Date: 2019-12-26 00:55:58 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 15148 rows and 152 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] 15148 152
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 | ||
|---|---|---|---|---|---|---|
| SD:mclust | 2 | 1.000 | 0.997 | 0.996 | ** | |
| MAD:mclust | 2 | 1.000 | 1.000 | 1.000 | ** | |
| ATC:kmeans | 2 | 1.000 | 0.968 | 0.986 | ** | |
| ATC:mclust | 2 | 1.000 | 0.969 | 0.987 | ** | |
| CV:skmeans | 3 | 0.991 | 0.957 | 0.983 | ** | |
| SD:NMF | 3 | 0.973 | 0.936 | 0.974 | ** | |
| SD:kmeans | 3 | 0.963 | 0.940 | 0.969 | ** | |
| ATC:pam | 3 | 0.958 | 0.942 | 0.968 | ** | 2 |
| CV:NMF | 3 | 0.957 | 0.938 | 0.975 | ** | |
| ATC:skmeans | 5 | 0.919 | 0.883 | 0.947 | * | 2,4 |
| MAD:NMF | 3 | 0.917 | 0.919 | 0.964 | * | |
| ATC:NMF | 3 | 0.914 | 0.908 | 0.951 | * | 2 |
| SD:pam | 6 | 0.912 | 0.794 | 0.911 | * | 3,5 |
| MAD:kmeans | 3 | 0.907 | 0.918 | 0.963 | * | |
| MAD:skmeans | 4 | 0.902 | 0.850 | 0.942 | * | 3 |
| MAD:pam | 6 | 0.900 | 0.852 | 0.935 | * | 3 |
| SD:skmeans | 3 | 0.897 | 0.897 | 0.959 | ||
| MAD:hclust | 4 | 0.659 | 0.794 | 0.877 | ||
| CV:kmeans | 3 | 0.656 | 0.848 | 0.891 | ||
| ATC:hclust | 2 | 0.636 | 0.839 | 0.925 | ||
| CV:mclust | 3 | 0.635 | 0.696 | 0.847 | ||
| CV:pam | 2 | 0.599 | 0.852 | 0.925 | ||
| SD:hclust | 2 | 0.422 | 0.648 | 0.861 | ||
| CV:hclust | 2 | 0.200 | 0.754 | 0.844 |
**: 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 0.816 0.915 0.962 0.471 0.528 0.528
#> CV:NMF 2 0.853 0.913 0.964 0.493 0.505 0.505
#> MAD:NMF 2 0.803 0.882 0.952 0.485 0.516 0.516
#> ATC:NMF 2 1.000 0.979 0.991 0.431 0.570 0.570
#> SD:skmeans 2 0.345 0.608 0.775 0.489 0.507 0.507
#> CV:skmeans 2 0.502 0.730 0.834 0.477 0.539 0.539
#> MAD:skmeans 2 0.460 0.760 0.887 0.498 0.497 0.497
#> ATC:skmeans 2 1.000 0.976 0.989 0.500 0.501 0.501
#> SD:mclust 2 1.000 0.997 0.996 0.458 0.543 0.543
#> CV:mclust 2 0.452 0.834 0.879 0.398 0.556 0.556
#> MAD:mclust 2 1.000 1.000 1.000 0.458 0.543 0.543
#> ATC:mclust 2 1.000 0.969 0.987 0.448 0.556 0.556
#> SD:kmeans 2 0.317 0.733 0.828 0.453 0.565 0.565
#> CV:kmeans 2 0.228 0.564 0.718 0.463 0.505 0.505
#> MAD:kmeans 2 0.299 0.625 0.802 0.462 0.535 0.535
#> ATC:kmeans 2 1.000 0.968 0.986 0.457 0.539 0.539
#> SD:pam 2 0.874 0.899 0.956 0.501 0.497 0.497
#> CV:pam 2 0.599 0.852 0.925 0.483 0.522 0.522
#> MAD:pam 2 0.880 0.913 0.966 0.502 0.498 0.498
#> ATC:pam 2 1.000 0.982 0.993 0.430 0.575 0.575
#> SD:hclust 2 0.422 0.648 0.861 0.458 0.505 0.505
#> CV:hclust 2 0.200 0.754 0.844 0.438 0.514 0.514
#> MAD:hclust 2 0.442 0.663 0.866 0.431 0.560 0.560
#> ATC:hclust 2 0.636 0.839 0.925 0.443 0.535 0.535
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.973 0.936 0.974 0.404 0.699 0.484
#> CV:NMF 3 0.957 0.938 0.975 0.356 0.698 0.469
#> MAD:NMF 3 0.917 0.919 0.964 0.371 0.690 0.466
#> ATC:NMF 3 0.914 0.908 0.951 0.502 0.686 0.491
#> SD:skmeans 3 0.897 0.897 0.959 0.368 0.666 0.429
#> CV:skmeans 3 0.991 0.957 0.983 0.407 0.782 0.598
#> MAD:skmeans 3 0.904 0.909 0.962 0.346 0.694 0.460
#> ATC:skmeans 3 0.839 0.935 0.952 0.296 0.776 0.581
#> SD:mclust 3 0.655 0.748 0.860 0.289 0.857 0.742
#> CV:mclust 3 0.635 0.696 0.847 0.585 0.745 0.566
#> MAD:mclust 3 0.609 0.729 0.830 0.281 0.941 0.893
#> ATC:mclust 3 0.634 0.748 0.861 0.390 0.809 0.657
#> SD:kmeans 3 0.963 0.940 0.969 0.439 0.715 0.525
#> CV:kmeans 3 0.656 0.848 0.891 0.404 0.690 0.459
#> MAD:kmeans 3 0.907 0.918 0.963 0.419 0.680 0.468
#> ATC:kmeans 3 0.667 0.870 0.910 0.402 0.645 0.436
#> SD:pam 3 0.940 0.943 0.976 0.233 0.825 0.670
#> CV:pam 3 0.542 0.748 0.869 0.275 0.681 0.482
#> MAD:pam 3 0.966 0.934 0.974 0.235 0.810 0.644
#> ATC:pam 3 0.958 0.942 0.968 0.459 0.665 0.481
#> SD:hclust 3 0.405 0.591 0.736 0.356 0.704 0.486
#> CV:hclust 3 0.286 0.674 0.774 0.367 0.832 0.674
#> MAD:hclust 3 0.333 0.529 0.718 0.468 0.682 0.483
#> ATC:hclust 3 0.473 0.626 0.768 0.339 0.819 0.675
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.751 0.738 0.889 0.1044 0.855 0.614
#> CV:NMF 4 0.743 0.467 0.741 0.1079 0.802 0.511
#> MAD:NMF 4 0.791 0.789 0.904 0.1004 0.868 0.640
#> ATC:NMF 4 0.655 0.690 0.831 0.1259 0.862 0.631
#> SD:skmeans 4 0.900 0.885 0.953 0.1220 0.866 0.624
#> CV:skmeans 4 0.770 0.748 0.859 0.1036 0.895 0.700
#> MAD:skmeans 4 0.902 0.850 0.942 0.1179 0.871 0.637
#> ATC:skmeans 4 0.927 0.880 0.945 0.1018 0.887 0.696
#> SD:mclust 4 0.687 0.765 0.855 0.1589 0.900 0.770
#> CV:mclust 4 0.635 0.653 0.808 0.1034 0.887 0.713
#> MAD:mclust 4 0.665 0.667 0.816 0.1835 0.739 0.504
#> ATC:mclust 4 0.583 0.720 0.796 0.0485 0.921 0.801
#> SD:kmeans 4 0.694 0.793 0.813 0.1150 0.863 0.631
#> CV:kmeans 4 0.584 0.559 0.761 0.1138 0.929 0.793
#> MAD:kmeans 4 0.686 0.774 0.814 0.1128 0.867 0.638
#> ATC:kmeans 4 0.630 0.706 0.837 0.1561 0.856 0.626
#> SD:pam 4 0.807 0.836 0.878 0.1372 0.892 0.719
#> CV:pam 4 0.643 0.722 0.841 0.1518 0.747 0.457
#> MAD:pam 4 0.794 0.870 0.908 0.1626 0.878 0.684
#> ATC:pam 4 0.873 0.881 0.947 0.1904 0.851 0.618
#> SD:hclust 4 0.586 0.718 0.814 0.1776 0.836 0.569
#> CV:hclust 4 0.381 0.583 0.686 0.1401 0.933 0.807
#> MAD:hclust 4 0.659 0.794 0.877 0.1751 0.858 0.617
#> ATC:hclust 4 0.500 0.645 0.769 0.1462 0.785 0.524
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.683 0.651 0.831 0.0681 0.867 0.572
#> CV:NMF 5 0.837 0.828 0.905 0.0661 0.861 0.557
#> MAD:NMF 5 0.740 0.725 0.857 0.0653 0.879 0.602
#> ATC:NMF 5 0.629 0.605 0.756 0.0740 0.831 0.473
#> SD:skmeans 5 0.827 0.730 0.832 0.0563 0.941 0.771
#> CV:skmeans 5 0.716 0.649 0.821 0.0671 0.923 0.720
#> MAD:skmeans 5 0.818 0.746 0.854 0.0586 0.920 0.701
#> ATC:skmeans 5 0.919 0.883 0.947 0.0687 0.921 0.738
#> SD:mclust 5 0.848 0.718 0.884 0.1107 0.883 0.668
#> CV:mclust 5 0.567 0.544 0.738 0.0624 0.941 0.814
#> MAD:mclust 5 0.872 0.884 0.946 0.1107 0.866 0.595
#> ATC:mclust 5 0.721 0.803 0.843 0.1635 0.859 0.605
#> SD:kmeans 5 0.756 0.796 0.842 0.0738 0.946 0.795
#> CV:kmeans 5 0.556 0.657 0.716 0.0602 0.801 0.429
#> MAD:kmeans 5 0.776 0.662 0.828 0.0724 0.983 0.935
#> ATC:kmeans 5 0.709 0.691 0.819 0.0705 0.870 0.561
#> SD:pam 5 0.960 0.913 0.952 0.0899 0.942 0.795
#> CV:pam 5 0.587 0.721 0.831 0.0612 0.921 0.743
#> MAD:pam 5 0.801 0.750 0.858 0.0785 0.942 0.790
#> ATC:pam 5 0.768 0.672 0.838 0.0444 0.979 0.917
#> SD:hclust 5 0.620 0.628 0.786 0.0515 0.952 0.813
#> CV:hclust 5 0.486 0.582 0.695 0.0915 0.928 0.755
#> MAD:hclust 5 0.664 0.638 0.819 0.0456 0.965 0.863
#> ATC:hclust 5 0.584 0.563 0.725 0.1143 0.833 0.491
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.702 0.621 0.800 0.0462 0.895 0.586
#> CV:NMF 6 0.723 0.667 0.813 0.0471 0.899 0.579
#> MAD:NMF 6 0.684 0.605 0.782 0.0487 0.905 0.627
#> ATC:NMF 6 0.642 0.507 0.704 0.0470 0.898 0.585
#> SD:skmeans 6 0.775 0.620 0.732 0.0396 0.908 0.608
#> CV:skmeans 6 0.719 0.542 0.767 0.0493 0.909 0.606
#> MAD:skmeans 6 0.751 0.685 0.755 0.0410 0.922 0.656
#> ATC:skmeans 6 0.882 0.870 0.931 0.0591 0.896 0.602
#> SD:mclust 6 0.840 0.853 0.914 0.0523 0.878 0.567
#> CV:mclust 6 0.607 0.561 0.709 0.0784 0.874 0.560
#> MAD:mclust 6 0.811 0.786 0.890 0.0245 0.901 0.636
#> ATC:mclust 6 0.847 0.853 0.908 0.0706 0.909 0.637
#> SD:kmeans 6 0.767 0.757 0.800 0.0440 0.952 0.788
#> CV:kmeans 6 0.639 0.673 0.737 0.0576 0.955 0.797
#> MAD:kmeans 6 0.772 0.763 0.810 0.0419 0.916 0.675
#> ATC:kmeans 6 0.724 0.543 0.734 0.0415 0.923 0.665
#> SD:pam 6 0.912 0.794 0.911 0.0692 0.903 0.616
#> CV:pam 6 0.716 0.740 0.847 0.0614 0.922 0.701
#> MAD:pam 6 0.900 0.852 0.935 0.0545 0.922 0.675
#> ATC:pam 6 0.797 0.748 0.863 0.0374 0.930 0.726
#> SD:hclust 6 0.653 0.680 0.792 0.0422 0.957 0.813
#> CV:hclust 6 0.606 0.538 0.709 0.0501 0.952 0.799
#> MAD:hclust 6 0.721 0.768 0.840 0.0368 0.951 0.791
#> ATC:hclust 6 0.694 0.558 0.749 0.0609 0.937 0.721
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 15148 rows and 152 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 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 0.422 0.648 0.861 0.4576 0.505 0.505
#> 3 3 0.405 0.591 0.736 0.3561 0.704 0.486
#> 4 4 0.586 0.718 0.814 0.1776 0.836 0.569
#> 5 5 0.620 0.628 0.786 0.0515 0.952 0.813
#> 6 6 0.653 0.680 0.792 0.0422 0.957 0.813
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
#> SRR1947547 1 0.3584 0.7786 0.932 0.068
#> SRR1947546 2 0.0000 0.8580 0.000 1.000
#> SRR1947545 1 0.0000 0.7699 1.000 0.000
#> SRR1947544 1 0.5946 0.7541 0.856 0.144
#> SRR1947542 2 0.0000 0.8580 0.000 1.000
#> SRR1947541 1 0.3584 0.7786 0.932 0.068
#> SRR1947540 2 0.9248 0.3333 0.340 0.660
#> SRR1947539 2 0.1414 0.8468 0.020 0.980
#> SRR1947538 1 0.9850 0.4026 0.572 0.428
#> SRR1947537 2 0.9881 0.1121 0.436 0.564
#> SRR1947536 1 0.7056 0.7144 0.808 0.192
#> SRR1947535 2 0.0000 0.8580 0.000 1.000
#> SRR1947534 1 0.8608 0.6041 0.716 0.284
#> SRR1947533 2 0.0000 0.8580 0.000 1.000
#> SRR1947532 2 1.0000 -0.2284 0.500 0.500
#> SRR1947531 2 0.9248 0.3333 0.340 0.660
#> SRR1947530 1 0.0672 0.7719 0.992 0.008
#> SRR1947529 2 0.0000 0.8580 0.000 1.000
#> SRR1947528 1 0.3733 0.7782 0.928 0.072
#> SRR1947527 2 0.5946 0.6990 0.144 0.856
#> SRR1947526 2 0.0000 0.8580 0.000 1.000
#> SRR1947525 1 0.9552 0.5173 0.624 0.376
#> SRR1947524 2 0.1414 0.8468 0.020 0.980
#> SRR1947523 2 1.0000 -0.2283 0.500 0.500
#> SRR1947521 2 0.0000 0.8580 0.000 1.000
#> SRR1947520 2 0.0000 0.8580 0.000 1.000
#> SRR1947519 2 0.0000 0.8580 0.000 1.000
#> SRR1947518 1 0.9850 0.4026 0.572 0.428
#> SRR1947517 1 0.9988 0.2280 0.520 0.480
#> SRR1947516 2 0.0000 0.8580 0.000 1.000
#> SRR1947515 2 1.0000 -0.2284 0.500 0.500
#> SRR1947514 2 0.0000 0.8580 0.000 1.000
#> SRR1947513 1 0.7139 0.7148 0.804 0.196
#> SRR1947512 1 0.0000 0.7699 1.000 0.000
#> SRR1947511 2 0.0000 0.8580 0.000 1.000
#> SRR1947510 2 0.0000 0.8580 0.000 1.000
#> SRR1947572 1 0.6148 0.7505 0.848 0.152
#> SRR1947611 2 0.0000 0.8580 0.000 1.000
#> SRR1947509 1 0.9988 0.2280 0.520 0.480
#> SRR1947644 2 0.0000 0.8580 0.000 1.000
#> SRR1947643 2 0.0000 0.8580 0.000 1.000
#> SRR1947642 2 0.0938 0.8516 0.012 0.988
#> SRR1947640 1 1.0000 0.2072 0.500 0.500
#> SRR1947641 2 0.0000 0.8580 0.000 1.000
#> SRR1947639 1 0.8207 0.6704 0.744 0.256
#> SRR1947638 1 0.5737 0.7589 0.864 0.136
#> SRR1947637 2 0.0000 0.8580 0.000 1.000
#> SRR1947636 2 0.9881 0.1121 0.436 0.564
#> SRR1947635 2 0.9754 0.0740 0.408 0.592
#> SRR1947634 2 0.0000 0.8580 0.000 1.000
#> SRR1947633 2 0.1414 0.8468 0.020 0.980
#> SRR1947632 2 0.0000 0.8580 0.000 1.000
#> SRR1947631 2 0.0000 0.8580 0.000 1.000
#> SRR1947629 2 0.1414 0.8468 0.020 0.980
#> SRR1947630 2 0.0000 0.8580 0.000 1.000
#> SRR1947627 1 0.6887 0.7194 0.816 0.184
#> SRR1947628 2 1.0000 -0.2150 0.496 0.504
#> SRR1947626 2 0.0000 0.8580 0.000 1.000
#> SRR1947625 2 0.0000 0.8580 0.000 1.000
#> SRR1947624 2 0.0000 0.8580 0.000 1.000
#> SRR1947623 1 0.6048 0.7528 0.852 0.148
#> SRR1947622 2 0.0000 0.8580 0.000 1.000
#> SRR1947621 2 0.0000 0.8580 0.000 1.000
#> SRR1947620 1 0.4690 0.7676 0.900 0.100
#> SRR1947619 2 0.7139 0.6434 0.196 0.804
#> SRR1947617 2 0.0000 0.8580 0.000 1.000
#> SRR1947618 1 0.4690 0.7676 0.900 0.100
#> SRR1947616 2 0.0000 0.8580 0.000 1.000
#> SRR1947615 1 0.3584 0.7786 0.932 0.068
#> SRR1947614 2 0.0000 0.8580 0.000 1.000
#> SRR1947613 1 0.0376 0.7716 0.996 0.004
#> SRR1947610 1 0.9850 0.4026 0.572 0.428
#> SRR1947612 2 0.0000 0.8580 0.000 1.000
#> SRR1947609 1 1.0000 0.2072 0.500 0.500
#> SRR1947608 2 0.0000 0.8580 0.000 1.000
#> SRR1947606 1 0.8267 0.6250 0.740 0.260
#> SRR1947607 1 0.0672 0.7729 0.992 0.008
#> SRR1947604 1 1.0000 0.2072 0.500 0.500
#> SRR1947605 1 0.0000 0.7699 1.000 0.000
#> SRR1947603 2 0.0000 0.8580 0.000 1.000
#> SRR1947602 1 0.0672 0.7719 0.992 0.008
#> SRR1947600 2 0.1414 0.8468 0.020 0.980
#> SRR1947601 2 0.0000 0.8580 0.000 1.000
#> SRR1947598 2 1.0000 -0.2150 0.496 0.504
#> SRR1947599 1 0.9998 0.2296 0.508 0.492
#> SRR1947597 2 0.4562 0.7696 0.096 0.904
#> SRR1947596 1 0.5946 0.7541 0.856 0.144
#> SRR1947595 2 1.0000 -0.2283 0.500 0.500
#> SRR1947594 1 0.0000 0.7699 1.000 0.000
#> SRR1947592 2 0.1414 0.8468 0.020 0.980
#> SRR1947591 2 0.0000 0.8580 0.000 1.000
#> SRR1947590 1 0.5946 0.7541 0.856 0.144
#> SRR1947588 1 0.0000 0.7699 1.000 0.000
#> SRR1947587 1 0.3584 0.7786 0.932 0.068
