.8084 0.000 0.880 0.000 0.000 0.120 0.000
#> SRR1313194 5 0.4242 0.7645 0.000 0.232 0.012 0.000 0.716 0.040
#> SRR1313195 5 0.4889 0.7648 0.000 0.204 0.052 0.000 0.696 0.048
#> SRR1313196 5 0.3384 0.7332 0.004 0.060 0.068 0.000 0.844 0.024
#> SRR1313197 5 0.3782 0.6644 0.000 0.360 0.004 0.000 0.636 0.000
#> SRR1313198 5 0.3284 0.7796 0.020 0.196 0.000 0.000 0.784 0.000
#> SRR1313199 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.2794 0.7677 0.004 0.104 0.020 0.000 0.864 0.008
#> SRR1313201 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.4341 0.7795 0.000 0.192 0.048 0.000 0.736 0.024
#> SRR1313203 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313204 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0458 0.9469 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1313207 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0146 0.9578 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313210 5 0.2420 0.7433 0.040 0.076 0.000 0.000 0.884 0.000
#> SRR1313209 5 0.3861 0.6725 0.008 0.352 0.000 0.000 0.640 0.000
#> SRR1313211 2 0.3620 0.1833 0.000 0.648 0.000 0.000 0.352 0.000
#> SRR1313212 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.3690 0.7327 0.012 0.288 0.000 0.000 0.700 0.000
#> SRR1313215 5 0.3409 0.7826 0.024 0.184 0.004 0.000 0.788 0.000
#> SRR1313213 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.3789 0.7777 0.040 0.196 0.004 0.000 0.760 0.000
#> SRR1313217 5 0.2214 0.7584 0.012 0.092 0.000 0.000 0.892 0.004
#> SRR1313219 5 0.2930 0.7704 0.036 0.124 0.000 0.000 0.840 0.000
#> SRR1313220 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.2340 0.7625 0.000 0.852 0.000 0.000 0.148 0.000
#> SRR1313222 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0146 0.9578 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313225 5 0.3847 0.5003 0.000 0.456 0.000 0.000 0.544 0.000
#> SRR1313226 5 0.1780 0.6795 0.000 0.000 0.048 0.000 0.924 0.028
#> SRR1313227 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9607 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "hclust"]
# you can also extract it by
# res = res_list["ATC:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.512 0.817 0.906 0.4581 0.519 0.519
#> 3 3 0.714 0.836 0.910 0.3984 0.819 0.651
#> 4 4 0.732 0.603 0.786 0.1303 0.847 0.596
#> 5 5 0.745 0.631 0.764 0.0451 0.902 0.667
#> 6 6 0.772 0.711 0.799 0.0273 0.945 0.770
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 2 0.2236 0.8942 0.036 0.964
#> SRR1313063 2 0.2236 0.8942 0.036 0.964
#> SRR1313064 2 0.2236 0.8942 0.036 0.964
#> SRR1313065 2 0.8555 0.6245 0.280 0.720
#> SRR1313066 2 0.2236 0.8942 0.036 0.964
#> SRR1313067 2 0.9909 0.1716 0.444 0.556
#> SRR1313068 2 0.2236 0.8942 0.036 0.964
#> SRR1313069 2 0.2236 0.8942 0.036 0.964
#> SRR1313070 2 0.2236 0.8942 0.036 0.964
#> SRR1313071 2 0.2236 0.8942 0.036 0.964
#> SRR1313072 2 0.2236 0.8942 0.036 0.964
#> SRR1313073 2 0.2236 0.8942 0.036 0.964
#> SRR1313074 2 0.2236 0.8942 0.036 0.964
#> SRR1313075 2 0.2236 0.8942 0.036 0.964
#> SRR1313076 2 0.2423 0.8919 0.040 0.960
#> SRR1313077 2 0.9552 0.4044 0.376 0.624
#> SRR1313078 1 0.6148 0.8446 0.848 0.152
#> SRR1313079 2 0.2236 0.8942 0.036 0.964
#> SRR1313080 2 0.2236 0.8942 0.036 0.964
#> SRR1313081 2 0.5629 0.8110 0.132 0.868
#> SRR1313082 2 0.8555 0.6245 0.280 0.720
#> SRR1313083 2 0.9954 0.1103 0.460 0.540
#> SRR1313084 2 0.2236 0.8942 0.036 0.964
#> SRR1313085 2 0.2236 0.8942 0.036 0.964
#> SRR1313086 2 0.2423 0.8919 0.040 0.960
#> SRR1313087 2 0.2236 0.8942 0.036 0.964
#> SRR1313088 2 0.2236 0.8942 0.036 0.964
#> SRR1313089 2 0.2236 0.8942 0.036 0.964
#> SRR1313092 1 0.4562 0.8770 0.904 0.096
#> SRR1313090 1 0.9170 0.6077 0.668 0.332
#> SRR1313091 1 0.3431 0.8810 0.936 0.064
#> SRR1313093 1 0.0000 0.8694 1.000 0.000
#> SRR1313095 1 0.7453 0.8013 0.788 0.212
#> SRR1313096 1 0.0000 0.8694 1.000 0.000
#> SRR1313094 1 0.2043 0.8791 0.968 0.032
#> SRR1313097 1 0.3274 0.8816 0.940 0.060
#> SRR1313099 1 0.0000 0.8694 1.000 0.000
#> SRR1313098 1 0.6438 0.8453 0.836 0.164
#> SRR1313101 1 0.8207 0.7463 0.744 0.256
#> SRR1313102 1 0.3274 0.8816 0.940 0.060
#> SRR1313103 1 0.1414 0.8717 0.980 0.020
#> SRR1313100 2 0.3274 0.8788 0.060 0.940
#> SRR1313105 1 0.2948 0.8809 0.948 0.052
#> SRR1313104 1 0.3114 0.8815 0.944 0.056
#> SRR1313107 1 0.0000 0.8694 1.000 0.000
#> SRR1313106 1 0.9954 0.2915 0.540 0.460
#> SRR1313109 1 0.2778 0.8801 0.952 0.048
#> SRR1313108 1 0.0000 0.8694 1.000 0.000
#> SRR1313111 1 0.3274 0.8816 0.940 0.060
#> SRR1313110 1 0.8144 0.7474 0.748 0.252
#> SRR1313112 1 0.8207 0.7463 0.744 0.256
#> SRR1313113 1 0.3274 0.8816 0.940 0.060
#> SRR1313115 1 0.0000 0.8694 1.000 0.000
#> SRR1313114 1 0.8443 0.7207 0.728 0.272
#> SRR1313117 1 0.8207 0.7463 0.744 0.256
#> SRR1313118 2 0.9460 0.4407 0.364 0.636
#> SRR1313116 1 0.3274 0.8816 0.940 0.060
#> SRR1313120 1 0.0000 0.8694 1.000 0.000
#> SRR1313119 1 0.8267 0.7404 0.740 0.260
#> SRR1313122 1 0.7528 0.7952 0.784 0.216
#> SRR1313124 1 0.8207 0.7463 0.744 0.256
#> SRR1313121 2 0.8661 0.6109 0.288 0.712
#> SRR1313125 1 0.8207 0.7463 0.744 0.256
#> SRR1313127 1 0.6438 0.8453 0.836 0.164
#> SRR1313123 1 0.6148 0.8543 0.848 0.152
#> SRR1313128 1 0.0938 0.8730 0.988 0.012
#> SRR1313126 1 0.6887 0.8277 0.816 0.184
#> SRR1313130 2 0.8713 0.5710 0.292 0.708
#> SRR1313132 1 0.1843 0.8783 0.972 0.028
#> SRR1313129 1 0.3274 0.8816 0.940 0.060
#> SRR1313133 1 0.0000 0.8694 1.000 0.000
#> SRR1313131 1 0.0000 0.8694 1.000 0.000
#> SRR1313134 1 0.0000 0.8694 1.000 0.000
#> SRR1313135 2 0.6623 0.7768 0.172 0.828
#> SRR1313136 1 0.5842 0.8623 0.860 0.140
#> SRR1313137 2 0.8608 0.6172 0.284 0.716
#> SRR1313138 1 0.9833 0.3534 0.576 0.424
#> SRR1313140 2 0.5294 0.8290 0.120 0.880
#> SRR1313141 1 0.0000 0.8694 1.000 0.000
#> SRR1313139 2 0.5294 0.8290 0.120 0.880
#> SRR1313143 1 0.0000 0.8694 1.000 0.000
#> SRR1313142 1 0.5842 0.8623 0.860 0.140
#> SRR1313144 2 0.6148 0.7961 0.152 0.848
#> SRR1313145 1 0.4431 0.8766 0.908 0.092
#> SRR1313146 1 0.5842 0.8623 0.860 0.140
#> SRR1313147 2 0.8386 0.6439 0.268 0.732
#> SRR1313150 2 0.8555 0.6241 0.280 0.720
#> SRR1313149 1 0.0000 0.8694 1.000 0.000
#> SRR1313152 2 0.8608 0.6172 0.284 0.716
#> SRR1313151 1 0.5842 0.8623 0.860 0.140
#> SRR1313154 1 0.2423 0.8791 0.960 0.040
#> SRR1313153 1 0.5842 0.8623 0.860 0.140
#> SRR1313156 1 0.5629 0.8656 0.868 0.132
#> SRR1313155 1 0.5842 0.8623 0.860 0.140
#> SRR1313157 2 0.8608 0.6172 0.284 0.716
#> SRR1313158 1 0.5842 0.8623 0.860 0.140
#> SRR1313161 2 0.8713 0.6025 0.292 0.708
#> SRR1313159 2 0.9970 -0.0253 0.468 0.532
#> SRR1313160 2 0.8763 0.5950 0.296 0.704
#> SRR1313162 1 0.5842 0.8623 0.860 0.140
#> SRR1313163 1 0.5629 0.8656 0.868 0.132
#> SRR1313165 2 0.8763 0.5950 0.296 0.704
#> SRR1313166 1 0.1843 0.8783 0.972 0.028
#> SRR1313164 1 0.0376 0.8697 0.996 0.004
#> SRR1313167 1 0.9775 0.3974 0.588 0.412
#> SRR1313168 2 0.8608 0.6172 0.284 0.716
#> SRR1313170 2 0.9970 -0.0253 0.468 0.532
#> SRR1313169 2 0.8608 0.6172 0.284 0.716
#> SRR1313172 1 0.0000 0.8694 1.000 0.000
#> SRR1313171 1 0.0000 0.8694 1.000 0.000
#> SRR1313174 2 0.0000 0.9035 0.000 1.000
#> SRR1313173 1 0.0000 0.8694 1.000 0.000
#> SRR1313176 2 0.0000 0.9035 0.000 1.000
#> SRR1313175 2 0.0000 0.9035 0.000 1.000
#> SRR1313178 2 0.0000 0.9035 0.000 1.000
#> SRR1313177 2 0.0000 0.9035 0.000 1.000
#> SRR1313179 2 0.0938 0.8992 0.012 0.988
#> SRR1313180 2 0.0000 0.9035 0.000 1.000
#> SRR1313181 2 0.0000 0.9035 0.000 1.000
#> SRR1313183 2 0.0000 0.9035 0.000 1.000
#> SRR1313182 2 0.0000 0.9035 0.000 1.000
#> SRR1313184 2 0.0000 0.9035 0.000 1.000
#> SRR1313185 2 0.0000 0.9035 0.000 1.000
#> SRR1313188 2 0.0000 0.9035 0.000 1.000
#> SRR1313187 2 0.0000 0.9035 0.000 1.000
#> SRR1313186 2 0.0000 0.9035 0.000 1.000
#> SRR1313189 2 0.0000 0.9035 0.000 1.000
#> SRR1313190 2 0.0000 0.9035 0.000 1.000
#> SRR1313191 2 0.0000 0.9035 0.000 1.000
#> SRR1313192 2 0.0000 0.9035 0.000 1.000
#> SRR1313193 2 0.0000 0.9035 0.000 1.000
#> SRR1313194 2 0.0000 0.9035 0.000 1.000
#> SRR1313195 2 0.0000 0.9035 0.000 1.000
#> SRR1313196 2 0.0000 0.9035 0.000 1.000
#> SRR1313197 2 0.0000 0.9035 0.000 1.000
#> SRR1313198 2 0.0000 0.9035 0.000 1.000
#> SRR1313199 2 0.0000 0.9035 0.000 1.000
#> SRR1313200 2 0.0000 0.9035 0.000 1.000
#> SRR1313201 2 0.0000 0.9035 0.000 1.000
#> SRR1313202 2 0.0000 0.9035 0.000 1.000
#> SRR1313203 1 0.4815 0.8730 0.896 0.104
#> SRR1313204 2 0.0000 0.9035 0.000 1.000
#> SRR1313205 2 0.0000 0.9035 0.000 1.000
#> SRR1313207 2 0.0000 0.9035 0.000 1.000
#> SRR1313208 2 0.0000 0.9035 0.000 1.000
#> SRR1313206 2 0.0000 0.9035 0.000 1.000
#> SRR1313210 2 0.0000 0.9035 0.000 1.000
#> SRR1313209 2 0.0000 0.9035 0.000 1.000
#> SRR1313211 2 0.0000 0.9035 0.000 1.000
#> SRR1313212 2 0.0000 0.9035 0.000 1.000
#> SRR1313214 2 0.0000 0.9035 0.000 1.000
#> SRR1313215 2 0.0000 0.9035 0.000 1.000
#> SRR1313213 2 0.0000 0.9035 0.000 1.000
#> SRR1313216 1 0.6712 0.8172 0.824 0.176
#> SRR1313217 2 0.0000 0.9035 0.000 1.000
#> SRR1313219 2 0.0000 0.9035 0.000 1.000
#> SRR1313220 2 0.0000 0.9035 0.000 1.000
#> SRR1313218 2 0.0000 0.9035 0.000 1.000
#> SRR1313222 2 0.0000 0.9035 0.000 1.000
#> SRR1313221 2 0.0000 0.9035 0.000 1.000
#> SRR1313223 2 0.0000 0.9035 0.000 1.000
#> SRR1313224 2 0.0000 0.9035 0.000 1.000
#> SRR1313225 2 0.0000 0.9035 0.000 1.000
#> SRR1313226 2 0.0000 0.9035 0.000 1.000
#> SRR1313227 2 0.0000 0.9035 0.000 1.000
#> SRR1313228 2 0.0000 0.9035 0.000 1.000
#> SRR1313229 2 0.0000 0.9035 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313063 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313065 1 0.6148 0.72189 0.728 0.028 0.244
#> SRR1313066 1 0.0237 0.83443 0.996 0.004 0.000
#> SRR1313067 1 0.7192 0.34170 0.560 0.028 0.412
#> SRR1313068 1 0.0237 0.83443 0.996 0.004 0.000
#> SRR1313069 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313076 1 0.0237 0.83472 0.996 0.000 0.004
#> SRR1313077 1 0.5905 0.54710 0.648 0.000 0.352
#> SRR1313078 3 0.3879 0.81546 0.152 0.000 0.848
#> SRR1313079 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313080 1 0.0237 0.83443 0.996 0.004 0.000
#> SRR1313081 1 0.3116 0.77729 0.892 0.000 0.108
#> SRR1313082 1 0.6148 0.72189 0.728 0.028 0.244
#> SRR1313083 1 0.7232 0.28941 0.544 0.028 0.428
#> SRR1313084 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313086 1 0.0237 0.83472 0.996 0.000 0.004
#> SRR1313087 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.83441 1.000 0.000 0.000
#> SRR1313089 1 0.0237 0.83443 0.996 0.004 0.000
#> SRR1313092 3 0.3623 0.86172 0.072 0.032 0.896
#> SRR1313090 3 0.7124 0.58226 0.296 0.048 0.656
#> SRR1313091 3 0.2165 0.85936 0.000 0.064 0.936
#> SRR1313093 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313095 3 0.5746 0.78738 0.180 0.040 0.780
#> SRR1313096 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313094 3 0.1289 0.86780 0.000 0.032 0.968
#> SRR1313097 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313099 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313098 3 0.4874 0.82507 0.144 0.028 0.828
#> SRR1313101 3 0.6354 0.74570 0.204 0.052 0.744
#> SRR1313102 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313103 3 0.0892 0.85958 0.000 0.020 0.980
#> SRR1313100 1 0.2313 0.82533 0.944 0.032 0.024
#> SRR1313105 3 0.1860 0.86363 0.000 0.052 0.948
#> SRR1313104 3 0.1964 0.86266 0.000 0.056 0.944
#> SRR1313107 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313106 3 0.6647 0.22684 0.008 0.452 0.540
#> SRR1313109 3 0.1753 0.86380 0.000 0.048 0.952
#> SRR1313108 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313111 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313110 3 0.6124 0.72951 0.220 0.036 0.744
#> SRR1313112 3 0.6354 0.74570 0.204 0.052 0.744
#> SRR1313113 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313115 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313114 3 0.6482 0.69598 0.244 0.040 0.716
#> SRR1313117 3 0.6354 0.74570 0.204 0.052 0.744
#> SRR1313118 1 0.7061 0.56585 0.632 0.036 0.332
#> SRR1313116 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313120 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313119 3 0.6400 0.74019 0.208 0.052 0.740
#> SRR1313122 3 0.5835 0.79251 0.164 0.052 0.784
#> SRR1313124 3 0.6354 0.74570 0.204 0.052 0.744
#> SRR1313121 1 0.6761 0.69568 0.700 0.048 0.252
#> SRR1313125 3 0.6354 0.74570 0.204 0.052 0.744
#> SRR1313127 3 0.4874 0.82507 0.144 0.028 0.828
#> SRR1313123 3 0.4677 0.83431 0.132 0.028 0.840
#> SRR1313128 3 0.0592 0.86402 0.012 0.000 0.988
#> SRR1313126 3 0.5178 0.80699 0.164 0.028 0.808
#> SRR1313130 2 0.5722 0.53418 0.004 0.704 0.292
#> SRR1313132 3 0.1337 0.86864 0.016 0.012 0.972
#> SRR1313129 3 0.2066 0.86128 0.000 0.060 0.940
#> SRR1313133 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313131 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313134 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313135 1 0.4618 0.79430 0.840 0.024 0.136
#> SRR1313136 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313137 1 0.6187 0.71752 0.724 0.028 0.248
#> SRR1313138 3 0.7236 0.33015 0.392 0.032 0.576
#> SRR1313140 1 0.3637 0.81499 0.892 0.024 0.084
#> SRR1313141 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313139 1 0.3637 0.81499 0.892 0.024 0.084
#> SRR1313143 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313142 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313144 1 0.4397 0.80123 0.856 0.028 0.116
#> SRR1313145 3 0.3499 0.86029 0.072 0.028 0.900
#> SRR1313146 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313147 1 0.6025 0.73172 0.740 0.028 0.232
#> SRR1313150 1 0.6148 0.72158 0.728 0.028 0.244
#> SRR1313149 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313152 1 0.6187 0.71752 0.724 0.028 0.248
#> SRR1313151 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313154 3 0.1999 0.86564 0.036 0.012 0.952
#> SRR1313153 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313156 3 0.4217 0.85129 0.100 0.032 0.868
#> SRR1313155 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313157 1 0.6187 0.71752 0.724 0.028 0.248
#> SRR1313158 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313161 1 0.6264 0.70694 0.716 0.028 0.256
#> SRR1313159 2 0.6669 -0.00667 0.008 0.524 0.468
#> SRR1313160 1 0.6337 0.69538 0.708 0.028 0.264
#> SRR1313162 3 0.4469 0.84251 0.120 0.028 0.852
#> SRR1313163 3 0.4217 0.85129 0.100 0.032 0.868
#> SRR1313165 1 0.6337 0.69538 0.708 0.028 0.264
#> SRR1313166 3 0.1337 0.86864 0.016 0.012 0.972
#> SRR1313164 3 0.0237 0.86310 0.000 0.004 0.996
#> SRR1313167 3 0.7129 0.34650 0.392 0.028 0.580
#> SRR1313168 1 0.6187 0.71752 0.724 0.028 0.248
#> SRR1313170 2 0.6669 -0.00667 0.008 0.524 0.468
#> SRR1313169 1 0.6187 0.71752 0.724 0.028 0.248
#> SRR1313172 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313171 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313174 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.86368 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313175 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313178 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313179 2 0.1015 0.95596 0.008 0.980 0.012
#> SRR1313180 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313181 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313188 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313187 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313186 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313194 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313195 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313196 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313197 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313198 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313199 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313200 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313201 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313203 3 0.3038 0.82579 0.000 0.104 0.896
#> SRR1313204 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313210 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313209 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313216 3 0.4235 0.75235 0.000 0.176 0.824
#> SRR1313217 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313219 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313220 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313226 2 0.0237 0.97067 0.004 0.996 0.000
#> SRR1313227 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.97279 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.97279 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0336 0.878674 0.008 0.000 0.000 0.992
#> SRR1313063 4 0.0188 0.879094 0.004 0.000 0.000 0.996
#> SRR1313064 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313065 1 0.4998 0.001040 0.512 0.000 0.000 0.488
#> SRR1313066 4 0.1118 0.872752 0.036 0.000 0.000 0.964
#> SRR1313067 1 0.4720 0.339259 0.672 0.000 0.004 0.324
#> SRR1313068 4 0.1118 0.872752 0.036 0.000 0.000 0.964
#> SRR1313069 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.1867 0.851983 0.072 0.000 0.000 0.928
#> SRR1313077 1 0.4977 0.092982 0.540 0.000 0.000 0.460
#> SRR1313078 1 0.3837 0.218909 0.776 0.000 0.224 0.000
#> SRR1313079 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.1118 0.872752 0.036 0.000 0.000 0.964
#> SRR1313081 4 0.3356 0.747304 0.176 0.000 0.000 0.824
#> SRR1313082 1 0.4998 0.001040 0.512 0.000 0.000 0.488
#> SRR1313083 1 0.4632 0.364636 0.688 0.000 0.004 0.308
#> SRR1313084 4 0.0469 0.878142 0.012 0.000 0.000 0.988
#> SRR1313085 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.1716 0.857158 0.064 0.000 0.000 0.936
#> SRR1313087 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.879243 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.1118 0.872752 0.036 0.000 0.000 0.964
#> SRR1313092 1 0.4614 0.222837 0.752 0.004 0.228 0.016
#> SRR1313090 1 0.6901 0.350921 0.608 0.020 0.280 0.092
#> SRR1313091 3 0.5816 0.285771 0.392 0.036 0.572 0.000
#> SRR1313093 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313095 1 0.3444 0.399238 0.868 0.012 0.104 0.016
#> SRR1313096 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313094 3 0.4584 0.400007 0.300 0.004 0.696 0.000
#> SRR1313097 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313099 3 0.1302 0.590540 0.044 0.000 0.956 0.000
#> SRR1313098 1 0.3335 0.390667 0.856 0.000 0.128 0.016
#> SRR1313101 1 0.5331 0.282677 0.644 0.024 0.332 0.000
#> SRR1313102 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313103 3 0.3447 0.564360 0.128 0.020 0.852 0.000
#> SRR1313100 4 0.3448 0.767328 0.168 0.004 0.000 0.828
#> SRR1313105 3 0.4574 0.486979 0.220 0.024 0.756 0.000
#> SRR1313104 3 0.5626 0.319581 0.384 0.028 0.588 0.000
#> SRR1313107 3 0.1302 0.590540 0.044 0.000 0.956 0.000
#> SRR1313106 2 0.7527 -0.068960 0.192 0.452 0.356 0.000
#> SRR1313109 3 0.5250 0.406954 0.316 0.024 0.660 0.000
#> SRR1313108 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313111 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313110 1 0.5210 0.302145 0.652 0.008 0.332 0.008
#> SRR1313112 1 0.5331 0.282677 0.644 0.024 0.332 0.000
#> SRR1313113 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313115 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313114 1 0.5515 0.349962 0.688 0.012 0.272 0.028
#> SRR1313117 1 0.5331 0.282677 0.644 0.024 0.332 0.000
#> SRR1313118 1 0.6226 0.207529 0.548 0.008 0.040 0.404
#> SRR1313116 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313120 3 0.1302 0.590540 0.044 0.000 0.956 0.000
#> SRR1313119 1 0.5487 0.287353 0.644 0.024 0.328 0.004
#> SRR1313122 1 0.5510 0.217093 0.600 0.024 0.376 0.000
#> SRR1313124 1 0.5331 0.282677 0.644 0.024 0.332 0.000
#> SRR1313121 4 0.6300 -0.066381 0.476 0.020 0.024 0.480
#> SRR1313125 1 0.5331 0.282677 0.644 0.024 0.332 0.000
#> SRR1313127 1 0.3335 0.390667 0.856 0.000 0.128 0.016
#> SRR1313123 1 0.3547 0.378464 0.840 0.000 0.144 0.016
#> SRR1313128 1 0.4989 -0.269609 0.528 0.000 0.472 0.000
#> SRR1313126 1 0.3441 0.397637 0.856 0.000 0.120 0.024
#> SRR1313130 2 0.5972 0.546856 0.176 0.692 0.132 0.000
#> SRR1313132 1 0.4746 -0.069366 0.632 0.000 0.368 0.000
#> SRR1313129 3 0.5686 0.324068 0.376 0.032 0.592 0.000
#> SRR1313133 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313131 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313134 3 0.3907 0.568458 0.232 0.000 0.768 0.000
#> SRR1313135 4 0.4608 0.562510 0.304 0.000 0.004 0.692
#> SRR1313136 1 0.3597 0.372745 0.836 0.000 0.148 0.016
#> SRR1313137 1 0.4996 0.015329 0.516 0.000 0.000 0.484
#> SRR1313138 1 0.6877 0.404023 0.608 0.004 0.232 0.156
#> SRR1313140 4 0.4008 0.672520 0.244 0.000 0.000 0.756
#> SRR1313141 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313139 4 0.4008 0.672520 0.244 0.000 0.000 0.756
#> SRR1313143 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313142 1 0.3647 0.367850 0.832 0.000 0.152 0.016
#> SRR1313144 4 0.4382 0.579097 0.296 0.000 0.000 0.704
#> SRR1313145 1 0.4214 0.280963 0.780 0.000 0.204 0.016
#> SRR1313146 1 0.3647 0.367850 0.832 0.000 0.152 0.016
#> SRR1313147 4 0.4996 0.040249 0.484 0.000 0.000 0.516
#> SRR1313150 1 0.4998 0.000831 0.512 0.000 0.000 0.488
#> SRR1313149 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313152 1 0.4996 0.015329 0.516 0.000 0.000 0.484
#> SRR1313151 1 0.3647 0.367850 0.832 0.000 0.152 0.016
#> SRR1313154 1 0.4831 0.122943 0.704 0.000 0.280 0.016
#> SRR1313153 1 0.3597 0.372745 0.836 0.000 0.148 0.016
#> SRR1313156 1 0.5004 0.177707 0.604 0.004 0.392 0.000
#> SRR1313155 1 0.3647 0.367850 0.832 0.000 0.152 0.016
#> SRR1313157 1 0.4996 0.015329 0.516 0.000 0.000 0.484
#> SRR1313158 1 0.3597 0.372745 0.836 0.000 0.148 0.016
#> SRR1313161 1 0.4992 0.039720 0.524 0.000 0.000 0.476
#> SRR1313159 2 0.7426 0.141234 0.224 0.512 0.264 0.000
#> SRR1313160 1 0.5285 0.057291 0.524 0.000 0.008 0.468
#> SRR1313162 1 0.3597 0.372745 0.836 0.000 0.148 0.016
#> SRR1313163 1 0.5004 0.177707 0.604 0.004 0.392 0.000
#> SRR1313165 1 0.5285 0.057291 0.524 0.000 0.008 0.468
#> SRR1313166 1 0.4679 -0.048728 0.648 0.000 0.352 0.000
#> SRR1313164 3 0.3710 0.530949 0.192 0.004 0.804 0.000
#> SRR1313167 1 0.4685 0.466609 0.784 0.000 0.060 0.156
#> SRR1313168 1 0.4996 0.015329 0.516 0.000 0.000 0.484
#> SRR1313170 2 0.7426 0.141234 0.224 0.512 0.264 0.000
#> SRR1313169 1 0.4996 0.015329 0.516 0.000 0.000 0.484
#> SRR1313172 3 0.1302 0.590540 0.044 0.000 0.956 0.000
#> SRR1313171 3 0.1389 0.590860 0.048 0.000 0.952 0.000
#> SRR1313174 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313173 3 0.4193 0.557841 0.268 0.000 0.732 0.000
#> SRR1313176 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313178 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0707 0.947980 0.020 0.980 0.000 0.000
#> SRR1313180 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313181 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313187 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313186 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313195 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313196 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313197 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313199 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313201 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313203 3 0.5672 0.460477 0.188 0.100 0.712 0.000
#> SRR1313204 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313209 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313216 3 0.7146 0.250530 0.336 0.148 0.516 0.000
#> SRR1313217 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313219 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313220 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.0188 0.962398 0.004 0.996 0.000 0.000
#> SRR1313227 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.964324 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.964324 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.2690 0.8265 0.156 0.000 0.000 0.844 0.000
#> SRR1313063 4 0.1197 0.8289 0.048 0.000 0.000 0.952 0.000
#> SRR1313064 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 1 0.3916 0.3633 0.732 0.000 0.012 0.256 0.000
#> SRR1313066 4 0.3756 0.7973 0.248 0.000 0.008 0.744 0.000
#> SRR1313067 1 0.3609 0.4665 0.836 0.000 0.016 0.112 0.036
#> SRR1313068 4 0.3756 0.7973 0.248 0.000 0.008 0.744 0.000
#> SRR1313069 4 0.2230 0.8335 0.116 0.000 0.000 0.884 0.000
#> SRR1313070 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.2074 0.8336 0.104 0.000 0.000 0.896 0.000
#> SRR1313074 4 0.1043 0.8272 0.040 0.000 0.000 0.960 0.000
#> SRR1313075 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.3814 0.7524 0.276 0.000 0.004 0.720 0.000
#> SRR1313077 1 0.5264 0.2491 0.652 0.000 0.092 0.256 0.000
#> SRR1313078 5 0.5884 0.0449 0.420 0.000 0.100 0.000 0.480
#> SRR1313079 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.3756 0.7973 0.248 0.000 0.008 0.744 0.000
#> SRR1313081 4 0.4288 0.6736 0.384 0.000 0.004 0.612 0.000
#> SRR1313082 1 0.3890 0.3682 0.736 0.000 0.012 0.252 0.000
#> SRR1313083 1 0.3346 0.4609 0.856 0.000 0.016 0.092 0.036
#> SRR1313084 4 0.3177 0.8166 0.208 0.000 0.000 0.792 0.000
#> SRR1313085 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.3636 0.7590 0.272 0.000 0.000 0.728 0.000
#> SRR1313087 4 0.0000 0.8157 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.2230 0.8335 0.116 0.000 0.000 0.884 0.000
#> SRR1313089 4 0.3756 0.7973 0.248 0.000 0.008 0.744 0.000
#> SRR1313092 1 0.6420 0.0669 0.448 0.000 0.176 0.000 0.376
#> SRR1313090 3 0.5504 0.4168 0.448 0.000 0.488 0.064 0.000
#> SRR1313091 3 0.5316 0.6641 0.152 0.004 0.688 0.000 0.156
#> SRR1313093 5 0.0000 0.7059 0.000 0.000 0.000 0.000 1.000
#> SRR1313095 1 0.6171 0.1661 0.556 0.000 0.204 0.000 0.240
#> SRR1313096 5 0.0162 0.7061 0.000 0.000 0.004 0.000 0.996
#> SRR1313094 3 0.5974 0.4565 0.144 0.000 0.564 0.000 0.292
#> SRR1313097 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313099 5 0.4182 0.4144 0.004 0.000 0.352 0.000 0.644
#> SRR1313098 1 0.5917 0.2720 0.564 0.000 0.132 0.000 0.304
#> SRR1313101 3 0.4227 0.5849 0.420 0.000 0.580 0.000 0.000
#> SRR1313102 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313103 5 0.5443 0.1207 0.060 0.000 0.436 0.000 0.504
#> SRR1313100 4 0.4588 0.6175 0.380 0.000 0.016 0.604 0.000
#> SRR1313105 3 0.5571 0.3398 0.084 0.000 0.568 0.000 0.348
#> SRR1313104 3 0.5155 0.6567 0.140 0.000 0.692 0.000 0.168
#> SRR1313107 5 0.4182 0.4144 0.004 0.000 0.352 0.000 0.644
#> SRR1313106 3 0.5407 0.1776 0.048 0.424 0.524 0.000 0.004
#> SRR1313109 3 0.5115 0.5663 0.092 0.000 0.676 0.000 0.232
#> SRR1313108 5 0.0000 0.7059 0.000 0.000 0.000 0.000 1.000
#> SRR1313111 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313110 3 0.4415 0.5504 0.444 0.000 0.552 0.004 0.000
#> SRR1313112 3 0.4227 0.5849 0.420 0.000 0.580 0.000 0.000
#> SRR1313113 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313115 5 0.0000 0.7059 0.000 0.000 0.000 0.000 1.000
#> SRR1313114 1 0.5423 -0.4270 0.500 0.000 0.452 0.008 0.040
#> SRR1313117 3 0.4227 0.5849 0.420 0.000 0.580 0.000 0.000
#> SRR1313118 1 0.5526 0.3914 0.648 0.000 0.152 0.200 0.000
#> SRR1313116 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313120 5 0.4182 0.4144 0.004 0.000 0.352 0.000 0.644
#> SRR1313119 3 0.4235 0.5795 0.424 0.000 0.576 0.000 0.000
#> SRR1313122 3 0.4225 0.6179 0.364 0.000 0.632 0.000 0.004
#> SRR1313124 3 0.4227 0.5849 0.420 0.000 0.580 0.000 0.000
#> SRR1313121 1 0.5493 0.3062 0.632 0.000 0.112 0.256 0.000
#> SRR1313125 3 0.4227 0.5849 0.420 0.000 0.580 0.000 0.000
#> SRR1313127 1 0.5917 0.2720 0.564 0.000 0.132 0.000 0.304
#> SRR1313123 1 0.6050 0.2493 0.544 0.000 0.144 0.000 0.312
#> SRR1313128 5 0.4613 0.4721 0.200 0.000 0.072 0.000 0.728
#> SRR1313126 1 0.5834 0.2641 0.584 0.000 0.132 0.000 0.284
#> SRR1313130 2 0.5028 0.5008 0.072 0.668 0.260 0.000 0.000
#> SRR1313132 5 0.5915 0.2514 0.324 0.000 0.124 0.000 0.552
#> SRR1313129 3 0.5079 0.6607 0.136 0.000 0.700 0.000 0.164
#> SRR1313133 5 0.0162 0.7061 0.000 0.000 0.004 0.000 0.996
#> SRR1313131 5 0.0000 0.7059 0.000 0.000 0.000 0.000 1.000
#> SRR1313134 5 0.1597 0.6834 0.012 0.000 0.048 0.000 0.940
#> SRR1313135 1 0.4653 -0.3259 0.516 0.000 0.012 0.472 0.000
#> SRR1313136 1 0.5903 0.2387 0.548 0.000 0.120 0.000 0.332
#> SRR1313137 1 0.3863 0.3738 0.740 0.000 0.012 0.248 0.000
#> SRR1313138 1 0.5420 -0.0596 0.592 0.000 0.332 0.076 0.000
#> SRR1313140 4 0.4294 0.4445 0.468 0.000 0.000 0.532 0.000
#> SRR1313141 5 0.0162 0.7061 0.000 0.000 0.004 0.000 0.996
#> SRR1313139 4 0.4294 0.4445 0.468 0.000 0.000 0.532 0.000
#> SRR1313143 5 0.0162 0.7061 0.000 0.000 0.004 0.000 0.996
#> SRR1313142 1 0.5916 0.2316 0.544 0.000 0.120 0.000 0.336
#> SRR1313144 1 0.4302 -0.3370 0.520 0.000 0.000 0.480 0.000
#> SRR1313145 1 0.6066 0.0867 0.488 0.000 0.124 0.000 0.388
#> SRR1313146 1 0.5916 0.2316 0.544 0.000 0.120 0.000 0.336
#> SRR1313147 1 0.4130 0.3045 0.696 0.000 0.012 0.292 0.000
#> SRR1313150 1 0.3890 0.3678 0.736 0.000 0.012 0.252 0.000
#> SRR1313149 5 0.0162 0.7061 0.000 0.000 0.004 0.000 0.996
#> SRR1313152 1 0.3863 0.3738 0.740 0.000 0.012 0.248 0.000
#> SRR1313151 1 0.5916 0.2316 0.544 0.000 0.120 0.000 0.336
#> SRR1313154 5 0.6030 0.0599 0.420 0.000 0.116 0.000 0.464
#> SRR1313153 1 0.5903 0.2387 0.548 0.000 0.120 0.000 0.332
#> SRR1313156 3 0.6381 0.3559 0.384 0.000 0.448 0.000 0.168
#> SRR1313155 1 0.5916 0.2316 0.544 0.000 0.120 0.000 0.336
#> SRR1313157 1 0.3863 0.3738 0.740 0.000 0.012 0.248 0.000
#> SRR1313158 1 0.5903 0.2387 0.548 0.000 0.120 0.000 0.332
#> SRR1313161 1 0.3807 0.3838 0.748 0.000 0.012 0.240 0.000
#> SRR1313159 2 0.5765 -0.0221 0.088 0.488 0.424 0.000 0.000
#> SRR1313160 1 0.3970 0.3891 0.744 0.000 0.020 0.236 0.000
#> SRR1313162 1 0.5903 0.2387 0.548 0.000 0.120 0.000 0.332
#> SRR1313163 3 0.6381 0.3559 0.384 0.000 0.448 0.000 0.168
#> SRR1313165 1 0.3970 0.3891 0.744 0.000 0.020 0.236 0.000
#> SRR1313166 5 0.5865 0.2369 0.332 0.000 0.116 0.000 0.552
#> SRR1313164 5 0.5965 0.1159 0.112 0.000 0.392 0.000 0.496
#> SRR1313167 1 0.6700 0.3183 0.620 0.000 0.140 0.104 0.136
#> SRR1313168 1 0.3863 0.3738 0.740 0.000 0.012 0.248 0.000
#> SRR1313170 2 0.5765 -0.0221 0.088 0.488 0.424 0.000 0.000
#> SRR1313169 1 0.3863 0.3738 0.740 0.000 0.012 0.248 0.000
#> SRR1313172 5 0.4151 0.4204 0.004 0.000 0.344 0.000 0.652
#> SRR1313171 5 0.4135 0.4265 0.004 0.000 0.340 0.000 0.656
#> SRR1313174 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313173 5 0.0000 0.7059 0.000 0.000 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313178 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0798 0.9544 0.016 0.976 0.008 0.000 0.000
#> SRR1313180 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313181 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313184 2 0.0404 0.9642 0.000 0.988 0.012 0.000 0.000
#> SRR1313185 2 0.0404 0.9642 0.000 0.988 0.012 0.000 0.000
#> SRR1313188 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313187 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313186 2 0.0404 0.9642 0.000 0.988 0.012 0.000 0.000
#> SRR1313189 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313195 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313196 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313197 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313198 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313199 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313201 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 2 0.0404 0.9642 0.000 0.988 0.012 0.000 0.000