#> SRR1947586 2 0.0000 0.8580 0.000 1.000
#> SRR1947585 2 0.1414 0.8468 0.020 0.980
#> SRR1947584 1 0.0000 0.7699 1.000 0.000
#> SRR1947583 1 1.0000 0.2072 0.500 0.500
#> SRR1947582 1 0.4690 0.7676 0.900 0.100
#> SRR1947580 2 0.0000 0.8580 0.000 1.000
#> SRR1947581 1 0.0000 0.7699 1.000 0.000
#> SRR1947576 2 0.0000 0.8580 0.000 1.000
#> SRR1947575 2 0.0000 0.8580 0.000 1.000
#> SRR1947579 2 0.0000 0.8580 0.000 1.000
#> SRR1947578 2 1.0000 -0.2150 0.496 0.504
#> SRR1947573 2 0.1414 0.8468 0.020 0.980
#> SRR1947574 1 0.9248 0.5538 0.660 0.340
#> SRR1947571 1 1.0000 0.2073 0.500 0.500
#> SRR1947577 1 0.4690 0.7676 0.900 0.100
#> SRR1947570 1 0.3584 0.7786 0.932 0.068
#> SRR1947569 2 0.1414 0.8468 0.020 0.980
#> SRR1947566 2 0.0000 0.8580 0.000 1.000
#> SRR1947567 2 0.9754 0.0740 0.408 0.592
#> SRR1947568 1 0.6247 0.7487 0.844 0.156
#> SRR1947564 2 0.0000 0.8580 0.000 1.000
#> SRR1947563 2 0.0000 0.8580 0.000 1.000
#> SRR1947562 2 0.9775 0.0909 0.412 0.588
#> SRR1947565 2 0.9881 0.1121 0.436 0.564
#> SRR1947559 2 0.4562 0.7696 0.096 0.904
#> SRR1947560 2 0.0000 0.8580 0.000 1.000
#> SRR1947561 2 0.0000 0.8580 0.000 1.000
#> SRR1947557 1 0.0000 0.7699 1.000 0.000
#> SRR1947558 2 0.0000 0.8580 0.000 1.000
#> SRR1947556 1 0.5946 0.7541 0.856 0.144
#> SRR1947553 1 0.9850 0.4026 0.572 0.428
#> SRR1947554 1 0.0672 0.7729 0.992 0.008
#> SRR1947555 2 0.0000 0.8580 0.000 1.000
#> SRR1947550 2 1.0000 -0.2283 0.500 0.500
#> SRR1947552 1 0.9998 0.2296 0.508 0.492
#> SRR1947549 2 0.1414 0.8468 0.020 0.980
#> SRR1947551 2 0.0000 0.8580 0.000 1.000
#> SRR1947548 1 1.0000 0.2073 0.500 0.500
#> SRR1947506 1 0.0672 0.7719 0.992 0.008
#> SRR1947507 1 0.0000 0.7699 1.000 0.000
#> SRR1947504 1 0.5946 0.7541 0.856 0.144
#> SRR1947503 1 0.5737 0.7589 0.864 0.136
#> SRR1947502 2 0.0000 0.8580 0.000 1.000
#> SRR1947501 2 0.0000 0.8580 0.000 1.000
#> SRR1947499 1 0.0672 0.7719 0.992 0.008
#> SRR1947498 2 0.1414 0.8468 0.020 0.980
#> SRR1947508 1 0.6887 0.7194 0.816 0.184
#> SRR1947505 2 1.0000 -0.2150 0.496 0.504
#> SRR1947497 2 0.0376 0.8553 0.004 0.996
#> SRR1947496 1 0.0000 0.7699 1.000 0.000
#> SRR1947495 2 0.0376 0.8553 0.004 0.996
#> SRR1947494 1 1.0000 0.2188 0.504 0.496
#> SRR1947493 1 0.0672 0.7719 0.992 0.008
#> SRR1947492 1 0.0376 0.7716 0.996 0.004
#> SRR1947500 1 1.0000 0.2072 0.500 0.500
#> SRR1947491 2 0.9754 0.0740 0.408 0.592
#> SRR1947490 1 0.0376 0.7716 0.996 0.004
#> SRR1947489 1 0.3584 0.7786 0.932 0.068
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.4779 0.7770 0.840 0.124 0.036
#> SRR1947546 2 0.5397 0.5097 0.000 0.720 0.280
#> SRR1947545 1 0.0000 0.8092 1.000 0.000 0.000
#> SRR1947544 1 0.6416 0.5534 0.616 0.376 0.008
#> SRR1947542 2 0.5397 0.5097 0.000 0.720 0.280
#> SRR1947541 1 0.4779 0.7770 0.840 0.124 0.036
#> SRR1947540 2 0.9975 0.4379 0.312 0.368 0.320
#> SRR1947539 3 0.1411 0.8964 0.000 0.036 0.964
#> SRR1947538 2 0.7940 0.1871 0.332 0.592 0.076
#> SRR1947537 3 0.8769 0.1904 0.348 0.124 0.528
#> SRR1947536 1 0.5581 0.6935 0.788 0.036 0.176
#> SRR1947535 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947534 1 0.6322 0.5089 0.700 0.276 0.024
#> SRR1947533 2 0.5650 0.4973 0.000 0.688 0.312
#> SRR1947532 2 0.9239 0.3210 0.328 0.500 0.172
#> SRR1947531 2 0.9975 0.4379 0.312 0.368 0.320
#> SRR1947530 1 0.1315 0.8085 0.972 0.020 0.008
#> SRR1947529 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947528 1 0.4891 0.7757 0.836 0.124 0.040
#> SRR1947527 2 0.8834 0.4824 0.140 0.544 0.316
#> SRR1947526 2 0.5733 0.4870 0.000 0.676 0.324
#> SRR1947525 2 0.7050 -0.0714 0.372 0.600 0.028
#> SRR1947524 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947523 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947521 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947520 2 0.5859 0.4625 0.000 0.656 0.344
#> SRR1947519 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947518 2 0.7940 0.1871 0.332 0.592 0.076
#> SRR1947517 1 0.7059 0.1240 0.520 0.020 0.460
#> SRR1947516 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947515 2 0.9239 0.3210 0.328 0.500 0.172
#> SRR1947514 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947513 1 0.5356 0.6389 0.784 0.196 0.020
#> SRR1947512 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947511 2 0.5859 0.4625 0.000 0.656 0.344
#> SRR1947510 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947572 1 0.6451 0.5419 0.608 0.384 0.008
#> SRR1947611 3 0.1163 0.8814 0.000 0.028 0.972
#> SRR1947509 1 0.7059 0.1240 0.520 0.020 0.460
#> SRR1947644 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947643 2 0.5621 0.5016 0.000 0.692 0.308
#> SRR1947642 3 0.1289 0.8992 0.000 0.032 0.968
#> SRR1947640 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947641 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947639 2 0.7188 -0.3497 0.484 0.492 0.024
#> SRR1947638 1 0.5253 0.7201 0.792 0.188 0.020
#> SRR1947637 3 0.1163 0.8814 0.000 0.028 0.972
#> SRR1947636 3 0.8769 0.1904 0.348 0.124 0.528
#> SRR1947635 2 0.8853 0.4083 0.252 0.572 0.176
#> SRR1947634 2 0.6235 0.3047 0.000 0.564 0.436
#> SRR1947633 3 0.1411 0.8964 0.000 0.036 0.964
#> SRR1947632 2 0.5397 0.5097 0.000 0.720 0.280
#> SRR1947631 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947629 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947630 2 0.6235 0.3047 0.000 0.564 0.436
#> SRR1947627 1 0.5470 0.6995 0.796 0.036 0.168
#> SRR1947628 2 0.9262 0.3256 0.324 0.500 0.176
#> SRR1947626 2 0.5591 0.5033 0.000 0.696 0.304
#> SRR1947625 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947624 2 0.6235 0.3047 0.000 0.564 0.436
#> SRR1947623 1 0.6434 0.5488 0.612 0.380 0.008
#> SRR1947622 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947621 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947620 1 0.3769 0.7594 0.880 0.104 0.016
#> SRR1947619 3 0.5988 0.6369 0.168 0.056 0.776
#> SRR1947617 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947618 1 0.3769 0.7594 0.880 0.104 0.016
#> SRR1947616 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947615 1 0.4779 0.7770 0.840 0.124 0.036
#> SRR1947614 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947613 1 0.0424 0.8097 0.992 0.008 0.000
#> SRR1947610 2 0.7940 0.1871 0.332 0.592 0.076
#> SRR1947612 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947609 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947608 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947606 1 0.7983 0.6073 0.648 0.124 0.228
#> SRR1947607 1 0.0983 0.8099 0.980 0.016 0.004
#> SRR1947604 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947605 1 0.0000 0.8092 1.000 0.000 0.000
#> SRR1947603 2 0.5733 0.4921 0.000 0.676 0.324
#> SRR1947602 1 0.1315 0.8085 0.972 0.020 0.008
#> SRR1947600 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947601 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947598 2 0.9262 0.3256 0.324 0.500 0.176
#> SRR1947599 2 0.9254 0.3053 0.332 0.496 0.172
#> SRR1947597 2 0.7545 0.4971 0.076 0.652 0.272
#> SRR1947596 1 0.6416 0.5534 0.616 0.376 0.008
#> SRR1947595 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947594 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947592 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947591 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947590 1 0.6416 0.5534 0.616 0.376 0.008
#> SRR1947588 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947587 1 0.4779 0.7770 0.840 0.124 0.036
#> SRR1947586 2 0.5591 0.5033 0.000 0.696 0.304
#> SRR1947585 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947584 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947583 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947582 1 0.3769 0.7594 0.880 0.104 0.016
#> SRR1947580 2 0.5591 0.5033 0.000 0.696 0.304
#> SRR1947581 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947576 3 0.1163 0.8814 0.000 0.028 0.972
#> SRR1947575 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947579 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947578 2 0.9262 0.3256 0.324 0.500 0.176
#> SRR1947573 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947574 1 0.8093 0.2318 0.516 0.416 0.068
#> SRR1947571 2 0.9239 0.3210 0.328 0.500 0.172
#> SRR1947577 1 0.3769 0.7594 0.880 0.104 0.016
#> SRR1947570 1 0.4779 0.7770 0.840 0.124 0.036
#> SRR1947569 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947566 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947567 2 0.8853 0.4083 0.252 0.572 0.176
#> SRR1947568 1 0.6483 0.5344 0.600 0.392 0.008
#> SRR1947564 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947563 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947562 2 0.8937 0.4079 0.252 0.564 0.184
#> SRR1947565 3 0.8769 0.1904 0.348 0.124 0.528
#> SRR1947559 2 0.7545 0.4971 0.076 0.652 0.272
#> SRR1947560 3 0.1163 0.8814 0.000 0.028 0.972
#> SRR1947561 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947557 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947558 3 0.1031 0.9000 0.000 0.024 0.976
#> SRR1947556 1 0.6416 0.5534 0.616 0.376 0.008
#> SRR1947553 2 0.7940 0.1871 0.332 0.592 0.076
#> SRR1947554 1 0.0983 0.8099 0.980 0.016 0.004
#> SRR1947555 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947550 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947552 2 0.9254 0.3053 0.332 0.496 0.172
#> SRR1947549 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947551 3 0.1031 0.8846 0.000 0.024 0.976
#> SRR1947548 2 0.9239 0.3210 0.328 0.500 0.172
#> SRR1947506 1 0.1453 0.8088 0.968 0.024 0.008
#> SRR1947507 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947504 1 0.6416 0.5534 0.616 0.376 0.008
#> SRR1947503 1 0.5253 0.7201 0.792 0.188 0.020
#> SRR1947502 2 0.5706 0.4921 0.000 0.680 0.320
#> SRR1947501 2 0.5397 0.5097 0.000 0.720 0.280
#> SRR1947499 1 0.1315 0.8085 0.972 0.020 0.008
#> SRR1947498 3 0.1529 0.8966 0.000 0.040 0.960
#> SRR1947508 1 0.5470 0.6995 0.796 0.036 0.168
#> SRR1947505 2 0.9262 0.3256 0.324 0.500 0.176
#> SRR1947497 2 0.5650 0.4979 0.000 0.688 0.312
#> SRR1947496 1 0.0237 0.8095 0.996 0.004 0.000
#> SRR1947495 2 0.5650 0.4979 0.000 0.688 0.312
#> SRR1947494 2 0.9254 0.3134 0.332 0.496 0.172
#> SRR1947493 1 0.1453 0.8088 0.968 0.024 0.008
#> SRR1947492 1 0.0424 0.8097 0.992 0.008 0.000
#> SRR1947500 2 0.9223 0.3216 0.324 0.504 0.172
#> SRR1947491 2 0.8853 0.4083 0.252 0.572 0.176
#> SRR1947490 1 0.0424 0.8097 0.992 0.008 0.000
#> SRR1947489 1 0.4779 0.7770 0.840 0.124 0.036
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.4973 0.575 0.644 0.000 0.008 0.348
#> SRR1947546 2 0.2489 0.848 0.000 0.912 0.020 0.068
#> SRR1947545 1 0.0188 0.783 0.996 0.000 0.000 0.004
#> SRR1947544 4 0.5028 0.265 0.400 0.004 0.000 0.596
#> SRR1947542 2 0.2489 0.848 0.000 0.912 0.020 0.068
#> SRR1947541 1 0.4973 0.575 0.644 0.000 0.008 0.348
#> SRR1947540 2 0.5408 -0.153 0.000 0.500 0.012 0.488
#> SRR1947539 3 0.2384 0.858 0.004 0.008 0.916 0.072
#> SRR1947538 4 0.3708 0.758 0.000 0.148 0.020 0.832
#> SRR1947537 3 0.7790 0.221 0.236 0.008 0.492 0.264
#> SRR1947536 1 0.6352 0.628 0.656 0.000 0.156 0.188
#> SRR1947535 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947534 1 0.7413 0.299 0.516 0.252 0.000 0.232
#> SRR1947533 2 0.0336 0.902 0.000 0.992 0.000 0.008
#> SRR1947532 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947531 2 0.5408 -0.153 0.000 0.500 0.012 0.488
#> SRR1947530 1 0.3402 0.762 0.832 0.000 0.004 0.164
#> SRR1947529 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947528 1 0.5075 0.577 0.644 0.000 0.012 0.344
#> SRR1947527 2 0.3266 0.737 0.000 0.832 0.000 0.168
#> SRR1947526 2 0.0188 0.902 0.000 0.996 0.004 0.000
#> SRR1947525 4 0.5042 0.628 0.096 0.136 0.000 0.768
#> SRR1947524 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947523 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947521 3 0.2125 0.807 0.000 0.076 0.920 0.004
#> SRR1947520 2 0.1256 0.883 0.000 0.964 0.028 0.008
#> SRR1947519 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947518 4 0.3708 0.758 0.000 0.148 0.020 0.832
#> SRR1947517 3 0.6447 -0.061 0.448 0.000 0.484 0.068
#> SRR1947516 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947514 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.6532 0.328 0.548 0.084 0.000 0.368
#> SRR1947512 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947511 2 0.1109 0.885 0.000 0.968 0.028 0.004
#> SRR1947510 3 0.2125 0.807 0.000 0.076 0.920 0.004
#> SRR1947572 4 0.4950 0.306 0.376 0.004 0.000 0.620
#> SRR1947611 3 0.2197 0.804 0.000 0.080 0.916 0.004
#> SRR1947509 3 0.6447 -0.061 0.448 0.000 0.484 0.068
#> SRR1947644 3 0.0804 0.834 0.000 0.012 0.980 0.008
#> SRR1947643 2 0.0817 0.899 0.000 0.976 0.000 0.024
#> SRR1947642 3 0.2561 0.858 0.004 0.016 0.912 0.068
#> SRR1947640 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947641 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947639 4 0.4019 0.533 0.196 0.012 0.000 0.792
#> SRR1947638 1 0.4673 0.627 0.700 0.008 0.000 0.292
#> SRR1947637 3 0.2197 0.804 0.000 0.080 0.916 0.004
#> SRR1947636 3 0.7790 0.221 0.236 0.008 0.492 0.264
#> SRR1947635 4 0.6837 0.572 0.000 0.340 0.116 0.544
#> SRR1947634 2 0.3668 0.728 0.000 0.808 0.188 0.004
#> SRR1947633 3 0.2384 0.858 0.004 0.008 0.916 0.072
#> SRR1947632 2 0.2489 0.848 0.000 0.912 0.020 0.068
#> SRR1947631 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947629 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947630 2 0.3810 0.726 0.000 0.804 0.188 0.008
#> SRR1947627 1 0.6274 0.638 0.664 0.000 0.152 0.184
#> SRR1947628 4 0.5522 0.801 0.000 0.148 0.120 0.732
#> SRR1947626 2 0.0817 0.896 0.000 0.976 0.000 0.024
#> SRR1947625 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947624 2 0.3810 0.726 0.000 0.804 0.188 0.008
#> SRR1947623 4 0.4964 0.298 0.380 0.004 0.000 0.616
#> SRR1947622 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.3569 0.710 0.804 0.000 0.000 0.196
#> SRR1947619 3 0.5650 0.662 0.080 0.008 0.728 0.184
#> SRR1947617 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.3569 0.710 0.804 0.000 0.000 0.196
#> SRR1947616 2 0.0188 0.903 0.000 0.996 0.000 0.004
#> SRR1947615 1 0.4973 0.575 0.644 0.000 0.008 0.348
#> SRR1947614 3 0.2125 0.807 0.000 0.076 0.920 0.004
#> SRR1947613 1 0.1022 0.781 0.968 0.000 0.000 0.032
#> SRR1947610 4 0.3708 0.758 0.000 0.148 0.020 0.832
#> SRR1947612 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947609 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947608 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947606 1 0.7346 0.394 0.520 0.000 0.200 0.280
#> SRR1947607 1 0.3074 0.750 0.848 0.000 0.000 0.152
#> SRR1947604 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947605 1 0.0188 0.783 0.996 0.000 0.000 0.004
#> SRR1947603 2 0.0188 0.903 0.000 0.996 0.000 0.004
#> SRR1947602 1 0.3402 0.762 0.832 0.000 0.004 0.164
#> SRR1947600 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947601 2 0.0336 0.900 0.000 0.992 0.000 0.008
#> SRR1947598 4 0.5522 0.801 0.000 0.148 0.120 0.732
#> SRR1947599 4 0.5694 0.799 0.008 0.140 0.116 0.736
#> SRR1947597 2 0.4797 0.563 0.000 0.720 0.020 0.260
#> SRR1947596 4 0.5028 0.265 0.400 0.004 0.000 0.596
#> SRR1947595 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947594 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947592 3 0.2457 0.856 0.004 0.008 0.912 0.076
#> SRR1947591 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.5028 0.265 0.400 0.004 0.000 0.596
#> SRR1947588 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947587 1 0.4973 0.575 0.644 0.000 0.008 0.348
#> SRR1947586 2 0.0817 0.896 0.000 0.976 0.000 0.024
#> SRR1947585 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947584 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947583 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947582 1 0.3569 0.710 0.804 0.000 0.000 0.196
#> SRR1947580 2 0.0921 0.897 0.000 0.972 0.000 0.028
#> SRR1947581 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947576 3 0.2197 0.804 0.000 0.080 0.916 0.004
#> SRR1947575 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947579 3 0.2125 0.807 0.000 0.076 0.920 0.004
#> SRR1947578 4 0.5522 0.801 0.000 0.148 0.120 0.732
#> SRR1947573 3 0.2457 0.856 0.004 0.008 0.912 0.076
#> SRR1947574 4 0.6596 0.592 0.184 0.132 0.016 0.668
#> SRR1947571 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947577 1 0.3569 0.710 0.804 0.000 0.000 0.196
#> SRR1947570 1 0.4973 0.575 0.644 0.000 0.008 0.348
#> SRR1947569 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947566 2 0.0188 0.903 0.000 0.996 0.000 0.004
#> SRR1947567 4 0.6837 0.572 0.000 0.340 0.116 0.544
#> SRR1947568 4 0.4889 0.328 0.360 0.004 0.000 0.636
#> SRR1947564 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947563 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947562 4 0.6338 0.704 0.000 0.236 0.120 0.644
#> SRR1947565 3 0.7790 0.221 0.236 0.008 0.492 0.264
#> SRR1947559 2 0.4797 0.563 0.000 0.720 0.020 0.260
#> SRR1947560 3 0.2197 0.804 0.000 0.080 0.916 0.004
#> SRR1947561 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947558 3 0.2565 0.859 0.000 0.032 0.912 0.056
#> SRR1947556 4 0.5028 0.265 0.400 0.004 0.000 0.596
#> SRR1947553 4 0.3708 0.758 0.000 0.148 0.020 0.832
#> SRR1947554 1 0.3123 0.748 0.844 0.000 0.000 0.156
#> SRR1947555 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947550 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947552 4 0.5694 0.799 0.008 0.140 0.116 0.736
#> SRR1947549 3 0.2457 0.856 0.004 0.008 0.912 0.076
#> SRR1947551 3 0.0804 0.834 0.000 0.012 0.980 0.008
#> SRR1947548 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947506 1 0.3626 0.762 0.812 0.000 0.004 0.184
#> SRR1947507 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947504 4 0.5016 0.274 0.396 0.004 0.000 0.600
#> SRR1947503 1 0.4673 0.627 0.700 0.008 0.000 0.292
#> SRR1947502 2 0.0000 0.904 0.000 1.000 0.000 0.000
#> SRR1947501 2 0.2489 0.848 0.000 0.912 0.020 0.068
#> SRR1947499 1 0.3402 0.762 0.832 0.000 0.004 0.164
#> SRR1947498 3 0.2311 0.857 0.004 0.004 0.916 0.076
#> SRR1947508 1 0.6274 0.638 0.664 0.000 0.152 0.184
#> SRR1947505 4 0.5522 0.801 0.000 0.148 0.120 0.732
#> SRR1947497 2 0.0592 0.900 0.000 0.984 0.000 0.016
#> SRR1947496 1 0.0469 0.783 0.988 0.000 0.000 0.012
#> SRR1947495 2 0.0592 0.900 0.000 0.984 0.000 0.016
#> SRR1947494 4 0.5602 0.801 0.004 0.144 0.116 0.736
#> SRR1947493 1 0.3626 0.762 0.812 0.000 0.004 0.184
#> SRR1947492 1 0.1022 0.781 0.968 0.000 0.000 0.032
#> SRR1947500 4 0.5470 0.802 0.000 0.148 0.116 0.736
#> SRR1947491 4 0.6837 0.572 0.000 0.340 0.116 0.544
#> SRR1947490 1 0.2704 0.757 0.876 0.000 0.000 0.124
#> SRR1947489 1 0.4973 0.575 0.644 0.000 0.008 0.348
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
#> SRR1947546 2 0.2011 0.8674 0.000 0.908 0.004 0.088 0.000
#> SRR1947545 1 0.2471 0.4475 0.864 0.000 0.000 0.000 0.136
#> SRR1947544 4 0.4074 0.2330 0.364 0.000 0.000 0.636 0.000
#> SRR1947542 2 0.2011 0.8674 0.000 0.908 0.004 0.088 0.000
#> SRR1947541 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
#> SRR1947540 4 0.4273 0.2688 0.000 0.448 0.000 0.552 0.000
#> SRR1947539 3 0.1630 0.7928 0.000 0.004 0.944 0.036 0.016
#> SRR1947538 4 0.2068 0.7247 0.000 0.092 0.004 0.904 0.000
#> SRR1947537 3 0.6393 0.2485 0.180 0.004 0.524 0.292 0.000
#> SRR1947536 5 0.5956 0.6208 0.196 0.000 0.212 0.000 0.592
#> SRR1947535 3 0.1830 0.7918 0.000 0.028 0.932 0.040 0.000
#> SRR1947534 1 0.6335 0.2118 0.520 0.204 0.000 0.276 0.000
#> SRR1947533 2 0.0609 0.9214 0.000 0.980 0.000 0.020 0.000
#> SRR1947532 4 0.3970 0.7689 0.000 0.096 0.104 0.800 0.000
#> SRR1947531 4 0.4273 0.2688 0.000 0.448 0.000 0.552 0.000
#> SRR1947530 5 0.5166 0.6115 0.368 0.000 0.028 0.012 0.592
#> SRR1947529 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947528 1 0.7627 0.0361 0.356 0.000 0.044 0.304 0.296
#> SRR1947527 2 0.3242 0.6808 0.000 0.784 0.000 0.216 0.000
#> SRR1947526 2 0.0566 0.9237 0.000 0.984 0.000 0.012 0.004
#> SRR1947525 4 0.3601 0.5650 0.052 0.128 0.000 0.820 0.000
#> SRR1947524 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947523 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947521 3 0.4557 0.5537 0.000 0.000 0.584 0.012 0.404
#> SRR1947520 2 0.1200 0.9058 0.000 0.964 0.016 0.012 0.008
#> SRR1947519 3 0.1830 0.7918 0.000 0.028 0.932 0.040 0.000
#> SRR1947518 4 0.2068 0.7247 0.000 0.092 0.004 0.904 0.000
#> SRR1947517 5 0.4138 0.4324 0.072 0.000 0.148 0.000 0.780
#> SRR1947516 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.3970 0.7689 0.000 0.096 0.104 0.800 0.000
#> SRR1947514 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 4 0.6993 -0.2335 0.408 0.036 0.000 0.416 0.140
#> SRR1947512 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1074 0.9084 0.000 0.968 0.016 0.012 0.004
#> SRR1947510 3 0.4557 0.5537 0.000 0.000 0.584 0.012 0.404
#> SRR1947572 4 0.3949 0.2780 0.332 0.000 0.000 0.668 0.000
#> SRR1947611 3 0.4696 0.5539 0.000 0.004 0.584 0.012 0.400
#> SRR1947509 5 0.4138 0.4324 0.072 0.000 0.148 0.000 0.780
#> SRR1947644 3 0.3715 0.6616 0.000 0.000 0.736 0.004 0.260
#> SRR1947643 2 0.0865 0.9204 0.000 0.972 0.000 0.024 0.004
#> SRR1947642 3 0.1364 0.7936 0.000 0.012 0.952 0.036 0.000
#> SRR1947640 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947641 3 0.1750 0.7925 0.000 0.028 0.936 0.036 0.000
#> SRR1947639 4 0.2971 0.5185 0.156 0.008 0.000 0.836 0.000
#> SRR1947638 1 0.6017 0.3710 0.580 0.008 0.000 0.292 0.120
#> SRR1947637 3 0.4696 0.5539 0.000 0.004 0.584 0.012 0.400
#> SRR1947636 3 0.6393 0.2485 0.180 0.004 0.524 0.292 0.000
#> SRR1947635 4 0.5570 0.6136 0.000 0.288 0.104 0.608 0.000
#> SRR1947634 2 0.5236 0.6848 0.000 0.724 0.108 0.024 0.144
#> SRR1947633 3 0.1630 0.7928 0.000 0.004 0.944 0.036 0.016
#> SRR1947632 2 0.2011 0.8674 0.000 0.908 0.004 0.088 0.000
#> SRR1947631 3 0.1750 0.7925 0.000 0.028 0.936 0.036 0.000
#> SRR1947629 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947630 2 0.4999 0.6851 0.000 0.732 0.108 0.012 0.148
#> SRR1947627 5 0.5958 0.6274 0.204 0.000 0.204 0.000 0.592
#> SRR1947628 4 0.4020 0.7679 0.000 0.096 0.108 0.796 0.000
#> SRR1947626 2 0.1043 0.9128 0.000 0.960 0.000 0.040 0.000
#> SRR1947625 3 0.1750 0.7925 0.000 0.028 0.936 0.036 0.000
#> SRR1947624 2 0.4999 0.6851 0.000 0.732 0.108 0.012 0.148
#> SRR1947623 4 0.3966 0.2709 0.336 0.000 0.000 0.664 0.000
#> SRR1947622 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947621 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.5490 0.3908 0.652 0.000 0.000 0.200 0.148
#> SRR1947619 3 0.3795 0.6117 0.024 0.004 0.788 0.184 0.000
#> SRR1947617 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.5490 0.3908 0.652 0.000 0.000 0.200 0.148
#> SRR1947616 2 0.0162 0.9249 0.000 0.996 0.000 0.000 0.004
#> SRR1947615 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
#> SRR1947614 3 0.4557 0.5537 0.000 0.000 0.584 0.012 0.404
#> SRR1947613 1 0.0794 0.5398 0.972 0.000 0.000 0.028 0.000
#> SRR1947610 4 0.2068 0.7247 0.000 0.092 0.004 0.904 0.000
#> SRR1947612 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947608 3 0.1830 0.7918 0.000 0.028 0.932 0.040 0.000
#> SRR1947606 1 0.8410 -0.0369 0.308 0.000 0.232 0.304 0.156
#> SRR1947607 1 0.2605 0.5096 0.852 0.000 0.000 0.148 0.000
#> SRR1947604 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947605 1 0.2471 0.4475 0.864 0.000 0.000 0.000 0.136
#> SRR1947603 2 0.0162 0.9257 0.000 0.996 0.000 0.004 0.000
#> SRR1947602 5 0.5166 0.6115 0.368 0.000 0.028 0.012 0.592
#> SRR1947600 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947601 2 0.0324 0.9228 0.000 0.992 0.000 0.004 0.004
#> SRR1947598 4 0.4020 0.7679 0.000 0.096 0.108 0.796 0.000
#> SRR1947599 4 0.4018 0.7658 0.004 0.088 0.104 0.804 0.000
#> SRR1947597 2 0.3838 0.5713 0.000 0.716 0.004 0.280 0.000
#> SRR1947596 4 0.4074 0.2330 0.364 0.000 0.000 0.636 0.000
#> SRR1947595 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947594 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.1124 0.7925 0.000 0.004 0.960 0.036 0.000
#> SRR1947591 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.4074 0.2330 0.364 0.000 0.000 0.636 0.000
#> SRR1947588 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
#> SRR1947586 2 0.1043 0.9128 0.000 0.960 0.000 0.040 0.000
#> SRR1947585 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947584 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947582 1 0.5490 0.3908 0.652 0.000 0.000 0.200 0.148
#> SRR1947580 2 0.1205 0.9137 0.000 0.956 0.000 0.040 0.004