#> SRR1313203 3 0.2719 0.3563 0.004 0.000 0.852 0.000 0.144
#> SRR1313204 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313209 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313211 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313215 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313213 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 3 0.6972 0.5620 0.144 0.116 0.592 0.000 0.148
#> SRR1313217 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313219 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313220 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313226 2 0.0324 0.9684 0.004 0.992 0.004 0.000 0.000
#> SRR1313227 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9716 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.3163 0.73422 0.212 0.000 0.000 0.780 0.004 0.004
#> SRR1313063 4 0.2006 0.77324 0.104 0.000 0.000 0.892 0.000 0.004
#> SRR1313064 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313065 1 0.2743 0.77997 0.828 0.000 0.000 0.008 0.164 0.000
#> SRR1313066 4 0.4952 0.51121 0.408 0.000 0.000 0.524 0.000 0.068
#> SRR1313067 1 0.3531 0.61842 0.672 0.000 0.000 0.000 0.328 0.000
#> SRR1313068 4 0.4978 0.47304 0.432 0.000 0.000 0.500 0.000 0.068
#> SRR1313069 4 0.2738 0.75667 0.176 0.000 0.000 0.820 0.000 0.004
#> SRR1313070 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313071 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313072 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313073 4 0.2595 0.76123 0.160 0.000 0.000 0.836 0.000 0.004
#> SRR1313074 4 0.1501 0.77332 0.076 0.000 0.000 0.924 0.000 0.000
#> SRR1313075 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313076 4 0.4387 0.50774 0.404 0.000 0.000 0.572 0.020 0.004
#> SRR1313077 1 0.6656 0.10747 0.476 0.000 0.004 0.116 0.324 0.080
#> SRR1313078 5 0.5547 -0.00415 0.116 0.000 0.004 0.000 0.456 0.424
#> SRR1313079 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313080 4 0.4978 0.47304 0.432 0.000 0.000 0.500 0.000 0.068
#> SRR1313081 4 0.5598 0.36766 0.408 0.000 0.000 0.464 0.124 0.004
#> SRR1313082 1 0.3134 0.77555 0.808 0.000 0.000 0.024 0.168 0.000
#> SRR1313083 1 0.3607 0.59736 0.652 0.000 0.000 0.000 0.348 0.000
#> SRR1313084 4 0.4495 0.65702 0.276 0.000 0.000 0.660 0.000 0.064
#> SRR1313085 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313086 4 0.4254 0.50544 0.404 0.000 0.000 0.576 0.020 0.000
#> SRR1313087 4 0.0458 0.76924 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313088 4 0.2738 0.75667 0.176 0.000 0.000 0.820 0.000 0.004
#> SRR1313089 4 0.4952 0.51121 0.408 0.000 0.000 0.524 0.000 0.068
#> SRR1313092 5 0.3755 0.68076 0.044 0.000 0.084 0.000 0.816 0.056
#> SRR1313090 3 0.6001 0.46091 0.348 0.000 0.412 0.000 0.240 0.000
#> SRR1313091 3 0.5478 0.66003 0.072 0.004 0.648 0.000 0.224 0.052
#> SRR1313093 6 0.2562 0.76172 0.000 0.000 0.000 0.000 0.172 0.828
#> SRR1313095 5 0.4680 0.42916 0.200 0.000 0.120 0.000 0.680 0.000
#> SRR1313096 6 0.2823 0.75135 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313094 3 0.6258 0.43154 0.028 0.000 0.504 0.000 0.264 0.204
#> SRR1313097 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313099 6 0.5091 0.50350 0.004 0.000 0.364 0.000 0.076 0.556
#> SRR1313098 5 0.2420 0.72641 0.076 0.000 0.040 0.000 0.884 0.000
#> SRR1313101 3 0.5786 0.60209 0.256 0.000 0.504 0.000 0.240 0.000
#> SRR1313102 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313103 3 0.5837 -0.19846 0.012 0.000 0.448 0.000 0.132 0.408
#> SRR1313100 1 0.4026 0.04655 0.636 0.000 0.000 0.348 0.016 0.000
#> SRR1313105 3 0.5796 0.35457 0.008 0.000 0.540 0.000 0.192 0.260
#> SRR1313104 3 0.5291 0.65352 0.056 0.000 0.652 0.000 0.232 0.060
#> SRR1313107 6 0.5091 0.50350 0.004 0.000 0.364 0.000 0.076 0.556
#> SRR1313106 3 0.4979 0.19161 0.024 0.424 0.524 0.000 0.028 0.000
#> SRR1313109 3 0.5120 0.59421 0.012 0.000 0.652 0.000 0.216 0.120
#> SRR1313108 6 0.2562 0.76172 0.000 0.000 0.000 0.000 0.172 0.828
#> SRR1313111 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313110 3 0.5867 0.57850 0.280 0.000 0.480 0.000 0.240 0.000
#> SRR1313112 3 0.5786 0.60209 0.256 0.000 0.504 0.000 0.240 0.000
#> SRR1313113 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313115 6 0.2597 0.76099 0.000 0.000 0.000 0.000 0.176 0.824
#> SRR1313114 3 0.6093 0.42613 0.284 0.000 0.380 0.000 0.336 0.000
#> SRR1313117 3 0.5786 0.60209 0.256 0.000 0.504 0.000 0.240 0.000
#> SRR1313118 1 0.4628 0.59988 0.684 0.000 0.112 0.000 0.204 0.000
#> SRR1313116 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313120 6 0.5091 0.50350 0.004 0.000 0.364 0.000 0.076 0.556
#> SRR1313119 3 0.5801 0.59855 0.260 0.000 0.500 0.000 0.240 0.000
#> SRR1313122 3 0.5488 0.62281 0.216 0.000 0.568 0.000 0.216 0.000
#> SRR1313124 3 0.5786 0.60209 0.256 0.000 0.504 0.000 0.240 0.000
#> SRR1313121 1 0.3946 0.70982 0.772 0.000 0.088 0.004 0.136 0.000
#> SRR1313125 3 0.5786 0.60209 0.256 0.000 0.504 0.000 0.240 0.000
#> SRR1313127 5 0.2420 0.72641 0.076 0.000 0.040 0.000 0.884 0.000
#> SRR1313123 5 0.1938 0.76002 0.040 0.000 0.036 0.000 0.920 0.004
#> SRR1313128 6 0.4093 0.24494 0.008 0.000 0.000 0.000 0.476 0.516
#> SRR1313126 5 0.3819 0.59235 0.172 0.000 0.064 0.000 0.764 0.000
#> SRR1313130 2 0.4985 0.49903 0.068 0.668 0.236 0.000 0.028 0.000
#> SRR1313132 5 0.3596 0.47867 0.008 0.000 0.008 0.000 0.740 0.244
#> SRR1313129 3 0.5190 0.66043 0.056 0.000 0.664 0.000 0.224 0.056
#> SRR1313133 6 0.2823 0.75135 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313131 6 0.2562 0.76172 0.000 0.000 0.000 0.000 0.172 0.828
#> SRR1313134 6 0.3456 0.74764 0.000 0.000 0.040 0.000 0.172 0.788
#> SRR1313135 1 0.4941 0.42340 0.640 0.000 0.000 0.236 0.124 0.000
#> SRR1313136 5 0.0363 0.79160 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1313137 1 0.2527 0.78291 0.832 0.000 0.000 0.000 0.168 0.000
#> SRR1313138 1 0.5599 0.09390 0.520 0.000 0.312 0.000 0.168 0.000
#> SRR1313140 1 0.4363 0.25319 0.636 0.000 0.000 0.324 0.040 0.000
#> SRR1313141 6 0.2823 0.75135 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313139 1 0.4363 0.25319 0.636 0.000 0.000 0.324 0.040 0.000
#> SRR1313143 6 0.2823 0.75135 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313142 5 0.0405 0.79187 0.008 0.000 0.000 0.000 0.988 0.004
#> SRR1313144 1 0.4305 0.45897 0.700 0.000 0.000 0.232 0.068 0.000
#> SRR1313145 5 0.1563 0.73811 0.012 0.000 0.000 0.000 0.932 0.056
#> SRR1313146 5 0.0405 0.79187 0.008 0.000 0.000 0.000 0.988 0.004
#> SRR1313147 1 0.3417 0.75949 0.796 0.000 0.000 0.044 0.160 0.000
#> SRR1313150 1 0.2632 0.78154 0.832 0.000 0.000 0.004 0.164 0.000
#> SRR1313149 6 0.2823 0.75135 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313152 1 0.2527 0.78291 0.832 0.000 0.000 0.000 0.168 0.000
#> SRR1313151 5 0.0405 0.79187 0.008 0.000 0.000 0.000 0.988 0.004
#> SRR1313154 5 0.2431 0.65212 0.008 0.000 0.000 0.000 0.860 0.132
#> SRR1313153 5 0.0363 0.79160 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1313156 5 0.3910 0.14180 0.008 0.000 0.328 0.000 0.660 0.004
#> SRR1313155 5 0.0405 0.79187 0.008 0.000 0.000 0.000 0.988 0.004
#> SRR1313157 1 0.2527 0.78291 0.832 0.000 0.000 0.000 0.168 0.000
#> SRR1313158 5 0.0363 0.79160 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1313161 1 0.2597 0.78177 0.824 0.000 0.000 0.000 0.176 0.000
#> SRR1313159 2 0.5874 -0.02900 0.072 0.488 0.392 0.000 0.048 0.000
#> SRR1313160 1 0.2848 0.77973 0.816 0.000 0.008 0.000 0.176 0.000
#> SRR1313162 5 0.0363 0.79160 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1313163 5 0.3910 0.14180 0.008 0.000 0.328 0.000 0.660 0.004
#> SRR1313165 1 0.2848 0.77973 0.816 0.000 0.008 0.000 0.176 0.000
#> SRR1313166 5 0.3298 0.49848 0.008 0.000 0.000 0.000 0.756 0.236
#> SRR1313164 6 0.6406 0.17513 0.024 0.000 0.368 0.000 0.204 0.404
#> SRR1313167 1 0.5408 0.26413 0.476 0.000 0.116 0.000 0.408 0.000
#> SRR1313168 1 0.2527 0.78291 0.832 0.000 0.000 0.000 0.168 0.000
#> SRR1313170 2 0.5874 -0.02900 0.072 0.488 0.392 0.000 0.048 0.000
#> SRR1313169 1 0.2527 0.78291 0.832 0.000 0.000 0.000 0.168 0.000
#> SRR1313172 6 0.5050 0.51801 0.004 0.000 0.348 0.000 0.076 0.572
#> SRR1313171 6 0.5083 0.52384 0.004 0.000 0.344 0.000 0.080 0.572
#> SRR1313174 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313173 6 0.2562 0.76172 0.000 0.000 0.000 0.000 0.172 0.828
#> SRR1313176 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313178 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.0767 0.95528 0.012 0.976 0.008 0.000 0.004 0.000
#> SRR1313180 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313181 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313184 2 0.0363 0.96384 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1313185 2 0.0363 0.96384 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1313188 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313187 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313186 2 0.0363 0.96384 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1313189 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313192 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313194 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313195 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313196 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313197 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313198 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313199 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313201 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 2 0.0363 0.96384 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1313203 3 0.0909 0.39611 0.012 0.000 0.968 0.000 0.000 0.020
#> SRR1313204 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313209 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313211 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313212 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313215 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313213 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 3 0.6919 0.56669 0.072 0.116 0.560 0.000 0.200 0.052
#> SRR1313217 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313219 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313220 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313222 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313226 2 0.0260 0.96816 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313227 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.97137 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "kmeans"]
# you can also extract it by
# res = res_list["ATC:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.599 0.932 0.949 0.4568 0.548 0.548
#> 3 3 0.997 0.962 0.976 0.4406 0.785 0.611
#> 4 4 0.879 0.860 0.939 0.1156 0.853 0.613
#> 5 5 0.763 0.695 0.777 0.0676 0.905 0.675
#> 6 6 0.763 0.733 0.809 0.0441 0.908 0.615
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.671 0.878 0.824 0.176
#> SRR1313063 1 0.671 0.878 0.824 0.176
#> SRR1313064 1 0.671 0.878 0.824 0.176
#> SRR1313065 1 0.671 0.878 0.824 0.176
#> SRR1313066 1 0.671 0.878 0.824 0.176
#> SRR1313067 1 0.000 0.917 1.000 0.000
#> SRR1313068 1 0.671 0.878 0.824 0.176
#> SRR1313069 1 0.671 0.878 0.824 0.176
#> SRR1313070 1 0.671 0.878 0.824 0.176
#> SRR1313071 1 0.671 0.878 0.824 0.176
#> SRR1313072 1 0.671 0.878 0.824 0.176
#> SRR1313073 1 0.671 0.878 0.824 0.176
#> SRR1313074 1 0.671 0.878 0.824 0.176
#> SRR1313075 1 0.671 0.878 0.824 0.176
#> SRR1313076 1 0.671 0.878 0.824 0.176
#> SRR1313077 1 0.000 0.917 1.000 0.000
#> SRR1313078 1 0.000 0.917 1.000 0.000
#> SRR1313079 1 0.671 0.878 0.824 0.176
#> SRR1313080 1 0.671 0.878 0.824 0.176
#> SRR1313081 1 0.000 0.917 1.000 0.000
#> SRR1313082 1 0.671 0.878 0.824 0.176
#> SRR1313083 1 0.000 0.917 1.000 0.000
#> SRR1313084 1 0.671 0.878 0.824 0.176
#> SRR1313085 1 0.671 0.878 0.824 0.176
#> SRR1313086 1 0.671 0.878 0.824 0.176
#> SRR1313087 1 0.671 0.878 0.824 0.176
#> SRR1313088 1 0.671 0.878 0.824 0.176
#> SRR1313089 1 0.671 0.878 0.824 0.176
#> SRR1313092 1 0.000 0.917 1.000 0.000
#> SRR1313090 1 0.671 0.878 0.824 0.176
#> SRR1313091 2 0.671 0.781 0.176 0.824
#> SRR1313093 1 0.000 0.917 1.000 0.000
#> SRR1313095 1 0.000 0.917 1.000 0.000
#> SRR1313096 1 0.000 0.917 1.000 0.000
#> SRR1313094 1 0.000 0.917 1.000 0.000
#> SRR1313097 1 0.000 0.917 1.000 0.000
#> SRR1313099 1 0.000 0.917 1.000 0.000
#> SRR1313098 1 0.000 0.917 1.000 0.000
#> SRR1313101 1 0.671 0.878 0.824 0.176
#> SRR1313102 1 0.000 0.917 1.000 0.000
#> SRR1313103 1 0.000 0.917 1.000 0.000
#> SRR1313100 1 0.671 0.878 0.824 0.176
#> SRR1313105 1 0.000 0.917 1.000 0.000
#> SRR1313104 1 0.000 0.917 1.000 0.000
#> SRR1313107 1 0.000 0.917 1.000 0.000
#> SRR1313106 1 0.689 0.870 0.816 0.184
#> SRR1313109 1 0.000 0.917 1.000 0.000
#> SRR1313108 1 0.000 0.917 1.000 0.000
#> SRR1313111 1 0.000 0.917 1.000 0.000
#> SRR1313110 1 0.541 0.891 0.876 0.124
#> SRR1313112 1 0.671 0.878 0.824 0.176
#> SRR1313113 1 0.000 0.917 1.000 0.000
#> SRR1313115 1 0.000 0.917 1.000 0.000
#> SRR1313114 1 0.184 0.911 0.972 0.028
#> SRR1313117 1 0.671 0.878 0.824 0.176
#> SRR1313118 1 0.671 0.878 0.824 0.176
#> SRR1313116 1 0.000 0.917 1.000 0.000
#> SRR1313120 1 0.000 0.917 1.000 0.000
#> SRR1313119 1 0.671 0.878 0.824 0.176
#> SRR1313122 1 0.000 0.917 1.000 0.000
#> SRR1313124 1 0.000 0.917 1.000 0.000
#> SRR1313121 1 0.671 0.878 0.824 0.176
#> SRR1313125 1 0.000 0.917 1.000 0.000
#> SRR1313127 1 0.000 0.917 1.000 0.000
#> SRR1313123 1 0.000 0.917 1.000 0.000
#> SRR1313128 1 0.000 0.917 1.000 0.000
#> SRR1313126 1 0.000 0.917 1.000 0.000
#> SRR1313130 2 0.000 0.996 0.000 1.000
#> SRR1313132 1 0.000 0.917 1.000 0.000
#> SRR1313129 1 0.000 0.917 1.000 0.000
#> SRR1313133 1 0.000 0.917 1.000 0.000
#> SRR1313131 1 0.000 0.917 1.000 0.000
#> SRR1313134 1 0.000 0.917 1.000 0.000
#> SRR1313135 1 0.000 0.917 1.000 0.000
#> SRR1313136 1 0.000 0.917 1.000 0.000
#> SRR1313137 1 0.671 0.878 0.824 0.176
#> SRR1313138 1 0.671 0.878 0.824 0.176
#> SRR1313140 1 0.671 0.878 0.824 0.176
#> SRR1313141 1 0.000 0.917 1.000 0.000
#> SRR1313139 1 0.671 0.878 0.824 0.176
#> SRR1313143 1 0.000 0.917 1.000 0.000
#> SRR1313142 1 0.000 0.917 1.000 0.000
#> SRR1313144 1 0.671 0.878 0.824 0.176
#> SRR1313145 1 0.000 0.917 1.000 0.000
#> SRR1313146 1 0.000 0.917 1.000 0.000
#> SRR1313147 1 0.671 0.878 0.824 0.176
#> SRR1313150 1 0.671 0.878 0.824 0.176
#> SRR1313149 1 0.000 0.917 1.000 0.000
#> SRR1313152 1 0.671 0.878 0.824 0.176
#> SRR1313151 1 0.000 0.917 1.000 0.000
#> SRR1313154 1 0.000 0.917 1.000 0.000
#> SRR1313153 1 0.000 0.917 1.000 0.000
#> SRR1313156 1 0.000 0.917 1.000 0.000
#> SRR1313155 1 0.000 0.917 1.000 0.000
#> SRR1313157 1 0.671 0.878 0.824 0.176
#> SRR1313158 1 0.000 0.917 1.000 0.000
#> SRR1313161 1 0.671 0.878 0.824 0.176
#> SRR1313159 1 0.000 0.917 1.000 0.000
#> SRR1313160 1 0.671 0.878 0.824 0.176
#> SRR1313162 1 0.000 0.917 1.000 0.000
#> SRR1313163 1 0.000 0.917 1.000 0.000
#> SRR1313165 1 0.671 0.878 0.824 0.176
#> SRR1313166 1 0.000 0.917 1.000 0.000
#> SRR1313164 1 0.000 0.917 1.000 0.000
#> SRR1313167 1 0.000 0.917 1.000 0.000
#> SRR1313168 1 0.430 0.899 0.912 0.088
#> SRR1313170 1 0.671 0.878 0.824 0.176
#> SRR1313169 1 0.671 0.878 0.824 0.176
#> SRR1313172 1 0.000 0.917 1.000 0.000
#> SRR1313171 1 0.000 0.917 1.000 0.000
#> SRR1313174 2 0.000 0.996 0.000 1.000
#> SRR1313173 1 0.000 0.917 1.000 0.000
#> SRR1313176 2 0.000 0.996 0.000 1.000
#> SRR1313175 2 0.000 0.996 0.000 1.000
#> SRR1313178 2 0.000 0.996 0.000 1.000
#> SRR1313177 2 0.000 0.996 0.000 1.000
#> SRR1313179 2 0.000 0.996 0.000 1.000
#> SRR1313180 2 0.000 0.996 0.000 1.000
#> SRR1313181 2 0.000 0.996 0.000 1.000
#> SRR1313183 2 0.000 0.996 0.000 1.000
#> SRR1313182 2 0.000 0.996 0.000 1.000
#> SRR1313184 2 0.000 0.996 0.000 1.000
#> SRR1313185 2 0.000 0.996 0.000 1.000
#> SRR1313188 2 0.000 0.996 0.000 1.000
#> SRR1313187 2 0.000 0.996 0.000 1.000
#> SRR1313186 2 0.000 0.996 0.000 1.000
#> SRR1313189 2 0.000 0.996 0.000 1.000
#> SRR1313190 2 0.000 0.996 0.000 1.000
#> SRR1313191 2 0.000 0.996 0.000 1.000
#> SRR1313192 2 0.000 0.996 0.000 1.000
#> SRR1313193 2 0.000 0.996 0.000 1.000
#> SRR1313194 2 0.000 0.996 0.000 1.000
#> SRR1313195 2 0.000 0.996 0.000 1.000
#> SRR1313196 2 0.000 0.996 0.000 1.000
#> SRR1313197 2 0.000 0.996 0.000 1.000
#> SRR1313198 2 0.000 0.996 0.000 1.000
#> SRR1313199 2 0.000 0.996 0.000 1.000
#> SRR1313200 2 0.000 0.996 0.000 1.000
#> SRR1313201 2 0.000 0.996 0.000 1.000
#> SRR1313202 2 0.000 0.996 0.000 1.000
#> SRR1313203 1 0.000 0.917 1.000 0.000
#> SRR1313204 2 0.000 0.996 0.000 1.000
#> SRR1313205 2 0.000 0.996 0.000 1.000
#> SRR1313207 2 0.000 0.996 0.000 1.000
#> SRR1313208 2 0.000 0.996 0.000 1.000
#> SRR1313206 2 0.000 0.996 0.000 1.000
#> SRR1313210 2 0.000 0.996 0.000 1.000
#> SRR1313209 2 0.000 0.996 0.000 1.000
#> SRR1313211 2 0.000 0.996 0.000 1.000
#> SRR1313212 2 0.000 0.996 0.000 1.000
#> SRR1313214 2 0.000 0.996 0.000 1.000
#> SRR1313215 2 0.000 0.996 0.000 1.000
#> SRR1313213 2 0.000 0.996 0.000 1.000
#> SRR1313216 2 0.000 0.996 0.000 1.000
#> SRR1313217 2 0.000 0.996 0.000 1.000
#> SRR1313219 2 0.000 0.996 0.000 1.000
#> SRR1313220 2 0.000 0.996 0.000 1.000
#> SRR1313218 2 0.000 0.996 0.000 1.000
#> SRR1313222 2 0.000 0.996 0.000 1.000
#> SRR1313221 2 0.000 0.996 0.000 1.000
#> SRR1313223 2 0.000 0.996 0.000 1.000
#> SRR1313224 2 0.000 0.996 0.000 1.000
#> SRR1313225 2 0.000 0.996 0.000 1.000
#> SRR1313226 2 0.000 0.996 0.000 1.000
#> SRR1313227 2 0.000 0.996 0.000 1.000
#> SRR1313228 2 0.000 0.996 0.000 1.000
#> SRR1313229 2 0.000 0.996 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313063 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313064 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313065 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313066 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313067 3 0.6305 0.0805 0.484 0.000 0.516
#> SRR1313068 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313069 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313070 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313071 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313072 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313073 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313074 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313075 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313076 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313077 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313078 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313079 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313080 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313081 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313082 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313083 3 0.6286 0.1517 0.464 0.000 0.536
#> SRR1313084 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313085 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313086 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313087 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313088 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313089 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313092 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313090 3 0.6305 0.0809 0.484 0.000 0.516
#> SRR1313091 3 0.3896 0.8325 0.008 0.128 0.864
#> SRR1313093 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313101 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313102 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313100 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313105 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313106 3 0.3532 0.8575 0.008 0.108 0.884
#> SRR1313109 3 0.0237 0.9612 0.004 0.000 0.996
#> SRR1313108 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313110 3 0.2448 0.8980 0.076 0.000 0.924
#> SRR1313112 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313113 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313114 3 0.2796 0.8817 0.092 0.000 0.908
#> SRR1313117 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313118 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313116 3 0.0237 0.9612 0.004 0.000 0.996
#> SRR1313120 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313119 3 0.3267 0.8554 0.116 0.000 0.884
#> SRR1313122 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313121 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313125 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313128 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313126 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313130 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313132 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313129 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313133 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313131 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313134 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313135 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313136 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313137 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313138 3 0.5178 0.6601 0.256 0.000 0.744
#> SRR1313140 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313141 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313139 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313143 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313142 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313144 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313145 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313146 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313147 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313150 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313149 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313152 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313151 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313154 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313153 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313156 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313155 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313157 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313158 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313161 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313159 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313160 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313162 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313163 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313165 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313166 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313164 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313167 3 0.2537 0.8940 0.080 0.000 0.920
#> SRR1313168 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313170 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313169 1 0.1031 1.0000 0.976 0.000 0.024
#> SRR1313172 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313171 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313174 2 0.0237 0.9908 0.004 0.996 0.000
#> SRR1313173 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313176 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313175 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313178 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313177 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313179 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313180 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313181 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313183 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313182 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313184 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313185 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313188 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313187 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313186 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313189 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313190 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313191 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313192 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313193 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313194 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313195 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313196 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313197 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313198 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313199 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313200 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313201 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313202 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313203 3 0.0000 0.9649 0.000 0.000 1.000
#> SRR1313204 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313205 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313207 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313208 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313206 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313210 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313209 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313211 2 0.0592 0.9910 0.012 0.988 0.000
#> SRR1313212 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313214 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313215 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313213 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313216 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313217 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313219 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313220 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313218 2 0.0237 0.9908 0.004 0.996 0.000
#> SRR1313222 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313221 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313223 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313224 2 0.0000 0.9909 0.000 1.000 0.000
#> SRR1313225 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313226 2 0.0424 0.9906 0.008 0.992 0.000
#> SRR1313227 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313228 2 0.0747 0.9909 0.016 0.984 0.000
#> SRR1313229 2 0.0747 0.9909 0.016 0.984 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313067 3 0.3266 0.7486 0.000 0.000 0.832 0.168
#> SRR1313068 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313078 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313079 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313082 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313083 3 0.3569 0.7262 0.000 0.000 0.804 0.196
#> SRR1313084 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313090 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313091 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313093 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313095 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313096 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313094 1 0.2281 0.8396 0.904 0.000 0.096 0.000
#> SRR1313097 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313099 1 0.3688 0.7180 0.792 0.000 0.208 0.000
#> SRR1313098 3 0.4356 0.6279 0.292 0.000 0.708 0.000
#> SRR1313101 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313103 1 0.4277 0.6335 0.720 0.000 0.280 0.000
#> SRR1313100 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313105 1 0.4941 0.3419 0.564 0.000 0.436 0.000
#> SRR1313104 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313107 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313106 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313109 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313108 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313111 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313110 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313112 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313113 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313115 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313114 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313117 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313116 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313120 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313119 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313122 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313124 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313121 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313125 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313127 3 0.3528 0.7236 0.192 0.000 0.808 0.000
#> SRR1313123 3 0.3486 0.7267 0.188 0.000 0.812 0.000
#> SRR1313128 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.3569 0.7204 0.196 0.000 0.804 0.000
#> SRR1313130 3 0.4967 0.0809 0.000 0.452 0.548 0.000
#> SRR1313132 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313133 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313131 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313134 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313135 3 0.4948 0.3506 0.000 0.000 0.560 0.440
#> SRR1313136 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313137 3 0.4877 0.4223 0.000 0.000 0.592 0.408
#> SRR1313138 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313140 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313141 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313139 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313143 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313142 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313144 3 0.4961 0.3302 0.000 0.000 0.552 0.448
#> SRR1313145 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313146 3 0.4356 0.6279 0.292 0.000 0.708 0.000
#> SRR1313147 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313150 4 0.0000 0.9840 0.000 0.000 0.000 1.000
#> SRR1313149 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313152 3 0.4948 0.3506 0.000 0.000 0.560 0.440
#> SRR1313151 1 0.4994 -0.1335 0.520 0.000 0.480 0.000
#> SRR1313154 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313153 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313156 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313155 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313157 4 0.4817 0.2049 0.000 0.000 0.388 0.612
#> SRR1313158 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313161 3 0.4948 0.3506 0.000 0.000 0.560 0.440
#> SRR1313159 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313160 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313162 3 0.4331 0.6333 0.288 0.000 0.712 0.000
#> SRR1313163 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313165 3 0.4866 0.4299 0.000 0.000 0.596 0.404
#> SRR1313166 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313167 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313168 3 0.4304 0.6298 0.000 0.000 0.716 0.284
#> SRR1313170 3 0.0000 0.8346 0.000 0.000 1.000 0.000
#> SRR1313169 3 0.4948 0.3506 0.000 0.000 0.560 0.440