#> SRR1947581 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.4696 0.5539 0.000 0.004 0.584 0.012 0.400
#> SRR1947575 3 0.1830 0.7918 0.000 0.028 0.932 0.040 0.000
#> SRR1947579 3 0.4557 0.5537 0.000 0.000 0.584 0.012 0.404
#> SRR1947578 4 0.4020 0.7679 0.000 0.096 0.108 0.796 0.000
#> SRR1947573 3 0.1124 0.7925 0.000 0.004 0.960 0.036 0.000
#> SRR1947574 4 0.5251 0.5800 0.124 0.080 0.000 0.740 0.056
#> SRR1947571 4 0.3970 0.7689 0.000 0.096 0.104 0.800 0.000
#> SRR1947577 1 0.5490 0.3908 0.652 0.000 0.000 0.200 0.148
#> SRR1947570 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
#> SRR1947569 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947566 2 0.0162 0.9249 0.000 0.996 0.000 0.000 0.004
#> SRR1947567 4 0.5570 0.6136 0.000 0.288 0.104 0.608 0.000
#> SRR1947568 4 0.3876 0.3027 0.316 0.000 0.000 0.684 0.000
#> SRR1947564 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 3 0.1830 0.7918 0.000 0.028 0.932 0.040 0.000
#> SRR1947562 4 0.4948 0.7027 0.000 0.184 0.108 0.708 0.000
#> SRR1947565 3 0.6393 0.2485 0.180 0.004 0.524 0.292 0.000
#> SRR1947559 2 0.3838 0.5713 0.000 0.716 0.004 0.280 0.000
#> SRR1947560 3 0.4696 0.5539 0.000 0.004 0.584 0.012 0.400
#> SRR1947561 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.1750 0.7925 0.000 0.028 0.936 0.036 0.000
#> SRR1947556 4 0.4074 0.2330 0.364 0.000 0.000 0.636 0.000
#> SRR1947553 4 0.2068 0.7247 0.000 0.092 0.004 0.904 0.000
#> SRR1947554 1 0.2648 0.5085 0.848 0.000 0.000 0.152 0.000
#> SRR1947555 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947550 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947552 4 0.4018 0.7658 0.004 0.088 0.104 0.804 0.000
#> SRR1947549 3 0.1124 0.7925 0.000 0.004 0.960 0.036 0.000
#> SRR1947551 3 0.3715 0.6616 0.000 0.000 0.736 0.004 0.260
#> SRR1947548 4 0.3970 0.7689 0.000 0.096 0.104 0.800 0.000
#> SRR1947506 5 0.5599 0.5749 0.376 0.000 0.028 0.032 0.564
#> SRR1947507 1 0.0000 0.5375 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.4045 0.2401 0.356 0.000 0.000 0.644 0.000
#> SRR1947503 1 0.6017 0.3710 0.580 0.008 0.000 0.292 0.120
#> SRR1947502 2 0.0000 0.9265 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 2 0.2011 0.8674 0.000 0.908 0.004 0.088 0.000
#> SRR1947499 5 0.5166 0.6115 0.368 0.000 0.028 0.012 0.592
#> SRR1947498 3 0.0963 0.7926 0.000 0.000 0.964 0.036 0.000
#> SRR1947508 5 0.5958 0.6274 0.204 0.000 0.204 0.000 0.592
#> SRR1947505 4 0.4020 0.7679 0.000 0.096 0.108 0.796 0.000
#> SRR1947497 2 0.0794 0.9197 0.000 0.972 0.000 0.028 0.000
#> SRR1947496 1 0.0162 0.5368 0.996 0.000 0.000 0.004 0.000
#> SRR1947495 2 0.0794 0.9197 0.000 0.972 0.000 0.028 0.000
#> SRR1947494 4 0.3916 0.7677 0.000 0.092 0.104 0.804 0.000
#> SRR1947493 5 0.5599 0.5749 0.376 0.000 0.028 0.032 0.564
#> SRR1947492 1 0.0794 0.5398 0.972 0.000 0.000 0.028 0.000
#> SRR1947500 4 0.3970 0.7691 0.000 0.096 0.104 0.800 0.000
#> SRR1947491 4 0.5570 0.6136 0.000 0.288 0.104 0.608 0.000
#> SRR1947490 1 0.2280 0.5130 0.880 0.000 0.000 0.120 0.000
#> SRR1947489 1 0.7577 0.0435 0.356 0.000 0.040 0.308 0.296
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
#> SRR1947546 2 0.3627 0.801 0.000 0.808 0.052 0.128 0.008 0.004
#> SRR1947545 1 0.2941 0.627 0.780 0.000 0.000 0.000 0.000 0.220
#> SRR1947544 4 0.5239 0.285 0.320 0.000 0.000 0.580 0.008 0.092
#> SRR1947542 2 0.3627 0.801 0.000 0.808 0.052 0.128 0.008 0.004
#> SRR1947541 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
#> SRR1947540 4 0.4691 0.304 0.000 0.356 0.028 0.600 0.016 0.000
#> SRR1947539 3 0.1088 0.838 0.000 0.000 0.960 0.000 0.016 0.024
#> SRR1947538 4 0.1657 0.716 0.000 0.012 0.040 0.936 0.012 0.000
#> SRR1947537 3 0.6327 0.228 0.044 0.000 0.528 0.200 0.000 0.228
#> SRR1947536 6 0.5101 0.519 0.020 0.000 0.188 0.000 0.120 0.672
#> SRR1947535 3 0.0146 0.840 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947534 1 0.6404 0.307 0.520 0.044 0.000 0.312 0.108 0.016
#> SRR1947533 2 0.3664 0.821 0.000 0.804 0.000 0.080 0.108 0.008
#> SRR1947532 4 0.2996 0.756 0.000 0.016 0.144 0.832 0.008 0.000
#> SRR1947531 4 0.4691 0.304 0.000 0.356 0.028 0.600 0.016 0.000
#> SRR1947530 6 0.3579 0.649 0.072 0.000 0.004 0.000 0.120 0.804
#> SRR1947529 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947528 6 0.4696 0.705 0.048 0.000 0.036 0.212 0.000 0.704
#> SRR1947527 2 0.5246 0.555 0.000 0.604 0.000 0.280 0.108 0.008
#> SRR1947526 2 0.1409 0.866 0.000 0.948 0.000 0.032 0.012 0.008
#> SRR1947525 4 0.4470 0.519 0.016 0.120 0.004 0.764 0.008 0.088
#> SRR1947524 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947523 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947521 5 0.3240 0.854 0.000 0.000 0.244 0.000 0.752 0.004
#> SRR1947520 2 0.1633 0.838 0.000 0.932 0.000 0.000 0.024 0.044
#> SRR1947519 3 0.0146 0.840 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947518 4 0.1657 0.716 0.000 0.012 0.040 0.936 0.012 0.000
#> SRR1947517 5 0.3765 0.213 0.000 0.000 0.000 0.000 0.596 0.404
#> SRR1947516 2 0.0622 0.869 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947515 4 0.2996 0.756 0.000 0.016 0.144 0.832 0.008 0.000
#> SRR1947514 2 0.0622 0.869 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947513 4 0.6127 -0.180 0.328 0.008 0.000 0.444 0.000 0.220
#> SRR1947512 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1321 0.850 0.000 0.952 0.000 0.004 0.024 0.020
#> SRR1947510 5 0.3240 0.854 0.000 0.000 0.244 0.000 0.752 0.004
#> SRR1947572 4 0.5201 0.315 0.288 0.000 0.000 0.604 0.008 0.100
#> SRR1947611 5 0.3349 0.854 0.000 0.008 0.244 0.000 0.748 0.000
#> SRR1947509 5 0.3765 0.213 0.000 0.000 0.000 0.000 0.596 0.404
#> SRR1947644 3 0.3868 -0.310 0.000 0.000 0.504 0.000 0.496 0.000
#> SRR1947643 2 0.3905 0.814 0.000 0.792 0.004 0.088 0.108 0.008
#> SRR1947642 3 0.0458 0.845 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947640 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947641 3 0.0000 0.842 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 4 0.3904 0.509 0.112 0.000 0.000 0.784 0.008 0.096
#> SRR1947638 1 0.5731 0.478 0.508 0.000 0.000 0.288 0.000 0.204
#> SRR1947637 5 0.3349 0.854 0.000 0.008 0.244 0.000 0.748 0.000
#> SRR1947636 3 0.6327 0.228 0.044 0.000 0.528 0.200 0.000 0.228
#> SRR1947635 4 0.4949 0.608 0.000 0.208 0.144 0.648 0.000 0.000
#> SRR1947634 2 0.4035 0.613 0.000 0.712 0.000 0.016 0.256 0.016
#> SRR1947633 3 0.1492 0.821 0.000 0.000 0.940 0.000 0.036 0.024
#> SRR1947632 2 0.3627 0.801 0.000 0.808 0.052 0.128 0.008 0.004
#> SRR1947631 3 0.0000 0.842 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947630 2 0.4107 0.586 0.000 0.700 0.000 0.000 0.256 0.044
#> SRR1947627 6 0.5043 0.527 0.020 0.000 0.180 0.000 0.120 0.680
#> SRR1947628 4 0.3035 0.755 0.000 0.016 0.148 0.828 0.008 0.000
#> SRR1947626 2 0.3932 0.804 0.000 0.776 0.004 0.112 0.108 0.000
#> SRR1947625 3 0.0000 0.842 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.4107 0.586 0.000 0.700 0.000 0.000 0.256 0.044
#> SRR1947623 4 0.5217 0.308 0.292 0.000 0.000 0.600 0.008 0.100
#> SRR1947622 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947621 2 0.0622 0.869 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947620 1 0.5497 0.529 0.564 0.000 0.000 0.196 0.000 0.240
#> SRR1947619 3 0.3644 0.646 0.000 0.000 0.792 0.120 0.000 0.088
#> SRR1947617 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947618 1 0.5497 0.529 0.564 0.000 0.000 0.196 0.000 0.240
#> SRR1947616 2 0.0520 0.867 0.000 0.984 0.000 0.008 0.000 0.008
#> SRR1947615 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
#> SRR1947614 5 0.3240 0.854 0.000 0.000 0.244 0.000 0.752 0.004
#> SRR1947613 1 0.0777 0.767 0.972 0.000 0.000 0.024 0.000 0.004
#> SRR1947610 4 0.1657 0.716 0.000 0.012 0.040 0.936 0.012 0.000
#> SRR1947612 2 0.0622 0.869 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947609 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947608 3 0.0146 0.840 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947606 6 0.6425 0.535 0.048 0.000 0.224 0.212 0.000 0.516
#> SRR1947607 1 0.2623 0.716 0.852 0.000 0.000 0.132 0.000 0.016
#> SRR1947604 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947605 1 0.2941 0.627 0.780 0.000 0.000 0.000 0.000 0.220
#> SRR1947603 2 0.1138 0.863 0.000 0.960 0.024 0.012 0.000 0.004
#> SRR1947602 6 0.3579 0.649 0.072 0.000 0.004 0.000 0.120 0.804
#> SRR1947600 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947601 2 0.1152 0.856 0.000 0.952 0.000 0.004 0.000 0.044
#> SRR1947598 4 0.3035 0.755 0.000 0.016 0.148 0.828 0.008 0.000
#> SRR1947599 4 0.2996 0.754 0.000 0.016 0.144 0.832 0.000 0.008
#> SRR1947597 2 0.4406 0.527 0.000 0.640 0.028 0.324 0.008 0.000
#> SRR1947596 4 0.5239 0.285 0.320 0.000 0.000 0.580 0.008 0.092
#> SRR1947595 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947594 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0632 0.844 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1947591 2 0.0622 0.869 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947590 4 0.5239 0.285 0.320 0.000 0.000 0.580 0.008 0.092
#> SRR1947588 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
#> SRR1947586 2 0.3932 0.804 0.000 0.776 0.004 0.112 0.108 0.000
#> SRR1947585 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947584 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947582 1 0.5497 0.529 0.564 0.000 0.000 0.196 0.000 0.240
#> SRR1947580 2 0.4137 0.802 0.000 0.772 0.004 0.108 0.108 0.008
#> SRR1947581 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.3349 0.854 0.000 0.008 0.244 0.000 0.748 0.000
#> SRR1947575 3 0.0146 0.840 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947579 5 0.3240 0.854 0.000 0.000 0.244 0.000 0.752 0.004
#> SRR1947578 4 0.3035 0.755 0.000 0.016 0.148 0.828 0.008 0.000
#> SRR1947573 3 0.0632 0.844 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1947574 4 0.4581 0.590 0.056 0.012 0.036 0.756 0.000 0.140
#> SRR1947571 4 0.2996 0.756 0.000 0.016 0.144 0.832 0.008 0.000
#> SRR1947577 1 0.5497 0.529 0.564 0.000 0.000 0.196 0.000 0.240
#> SRR1947570 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
#> SRR1947569 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947566 2 0.0520 0.867 0.000 0.984 0.000 0.008 0.000 0.008
#> SRR1947567 4 0.4949 0.608 0.000 0.208 0.144 0.648 0.000 0.000
#> SRR1947568 4 0.5131 0.335 0.272 0.000 0.000 0.620 0.008 0.100
#> SRR1947564 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947563 3 0.0146 0.840 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947562 4 0.4315 0.694 0.000 0.104 0.144 0.744 0.008 0.000
#> SRR1947565 3 0.6327 0.228 0.044 0.000 0.528 0.200 0.000 0.228
#> SRR1947559 2 0.4406 0.527 0.000 0.640 0.028 0.324 0.008 0.000
#> SRR1947560 5 0.3349 0.854 0.000 0.008 0.244 0.000 0.748 0.000
#> SRR1947561 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947557 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.842 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 4 0.5239 0.285 0.320 0.000 0.000 0.580 0.008 0.092
#> SRR1947553 4 0.1657 0.716 0.000 0.012 0.040 0.936 0.012 0.000
#> SRR1947554 1 0.2664 0.714 0.848 0.000 0.000 0.136 0.000 0.016
#> SRR1947555 2 0.0993 0.864 0.000 0.964 0.024 0.012 0.000 0.000
#> SRR1947550 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947552 4 0.2996 0.754 0.000 0.016 0.144 0.832 0.000 0.008
#> SRR1947549 3 0.0632 0.844 0.000 0.000 0.976 0.000 0.000 0.024
#> SRR1947551 3 0.3868 -0.310 0.000 0.000 0.504 0.000 0.496 0.000
#> SRR1947548 4 0.2996 0.756 0.000 0.016 0.144 0.832 0.008 0.000
#> SRR1947506 6 0.3564 0.665 0.084 0.000 0.004 0.012 0.076 0.824
#> SRR1947507 1 0.0000 0.768 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.5292 0.283 0.312 0.000 0.000 0.580 0.008 0.100
#> SRR1947503 1 0.5731 0.478 0.508 0.000 0.000 0.288 0.000 0.204
#> SRR1947502 2 0.0363 0.869 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947501 2 0.3627 0.801 0.000 0.808 0.052 0.128 0.008 0.004
#> SRR1947499 6 0.3579 0.649 0.072 0.000 0.004 0.000 0.120 0.804
#> SRR1947498 3 0.0777 0.844 0.000 0.000 0.972 0.000 0.004 0.024
#> SRR1947508 6 0.5043 0.527 0.020 0.000 0.180 0.000 0.120 0.680
#> SRR1947505 4 0.3035 0.755 0.000 0.016 0.148 0.828 0.008 0.000
#> SRR1947497 2 0.3764 0.817 0.000 0.796 0.000 0.088 0.108 0.008