#> SRR1313172 1 0.0188 0.9293 0.996 0.000 0.004 0.000
#> SRR1313171 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313174 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.0000 0.9323 1.000 0.000 0.000 0.000
#> SRR1313176 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313203 3 0.4643 0.3169 0.344 0.000 0.656 0.000
#> SRR1313204 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.4925 0.3089 0.000 0.572 0.428 0.000
#> SRR1313217 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.4356 0.6127 0.000 0.708 0.292 0.000
#> SRR1313227 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9856 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9856 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0162 0.91812 0.004 0.000 0.000 0.996 0.000
#> SRR1313063 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313064 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.4015 0.53613 0.348 0.000 0.000 0.652 0.000
#> SRR1313066 4 0.0510 0.91310 0.016 0.000 0.000 0.984 0.000
#> SRR1313067 1 0.3507 0.57590 0.828 0.000 0.120 0.052 0.000
#> SRR1313068 4 0.1341 0.89131 0.056 0.000 0.000 0.944 0.000
#> SRR1313069 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.0162 0.91812 0.004 0.000 0.000 0.996 0.000
#> SRR1313077 4 0.3561 0.65242 0.260 0.000 0.000 0.740 0.000
#> SRR1313078 5 0.0290 0.94623 0.008 0.000 0.000 0.000 0.992
#> SRR1313079 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.1544 0.88354 0.068 0.000 0.000 0.932 0.000
#> SRR1313081 1 0.4306 -0.17923 0.508 0.000 0.000 0.492 0.000
#> SRR1313082 4 0.2966 0.78146 0.184 0.000 0.000 0.816 0.000
#> SRR1313083 1 0.1851 0.65683 0.912 0.000 0.000 0.088 0.000
#> SRR1313084 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313085 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0162 0.91812 0.004 0.000 0.000 0.996 0.000
#> SRR1313087 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.91892 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0510 0.91310 0.016 0.000 0.000 0.984 0.000
#> SRR1313092 3 0.4632 0.68024 0.448 0.000 0.540 0.000 0.012
#> SRR1313090 1 0.4138 -0.35018 0.616 0.000 0.384 0.000 0.000
#> SRR1313091 3 0.4161 0.67281 0.392 0.000 0.608 0.000 0.000
#> SRR1313093 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313095 1 0.3452 0.31277 0.756 0.000 0.244 0.000 0.000
#> SRR1313096 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313094 5 0.5501 -0.00985 0.064 0.000 0.444 0.000 0.492
#> SRR1313097 3 0.4262 0.69856 0.440 0.000 0.560 0.000 0.000
#> SRR1313099 3 0.5766 0.23748 0.092 0.000 0.516 0.000 0.392
#> SRR1313098 1 0.5602 0.44158 0.636 0.000 0.216 0.000 0.148
#> SRR1313101 3 0.4262 0.69782 0.440 0.000 0.560 0.000 0.000
#> SRR1313102 3 0.4262 0.69856 0.440 0.000 0.560 0.000 0.000
#> SRR1313103 3 0.5930 0.29341 0.112 0.000 0.516 0.000 0.372
#> SRR1313100 4 0.2516 0.82585 0.140 0.000 0.000 0.860 0.000
#> SRR1313105 3 0.6000 0.38806 0.132 0.000 0.540 0.000 0.328
#> SRR1313104 3 0.4708 0.68665 0.436 0.000 0.548 0.000 0.016
#> SRR1313107 5 0.2230 0.87815 0.044 0.000 0.044 0.000 0.912
#> SRR1313106 3 0.2127 0.42828 0.108 0.000 0.892 0.000 0.000
#> SRR1313109 3 0.4497 0.69855 0.424 0.000 0.568 0.000 0.008
#> SRR1313108 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313111 3 0.4604 0.69681 0.428 0.000 0.560 0.000 0.012
#> SRR1313110 1 0.2929 0.41084 0.820 0.000 0.180 0.000 0.000
#> SRR1313112 3 0.4262 0.69782 0.440 0.000 0.560 0.000 0.000
#> SRR1313113 3 0.4604 0.69681 0.428 0.000 0.560 0.000 0.012
#> SRR1313115 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313114 1 0.1792 0.57343 0.916 0.000 0.084 0.000 0.000
#> SRR1313117 3 0.4268 0.69532 0.444 0.000 0.556 0.000 0.000
#> SRR1313118 1 0.1270 0.60120 0.948 0.000 0.052 0.000 0.000
#> SRR1313116 3 0.4249 0.69977 0.432 0.000 0.568 0.000 0.000
#> SRR1313120 5 0.0955 0.93319 0.004 0.000 0.028 0.000 0.968
#> SRR1313119 1 0.4278 -0.52373 0.548 0.000 0.452 0.000 0.000
#> SRR1313122 3 0.4268 0.69511 0.444 0.000 0.556 0.000 0.000
#> SRR1313124 3 0.4287 0.67479 0.460 0.000 0.540 0.000 0.000
#> SRR1313121 1 0.4288 -0.34032 0.612 0.000 0.384 0.004 0.000
#> SRR1313125 3 0.4294 0.66043 0.468 0.000 0.532 0.000 0.000
#> SRR1313127 1 0.3390 0.59498 0.840 0.000 0.100 0.000 0.060
#> SRR1313123 1 0.4180 0.33965 0.744 0.000 0.220 0.000 0.036
#> SRR1313128 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313126 1 0.2927 0.64650 0.868 0.000 0.040 0.000 0.092
#> SRR1313130 3 0.1952 0.24935 0.004 0.084 0.912 0.000 0.000
#> SRR1313132 5 0.0880 0.92867 0.000 0.000 0.032 0.000 0.968
#> SRR1313129 3 0.4256 0.69926 0.436 0.000 0.564 0.000 0.000
#> SRR1313133 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313131 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313134 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313135 1 0.2813 0.63571 0.832 0.000 0.000 0.168 0.000
#> SRR1313136 1 0.4394 0.61210 0.764 0.000 0.100 0.000 0.136
#> SRR1313137 1 0.2843 0.64593 0.848 0.000 0.008 0.144 0.000
#> SRR1313138 1 0.2891 0.40854 0.824 0.000 0.176 0.000 0.000
#> SRR1313140 1 0.4287 -0.09339 0.540 0.000 0.000 0.460 0.000
#> SRR1313141 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313139 4 0.4235 0.37976 0.424 0.000 0.000 0.576 0.000
#> SRR1313143 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313142 1 0.4478 0.60614 0.756 0.000 0.100 0.000 0.144
#> SRR1313144 1 0.3171 0.63056 0.816 0.000 0.008 0.176 0.000
#> SRR1313145 1 0.4478 0.60614 0.756 0.000 0.100 0.000 0.144
#> SRR1313146 1 0.4519 0.60480 0.752 0.000 0.100 0.000 0.148
#> SRR1313147 1 0.4262 -0.02910 0.560 0.000 0.000 0.440 0.000
#> SRR1313150 4 0.4242 0.37151 0.428 0.000 0.000 0.572 0.000
#> SRR1313149 5 0.0000 0.95014 0.000 0.000 0.000 0.000 1.000
#> SRR1313152 1 0.3093 0.63596 0.824 0.000 0.008 0.168 0.000
#> SRR1313151 1 0.4763 0.56474 0.712 0.000 0.076 0.000 0.212
#> SRR1313154 5 0.3477 0.78418 0.112 0.000 0.056 0.000 0.832
#> SRR1313153 1 0.4343 0.61451 0.768 0.000 0.096 0.000 0.136
#> SRR1313156 3 0.4731 0.66517 0.456 0.000 0.528 0.000 0.016
#> SRR1313155 1 0.4478 0.60614 0.756 0.000 0.100 0.000 0.144
#> SRR1313157 1 0.3642 0.56784 0.760 0.000 0.008 0.232 0.000
#> SRR1313158 1 0.4266 0.60344 0.776 0.000 0.104 0.000 0.120
#> SRR1313161 1 0.3093 0.63596 0.824 0.000 0.008 0.168 0.000
#> SRR1313159 3 0.4273 0.69090 0.448 0.000 0.552 0.000 0.000
#> SRR1313160 1 0.0798 0.63892 0.976 0.000 0.008 0.016 0.000
#> SRR1313162 1 0.4394 0.61210 0.764 0.000 0.100 0.000 0.136
#> SRR1313163 1 0.2471 0.54105 0.864 0.000 0.136 0.000 0.000
#> SRR1313165 1 0.2798 0.64719 0.852 0.000 0.008 0.140 0.000
#> SRR1313166 5 0.0290 0.94623 0.008 0.000 0.000 0.000 0.992
#> SRR1313164 5 0.0290 0.94907 0.000 0.000 0.008 0.000 0.992
#> SRR1313167 1 0.0404 0.62910 0.988 0.000 0.012 0.000 0.000
#> SRR1313168 1 0.2304 0.65521 0.892 0.000 0.008 0.100 0.000
#> SRR1313170 3 0.4262 0.69782 0.440 0.000 0.560 0.000 0.000
#> SRR1313169 1 0.3093 0.63596 0.824 0.000 0.008 0.168 0.000
#> SRR1313172 5 0.2304 0.87335 0.048 0.000 0.044 0.000 0.908
#> SRR1313171 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313174 2 0.3999 0.77694 0.000 0.656 0.344 0.000 0.000
#> SRR1313173 5 0.0162 0.95043 0.000 0.000 0.004 0.000 0.996
#> SRR1313176 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 2 0.4256 0.75336 0.000 0.564 0.436 0.000 0.000
#> SRR1313178 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313180 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313181 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.1270 0.81080 0.000 0.948 0.052 0.000 0.000
#> SRR1313184 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313185 2 0.3480 0.79317 0.000 0.752 0.248 0.000 0.000
#> SRR1313188 2 0.4268 0.74875 0.000 0.556 0.444 0.000 0.000
#> SRR1313187 2 0.4268 0.74875 0.000 0.556 0.444 0.000 0.000
#> SRR1313186 2 0.3876 0.78252 0.000 0.684 0.316 0.000 0.000
#> SRR1313189 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.1270 0.81080 0.000 0.948 0.052 0.000 0.000
#> SRR1313192 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313195 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313196 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313197 2 0.4242 0.75659 0.000 0.572 0.428 0.000 0.000
#> SRR1313198 2 0.4249 0.75516 0.000 0.568 0.432 0.000 0.000
#> SRR1313199 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 2 0.4256 0.75336 0.000 0.564 0.436 0.000 0.000
#> SRR1313201 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 2 0.4273 0.74614 0.000 0.552 0.448 0.000 0.000
#> SRR1313203 3 0.6080 0.55575 0.272 0.000 0.560 0.000 0.168
#> SRR1313204 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 2 0.4256 0.75336 0.000 0.564 0.436 0.000 0.000
#> SRR1313209 2 0.4235 0.75790 0.000 0.576 0.424 0.000 0.000
#> SRR1313211 2 0.2074 0.80799 0.000 0.896 0.104 0.000 0.000
#> SRR1313212 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 2 0.4235 0.75790 0.000 0.576 0.424 0.000 0.000
#> SRR1313215 2 0.4249 0.75516 0.000 0.568 0.432 0.000 0.000
#> SRR1313213 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 3 0.0609 0.34179 0.000 0.020 0.980 0.000 0.000
#> SRR1313217 2 0.4256 0.75336 0.000 0.564 0.436 0.000 0.000
#> SRR1313219 2 0.4249 0.75516 0.000 0.568 0.432 0.000 0.000
#> SRR1313220 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.3707 0.78771 0.000 0.716 0.284 0.000 0.000
#> SRR1313222 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.3395 0.79483 0.000 0.764 0.236 0.000 0.000
#> SRR1313225 2 0.4249 0.75516 0.000 0.568 0.432 0.000 0.000
#> SRR1313226 3 0.4341 -0.57422 0.004 0.404 0.592 0.000 0.000
#> SRR1313227 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.81153 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.1745 0.883 0.020 0.000 0.000 0.924 0.056 0.000
#> SRR1313063 4 0.1462 0.882 0.008 0.000 0.000 0.936 0.056 0.000
#> SRR1313064 4 0.0000 0.896 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 1 0.5562 0.158 0.532 0.000 0.000 0.300 0.168 0.000
#> SRR1313066 4 0.2790 0.845 0.024 0.000 0.000 0.844 0.132 0.000
#> SRR1313067 1 0.5357 0.555 0.608 0.000 0.208 0.004 0.180 0.000
#> SRR1313068 4 0.4354 0.751 0.132 0.000 0.000 0.724 0.144 0.000
#> SRR1313069 4 0.0363 0.895 0.000 0.000 0.000 0.988 0.012 0.000
#> SRR1313070 4 0.0146 0.896 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313071 4 0.0146 0.896 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313072 4 0.0146 0.896 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313073 4 0.0363 0.895 0.000 0.000 0.000 0.988 0.012 0.000
#> SRR1313074 4 0.0363 0.895 0.000 0.000 0.000 0.988 0.012 0.000
#> SRR1313075 4 0.0000 0.896 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.1745 0.883 0.020 0.000 0.000 0.924 0.056 0.000
#> SRR1313077 4 0.5246 0.213 0.416 0.000 0.000 0.488 0.096 0.000
#> SRR1313078 6 0.1644 0.877 0.000 0.000 0.004 0.000 0.076 0.920
#> SRR1313079 4 0.0000 0.896 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.4603 0.721 0.156 0.000 0.000 0.696 0.148 0.000
#> SRR1313081 1 0.4039 0.588 0.752 0.000 0.000 0.156 0.092 0.000
#> SRR1313082 4 0.5116 0.467 0.344 0.000 0.000 0.560 0.096 0.000
#> SRR1313083 1 0.2834 0.731 0.864 0.000 0.096 0.020 0.020 0.000
#> SRR1313084 4 0.0622 0.892 0.012 0.000 0.000 0.980 0.008 0.000
#> SRR1313085 4 0.0146 0.896 0.000 0.000 0.000 0.996 0.004 0.000
#> SRR1313086 4 0.1492 0.883 0.036 0.000 0.000 0.940 0.024 0.000
#> SRR1313087 4 0.0000 0.896 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0363 0.895 0.000 0.000 0.000 0.988 0.012 0.000
#> SRR1313089 4 0.2748 0.847 0.024 0.000 0.000 0.848 0.128 0.000
#> SRR1313092 3 0.1370 0.800 0.012 0.000 0.948 0.000 0.036 0.004
#> SRR1313090 3 0.5279 0.270 0.336 0.000 0.548 0.000 0.116 0.000
#> SRR1313091 3 0.0632 0.815 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR1313093 6 0.0260 0.920 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1313095 3 0.5153 -0.249 0.452 0.000 0.464 0.000 0.084 0.000
#> SRR1313096 6 0.0000 0.920 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313094 3 0.2915 0.672 0.000 0.000 0.808 0.000 0.008 0.184
#> SRR1313097 3 0.0405 0.818 0.008 0.000 0.988 0.000 0.004 0.000
#> SRR1313099 3 0.2513 0.723 0.000 0.000 0.852 0.000 0.008 0.140
#> SRR1313098 1 0.7112 0.367 0.372 0.000 0.360 0.000 0.132 0.136
#> SRR1313101 3 0.2263 0.792 0.048 0.000 0.896 0.000 0.056 0.000
#> SRR1313102 3 0.1003 0.815 0.016 0.000 0.964 0.000 0.020 0.000
#> SRR1313103 3 0.2431 0.733 0.000 0.000 0.860 0.000 0.008 0.132
#> SRR1313100 4 0.5667 0.401 0.340 0.000 0.000 0.492 0.168 0.000
#> SRR1313105 3 0.1918 0.768 0.000 0.000 0.904 0.000 0.008 0.088
#> SRR1313104 3 0.0622 0.815 0.000 0.000 0.980 0.000 0.008 0.012
#> SRR1313107 6 0.2882 0.791 0.000 0.000 0.180 0.000 0.008 0.812
#> SRR1313106 3 0.3468 0.642 0.008 0.000 0.728 0.000 0.264 0.000
#> SRR1313109 3 0.0520 0.816 0.000 0.000 0.984 0.000 0.008 0.008
#> SRR1313108 6 0.0260 0.920 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1313111 3 0.0405 0.816 0.000 0.000 0.988 0.000 0.008 0.004
#> SRR1313110 1 0.4822 0.460 0.596 0.000 0.332 0.000 0.072 0.000
#> SRR1313112 3 0.2129 0.797 0.040 0.000 0.904 0.000 0.056 0.000
#> SRR1313113 3 0.0520 0.816 0.000 0.000 0.984 0.000 0.008 0.008
#> SRR1313115 6 0.0260 0.920 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1313114 1 0.4215 0.614 0.700 0.000 0.244 0.000 0.056 0.000
#> SRR1313117 3 0.2129 0.797 0.040 0.000 0.904 0.000 0.056 0.000
#> SRR1313118 1 0.4026 0.663 0.752 0.000 0.160 0.000 0.088 0.000
#> SRR1313116 3 0.0363 0.817 0.000 0.000 0.988 0.000 0.012 0.000
#> SRR1313120 6 0.2778 0.806 0.000 0.000 0.168 0.000 0.008 0.824
#> SRR1313119 3 0.4418 0.587 0.192 0.000 0.708 0.000 0.100 0.000
#> SRR1313122 3 0.1745 0.805 0.020 0.000 0.924 0.000 0.056 0.000
#> SRR1313124 3 0.1908 0.802 0.028 0.000 0.916 0.000 0.056 0.000
#> SRR1313121 3 0.5386 0.191 0.368 0.000 0.512 0.000 0.120 0.000
#> SRR1313125 3 0.2568 0.776 0.068 0.000 0.876 0.000 0.056 0.000
#> SRR1313127 1 0.5948 0.600 0.560 0.000 0.272 0.000 0.132 0.036
#> SRR1313123 3 0.6107 -0.313 0.392 0.000 0.448 0.000 0.132 0.028
#> SRR1313128 6 0.0291 0.917 0.000 0.000 0.004 0.000 0.004 0.992
#> SRR1313126 1 0.5454 0.657 0.644 0.000 0.204 0.000 0.116 0.036
#> SRR1313130 5 0.4267 0.463 0.004 0.044 0.260 0.000 0.692 0.000
#> SRR1313132 6 0.3845 0.775 0.000 0.000 0.140 0.000 0.088 0.772
#> SRR1313129 3 0.0260 0.817 0.008 0.000 0.992 0.000 0.000 0.000
#> SRR1313133 6 0.0000 0.920 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313131 6 0.0405 0.920 0.000 0.000 0.008 0.000 0.004 0.988
#> SRR1313134 6 0.0405 0.920 0.000 0.000 0.008 0.000 0.004 0.988
#> SRR1313135 1 0.3103 0.733 0.856 0.000 0.076 0.044 0.024 0.000
#> SRR1313136 1 0.6624 0.600 0.528 0.000 0.228 0.000 0.132 0.112
#> SRR1313137 1 0.2433 0.731 0.884 0.000 0.072 0.044 0.000 0.000
#> SRR1313138 1 0.4548 0.503 0.632 0.000 0.312 0.000 0.056 0.000
#> SRR1313140 1 0.2489 0.662 0.860 0.000 0.000 0.128 0.012 0.000
#> SRR1313141 6 0.0000 0.920 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313139 1 0.3812 0.468 0.712 0.000 0.000 0.264 0.024 0.000
#> SRR1313143 6 0.0000 0.920 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313142 1 0.6755 0.588 0.512 0.000 0.228 0.000 0.132 0.128
#> SRR1313144 1 0.2697 0.729 0.876 0.000 0.068 0.048 0.008 0.000
#> SRR1313145 1 0.6755 0.588 0.512 0.000 0.228 0.000 0.132 0.128
#> SRR1313146 1 0.6755 0.588 0.512 0.000 0.228 0.000 0.132 0.128
#> SRR1313147 1 0.2257 0.673 0.876 0.000 0.000 0.116 0.008 0.000
#> SRR1313150 1 0.4479 0.455 0.684 0.000 0.000 0.236 0.080 0.000
#> SRR1313149 6 0.0000 0.920 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313152 1 0.2433 0.731 0.884 0.000 0.072 0.044 0.000 0.000
#> SRR1313151 1 0.6954 0.566 0.488 0.000 0.212 0.000 0.132 0.168
#> SRR1313154 6 0.6342 0.412 0.172 0.000 0.120 0.000 0.128 0.580
#> SRR1313153 1 0.6605 0.603 0.532 0.000 0.224 0.000 0.132 0.112
#> SRR1313156 3 0.2544 0.736 0.012 0.000 0.864 0.000 0.120 0.004
#> SRR1313155 1 0.6755 0.588 0.512 0.000 0.228 0.000 0.132 0.128
#> SRR1313157 1 0.3141 0.725 0.856 0.000 0.064 0.052 0.028 0.000
#> SRR1313158 1 0.6615 0.576 0.512 0.000 0.260 0.000 0.132 0.096
#> SRR1313161 1 0.3590 0.716 0.828 0.000 0.072 0.040 0.060 0.000
#> SRR1313159 3 0.0508 0.816 0.012 0.000 0.984 0.000 0.004 0.000
#> SRR1313160 1 0.3183 0.707 0.828 0.000 0.112 0.000 0.060 0.000
#> SRR1313162 1 0.6624 0.600 0.528 0.000 0.228 0.000 0.132 0.112
#> SRR1313163 1 0.5199 0.576 0.580 0.000 0.300 0.000 0.120 0.000
#> SRR1313165 1 0.3590 0.716 0.828 0.000 0.072 0.040 0.060 0.000
#> SRR1313166 6 0.2740 0.827 0.000 0.000 0.028 0.000 0.120 0.852
#> SRR1313164 6 0.2020 0.878 0.000 0.000 0.096 0.000 0.008 0.896
#> SRR1313167 1 0.2624 0.719 0.856 0.000 0.124 0.000 0.020 0.000
#> SRR1313168 1 0.2384 0.731 0.884 0.000 0.084 0.032 0.000 0.000
#> SRR1313170 3 0.1908 0.802 0.028 0.000 0.916 0.000 0.056 0.000
#> SRR1313169 1 0.2433 0.731 0.884 0.000 0.072 0.044 0.000 0.000
#> SRR1313172 6 0.2841 0.804 0.000 0.000 0.164 0.000 0.012 0.824
#> SRR1313171 6 0.0993 0.910 0.000 0.000 0.024 0.000 0.012 0.964
#> SRR1313174 5 0.3961 0.769 0.004 0.440 0.000 0.000 0.556 0.000
#> SRR1313173 6 0.0405 0.920 0.000 0.000 0.008 0.000 0.004 0.988
#> SRR1313176 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313175 5 0.3578 0.934 0.000 0.340 0.000 0.000 0.660 0.000
#> SRR1313178 2 0.1285 0.857 0.052 0.944 0.004 0.000 0.000 0.000
#> SRR1313177 2 0.1644 0.844 0.076 0.920 0.004 0.000 0.000 0.000
#> SRR1313179 5 0.3699 0.933 0.000 0.336 0.004 0.000 0.660 0.000
#> SRR1313180 5 0.3721 0.897 0.004 0.308 0.004 0.000 0.684 0.000
#> SRR1313181 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313183 2 0.1644 0.844 0.076 0.920 0.004 0.000 0.000 0.000
#> SRR1313182 2 0.2431 0.697 0.008 0.860 0.000 0.000 0.132 0.000
#> SRR1313184 5 0.3878 0.923 0.004 0.348 0.004 0.000 0.644 0.000
#> SRR1313185 2 0.4159 -0.256 0.016 0.588 0.000 0.000 0.396 0.000
#> SRR1313188 5 0.3578 0.934 0.000 0.340 0.000 0.000 0.660 0.000
#> SRR1313187 5 0.3578 0.934 0.000 0.340 0.000 0.000 0.660 0.000
#> SRR1313186 2 0.4184 -0.597 0.012 0.500 0.000 0.000 0.488 0.000
#> SRR1313189 2 0.1285 0.856 0.052 0.944 0.004 0.000 0.000 0.000
#> SRR1313190 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313191 2 0.2178 0.695 0.000 0.868 0.000 0.000 0.132 0.000
#> SRR1313192 2 0.0260 0.861 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0260 0.858 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313194 5 0.3699 0.933 0.000 0.336 0.004 0.000 0.660 0.000
#> SRR1313195 5 0.3699 0.933 0.000 0.336 0.004 0.000 0.660 0.000
#> SRR1313196 5 0.3699 0.933 0.000 0.336 0.004 0.000 0.660 0.000
#> SRR1313197 5 0.3728 0.931 0.004 0.344 0.000 0.000 0.652 0.000
#> SRR1313198 5 0.3714 0.934 0.004 0.340 0.000 0.000 0.656 0.000
#> SRR1313199 2 0.0632 0.861 0.024 0.976 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.3578 0.934 0.000 0.340 0.000 0.000 0.660 0.000
#> SRR1313201 2 0.0363 0.859 0.012 0.988 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.3699 0.933 0.000 0.336 0.004 0.000 0.660 0.000
#> SRR1313203 3 0.2095 0.787 0.028 0.000 0.916 0.000 0.016 0.040
#> SRR1313204 2 0.0458 0.858 0.016 0.984 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0260 0.858 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313208 2 0.0363 0.857 0.012 0.988 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0260 0.858 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.3714 0.934 0.004 0.340 0.000 0.000 0.656 0.000
#> SRR1313209 5 0.3979 0.908 0.012 0.360 0.000 0.000 0.628 0.000
#> SRR1313211 2 0.2768 0.637 0.012 0.832 0.000 0.000 0.156 0.000
#> SRR1313212 2 0.0777 0.859 0.024 0.972 0.004 0.000 0.000 0.000
#> SRR1313214 5 0.3992 0.903 0.012 0.364 0.000 0.000 0.624 0.000
#> SRR1313215 5 0.3714 0.934 0.004 0.340 0.000 0.000 0.656 0.000
#> SRR1313213 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313216 3 0.3819 0.461 0.000 0.008 0.652 0.000 0.340 0.000
#> SRR1313217 5 0.3714 0.934 0.004 0.340 0.000 0.000 0.656 0.000
#> SRR1313219 5 0.3714 0.934 0.004 0.340 0.000 0.000 0.656 0.000
#> SRR1313220 2 0.0260 0.858 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.4179 -0.568 0.012 0.516 0.000 0.000 0.472 0.000
#> SRR1313222 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313221 2 0.1349 0.857 0.056 0.940 0.004 0.000 0.000 0.000
#> SRR1313223 2 0.0458 0.858 0.016 0.984 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.4004 -0.166 0.012 0.620 0.000 0.000 0.368 0.000
#> SRR1313225 5 0.3940 0.921 0.012 0.348 0.000 0.000 0.640 0.000
#> SRR1313226 5 0.4096 0.676 0.016 0.160 0.060 0.000 0.764 0.000
#> SRR1313227 2 0.0632 0.861 0.024 0.976 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0547 0.861 0.020 0.980 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0632 0.861 0.024 0.976 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "skmeans"]
# you can also extract it by
# res = res_list["ATC:skmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.972 0.989 0.4793 0.519 0.519
#> 3 3 1.000 0.984 0.994 0.3960 0.760 0.560
#> 4 4 0.923 0.844 0.926 0.0927 0.923 0.773
#> 5 5 0.882 0.864 0.909 0.0527 0.940 0.787
#> 6 6 0.861 0.853 0.880 0.0466 0.968 0.866
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.9944 1.000 0.000
#> SRR1313063 1 0.000 0.9944 1.000 0.000
#> SRR1313064 1 0.000 0.9944 1.000 0.000
#> SRR1313065 1 0.000 0.9944 1.000 0.000
#> SRR1313066 1 0.000 0.9944 1.000 0.000
#> SRR1313067 1 0.000 0.9944 1.000 0.000
#> SRR1313068 1 0.000 0.9944 1.000 0.000
#> SRR1313069 1 0.000 0.9944 1.000 0.000
#> SRR1313070 1 0.000 0.9944 1.000 0.000
#> SRR1313071 1 0.000 0.9944 1.000 0.000
#> SRR1313072 1 0.000 0.9944 1.000 0.000
#> SRR1313073 1 0.000 0.9944 1.000 0.000
#> SRR1313074 1 0.000 0.9944 1.000 0.000
#> SRR1313075 1 0.000 0.9944 1.000 0.000
#> SRR1313076 1 0.000 0.9944 1.000 0.000
#> SRR1313077 1 0.000 0.9944 1.000 0.000
#> SRR1313078 1 0.000 0.9944 1.000 0.000
#> SRR1313079 1 0.000 0.9944 1.000 0.000
#> SRR1313080 1 0.000 0.9944 1.000 0.000
#> SRR1313081 1 0.000 0.9944 1.000 0.000
#> SRR1313082 1 0.000 0.9944 1.000 0.000
#> SRR1313083 1 0.000 0.9944 1.000 0.000
#> SRR1313084 1 0.000 0.9944 1.000 0.000
#> SRR1313085 1 0.000 0.9944 1.000 0.000
#> SRR1313086 1 0.000 0.9944 1.000 0.000
#> SRR1313087 1 0.000 0.9944 1.000 0.000
#> SRR1313088 1 0.000 0.9944 1.000 0.000
#> SRR1313089 1 0.000 0.9944 1.000 0.000
#> SRR1313092 1 0.000 0.9944 1.000 0.000
#> SRR1313090 1 0.000 0.9944 1.000 0.000
#> SRR1313091 2 0.000 0.9792 0.000 1.000
#> SRR1313093 1 0.000 0.9944 1.000 0.000
#> SRR1313095 1 0.000 0.9944 1.000 0.000
#> SRR1313096 1 0.000 0.9944 1.000 0.000
#> SRR1313094 1 0.000 0.9944 1.000 0.000
#> SRR1313097 1 0.000 0.9944 1.000 0.000
#> SRR1313099 1 0.506 0.8717 0.888 0.112
#> SRR1313098 1 0.000 0.9944 1.000 0.000
#> SRR1313101 2 0.000 0.9792 0.000 1.000
#> SRR1313102 2 0.999 0.0896 0.480 0.520
#> SRR1313103 1 0.000 0.9944 1.000 0.000
#> SRR1313100 1 0.000 0.9944 1.000 0.000
#> SRR1313105 1 0.000 0.9944 1.000 0.000
#> SRR1313104 1 0.000 0.9944 1.000 0.000
#> SRR1313107 1 0.000 0.9944 1.000 0.000
#> SRR1313106 2 0.000 0.9792 0.000 1.000
#> SRR1313109 2 0.000 0.9792 0.000 1.000
#> SRR1313108 1 0.000 0.9944 1.000 0.000
#> SRR1313111 1 0.000 0.9944 1.000 0.000
#> SRR1313110 1 0.000 0.9944 1.000 0.000
#> SRR1313112 2 0.224 0.9456 0.036 0.964
#> SRR1313113 1 0.000 0.9944 1.000 0.000
#> SRR1313115 1 0.000 0.9944 1.000 0.000
#> SRR1313114 1 0.000 0.9944 1.000 0.000
#> SRR1313117 1 0.000 0.9944 1.000 0.000
#> SRR1313118 1 0.000 0.9944 1.000 0.000
#> SRR1313116 2 0.000 0.9792 0.000 1.000
#> SRR1313120 1 0.000 0.9944 1.000 0.000
#> SRR1313119 1 0.000 0.9944 1.000 0.000
#> SRR1313122 1 0.000 0.9944 1.000 0.000
#> SRR1313124 1 0.000 0.9944 1.000 0.000
#> SRR1313121 1 0.680 0.7766 0.820 0.180
#> SRR1313125 1 0.000 0.9944 1.000 0.000
#> SRR1313127 1 0.000 0.9944 1.000 0.000
#> SRR1313123 1 0.000 0.9944 1.000 0.000
#> SRR1313128 1 0.000 0.9944 1.000 0.000
#> SRR1313126 1 0.000 0.9944 1.000 0.000
#> SRR1313130 2 0.000 0.9792 0.000 1.000
#> SRR1313132 1 0.000 0.9944 1.000 0.000
#> SRR1313129 2 0.969 0.3567 0.396 0.604
#> SRR1313133 1 0.000 0.9944 1.000 0.000
#> SRR1313131 1 0.000 0.9944 1.000 0.000
#> SRR1313134 1 0.000 0.9944 1.000 0.000
#> SRR1313135 1 0.000 0.9944 1.000 0.000
#> SRR1313136 1 0.000 0.9944 1.000 0.000
#> SRR1313137 1 0.000 0.9944 1.000 0.000
#> SRR1313138 2 0.795 0.6876 0.240 0.760
#> SRR1313140 1 0.000 0.9944 1.000 0.000
#> SRR1313141 1 0.000 0.9944 1.000 0.000
#> SRR1313139 1 0.000 0.9944 1.000 0.000
#> SRR1313143 1 0.000 0.9944 1.000 0.000
#> SRR1313142 1 0.000 0.9944 1.000 0.000
#> SRR1313144 1 0.000 0.9944 1.000 0.000
#> SRR1313145 1 0.000 0.9944 1.000 0.000
#> SRR1313146 1 0.000 0.9944 1.000 0.000
#> SRR1313147 1 0.000 0.9944 1.000 0.000
#> SRR1313150 1 0.000 0.9944 1.000 0.000
#> SRR1313149 1 0.000 0.9944 1.000 0.000
#> SRR1313152 1 0.000 0.9944 1.000 0.000
#> SRR1313151 1 0.000 0.9944 1.000 0.000
#> SRR1313154 1 0.000 0.9944 1.000 0.000
#> SRR1313153 1 0.000 0.9944 1.000 0.000
#> SRR1313156 1 0.000 0.9944 1.000 0.000
#> SRR1313155 1 0.000 0.9944 1.000 0.000
#> SRR1313157 1 0.000 0.9944 1.000 0.000
#> SRR1313158 1 0.000 0.9944 1.000 0.000
#> SRR1313161 1 0.000 0.9944 1.000 0.000
#> SRR1313159 1 0.278 0.9461 0.952 0.048
#> SRR1313160 1 0.000 0.9944 1.000 0.000
#> SRR1313162 1 0.000 0.9944 1.000 0.000
#> SRR1313163 1 0.000 0.9944 1.000 0.000
#> SRR1313165 1 0.000 0.9944 1.000 0.000
#> SRR1313166 1 0.000 0.9944 1.000 0.000
#> SRR1313164 1 0.000 0.9944 1.000 0.000
#> SRR1313167 1 0.000 0.9944 1.000 0.000
#> SRR1313168 1 0.000 0.9944 1.000 0.000
#> SRR1313170 1 0.118 0.9789 0.984 0.016
#> SRR1313169 1 0.000 0.9944 1.000 0.000
#> SRR1313172 1 0.697 0.7657 0.812 0.188
#> SRR1313171 1 0.000 0.9944 1.000 0.000
#> SRR1313174 2 0.000 0.9792 0.000 1.000
#> SRR1313173 1 0.000 0.9944 1.000 0.000
#> SRR1313176 2 0.000 0.9792 0.000 1.000
#> SRR1313175 2 0.000 0.9792 0.000 1.000
#> SRR1313178 2 0.000 0.9792 0.000 1.000
#> SRR1313177 2 0.000 0.9792 0.000 1.000
#> SRR1313179 2 0.000 0.9792 0.000 1.000
#> SRR1313180 2 0.000 0.9792 0.000 1.000
#> SRR1313181 2 0.000 0.9792 0.000 1.000
#> SRR1313183 2 0.000 0.9792 0.000 1.000
#> SRR1313182 2 0.000 0.9792 0.000 1.000
#> SRR1313184 2 0.000 0.9792 0.000 1.000
#> SRR1313185 2 0.000 0.9792 0.000 1.000
#> SRR1313188 2 0.000 0.9792 0.000 1.000
#> SRR1313187 2 0.000 0.9792 0.000 1.000
#> SRR1313186 2 0.000 0.9792 0.000 1.000
#> SRR1313189 2 0.000 0.9792 0.000 1.000
#> SRR1313190 2 0.000 0.9792 0.000 1.000
#> SRR1313191 2 0.000 0.9792 0.000 1.000
#> SRR1313192 2 0.000 0.9792 0.000 1.000
#> SRR1313193 2 0.000 0.9792 0.000 1.000
#> SRR1313194 2 0.000 0.9792 0.000 1.000
#> SRR1313195 2 0.000 0.9792 0.000 1.000
#> SRR1313196 2 0.000 0.9792 0.000 1.000
#> SRR1313197 2 0.000 0.9792 0.000 1.000
#> SRR1313198 2 0.000 0.9792 0.000 1.000
#> SRR1313199 2 0.000 0.9792 0.000 1.000
#> SRR1313200 2 0.000 0.9792 0.000 1.000
#> SRR1313201 2 0.000 0.9792 0.000 1.000
#> SRR1313202 2 0.000 0.9792 0.000 1.000
#> SRR1313203 2 0.689 0.7716 0.184 0.816
#> SRR1313204 2 0.000 0.9792 0.000 1.000
#> SRR1313205 2 0.000 0.9792 0.000 1.000
#> SRR1313207 2 0.000 0.9792 0.000 1.000
#> SRR1313208 2 0.000 0.9792 0.000 1.000
#> SRR1313206 2 0.000 0.9792 0.000 1.000
#> SRR1313210 2 0.000 0.9792 0.000 1.000
#> SRR1313209 2 0.000 0.9792 0.000 1.000
#> SRR1313211 2 0.000 0.9792 0.000 1.000
#> SRR1313212 2 0.000 0.9792 0.000 1.000
#> SRR1313214 2 0.000 0.9792 0.000 1.000
#> SRR1313215 2 0.000 0.9792 0.000 1.000
#> SRR1313213 2 0.000 0.9792 0.000 1.000
#> SRR1313216 2 0.000 0.9792 0.000 1.000
#> SRR1313217 2 0.000 0.9792 0.000 1.000
#> SRR1313219 2 0.000 0.9792 0.000 1.000
#> SRR1313220 2 0.000 0.9792 0.000 1.000
#> SRR1313218 2 0.000 0.9792 0.000 1.000
#> SRR1313222 2 0.000 0.9792 0.000 1.000
#> SRR1313221 2 0.000 0.9792 0.000 1.000
#> SRR1313223 2 0.000 0.9792 0.000 1.000
#> SRR1313224 2 0.000 0.9792 0.000 1.000
#> SRR1313225 2 0.000 0.9792 0.000 1.000
#> SRR1313226 2 0.000 0.9792 0.000 1.000
#> SRR1313227 2 0.000 0.9792 0.000 1.000
#> SRR1313228 2 0.000 0.9792 0.000 1.000
#> SRR1313229 2 0.000 0.9792 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313063 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313067 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313068 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313069 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313076 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313077 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313078 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313079 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313080 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313081 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313082 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313083 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313084 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313090 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313091 3 0.6140 0.311 0.000 0.404 0.596
#> SRR1313093 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313095 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313096 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313097 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313099 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313098 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313101 2 0.0592 0.981 0.000 0.988 0.012
#> SRR1313102 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313103 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313100 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313105 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313104 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313107 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313106 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313109 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313108 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313110 1 0.0747 0.981 0.984 0.000 0.016
#> SRR1313112 2 0.6140 0.313 0.000 0.596 0.404
#> SRR1313113 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313115 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313114 1 0.4346 0.776 0.816 0.000 0.184
#> SRR1313117 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313118 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313116 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313120 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313119 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313122 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313124 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313121 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313125 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313127 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313123 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313128 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313126 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313130 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313132 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313129 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313133 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313131 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313134 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313135 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313136 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313137 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313138 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313140 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313141 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313139 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313143 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313142 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313144 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313145 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313146 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313147 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313150 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313149 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313152 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313151 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313154 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313153 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313156 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313155 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313157 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313158 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313161 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313159 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313160 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313162 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313163 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313165 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313166 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313164 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313167 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313168 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313170 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313169 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1313172 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313171 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313174 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313180 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313203 3 0.0000 0.993 0.000 0.000 1.000
#> SRR1313204 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313226 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.993 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.993 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313066 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313067 3 0.4998 0.2282 0.000 0.000 0.512 0.488
#> SRR1313068 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313069 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313078 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313079 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313081 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313082 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.2773 0.8153 0.116 0.000 0.004 0.880
#> SRR1313084 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313092 1 0.0707 0.8065 0.980 0.000 0.020 0.000
#> SRR1313090 3 0.4967 0.3107 0.000 0.000 0.548 0.452
#> SRR1313091 1 0.5294 0.4332 0.508 0.008 0.484 0.000
#> SRR1313093 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313095 3 0.4941 0.2956 0.436 0.000 0.564 0.000
#> SRR1313096 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313094 1 0.4985 0.4672 0.532 0.000 0.468 0.000
#> SRR1313097 3 0.0188 0.6465 0.004 0.000 0.996 0.000
#> SRR1313099 1 0.4985 0.4672 0.532 0.000 0.468 0.000
#> SRR1313098 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313101 3 0.0000 0.6481 0.000 0.000 1.000 0.000
#> SRR1313102 3 0.0188 0.6465 0.004 0.000 0.996 0.000
#> SRR1313103 1 0.4985 0.4672 0.532 0.000 0.468 0.000
#> SRR1313100 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313105 1 0.4998 0.4376 0.512 0.000 0.488 0.000
#> SRR1313104 3 0.4817 -0.0664 0.388 0.000 0.612 0.000
#> SRR1313107 1 0.4967 0.4846 0.548 0.000 0.452 0.000
#> SRR1313106 3 0.0188 0.6466 0.000 0.004 0.996 0.000
#> SRR1313109 1 0.4985 0.4672 0.532 0.000 0.468 0.000
#> SRR1313108 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313111 1 0.4996 0.4441 0.516 0.000 0.484 0.000
#> SRR1313110 3 0.7011 0.5043 0.148 0.000 0.552 0.300
#> SRR1313112 3 0.0000 0.6481 0.000 0.000 1.000 0.000
#> SRR1313113 1 0.4996 0.4441 0.516 0.000 0.484 0.000
#> SRR1313115 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313114 3 0.7182 0.5401 0.200 0.000 0.552 0.248
#> SRR1313117 3 0.0000 0.6481 0.000 0.000 1.000 0.000
#> SRR1313118 3 0.4999 0.2093 0.000 0.000 0.508 0.492
#> SRR1313116 1 0.4998 0.4376 0.512 0.000 0.488 0.000
#> SRR1313120 1 0.4948 0.4968 0.560 0.000 0.440 0.000
#> SRR1313119 3 0.4907 0.3728 0.000 0.000 0.580 0.420
#> SRR1313122 3 0.0188 0.6465 0.004 0.000 0.996 0.000
#> SRR1313124 3 0.2081 0.6196 0.084 0.000 0.916 0.000
#> SRR1313121 3 0.4989 0.2704 0.000 0.000 0.528 0.472
#> SRR1313125 3 0.4661 0.4098 0.348 0.000 0.652 0.000
#> SRR1313127 1 0.0188 0.8163 0.996 0.000 0.004 0.000
#> SRR1313123 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313128 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313126 3 0.4998 0.2041 0.488 0.000 0.512 0.000
#> SRR1313130 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313132 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313129 1 0.4998 0.4376 0.512 0.000 0.488 0.000
#> SRR1313133 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313131 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313134 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313135 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313136 1 0.0188 0.8163 0.996 0.000 0.004 0.000
#> SRR1313137 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313138 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313140 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313141 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313139 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313143 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313142 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313144 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313145 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313146 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313147 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313150 4 0.0000 0.9873 0.000 0.000 0.000 1.000
#> SRR1313149 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313152 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313151 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313154 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313153 1 0.0188 0.8163 0.996 0.000 0.004 0.000
#> SRR1313156 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313155 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313157 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313158 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313161 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313159 1 0.2149 0.7666 0.912 0.000 0.088 0.000
#> SRR1313160 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313162 1 0.0188 0.8163 0.996 0.000 0.004 0.000
#> SRR1313163 1 0.0188 0.8163 0.996 0.000 0.004 0.000
#> SRR1313165 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313166 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313164 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313167 4 0.3870 0.6509 0.208 0.000 0.004 0.788
#> SRR1313168 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313170 3 0.0707 0.6336 0.020 0.000 0.980 0.000
#> SRR1313169 4 0.0188 0.9859 0.000 0.000 0.004 0.996
#> SRR1313172 1 0.4933 0.5046 0.568 0.000 0.432 0.000
#> SRR1313171 1 0.4661 0.5749 0.652 0.000 0.348 0.000
#> SRR1313174 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.0000 0.8194 1.000 0.000 0.000 0.000
#> SRR1313176 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313203 1 0.4933 0.5046 0.568 0.000 0.432 0.000
#> SRR1313204 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313227 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 1.0000 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 1.0000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313063 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313064 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313066 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313067 3 0.3366 0.718 0.000 0.000 0.768 0.232 0.000
#> SRR1313068 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313069 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313077 4 0.0162 0.880 0.000 0.000 0.004 0.996 0.000
#> SRR1313078 1 0.0771 0.873 0.976 0.000 0.004 0.000 0.020
#> SRR1313079 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313080 4 0.1851 0.807 0.000 0.000 0.088 0.912 0.000
#> SRR1313081 4 0.0162 0.880 0.000 0.000 0.004 0.996 0.000
#> SRR1313082 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313083 1 0.7223 0.345 0.548 0.000 0.168 0.196 0.088
#> SRR1313084 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313085 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313087 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.882 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313092 1 0.1544 0.851 0.932 0.000 0.000 0.000 0.068
#> SRR1313090 3 0.1918 0.807 0.000 0.000 0.928 0.036 0.036
#> SRR1313091 5 0.2520 0.869 0.096 0.012 0.004 0.000 0.888
#> SRR1313093 1 0.4150 0.269 0.612 0.000 0.000 0.000 0.388
#> SRR1313095 3 0.4066 0.702 0.188 0.000 0.768 0.000 0.044
#> SRR1313096 1 0.0794 0.872 0.972 0.000 0.000 0.000 0.028
#> SRR1313094 5 0.2230 0.877 0.116 0.000 0.000 0.000 0.884
#> SRR1313097 5 0.2516 0.709 0.000 0.000 0.140 0.000 0.860
#> SRR1313099 5 0.2127 0.879 0.108 0.000 0.000 0.000 0.892
#> SRR1313098 1 0.0771 0.873 0.976 0.000 0.004 0.000 0.020
#> SRR1313101 3 0.3177 0.800 0.000 0.000 0.792 0.000 0.208
#> SRR1313102 5 0.2813 0.677 0.000 0.000 0.168 0.000 0.832
#> SRR1313103 5 0.2127 0.879 0.108 0.000 0.000 0.000 0.892
#> SRR1313100 4 0.0162 0.881 0.000 0.000 0.004 0.996 0.000
#> SRR1313105 5 0.2233 0.878 0.104 0.000 0.004 0.000 0.892
#> SRR1313104 5 0.3169 0.824 0.084 0.000 0.060 0.000 0.856
#> SRR1313107 5 0.2471 0.865 0.136 0.000 0.000 0.000 0.864
#> SRR1313106 3 0.3336 0.779 0.000 0.000 0.772 0.000 0.228
#> SRR1313109 5 0.2127 0.879 0.108 0.000 0.000 0.000 0.892
#> SRR1313108 1 0.2773 0.768 0.836 0.000 0.000 0.000 0.164
#> SRR1313111 5 0.2074 0.879 0.104 0.000 0.000 0.000 0.896
#> SRR1313110 3 0.0912 0.788 0.016 0.000 0.972 0.012 0.000
#> SRR1313112 3 0.3177 0.800 0.000 0.000 0.792 0.000 0.208
#> SRR1313113 5 0.2233 0.878 0.104 0.000 0.004 0.000 0.892
#> SRR1313115 1 0.2773 0.768 0.836 0.000 0.000 0.000 0.164
#> SRR1313114 3 0.0898 0.789 0.020 0.000 0.972 0.008 0.000
#> SRR1313117 3 0.3177 0.800 0.000 0.000 0.792 0.000 0.208
#> SRR1313118 3 0.1851 0.741 0.000 0.000 0.912 0.088 0.000
#> SRR1313116 5 0.2358 0.877 0.104 0.000 0.008 0.000 0.888
#> SRR1313120 5 0.2561 0.861 0.144 0.000 0.000 0.000 0.856
#> SRR1313119 3 0.1648 0.810 0.000 0.000 0.940 0.020 0.040
#> SRR1313122 3 0.3177 0.800 0.000 0.000 0.792 0.000 0.208
#> SRR1313124 3 0.3388 0.801 0.008 0.000 0.792 0.000 0.200
#> SRR1313121 3 0.3366 0.719 0.000 0.000 0.768 0.232 0.000
#> SRR1313125 3 0.4121 0.776 0.100 0.000 0.788 0.000 0.112
#> SRR1313127 1 0.0451 0.869 0.988 0.000 0.008 0.000 0.004
#> SRR1313123 1 0.0566 0.873 0.984 0.000 0.004 0.000 0.012
#> SRR1313128 1 0.0703 0.873 0.976 0.000 0.000 0.000 0.024
#> SRR1313126 1 0.3966 0.465 0.664 0.000 0.336 0.000 0.000
#> SRR1313130 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313132 1 0.1851 0.837 0.912 0.000 0.000 0.000 0.088
#> SRR1313129 5 0.2233 0.878 0.104 0.000 0.004 0.000 0.892
#> SRR1313133 1 0.0880 0.871 0.968 0.000 0.000 0.000 0.032
#> SRR1313131 1 0.2773 0.768 0.836 0.000 0.000 0.000 0.164
#> SRR1313134 1 0.2329 0.808 0.876 0.000 0.000 0.000 0.124
#> SRR1313135 4 0.5581 0.761 0.032 0.000 0.192 0.688 0.088
#> SRR1313136 1 0.2136 0.807 0.904 0.000 0.008 0.000 0.088
#> SRR1313137 4 0.5303 0.776 0.020 0.000 0.188 0.704 0.088
#> SRR1313138 4 0.5303 0.776 0.020 0.000 0.188 0.704 0.088
#> SRR1313140 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313141 1 0.0794 0.872 0.972 0.000 0.000 0.000 0.028
#> SRR1313139 4 0.5007 0.783 0.008 0.000 0.188 0.716 0.088
#> SRR1313143 1 0.0794 0.872 0.972 0.000 0.000 0.000 0.028
#> SRR1313142 1 0.0162 0.872 0.996 0.000 0.004 0.000 0.000
#> SRR1313144 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313145 1 0.0162 0.872 0.996 0.000 0.004 0.000 0.000
#> SRR1313146 1 0.0324 0.870 0.992 0.000 0.004 0.000 0.004
#> SRR1313147 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313150 4 0.4325 0.798 0.000 0.000 0.180 0.756 0.064
#> SRR1313149 1 0.0794 0.872 0.972 0.000 0.000 0.000 0.028
#> SRR1313152 4 0.5303 0.776 0.020 0.000 0.188 0.704 0.088
#> SRR1313151 1 0.0162 0.872 0.996 0.000 0.004 0.000 0.000
#> SRR1313154 1 0.0566 0.873 0.984 0.000 0.004 0.000 0.012
#> SRR1313153 1 0.2136 0.807 0.904 0.000 0.008 0.000 0.088
#> SRR1313156 1 0.1197 0.864 0.952 0.000 0.000 0.000 0.048
#> SRR1313155 1 0.0451 0.869 0.988 0.000 0.004 0.000 0.008
#> SRR1313157 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313158 1 0.0162 0.872 0.996 0.000 0.004 0.000 0.000
#> SRR1313161 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313159 5 0.4304 0.265 0.484 0.000 0.000 0.000 0.516
#> SRR1313160 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313162 1 0.2017 0.814 0.912 0.000 0.008 0.000 0.080
#> SRR1313163 1 0.3354 0.755 0.844 0.000 0.068 0.000 0.088
#> SRR1313165 4 0.5114 0.781 0.012 0.000 0.188 0.712 0.088
#> SRR1313166 1 0.0703 0.873 0.976 0.000 0.000 0.000 0.024
#> SRR1313164 1 0.2813 0.763 0.832 0.000 0.000 0.000 0.168
#> SRR1313167 1 0.7479 0.275 0.508 0.000 0.192 0.212 0.088
#> SRR1313168 4 0.5303 0.776 0.020 0.000 0.188 0.704 0.088
#> SRR1313170 5 0.3109 0.628 0.000 0.000 0.200 0.000 0.800
#> SRR1313169 4 0.5303 0.776 0.020 0.000 0.188 0.704 0.088
#> SRR1313172 5 0.2773 0.843 0.164 0.000 0.000 0.000 0.836
#> SRR1313171 5 0.4074 0.555 0.364 0.000 0.000 0.000 0.636
#> SRR1313174 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313173 1 0.2813 0.763 0.832 0.000 0.000 0.000 0.168
#> SRR1313176 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313178 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313180 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313181 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.0671 0.984 0.000 0.980 0.004 0.000 0.016
#> SRR1313184 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313185 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313188 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313187 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313186 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313189 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313192 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313195 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313196 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313197 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313198 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313199 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313201 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313203 5 0.3837 0.666 0.308 0.000 0.000 0.000 0.692
#> SRR1313204 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313209 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313211 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313212 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313215 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313213 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 2 0.2773 0.801 0.000 0.836 0.000 0.000 0.164
#> SRR1313217 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313219 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313220 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313222 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 2 0.0798 0.983 0.000 0.976 0.008 0.000 0.016
#> SRR1313226 2 0.0912 0.982 0.000 0.972 0.012 0.000 0.016
#> SRR1313227 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.986 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0458 0.9789 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313063 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313064 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313066 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313067 3 0.3215 0.7135 0.004 0.000 0.756 0.240 0.000 0.000
#> SRR1313068 4 0.0146 0.9852 0.000 0.000 0.004 0.996 0.000 0.000
#> SRR1313069 4 0.0146 0.9877 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313070 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.0146 0.9877 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313074 4 0.0146 0.9877 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313075 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.0458 0.9789 0.016 0.000 0.000 0.984 0.000 0.000
#> SRR1313077 4 0.0790 0.9667 0.032 0.000 0.000 0.968 0.000 0.000
#> SRR1313078 6 0.0603 0.8936 0.016 0.000 0.000 0.000 0.004 0.980
#> SRR1313079 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.0937 0.9370 0.000 0.000 0.040 0.960 0.000 0.000
#> SRR1313081 4 0.0790 0.9667 0.032 0.000 0.000 0.968 0.000 0.000
#> SRR1313082 4 0.0363 0.9824 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1313083 6 0.5082 0.0797 0.408 0.000 0.000 0.080 0.000 0.512
#> SRR1313084 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 4 0.0713 0.9653 0.028 0.000 0.000 0.972 0.000 0.000
#> SRR1313087 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0363 0.9824 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1313089 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313092 6 0.0632 0.8886 0.000 0.000 0.000 0.000 0.024 0.976
#> SRR1313090 3 0.1829 0.8759 0.028 0.000 0.928 0.036 0.008 0.000
#> SRR1313091 5 0.1515 0.8820 0.000 0.028 0.008 0.000 0.944 0.020
#> SRR1313093 6 0.3838 0.1545 0.000 0.000 0.000 0.000 0.448 0.552
#> SRR1313095 3 0.3073 0.7758 0.008 0.000 0.824 0.000 0.016 0.152
#> SRR1313096 6 0.0260 0.8923 0.000 0.000 0.000 0.000 0.008 0.992
#> SRR1313094 5 0.1141 0.8987 0.000 0.000 0.000 0.000 0.948 0.052
#> SRR1313097 5 0.1327 0.8562 0.000 0.000 0.064 0.000 0.936 0.000
#> SRR1313099 5 0.0865 0.9024 0.000 0.000 0.000 0.000 0.964 0.036
#> SRR1313098 6 0.0603 0.8936 0.016 0.000 0.000 0.000 0.004 0.980
#> SRR1313101 3 0.1007 0.8811 0.000 0.000 0.956 0.000 0.044 0.000
#> SRR1313102 5 0.2003 0.8238 0.000 0.000 0.116 0.000 0.884 0.000
#> SRR1313103 5 0.0865 0.9024 0.000 0.000 0.000 0.000 0.964 0.036
#> SRR1313100 4 0.0000 0.9891 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313105 5 0.0972 0.9013 0.000 0.000 0.008 0.000 0.964 0.028
#> SRR1313104 5 0.2309 0.8555 0.000 0.000 0.028 0.000 0.888 0.084
#> SRR1313107 5 0.1007 0.9002 0.000 0.000 0.000 0.000 0.956 0.044
#> SRR1313106 3 0.2744 0.8321 0.064 0.000 0.864 0.000 0.072 0.000
#> SRR1313109 5 0.0865 0.9024 0.000 0.000 0.000 0.000 0.964 0.036
#> SRR1313108 6 0.2823 0.7305 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313111 5 0.0972 0.9013 0.000 0.000 0.008 0.000 0.964 0.028
#> SRR1313110 3 0.2772 0.7994 0.180 0.000 0.816 0.000 0.000 0.004
#> SRR1313112 3 0.1007 0.8811 0.000 0.000 0.956 0.000 0.044 0.000
#> SRR1313113 5 0.0972 0.9013 0.000 0.000 0.008 0.000 0.964 0.028
#> SRR1313115 6 0.2823 0.7305 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1313114 3 0.2877 0.8076 0.168 0.000 0.820 0.000 0.000 0.012
#> SRR1313117 3 0.1007 0.8811 0.000 0.000 0.956 0.000 0.044 0.000
#> SRR1313118 3 0.4186 0.5731 0.312 0.000 0.656 0.032 0.000 0.000
#> SRR1313116 5 0.1074 0.9001 0.000 0.000 0.012 0.000 0.960 0.028
#> SRR1313120 5 0.1141 0.8962 0.000 0.000 0.000 0.000 0.948 0.052
#> SRR1313119 3 0.1168 0.8801 0.028 0.000 0.956 0.000 0.016 0.000
#> SRR1313122 3 0.1007 0.8811 0.000 0.000 0.956 0.000 0.044 0.000
#> SRR1313124 3 0.1007 0.8811 0.000 0.000 0.956 0.000 0.044 0.000
#> SRR1313121 3 0.2597 0.7845 0.000 0.000 0.824 0.176 0.000 0.000
#> SRR1313125 3 0.1806 0.8666 0.008 0.000 0.928 0.000 0.020 0.044
#> SRR1313127 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313123 6 0.0603 0.8936 0.016 0.000 0.000 0.000 0.004 0.980
#> SRR1313128 6 0.0146 0.8927 0.000 0.000 0.000 0.000 0.004 0.996
#> SRR1313126 6 0.4236 0.4656 0.036 0.000 0.308 0.000 0.000 0.656
#> SRR1313130 2 0.4752 0.7866 0.252 0.676 0.036 0.000 0.036 0.000
#> SRR1313132 6 0.1204 0.8676 0.000 0.000 0.000 0.000 0.056 0.944
#> SRR1313129 5 0.0972 0.9013 0.000 0.000 0.008 0.000 0.964 0.028
#> SRR1313133 6 0.0458 0.8900 0.000 0.000 0.000 0.000 0.016 0.984
#> SRR1313131 6 0.2793 0.7352 0.000 0.000 0.000 0.000 0.200 0.800
#> SRR1313134 6 0.1910 0.8289 0.000 0.000 0.000 0.000 0.108 0.892
#> SRR1313135 1 0.3490 0.9458 0.724 0.000 0.000 0.268 0.000 0.008
#> SRR1313136 6 0.1007 0.8773 0.044 0.000 0.000 0.000 0.000 0.956
#> SRR1313137 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313138 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313140 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313141 6 0.0260 0.8923 0.000 0.000 0.000 0.000 0.008 0.992
#> SRR1313139 1 0.3351 0.9642 0.712 0.000 0.000 0.288 0.000 0.000
#> SRR1313143 6 0.0260 0.8923 0.000 0.000 0.000 0.000 0.008 0.992
#> SRR1313142 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313144 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313145 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313146 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313147 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313150 1 0.3428 0.9430 0.696 0.000 0.000 0.304 0.000 0.000
#> SRR1313149 6 0.0260 0.8923 0.000 0.000 0.000 0.000 0.008 0.992
#> SRR1313152 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313151 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313154 6 0.0603 0.8936 0.016 0.000 0.000 0.000 0.004 0.980
#> SRR1313153 6 0.1007 0.8773 0.044 0.000 0.000 0.000 0.000 0.956
#> SRR1313156 6 0.0790 0.8820 0.000 0.000 0.000 0.000 0.032 0.968
#> SRR1313155 6 0.0547 0.8915 0.020 0.000 0.000 0.000 0.000 0.980
#> SRR1313157 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313158 6 0.0458 0.8932 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1313161 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313159 5 0.3672 0.4778 0.000 0.000 0.000 0.000 0.632 0.368
#> SRR1313160 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313162 6 0.1007 0.8773 0.044 0.000 0.000 0.000 0.000 0.956
#> SRR1313163 6 0.3390 0.5965 0.296 0.000 0.000 0.000 0.000 0.704
#> SRR1313165 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313166 6 0.0291 0.8932 0.004 0.000 0.000 0.000 0.004 0.992
#> SRR1313164 6 0.2912 0.7139 0.000 0.000 0.000 0.000 0.216 0.784
#> SRR1313167 1 0.4122 0.5986 0.724 0.000 0.000 0.064 0.000 0.212
#> SRR1313168 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313170 5 0.3290 0.6440 0.000 0.000 0.252 0.000 0.744 0.004
#> SRR1313169 1 0.3468 0.9691 0.712 0.000 0.000 0.284 0.000 0.004
#> SRR1313172 5 0.1204 0.8944 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1313171 5 0.3409 0.5987 0.000 0.000 0.000 0.000 0.700 0.300
#> SRR1313174 2 0.4899 0.7825 0.256 0.664 0.044 0.000 0.036 0.000
#> SRR1313173 6 0.2793 0.7352 0.000 0.000 0.000 0.000 0.200 0.800
#> SRR1313176 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 2 0.4941 0.7791 0.264 0.656 0.044 0.000 0.036 0.000
#> SRR1313178 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.4158 0.8048 0.204 0.740 0.020 0.000 0.036 0.000
#> SRR1313180 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313181 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3428 0.8222 0.128 0.820 0.020 0.000 0.032 0.000
#> SRR1313184 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313185 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313188 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313187 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313186 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313189 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313192 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313194 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313195 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313196 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313197 2 0.4899 0.7825 0.256 0.664 0.044 0.000 0.036 0.000
#> SRR1313198 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313199 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313201 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313203 5 0.3351 0.6161 0.000 0.000 0.000 0.000 0.712 0.288
#> SRR1313204 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313209 2 0.4899 0.7825 0.256 0.664 0.044 0.000 0.036 0.000
#> SRR1313211 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313212 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 2 0.4899 0.7825 0.256 0.664 0.044 0.000 0.036 0.000
#> SRR1313215 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313213 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 2 0.3076 0.6146 0.000 0.760 0.000 0.000 0.240 0.000
#> SRR1313217 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313219 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313220 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.4148 0.8067 0.192 0.748 0.024 0.000 0.036 0.000
#> SRR1313222 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 2 0.4054 0.8096 0.180 0.760 0.024 0.000 0.036 0.000
#> SRR1313226 2 0.4980 0.7756 0.272 0.648 0.044 0.000 0.036 0.000
#> SRR1313227 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.8549 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "pam"]
# you can also extract it by
# res = res_list["ATC:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4408 0.560 0.560
#> 3 3 0.765 0.749 0.890 0.4302 0.787 0.625
#> 4 4 0.993 0.941 0.974 0.1037 0.835 0.604
#> 5 5 0.776 0.758 0.820 0.0977 0.914 0.728
#> 6 6 0.804 0.727 0.862 0.0789 0.876 0.534
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2
There is also optional best \(k\) = 2 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 1.000 1.000 0.000
#> SRR1313063 1 0.0000 1.000 1.000 0.000
#> SRR1313064 1 0.0000 1.000 1.000 0.000
#> SRR1313065 1 0.0000 1.000 1.000 0.000
#> SRR1313066 1 0.0000 1.000 1.000 0.000
#> SRR1313067 1 0.0000 1.000 1.000 0.000
#> SRR1313068 1 0.0000 1.000 1.000 0.000
#> SRR1313069 1 0.0000 1.000 1.000 0.000
#> SRR1313070 1 0.0000 1.000 1.000 0.000
#> SRR1313071 1 0.0000 1.000 1.000 0.000
#> SRR1313072 1 0.0000 1.000 1.000 0.000
#> SRR1313073 1 0.0000 1.000 1.000 0.000
#> SRR1313074 1 0.0000 1.000 1.000 0.000
#> SRR1313075 1 0.0000 1.000 1.000 0.000
#> SRR1313076 1 0.0000 1.000 1.000 0.000
#> SRR1313077 1 0.0000 1.000 1.000 0.000
#> SRR1313078 1 0.0000 1.000 1.000 0.000
#> SRR1313079 1 0.0000 1.000 1.000 0.000
#> SRR1313080 1 0.0000 1.000 1.000 0.000
#> SRR1313081 1 0.0000 1.000 1.000 0.000
#> SRR1313082 1 0.0000 1.000 1.000 0.000
#> SRR1313083 1 0.0000 1.000 1.000 0.000
#> SRR1313084 1 0.0000 1.000 1.000 0.000
#> SRR1313085 1 0.0000 1.000 1.000 0.000
#> SRR1313086 1 0.0000 1.000 1.000 0.000
#> SRR1313087 1 0.0000 1.000 1.000 0.000
#> SRR1313088 1 0.0000 1.000 1.000 0.000
#> SRR1313089 1 0.0000 1.000 1.000 0.000
#> SRR1313092 1 0.0000 1.000 1.000 0.000
#> SRR1313090 1 0.0000 1.000 1.000 0.000
#> SRR1313091 1 0.0000 1.000 1.000 0.000
#> SRR1313093 1 0.0000 1.000 1.000 0.000
#> SRR1313095 1 0.0000 1.000 1.000 0.000
#> SRR1313096 1 0.0000 1.000 1.000 0.000
#> SRR1313094 1 0.0000 1.000 1.000 0.000
#> SRR1313097 1 0.0000 1.000 1.000 0.000
#> SRR1313099 1 0.0000 1.000 1.000 0.000
#> SRR1313098 1 0.0000 1.000 1.000 0.000
#> SRR1313101 1 0.0000 1.000 1.000 0.000
#> SRR1313102 1 0.0000 1.000 1.000 0.000
#> SRR1313103 1 0.0000 1.000 1.000 0.000
#> SRR1313100 1 0.0000 1.000 1.000 0.000
#> SRR1313105 1 0.0000 1.000 1.000 0.000
#> SRR1313104 1 0.0000 1.000 1.000 0.000
#> SRR1313107 1 0.0000 1.000 1.000 0.000
#> SRR1313106 1 0.0000 1.000 1.000 0.000
#> SRR1313109 1 0.0000 1.000 1.000 0.000
#> SRR1313108 1 0.0000 1.000 1.000 0.000
#> SRR1313111 1 0.0000 1.000 1.000 0.000
#> SRR1313110 1 0.0000 1.000 1.000 0.000
#> SRR1313112 1 0.0000 1.000 1.000 0.000
#> SRR1313113 1 0.0000 1.000 1.000 0.000
#> SRR1313115 1 0.0000 1.000 1.000 0.000
#> SRR1313114 1 0.0000 1.000 1.000 0.000
#> SRR1313117 1 0.0000 1.000 1.000 0.000
#> SRR1313118 1 0.0000 1.000 1.000 0.000
#> SRR1313116 1 0.0000 1.000 1.000 0.000
#> SRR1313120 1 0.0000 1.000 1.000 0.000
#> SRR1313119 1 0.0000 1.000 1.000 0.000
#> SRR1313122 1 0.0000 1.000 1.000 0.000
#> SRR1313124 1 0.0000 1.000 1.000 0.000
#> SRR1313121 1 0.0000 1.000 1.000 0.000
#> SRR1313125 1 0.0000 1.000 1.000 0.000
#> SRR1313127 1 0.0000 1.000 1.000 0.000
#> SRR1313123 1 0.0000 1.000 1.000 0.000
#> SRR1313128 1 0.0000 1.000 1.000 0.000
#> SRR1313126 1 0.0000 1.000 1.000 0.000
#> SRR1313130 1 0.1633 0.975 0.976 0.024
#> SRR1313132 1 0.0000 1.000 1.000 0.000
#> SRR1313129 1 0.0000 1.000 1.000 0.000
#> SRR1313133 1 0.0000 1.000 1.000 0.000
#> SRR1313131 1 0.0000 1.000 1.000 0.000
#> SRR1313134 1 0.0000 1.000 1.000 0.000
#> SRR1313135 1 0.0000 1.000 1.000 0.000
#> SRR1313136 1 0.0000 1.000 1.000 0.000
#> SRR1313137 1 0.0000 1.000 1.000 0.000
#> SRR1313138 1 0.0000 1.000 1.000 0.000
#> SRR1313140 1 0.0000 1.000 1.000 0.000
#> SRR1313141 1 0.0000 1.000 1.000 0.000
#> SRR1313139 1 0.0000 1.000 1.000 0.000
#> SRR1313143 1 0.0000 1.000 1.000 0.000
#> SRR1313142 1 0.0000 1.000 1.000 0.000
#> SRR1313144 1 0.0000 1.000 1.000 0.000
#> SRR1313145 1 0.0000 1.000 1.000 0.000
#> SRR1313146 1 0.0000 1.000 1.000 0.000
#> SRR1313147 1 0.0000 1.000 1.000 0.000
#> SRR1313150 1 0.0000 1.000 1.000 0.000
#> SRR1313149 1 0.0000 1.000 1.000 0.000
#> SRR1313152 1 0.0000 1.000 1.000 0.000
#> SRR1313151 1 0.0000 1.000 1.000 0.000
#> SRR1313154 1 0.0000 1.000 1.000 0.000
#> SRR1313153 1 0.0000 1.000 1.000 0.000
#> SRR1313156 1 0.0000 1.000 1.000 0.000
#> SRR1313155 1 0.0000 1.000 1.000 0.000
#> SRR1313157 1 0.0000 1.000 1.000 0.000
#> SRR1313158 1 0.0000 1.000 1.000 0.000
#> SRR1313161 1 0.0000 1.000 1.000 0.000
#> SRR1313159 1 0.0000 1.000 1.000 0.000
#> SRR1313160 1 0.0000 1.000 1.000 0.000
#> SRR1313162 1 0.0000 1.000 1.000 0.000
#> SRR1313163 1 0.0000 1.000 1.000 0.000
#> SRR1313165 1 0.0000 1.000 1.000 0.000
#> SRR1313166 1 0.0000 1.000 1.000 0.000
#> SRR1313164 1 0.0000 1.000 1.000 0.000
#> SRR1313167 1 0.0000 1.000 1.000 0.000
#> SRR1313168 1 0.0000 1.000 1.000 0.000
#> SRR1313170 1 0.0000 1.000 1.000 0.000
#> SRR1313169 1 0.0000 1.000 1.000 0.000
#> SRR1313172 1 0.0000 1.000 1.000 0.000
#> SRR1313171 1 0.0000 1.000 1.000 0.000
#> SRR1313174 2 0.0000 1.000 0.000 1.000
#> SRR1313173 1 0.0000 1.000 1.000 0.000
#> SRR1313176 2 0.0000 1.000 0.000 1.000
#> SRR1313175 2 0.0000 1.000 0.000 1.000
#> SRR1313178 2 0.0000 1.000 0.000 1.000
#> SRR1313177 2 0.0000 1.000 0.000 1.000
#> SRR1313179 2 0.0000 1.000 0.000 1.000
#> SRR1313180 2 0.0000 1.000 0.000 1.000
#> SRR1313181 2 0.0000 1.000 0.000 1.000
#> SRR1313183 2 0.0000 1.000 0.000 1.000
#> SRR1313182 2 0.0000 1.000 0.000 1.000
#> SRR1313184 2 0.0000 1.000 0.000 1.000
#> SRR1313185 2 0.0000 1.000 0.000 1.000
#> SRR1313188 2 0.0000 1.000 0.000 1.000
#> SRR1313187 2 0.0000 1.000 0.000 1.000
#> SRR1313186 2 0.0000 1.000 0.000 1.000
#> SRR1313189 2 0.0000 1.000 0.000 1.000
#> SRR1313190 2 0.0000 1.000 0.000 1.000
#> SRR1313191 2 0.0000 1.000 0.000 1.000
#> SRR1313192 2 0.0000 1.000 0.000 1.000
#> SRR1313193 2 0.0000 1.000 0.000 1.000
#> SRR1313194 2 0.0000 1.000 0.000 1.000