#> SRR1947496 1 0.0146 0.767 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947495 2 0.3764 0.817 0.000 0.796 0.000 0.088 0.108 0.008
#> SRR1947494 4 0.3138 0.756 0.000 0.016 0.144 0.828 0.008 0.004
#> SRR1947493 6 0.3564 0.665 0.084 0.000 0.004 0.012 0.076 0.824
#> SRR1947492 1 0.0777 0.767 0.972 0.000 0.000 0.024 0.000 0.004
#> SRR1947500 4 0.2744 0.757 0.000 0.016 0.144 0.840 0.000 0.000
#> SRR1947491 4 0.4949 0.608 0.000 0.208 0.144 0.648 0.000 0.000
#> SRR1947490 1 0.2146 0.724 0.880 0.000 0.000 0.116 0.000 0.004
#> SRR1947489 6 0.4594 0.707 0.044 0.000 0.032 0.216 0.000 0.708
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 15148 rows and 152 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 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 0.317 0.733 0.828 0.4534 0.565 0.565
#> 3 3 0.963 0.940 0.969 0.4389 0.715 0.525
#> 4 4 0.694 0.793 0.813 0.1150 0.863 0.631
#> 5 5 0.756 0.796 0.842 0.0738 0.946 0.795
#> 6 6 0.767 0.757 0.800 0.0440 0.952 0.788
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
#> SRR1947547 1 0.0376 0.7213 0.996 0.004
#> SRR1947546 2 0.0000 0.7978 0.000 1.000
#> SRR1947545 1 0.8016 0.8433 0.756 0.244
#> SRR1947544 1 0.8016 0.8433 0.756 0.244
#> SRR1947542 2 0.0000 0.7978 0.000 1.000
#> SRR1947541 1 0.4939 0.6344 0.892 0.108
#> SRR1947540 2 0.0000 0.7978 0.000 1.000
#> SRR1947539 2 0.9460 0.6494 0.364 0.636
#> SRR1947538 2 0.6438 0.6800 0.164 0.836
#> SRR1947537 2 0.9460 0.6494 0.364 0.636
#> SRR1947536 1 0.4939 0.6344 0.892 0.108
#> SRR1947535 2 0.9209 0.6680 0.336 0.664
#> SRR1947534 1 0.8608 0.7947 0.716 0.284
#> SRR1947533 2 0.0000 0.7978 0.000 1.000
#> SRR1947532 2 0.8713 0.4734 0.292 0.708
#> SRR1947531 2 0.0000 0.7978 0.000 1.000
#> SRR1947530 1 0.0376 0.7213 0.996 0.004
#> SRR1947529 2 0.0000 0.7978 0.000 1.000
#> SRR1947528 1 0.3879 0.6655 0.924 0.076
#> SRR1947527 2 0.0000 0.7978 0.000 1.000
#> SRR1947526 2 0.0000 0.7978 0.000 1.000
#> SRR1947525 2 0.4431 0.7269 0.092 0.908
#> SRR1947524 2 0.9460 0.6494 0.364 0.636
#> SRR1947523 2 0.3114 0.7733 0.056 0.944
#> SRR1947521 2 0.9460 0.6494 0.364 0.636
#> SRR1947520 2 0.0000 0.7978 0.000 1.000
#> SRR1947519 2 0.9427 0.6527 0.360 0.640
#> SRR1947518 2 0.6973 0.6491 0.188 0.812
#> SRR1947517 2 0.9998 0.4296 0.492 0.508
#> SRR1947516 2 0.0000 0.7978 0.000 1.000
#> SRR1947515 2 0.7674 0.6152 0.224 0.776
#> SRR1947514 2 0.0000 0.7978 0.000 1.000
#> SRR1947513 1 0.8016 0.8433 0.756 0.244
#> SRR1947512 1 0.8016 0.8433 0.756 0.244
#> SRR1947511 2 0.0000 0.7978 0.000 1.000
#> SRR1947510 2 0.8713 0.6848 0.292 0.708
#> SRR1947572 2 0.9732 0.0731 0.404 0.596
#> SRR1947611 2 0.8016 0.6975 0.244 0.756
#> SRR1947509 1 0.4939 0.6344 0.892 0.108
#> SRR1947644 2 0.9460 0.6494 0.364 0.636
#> SRR1947643 2 0.0000 0.7978 0.000 1.000
#> SRR1947642 2 0.9427 0.6527 0.360 0.640
#> SRR1947640 2 0.6438 0.6761 0.164 0.836
#> SRR1947641 2 0.8661 0.6867 0.288 0.712
#> SRR1947639 2 0.4815 0.7144 0.104 0.896
#> SRR1947638 1 0.8016 0.8433 0.756 0.244
#> SRR1947637 2 0.8016 0.6975 0.244 0.756
#> SRR1947636 2 0.9460 0.6494 0.364 0.636
#> SRR1947635 2 0.0000 0.7978 0.000 1.000
#> SRR1947634 2 0.0000 0.7978 0.000 1.000
#> SRR1947633 2 0.9460 0.6494 0.364 0.636
#> SRR1947632 2 0.0376 0.7974 0.004 0.996
#> SRR1947631 2 0.9427 0.6527 0.360 0.640
#> SRR1947629 2 0.9393 0.6549 0.356 0.644
#> SRR1947630 2 0.0000 0.7978 0.000 1.000
#> SRR1947627 1 0.4939 0.6344 0.892 0.108
#> SRR1947628 2 0.0000 0.7978 0.000 1.000
#> SRR1947626 2 0.0000 0.7978 0.000 1.000
#> SRR1947625 2 0.8661 0.6867 0.288 0.712
#> SRR1947624 2 0.0376 0.7974 0.004 0.996
#> SRR1947623 1 0.8016 0.8433 0.756 0.244
#> SRR1947622 2 0.0000 0.7978 0.000 1.000
#> SRR1947621 2 0.0000 0.7978 0.000 1.000
#> SRR1947620 1 0.8016 0.8433 0.756 0.244
#> SRR1947619 2 0.9460 0.6494 0.364 0.636
#> SRR1947617 2 0.0000 0.7978 0.000 1.000
#> SRR1947618 1 0.8016 0.8433 0.756 0.244
#> SRR1947616 2 0.0376 0.7974 0.004 0.996
#> SRR1947615 1 0.4690 0.6565 0.900 0.100
#> SRR1947614 2 0.9460 0.6494 0.364 0.636
#> SRR1947613 1 0.8016 0.8433 0.756 0.244
#> SRR1947610 2 0.4562 0.7229 0.096 0.904
#> SRR1947612 2 0.0000 0.7978 0.000 1.000
#> SRR1947609 1 0.8016 0.8433 0.756 0.244
#> SRR1947608 2 0.8608 0.6878 0.284 0.716
#> SRR1947606 1 0.4815 0.6388 0.896 0.104
#> SRR1947607 1 0.8016 0.8433 0.756 0.244
#> SRR1947604 2 0.9286 0.3155 0.344 0.656
#> SRR1947605 1 0.8016 0.8433 0.756 0.244
#> SRR1947603 2 0.0376 0.7974 0.004 0.996
#> SRR1947602 1 0.0376 0.7213 0.996 0.004
#> SRR1947600 2 0.9460 0.6494 0.364 0.636
#> SRR1947601 2 0.0376 0.7974 0.004 0.996
#> SRR1947598 2 0.6801 0.6697 0.180 0.820
#> SRR1947599 1 0.8016 0.8433 0.756 0.244
#> SRR1947597 2 0.0000 0.7978 0.000 1.000
#> SRR1947596 1 0.9460 0.6709 0.636 0.364
#> SRR1947595 2 0.0000 0.7978 0.000 1.000
#> SRR1947594 1 0.8016 0.8433 0.756 0.244
#> SRR1947592 2 0.9460 0.6494 0.364 0.636
#> SRR1947591 2 0.0000 0.7978 0.000 1.000
#> SRR1947590 1 0.9710 0.5964 0.600 0.400
#> SRR1947588 1 0.8016 0.8433 0.756 0.244
#> SRR1947587 2 0.9460 0.6494 0.364 0.636
#> SRR1947586 2 0.0000 0.7978 0.000 1.000
#> SRR1947585 2 0.9460 0.6494 0.364 0.636
#> SRR1947584 1 0.8016 0.8433 0.756 0.244
#> SRR1947583 2 0.4562 0.7229 0.096 0.904
#> SRR1947582 1 0.8016 0.8433 0.756 0.244
#> SRR1947580 2 0.0000 0.7978 0.000 1.000
#> SRR1947581 1 0.8016 0.8433 0.756 0.244
#> SRR1947576 2 0.8016 0.6975 0.244 0.756
#> SRR1947575 2 0.8016 0.6975 0.244 0.756
#> SRR1947579 2 0.9460 0.6494 0.364 0.636
#> SRR1947578 2 0.0000 0.7978 0.000 1.000
#> SRR1947573 2 0.8713 0.6848 0.292 0.708
#> SRR1947574 2 0.6801 0.6614 0.180 0.820
#> SRR1947571 2 0.6048 0.6920 0.148 0.852
#> SRR1947577 1 0.8016 0.8433 0.756 0.244
#> SRR1947570 1 0.0376 0.7213 0.996 0.004
#> SRR1947569 2 0.9460 0.6494 0.364 0.636
#> SRR1947566 2 0.0376 0.7974 0.004 0.996
#> SRR1947567 2 0.0000 0.7978 0.000 1.000
#> SRR1947568 2 0.4939 0.7100 0.108 0.892
#> SRR1947564 2 0.0000 0.7978 0.000 1.000
#> SRR1947563 2 0.8267 0.6944 0.260 0.740
#> SRR1947562 2 0.4690 0.7186 0.100 0.900
#> SRR1947565 2 0.9460 0.6494 0.364 0.636
#> SRR1947559 2 0.0000 0.7978 0.000 1.000
#> SRR1947560 2 0.8016 0.6975 0.244 0.756
#> SRR1947561 2 0.0376 0.7974 0.004 0.996
#> SRR1947557 1 0.8016 0.8433 0.756 0.244
#> SRR1947558 2 0.9427 0.6527 0.360 0.640
#> SRR1947556 1 0.8016 0.8433 0.756 0.244
#> SRR1947553 2 0.3431 0.7526 0.064 0.936
#> SRR1947554 1 0.8016 0.8433 0.756 0.244
#> SRR1947555 2 0.0376 0.7974 0.004 0.996
#> SRR1947550 2 0.4690 0.7186 0.100 0.900
#> SRR1947552 1 0.9795 0.5583 0.584 0.416
#> SRR1947549 2 0.8713 0.6848 0.292 0.708
#> SRR1947551 2 0.8713 0.6848 0.292 0.708
#> SRR1947548 2 0.6438 0.6825 0.164 0.836
#> SRR1947506 1 0.0376 0.7213 0.996 0.004
#> SRR1947507 1 0.8016 0.8433 0.756 0.244
#> SRR1947504 1 0.8016 0.8433 0.756 0.244
#> SRR1947503 1 0.8016 0.8433 0.756 0.244
#> SRR1947502 2 0.0000 0.7978 0.000 1.000
#> SRR1947501 2 0.0376 0.7974 0.004 0.996
#> SRR1947499 1 0.0376 0.7213 0.996 0.004
#> SRR1947498 2 0.9460 0.6494 0.364 0.636
#> SRR1947508 1 0.5059 0.6381 0.888 0.112
#> SRR1947505 2 0.3114 0.7733 0.056 0.944
#> SRR1947497 2 0.0000 0.7978 0.000 1.000
#> SRR1947496 1 0.8016 0.8433 0.756 0.244
#> SRR1947495 2 0.0000 0.7978 0.000 1.000
#> SRR1947494 2 0.7528 0.6284 0.216 0.784
#> SRR1947493 1 0.0376 0.7213 0.996 0.004
#> SRR1947492 1 0.8016 0.8433 0.756 0.244
#> SRR1947500 2 0.3584 0.7492 0.068 0.932
#> SRR1947491 2 0.6048 0.6939 0.148 0.852
#> SRR1947490 1 0.8016 0.8433 0.756 0.244
#> SRR1947489 1 0.0376 0.7213 0.996 0.004
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.6309 -0.0211 0.500 0.000 0.500
#> SRR1947546 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947545 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947544 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947542 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947541 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947540 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947539 3 0.0424 0.9787 0.008 0.000 0.992
#> SRR1947538 2 0.2860 0.9094 0.084 0.912 0.004
#> SRR1947537 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947536 3 0.2356 0.9186 0.072 0.000 0.928
#> SRR1947535 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947534 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947533 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947532 2 0.4629 0.7962 0.188 0.808 0.004
#> SRR1947531 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947530 1 0.0592 0.9660 0.988 0.000 0.012
#> SRR1947529 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947528 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947527 2 0.0237 0.9608 0.004 0.996 0.000
#> SRR1947526 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947525 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947524 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947523 2 0.1399 0.9486 0.028 0.968 0.004
#> SRR1947521 3 0.0661 0.9774 0.008 0.004 0.988
#> SRR1947520 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947518 2 0.4629 0.7961 0.188 0.808 0.004
#> SRR1947517 3 0.0661 0.9774 0.008 0.004 0.988
#> SRR1947516 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947515 2 0.4629 0.7961 0.188 0.808 0.004
#> SRR1947514 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947513 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947512 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947511 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947510 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947572 2 0.6192 0.3435 0.420 0.580 0.000
#> SRR1947611 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947509 3 0.2772 0.9163 0.080 0.004 0.916
#> SRR1947644 3 0.0661 0.9774 0.008 0.004 0.988
#> SRR1947643 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947640 2 0.2590 0.9188 0.072 0.924 0.004
#> SRR1947641 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947639 2 0.2301 0.9269 0.060 0.936 0.004
#> SRR1947638 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947637 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947636 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947635 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947634 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947633 3 0.0424 0.9787 0.008 0.000 0.992
#> SRR1947632 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947631 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947630 2 0.0424 0.9559 0.008 0.992 0.000
#> SRR1947627 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947628 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947626 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947625 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947624 2 0.0424 0.9559 0.008 0.992 0.000
#> SRR1947623 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947622 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947621 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947620 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947619 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947618 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947616 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947615 3 0.4796 0.7075 0.220 0.000 0.780
#> SRR1947614 3 0.0661 0.9774 0.008 0.004 0.988
#> SRR1947613 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947610 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947612 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947609 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947608 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947606 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947607 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947604 2 0.4682 0.7907 0.192 0.804 0.004
#> SRR1947605 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947603 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947602 1 0.0592 0.9660 0.988 0.000 0.012
#> SRR1947600 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947598 2 0.2772 0.9126 0.080 0.916 0.004
#> SRR1947599 1 0.0661 0.9687 0.988 0.008 0.004
#> SRR1947597 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947596 1 0.4178 0.7781 0.828 0.172 0.000