#> SRR1313195 2 0.0000 1.000 0.000 1.000
#> SRR1313196 2 0.0000 1.000 0.000 1.000
#> SRR1313197 2 0.0000 1.000 0.000 1.000
#> SRR1313198 2 0.0000 1.000 0.000 1.000
#> SRR1313199 2 0.0000 1.000 0.000 1.000
#> SRR1313200 2 0.0000 1.000 0.000 1.000
#> SRR1313201 2 0.0000 1.000 0.000 1.000
#> SRR1313202 2 0.0000 1.000 0.000 1.000
#> SRR1313203 1 0.0000 1.000 1.000 0.000
#> SRR1313204 2 0.0000 1.000 0.000 1.000
#> SRR1313205 2 0.0000 1.000 0.000 1.000
#> SRR1313207 2 0.0000 1.000 0.000 1.000
#> SRR1313208 2 0.0000 1.000 0.000 1.000
#> SRR1313206 2 0.0000 1.000 0.000 1.000
#> SRR1313210 2 0.0000 1.000 0.000 1.000
#> SRR1313209 2 0.0000 1.000 0.000 1.000
#> SRR1313211 2 0.0000 1.000 0.000 1.000
#> SRR1313212 2 0.0000 1.000 0.000 1.000
#> SRR1313214 2 0.0000 1.000 0.000 1.000
#> SRR1313215 2 0.0000 1.000 0.000 1.000
#> SRR1313213 2 0.0000 1.000 0.000 1.000
#> SRR1313216 2 0.0938 0.988 0.012 0.988
#> SRR1313217 2 0.0000 1.000 0.000 1.000
#> SRR1313219 2 0.0000 1.000 0.000 1.000
#> SRR1313220 2 0.0000 1.000 0.000 1.000
#> SRR1313218 2 0.0000 1.000 0.000 1.000
#> SRR1313222 2 0.0000 1.000 0.000 1.000
#> SRR1313221 2 0.0000 1.000 0.000 1.000
#> SRR1313223 2 0.0000 1.000 0.000 1.000
#> SRR1313224 2 0.0000 1.000 0.000 1.000
#> SRR1313225 2 0.0000 1.000 0.000 1.000
#> SRR1313226 1 0.0000 1.000 1.000 0.000
#> SRR1313227 2 0.0000 1.000 0.000 1.000
#> SRR1313228 2 0.0000 1.000 0.000 1.000
#> SRR1313229 2 0.0000 1.000 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313063 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313065 1 0.6286 -0.1039 0.536 0.000 0.464
#> SRR1313066 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313067 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313068 1 0.1411 0.7959 0.964 0.000 0.036
#> SRR1313069 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313076 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313077 1 0.0747 0.8125 0.984 0.000 0.016
#> SRR1313078 3 0.0424 0.7646 0.008 0.000 0.992
#> SRR1313079 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313080 1 0.2959 0.7359 0.900 0.000 0.100
#> SRR1313081 1 0.6274 -0.0719 0.544 0.000 0.456
#> SRR1313082 1 0.0237 0.8203 0.996 0.000 0.004
#> SRR1313083 3 0.6235 0.4198 0.436 0.000 0.564
#> SRR1313084 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313086 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313087 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313088 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313089 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313092 3 0.4974 0.6722 0.236 0.000 0.764
#> SRR1313090 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313091 3 0.3155 0.7556 0.040 0.044 0.916
#> SRR1313093 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313095 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313096 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313094 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313097 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313099 3 0.0237 0.7671 0.004 0.000 0.996
#> SRR1313098 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313101 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313102 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313103 3 0.1289 0.7725 0.032 0.000 0.968
#> SRR1313100 1 0.0000 0.8224 1.000 0.000 0.000
#> SRR1313105 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313104 3 0.3038 0.7523 0.104 0.000 0.896
#> SRR1313107 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313106 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313109 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313108 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313111 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313110 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313112 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313113 3 0.1643 0.7730 0.044 0.000 0.956
#> SRR1313115 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313114 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313117 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313118 3 0.6079 0.5279 0.388 0.000 0.612
#> SRR1313116 3 0.2878 0.7562 0.096 0.000 0.904
#> SRR1313120 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313119 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313122 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313124 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313121 3 0.6126 0.5021 0.400 0.000 0.600
#> SRR1313125 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313127 3 0.2537 0.7640 0.080 0.000 0.920
#> SRR1313123 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313128 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313126 3 0.6008 0.5560 0.372 0.000 0.628
#> SRR1313130 2 0.6728 0.6255 0.184 0.736 0.080
#> SRR1313132 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313129 3 0.4605 0.6949 0.204 0.000 0.796
#> SRR1313133 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313131 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313134 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313135 1 0.6291 -0.1204 0.532 0.000 0.468
#> SRR1313136 3 0.1964 0.7702 0.056 0.000 0.944
#> SRR1313137 3 0.6291 0.3273 0.468 0.000 0.532
#> SRR1313138 3 0.6008 0.5545 0.372 0.000 0.628
#> SRR1313140 1 0.4178 0.6518 0.828 0.000 0.172
#> SRR1313141 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313139 1 0.4504 0.6165 0.804 0.000 0.196
#> SRR1313143 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313142 3 0.1753 0.7721 0.048 0.000 0.952
#> SRR1313144 1 0.6274 -0.0719 0.544 0.000 0.456
#> SRR1313145 3 0.1964 0.7702 0.056 0.000 0.944
#> SRR1313146 3 0.1163 0.7671 0.028 0.000 0.972
#> SRR1313147 1 0.6274 -0.0719 0.544 0.000 0.456
#> SRR1313150 1 0.5859 0.3052 0.656 0.000 0.344
#> SRR1313149 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313152 3 0.6308 0.2440 0.492 0.000 0.508
#> SRR1313151 3 0.0424 0.7646 0.008 0.000 0.992
#> SRR1313154 3 0.0237 0.7654 0.004 0.000 0.996
#> SRR1313153 3 0.1964 0.7702 0.056 0.000 0.944
#> SRR1313156 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313155 3 0.1964 0.7702 0.056 0.000 0.944
#> SRR1313157 1 0.6274 -0.0719 0.544 0.000 0.456
#> SRR1313158 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313161 3 0.6307 0.2588 0.488 0.000 0.512
#> SRR1313159 3 0.1529 0.7732 0.040 0.000 0.960
#> SRR1313160 3 0.6225 0.4309 0.432 0.000 0.568
#> SRR1313162 3 0.1964 0.7702 0.056 0.000 0.944
#> SRR1313163 3 0.6008 0.5545 0.372 0.000 0.628
#> SRR1313165 3 0.6252 0.3996 0.444 0.000 0.556
#> SRR1313166 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313164 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313167 3 0.6008 0.5560 0.372 0.000 0.628
#> SRR1313168 3 0.6244 0.4107 0.440 0.000 0.560
#> SRR1313170 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313169 1 0.6309 -0.2316 0.504 0.000 0.496
#> SRR1313172 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313171 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313174 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.7659 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313180 2 0.5098 0.6223 0.248 0.752 0.000
#> SRR1313181 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313203 3 0.5968 0.5662 0.364 0.000 0.636
#> SRR1313204 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313216 2 0.2537 0.8895 0.000 0.920 0.080
#> SRR1313217 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313226 2 0.6359 0.3290 0.364 0.628 0.008
#> SRR1313227 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.9801 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.9801 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313063 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313064 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313065 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313066 4 0.1302 0.859 0.000 0.000 0.044 0.956
#> SRR1313067 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313068 4 0.4761 0.547 0.004 0.000 0.332 0.664
#> SRR1313069 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313077 4 0.4866 0.410 0.000 0.000 0.404 0.596
#> SRR1313078 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313079 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313080 4 0.4819 0.524 0.004 0.000 0.344 0.652
#> SRR1313081 3 0.0817 0.944 0.000 0.000 0.976 0.024
#> SRR1313082 4 0.4907 0.272 0.000 0.000 0.420 0.580
#> SRR1313083 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313084 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313085 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0188 0.895 0.000 0.000 0.004 0.996
#> SRR1313087 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313088 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.0000 0.899 0.000 0.000 0.000 1.000
#> SRR1313092 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313090 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313091 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313093 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313095 3 0.0592 0.961 0.016 0.000 0.984 0.000
#> SRR1313096 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313094 3 0.4855 0.400 0.400 0.000 0.600 0.000
#> SRR1313097 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313099 1 0.1022 0.948 0.968 0.000 0.032 0.000
#> SRR1313098 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313101 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313102 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313103 3 0.4040 0.698 0.248 0.000 0.752 0.000
#> SRR1313100 3 0.0707 0.954 0.000 0.000 0.980 0.020
#> SRR1313105 3 0.0817 0.959 0.024 0.000 0.976 0.000
#> SRR1313104 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313107 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313106 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313109 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313108 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313111 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313110 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313112 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313113 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313115 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313114 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313117 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313118 3 0.0592 0.961 0.016 0.000 0.984 0.000
#> SRR1313116 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313120 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313119 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313122 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313124 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313121 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313125 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313127 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313123 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313128 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313126 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313130 3 0.1411 0.945 0.020 0.020 0.960 0.000
#> SRR1313132 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313129 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313133 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313131 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313134 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313135 3 0.0188 0.958 0.000 0.000 0.996 0.004
#> SRR1313136 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313137 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313138 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313140 3 0.0817 0.944 0.000 0.000 0.976 0.024
#> SRR1313141 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313139 3 0.3569 0.733 0.000 0.000 0.804 0.196
#> SRR1313143 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313142 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313144 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313145 3 0.0188 0.958 0.004 0.000 0.996 0.000
#> SRR1313146 3 0.3311 0.784 0.172 0.000 0.828 0.000
#> SRR1313147 3 0.0336 0.956 0.000 0.000 0.992 0.008
#> SRR1313150 3 0.0469 0.957 0.000 0.000 0.988 0.012
#> SRR1313149 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313152 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313151 3 0.4804 0.393 0.384 0.000 0.616 0.000
#> SRR1313154 3 0.4804 0.393 0.384 0.000 0.616 0.000
#> SRR1313153 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313156 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313155 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313157 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313158 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313161 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313159 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313160 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313162 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313163 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313165 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313166 1 0.0707 0.979 0.980 0.000 0.020 0.000
#> SRR1313164 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313167 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313168 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313170 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313169 3 0.0000 0.959 0.000 0.000 1.000 0.000
#> SRR1313172 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313171 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313174 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1313176 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313180 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313181 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313188 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313203 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313204 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.1174 0.962 0.020 0.968 0.012 0.000
#> SRR1313217 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.0707 0.961 0.020 0.000 0.980 0.000
#> SRR1313227 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.999 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.999 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313063 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313064 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313065 1 0.2773 0.8089 0.836 0.000 0.164 0.000 0.000
#> SRR1313066 4 0.1478 0.8439 0.064 0.000 0.000 0.936 0.000
#> SRR1313067 1 0.3913 0.8139 0.676 0.000 0.324 0.000 0.000
#> SRR1313068 4 0.4015 0.4573 0.348 0.000 0.000 0.652 0.000
#> SRR1313069 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313070 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313071 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313072 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313073 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313074 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313075 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313076 4 0.0162 0.8875 0.004 0.000 0.000 0.996 0.000
#> SRR1313077 4 0.4410 0.2565 0.440 0.000 0.004 0.556 0.000
#> SRR1313078 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313079 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313080 4 0.4313 0.4259 0.356 0.000 0.008 0.636 0.000
#> SRR1313081 1 0.3656 0.7973 0.800 0.000 0.168 0.032 0.000
#> SRR1313082 4 0.6244 0.2750 0.348 0.000 0.156 0.496 0.000
#> SRR1313083 1 0.2773 0.8089 0.836 0.000 0.164 0.000 0.000
#> SRR1313084 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313085 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313086 4 0.2732 0.7626 0.160 0.000 0.000 0.840 0.000
#> SRR1313087 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313088 4 0.0000 0.8896 0.000 0.000 0.000 1.000 0.000
#> SRR1313089 4 0.0609 0.8779 0.020 0.000 0.000 0.980 0.000
#> SRR1313092 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313090 1 0.3913 0.8138 0.676 0.000 0.324 0.000 0.000
#> SRR1313091 5 0.6814 -0.2733 0.304 0.000 0.348 0.000 0.348
#> SRR1313093 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313095 1 0.3932 0.8145 0.672 0.000 0.328 0.000 0.000
#> SRR1313096 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313094 3 0.3707 -0.1814 0.284 0.000 0.716 0.000 0.000
#> SRR1313097 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313099 3 0.3449 0.7242 0.024 0.000 0.812 0.000 0.164
#> SRR1313098 1 0.4252 0.8094 0.652 0.000 0.340 0.000 0.008
#> SRR1313101 1 0.3949 0.8119 0.668 0.000 0.332 0.000 0.000
#> SRR1313102 1 0.3999 0.8091 0.656 0.000 0.344 0.000 0.000
#> SRR1313103 3 0.4256 -0.5484 0.436 0.000 0.564 0.000 0.000
#> SRR1313100 1 0.3053 0.8073 0.828 0.000 0.164 0.008 0.000
#> SRR1313105 1 0.4030 0.8067 0.648 0.000 0.352 0.000 0.000
#> SRR1313104 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313107 3 0.3895 0.8719 0.000 0.000 0.680 0.000 0.320
#> SRR1313106 5 0.4794 0.4494 0.032 0.000 0.344 0.000 0.624
#> SRR1313109 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313108 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313111 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313110 1 0.3857 0.8164 0.688 0.000 0.312 0.000 0.000
#> SRR1313112 1 0.3949 0.8119 0.668 0.000 0.332 0.000 0.000
#> SRR1313113 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313115 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313114 1 0.3876 0.8159 0.684 0.000 0.316 0.000 0.000
#> SRR1313117 1 0.3999 0.8091 0.656 0.000 0.344 0.000 0.000
#> SRR1313118 1 0.2773 0.8089 0.836 0.000 0.164 0.000 0.000
#> SRR1313116 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313120 3 0.3895 0.8719 0.000 0.000 0.680 0.000 0.320
#> SRR1313119 1 0.3949 0.8119 0.668 0.000 0.332 0.000 0.000
#> SRR1313122 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313124 1 0.3949 0.8119 0.668 0.000 0.332 0.000 0.000
#> SRR1313121 1 0.3895 0.8146 0.680 0.000 0.320 0.000 0.000
#> SRR1313125 1 0.3949 0.8119 0.668 0.000 0.332 0.000 0.000
#> SRR1313127 1 0.2929 0.8089 0.840 0.000 0.152 0.000 0.008
#> SRR1313123 1 0.2891 0.8074 0.824 0.000 0.176 0.000 0.000
#> SRR1313128 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313126 1 0.2966 0.8128 0.816 0.000 0.184 0.000 0.000
#> SRR1313130 5 0.4558 0.4994 0.000 0.024 0.324 0.000 0.652
#> SRR1313132 3 0.3862 0.6919 0.104 0.000 0.808 0.000 0.088
#> SRR1313129 1 0.4015 0.8086 0.652 0.000 0.348 0.000 0.000
#> SRR1313133 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313131 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313134 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313135 1 0.0162 0.7908 0.996 0.000 0.000 0.004 0.000
#> SRR1313136 1 0.0451 0.7916 0.988 0.000 0.004 0.000 0.008
#> SRR1313137 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.0162 0.7941 0.996 0.000 0.004 0.000 0.000
#> SRR1313140 1 0.0880 0.7717 0.968 0.000 0.000 0.032 0.000
#> SRR1313141 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313139 1 0.3039 0.5677 0.808 0.000 0.000 0.192 0.000
#> SRR1313143 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313142 1 0.0579 0.7918 0.984 0.000 0.008 0.000 0.008
#> SRR1313144 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313145 1 0.0898 0.7876 0.972 0.000 0.008 0.000 0.020
#> SRR1313146 1 0.3488 0.6047 0.808 0.000 0.168 0.000 0.024
#> SRR1313147 1 0.0290 0.7886 0.992 0.000 0.000 0.008 0.000
#> SRR1313150 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313149 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313152 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.4902 0.0903 0.564 0.000 0.408 0.000 0.028
#> SRR1313154 1 0.4974 0.0874 0.508 0.000 0.464 0.000 0.028
#> SRR1313153 1 0.0566 0.7907 0.984 0.000 0.004 0.000 0.012
#> SRR1313156 1 0.2891 0.8074 0.824 0.000 0.176 0.000 0.000
#> SRR1313155 1 0.0566 0.7907 0.984 0.000 0.004 0.000 0.012
#> SRR1313157 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313158 1 0.3093 0.8069 0.824 0.000 0.168 0.000 0.008
#> SRR1313161 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313159 1 0.2891 0.8074 0.824 0.000 0.176 0.000 0.000
#> SRR1313160 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313162 1 0.0451 0.7916 0.988 0.000 0.004 0.000 0.008
#> SRR1313163 1 0.1908 0.8086 0.908 0.000 0.092 0.000 0.000
#> SRR1313165 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313166 3 0.3983 0.8812 0.000 0.000 0.660 0.000 0.340
#> SRR1313164 3 0.2852 0.7537 0.000 0.000 0.828 0.000 0.172
#> SRR1313167 1 0.1341 0.8049 0.944 0.000 0.056 0.000 0.000
#> SRR1313168 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313170 1 0.3999 0.8091 0.656 0.000 0.344 0.000 0.000
#> SRR1313169 1 0.0000 0.7927 1.000 0.000 0.000 0.000 0.000
#> SRR1313172 3 0.3895 0.8719 0.000 0.000 0.680 0.000 0.320
#> SRR1313171 3 0.3983 0.8806 0.000 0.000 0.660 0.000 0.340
#> SRR1313174 5 0.4114 0.7805 0.000 0.376 0.000 0.000 0.624
#> SRR1313173 3 0.4015 0.8840 0.000 0.000 0.652 0.000 0.348
#> SRR1313176 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313178 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313180 5 0.4418 0.8071 0.016 0.332 0.000 0.000 0.652
#> SRR1313181 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.0609 0.8672 0.000 0.980 0.000 0.000 0.020
#> SRR1313184 2 0.4074 0.1000 0.000 0.636 0.000 0.000 0.364
#> SRR1313185 2 0.4114 0.0419 0.000 0.624 0.000 0.000 0.376
#> SRR1313188 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313187 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313186 2 0.4283 -0.3344 0.000 0.544 0.000 0.000 0.456
#> SRR1313189 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.3612 0.4381 0.000 0.732 0.000 0.000 0.268
#> SRR1313192 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0162 0.8822 0.000 0.996 0.000 0.000 0.004
#> SRR1313194 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313195 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313196 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313197 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313198 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313199 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313201 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313203 1 0.4166 0.8069 0.648 0.000 0.348 0.000 0.004
#> SRR1313204 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313209 5 0.4235 0.6789 0.000 0.424 0.000 0.000 0.576
#> SRR1313211 2 0.3966 0.2072 0.000 0.664 0.000 0.000 0.336
#> SRR1313212 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313215 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313213 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 5 0.5979 0.6092 0.016 0.168 0.180 0.000 0.636
#> SRR1313217 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313219 5 0.4015 0.8257 0.000 0.348 0.000 0.000 0.652
#> SRR1313220 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.3074 0.6088 0.000 0.804 0.000 0.000 0.196
#> SRR1313222 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.1908 0.7824 0.000 0.908 0.000 0.000 0.092
#> SRR1313225 2 0.4030 0.1520 0.000 0.648 0.000 0.000 0.352
#> SRR1313226 5 0.5844 0.6147 0.016 0.156 0.176 0.000 0.652
#> SRR1313227 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.8857 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.0260 0.94879 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1313063 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313064 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 1 0.3706 0.36989 0.620 0.000 0.380 0.000 0.000 0.000
#> SRR1313066 4 0.2070 0.86478 0.100 0.000 0.008 0.892 0.000 0.000
#> SRR1313067 3 0.2260 0.76030 0.140 0.000 0.860 0.000 0.000 0.000
#> SRR1313068 4 0.4136 0.62224 0.076 0.000 0.192 0.732 0.000 0.000
#> SRR1313069 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313070 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313071 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313072 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313073 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313074 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313075 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.1204 0.91018 0.056 0.000 0.000 0.944 0.000 0.000
#> SRR1313077 1 0.3866 -0.07704 0.516 0.000 0.000 0.484 0.000 0.000
#> SRR1313078 6 0.0146 0.89485 0.004 0.000 0.000 0.000 0.000 0.996
#> SRR1313079 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 4 0.4382 0.56559 0.076 0.000 0.228 0.696 0.000 0.000
#> SRR1313081 1 0.3582 0.54267 0.732 0.000 0.252 0.016 0.000 0.000
#> SRR1313082 1 0.4944 0.50557 0.644 0.000 0.224 0.132 0.000 0.000
#> SRR1313083 1 0.3823 0.25570 0.564 0.000 0.436 0.000 0.000 0.000
#> SRR1313084 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313085 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313086 1 0.3765 0.17837 0.596 0.000 0.000 0.404 0.000 0.000
#> SRR1313087 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0000 0.95381 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313089 4 0.0146 0.95116 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313092 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313090 3 0.2219 0.76371 0.136 0.000 0.864 0.000 0.000 0.000
#> SRR1313091 3 0.3409 0.40248 0.000 0.000 0.700 0.000 0.300 0.000
#> SRR1313093 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313095 3 0.2454 0.74286 0.160 0.000 0.840 0.000 0.000 0.000
#> SRR1313096 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313094 3 0.3198 0.42835 0.000 0.000 0.740 0.000 0.000 0.260
#> SRR1313097 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313099 3 0.3866 -0.20104 0.000 0.000 0.516 0.000 0.000 0.484
#> SRR1313098 3 0.2178 0.76733 0.132 0.000 0.868 0.000 0.000 0.000
#> SRR1313101 3 0.2135 0.76774 0.128 0.000 0.872 0.000 0.000 0.000
#> SRR1313102 3 0.1204 0.77205 0.056 0.000 0.944 0.000 0.000 0.000
#> SRR1313103 3 0.1814 0.68951 0.000 0.000 0.900 0.000 0.000 0.100
#> SRR1313100 1 0.4569 0.29080 0.564 0.000 0.396 0.040 0.000 0.000
#> SRR1313105 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313104 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313107 6 0.2003 0.82699 0.000 0.000 0.116 0.000 0.000 0.884
#> SRR1313106 3 0.3592 0.32922 0.000 0.000 0.656 0.000 0.344 0.000
#> SRR1313109 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313108 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313111 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313110 3 0.3126 0.62858 0.248 0.000 0.752 0.000 0.000 0.000
#> SRR1313112 3 0.2135 0.76774 0.128 0.000 0.872 0.000 0.000 0.000
#> SRR1313113 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313115 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313114 3 0.3050 0.64825 0.236 0.000 0.764 0.000 0.000 0.000
#> SRR1313117 3 0.2092 0.76904 0.124 0.000 0.876 0.000 0.000 0.000
#> SRR1313118 3 0.3869 -0.11643 0.500 0.000 0.500 0.000 0.000 0.000
#> SRR1313116 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313120 6 0.2003 0.82699 0.000 0.000 0.116 0.000 0.000 0.884
#> SRR1313119 3 0.2135 0.76774 0.128 0.000 0.872 0.000 0.000 0.000
#> SRR1313122 3 0.1765 0.77217 0.096 0.000 0.904 0.000 0.000 0.000
#> SRR1313124 3 0.2135 0.76774 0.128 0.000 0.872 0.000 0.000 0.000
#> SRR1313121 3 0.3315 0.72752 0.156 0.000 0.804 0.000 0.040 0.000
#> SRR1313125 3 0.2219 0.76335 0.136 0.000 0.864 0.000 0.000 0.000
#> SRR1313127 1 0.3869 -0.10374 0.500 0.000 0.500 0.000 0.000 0.000
#> SRR1313123 3 0.3747 0.37883 0.396 0.000 0.604 0.000 0.000 0.000
#> SRR1313128 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313126 3 0.3857 0.00664 0.468 0.000 0.532 0.000 0.000 0.000
#> SRR1313130 5 0.3023 0.64058 0.000 0.000 0.232 0.000 0.768 0.000
#> SRR1313132 6 0.5605 0.26663 0.152 0.000 0.360 0.000 0.000 0.488
#> SRR1313129 3 0.0000 0.76662 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313133 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313131 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313134 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313135 1 0.0146 0.76259 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313136 1 0.1714 0.73547 0.908 0.000 0.092 0.000 0.000 0.000
#> SRR1313137 1 0.0000 0.76370 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313138 1 0.3266 0.56716 0.728 0.000 0.272 0.000 0.000 0.000
#> SRR1313140 1 0.0458 0.75659 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1313141 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313139 1 0.0632 0.75192 0.976 0.000 0.000 0.024 0.000 0.000
#> SRR1313143 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313142 1 0.3198 0.58146 0.740 0.000 0.260 0.000 0.000 0.000
#> SRR1313144 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313145 1 0.2445 0.72690 0.872 0.000 0.108 0.000 0.000 0.020
#> SRR1313146 1 0.2679 0.72832 0.864 0.000 0.096 0.000 0.000 0.040
#> SRR1313147 1 0.0146 0.76259 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1313150 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313149 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313152 1 0.0000 0.76370 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313151 1 0.5740 0.00111 0.436 0.000 0.168 0.000 0.000 0.396
#> SRR1313154 6 0.6012 0.05566 0.364 0.000 0.240 0.000 0.000 0.396
#> SRR1313153 1 0.0000 0.76370 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313156 3 0.3244 0.48546 0.268 0.000 0.732 0.000 0.000 0.000
#> SRR1313155 1 0.1957 0.72480 0.888 0.000 0.112 0.000 0.000 0.000
#> SRR1313157 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313158 3 0.3756 0.37309 0.400 0.000 0.600 0.000 0.000 0.000
#> SRR1313161 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313159 3 0.3747 0.37883 0.396 0.000 0.604 0.000 0.000 0.000
#> SRR1313160 1 0.3050 0.61298 0.764 0.000 0.236 0.000 0.000 0.000
#> SRR1313162 1 0.3023 0.61869 0.768 0.000 0.232 0.000 0.000 0.000
#> SRR1313163 1 0.3804 0.20466 0.576 0.000 0.424 0.000 0.000 0.000
#> SRR1313165 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313166 6 0.0291 0.89381 0.004 0.000 0.004 0.000 0.000 0.992
#> SRR1313164 6 0.3866 0.23765 0.000 0.000 0.484 0.000 0.000 0.516
#> SRR1313167 1 0.3659 0.43011 0.636 0.000 0.364 0.000 0.000 0.000
#> SRR1313168 1 0.0146 0.76445 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1313170 3 0.2092 0.76904 0.124 0.000 0.876 0.000 0.000 0.000
#> SRR1313169 1 0.0000 0.76370 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1313172 6 0.2260 0.80510 0.000 0.000 0.140 0.000 0.000 0.860
#> SRR1313171 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313174 5 0.0458 0.89144 0.000 0.016 0.000 0.000 0.984 0.000
#> SRR1313173 6 0.0000 0.89715 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313180 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313181 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.3727 0.33740 0.000 0.612 0.000 0.000 0.388 0.000
#> SRR1313184 5 0.5300 0.36045 0.000 0.344 0.116 0.000 0.540 0.000
#> SRR1313185 5 0.3151 0.63973 0.000 0.252 0.000 0.000 0.748 0.000
#> SRR1313188 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313187 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313186 5 0.2048 0.80695 0.000 0.120 0.000 0.000 0.880 0.000
#> SRR1313189 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 5 0.3789 0.28079 0.000 0.416 0.000 0.000 0.584 0.000
#> SRR1313192 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0937 0.89333 0.000 0.960 0.000 0.000 0.040 0.000