#> SRR1947595 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947594 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947592 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947590 1 0.4178 0.7781 0.828 0.172 0.000
#> SRR1947588 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947587 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947586 2 0.0237 0.9608 0.004 0.996 0.000
#> SRR1947585 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947584 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947583 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947582 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947580 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947581 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947576 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947575 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947579 3 0.0661 0.9774 0.008 0.004 0.988
#> SRR1947578 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947573 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947574 2 0.2860 0.9094 0.084 0.912 0.004
#> SRR1947571 2 0.2860 0.9094 0.084 0.912 0.004
#> SRR1947577 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947570 1 0.0592 0.9660 0.988 0.000 0.012
#> SRR1947569 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947567 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947568 2 0.3619 0.8575 0.136 0.864 0.000
#> SRR1947564 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947563 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947562 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947565 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947559 2 0.0237 0.9608 0.004 0.996 0.000
#> SRR1947560 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947561 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947557 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947558 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947556 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947553 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947554 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947555 2 0.0237 0.9587 0.004 0.996 0.000
#> SRR1947550 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947552 2 0.6264 0.4450 0.380 0.616 0.004
#> SRR1947549 3 0.0237 0.9795 0.000 0.004 0.996
#> SRR1947551 3 0.0848 0.9760 0.008 0.008 0.984
#> SRR1947548 2 0.2860 0.9094 0.084 0.912 0.004
#> SRR1947506 1 0.1031 0.9579 0.976 0.000 0.024
#> SRR1947507 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947504 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947503 1 0.0424 0.9708 0.992 0.008 0.000
#> SRR1947502 2 0.0000 0.9609 0.000 1.000 0.000
#> SRR1947501 2 0.0237 0.9607 0.000 0.996 0.004
#> SRR1947499 1 0.0592 0.9660 0.988 0.000 0.012
#> SRR1947498 3 0.0000 0.9806 0.000 0.000 1.000
#> SRR1947508 3 0.2356 0.9186 0.072 0.000 0.928
#> SRR1947505 2 0.1399 0.9486 0.028 0.968 0.004
#> SRR1947497 2 0.0237 0.9608 0.004 0.996 0.000
#> SRR1947496 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947495 2 0.0237 0.9608 0.004 0.996 0.000
#> SRR1947494 2 0.2860 0.9094 0.084 0.912 0.004
#> SRR1947493 1 0.0592 0.9660 0.988 0.000 0.012
#> SRR1947492 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947500 2 0.0475 0.9607 0.004 0.992 0.004
#> SRR1947491 2 0.1399 0.9486 0.028 0.968 0.004
#> SRR1947490 1 0.0661 0.9724 0.988 0.008 0.004
#> SRR1947489 3 0.4796 0.7075 0.220 0.000 0.780
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.5555 0.7152 0.052 0.200 0.732 0.016
#> SRR1947546 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947545 1 0.2714 0.8795 0.884 0.112 0.004 0.000
#> SRR1947544 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947541 3 0.3450 0.8123 0.000 0.156 0.836 0.008
#> SRR1947540 4 0.1474 0.6420 0.000 0.052 0.000 0.948
#> SRR1947539 3 0.3448 0.8253 0.000 0.168 0.828 0.004
#> SRR1947538 4 0.2578 0.7308 0.052 0.036 0.000 0.912
#> SRR1947537 3 0.1584 0.8698 0.000 0.036 0.952 0.012
#> SRR1947536 3 0.4855 0.7750 0.076 0.132 0.788 0.004
#> SRR1947535 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947534 1 0.2530 0.8362 0.888 0.000 0.000 0.112
#> SRR1947533 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947532 4 0.5853 0.6623 0.052 0.144 0.056 0.748
#> SRR1947531 4 0.1474 0.6420 0.000 0.052 0.000 0.948
#> SRR1947530 1 0.4217 0.8514 0.800 0.176 0.020 0.004
#> SRR1947529 2 0.4996 0.9646 0.000 0.516 0.000 0.484
#> SRR1947528 3 0.3401 0.8153 0.000 0.152 0.840 0.008
#> SRR1947527 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947526 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947525 4 0.0188 0.7146 0.000 0.004 0.000 0.996
#> SRR1947524 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947523 4 0.4912 0.6830 0.020 0.132 0.052 0.796
#> SRR1947521 3 0.4193 0.7819 0.000 0.268 0.732 0.000
#> SRR1947520 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947519 3 0.3377 0.8237 0.000 0.140 0.848 0.012
#> SRR1947518 4 0.2623 0.7285 0.064 0.028 0.000 0.908
#> SRR1947517 3 0.4193 0.7819 0.000 0.268 0.732 0.000
#> SRR1947516 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947515 4 0.5878 0.6681 0.064 0.128 0.056 0.752
#> SRR1947514 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947513 1 0.5302 0.7992 0.760 0.120 0.004 0.116
#> SRR1947512 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947510 3 0.4222 0.7813 0.000 0.272 0.728 0.000
#> SRR1947572 4 0.4420 0.6110 0.240 0.012 0.000 0.748
#> SRR1947611 3 0.4222 0.7813 0.000 0.272 0.728 0.000
#> SRR1947509 3 0.6147 0.6846 0.056 0.380 0.564 0.000
#> SRR1947644 3 0.4428 0.7806 0.000 0.276 0.720 0.004
#> SRR1947643 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947642 3 0.2542 0.8537 0.000 0.084 0.904 0.012
#> SRR1947640 4 0.2759 0.7311 0.044 0.052 0.000 0.904
#> SRR1947641 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947639 4 0.1209 0.7226 0.032 0.004 0.000 0.964
#> SRR1947638 1 0.5408 0.7904 0.752 0.120 0.004 0.124
#> SRR1947637 3 0.4222 0.7813 0.000 0.272 0.728 0.000
#> SRR1947636 3 0.1488 0.8706 0.000 0.032 0.956 0.012
#> SRR1947635 4 0.0469 0.7187 0.000 0.012 0.000 0.988
#> SRR1947634 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947633 3 0.3494 0.8237 0.000 0.172 0.824 0.004
#> SRR1947632 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947631 3 0.1584 0.8698 0.000 0.036 0.952 0.012
#> SRR1947629 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947630 2 0.4697 0.7833 0.000 0.644 0.000 0.356
#> SRR1947627 3 0.3249 0.8228 0.000 0.140 0.852 0.008
#> SRR1947628 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947626 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947625 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947624 2 0.4222 0.6541 0.000 0.728 0.000 0.272
#> SRR1947623 1 0.0336 0.9000 0.992 0.000 0.000 0.008
#> SRR1947622 4 0.0817 0.6885 0.000 0.024 0.000 0.976
#> SRR1947621 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947620 1 0.3236 0.8709 0.856 0.136 0.004 0.004
#> SRR1947619 3 0.1584 0.8698 0.000 0.036 0.952 0.012
#> SRR1947617 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947618 1 0.5406 0.8003 0.752 0.128 0.004 0.116
#> SRR1947616 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947615 3 0.6286 0.6342 0.000 0.200 0.660 0.140
#> SRR1947614 3 0.4193 0.7819 0.000 0.268 0.732 0.000
#> SRR1947613 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947612 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947609 4 0.8058 0.3483 0.264 0.144 0.052 0.540
#> SRR1947608 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947606 3 0.3249 0.8228 0.000 0.140 0.852 0.008
#> SRR1947607 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.5802 0.6709 0.064 0.128 0.052 0.756
#> SRR1947605 1 0.2466 0.8858 0.900 0.096 0.004 0.000
#> SRR1947603 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947602 1 0.5365 0.8104 0.744 0.176 0.076 0.004
#> SRR1947600 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947601 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947598 4 0.5189 0.6933 0.052 0.100 0.052 0.796
#> SRR1947599 4 0.8037 0.3582 0.260 0.144 0.052 0.544
#> SRR1947597 4 0.4746 -0.6166 0.000 0.368 0.000 0.632
#> SRR1947596 4 0.8401 0.0854 0.384 0.144 0.052 0.420
#> SRR1947595 4 0.0336 0.7203 0.000 0.008 0.000 0.992
#> SRR1947594 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947591 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947590 4 0.8765 0.0605 0.372 0.144 0.080 0.404
#> SRR1947588 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.1854 0.8669 0.000 0.048 0.940 0.012
#> SRR1947586 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947585 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947584 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.7175 0.000 0.000 0.000 1.000
#> SRR1947582 1 0.3236 0.8709 0.856 0.136 0.004 0.004
#> SRR1947580 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947581 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.4222 0.7813 0.000 0.272 0.728 0.000
#> SRR1947575 3 0.0657 0.8758 0.000 0.004 0.984 0.012
#> SRR1947579 3 0.4193 0.7819 0.000 0.268 0.732 0.000
#> SRR1947578 4 0.1474 0.6420 0.000 0.052 0.000 0.948
#> SRR1947573 3 0.0376 0.8746 0.000 0.004 0.992 0.004
#> SRR1947574 4 0.2385 0.7303 0.052 0.028 0.000 0.920
#> SRR1947571 4 0.3089 0.7294 0.052 0.044 0.008 0.896
#> SRR1947577 1 0.5406 0.8003 0.752 0.128 0.004 0.116
#> SRR1947570 1 0.7097 0.6421 0.600 0.200 0.192 0.008
#> SRR1947569 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947566 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947567 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947568 4 0.3761 0.6181 0.068 0.080 0.000 0.852
#> SRR1947564 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947563 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947562 4 0.0000 0.7175 0.000 0.000 0.000 1.000
#> SRR1947565 3 0.1388 0.8716 0.000 0.028 0.960 0.012
#> SRR1947559 4 0.2011 0.5810 0.000 0.080 0.000 0.920
#> SRR1947560 3 0.4222 0.7813 0.000 0.272 0.728 0.000
#> SRR1947561 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947557 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0469 0.8761 0.000 0.000 0.988 0.012
#> SRR1947556 1 0.0336 0.9000 0.992 0.000 0.000 0.008
#> SRR1947553 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947554 1 0.2469 0.8388 0.892 0.000 0.000 0.108
#> SRR1947555 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947550 4 0.0000 0.7175 0.000 0.000 0.000 1.000
#> SRR1947552 4 0.6675 0.6239 0.108 0.144 0.052 0.696
#> SRR1947549 3 0.0657 0.8758 0.000 0.004 0.984 0.012
#> SRR1947551 3 0.4428 0.7806 0.000 0.276 0.720 0.004
#> SRR1947548 4 0.5067 0.6971 0.052 0.092 0.052 0.804
#> SRR1947506 1 0.7256 0.5762 0.564 0.200 0.232 0.004
#> SRR1947507 1 0.0336 0.9003 0.992 0.008 0.000 0.000
#> SRR1947504 1 0.0336 0.9000 0.992 0.000 0.000 0.008
#> SRR1947503 4 0.7291 0.2124 0.340 0.144 0.004 0.512
#> SRR1947502 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947501 4 0.0336 0.7113 0.000 0.008 0.000 0.992
#> SRR1947499 1 0.5298 0.8142 0.748 0.176 0.072 0.004
#> SRR1947498 3 0.0937 0.8758 0.000 0.012 0.976 0.012
#> SRR1947508 3 0.5317 0.7239 0.052 0.200 0.740 0.008
#> SRR1947505 4 0.4696 0.6914 0.020 0.116 0.052 0.812
#> SRR1947497 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947496 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.4992 0.9781 0.000 0.524 0.000 0.476
#> SRR1947494 4 0.5630 0.6742 0.052 0.132 0.052 0.764
#> SRR1947493 1 0.3863 0.8565 0.812 0.176 0.008 0.004
#> SRR1947492 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.7175 0.000 0.000 0.000 1.000
#> SRR1947491 4 0.2973 0.7214 0.020 0.096 0.000 0.884
#> SRR1947490 1 0.0000 0.9025 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.5763 0.7105 0.024 0.200 0.724 0.052
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.6480 0.476 0.024 0.012 0.564 0.088 0.312
#> SRR1947546 4 0.3409 0.898 0.000 0.112 0.000 0.836 0.052
#> SRR1947545 1 0.4349 0.758 0.756 0.000 0.000 0.068 0.176
#> SRR1947544 1 0.0579 0.822 0.984 0.000 0.000 0.008 0.008
#> SRR1947542 4 0.3146 0.906 0.000 0.092 0.000 0.856 0.052
#> SRR1947541 3 0.5197 0.552 0.000 0.012 0.660 0.052 0.276
#> SRR1947540 4 0.3359 0.898 0.000 0.108 0.000 0.840 0.052
#> SRR1947539 3 0.3561 -0.092 0.000 0.000 0.740 0.000 0.260
#> SRR1947538 4 0.2419 0.914 0.004 0.064 0.000 0.904 0.028