#> SRR1313194 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313195 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313196 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313197 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313198 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313203 3 0.0146 0.76462 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1313204 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313209 5 0.1444 0.85037 0.000 0.072 0.000 0.000 0.928 0.000
#> SRR1313211 2 0.3727 0.30634 0.000 0.612 0.000 0.000 0.388 0.000
#> SRR1313212 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 5 0.0260 0.89598 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1313215 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 5 0.4381 0.20324 0.016 0.004 0.456 0.000 0.524 0.000
#> SRR1313217 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313219 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.3868 -0.01010 0.000 0.508 0.000 0.000 0.492 0.000
#> SRR1313222 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.3810 0.22297 0.000 0.572 0.000 0.000 0.428 0.000
#> SRR1313225 5 0.3515 0.50981 0.000 0.324 0.000 0.000 0.676 0.000
#> SRR1313226 5 0.0000 0.89971 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1313227 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.93015 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "mclust"]
# you can also extract it by
# res = res_list["ATC:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.986 0.992 0.4445 0.556 0.556
#> 3 3 0.517 0.582 0.712 0.4048 0.790 0.622
#> 4 4 0.572 0.647 0.750 0.1118 0.851 0.605
#> 5 5 0.608 0.551 0.714 0.0860 0.893 0.628
#> 6 6 0.672 0.620 0.748 0.0563 0.896 0.594
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.0000 0.993 1.000 0.000
#> SRR1313063 1 0.0000 0.993 1.000 0.000
#> SRR1313064 1 0.0000 0.993 1.000 0.000
#> SRR1313065 1 0.0000 0.993 1.000 0.000
#> SRR1313066 1 0.0000 0.993 1.000 0.000
#> SRR1313067 1 0.0000 0.993 1.000 0.000
#> SRR1313068 1 0.0000 0.993 1.000 0.000
#> SRR1313069 1 0.0000 0.993 1.000 0.000
#> SRR1313070 1 0.0000 0.993 1.000 0.000
#> SRR1313071 1 0.0000 0.993 1.000 0.000
#> SRR1313072 1 0.0000 0.993 1.000 0.000
#> SRR1313073 1 0.0000 0.993 1.000 0.000
#> SRR1313074 1 0.0000 0.993 1.000 0.000
#> SRR1313075 1 0.0000 0.993 1.000 0.000
#> SRR1313076 1 0.0000 0.993 1.000 0.000
#> SRR1313077 1 0.0000 0.993 1.000 0.000
#> SRR1313078 1 0.0000 0.993 1.000 0.000
#> SRR1313079 1 0.0000 0.993 1.000 0.000
#> SRR1313080 1 0.0000 0.993 1.000 0.000
#> SRR1313081 1 0.0000 0.993 1.000 0.000
#> SRR1313082 1 0.0000 0.993 1.000 0.000
#> SRR1313083 1 0.0000 0.993 1.000 0.000
#> SRR1313084 1 0.0000 0.993 1.000 0.000
#> SRR1313085 1 0.0000 0.993 1.000 0.000
#> SRR1313086 1 0.0000 0.993 1.000 0.000
#> SRR1313087 1 0.0000 0.993 1.000 0.000
#> SRR1313088 1 0.0000 0.993 1.000 0.000
#> SRR1313089 1 0.0000 0.993 1.000 0.000
#> SRR1313092 1 0.0000 0.993 1.000 0.000
#> SRR1313090 1 0.1633 0.981 0.976 0.024
#> SRR1313091 1 0.1633 0.981 0.976 0.024
#> SRR1313093 1 0.0000 0.993 1.000 0.000
#> SRR1313095 1 0.0000 0.993 1.000 0.000
#> SRR1313096 1 0.0000 0.993 1.000 0.000
#> SRR1313094 1 0.1633 0.981 0.976 0.024
#> SRR1313097 1 0.1633 0.981 0.976 0.024
#> SRR1313099 1 0.1633 0.981 0.976 0.024
#> SRR1313098 1 0.0000 0.993 1.000 0.000
#> SRR1313101 1 0.1633 0.981 0.976 0.024
#> SRR1313102 1 0.1633 0.981 0.976 0.024
#> SRR1313103 1 0.1633 0.981 0.976 0.024
#> SRR1313100 1 0.0000 0.993 1.000 0.000
#> SRR1313105 1 0.1633 0.981 0.976 0.024
#> SRR1313104 1 0.1633 0.981 0.976 0.024
#> SRR1313107 1 0.1633 0.981 0.976 0.024
#> SRR1313106 1 0.1633 0.981 0.976 0.024
#> SRR1313109 1 0.1633 0.981 0.976 0.024
#> SRR1313108 1 0.0000 0.993 1.000 0.000
#> SRR1313111 1 0.1633 0.981 0.976 0.024
#> SRR1313110 1 0.0938 0.987 0.988 0.012
#> SRR1313112 1 0.1633 0.981 0.976 0.024
#> SRR1313113 1 0.1633 0.981 0.976 0.024
#> SRR1313115 1 0.0000 0.993 1.000 0.000
#> SRR1313114 1 0.0672 0.989 0.992 0.008
#> SRR1313117 1 0.1633 0.981 0.976 0.024
#> SRR1313118 1 0.1633 0.981 0.976 0.024
#> SRR1313116 1 0.1633 0.981 0.976 0.024
#> SRR1313120 1 0.0000 0.993 1.000 0.000
#> SRR1313119 1 0.1633 0.981 0.976 0.024
#> SRR1313122 1 0.1633 0.981 0.976 0.024
#> SRR1313124 1 0.1633 0.981 0.976 0.024
#> SRR1313121 1 0.1633 0.981 0.976 0.024
#> SRR1313125 1 0.1633 0.981 0.976 0.024
#> SRR1313127 1 0.0000 0.993 1.000 0.000
#> SRR1313123 1 0.0000 0.993 1.000 0.000
#> SRR1313128 1 0.0000 0.993 1.000 0.000
#> SRR1313126 1 0.0000 0.993 1.000 0.000
#> SRR1313130 2 0.8081 0.670 0.248 0.752
#> SRR1313132 1 0.0000 0.993 1.000 0.000
#> SRR1313129 1 0.1633 0.981 0.976 0.024
#> SRR1313133 1 0.0000 0.993 1.000 0.000
#> SRR1313131 1 0.0000 0.993 1.000 0.000
#> SRR1313134 1 0.0000 0.993 1.000 0.000
#> SRR1313135 1 0.0000 0.993 1.000 0.000
#> SRR1313136 1 0.0000 0.993 1.000 0.000
#> SRR1313137 1 0.0000 0.993 1.000 0.000
#> SRR1313138 1 0.1633 0.981 0.976 0.024
#> SRR1313140 1 0.0000 0.993 1.000 0.000
#> SRR1313141 1 0.0000 0.993 1.000 0.000
#> SRR1313139 1 0.0000 0.993 1.000 0.000
#> SRR1313143 1 0.0000 0.993 1.000 0.000
#> SRR1313142 1 0.0000 0.993 1.000 0.000
#> SRR1313144 1 0.0000 0.993 1.000 0.000
#> SRR1313145 1 0.0000 0.993 1.000 0.000
#> SRR1313146 1 0.0000 0.993 1.000 0.000
#> SRR1313147 1 0.0000 0.993 1.000 0.000
#> SRR1313150 1 0.0000 0.993 1.000 0.000
#> SRR1313149 1 0.0000 0.993 1.000 0.000
#> SRR1313152 1 0.0000 0.993 1.000 0.000
#> SRR1313151 1 0.0000 0.993 1.000 0.000
#> SRR1313154 1 0.0000 0.993 1.000 0.000
#> SRR1313153 1 0.0000 0.993 1.000 0.000
#> SRR1313156 1 0.0000 0.993 1.000 0.000
#> SRR1313155 1 0.0000 0.993 1.000 0.000
#> SRR1313157 1 0.0000 0.993 1.000 0.000
#> SRR1313158 1 0.0000 0.993 1.000 0.000
#> SRR1313161 1 0.0000 0.993 1.000 0.000
#> SRR1313159 1 0.1633 0.981 0.976 0.024
#> SRR1313160 1 0.0000 0.993 1.000 0.000
#> SRR1313162 1 0.0000 0.993 1.000 0.000
#> SRR1313163 1 0.0000 0.993 1.000 0.000
#> SRR1313165 1 0.0000 0.993 1.000 0.000
#> SRR1313166 1 0.0000 0.993 1.000 0.000
#> SRR1313164 1 0.0000 0.993 1.000 0.000
#> SRR1313167 1 0.0000 0.993 1.000 0.000
#> SRR1313168 1 0.0000 0.993 1.000 0.000
#> SRR1313170 1 0.1633 0.981 0.976 0.024
#> SRR1313169 1 0.0000 0.993 1.000 0.000
#> SRR1313172 1 0.0000 0.993 1.000 0.000
#> SRR1313171 1 0.0000 0.993 1.000 0.000
#> SRR1313174 2 0.0000 0.991 0.000 1.000
#> SRR1313173 1 0.0000 0.993 1.000 0.000
#> SRR1313176 2 0.0000 0.991 0.000 1.000
#> SRR1313175 2 0.0000 0.991 0.000 1.000
#> SRR1313178 2 0.0000 0.991 0.000 1.000
#> SRR1313177 2 0.0000 0.991 0.000 1.000
#> SRR1313179 2 0.0000 0.991 0.000 1.000
#> SRR1313180 2 0.0000 0.991 0.000 1.000
#> SRR1313181 2 0.0000 0.991 0.000 1.000
#> SRR1313183 2 0.0000 0.991 0.000 1.000
#> SRR1313182 2 0.0000 0.991 0.000 1.000
#> SRR1313184 2 0.0000 0.991 0.000 1.000
#> SRR1313185 2 0.0000 0.991 0.000 1.000
#> SRR1313188 2 0.0000 0.991 0.000 1.000
#> SRR1313187 2 0.0000 0.991 0.000 1.000
#> SRR1313186 2 0.0000 0.991 0.000 1.000
#> SRR1313189 2 0.0000 0.991 0.000 1.000
#> SRR1313190 2 0.0000 0.991 0.000 1.000
#> SRR1313191 2 0.0000 0.991 0.000 1.000
#> SRR1313192 2 0.0000 0.991 0.000 1.000
#> SRR1313193 2 0.0000 0.991 0.000 1.000
#> SRR1313194 2 0.0000 0.991 0.000 1.000
#> SRR1313195 2 0.0000 0.991 0.000 1.000
#> SRR1313196 2 0.0000 0.991 0.000 1.000
#> SRR1313197 2 0.0000 0.991 0.000 1.000
#> SRR1313198 2 0.0000 0.991 0.000 1.000
#> SRR1313199 2 0.0000 0.991 0.000 1.000
#> SRR1313200 2 0.0000 0.991 0.000 1.000
#> SRR1313201 2 0.0000 0.991 0.000 1.000
#> SRR1313202 2 0.0000 0.991 0.000 1.000
#> SRR1313203 1 0.0000 0.993 1.000 0.000
#> SRR1313204 2 0.0000 0.991 0.000 1.000
#> SRR1313205 2 0.0000 0.991 0.000 1.000
#> SRR1313207 2 0.0000 0.991 0.000 1.000
#> SRR1313208 2 0.0000 0.991 0.000 1.000
#> SRR1313206 2 0.0000 0.991 0.000 1.000
#> SRR1313210 2 0.0000 0.991 0.000 1.000
#> SRR1313209 2 0.0000 0.991 0.000 1.000
#> SRR1313211 2 0.0000 0.991 0.000 1.000
#> SRR1313212 2 0.0000 0.991 0.000 1.000
#> SRR1313214 2 0.0000 0.991 0.000 1.000
#> SRR1313215 2 0.0000 0.991 0.000 1.000
#> SRR1313213 2 0.0000 0.991 0.000 1.000
#> SRR1313216 1 0.4562 0.905 0.904 0.096
#> SRR1313217 2 0.0000 0.991 0.000 1.000
#> SRR1313219 2 0.0000 0.991 0.000 1.000
#> SRR1313220 2 0.0000 0.991 0.000 1.000
#> SRR1313218 2 0.0000 0.991 0.000 1.000
#> SRR1313222 2 0.0000 0.991 0.000 1.000
#> SRR1313221 2 0.0000 0.991 0.000 1.000
#> SRR1313223 2 0.0000 0.991 0.000 1.000
#> SRR1313224 2 0.0000 0.991 0.000 1.000
#> SRR1313225 2 0.0000 0.991 0.000 1.000
#> SRR1313226 2 0.8207 0.655 0.256 0.744
#> SRR1313227 2 0.0000 0.991 0.000 1.000
#> SRR1313228 2 0.0000 0.991 0.000 1.000
#> SRR1313229 2 0.0000 0.991 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.5591 0.5476 0.696 0.000 0.304
#> SRR1313063 1 0.5591 0.5639 0.696 0.000 0.304
#> SRR1313064 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313065 1 0.6026 0.3736 0.624 0.000 0.376
#> SRR1313066 1 0.6026 0.4376 0.624 0.000 0.376
#> SRR1313067 3 0.6154 0.6912 0.408 0.000 0.592
#> SRR1313068 1 0.6973 0.2700 0.564 0.020 0.416
#> SRR1313069 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313070 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313071 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313072 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313073 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313074 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313075 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313076 1 0.6192 0.4289 0.580 0.000 0.420
#> SRR1313077 1 0.4178 0.5874 0.828 0.000 0.172
#> SRR1313078 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313079 1 0.5254 0.5730 0.736 0.000 0.264
#> SRR1313080 1 0.7839 0.2977 0.560 0.060 0.380
#> SRR1313081 1 0.6302 0.2275 0.520 0.000 0.480
#> SRR1313082 1 0.4931 0.5756 0.768 0.000 0.232
#> SRR1313083 1 0.3941 0.5376 0.844 0.000 0.156
#> SRR1313084 1 0.6026 0.4467 0.624 0.000 0.376
#> SRR1313085 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313086 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313087 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313088 1 0.4842 0.5748 0.776 0.000 0.224
#> SRR1313089 1 0.5926 0.4165 0.644 0.000 0.356
#> SRR1313092 3 0.6215 0.6909 0.428 0.000 0.572
#> SRR1313090 3 0.6359 0.7022 0.404 0.004 0.592
#> SRR1313091 3 0.9063 0.5181 0.200 0.248 0.552
#> SRR1313093 1 0.2711 0.5227 0.912 0.000 0.088
#> SRR1313095 3 0.6154 0.6980 0.408 0.000 0.592
#> SRR1313096 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313094 3 0.6225 0.6975 0.432 0.000 0.568
#> SRR1313097 3 0.8625 0.6407 0.252 0.156 0.592
#> SRR1313099 3 0.6252 0.6905 0.444 0.000 0.556
#> SRR1313098 1 0.6154 -0.2484 0.592 0.000 0.408
#> SRR1313101 3 0.8753 0.5640 0.188 0.224 0.588
#> SRR1313102 3 0.8714 0.6405 0.264 0.156 0.580
#> SRR1313103 3 0.6252 0.6905 0.444 0.000 0.556
#> SRR1313100 3 0.6154 0.6912 0.408 0.000 0.592
#> SRR1313105 3 0.6168 0.6994 0.412 0.000 0.588
#> SRR1313104 3 0.7490 0.7124 0.380 0.044 0.576
#> SRR1313107 3 0.6260 0.6870 0.448 0.000 0.552
#> SRR1313106 3 0.9371 0.3850 0.172 0.376 0.452
#> SRR1313109 3 0.8771 0.6321 0.304 0.140 0.556
#> SRR1313108 1 0.2711 0.5227 0.912 0.000 0.088
#> SRR1313111 3 0.6460 0.6945 0.440 0.004 0.556
#> SRR1313110 3 0.6154 0.6980 0.408 0.000 0.592
#> SRR1313112 3 0.8862 0.6293 0.272 0.164 0.564
#> SRR1313113 3 0.8269 0.6767 0.316 0.100 0.584
#> SRR1313115 1 0.4555 0.3701 0.800 0.000 0.200
#> SRR1313114 3 0.6154 0.6980 0.408 0.000 0.592
#> SRR1313117 3 0.8717 0.6075 0.220 0.188 0.592
#> SRR1313118 3 0.6154 0.6980 0.408 0.000 0.592
#> SRR1313116 3 0.8799 0.5675 0.196 0.220 0.584
#> SRR1313120 3 0.6291 0.6594 0.468 0.000 0.532
#> SRR1313119 3 0.6881 0.7114 0.388 0.020 0.592
#> SRR1313122 3 0.8683 0.6251 0.236 0.172 0.592
#> SRR1313124 3 0.7571 0.7103 0.356 0.052 0.592
#> SRR1313121 3 0.7099 0.7133 0.384 0.028 0.588
#> SRR1313125 3 0.7571 0.7103 0.356 0.052 0.592
#> SRR1313127 1 0.5988 -0.0562 0.632 0.000 0.368
#> SRR1313123 1 0.6244 -0.4083 0.560 0.000 0.440
#> SRR1313128 1 0.1529 0.5564 0.960 0.000 0.040
#> SRR1313126 1 0.6235 -0.2449 0.564 0.000 0.436
#> SRR1313130 2 0.7918 0.3050 0.136 0.660 0.204
#> SRR1313132 1 0.6140 -0.2727 0.596 0.000 0.404
#> SRR1313129 3 0.9040 0.5750 0.240 0.204 0.556
#> SRR1313133 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313131 1 0.2711 0.5227 0.912 0.000 0.088
#> SRR1313134 1 0.2711 0.5227 0.912 0.000 0.088
#> SRR1313135 1 0.6267 0.2603 0.548 0.000 0.452
#> SRR1313136 1 0.5529 0.1325 0.704 0.000 0.296
#> SRR1313137 1 0.6274 0.2659 0.544 0.000 0.456
#> SRR1313138 3 0.6299 0.6450 0.476 0.000 0.524
#> SRR1313140 1 0.6305 0.2965 0.516 0.000 0.484
#> SRR1313141 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313139 1 0.6307 0.2992 0.512 0.000 0.488
#> SRR1313143 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313142 1 0.1031 0.5717 0.976 0.000 0.024
#> SRR1313144 1 0.6295 0.2859 0.528 0.000 0.472
#> SRR1313145 1 0.5529 0.1325 0.704 0.000 0.296
#> SRR1313146 1 0.4842 0.2684 0.776 0.000 0.224
#> SRR1313147 1 0.6305 0.2965 0.516 0.000 0.484
#> SRR1313150 3 0.6062 0.3109 0.384 0.000 0.616
#> SRR1313149 1 0.1860 0.5519 0.948 0.000 0.052
#> SRR1313152 1 0.6299 0.2899 0.524 0.000 0.476
#> SRR1313151 1 0.0237 0.5663 0.996 0.000 0.004
#> SRR1313154 1 0.0237 0.5663 0.996 0.000 0.004
#> SRR1313153 1 0.4931 0.3198 0.768 0.000 0.232
#> SRR1313156 1 0.6309 -0.5943 0.504 0.000 0.496
#> SRR1313155 1 0.1529 0.5705 0.960 0.000 0.040
#> SRR1313157 1 0.6299 0.2899 0.524 0.000 0.476
#> SRR1313158 1 0.5926 -0.1257 0.644 0.000 0.356
#> SRR1313161 3 0.6192 0.2603 0.420 0.000 0.580
#> SRR1313159 3 0.6299 0.6450 0.476 0.000 0.524
#> SRR1313160 3 0.6079 0.3438 0.388 0.000 0.612
#> SRR1313162 1 0.5706 0.1043 0.680 0.000 0.320
#> SRR1313163 1 0.6274 -0.4806 0.544 0.000 0.456
#> SRR1313165 3 0.6168 0.3594 0.412 0.000 0.588
#> SRR1313166 1 0.1860 0.5550 0.948 0.000 0.052
#> SRR1313164 1 0.4750 0.3643 0.784 0.000 0.216
#> SRR1313167 3 0.6286 0.5769 0.464 0.000 0.536
#> SRR1313168 1 0.6267 0.2603 0.548 0.000 0.452
#> SRR1313170 3 0.7589 0.7110 0.360 0.052 0.588
#> SRR1313169 1 0.6295 0.2859 0.528 0.000 0.472
#> SRR1313172 1 0.5363 0.2315 0.724 0.000 0.276
#> SRR1313171 1 0.4974 0.3176 0.764 0.000 0.236
#> SRR1313174 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313173 1 0.2711 0.5227 0.912 0.000 0.088
#> SRR1313176 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313175 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313178 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313177 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313179 2 0.0475 0.8733 0.004 0.992 0.004
#> SRR1313180 2 0.0592 0.8709 0.012 0.988 0.000
#> SRR1313181 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313183 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313182 2 0.1031 0.8794 0.000 0.976 0.024
#> SRR1313184 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313185 2 0.2448 0.8814 0.000 0.924 0.076
#> SRR1313188 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313186 2 0.2165 0.8812 0.000 0.936 0.064
#> SRR1313189 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313190 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313191 2 0.2356 0.8817 0.000 0.928 0.072
#> SRR1313192 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313193 2 0.4931 0.8759 0.000 0.768 0.232
#> SRR1313194 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313199 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313200 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313201 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313202 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313203 1 0.8941 0.0217 0.544 0.156 0.300
#> SRR1313204 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313205 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313207 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313208 2 0.2878 0.8810 0.000 0.904 0.096
#> SRR1313206 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313210 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313211 2 0.4654 0.8771 0.000 0.792 0.208
#> SRR1313212 2 0.5058 0.8754 0.000 0.756 0.244
#> SRR1313214 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313213 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313216 3 0.9500 0.4100 0.196 0.344 0.460
#> SRR1313217 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.8771 0.000 1.000 0.000
#> SRR1313220 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313218 2 0.0892 0.8790 0.000 0.980 0.020
#> SRR1313222 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313221 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313223 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313224 2 0.0892 0.8790 0.000 0.980 0.020
#> SRR1313225 2 0.0424 0.8780 0.000 0.992 0.008
#> SRR1313226 2 0.8657 0.0829 0.164 0.592 0.244
#> SRR1313227 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313228 2 0.5254 0.8735 0.000 0.736 0.264
#> SRR1313229 2 0.5254 0.8735 0.000 0.736 0.264
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.3172 0.6357 0.000 0.000 0.160 0.840
#> SRR1313063 4 0.3024 0.5858 0.000 0.000 0.148 0.852
#> SRR1313064 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313065 4 0.4008 0.4687 0.000 0.000 0.244 0.756
#> SRR1313066 4 0.3486 0.5442 0.000 0.000 0.188 0.812
#> SRR1313067 3 0.4594 0.6517 0.008 0.000 0.712 0.280
#> SRR1313068 4 0.5632 0.2549 0.000 0.036 0.340 0.624
#> SRR1313069 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313070 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313071 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313072 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313073 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313074 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313075 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313076 4 0.3610 0.6161 0.000 0.000 0.200 0.800
#> SRR1313077 4 0.5343 0.4648 0.028 0.000 0.316 0.656
#> SRR1313078 1 0.6578 0.6482 0.620 0.000 0.244 0.136
#> SRR1313079 4 0.0921 0.6531 0.000 0.000 0.028 0.972
#> SRR1313080 4 0.6238 0.2843 0.000 0.084 0.296 0.620
#> SRR1313081 4 0.4313 0.5730 0.004 0.000 0.260 0.736
#> SRR1313082 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313083 4 0.7253 0.2495 0.172 0.000 0.308 0.520
#> SRR1313084 4 0.3356 0.5571 0.000 0.000 0.176 0.824
#> SRR1313085 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313086 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.0469 0.6559 0.000 0.000 0.012 0.988
#> SRR1313088 4 0.0000 0.6582 0.000 0.000 0.000 1.000
#> SRR1313089 4 0.3942 0.4812 0.000 0.000 0.236 0.764
#> SRR1313092 3 0.4907 0.7423 0.060 0.000 0.764 0.176
#> SRR1313090 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313091 3 0.5111 0.5463 0.052 0.148 0.780 0.020
#> SRR1313093 1 0.4713 0.5693 0.640 0.000 0.360 0.000
#> SRR1313095 3 0.5314 0.7087 0.084 0.000 0.740 0.176
#> SRR1313096 1 0.5083 0.6490 0.716 0.000 0.248 0.036
#> SRR1313094 3 0.4370 0.7569 0.044 0.000 0.800 0.156
#> SRR1313097 3 0.3862 0.7564 0.000 0.024 0.824 0.152
#> SRR1313099 3 0.4370 0.7567 0.044 0.000 0.800 0.156
#> SRR1313098 3 0.7748 0.0592 0.276 0.000 0.440 0.284
#> SRR1313101 3 0.4231 0.6688 0.000 0.096 0.824 0.080
#> SRR1313102 3 0.4688 0.6788 0.012 0.088 0.812 0.088
#> SRR1313103 3 0.4452 0.7551 0.048 0.000 0.796 0.156
#> SRR1313100 3 0.4453 0.7076 0.012 0.000 0.744 0.244
#> SRR1313105 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313104 3 0.4139 0.7648 0.024 0.000 0.800 0.176
#> SRR1313107 3 0.4370 0.7567 0.044 0.000 0.800 0.156
#> SRR1313106 3 0.7297 0.1952 0.000 0.392 0.456 0.152
#> SRR1313109 3 0.4452 0.7546 0.048 0.000 0.796 0.156
#> SRR1313108 1 0.4661 0.5793 0.652 0.000 0.348 0.000
#> SRR1313111 3 0.4285 0.7585 0.040 0.000 0.804 0.156
#> SRR1313110 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313112 3 0.4199 0.7627 0.032 0.000 0.804 0.164
#> SRR1313113 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313115 1 0.4948 0.4888 0.560 0.000 0.440 0.000
#> SRR1313114 3 0.4756 0.7284 0.052 0.000 0.772 0.176
#> SRR1313117 3 0.3539 0.7677 0.000 0.004 0.820 0.176
#> SRR1313118 3 0.3681 0.7654 0.008 0.000 0.816 0.176
#> SRR1313116 3 0.4231 0.6682 0.000 0.096 0.824 0.080
#> SRR1313120 3 0.4685 0.7469 0.060 0.000 0.784 0.156
#> SRR1313119 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313122 3 0.4035 0.7607 0.000 0.020 0.804 0.176
#> SRR1313124 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313121 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313125 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313127 3 0.7760 -0.0409 0.236 0.000 0.392 0.372
#> SRR1313123 3 0.7510 -0.1768 0.380 0.000 0.436 0.184
#> SRR1313128 1 0.5219 0.6506 0.712 0.000 0.244 0.044
#> SRR1313126 4 0.6969 -0.0227 0.112 0.000 0.436 0.452
#> SRR1313130 2 0.5306 0.2654 0.020 0.632 0.348 0.000
#> SRR1313132 1 0.7442 0.3428 0.456 0.000 0.368 0.176
#> SRR1313129 3 0.5146 0.6616 0.044 0.084 0.800 0.072
#> SRR1313133 1 0.3557 0.5885 0.856 0.000 0.108 0.036
#> SRR1313131 1 0.2011 0.5392 0.920 0.000 0.080 0.000
#> SRR1313134 1 0.4168 0.5718 0.828 0.000 0.080 0.092
#> SRR1313135 4 0.6452 0.4787 0.112 0.000 0.268 0.620
#> SRR1313136 1 0.7530 0.5805 0.480 0.000 0.308 0.212
#> SRR1313137 4 0.5979 0.5097 0.076 0.000 0.272 0.652
#> SRR1313138 3 0.5957 0.2408 0.040 0.000 0.540 0.420
#> SRR1313140 4 0.3907 0.5955 0.000 0.000 0.232 0.768
#> SRR1313141 1 0.5083 0.6490 0.716 0.000 0.248 0.036
#> SRR1313139 4 0.4103 0.5747 0.000 0.000 0.256 0.744
#> SRR1313143 1 0.2408 0.5457 0.920 0.000 0.044 0.036
#> SRR1313142 1 0.7503 0.5867 0.488 0.000 0.300 0.212
#> SRR1313144 4 0.5890 0.5202 0.072 0.000 0.268 0.660
#> SRR1313145 1 0.7517 0.5855 0.484 0.000 0.304 0.212
#> SRR1313146 1 0.7344 0.6109 0.512 0.000 0.300 0.188
#> SRR1313147 4 0.5744 0.5405 0.068 0.000 0.256 0.676
#> SRR1313150 4 0.6058 0.5004 0.072 0.000 0.296 0.632
#> SRR1313149 1 0.2408 0.5457 0.920 0.000 0.044 0.036
#> SRR1313152 4 0.5873 0.5354 0.076 0.000 0.256 0.668
#> SRR1313151 1 0.7235 0.6267 0.532 0.000 0.288 0.180
#> SRR1313154 1 0.7091 0.6427 0.564 0.000 0.248 0.188
#> SRR1313153 1 0.7517 0.5855 0.484 0.000 0.304 0.212
#> SRR1313156 3 0.7510 -0.1657 0.380 0.000 0.436 0.184
#> SRR1313155 1 0.7517 0.5855 0.484 0.000 0.304 0.212
#> SRR1313157 4 0.5837 0.5327 0.072 0.000 0.260 0.668
#> SRR1313158 1 0.7717 0.4007 0.424 0.000 0.344 0.232
#> SRR1313161 4 0.6421 0.3497 0.076 0.000 0.368 0.556
#> SRR1313159 3 0.7241 0.2633 0.276 0.000 0.536 0.188
#> SRR1313160 4 0.6355 0.4056 0.076 0.000 0.348 0.576
#> SRR1313162 1 0.7712 0.4576 0.404 0.000 0.372 0.224
#> SRR1313163 3 0.7756 -0.2008 0.364 0.000 0.400 0.236
#> SRR1313165 4 0.6374 0.3460 0.072 0.000 0.372 0.556
#> SRR1313166 1 0.7205 0.6218 0.532 0.000 0.296 0.172
#> SRR1313164 1 0.7421 0.3293 0.456 0.000 0.372 0.172
#> SRR1313167 4 0.7423 0.0280 0.168 0.000 0.404 0.428
#> SRR1313168 4 0.6004 0.5022 0.076 0.000 0.276 0.648
#> SRR1313170 3 0.3356 0.7680 0.000 0.000 0.824 0.176
#> SRR1313169 4 0.5873 0.5354 0.076 0.000 0.256 0.668
#> SRR1313172 3 0.7335 0.1768 0.400 0.000 0.444 0.156
#> SRR1313171 1 0.6423 0.3824 0.648 0.000 0.196 0.156
#> SRR1313174 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.2011 0.5392 0.920 0.000 0.080 0.000
#> SRR1313176 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313175 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313177 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313179 2 0.0592 0.8690 0.016 0.984 0.000 0.000
#> SRR1313180 2 0.0592 0.8723 0.000 0.984 0.016 0.000
#> SRR1313181 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313183 2 0.5118 0.8684 0.072 0.752 0.176 0.000
#> SRR1313182 2 0.1557 0.8809 0.056 0.944 0.000 0.000
#> SRR1313184 2 0.0707 0.8664 0.020 0.980 0.000 0.000
#> SRR1313185 2 0.1256 0.8809 0.008 0.964 0.028 0.000
#> SRR1313188 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313187 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313186 2 0.1151 0.8806 0.008 0.968 0.024 0.000
#> SRR1313189 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313190 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313191 2 0.1733 0.8814 0.028 0.948 0.024 0.000
#> SRR1313192 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313193 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313194 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313195 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313196 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313197 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313200 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313201 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313202 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313203 3 0.8326 0.1180 0.380 0.076 0.444 0.100
#> SRR1313204 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313205 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313207 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313208 2 0.2759 0.8807 0.044 0.904 0.052 0.000
#> SRR1313206 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313210 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.3606 0.8765 0.024 0.844 0.132 0.000
#> SRR1313212 2 0.4356 0.8735 0.048 0.804 0.148 0.000
#> SRR1313214 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313216 3 0.5624 0.3514 0.052 0.280 0.668 0.000
#> SRR1313217 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313219 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313218 2 0.0592 0.8794 0.016 0.984 0.000 0.000
#> SRR1313222 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313221 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313223 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313224 2 0.0469 0.8714 0.012 0.988 0.000 0.000
#> SRR1313225 2 0.0000 0.8775 0.000 1.000 0.000 0.000
#> SRR1313226 2 0.4585 0.3284 0.000 0.668 0.332 0.000
#> SRR1313227 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313228 2 0.5250 0.8676 0.080 0.744 0.176 0.000
#> SRR1313229 2 0.5250 0.8676 0.080 0.744 0.176 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 4 0.5714 0.5876 0.000 0.000 0.164 0.624 0.212
#> SRR1313063 4 0.6886 0.5764 0.096 0.000 0.108 0.584 0.212
#> SRR1313064 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313065 3 0.6804 -0.1476 0.084 0.000 0.440 0.420 0.056
#> SRR1313066 4 0.7193 0.4974 0.064 0.000 0.208 0.532 0.196
#> SRR1313067 3 0.6147 0.4460 0.092 0.000 0.672 0.104 0.132
#> SRR1313068 4 0.7589 0.2775 0.064 0.000 0.352 0.400 0.184
#> SRR1313069 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313070 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313071 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313072 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313073 4 0.3877 0.6254 0.000 0.000 0.024 0.764 0.212
#> SRR1313074 4 0.3877 0.6254 0.000 0.000 0.024 0.764 0.212
#> SRR1313075 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313076 4 0.6109 0.5514 0.000 0.000 0.220 0.568 0.212
#> SRR1313077 3 0.8456 -0.2159 0.228 0.000 0.348 0.228 0.196
#> SRR1313078 1 0.5922 0.5637 0.572 0.000 0.320 0.100 0.008
#> SRR1313079 4 0.3993 0.6241 0.000 0.000 0.028 0.756 0.216
#> SRR1313080 4 0.7769 0.2822 0.064 0.004 0.336 0.400 0.196
#> SRR1313081 4 0.7391 0.4145 0.044 0.000 0.348 0.412 0.196
#> SRR1313082 4 0.4944 0.6180 0.044 0.000 0.028 0.724 0.204
#> SRR1313083 3 0.7100 -0.2881 0.284 0.000 0.424 0.276 0.016
#> SRR1313084 4 0.6982 0.5710 0.096 0.000 0.120 0.576 0.208
#> SRR1313085 4 0.3789 0.6243 0.000 0.000 0.020 0.768 0.212
#> SRR1313086 4 0.2236 0.5814 0.000 0.000 0.024 0.908 0.068
#> SRR1313087 4 0.3877 0.6254 0.000 0.000 0.024 0.764 0.212
#> SRR1313088 4 0.3877 0.6254 0.000 0.000 0.024 0.764 0.212
#> SRR1313089 4 0.7488 0.4411 0.068 0.000 0.248 0.480 0.204
#> SRR1313092 3 0.0579 0.6677 0.008 0.000 0.984 0.000 0.008
#> SRR1313090 3 0.1043 0.6633 0.040 0.000 0.960 0.000 0.000
#> SRR1313091 3 0.3491 0.5955 0.036 0.036 0.856 0.000 0.072
#> SRR1313093 1 0.4972 0.5250 0.620 0.000 0.336 0.000 0.044
#> SRR1313095 3 0.0579 0.6677 0.008 0.000 0.984 0.000 0.008
#> SRR1313096 1 0.3707 0.5778 0.716 0.000 0.284 0.000 0.000
#> SRR1313094 3 0.0693 0.6659 0.012 0.000 0.980 0.000 0.008
#> SRR1313097 3 0.0510 0.6700 0.016 0.000 0.984 0.000 0.000
#> SRR1313099 3 0.1831 0.6310 0.076 0.000 0.920 0.000 0.004
#> SRR1313098 3 0.6667 -0.3730 0.372 0.000 0.464 0.148 0.016
#> SRR1313101 3 0.1638 0.6491 0.064 0.000 0.932 0.000 0.004
#> SRR1313102 3 0.0162 0.6699 0.000 0.000 0.996 0.000 0.004
#> SRR1313103 3 0.2389 0.5973 0.116 0.000 0.880 0.000 0.004
#> SRR1313100 3 0.5251 0.4781 0.136 0.000 0.680 0.000 0.184
#> SRR1313105 3 0.0963 0.6671 0.036 0.000 0.964 0.000 0.000
#> SRR1313104 3 0.0451 0.6685 0.004 0.000 0.988 0.000 0.008
#> SRR1313107 3 0.3790 0.3670 0.272 0.000 0.724 0.000 0.004
#> SRR1313106 3 0.5005 0.4545 0.064 0.204 0.716 0.000 0.016
#> SRR1313109 3 0.1704 0.6371 0.068 0.000 0.928 0.000 0.004
#> SRR1313108 1 0.4854 0.5353 0.648 0.000 0.308 0.000 0.044
#> SRR1313111 3 0.0566 0.6661 0.012 0.000 0.984 0.000 0.004
#> SRR1313110 3 0.0566 0.6674 0.000 0.000 0.984 0.012 0.004
#> SRR1313112 3 0.0162 0.6691 0.004 0.000 0.996 0.000 0.000
#> SRR1313113 3 0.0324 0.6691 0.004 0.000 0.992 0.000 0.004
#> SRR1313115 1 0.4235 0.4313 0.576 0.000 0.424 0.000 0.000
#> SRR1313114 3 0.0867 0.6642 0.008 0.000 0.976 0.008 0.008
#> SRR1313117 3 0.1638 0.6491 0.064 0.000 0.932 0.000 0.004
#> SRR1313118 3 0.1455 0.6466 0.032 0.000 0.952 0.008 0.008
#> SRR1313116 3 0.0880 0.6663 0.032 0.000 0.968 0.000 0.000
#> SRR1313120 3 0.4009 0.2624 0.312 0.000 0.684 0.000 0.004
#> SRR1313119 3 0.1638 0.6491 0.064 0.000 0.932 0.000 0.004
#> SRR1313122 3 0.1924 0.6481 0.064 0.008 0.924 0.000 0.004
#> SRR1313124 3 0.1197 0.6595 0.048 0.000 0.952 0.000 0.000
#> SRR1313121 3 0.1764 0.6480 0.064 0.000 0.928 0.000 0.008
#> SRR1313125 3 0.0290 0.6692 0.000 0.000 0.992 0.000 0.008
#> SRR1313127 3 0.7096 -0.3415 0.276 0.000 0.448 0.256 0.020
#> SRR1313123 1 0.7125 0.4499 0.380 0.000 0.380 0.220 0.020
#> SRR1313128 1 0.4315 0.5838 0.700 0.000 0.276 0.024 0.000
#> SRR1313126 3 0.5402 0.3333 0.172 0.000 0.692 0.124 0.012
#> SRR1313130 3 0.7006 -0.3278 0.008 0.280 0.388 0.000 0.324
#> SRR1313132 1 0.6587 0.4685 0.440 0.000 0.392 0.160 0.008
#> SRR1313129 3 0.0771 0.6630 0.020 0.000 0.976 0.000 0.004
#> SRR1313133 1 0.4002 0.5190 0.796 0.000 0.120 0.000 0.084
#> SRR1313131 1 0.4149 0.4784 0.784 0.000 0.128 0.000 0.088
#> SRR1313134 1 0.4749 0.4742 0.736 0.000 0.172 0.004 0.088
#> SRR1313135 4 0.5947 0.2041 0.084 0.000 0.324 0.576 0.016
#> SRR1313136 1 0.7162 0.5291 0.420 0.000 0.308 0.252 0.020
#> SRR1313137 4 0.6026 0.2037 0.092 0.000 0.320 0.572 0.016
#> SRR1313138 3 0.5709 0.2330 0.116 0.000 0.636 0.240 0.008
#> SRR1313140 4 0.4030 0.4115 0.008 0.000 0.248 0.736 0.008
#> SRR1313141 1 0.3730 0.5755 0.712 0.000 0.288 0.000 0.000
#> SRR1313139 4 0.5113 0.4066 0.036 0.000 0.248 0.688 0.028
#> SRR1313143 1 0.3593 0.4980 0.828 0.000 0.084 0.000 0.088
#> SRR1313142 1 0.7136 0.5401 0.432 0.000 0.296 0.252 0.020
#> SRR1313144 4 0.6010 0.2290 0.096 0.000 0.304 0.584 0.016
#> SRR1313145 1 0.7154 0.5331 0.424 0.000 0.304 0.252 0.020
#> SRR1313146 1 0.7136 0.5405 0.432 0.000 0.296 0.252 0.020
#> SRR1313147 4 0.5617 0.3109 0.076 0.000 0.272 0.636 0.016
#> SRR1313150 4 0.6011 0.2923 0.104 0.000 0.284 0.596 0.016
#> SRR1313149 1 0.3593 0.4980 0.828 0.000 0.084 0.000 0.088
#> SRR1313152 4 0.5869 0.2328 0.080 0.000 0.316 0.588 0.016
#> SRR1313151 1 0.7037 0.5489 0.444 0.000 0.288 0.252 0.016
#> SRR1313154 1 0.6976 0.5586 0.464 0.000 0.268 0.252 0.016
#> SRR1313153 1 0.7154 0.5331 0.424 0.000 0.304 0.252 0.020