#> SRR1947537 3 0.0833 0.705 0.000 0.004 0.976 0.004 0.016
#> SRR1947536 3 0.5970 0.526 0.032 0.008 0.624 0.056 0.280
#> SRR1947535 3 0.0693 0.703 0.000 0.000 0.980 0.008 0.012
#> SRR1947534 1 0.3351 0.748 0.836 0.004 0.000 0.132 0.028
#> SRR1947533 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947532 4 0.1483 0.880 0.008 0.000 0.012 0.952 0.028
#> SRR1947531 4 0.3409 0.898 0.000 0.112 0.000 0.836 0.052
#> SRR1947530 1 0.6232 0.665 0.592 0.012 0.016 0.088 0.292
#> SRR1947529 2 0.2853 0.887 0.000 0.876 0.000 0.072 0.052
#> SRR1947528 3 0.5237 0.550 0.000 0.012 0.660 0.056 0.272
#> SRR1947527 2 0.1012 0.962 0.000 0.968 0.000 0.012 0.020
#> SRR1947526 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947525 4 0.2597 0.914 0.000 0.092 0.000 0.884 0.024
#> SRR1947524 3 0.0865 0.693 0.000 0.000 0.972 0.004 0.024
#> SRR1947523 4 0.1564 0.898 0.000 0.024 0.004 0.948 0.024
#> SRR1947521 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947520 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947519 3 0.3720 0.608 0.000 0.000 0.760 0.012 0.228
#> SRR1947518 4 0.2478 0.914 0.008 0.060 0.000 0.904 0.028
#> SRR1947517 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947516 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947515 4 0.1770 0.886 0.008 0.008 0.012 0.944 0.028
#> SRR1947514 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947513 1 0.6335 0.633 0.520 0.000 0.000 0.276 0.204
#> SRR1947512 1 0.0000 0.822 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947510 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947572 4 0.4790 0.794 0.160 0.044 0.000 0.756 0.040
#> SRR1947611 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947509 5 0.3808 0.434 0.028 0.004 0.160 0.004 0.804
#> SRR1947644 5 0.4256 0.929 0.000 0.000 0.436 0.000 0.564
#> SRR1947643 2 0.1626 0.957 0.000 0.940 0.000 0.016 0.044
#> SRR1947642 3 0.2006 0.689 0.000 0.000 0.916 0.012 0.072
#> SRR1947640 4 0.1970 0.915 0.004 0.060 0.000 0.924 0.012
#> SRR1947641 3 0.0693 0.701 0.000 0.000 0.980 0.008 0.012
#> SRR1947639 4 0.2700 0.914 0.004 0.088 0.000 0.884 0.024
#> SRR1947638 1 0.6301 0.609 0.516 0.000 0.000 0.300 0.184
#> SRR1947637 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947636 3 0.0932 0.705 0.000 0.004 0.972 0.004 0.020
#> SRR1947635 4 0.3201 0.906 0.000 0.096 0.000 0.852 0.052
#> SRR1947634 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947633 3 0.3949 -0.404 0.000 0.000 0.668 0.000 0.332
#> SRR1947632 4 0.3359 0.900 0.000 0.108 0.000 0.840 0.052
#> SRR1947631 3 0.1082 0.705 0.000 0.000 0.964 0.008 0.028
#> SRR1947629 3 0.0865 0.693 0.000 0.000 0.972 0.004 0.024
#> SRR1947630 2 0.1764 0.929 0.000 0.928 0.000 0.008 0.064
#> SRR1947627 3 0.5215 0.553 0.000 0.012 0.664 0.056 0.268
#> SRR1947628 4 0.3146 0.906 0.000 0.092 0.000 0.856 0.052
#> SRR1947626 2 0.0798 0.962 0.000 0.976 0.000 0.016 0.008
#> SRR1947625 3 0.0898 0.696 0.000 0.000 0.972 0.008 0.020
#> SRR1947624 2 0.1831 0.916 0.000 0.920 0.000 0.004 0.076
#> SRR1947623 1 0.1043 0.812 0.960 0.000 0.000 0.000 0.040
#> SRR1947622 4 0.3601 0.888 0.000 0.128 0.000 0.820 0.052
#> SRR1947621 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947620 1 0.4958 0.730 0.692 0.000 0.000 0.084 0.224
#> SRR1947619 3 0.0833 0.705 0.000 0.004 0.976 0.004 0.016
#> SRR1947617 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947618 1 0.6367 0.643 0.520 0.000 0.000 0.248 0.232
#> SRR1947616 2 0.2149 0.926 0.000 0.916 0.000 0.036 0.048
#> SRR1947615 3 0.6367 0.456 0.000 0.012 0.532 0.136 0.320
#> SRR1947614 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947613 1 0.0290 0.822 0.992 0.000 0.000 0.000 0.008
#> SRR1947610 4 0.3058 0.910 0.000 0.096 0.000 0.860 0.044
#> SRR1947612 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947609 4 0.1822 0.862 0.024 0.000 0.004 0.936 0.036
#> SRR1947608 3 0.0898 0.696 0.000 0.000 0.972 0.008 0.020
#> SRR1947606 3 0.5065 0.562 0.000 0.012 0.676 0.048 0.264
#> SRR1947607 1 0.1211 0.814 0.960 0.000 0.000 0.016 0.024
#> SRR1947604 4 0.1659 0.892 0.008 0.016 0.004 0.948 0.024
#> SRR1947605 1 0.4096 0.763 0.772 0.000 0.000 0.052 0.176
#> SRR1947603 2 0.2300 0.919 0.000 0.908 0.000 0.040 0.052
#> SRR1947602 1 0.7683 0.528 0.484 0.012 0.124 0.088 0.292
#> SRR1947600 3 0.0865 0.693 0.000 0.000 0.972 0.004 0.024
#> SRR1947601 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947598 4 0.1757 0.904 0.004 0.028 0.012 0.944 0.012
#> SRR1947599 4 0.1547 0.870 0.016 0.000 0.004 0.948 0.032
#> SRR1947597 2 0.4712 0.554 0.000 0.684 0.000 0.268 0.048
#> SRR1947596 4 0.4166 0.701 0.160 0.000 0.004 0.780 0.056
#> SRR1947595 4 0.2305 0.916 0.000 0.092 0.000 0.896 0.012
#> SRR1947594 1 0.0000 0.822 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0162 0.701 0.000 0.000 0.996 0.004 0.000
#> SRR1947591 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947590 4 0.4617 0.678 0.184 0.000 0.012 0.748 0.056
#> SRR1947588 1 0.0000 0.822 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.1798 0.692 0.000 0.004 0.928 0.004 0.064
#> SRR1947586 2 0.1195 0.962 0.000 0.960 0.000 0.012 0.028
#> SRR1947585 3 0.0865 0.693 0.000 0.000 0.972 0.004 0.024
#> SRR1947584 1 0.0162 0.822 0.996 0.000 0.000 0.000 0.004
#> SRR1947583 4 0.2305 0.916 0.000 0.092 0.000 0.896 0.012
#> SRR1947582 1 0.5917 0.695 0.596 0.000 0.000 0.180 0.224
#> SRR1947580 2 0.1597 0.955 0.000 0.940 0.000 0.012 0.048
#> SRR1947581 1 0.0162 0.822 0.996 0.000 0.000 0.000 0.004
#> SRR1947576 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947575 3 0.0898 0.696 0.000 0.000 0.972 0.008 0.020
#> SRR1947579 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947578 4 0.3409 0.895 0.000 0.112 0.000 0.836 0.052
#> SRR1947573 3 0.0404 0.691 0.000 0.000 0.988 0.000 0.012
#> SRR1947574 4 0.2798 0.911 0.008 0.060 0.000 0.888 0.044
#> SRR1947571 4 0.2141 0.915 0.004 0.064 0.000 0.916 0.016
#> SRR1947577 1 0.6367 0.643 0.520 0.000 0.000 0.248 0.232
#> SRR1947570 3 0.7780 0.370 0.128 0.012 0.456 0.088 0.316
#> SRR1947569 3 0.0865 0.693 0.000 0.000 0.972 0.004 0.024
#> SRR1947566 2 0.0798 0.962 0.000 0.976 0.000 0.016 0.008
#> SRR1947567 4 0.3146 0.906 0.000 0.092 0.000 0.856 0.052
#> SRR1947568 4 0.4904 0.829 0.060 0.160 0.000 0.748 0.032
#> SRR1947564 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947563 3 0.0898 0.696 0.000 0.000 0.972 0.008 0.020
#> SRR1947562 4 0.1851 0.916 0.000 0.088 0.000 0.912 0.000
#> SRR1947565 3 0.0833 0.705 0.000 0.004 0.976 0.004 0.016
#> SRR1947559 4 0.3630 0.829 0.000 0.204 0.000 0.780 0.016
#> SRR1947560 5 0.4273 0.942 0.000 0.000 0.448 0.000 0.552
#> SRR1947561 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947557 1 0.0162 0.822 0.996 0.000 0.000 0.000 0.004
#> SRR1947558 3 0.0693 0.703 0.000 0.000 0.980 0.008 0.012
#> SRR1947556 1 0.0880 0.814 0.968 0.000 0.000 0.000 0.032
#> SRR1947553 4 0.3058 0.910 0.000 0.096 0.000 0.860 0.044
#> SRR1947554 1 0.3099 0.756 0.848 0.000 0.000 0.124 0.028
#> SRR1947555 2 0.1018 0.959 0.000 0.968 0.000 0.016 0.016
#> SRR1947550 4 0.2011 0.915 0.000 0.088 0.000 0.908 0.004
#> SRR1947552 4 0.1243 0.878 0.008 0.000 0.004 0.960 0.028
#> SRR1947549 3 0.0566 0.694 0.000 0.000 0.984 0.004 0.012
#> SRR1947551 5 0.4256 0.929 0.000 0.000 0.436 0.000 0.564
#> SRR1947548 4 0.2227 0.902 0.004 0.032 0.012 0.924 0.028
#> SRR1947506 3 0.8173 0.229 0.200 0.012 0.404 0.088 0.296
#> SRR1947507 1 0.0162 0.822 0.996 0.000 0.000 0.000 0.004
#> SRR1947504 1 0.0703 0.815 0.976 0.000 0.000 0.000 0.024
#> SRR1947503 4 0.1907 0.858 0.028 0.000 0.000 0.928 0.044
#> SRR1947502 2 0.0510 0.964 0.000 0.984 0.000 0.016 0.000
#> SRR1947501 4 0.3409 0.898 0.000 0.112 0.000 0.836 0.052
#> SRR1947499 1 0.7683 0.528 0.484 0.012 0.124 0.088 0.292
#> SRR1947498 3 0.0771 0.701 0.000 0.000 0.976 0.004 0.020
#> SRR1947508 3 0.6294 0.512 0.028 0.012 0.600 0.076 0.284
#> SRR1947505 4 0.1990 0.905 0.000 0.028 0.004 0.928 0.040
#> SRR1947497 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947496 1 0.0000 0.822 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.1195 0.961 0.000 0.960 0.000 0.012 0.028
#> SRR1947494 4 0.1770 0.886 0.008 0.008 0.012 0.944 0.028
#> SRR1947493 1 0.5873 0.676 0.608 0.012 0.004 0.084 0.292
#> SRR1947492 1 0.0290 0.822 0.992 0.000 0.000 0.000 0.008
#> SRR1947500 4 0.2305 0.916 0.000 0.092 0.000 0.896 0.012
#> SRR1947491 4 0.1522 0.910 0.000 0.044 0.000 0.944 0.012
#> SRR1947490 1 0.0290 0.822 0.992 0.000 0.000 0.000 0.008
#> SRR1947489 3 0.6346 0.455 0.000 0.012 0.532 0.132 0.324
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.4161 0.5176 0.012 0.000 0.376 0.004 0.000 0.608
#> SRR1947546 4 0.4780 0.7733 0.000 0.080 0.012 0.756 0.064 0.088
#> SRR1947545 1 0.4048 0.3515 0.644 0.000 0.000 0.004 0.012 0.340
#> SRR1947544 1 0.0964 0.8575 0.968 0.000 0.000 0.004 0.012 0.016
#> SRR1947542 4 0.3560 0.8135 0.000 0.008 0.012 0.828 0.064 0.088
#> SRR1947541 6 0.3996 0.3197 0.000 0.000 0.484 0.000 0.004 0.512
#> SRR1947540 4 0.4582 0.7898 0.000 0.024 0.012 0.756 0.084 0.124
#> SRR1947539 3 0.3426 0.4025 0.000 0.000 0.720 0.000 0.276 0.004
#> SRR1947538 4 0.2119 0.8445 0.000 0.000 0.000 0.904 0.060 0.036
#> SRR1947537 3 0.1075 0.8743 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1947536 6 0.4809 0.4329 0.016 0.000 0.408 0.000 0.028 0.548
#> SRR1947535 3 0.0777 0.8828 0.000 0.004 0.972 0.000 0.000 0.024
#> SRR1947534 1 0.4698 0.6646 0.744 0.020 0.000 0.140 0.016 0.080
#> SRR1947533 2 0.2507 0.8846 0.000 0.884 0.000 0.004 0.040 0.072
#> SRR1947532 4 0.2390 0.8397 0.000 0.000 0.000 0.888 0.056 0.056
#> SRR1947531 4 0.5003 0.7861 0.000 0.028 0.012 0.720 0.104 0.136
#> SRR1947530 6 0.5031 0.3896 0.344 0.000 0.056 0.004 0.008 0.588
#> SRR1947529 2 0.5658 0.6680 0.000 0.676 0.012 0.140 0.076 0.096
#> SRR1947528 6 0.3993 0.3522 0.000 0.000 0.476 0.000 0.004 0.520
#> SRR1947527 2 0.2585 0.8848 0.000 0.880 0.000 0.004 0.048 0.068
#> SRR1947526 2 0.2437 0.8855 0.000 0.888 0.000 0.004 0.036 0.072
#> SRR1947525 4 0.1977 0.8512 0.000 0.008 0.000 0.920 0.032 0.040
#> SRR1947524 3 0.1856 0.8611 0.000 0.000 0.920 0.000 0.048 0.032
#> SRR1947523 4 0.2655 0.8440 0.000 0.004 0.000 0.876 0.060 0.060
#> SRR1947521 5 0.3468 0.9416 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947520 2 0.2918 0.8804 0.000 0.856 0.000 0.004 0.052 0.088
#> SRR1947519 3 0.3109 0.5798 0.000 0.004 0.772 0.000 0.000 0.224
#> SRR1947518 4 0.2448 0.8418 0.000 0.000 0.000 0.884 0.064 0.052
#> SRR1947517 5 0.3468 0.9416 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947516 2 0.0363 0.8921 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947515 4 0.2134 0.8429 0.000 0.000 0.000 0.904 0.052 0.044
#> SRR1947514 2 0.0508 0.8918 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947513 6 0.6628 0.1242 0.316 0.000 0.000 0.232 0.036 0.416
#> SRR1947512 1 0.0146 0.8642 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947511 2 0.2750 0.8824 0.000 0.868 0.000 0.004 0.048 0.080
#> SRR1947510 5 0.3244 0.9402 0.000 0.000 0.268 0.000 0.732 0.000
#> SRR1947572 4 0.4322 0.7781 0.084 0.000 0.000 0.776 0.056 0.084
#> SRR1947611 5 0.3468 0.9408 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947509 5 0.4453 0.4678 0.012 0.000 0.032 0.000 0.660 0.296
#> SRR1947644 5 0.3298 0.9169 0.000 0.000 0.236 0.000 0.756 0.008
#> SRR1947643 2 0.3927 0.8601 0.000 0.780 0.000 0.008 0.084 0.128
#> SRR1947642 3 0.1700 0.8485 0.000 0.004 0.916 0.000 0.000 0.080
#> SRR1947640 4 0.1970 0.8505 0.000 0.008 0.000 0.920 0.028 0.044
#> SRR1947641 3 0.0777 0.8828 0.000 0.004 0.972 0.000 0.000 0.024
#> SRR1947639 4 0.2046 0.8513 0.000 0.008 0.000 0.916 0.032 0.044
#> SRR1947638 6 0.6791 0.0801 0.308 0.000 0.000 0.284 0.040 0.368
#> SRR1947637 5 0.3564 0.9392 0.000 0.000 0.264 0.000 0.724 0.012
#> SRR1947636 3 0.1075 0.8743 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1947635 4 0.4050 0.8167 0.000 0.016 0.012 0.796 0.072 0.104
#> SRR1947634 2 0.2750 0.8824 0.000 0.868 0.000 0.004 0.048 0.080
#> SRR1947633 3 0.3690 0.2818 0.000 0.000 0.684 0.000 0.308 0.008
#> SRR1947632 4 0.4827 0.7715 0.000 0.080 0.012 0.752 0.064 0.092
#> SRR1947631 3 0.1082 0.8798 0.000 0.004 0.956 0.000 0.000 0.040
#> SRR1947629 3 0.1856 0.8611 0.000 0.000 0.920 0.000 0.048 0.032
#> SRR1947630 2 0.2918 0.8789 0.000 0.856 0.000 0.004 0.052 0.088