#> SRR1313156 3 0.6842 -0.4000 0.340 0.000 0.432 0.220 0.008
#> SRR1313155 1 0.7145 0.5365 0.428 0.000 0.300 0.252 0.020
#> SRR1313157 4 0.5626 0.3168 0.080 0.000 0.264 0.640 0.016
#> SRR1313158 1 0.7080 0.4945 0.408 0.000 0.340 0.236 0.016
#> SRR1313161 4 0.6183 0.0959 0.100 0.000 0.380 0.508 0.012
#> SRR1313159 3 0.6018 0.1384 0.172 0.000 0.612 0.208 0.008
#> SRR1313160 4 0.6142 0.0728 0.092 0.000 0.408 0.488 0.012
#> SRR1313162 3 0.7277 -0.4887 0.344 0.000 0.348 0.288 0.020
#> SRR1313163 3 0.6878 -0.2164 0.280 0.000 0.484 0.220 0.016
#> SRR1313165 4 0.6319 0.0112 0.100 0.000 0.420 0.464 0.016
#> SRR1313166 1 0.7003 0.5293 0.444 0.000 0.312 0.228 0.016
#> SRR1313164 1 0.4201 0.4545 0.592 0.000 0.408 0.000 0.000
#> SRR1313167 3 0.6275 0.0980 0.208 0.000 0.596 0.180 0.016
#> SRR1313168 4 0.6040 0.1939 0.092 0.000 0.324 0.568 0.016
#> SRR1313170 3 0.0510 0.6700 0.016 0.000 0.984 0.000 0.000
#> SRR1313169 4 0.5917 0.2267 0.084 0.000 0.316 0.584 0.016
#> SRR1313172 1 0.5538 0.3016 0.596 0.000 0.312 0.000 0.092
#> SRR1313171 1 0.5117 0.4122 0.672 0.000 0.240 0.000 0.088
#> SRR1313174 5 0.4218 0.9411 0.000 0.332 0.008 0.000 0.660
#> SRR1313173 1 0.4149 0.4784 0.784 0.000 0.128 0.000 0.088
#> SRR1313176 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 5 0.4306 0.9442 0.000 0.328 0.012 0.000 0.660
#> SRR1313178 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0290 0.8865 0.000 0.992 0.000 0.000 0.008
#> SRR1313179 5 0.4828 0.9259 0.012 0.320 0.020 0.000 0.648
#> SRR1313180 5 0.6795 0.7345 0.064 0.324 0.088 0.000 0.524
#> SRR1313181 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0290 0.8865 0.000 0.992 0.000 0.000 0.008
#> SRR1313182 2 0.3816 0.2400 0.000 0.696 0.000 0.000 0.304
#> SRR1313184 5 0.4828 0.9291 0.012 0.320 0.020 0.000 0.648
#> SRR1313185 5 0.4300 0.6782 0.000 0.476 0.000 0.000 0.524
#> SRR1313188 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313187 5 0.4852 0.9309 0.016 0.324 0.016 0.000 0.644
#> SRR1313186 5 0.4443 0.6882 0.000 0.472 0.004 0.000 0.524
#> SRR1313189 2 0.0290 0.8865 0.000 0.992 0.000 0.000 0.008
#> SRR1313190 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.4114 -0.1546 0.000 0.624 0.000 0.000 0.376
#> SRR1313192 2 0.1478 0.8286 0.000 0.936 0.000 0.000 0.064
#> SRR1313193 2 0.1478 0.8286 0.000 0.936 0.000 0.000 0.064
#> SRR1313194 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313195 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313196 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313197 5 0.4118 0.9370 0.000 0.336 0.004 0.000 0.660
#> SRR1313198 5 0.4306 0.9442 0.000 0.328 0.012 0.000 0.660
#> SRR1313199 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313201 2 0.0404 0.8832 0.000 0.988 0.000 0.000 0.012
#> SRR1313202 5 0.4625 0.9380 0.004 0.324 0.020 0.000 0.652
#> SRR1313203 3 0.5744 0.1885 0.380 0.000 0.528 0.000 0.092
#> SRR1313204 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.1851 0.7929 0.000 0.912 0.000 0.000 0.088
#> SRR1313206 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 5 0.4306 0.9442 0.000 0.328 0.012 0.000 0.660
#> SRR1313209 5 0.3983 0.9305 0.000 0.340 0.000 0.000 0.660
#> SRR1313211 2 0.3395 0.4772 0.000 0.764 0.000 0.000 0.236
#> SRR1313212 2 0.0963 0.8603 0.000 0.964 0.000 0.000 0.036
#> SRR1313214 5 0.4118 0.9370 0.000 0.336 0.004 0.000 0.660
#> SRR1313215 5 0.4118 0.9370 0.000 0.336 0.004 0.000 0.660
#> SRR1313213 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 3 0.5895 0.3704 0.036 0.108 0.664 0.000 0.192
#> SRR1313217 5 0.4384 0.9438 0.000 0.324 0.016 0.000 0.660
#> SRR1313219 5 0.4306 0.9442 0.000 0.328 0.012 0.000 0.660
#> SRR1313220 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.4192 -0.2495 0.000 0.596 0.000 0.000 0.404
#> SRR1313222 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.8898 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.4192 -0.2495 0.000 0.596 0.000 0.000 0.404
#> SRR1313225 5 0.4242 0.7884 0.000 0.428 0.000 0.000 0.572
#> SRR1313226 3 0.7313 0.0338 0.068 0.320 0.472 0.000 0.140
#> SRR1313227 2 0.0162 0.8888 0.000 0.996 0.000 0.000 0.004
#> SRR1313228 2 0.0162 0.8888 0.000 0.996 0.000 0.000 0.004
#> SRR1313229 2 0.0162 0.8888 0.000 0.996 0.000 0.000 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.4418 0.5574 0.192 0.000 0.100 0.708 0.000 0.000
#> SRR1313063 4 0.5954 0.4053 0.060 0.000 0.224 0.596 0.000 0.120
#> SRR1313064 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313065 3 0.7227 0.3028 0.232 0.000 0.420 0.228 0.000 0.120
#> SRR1313066 4 0.6517 0.1215 0.076 0.000 0.324 0.480 0.000 0.120
#> SRR1313067 3 0.5064 0.5365 0.216 0.000 0.652 0.008 0.000 0.124
#> SRR1313068 3 0.6856 0.3662 0.128 0.000 0.472 0.280 0.000 0.120
#> SRR1313069 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313070 4 0.0146 0.7271 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313071 4 0.0146 0.7271 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313072 4 0.0146 0.7271 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313073 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313074 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313075 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313076 4 0.4573 0.5347 0.208 0.000 0.104 0.688 0.000 0.000
#> SRR1313077 3 0.6888 0.0325 0.248 0.000 0.360 0.340 0.000 0.052
#> SRR1313078 6 0.4478 0.7946 0.244 0.000 0.076 0.000 0.000 0.680
#> SRR1313079 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313080 3 0.6831 0.3859 0.128 0.000 0.480 0.272 0.000 0.120
#> SRR1313081 3 0.6296 -0.0834 0.320 0.000 0.388 0.284 0.000 0.008
#> SRR1313082 4 0.3564 0.6078 0.204 0.000 0.024 0.768 0.000 0.004
#> SRR1313083 1 0.4566 -0.1054 0.540 0.000 0.428 0.028 0.000 0.004
#> SRR1313084 4 0.6237 0.2547 0.060 0.000 0.288 0.532 0.000 0.120
#> SRR1313085 4 0.0146 0.7271 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1313086 4 0.1719 0.7025 0.060 0.000 0.000 0.924 0.016 0.000
#> SRR1313087 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313088 4 0.0000 0.7286 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1313089 3 0.7064 0.1942 0.144 0.000 0.404 0.332 0.000 0.120
#> SRR1313092 3 0.1444 0.7020 0.072 0.000 0.928 0.000 0.000 0.000
#> SRR1313090 3 0.1341 0.7153 0.028 0.000 0.948 0.000 0.000 0.024
#> SRR1313091 3 0.3239 0.6956 0.004 0.164 0.808 0.000 0.024 0.000
#> SRR1313093 6 0.4687 0.8066 0.180 0.000 0.136 0.000 0.000 0.684
#> SRR1313095 3 0.1967 0.6903 0.084 0.000 0.904 0.012 0.000 0.000
#> SRR1313096 6 0.4573 0.8012 0.236 0.000 0.088 0.000 0.000 0.676
#> SRR1313094 3 0.2558 0.7171 0.028 0.104 0.868 0.000 0.000 0.000
#> SRR1313097 3 0.0363 0.7208 0.000 0.012 0.988 0.000 0.000 0.000
#> SRR1313099 3 0.3147 0.6983 0.008 0.160 0.816 0.000 0.000 0.016
#> SRR1313098 3 0.5192 0.3490 0.308 0.000 0.576 0.000 0.000 0.116
#> SRR1313101 3 0.1204 0.7103 0.000 0.000 0.944 0.000 0.000 0.056
#> SRR1313102 3 0.2454 0.7031 0.000 0.160 0.840 0.000 0.000 0.000
#> SRR1313103 3 0.3122 0.6951 0.004 0.160 0.816 0.000 0.000 0.020
#> SRR1313100 3 0.4596 0.5496 0.188 0.000 0.692 0.000 0.000 0.120
#> SRR1313105 3 0.1765 0.7144 0.000 0.096 0.904 0.000 0.000 0.000
#> SRR1313104 3 0.1714 0.7153 0.000 0.092 0.908 0.000 0.000 0.000
#> SRR1313107 3 0.3331 0.6976 0.012 0.160 0.808 0.000 0.000 0.020
#> SRR1313106 3 0.2588 0.6982 0.008 0.024 0.876 0.000 0.000 0.092
#> SRR1313109 3 0.2595 0.7026 0.004 0.160 0.836 0.000 0.000 0.000
#> SRR1313108 6 0.4650 0.8108 0.180 0.000 0.132 0.000 0.000 0.688
#> SRR1313111 3 0.2454 0.7031 0.000 0.160 0.840 0.000 0.000 0.000
#> SRR1313110 3 0.0713 0.7142 0.028 0.000 0.972 0.000 0.000 0.000
#> SRR1313112 3 0.0458 0.7209 0.000 0.016 0.984 0.000 0.000 0.000
#> SRR1313113 3 0.2595 0.7045 0.004 0.160 0.836 0.000 0.000 0.000
#> SRR1313115 6 0.4757 0.7850 0.144 0.000 0.180 0.000 0.000 0.676
#> SRR1313114 3 0.0865 0.7135 0.036 0.000 0.964 0.000 0.000 0.000
#> SRR1313117 3 0.2163 0.6950 0.016 0.000 0.892 0.000 0.000 0.092
#> SRR1313118 3 0.1007 0.7118 0.044 0.000 0.956 0.000 0.000 0.000
#> SRR1313116 3 0.1610 0.7170 0.000 0.084 0.916 0.000 0.000 0.000
#> SRR1313120 3 0.3819 0.6952 0.028 0.160 0.784 0.000 0.000 0.028
#> SRR1313119 3 0.2145 0.7024 0.028 0.000 0.900 0.000 0.000 0.072
#> SRR1313122 3 0.1970 0.6950 0.008 0.000 0.900 0.000 0.000 0.092
#> SRR1313124 3 0.0405 0.7192 0.004 0.000 0.988 0.000 0.000 0.008
#> SRR1313121 3 0.2250 0.6948 0.020 0.000 0.888 0.000 0.000 0.092
#> SRR1313125 3 0.0622 0.7194 0.012 0.008 0.980 0.000 0.000 0.000
#> SRR1313127 1 0.5221 0.1998 0.476 0.000 0.432 0.000 0.000 0.092
#> SRR1313123 1 0.5179 0.1263 0.516 0.000 0.392 0.000 0.000 0.092
#> SRR1313128 6 0.4526 0.7923 0.244 0.000 0.080 0.000 0.000 0.676
#> SRR1313126 3 0.4150 0.5301 0.204 0.000 0.732 0.004 0.000 0.060
#> SRR1313130 5 0.4264 0.0364 0.000 0.016 0.484 0.000 0.500 0.000
#> SRR1313132 1 0.5803 0.1115 0.444 0.000 0.372 0.000 0.000 0.184
#> SRR1313129 3 0.2454 0.7031 0.000 0.160 0.840 0.000 0.000 0.000
#> SRR1313133 6 0.3020 0.8231 0.080 0.000 0.076 0.000 0.000 0.844
#> SRR1313131 6 0.2678 0.7945 0.004 0.020 0.116 0.000 0.000 0.860
#> SRR1313134 6 0.3041 0.8032 0.036 0.020 0.088 0.000 0.000 0.856
#> SRR1313135 1 0.5768 -0.1030 0.464 0.000 0.112 0.408 0.016 0.000
#> SRR1313136 1 0.2537 0.4218 0.872 0.000 0.032 0.000 0.000 0.096
#> SRR1313137 1 0.5774 -0.1282 0.452 0.000 0.112 0.420 0.016 0.000
#> SRR1313138 3 0.2647 0.6994 0.088 0.000 0.868 0.044 0.000 0.000
#> SRR1313140 4 0.5699 0.1975 0.404 0.000 0.104 0.476 0.016 0.000
#> SRR1313141 6 0.4573 0.8012 0.236 0.000 0.088 0.000 0.000 0.676
#> SRR1313139 4 0.5514 0.3744 0.304 0.000 0.108 0.572 0.016 0.000
#> SRR1313143 6 0.2641 0.8095 0.048 0.004 0.072 0.000 0.000 0.876
#> SRR1313142 1 0.2404 0.3960 0.872 0.000 0.016 0.000 0.000 0.112
#> SRR1313144 1 0.5743 -0.1350 0.456 0.000 0.108 0.420 0.016 0.000
#> SRR1313145 1 0.2350 0.4147 0.880 0.000 0.020 0.000 0.000 0.100
#> SRR1313146 1 0.2624 0.3891 0.856 0.000 0.020 0.000 0.000 0.124
#> SRR1313147 4 0.5744 0.1398 0.424 0.000 0.108 0.452 0.016 0.000
#> SRR1313150 4 0.6041 0.1565 0.312 0.000 0.272 0.416 0.000 0.000
#> SRR1313149 6 0.3031 0.8042 0.048 0.020 0.072 0.000 0.000 0.860
#> SRR1313152 1 0.5743 -0.1350 0.456 0.000 0.108 0.420 0.016 0.000
#> SRR1313151 1 0.3629 0.0923 0.724 0.000 0.016 0.000 0.000 0.260
#> SRR1313154 1 0.3629 0.0923 0.724 0.000 0.016 0.000 0.000 0.260
#> SRR1313153 1 0.2301 0.4167 0.884 0.000 0.020 0.000 0.000 0.096
#> SRR1313156 3 0.5361 0.2480 0.372 0.000 0.512 0.000 0.000 0.116
#> SRR1313155 1 0.2263 0.4103 0.884 0.000 0.016 0.000 0.000 0.100
#> SRR1313157 4 0.5907 0.1742 0.396 0.000 0.132 0.456 0.016 0.000
#> SRR1313158 1 0.4812 0.3190 0.640 0.000 0.264 0.000 0.000 0.096
#> SRR1313161 3 0.6430 -0.0697 0.328 0.000 0.388 0.268 0.016 0.000
#> SRR1313159 3 0.2668 0.6734 0.168 0.004 0.828 0.000 0.000 0.000
#> SRR1313160 3 0.4812 0.3685 0.344 0.000 0.588 0.068 0.000 0.000
#> SRR1313162 1 0.4849 0.4023 0.648 0.000 0.240 0.000 0.000 0.112
#> SRR1313163 3 0.4229 0.1758 0.436 0.000 0.548 0.000 0.000 0.016
#> SRR1313165 3 0.5590 0.2138 0.328 0.000 0.512 0.160 0.000 0.000
#> SRR1313166 1 0.3799 0.0495 0.704 0.000 0.020 0.000 0.000 0.276
#> SRR1313164 3 0.5703 0.2365 0.212 0.000 0.520 0.000 0.000 0.268
#> SRR1313167 3 0.3989 0.3310 0.468 0.000 0.528 0.000 0.000 0.004
#> SRR1313168 1 0.5799 -0.1045 0.460 0.000 0.116 0.408 0.016 0.000
#> SRR1313170 3 0.0820 0.7198 0.016 0.012 0.972 0.000 0.000 0.000
#> SRR1313169 1 0.5712 -0.1427 0.456 0.000 0.104 0.424 0.016 0.000
#> SRR1313172 3 0.4394 0.3554 0.004 0.020 0.568 0.000 0.000 0.408
#> SRR1313171 3 0.4463 0.1969 0.004 0.020 0.508 0.000 0.000 0.468
#> SRR1313174 5 0.2060 0.8300 0.000 0.084 0.016 0.000 0.900 0.000
#> SRR1313173 6 0.2678 0.7945 0.004 0.020 0.116 0.000 0.000 0.860
#> SRR1313176 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313175 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313178 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313177 2 0.2631 0.9619 0.000 0.820 0.000 0.000 0.180 0.000
#> SRR1313179 5 0.1984 0.8490 0.000 0.056 0.032 0.000 0.912 0.000
#> SRR1313180 5 0.3967 0.6741 0.000 0.000 0.148 0.000 0.760 0.092
#> SRR1313181 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313183 2 0.2631 0.9619 0.000 0.820 0.000 0.000 0.180 0.000
#> SRR1313182 2 0.3023 0.9235 0.000 0.768 0.000 0.000 0.232 0.000
#> SRR1313184 5 0.0935 0.9011 0.000 0.004 0.032 0.000 0.964 0.000
#> SRR1313185 5 0.1387 0.8519 0.000 0.068 0.000 0.000 0.932 0.000
#> SRR1313188 5 0.0692 0.9063 0.000 0.000 0.020 0.000 0.976 0.004
#> SRR1313187 5 0.0692 0.9063 0.000 0.000 0.020 0.000 0.976 0.004
#> SRR1313186 5 0.1151 0.8897 0.000 0.032 0.012 0.000 0.956 0.000
#> SRR1313189 2 0.2631 0.9619 0.000 0.820 0.000 0.000 0.180 0.000
#> SRR1313190 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313191 5 0.3817 -0.1469 0.000 0.432 0.000 0.000 0.568 0.000
#> SRR1313192 2 0.2793 0.9549 0.000 0.800 0.000 0.000 0.200 0.000
#> SRR1313193 2 0.2854 0.9478 0.000 0.792 0.000 0.000 0.208 0.000
#> SRR1313194 5 0.0632 0.9066 0.000 0.000 0.024 0.000 0.976 0.000
#> SRR1313195 5 0.0713 0.9048 0.000 0.000 0.028 0.000 0.972 0.000
#> SRR1313196 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313197 5 0.0508 0.9063 0.000 0.004 0.012 0.000 0.984 0.000
#> SRR1313198 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313199 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313200 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313201 2 0.2762 0.9580 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313202 5 0.0713 0.9048 0.000 0.000 0.028 0.000 0.972 0.000
#> SRR1313203 3 0.4442 0.4067 0.004 0.020 0.536 0.000 0.000 0.440
#> SRR1313204 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313205 2 0.2762 0.9580 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1313207 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313208 2 0.2664 0.9611 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313206 2 0.2730 0.9606 0.000 0.808 0.000 0.000 0.192 0.000
#> SRR1313210 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313209 5 0.0458 0.8945 0.000 0.016 0.000 0.000 0.984 0.000
#> SRR1313211 2 0.3717 0.6919 0.000 0.616 0.000 0.000 0.384 0.000
#> SRR1313212 2 0.2631 0.9619 0.000 0.820 0.000 0.000 0.180 0.000
#> SRR1313214 5 0.0508 0.8991 0.000 0.012 0.004 0.000 0.984 0.000
#> SRR1313215 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313213 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313216 3 0.3389 0.6918 0.004 0.164 0.800 0.000 0.032 0.000
#> SRR1313217 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313219 5 0.0458 0.9087 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1313220 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313218 2 0.3756 0.6655 0.000 0.600 0.000 0.000 0.400 0.000
#> SRR1313222 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313221 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313223 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313224 2 0.3756 0.6655 0.000 0.600 0.000 0.000 0.400 0.000
#> SRR1313225 5 0.2653 0.7396 0.000 0.144 0.012 0.000 0.844 0.000
#> SRR1313226 3 0.4980 0.4450 0.000 0.004 0.624 0.000 0.280 0.092
#> SRR1313227 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313228 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
#> SRR1313229 2 0.2664 0.9647 0.000 0.816 0.000 0.000 0.184 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "NMF"]
# you can also extract it by
# res = res_list["ATC:NMF"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 18147 rows and 167 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.975 0.946 0.979 0.5006 0.500 0.500
#> 3 3 0.918 0.903 0.959 0.2935 0.812 0.638
#> 4 4 0.777 0.794 0.905 0.1404 0.805 0.515
#> 5 5 0.804 0.774 0.882 0.0479 0.901 0.662
#> 6 6 0.750 0.595 0.779 0.0409 0.935 0.741
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
#> attr(,"optional")
#> [1] 2
There is also optional best \(k\) = 2 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR1313062 1 0.000 0.9729 1.000 0.000
#> SRR1313063 1 0.000 0.9729 1.000 0.000
#> SRR1313064 1 0.000 0.9729 1.000 0.000
#> SRR1313065 1 0.000 0.9729 1.000 0.000
#> SRR1313066 1 0.000 0.9729 1.000 0.000
#> SRR1313067 1 0.000 0.9729 1.000 0.000
#> SRR1313068 1 0.000 0.9729 1.000 0.000
#> SRR1313069 1 0.000 0.9729 1.000 0.000
#> SRR1313070 1 0.000 0.9729 1.000 0.000
#> SRR1313071 1 0.000 0.9729 1.000 0.000
#> SRR1313072 1 0.000 0.9729 1.000 0.000
#> SRR1313073 1 0.000 0.9729 1.000 0.000
#> SRR1313074 1 0.000 0.9729 1.000 0.000
#> SRR1313075 1 0.000 0.9729 1.000 0.000
#> SRR1313076 1 0.000 0.9729 1.000 0.000
#> SRR1313077 1 0.000 0.9729 1.000 0.000
#> SRR1313078 1 0.000 0.9729 1.000 0.000
#> SRR1313079 1 0.000 0.9729 1.000 0.000
#> SRR1313080 1 0.000 0.9729 1.000 0.000
#> SRR1313081 1 0.000 0.9729 1.000 0.000
#> SRR1313082 1 0.000 0.9729 1.000 0.000
#> SRR1313083 1 0.000 0.9729 1.000 0.000
#> SRR1313084 1 0.000 0.9729 1.000 0.000
#> SRR1313085 1 0.000 0.9729 1.000 0.000
#> SRR1313086 1 0.000 0.9729 1.000 0.000
#> SRR1313087 1 0.000 0.9729 1.000 0.000
#> SRR1313088 1 0.000 0.9729 1.000 0.000
#> SRR1313089 1 0.000 0.9729 1.000 0.000
#> SRR1313092 1 0.000 0.9729 1.000 0.000
#> SRR1313090 1 0.000 0.9729 1.000 0.000
#> SRR1313091 2 0.000 0.9844 0.000 1.000
#> SRR1313093 1 0.204 0.9433 0.968 0.032
#> SRR1313095 1 0.000 0.9729 1.000 0.000
#> SRR1313096 1 0.000 0.9729 1.000 0.000
#> SRR1313094 1 0.706 0.7544 0.808 0.192
#> SRR1313097 2 0.644 0.7945 0.164 0.836
#> SRR1313099 2 0.000 0.9844 0.000 1.000
#> SRR1313098 1 0.000 0.9729 1.000 0.000
#> SRR1313101 2 0.000 0.9844 0.000 1.000
#> SRR1313102 2 0.000 0.9844 0.000 1.000
#> SRR1313103 2 0.000 0.9844 0.000 1.000
#> SRR1313100 1 0.000 0.9729 1.000 0.000
#> SRR1313105 2 0.000 0.9844 0.000 1.000
#> SRR1313104 1 0.788 0.6873 0.764 0.236
#> SRR1313107 2 0.000 0.9844 0.000 1.000
#> SRR1313106 2 0.000 0.9844 0.000 1.000
#> SRR1313109 2 0.000 0.9844 0.000 1.000
#> SRR1313108 1 0.000 0.9729 1.000 0.000
#> SRR1313111 2 0.204 0.9531 0.032 0.968
#> SRR1313110 1 0.000 0.9729 1.000 0.000
#> SRR1313112 2 0.775 0.6964 0.228 0.772
#> SRR1313113 2 0.000 0.9844 0.000 1.000
#> SRR1313115 1 0.000 0.9729 1.000 0.000
#> SRR1313114 1 0.000 0.9729 1.000 0.000
#> SRR1313117 1 1.000 0.0588 0.512 0.488
#> SRR1313118 1 0.000 0.9729 1.000 0.000
#> SRR1313116 2 0.000 0.9844 0.000 1.000
#> SRR1313120 2 0.000 0.9844 0.000 1.000
#> SRR1313119 1 0.000 0.9729 1.000 0.000
#> SRR1313122 1 0.966 0.3629 0.608 0.392
#> SRR1313124 1 0.000 0.9729 1.000 0.000
#> SRR1313121 1 0.000 0.9729 1.000 0.000
#> SRR1313125 1 0.000 0.9729 1.000 0.000
#> SRR1313127 1 0.000 0.9729 1.000 0.000
#> SRR1313123 1 0.000 0.9729 1.000 0.000
#> SRR1313128 1 0.000 0.9729 1.000 0.000
#> SRR1313126 1 0.000 0.9729 1.000 0.000
#> SRR1313130 2 0.000 0.9844 0.000 1.000
#> SRR1313132 1 0.000 0.9729 1.000 0.000
#> SRR1313129 2 0.000 0.9844 0.000 1.000
#> SRR1313133 1 0.000 0.9729 1.000 0.000
#> SRR1313131 1 0.000 0.9729 1.000 0.000
#> SRR1313134 1 0.000 0.9729 1.000 0.000
#> SRR1313135 1 0.000 0.9729 1.000 0.000
#> SRR1313136 1 0.000 0.9729 1.000 0.000
#> SRR1313137 1 0.000 0.9729 1.000 0.000
#> SRR1313138 1 0.999 0.0744 0.516 0.484
#> SRR1313140 1 0.000 0.9729 1.000 0.000
#> SRR1313141 1 0.000 0.9729 1.000 0.000
#> SRR1313139 1 0.000 0.9729 1.000 0.000
#> SRR1313143 1 0.000 0.9729 1.000 0.000
#> SRR1313142 1 0.000 0.9729 1.000 0.000
#> SRR1313144 1 0.000 0.9729 1.000 0.000
#> SRR1313145 1 0.000 0.9729 1.000 0.000
#> SRR1313146 1 0.000 0.9729 1.000 0.000
#> SRR1313147 1 0.000 0.9729 1.000 0.000
#> SRR1313150 1 0.000 0.9729 1.000 0.000
#> SRR1313149 1 0.000 0.9729 1.000 0.000
#> SRR1313152 1 0.000 0.9729 1.000 0.000
#> SRR1313151 1 0.000 0.9729 1.000 0.000
#> SRR1313154 1 0.000 0.9729 1.000 0.000
#> SRR1313153 1 0.000 0.9729 1.000 0.000
#> SRR1313156 1 0.963 0.3738 0.612 0.388
#> SRR1313155 1 0.000 0.9729 1.000 0.000
#> SRR1313157 1 0.000 0.9729 1.000 0.000
#> SRR1313158 1 0.000 0.9729 1.000 0.000
#> SRR1313161 1 0.000 0.9729 1.000 0.000
#> SRR1313159 2 0.833 0.6325 0.264 0.736
#> SRR1313160 1 0.000 0.9729 1.000 0.000
#> SRR1313162 1 0.000 0.9729 1.000 0.000
#> SRR1313163 1 0.000 0.9729 1.000 0.000
#> SRR1313165 1 0.000 0.9729 1.000 0.000
#> SRR1313166 1 0.000 0.9729 1.000 0.000
#> SRR1313164 1 0.552 0.8394 0.872 0.128
#> SRR1313167 1 0.000 0.9729 1.000 0.000
#> SRR1313168 1 0.000 0.9729 1.000 0.000
#> SRR1313170 2 0.992 0.1625 0.448 0.552
#> SRR1313169 1 0.000 0.9729 1.000 0.000
#> SRR1313172 2 0.000 0.9844 0.000 1.000
#> SRR1313171 2 0.000 0.9844 0.000 1.000
#> SRR1313174 2 0.000 0.9844 0.000 1.000
#> SRR1313173 1 0.000 0.9729 1.000 0.000
#> SRR1313176 2 0.000 0.9844 0.000 1.000
#> SRR1313175 2 0.000 0.9844 0.000 1.000
#> SRR1313178 2 0.000 0.9844 0.000 1.000
#> SRR1313177 2 0.000 0.9844 0.000 1.000
#> SRR1313179 2 0.000 0.9844 0.000 1.000
#> SRR1313180 2 0.000 0.9844 0.000 1.000
#> SRR1313181 2 0.000 0.9844 0.000 1.000
#> SRR1313183 2 0.000 0.9844 0.000 1.000
#> SRR1313182 2 0.000 0.9844 0.000 1.000
#> SRR1313184 2 0.000 0.9844 0.000 1.000
#> SRR1313185 2 0.000 0.9844 0.000 1.000
#> SRR1313188 2 0.000 0.9844 0.000 1.000
#> SRR1313187 2 0.000 0.9844 0.000 1.000
#> SRR1313186 2 0.000 0.9844 0.000 1.000
#> SRR1313189 2 0.000 0.9844 0.000 1.000
#> SRR1313190 2 0.000 0.9844 0.000 1.000
#> SRR1313191 2 0.000 0.9844 0.000 1.000
#> SRR1313192 2 0.000 0.9844 0.000 1.000
#> SRR1313193 2 0.000 0.9844 0.000 1.000
#> SRR1313194 2 0.000 0.9844 0.000 1.000
#> SRR1313195 2 0.000 0.9844 0.000 1.000
#> SRR1313196 2 0.000 0.9844 0.000 1.000
#> SRR1313197 2 0.000 0.9844 0.000 1.000
#> SRR1313198 2 0.000 0.9844 0.000 1.000
#> SRR1313199 2 0.000 0.9844 0.000 1.000
#> SRR1313200 2 0.000 0.9844 0.000 1.000
#> SRR1313201 2 0.000 0.9844 0.000 1.000
#> SRR1313202 2 0.000 0.9844 0.000 1.000
#> SRR1313203 2 0.000 0.9844 0.000 1.000
#> SRR1313204 2 0.000 0.9844 0.000 1.000
#> SRR1313205 2 0.000 0.9844 0.000 1.000
#> SRR1313207 2 0.000 0.9844 0.000 1.000
#> SRR1313208 2 0.000 0.9844 0.000 1.000
#> SRR1313206 2 0.000 0.9844 0.000 1.000
#> SRR1313210 2 0.000 0.9844 0.000 1.000
#> SRR1313209 2 0.000 0.9844 0.000 1.000
#> SRR1313211 2 0.000 0.9844 0.000 1.000
#> SRR1313212 2 0.000 0.9844 0.000 1.000
#> SRR1313214 2 0.000 0.9844 0.000 1.000
#> SRR1313215 2 0.000 0.9844 0.000 1.000
#> SRR1313213 2 0.000 0.9844 0.000 1.000
#> SRR1313216 2 0.000 0.9844 0.000 1.000
#> SRR1313217 2 0.000 0.9844 0.000 1.000
#> SRR1313219 2 0.000 0.9844 0.000 1.000
#> SRR1313220 2 0.000 0.9844 0.000 1.000
#> SRR1313218 2 0.000 0.9844 0.000 1.000
#> SRR1313222 2 0.000 0.9844 0.000 1.000
#> SRR1313221 2 0.000 0.9844 0.000 1.000
#> SRR1313223 2 0.000 0.9844 0.000 1.000
#> SRR1313224 2 0.000 0.9844 0.000 1.000
#> SRR1313225 2 0.000 0.9844 0.000 1.000
#> SRR1313226 2 0.000 0.9844 0.000 1.000
#> SRR1313227 2 0.000 0.9844 0.000 1.000
#> SRR1313228 2 0.000 0.9844 0.000 1.000
#> SRR1313229 2 0.000 0.9844 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1313062 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313063 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313064 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313065 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313066 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313067 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313068 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313069 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313070 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313071 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313072 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313073 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313074 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313075 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313076 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313077 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313078 3 0.6168 0.317 0.412 0.000 0.588
#> SRR1313079 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313080 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313081 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313082 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313083 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313084 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313085 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313086 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313087 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313088 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313089 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313092 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313090 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313091 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313093 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313095 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313096 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313094 3 0.1529 0.894 0.000 0.040 0.960
#> SRR1313097 2 0.6204 0.252 0.000 0.576 0.424
#> SRR1313099 3 0.6008 0.399 0.000 0.372 0.628
#> SRR1313098 3 0.0424 0.907 0.008 0.000 0.992
#> SRR1313101 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313102 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313103 3 0.1964 0.883 0.000 0.056 0.944
#> SRR1313100 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313105 2 0.5785 0.492 0.000 0.668 0.332
#> SRR1313104 3 0.1163 0.900 0.000 0.028 0.972
#> SRR1313107 3 0.1964 0.883 0.000 0.056 0.944
#> SRR1313106 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313109 2 0.0237 0.970 0.000 0.996 0.004
#> SRR1313108 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313111 3 0.5529 0.570 0.000 0.296 0.704
#> SRR1313110 1 0.0424 0.954 0.992 0.008 0.000
#> SRR1313112 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313113 2 0.4178 0.776 0.000 0.828 0.172
#> SRR1313115 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313114 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313117 2 0.6126 0.329 0.400 0.600 0.000
#> SRR1313118 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313116 2 0.0237 0.970 0.000 0.996 0.004
#> SRR1313120 3 0.1643 0.892 0.000 0.044 0.956
#> SRR1313119 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313122 1 0.5948 0.429 0.640 0.360 0.000
#> SRR1313124 1 0.5706 0.477 0.680 0.000 0.320
#> SRR1313121 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313125 1 0.3771 0.833 0.876 0.012 0.112
#> SRR1313127 3 0.0747 0.902 0.016 0.000 0.984
#> SRR1313123 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313128 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313126 1 0.1031 0.945 0.976 0.000 0.024
#> SRR1313130 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313132 3 0.0747 0.905 0.000 0.016 0.984
#> SRR1313129 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313133 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313131 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313134 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313135 1 0.1289 0.938 0.968 0.000 0.032
#> SRR1313136 3 0.4842 0.696 0.224 0.000 0.776
#> SRR1313137 1 0.1031 0.945 0.976 0.000 0.024
#> SRR1313138 1 0.6008 0.411 0.628 0.372 0.000
#> SRR1313140 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313141 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313139 1 0.0237 0.958 0.996 0.000 0.004
#> SRR1313143 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313142 3 0.5431 0.603 0.284 0.000 0.716
#> SRR1313144 1 0.0747 0.951 0.984 0.000 0.016
#> SRR1313145 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313146 3 0.5098 0.669 0.248 0.000 0.752
#> SRR1313147 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313150 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313149 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313152 1 0.0892 0.948 0.980 0.000 0.020
#> SRR1313151 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313154 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313153 1 0.5859 0.458 0.656 0.000 0.344
#> SRR1313156 3 0.1643 0.892 0.000 0.044 0.956
#> SRR1313155 1 0.5058 0.663 0.756 0.000 0.244
#> SRR1313157 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313158 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313161 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313159 2 0.5465 0.584 0.000 0.712 0.288
#> SRR1313160 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313162 3 0.5859 0.494 0.344 0.000 0.656
#> SRR1313163 3 0.6629 0.456 0.360 0.016 0.624
#> SRR1313165 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313166 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313164 3 0.1163 0.900 0.000 0.028 0.972
#> SRR1313167 1 0.0000 0.959 1.000 0.000 0.000
#> SRR1313168 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313170 2 0.2261 0.906 0.000 0.932 0.068
#> SRR1313169 1 0.0424 0.957 0.992 0.000 0.008
#> SRR1313172 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313171 3 0.3816 0.795 0.000 0.148 0.852
#> SRR1313174 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313173 3 0.0000 0.910 0.000 0.000 1.000
#> SRR1313176 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313175 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313178 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313177 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313179 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313180 2 0.1163 0.945 0.028 0.972 0.000
#> SRR1313181 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313183 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313182 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313184 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313185 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313188 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313187 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313186 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313189 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313190 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313191 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313192 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313193 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313194 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313195 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313196 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313197 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313198 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313199 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313200 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313201 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313202 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313203 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313204 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313205 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313207 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313208 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313206 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313210 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313209 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313211 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313212 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313214 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313215 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313213 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313216 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313217 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313219 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313220 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313218 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313222 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313221 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313223 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313224 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313225 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313226 2 0.1289 0.941 0.032 0.968 0.000
#> SRR1313227 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313228 2 0.0000 0.973 0.000 1.000 0.000
#> SRR1313229 2 0.0000 0.973 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1313062 4 0.0336 0.8576 0.000 0.000 0.008 0.992
#> SRR1313063 4 0.4406 0.6712 0.000 0.000 0.300 0.700
#> SRR1313064 4 0.2868 0.8366 0.000 0.000 0.136 0.864
#> SRR1313065 3 0.4989 -0.1542 0.000 0.000 0.528 0.472
#> SRR1313066 3 0.5000 -0.2412 0.000 0.000 0.504 0.496
#> SRR1313067 3 0.0707 0.7790 0.000 0.000 0.980 0.020
#> SRR1313068 3 0.3528 0.6020 0.000 0.000 0.808 0.192
#> SRR1313069 4 0.0188 0.8574 0.000 0.000 0.004 0.996
#> SRR1313070 4 0.3024 0.8308 0.000 0.000 0.148 0.852
#> SRR1313071 4 0.2921 0.8348 0.000 0.000 0.140 0.860
#> SRR1313072 4 0.3486 0.8037 0.000 0.000 0.188 0.812
#> SRR1313073 4 0.1867 0.8546 0.000 0.000 0.072 0.928
#> SRR1313074 4 0.1211 0.8588 0.000 0.000 0.040 0.960
#> SRR1313075 4 0.2530 0.8452 0.000 0.000 0.112 0.888
#> SRR1313076 4 0.0188 0.8574 0.000 0.000 0.004 0.996
#> SRR1313077 4 0.0188 0.8574 0.000 0.000 0.004 0.996
#> SRR1313078 4 0.1637 0.8308 0.060 0.000 0.000 0.940
#> SRR1313079 4 0.3610 0.7936 0.000 0.000 0.200 0.800
#> SRR1313080 3 0.2530 0.7092 0.000 0.000 0.888 0.112
#> SRR1313081 4 0.0336 0.8576 0.000 0.000 0.008 0.992
#> SRR1313082 4 0.3074 0.8287 0.000 0.000 0.152 0.848
#> SRR1313083 4 0.0000 0.8568 0.000 0.000 0.000 1.000
#> SRR1313084 4 0.4948 0.3915 0.000 0.000 0.440 0.560
#> SRR1313085 4 0.2814 0.8383 0.000 0.000 0.132 0.868
#> SRR1313086 4 0.0000 0.8568 0.000 0.000 0.000 1.000
#> SRR1313087 4 0.3801 0.7756 0.000 0.000 0.220 0.780
#> SRR1313088 4 0.0000 0.8568 0.000 0.000 0.000 1.000
#> SRR1313089 3 0.4948 -0.0521 0.000 0.000 0.560 0.440
#> SRR1313092 1 0.3052 0.7704 0.860 0.000 0.136 0.004
#> SRR1313090 3 0.0336 0.7817 0.000 0.000 0.992 0.008
#> SRR1313091 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313093 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313095 3 0.2048 0.7549 0.064 0.000 0.928 0.008
#> SRR1313096 1 0.2760 0.7907 0.872 0.000 0.000 0.128
#> SRR1313094 1 0.3356 0.7336 0.824 0.000 0.176 0.000
#> SRR1313097 3 0.5163 -0.0291 0.480 0.004 0.516 0.000
#> SRR1313099 1 0.1576 0.8336 0.948 0.048 0.004 0.000
#> SRR1313098 1 0.0376 0.8567 0.992 0.000 0.004 0.004
#> SRR1313101 3 0.0376 0.7815 0.000 0.004 0.992 0.004
#> SRR1313102 3 0.5055 0.2953 0.368 0.008 0.624 0.000
#> SRR1313103 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313100 3 0.0921 0.7759 0.000 0.000 0.972 0.028
#> SRR1313105 1 0.3831 0.6973 0.792 0.004 0.204 0.000
#> SRR1313104 1 0.4356 0.5661 0.708 0.000 0.292 0.000
#> SRR1313107 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313106 3 0.0336 0.7798 0.000 0.008 0.992 0.000
#> SRR1313109 1 0.5097 0.2641 0.568 0.428 0.004 0.000
#> SRR1313108 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313111 1 0.1716 0.8286 0.936 0.000 0.064 0.000
#> SRR1313110 3 0.1576 0.7676 0.004 0.000 0.948 0.048
#> SRR1313112 3 0.2988 0.7093 0.012 0.112 0.876 0.000
#> SRR1313113 1 0.5039 0.3247 0.592 0.004 0.404 0.000
#> SRR1313115 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313114 3 0.3351 0.6744 0.148 0.000 0.844 0.008
#> SRR1313117 3 0.0188 0.7812 0.000 0.000 0.996 0.004
#> SRR1313118 3 0.0336 0.7817 0.000 0.000 0.992 0.008
#> SRR1313116 1 0.5080 0.2902 0.576 0.004 0.420 0.000
#> SRR1313120 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313119 3 0.0336 0.7817 0.000 0.000 0.992 0.008
#> SRR1313122 3 0.0188 0.7812 0.000 0.000 0.996 0.004
#> SRR1313124 3 0.2053 0.7409 0.072 0.000 0.924 0.004
#> SRR1313121 3 0.0336 0.7817 0.000 0.000 0.992 0.008
#> SRR1313125 3 0.5151 0.0284 0.464 0.000 0.532 0.004
#> SRR1313127 1 0.0657 0.8556 0.984 0.000 0.004 0.012
#> SRR1313123 1 0.0779 0.8545 0.980 0.000 0.004 0.016
#> SRR1313128 1 0.3688 0.7222 0.792 0.000 0.000 0.208
#> SRR1313126 4 0.4793 0.6873 0.040 0.000 0.204 0.756
#> SRR1313130 3 0.4761 0.3922 0.000 0.372 0.628 0.000
#> SRR1313132 1 0.0000 0.8570 1.000 0.000 0.000 0.000
#> SRR1313129 1 0.4152 0.7361 0.808 0.032 0.160 0.000
#> SRR1313133 1 0.0000 0.8570 1.000 0.000 0.000 0.000
#> SRR1313131 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313134 1 0.0000 0.8570 1.000 0.000 0.000 0.000
#> SRR1313135 4 0.0188 0.8555 0.004 0.000 0.000 0.996
#> SRR1313136 4 0.2530 0.8013 0.112 0.000 0.000 0.888
#> SRR1313137 4 0.0188 0.8579 0.000 0.000 0.004 0.996
#> SRR1313138 4 0.7133 0.4330 0.000 0.172 0.280 0.548
#> SRR1313140 4 0.0000 0.8568 0.000 0.000 0.000 1.000
#> SRR1313141 1 0.3074 0.7726 0.848 0.000 0.000 0.152
#> SRR1313139 4 0.2408 0.8471 0.000 0.000 0.104 0.896
#> SRR1313143 1 0.3688 0.7210 0.792 0.000 0.000 0.208
#> SRR1313142 4 0.1792 0.8241 0.068 0.000 0.000 0.932
#> SRR1313144 4 0.0188 0.8579 0.000 0.000 0.004 0.996
#> SRR1313145 4 0.4898 0.2179 0.416 0.000 0.000 0.584
#> SRR1313146 4 0.2281 0.8037 0.096 0.000 0.000 0.904
#> SRR1313147 4 0.1022 0.8593 0.000 0.000 0.032 0.968
#> SRR1313150 4 0.3400 0.8088 0.000 0.000 0.180 0.820
#> SRR1313149 1 0.3486 0.7409 0.812 0.000 0.000 0.188
#> SRR1313152 4 0.0921 0.8592 0.000 0.000 0.028 0.972
#> SRR1313151 4 0.3400 0.7225 0.180 0.000 0.000 0.820
#> SRR1313154 4 0.3726 0.6786 0.212 0.000 0.000 0.788
#> SRR1313153 4 0.1022 0.8448 0.032 0.000 0.000 0.968
#> SRR1313156 1 0.6646 0.4984 0.624 0.172 0.000 0.204
#> SRR1313155 4 0.0469 0.8532 0.012 0.000 0.000 0.988
#> SRR1313157 4 0.3024 0.8300 0.000 0.000 0.148 0.852
#> SRR1313158 1 0.1716 0.8250 0.936 0.000 0.000 0.064
#> SRR1313161 4 0.3311 0.8146 0.000 0.000 0.172 0.828
#> SRR1313159 2 0.3494 0.7738 0.172 0.824 0.000 0.004
#> SRR1313160 4 0.3688 0.7850 0.000 0.000 0.208 0.792
#> SRR1313162 4 0.3873 0.6536 0.228 0.000 0.000 0.772
#> SRR1313163 4 0.4072 0.7009 0.252 0.000 0.000 0.748
#> SRR1313165 4 0.3726 0.7812 0.000 0.000 0.212 0.788
#> SRR1313166 1 0.2704 0.7952 0.876 0.000 0.000 0.124
#> SRR1313164 1 0.0000 0.8570 1.000 0.000 0.000 0.000
#> SRR1313167 4 0.3688 0.7855 0.000 0.000 0.208 0.792
#> SRR1313168 4 0.2814 0.8376 0.000 0.000 0.132 0.868
#> SRR1313170 3 0.1716 0.7528 0.064 0.000 0.936 0.000
#> SRR1313169 4 0.0469 0.8589 0.000 0.000 0.012 0.988
#> SRR1313172 2 0.0188 0.9775 0.000 0.996 0.004 0.000
#> SRR1313171 1 0.1398 0.8391 0.956 0.040 0.004 0.000
#> SRR1313174 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313173 1 0.0188 0.8574 0.996 0.000 0.004 0.000
#> SRR1313176 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313175 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313178 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313179 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313180 3 0.0336 0.7800 0.000 0.008 0.992 0.000
#> SRR1313181 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313185 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313188 3 0.3074 0.6742 0.000 0.152 0.848 0.000
#> SRR1313187 3 0.4817 0.3540 0.000 0.388 0.612 0.000
#> SRR1313186 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313189 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313194 2 0.0592 0.9663 0.000 0.984 0.016 0.000
#> SRR1313195 2 0.1211 0.9415 0.000 0.960 0.040 0.000
#> SRR1313196 3 0.4697 0.4242 0.000 0.356 0.644 0.000
#> SRR1313197 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313198 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313199 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313200 2 0.4679 0.4194 0.000 0.648 0.352 0.000
#> SRR1313201 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313202 2 0.0592 0.9664 0.000 0.984 0.016 0.000
#> SRR1313203 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313204 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313210 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313209 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313211 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313215 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313213 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313216 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313217 2 0.4406 0.5425 0.000 0.700 0.300 0.000
#> SRR1313219 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313220 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313226 3 0.0188 0.7811 0.000 0.000 0.996 0.004
#> SRR1313227 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9813 0.000 1.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9813 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1313062 1 0.3318 0.7296 0.800 0.000 0.008 0.192 0.000
#> SRR1313063 4 0.3132 0.6843 0.172 0.000 0.008 0.820 0.000
#> SRR1313064 1 0.4101 0.4177 0.628 0.000 0.000 0.372 0.000
#> SRR1313065 4 0.2230 0.7272 0.116 0.000 0.000 0.884 0.000
#> SRR1313066 4 0.1768 0.7473 0.072 0.000 0.004 0.924 0.000
#> SRR1313067 4 0.2377 0.6850 0.000 0.000 0.128 0.872 0.000
#> SRR1313068 4 0.1661 0.7431 0.036 0.000 0.024 0.940 0.000
#> SRR1313069 1 0.2471 0.7639 0.864 0.000 0.000 0.136 0.000
#> SRR1313070 1 0.3177 0.7116 0.792 0.000 0.000 0.208 0.000
#> SRR1313071 1 0.3109 0.7191 0.800 0.000 0.000 0.200 0.000
#> SRR1313072 4 0.4304 -0.0496 0.484 0.000 0.000 0.516 0.000
#> SRR1313073 1 0.2605 0.7564 0.852 0.000 0.000 0.148 0.000
#> SRR1313074 1 0.2329 0.7713 0.876 0.000 0.000 0.124 0.000
#> SRR1313075 1 0.2516 0.7665 0.860 0.000 0.000 0.140 0.000
#> SRR1313076 1 0.4883 0.4031 0.600 0.000 0.004 0.372 0.024
#> SRR1313077 1 0.5095 0.3920 0.592 0.000 0.004 0.368 0.036
#> SRR1313078 5 0.5409 0.4280 0.304 0.000 0.000 0.084 0.612
#> SRR1313079 4 0.3752 0.5079 0.292 0.000 0.000 0.708 0.000
#> SRR1313080 4 0.1774 0.7324 0.016 0.000 0.052 0.932 0.000
#> SRR1313081 4 0.5875 0.1558 0.396 0.000 0.004 0.512 0.088
#> SRR1313082 1 0.2020 0.7835 0.900 0.000 0.000 0.100 0.000
#> SRR1313083 1 0.1952 0.7934 0.912 0.000 0.000 0.084 0.004
#> SRR1313084 4 0.2377 0.7189 0.128 0.000 0.000 0.872 0.000
#> SRR1313085 1 0.2690 0.7581 0.844 0.000 0.000 0.156 0.000
#> SRR1313086 1 0.1851 0.7856 0.912 0.000 0.000 0.088 0.000
#> SRR1313087 4 0.4060 0.3645 0.360 0.000 0.000 0.640 0.000
#> SRR1313088 1 0.1965 0.7837 0.904 0.000 0.000 0.096 0.000
#> SRR1313089 4 0.1571 0.7490 0.060 0.000 0.004 0.936 0.000
#> SRR1313092 3 0.2450 0.8089 0.048 0.000 0.900 0.000 0.052
#> SRR1313090 3 0.2732 0.7875 0.000 0.000 0.840 0.160 0.000
#> SRR1313091 2 0.0162 0.9694 0.000 0.996 0.000 0.004 0.000
#> SRR1313093 5 0.1043 0.8536 0.000 0.000 0.040 0.000 0.960
#> SRR1313095 3 0.3132 0.7783 0.000 0.000 0.820 0.172 0.008
#> SRR1313096 5 0.0609 0.8524 0.000 0.000 0.000 0.020 0.980
#> SRR1313094 3 0.3895 0.6211 0.004 0.000 0.728 0.004 0.264
#> SRR1313097 3 0.1907 0.8216 0.000 0.000 0.928 0.044 0.028
#> SRR1313099 5 0.4328 0.7374 0.000 0.108 0.108 0.004 0.780
#> SRR1313098 3 0.5155 0.6954 0.140 0.000 0.692 0.000 0.168
#> SRR1313101 3 0.1608 0.8201 0.000 0.000 0.928 0.072 0.000
#> SRR1313102 3 0.0609 0.8225 0.000 0.000 0.980 0.020 0.000
#> SRR1313103 5 0.3266 0.7456 0.000 0.000 0.200 0.004 0.796
#> SRR1313100 4 0.3132 0.6543 0.008 0.000 0.172 0.820 0.000
#> SRR1313105 3 0.1740 0.8148 0.000 0.000 0.932 0.012 0.056
#> SRR1313104 3 0.1082 0.8222 0.000 0.000 0.964 0.008 0.028
#> SRR1313107 5 0.3167 0.7771 0.000 0.004 0.172 0.004 0.820
#> SRR1313106 3 0.3074 0.7687 0.000 0.000 0.804 0.196 0.000
#> SRR1313109 5 0.6142 0.1897 0.000 0.428 0.112 0.004 0.456
#> SRR1313108 5 0.0162 0.8596 0.000 0.000 0.004 0.000 0.996
#> SRR1313111 3 0.4047 0.4904 0.000 0.000 0.676 0.004 0.320
#> SRR1313110 3 0.2516 0.7700 0.140 0.000 0.860 0.000 0.000
#> SRR1313112 3 0.2863 0.7949 0.000 0.064 0.876 0.060 0.000
#> SRR1313113 3 0.2012 0.8163 0.000 0.000 0.920 0.020 0.060
#> SRR1313115 5 0.0162 0.8596 0.000 0.000 0.004 0.000 0.996
#> SRR1313114 3 0.2411 0.7893 0.108 0.000 0.884 0.000 0.008
#> SRR1313117 3 0.2605 0.7927 0.000 0.000 0.852 0.148 0.000
#> SRR1313118 3 0.2144 0.8142 0.068 0.000 0.912 0.020 0.000
#> SRR1313116 3 0.2291 0.8157 0.000 0.000 0.908 0.036 0.056
#> SRR1313120 5 0.1341 0.8478 0.000 0.000 0.056 0.000 0.944
#> SRR1313119 3 0.1831 0.8192 0.004 0.000 0.920 0.076 0.000
#> SRR1313122 3 0.3336 0.7352 0.000 0.000 0.772 0.228 0.000
#> SRR1313124 3 0.1671 0.8196 0.000 0.000 0.924 0.076 0.000
#> SRR1313121 3 0.3039 0.7691 0.000 0.000 0.808 0.192 0.000
#> SRR1313125 3 0.1830 0.8136 0.052 0.000 0.932 0.004 0.012
#> SRR1313127 3 0.4925 0.5098 0.324 0.000 0.632 0.000 0.044
#> SRR1313123 3 0.3752 0.7472 0.148 0.000 0.804 0.000 0.048
#> SRR1313128 5 0.0771 0.8513 0.004 0.000 0.000 0.020 0.976
#> SRR1313126 1 0.5185 0.2833 0.568 0.000 0.384 0.000 0.048
#> SRR1313130 3 0.6183 0.4161 0.000 0.284 0.584 0.112 0.020
#> SRR1313132 5 0.0794 0.8567 0.000 0.000 0.028 0.000 0.972
#> SRR1313129 3 0.2430 0.8081 0.020 0.012 0.912 0.004 0.052
#> SRR1313133 5 0.0162 0.8596 0.000 0.000 0.004 0.000 0.996
#> SRR1313131 5 0.0162 0.8596 0.000 0.000 0.004 0.000 0.996
#> SRR1313134 5 0.0162 0.8596 0.000 0.000 0.004 0.000 0.996
#> SRR1313135 1 0.1270 0.7987 0.948 0.000 0.000 0.052 0.000
#> SRR1313136 1 0.1872 0.7859 0.928 0.000 0.020 0.000 0.052
#> SRR1313137 1 0.0963 0.7982 0.964 0.000 0.036 0.000 0.000
#> SRR1313138 3 0.4524 0.4809 0.336 0.000 0.644 0.020 0.000
#> SRR1313140 1 0.1041 0.8045 0.964 0.000 0.004 0.032 0.000
#> SRR1313141 5 0.0771 0.8509 0.004 0.000 0.000 0.020 0.976
#> SRR1313139 1 0.0451 0.8042 0.988 0.000 0.008 0.004 0.000
#> SRR1313143 5 0.1582 0.8334 0.028 0.000 0.000 0.028 0.944
#> SRR1313142 1 0.1626 0.7922 0.940 0.000 0.016 0.000 0.044
#> SRR1313144 1 0.0671 0.8052 0.980 0.000 0.004 0.016 0.000
#> SRR1313145 5 0.4383 0.2291 0.424 0.000 0.000 0.004 0.572
#> SRR1313146 1 0.1560 0.7954 0.948 0.000 0.004 0.028 0.020
#> SRR1313147 1 0.0693 0.8047 0.980 0.000 0.008 0.012 0.000
#> SRR1313150 1 0.0992 0.8039 0.968 0.000 0.008 0.024 0.000
#> SRR1313149 5 0.1399 0.8376 0.020 0.000 0.000 0.028 0.952
#> SRR1313152 1 0.1018 0.8024 0.968 0.000 0.016 0.016 0.000
#> SRR1313151 1 0.2305 0.7804 0.916 0.000 0.012 0.028 0.044
#> SRR1313154 5 0.3596 0.6680 0.212 0.000 0.000 0.012 0.776
#> SRR1313153 1 0.0798 0.8041 0.976 0.000 0.000 0.016 0.008
#> SRR1313156 1 0.6234 0.4888 0.660 0.172 0.104 0.004 0.060
#> SRR1313155 1 0.1116 0.8010 0.964 0.000 0.004 0.028 0.004
#> SRR1313157 1 0.1485 0.7990 0.948 0.000 0.032 0.020 0.000
#> SRR1313158 1 0.5812 0.2137 0.528 0.000 0.100 0.000 0.372
#> SRR1313161 1 0.3724 0.6508 0.776 0.000 0.204 0.020 0.000
#> SRR1313159 2 0.2929 0.7969 0.008 0.840 0.000 0.000 0.152
#> SRR1313160 1 0.4132 0.5823 0.720 0.000 0.260 0.020 0.000
#> SRR1313162 1 0.1911 0.7924 0.932 0.000 0.004 0.028 0.036
#> SRR1313163 1 0.4946 0.4744 0.648 0.000 0.300 0.000 0.052
#> SRR1313165 1 0.4555 0.4334 0.636 0.000 0.344 0.020 0.000
#> SRR1313166 5 0.0451 0.8588 0.008 0.000 0.004 0.000 0.988
#> SRR1313164 5 0.2377 0.8119 0.000 0.000 0.128 0.000 0.872
#> SRR1313167 1 0.4824 0.0498 0.512 0.000 0.468 0.020 0.000
#> SRR1313168 1 0.1399 0.8002 0.952 0.000 0.028 0.020 0.000
#> SRR1313170 3 0.4581 0.7636 0.000 0.000 0.732 0.196 0.072
#> SRR1313169 1 0.1251 0.7983 0.956 0.000 0.036 0.008 0.000
#> SRR1313172 2 0.2741 0.8299 0.000 0.860 0.132 0.004 0.004
#> SRR1313171 5 0.3594 0.7737 0.000 0.020 0.172 0.004 0.804
#> SRR1313174 2 0.0290 0.9676 0.000 0.992 0.000 0.008 0.000
#> SRR1313173 5 0.0609 0.8583 0.000 0.000 0.020 0.000 0.980
#> SRR1313176 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313175 2 0.0290 0.9677 0.000 0.992 0.000 0.008 0.000
#> SRR1313178 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313179 2 0.0290 0.9679 0.000 0.992 0.000 0.008 0.000
#> SRR1313180 4 0.2516 0.6670 0.000 0.000 0.140 0.860 0.000
#> SRR1313181 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313182 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313184 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313185 2 0.0162 0.9698 0.000 0.996 0.000 0.004 0.000
#> SRR1313188 4 0.2825 0.6698 0.000 0.016 0.124 0.860 0.000
#> SRR1313187 4 0.5948 0.1516 0.000 0.408 0.108 0.484 0.000
#> SRR1313186 2 0.0162 0.9698 0.000 0.996 0.000 0.004 0.000
#> SRR1313189 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313191 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313192 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313193 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313194 2 0.1331 0.9311 0.000 0.952 0.040 0.008 0.000
#> SRR1313195 2 0.4464 0.2441 0.000 0.584 0.408 0.008 0.000
#> SRR1313196 3 0.4101 0.7504 0.000 0.048 0.768 0.184 0.000
#> SRR1313197 2 0.0162 0.9698 0.000 0.996 0.000 0.004 0.000
#> SRR1313198 2 0.0404 0.9654 0.000 0.988 0.000 0.012 0.000
#> SRR1313199 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313200 2 0.4238 0.6912 0.000 0.756 0.052 0.192 0.000
#> SRR1313201 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313202 2 0.0671 0.9594 0.000 0.980 0.004 0.016 0.000
#> SRR1313203 2 0.0162 0.9692 0.000 0.996 0.000 0.004 0.000
#> SRR1313204 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313210 2 0.0290 0.9677 0.000 0.992 0.000 0.008 0.000
#> SRR1313209 2 0.0162 0.9698 0.000 0.996 0.000 0.004 0.000
#> SRR1313211 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313212 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313214 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313215 2 0.0290 0.9677 0.000 0.992 0.000 0.008 0.000
#> SRR1313213 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313216 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313217 2 0.4003 0.5957 0.000 0.704 0.008 0.288 0.000
#> SRR1313219 2 0.0510 0.9627 0.000 0.984 0.000 0.016 0.000
#> SRR1313220 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313218 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313222 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313225 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313226 4 0.2732 0.6481 0.000 0.000 0.160 0.840 0.000
#> SRR1313227 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.9715 0.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1313062 4 0.6816 0.041768 0.312 0.000 0.040 0.344 0.304 0.000
#> SRR1313063 4 0.4225 0.495532 0.060 0.000 0.072 0.784 0.084 0.000
#> SRR1313064 4 0.3998 0.496177 0.248 0.000 0.000 0.712 0.040 0.000
#> SRR1313065 4 0.2685 0.528336 0.052 0.000 0.024 0.884 0.040 0.000
#> SRR1313066 4 0.2006 0.489597 0.000 0.000 0.004 0.892 0.104 0.000
#> SRR1313067 3 0.4783 0.317457 0.000 0.000 0.616 0.308 0.076 0.000
#> SRR1313068 4 0.3819 0.439958 0.004 0.000 0.176 0.768 0.052 0.000
#> SRR1313069 1 0.5556 -0.098440 0.452 0.000 0.000 0.412 0.136 0.000
#> SRR1313070 4 0.4029 0.488939 0.292 0.000 0.000 0.680 0.028 0.000
#> SRR1313071 4 0.4167 0.503425 0.236 0.000 0.000 0.708 0.056 0.000
#> SRR1313072 4 0.3283 0.537511 0.160 0.000 0.000 0.804 0.036 0.000
#> SRR1313073 4 0.5682 0.205568 0.380 0.000 0.000 0.460 0.160 0.000
#> SRR1313074 4 0.5190 0.133780 0.448 0.000 0.000 0.464 0.088 0.000
#> SRR1313075 4 0.4475 0.307517 0.412 0.000 0.000 0.556 0.032 0.000
#> SRR1313076 4 0.6723 0.039674 0.312 0.000 0.032 0.336 0.320 0.000
#> SRR1313077 4 0.6139 0.230022 0.276 0.000 0.008 0.460 0.256 0.000
#> SRR1313078 6 0.6704 0.106792 0.140 0.000 0.000 0.076 0.352 0.432
#> SRR1313079 4 0.3172 0.534519 0.128 0.000 0.000 0.824 0.048 0.000
#> SRR1313080 4 0.3954 0.419399 0.000 0.000 0.204 0.740 0.056 0.000
#> SRR1313081 5 0.7500 -0.459921 0.244 0.000 0.080 0.320 0.340 0.016
#> SRR1313082 1 0.5601 0.323605 0.544 0.000 0.000 0.208 0.248 0.000
#> SRR1313083 1 0.5227 0.431487 0.564 0.000 0.004 0.080 0.348 0.004
#> SRR1313084 4 0.2030 0.518619 0.028 0.000 0.000 0.908 0.064 0.000
#> SRR1313085 4 0.4548 0.462919 0.312 0.000 0.000 0.632 0.056 0.000
#> SRR1313086 1 0.5495 0.363174 0.548 0.000 0.000 0.164 0.288 0.000
#> SRR1313087 4 0.3522 0.527812 0.172 0.000 0.000 0.784 0.044 0.000
#> SRR1313088 1 0.5708 0.228257 0.520 0.000 0.000 0.264 0.216 0.000
#> SRR1313089 4 0.1542 0.510305 0.008 0.000 0.004 0.936 0.052 0.000
#> SRR1313092 3 0.5350 0.573466 0.260 0.000 0.624 0.000 0.088 0.028
#> SRR1313090 3 0.1515 0.632802 0.020 0.000 0.944 0.008 0.028 0.000
#> SRR1313091 2 0.1332 0.866316 0.000 0.952 0.008 0.000 0.012 0.028
#> SRR1313093 6 0.0806 0.813369 0.000 0.000 0.020 0.000 0.008 0.972
#> SRR1313095 3 0.4774 0.587346 0.100 0.000 0.740 0.092 0.068 0.000
#> SRR1313096 6 0.1387 0.798901 0.000 0.000 0.000 0.000 0.068 0.932
#> SRR1313094 6 0.5905 0.000757 0.032 0.000 0.416 0.000 0.096 0.456
#> SRR1313097 3 0.2831 0.610197 0.000 0.000 0.840 0.000 0.136 0.024
#> SRR1313099 6 0.3554 0.749372 0.000 0.040 0.028 0.000 0.112 0.820
#> SRR1313098 3 0.6864 0.412647 0.324 0.000 0.444 0.004 0.076 0.152
#> SRR1313101 3 0.2636 0.652737 0.120 0.000 0.860 0.004 0.016 0.000
#> SRR1313102 3 0.3283 0.622763 0.036 0.000 0.804 0.000 0.160 0.000
#> SRR1313103 6 0.2912 0.762051 0.000 0.000 0.040 0.000 0.116 0.844
#> SRR1313100 3 0.4941 0.252970 0.004 0.000 0.572 0.360 0.064 0.000
#> SRR1313105 3 0.4249 0.518726 0.000 0.000 0.688 0.000 0.260 0.052
#> SRR1313104 3 0.3239 0.620836 0.024 0.000 0.816 0.000 0.152 0.008
#> SRR1313107 6 0.4532 0.601942 0.000 0.000 0.056 0.000 0.308 0.636
#> SRR1313106 3 0.2692 0.557172 0.000 0.000 0.840 0.012 0.148 0.000
#> SRR1313109 6 0.5935 0.355544 0.000 0.256 0.028 0.000 0.156 0.560
#> SRR1313108 6 0.0725 0.814745 0.000 0.000 0.012 0.000 0.012 0.976
#> SRR1313111 6 0.5830 0.415882 0.008 0.000 0.204 0.000 0.252 0.536
#> SRR1313110 3 0.4736 0.513591 0.352 0.000 0.588 0.000 0.060 0.000
#> SRR1313112 3 0.4355 0.624278 0.116 0.024 0.780 0.020 0.060 0.000
#> SRR1313113 3 0.4975 0.563979 0.028 0.000 0.692 0.000 0.184 0.096
#> SRR1313115 6 0.0622 0.814291 0.000 0.000 0.012 0.000 0.008 0.980
#> SRR1313114 3 0.5127 0.509748 0.348 0.000 0.556 0.000 0.096 0.000
#> SRR1313117 3 0.2556 0.649200 0.076 0.000 0.884 0.012 0.028 0.000
#> SRR1313118 3 0.3316 0.653379 0.136 0.000 0.812 0.000 0.052 0.000
#> SRR1313116 3 0.4797 0.398047 0.000 0.000 0.580 0.000 0.356 0.064
#> SRR1313120 6 0.1867 0.796517 0.000 0.000 0.020 0.000 0.064 0.916
#> SRR1313119 3 0.3229 0.645950 0.172 0.000 0.804 0.004 0.020 0.000
#> SRR1313122 3 0.3351 0.627299 0.060 0.000 0.844 0.036 0.060 0.000
#> SRR1313124 3 0.1713 0.654709 0.044 0.000 0.928 0.000 0.028 0.000
#> SRR1313121 3 0.1700 0.607668 0.000 0.000 0.928 0.024 0.048 0.000
#> SRR1313125 3 0.5305 0.525147 0.328 0.000 0.568 0.000 0.096 0.008
#> SRR1313127 1 0.3541 0.471719 0.748 0.000 0.232 0.000 0.020 0.000
#> SRR1313123 1 0.4793 0.276112 0.648 0.000 0.252 0.000 0.100 0.000
#> SRR1313128 6 0.1531 0.798659 0.004 0.000 0.000 0.000 0.068 0.928
#> SRR1313126 3 0.5896 0.390021 0.292 0.000 0.552 0.032 0.124 0.000
#> SRR1313130 5 0.7241 -0.277124 0.028 0.256 0.300 0.000 0.380 0.036
#> SRR1313132 6 0.0632 0.815003 0.000 0.000 0.000 0.000 0.024 0.976
#> SRR1313129 3 0.6743 0.398699 0.316 0.000 0.424 0.000 0.208 0.052
#> SRR1313133 6 0.1007 0.806757 0.000 0.000 0.000 0.000 0.044 0.956
#> SRR1313131 6 0.0508 0.814113 0.000 0.000 0.004 0.000 0.012 0.984
#> SRR1313134 6 0.0777 0.814940 0.004 0.000 0.000 0.000 0.024 0.972
#> SRR1313135 1 0.4740 0.504047 0.632 0.000 0.000 0.064 0.300 0.004
#> SRR1313136 1 0.0951 0.673401 0.968 0.000 0.004 0.000 0.020 0.008
#> SRR1313137 1 0.1333 0.665743 0.944 0.000 0.048 0.000 0.008 0.000
#> SRR1313138 1 0.5636 0.048643 0.516 0.000 0.176 0.000 0.308 0.000
#> SRR1313140 1 0.4420 0.523629 0.644 0.000 0.000 0.048 0.308 0.000
#> SRR1313141 6 0.1588 0.796711 0.004 0.000 0.000 0.000 0.072 0.924
#> SRR1313139 1 0.3881 0.590140 0.720 0.000 0.004 0.024 0.252 0.000
#> SRR1313143 6 0.1866 0.789540 0.008 0.000 0.000 0.000 0.084 0.908
#> SRR1313142 1 0.0767 0.673790 0.976 0.000 0.004 0.000 0.008 0.012
#> SRR1313144 1 0.3134 0.634128 0.808 0.000 0.000 0.024 0.168 0.000
#> SRR1313145 6 0.4932 0.493863 0.240 0.000 0.000 0.012 0.088 0.660
#> SRR1313146 1 0.4134 0.545849 0.656 0.000 0.000 0.000 0.316 0.028
#> SRR1313147 1 0.2782 0.668459 0.876 0.000 0.032 0.024 0.068 0.000
#> SRR1313150 1 0.2136 0.668065 0.908 0.000 0.012 0.016 0.064 0.000
#> SRR1313149 6 0.1866 0.789540 0.008 0.000 0.000 0.000 0.084 0.908
#> SRR1313152 1 0.1053 0.672205 0.964 0.000 0.020 0.004 0.012 0.000
#> SRR1313151 1 0.4170 0.549297 0.660 0.000 0.000 0.000 0.308 0.032
#> SRR1313154 6 0.2604 0.750258 0.096 0.000 0.000 0.028 0.004 0.872
#> SRR1313153 1 0.2925 0.652228 0.856 0.000 0.000 0.016 0.104 0.024
#> SRR1313156 1 0.5712 0.387907 0.660 0.052 0.028 0.000 0.196 0.064
#> SRR1313155 1 0.3782 0.606302 0.752 0.000 0.000 0.016 0.216 0.016
#> SRR1313157 1 0.1820 0.663360 0.924 0.000 0.056 0.012 0.008 0.000
#> SRR1313158 1 0.5928 0.107048 0.492 0.000 0.020 0.000 0.132 0.356
#> SRR1313161 1 0.3196 0.616662 0.836 0.000 0.096 0.004 0.064 0.000
#> SRR1313159 2 0.6815 -0.024315 0.188 0.452 0.000 0.000 0.072 0.288
#> SRR1313160 1 0.3404 0.615985 0.832 0.000 0.096 0.020 0.052 0.000
#> SRR1313162 1 0.4818 0.574461 0.684 0.000 0.032 0.004 0.240 0.040
#> SRR1313163 1 0.3740 0.560729 0.784 0.000 0.120 0.000 0.096 0.000
#> SRR1313165 1 0.2612 0.629944 0.868 0.000 0.108 0.008 0.016 0.000
#> SRR1313166 6 0.0777 0.810334 0.024 0.000 0.000 0.000 0.004 0.972
#> SRR1313164 6 0.2633 0.773041 0.004 0.000 0.020 0.000 0.112 0.864
#> SRR1313167 1 0.3252 0.610882 0.828 0.000 0.128 0.012 0.032 0.000
#> SRR1313168 1 0.2137 0.664302 0.912 0.000 0.048 0.028 0.012 0.000
#> SRR1313170 3 0.8254 0.265520 0.276 0.000 0.328 0.072 0.220 0.104
#> SRR1313169 1 0.1624 0.668545 0.936 0.000 0.044 0.008 0.012 0.000
#> SRR1313172 2 0.4695 0.402520 0.000 0.616 0.016 0.000 0.336 0.032
#> SRR1313171 6 0.4607 0.564154 0.000 0.012 0.028 0.000 0.356 0.604
#> SRR1313174 2 0.0865 0.882745 0.000 0.964 0.000 0.000 0.036 0.000
#> SRR1313173 6 0.0520 0.814510 0.000 0.000 0.008 0.000 0.008 0.984
#> SRR1313176 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313175 2 0.1333 0.872376 0.000 0.944 0.008 0.000 0.048 0.000
#> SRR1313178 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313177 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313179 2 0.2511 0.822954 0.000 0.880 0.000 0.064 0.056 0.000
#> SRR1313180 4 0.5238 0.283467 0.000 0.000 0.236 0.604 0.160 0.000
#> SRR1313181 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313183 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313182 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313184 2 0.0260 0.893882 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1313185 2 0.1003 0.881910 0.000 0.964 0.016 0.000 0.020 0.000
#> SRR1313188 4 0.6730 0.166967 0.000 0.096 0.208 0.512 0.184 0.000
#> SRR1313187 4 0.7666 -0.136059 0.000 0.272 0.220 0.304 0.204 0.000
#> SRR1313186 2 0.2972 0.785233 0.000 0.836 0.036 0.000 0.128 0.000
#> SRR1313189 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313190 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313191 2 0.0146 0.895381 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313192 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313193 2 0.0146 0.895406 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313194 2 0.3650 0.729455 0.000 0.792 0.116 0.000 0.092 0.000
#> SRR1313195 2 0.5623 0.027539 0.000 0.476 0.372 0.000 0.152 0.000
#> SRR1313196 3 0.5113 0.324023 0.000 0.028 0.572 0.040 0.360 0.000
#> SRR1313197 2 0.1867 0.853819 0.000 0.916 0.020 0.000 0.064 0.000
#> SRR1313198 2 0.5303 0.537908 0.000 0.648 0.020 0.196 0.136 0.000
#> SRR1313199 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313200 2 0.7332 -0.070297 0.000 0.384 0.140 0.184 0.292 0.000
#> SRR1313201 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313202 2 0.4478 0.635514 0.000 0.708 0.088 0.004 0.200 0.000
#> SRR1313203 2 0.0146 0.894880 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1313204 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313205 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313207 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313208 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313206 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313210 2 0.4148 0.699032 0.000 0.748 0.016 0.048 0.188 0.000
#> SRR1313209 2 0.1204 0.872648 0.000 0.944 0.000 0.000 0.056 0.000
#> SRR1313211 2 0.0146 0.895406 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1313212 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313214 2 0.1204 0.873727 0.000 0.944 0.000 0.000 0.056 0.000
#> SRR1313215 2 0.3087 0.767691 0.000 0.808 0.012 0.004 0.176 0.000
#> SRR1313213 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313216 2 0.1267 0.870594 0.000 0.940 0.000 0.000 0.060 0.000
#> SRR1313217 2 0.6042 0.330141 0.000 0.544 0.036 0.280 0.140 0.000
#> SRR1313219 2 0.5516 0.422170 0.000 0.588 0.012 0.264 0.136 0.000
#> SRR1313220 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313218 2 0.0363 0.893181 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1313222 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313221 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313223 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313224 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313225 2 0.0937 0.881941 0.000 0.960 0.000 0.000 0.040 0.000
#> SRR1313226 4 0.5591 0.161569 0.000 0.000 0.388 0.468 0.144 0.000
#> SRR1313227 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313228 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1313229 2 0.0000 0.896558 0.000 1.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
sessionInfo()
#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: CentOS Linux 7 (Core)
#>
#> Matrix products: default
#> BLAS: /usr/lib64/libblas.so.3.4.2
#> LAPACK: /usr/lib64/liblapack.so.3.4.2
#>
#> locale:
#> [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8
#> [4] LC_COLLATE=en_GB.UTF-8 LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
#> [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C LC_ADDRESS=C
#> [10] LC_TELEPHONE=C LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
#>
#> attached base packages:
#> [1] grid stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] genefilter_1.66.0 ComplexHeatmap_2.3.1 markdown_1.1 knitr_1.26
#> [5] GetoptLong_0.1.7 cola_1.3.2
#>
#> loaded via a namespace (and not attached):
#> [1] circlize_0.4.8 shape_1.4.4 xfun_0.11 slam_0.1-46
#> [5] lattice_0.20-38 splines_3.6.0 colorspace_1.4-1 vctrs_0.2.0
#> [9] stats4_3.6.0 blob_1.2.0 XML_3.98-1.20 survival_2.44-1.1
#> [13] rlang_0.4.2 pillar_1.4.2 DBI_1.0.0 BiocGenerics_0.30.0
#> [17] bit64_0.9-7 RColorBrewer_1.1-2 matrixStats_0.55.0 stringr_1.4.0
#> [21] GlobalOptions_0.1.1 evaluate_0.14 memoise_1.1.0 Biobase_2.44.0
#> [25] IRanges_2.18.3 parallel_3.6.0 AnnotationDbi_1.46.1 highr_0.8
#> [29] Rcpp_1.0.3 xtable_1.8-4 backports_1.1.5 S4Vectors_0.22.1
#> [33] annotate_1.62.0 skmeans_0.2-11 bit_1.1-14 microbenchmark_1.4-7
#> [37] brew_1.0-6 impute_1.58.0 rjson_0.2.20 png_0.1-7
#> [41] digest_0.6.23 stringi_1.4.3 polyclip_1.10-0 clue_0.3-57
#> [45] tools_3.6.0 bitops_1.0-6 magrittr_1.5 eulerr_6.0.0
#> [49] RCurl_1.95-4.12 RSQLite_2.1.4 tibble_2.1.3 cluster_2.1.0
#> [53] crayon_1.3.4 pkgconfig_2.0.3 zeallot_0.1.0 Matrix_1.2-17
#> [57] xml2_1.2.2 httr_1.4.1 R6_2.4.1 mclust_5.4.5
#> [61] compiler_3.6.0