#> SRR1947627 6 0.4086 0.3802 0.000 0.000 0.464 0.000 0.008 0.528
#> SRR1947628 4 0.3897 0.8084 0.000 0.008 0.012 0.800 0.068 0.112
#> SRR1947626 2 0.2291 0.8726 0.000 0.904 0.000 0.012 0.044 0.040
#> SRR1947625 3 0.0777 0.8828 0.000 0.004 0.972 0.000 0.000 0.024
#> SRR1947624 2 0.2776 0.8772 0.000 0.860 0.000 0.000 0.052 0.088
#> SRR1947623 1 0.2467 0.8190 0.884 0.000 0.000 0.012 0.016 0.088
#> SRR1947622 4 0.5212 0.7498 0.000 0.104 0.012 0.720 0.072 0.092
#> SRR1947621 2 0.0508 0.8918 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947620 1 0.5292 -0.0360 0.472 0.000 0.000 0.060 0.016 0.452
#> SRR1947619 3 0.1075 0.8743 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1947617 2 0.0508 0.8918 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947618 6 0.6428 0.1555 0.316 0.000 0.000 0.196 0.032 0.456
#> SRR1947616 2 0.5421 0.7311 0.000 0.700 0.012 0.076 0.088 0.124
#> SRR1947615 6 0.4109 0.4758 0.000 0.004 0.392 0.008 0.000 0.596
#> SRR1947614 5 0.3468 0.9416 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947613 1 0.1138 0.8582 0.960 0.000 0.000 0.004 0.012 0.024
#> SRR1947610 4 0.3731 0.8279 0.000 0.008 0.000 0.796 0.072 0.124
#> SRR1947612 2 0.0508 0.8918 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947609 4 0.3324 0.8186 0.004 0.000 0.000 0.824 0.060 0.112
#> SRR1947608 3 0.0858 0.8818 0.000 0.004 0.968 0.000 0.000 0.028
#> SRR1947606 3 0.3782 0.1897 0.000 0.000 0.636 0.000 0.004 0.360
#> SRR1947607 1 0.2123 0.8354 0.912 0.000 0.000 0.024 0.012 0.052
#> SRR1947604 4 0.2762 0.8321 0.000 0.000 0.000 0.860 0.048 0.092
#> SRR1947605 1 0.3819 0.3570 0.652 0.000 0.000 0.000 0.008 0.340
#> SRR1947603 2 0.4771 0.7463 0.000 0.756 0.012 0.080 0.060 0.092
#> SRR1947602 6 0.5471 0.4866 0.284 0.000 0.116 0.004 0.008 0.588
#> SRR1947600 3 0.1856 0.8611 0.000 0.000 0.920 0.000 0.048 0.032
#> SRR1947601 2 0.1353 0.8912 0.000 0.952 0.000 0.012 0.012 0.024
#> SRR1947598 4 0.2001 0.8493 0.000 0.000 0.000 0.912 0.048 0.040
#> SRR1947599 4 0.3279 0.8190 0.004 0.000 0.000 0.828 0.060 0.108
#> SRR1947597 2 0.6141 0.3620 0.000 0.548 0.004 0.296 0.060 0.092
#> SRR1947596 4 0.5255 0.6989 0.096 0.000 0.000 0.692 0.068 0.144
#> SRR1947595 4 0.2479 0.8490 0.000 0.016 0.000 0.892 0.028 0.064
#> SRR1947594 1 0.0291 0.8639 0.992 0.000 0.000 0.004 0.004 0.000
#> SRR1947592 3 0.0547 0.8823 0.000 0.000 0.980 0.000 0.000 0.020
#> SRR1947591 2 0.0363 0.8921 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947590 4 0.5739 0.6374 0.176 0.000 0.000 0.636 0.064 0.124
#> SRR1947588 1 0.0146 0.8642 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947587 3 0.1863 0.8206 0.000 0.000 0.896 0.000 0.000 0.104
#> SRR1947586 2 0.3554 0.8673 0.000 0.808 0.000 0.004 0.080 0.108
#> SRR1947585 3 0.1856 0.8611 0.000 0.000 0.920 0.000 0.048 0.032
#> SRR1947584 1 0.0146 0.8642 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947583 4 0.2164 0.8516 0.000 0.016 0.000 0.912 0.044 0.028
#> SRR1947582 6 0.5728 0.0730 0.400 0.000 0.000 0.108 0.016 0.476
#> SRR1947580 2 0.4247 0.8369 0.000 0.740 0.000 0.004 0.092 0.164
#> SRR1947581 1 0.0146 0.8642 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947576 5 0.3468 0.9408 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947575 3 0.0858 0.8818 0.000 0.004 0.968 0.000 0.000 0.028
#> SRR1947579 5 0.3468 0.9416 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947578 4 0.4661 0.7847 0.000 0.024 0.012 0.748 0.084 0.132
#> SRR1947573 3 0.0717 0.8800 0.000 0.000 0.976 0.000 0.016 0.008
#> SRR1947574 4 0.4016 0.8095 0.000 0.008 0.000 0.772 0.088 0.132
#> SRR1947571 4 0.1908 0.8456 0.000 0.000 0.000 0.916 0.056 0.028
#> SRR1947577 6 0.6436 0.1604 0.320 0.000 0.000 0.196 0.032 0.452
#> SRR1947570 6 0.4601 0.5494 0.044 0.000 0.336 0.004 0.000 0.616
#> SRR1947569 3 0.1863 0.8621 0.000 0.000 0.920 0.000 0.044 0.036
#> SRR1947566 2 0.1693 0.8903 0.000 0.936 0.000 0.012 0.020 0.032
#> SRR1947567 4 0.3657 0.8127 0.000 0.008 0.012 0.820 0.064 0.096
#> SRR1947568 4 0.5493 0.7235 0.028 0.156 0.000 0.692 0.044 0.080
#> SRR1947564 2 0.1148 0.8860 0.000 0.960 0.000 0.020 0.016 0.004
#> SRR1947563 3 0.0858 0.8818 0.000 0.004 0.968 0.000 0.000 0.028
#> SRR1947562 4 0.0717 0.8527 0.000 0.008 0.000 0.976 0.016 0.000
#> SRR1947565 3 0.1075 0.8743 0.000 0.000 0.952 0.000 0.000 0.048
#> SRR1947559 4 0.4781 0.6896 0.000 0.216 0.000 0.696 0.052 0.036
#> SRR1947560 5 0.3468 0.9408 0.000 0.000 0.264 0.000 0.728 0.008
#> SRR1947561 2 0.0363 0.8921 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947557 1 0.0000 0.8621 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0777 0.8828 0.000 0.004 0.972 0.000 0.000 0.024
#> SRR1947556 1 0.1991 0.8293 0.920 0.000 0.000 0.012 0.024 0.044
#> SRR1947553 4 0.3731 0.8279 0.000 0.008 0.000 0.796 0.072 0.124
#> SRR1947554 1 0.4053 0.6831 0.772 0.000 0.000 0.136 0.012 0.080
#> SRR1947555 2 0.2542 0.8711 0.000 0.896 0.012 0.012 0.024 0.056
#> SRR1947550 4 0.1251 0.8524 0.000 0.008 0.000 0.956 0.024 0.012
#> SRR1947552 4 0.3092 0.8236 0.000 0.000 0.000 0.836 0.060 0.104
#> SRR1947549 3 0.0725 0.8811 0.000 0.000 0.976 0.000 0.012 0.012
#> SRR1947551 5 0.3298 0.9169 0.000 0.000 0.236 0.000 0.756 0.008
#> SRR1947548 4 0.1995 0.8446 0.000 0.000 0.000 0.912 0.052 0.036
#> SRR1947506 6 0.5157 0.5699 0.084 0.000 0.312 0.004 0.004 0.596
#> SRR1947507 1 0.0146 0.8625 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947504 1 0.1952 0.8278 0.920 0.000 0.000 0.012 0.016 0.052
#> SRR1947503 4 0.3743 0.8029 0.004 0.000 0.000 0.788 0.072 0.136
#> SRR1947502 2 0.0508 0.8918 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947501 4 0.5018 0.7588 0.000 0.096 0.012 0.736 0.064 0.092
#> SRR1947499 6 0.5471 0.4866 0.284 0.000 0.116 0.004 0.008 0.588
#> SRR1947498 3 0.1856 0.8611 0.000 0.000 0.920 0.000 0.048 0.032
#> SRR1947508 6 0.4529 0.4789 0.016 0.000 0.396 0.004 0.008 0.576
#> SRR1947505 4 0.3689 0.8347 0.000 0.004 0.008 0.808 0.068 0.112
#> SRR1947497 2 0.2705 0.8832 0.000 0.872 0.000 0.004 0.052 0.072
#> SRR1947496 1 0.0146 0.8642 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947495 2 0.2705 0.8832 0.000 0.872 0.000 0.004 0.052 0.072
#> SRR1947494 4 0.2786 0.8313 0.000 0.000 0.000 0.860 0.056 0.084
#> SRR1947493 6 0.4399 0.3051 0.384 0.000 0.016 0.004 0.004 0.592
#> SRR1947492 1 0.1036 0.8593 0.964 0.000 0.000 0.004 0.008 0.024
#> SRR1947500 4 0.2583 0.8504 0.000 0.016 0.000 0.888 0.044 0.052
#> SRR1947491 4 0.2251 0.8524 0.000 0.008 0.000 0.904 0.036 0.052
#> SRR1947490 1 0.1370 0.8535 0.948 0.000 0.000 0.004 0.012 0.036
#> SRR1947489 6 0.4100 0.4984 0.004 0.004 0.376 0.004 0.000 0.612
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 15148 rows and 152 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 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 0.345 0.608 0.775 0.4891 0.507 0.507
#> 3 3 0.897 0.897 0.959 0.3678 0.666 0.429
#> 4 4 0.900 0.885 0.953 0.1220 0.866 0.624
#> 5 5 0.827 0.730 0.832 0.0563 0.941 0.771
#> 6 6 0.775 0.620 0.732 0.0396 0.908 0.608
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
#> SRR1947547 1 0.000 0.649221 1.000 0.000
#> SRR1947546 2 0.000 0.738627 0.000 1.000
#> SRR1947545 1 0.855 0.741748 0.720 0.280
#> SRR1947544 1 0.855 0.741748 0.720 0.280
#> SRR1947542 2 0.000 0.738627 0.000 1.000
#> SRR1947541 1 0.000 0.649221 1.000 0.000
#> SRR1947540 2 0.000 0.738627 0.000 1.000
#> SRR1947539 2 0.997 0.453977 0.468 0.532
#> SRR1947538 2 0.671 0.498844 0.176 0.824
#> SRR1947537 2 0.999 0.438562 0.484 0.516
#> SRR1947536 1 0.118 0.640537 0.984 0.016
#> SRR1947535 2 0.997 0.453977 0.468 0.532
#> SRR1947534 1 0.990 0.554866 0.560 0.440
#> SRR1947533 2 0.000 0.738627 0.000 1.000
#> SRR1947532 1 0.921 0.700560 0.664 0.336
#> SRR1947531 2 0.000 0.738627 0.000 1.000
#> SRR1947530 1 0.000 0.649221 1.000 0.000
#> SRR1947529 2 0.000 0.738627 0.000 1.000
#> SRR1947528 1 0.000 0.649221 1.000 0.000
#> SRR1947527 2 0.000 0.738627 0.000 1.000
#> SRR1947526 2 0.000 0.738627 0.000 1.000
#> SRR1947525 2 0.184 0.716439 0.028 0.972
#> SRR1947524 2 0.997 0.453977 0.468 0.532
#> SRR1947523 1 0.998 0.508068 0.528 0.472
#> SRR1947521 1 0.929 0.000256 0.656 0.344
#> SRR1947520 2 0.000 0.738627 0.000 1.000
#> SRR1947519 1 0.242 0.619680 0.960 0.040
#> SRR1947518 2 0.929 0.011151 0.344 0.656
#> SRR1947517 1 0.430 0.569054 0.912 0.088
#> SRR1947516 2 0.000 0.738627 0.000 1.000
#> SRR1947515 2 0.958 -0.092183 0.380 0.620
#> SRR1947514 2 0.000 0.738627 0.000 1.000
#> SRR1947513 1 0.909 0.713526 0.676 0.324
#> SRR1947512 1 0.855 0.741748 0.720 0.280
#> SRR1947511 2 0.000 0.738627 0.000 1.000
#> SRR1947510 2 0.995 0.463164 0.460 0.540
#> SRR1947572 2 0.987 -0.291798 0.432 0.568
#> SRR1947611 2 0.909 0.569585 0.324 0.676
#> SRR1947509 1 0.118 0.640537 0.984 0.016
#> SRR1947644 2 0.997 0.453977 0.468 0.532
#> SRR1947643 2 0.000 0.738627 0.000 1.000
#> SRR1947642 1 0.430 0.569054 0.912 0.088
#> SRR1947640 1 0.997 0.508439 0.532 0.468
#> SRR1947641 2 0.996 0.458618 0.464 0.536
#> SRR1947639 2 0.242 0.705525 0.040 0.960
#> SRR1947638 1 0.909 0.713526 0.676 0.324
#> SRR1947637 2 0.909 0.569585 0.324 0.676
#> SRR1947636 1 0.311 0.604417 0.944 0.056
#> SRR1947635 2 0.000 0.738627 0.000 1.000
#> SRR1947634 2 0.000 0.738627 0.000 1.000
#> SRR1947633 2 0.997 0.453977 0.468 0.532
#> SRR1947632 2 0.000 0.738627 0.000 1.000
#> SRR1947631 1 0.991 -0.291362 0.556 0.444
#> SRR1947629 2 0.997 0.453977 0.468 0.532
#> SRR1947630 2 0.000 0.738627 0.000 1.000
#> SRR1947627 1 0.118 0.640537 0.984 0.016
#> SRR1947628 2 0.000 0.738627 0.000 1.000
#> SRR1947626 2 0.000 0.738627 0.000 1.000
#> SRR1947625 2 0.991 0.480114 0.444 0.556
#> SRR1947624 2 0.625 0.664306 0.156 0.844
#> SRR1947623 1 0.909 0.713526 0.676 0.324
#> SRR1947622 2 0.000 0.738627 0.000 1.000
#> SRR1947621 2 0.000 0.738627 0.000 1.000
#> SRR1947620 1 0.855 0.741748 0.720 0.280
#> SRR1947619 2 0.999 0.438562 0.484 0.516
#> SRR1947617 2 0.000 0.738627 0.000 1.000
#> SRR1947618 1 0.861 0.740281 0.716 0.284
#> SRR1947616 2 0.680 0.651293 0.180 0.820
#> SRR1947615 1 0.000 0.649221 1.000 0.000
#> SRR1947614 1 0.895 0.104144 0.688 0.312
#> SRR1947613 1 0.866 0.738111 0.712 0.288
#> SRR1947610 2 0.242 0.705525 0.040 0.960
#> SRR1947612 2 0.000 0.738627 0.000 1.000
#> SRR1947609 1 0.909 0.713526 0.676 0.324
#> SRR1947608 2 0.990 0.484092 0.440 0.560
#> SRR1947606 1 0.000 0.649221 1.000 0.000
#> SRR1947607 1 0.913 0.709467 0.672 0.328
#> SRR1947604 1 0.996 0.515369 0.536 0.464
#> SRR1947605 1 0.808 0.732797 0.752 0.248
#> SRR1947603 2 0.000 0.738627 0.000 1.000
#> SRR1947602 1 0.000 0.649221 1.000 0.000
#> SRR1947600 2 0.997 0.453977 0.468 0.532
#> SRR1947601 2 0.000 0.738627 0.000 1.000
#> SRR1947598 2 0.634 0.529838 0.160 0.840
#> SRR1947599 1 0.909 0.713526 0.676 0.324
#> SRR1947597 2 0.000 0.738627 0.000 1.000
#> SRR1947596 1 0.855 0.741748 0.720 0.280
#> SRR1947595 2 0.242 0.705525 0.040 0.960
#> SRR1947594 1 0.855 0.741748 0.720 0.280
#> SRR1947592 2 0.997 0.453977 0.468 0.532
#> SRR1947591 2 0.000 0.738627 0.000 1.000
#> SRR1947590 1 0.855 0.741748 0.720 0.280
#> SRR1947588 1 0.855 0.741748 0.720 0.280
#> SRR1947587 1 0.118 0.639844 0.984 0.016
#> SRR1947586 2 0.000 0.738627 0.000 1.000
#> SRR1947585 2 0.997 0.453977 0.468 0.532
#> SRR1947584 1 0.855 0.741748 0.720 0.280
#> SRR1947583 2 0.278 0.696945 0.048 0.952
#> SRR1947582 1 0.861 0.740281 0.716 0.284
#> SRR1947580 2 0.000 0.738627 0.000 1.000
#> SRR1947581 1 0.855 0.741748 0.720 0.280
#> SRR1947576 2 0.909 0.569585 0.324 0.676
#> SRR1947575 2 0.909 0.569585 0.324 0.676
#> SRR1947579 2 0.997 0.453977 0.468 0.532
#> SRR1947578 2 0.000 0.738627 0.000 1.000
#> SRR1947573 2 0.990 0.484092 0.440 0.560
#> SRR1947574 1 0.997 0.508439 0.532 0.468
#> SRR1947571 2 0.881 0.170205 0.300 0.700
#> SRR1947577 1 0.861 0.740281 0.716 0.284
#> SRR1947570 1 0.000 0.649221 1.000 0.000
#> SRR1947569 2 0.997 0.453977 0.468 0.532
#> SRR1947566 2 0.000 0.738627 0.000 1.000
#> SRR1947567 2 0.000 0.738627 0.000 1.000
#> SRR1947568 2 0.358 0.672857 0.068 0.932
#> SRR1947564 2 0.000 0.738627 0.000 1.000
#> SRR1947563 2 0.913 0.567293 0.328 0.672
#> SRR1947562 2 0.242 0.705525 0.040 0.960
#> SRR1947565 2 0.998 0.446404 0.476 0.524
#> SRR1947559 2 0.000 0.738627 0.000 1.000
#> SRR1947560 2 0.909 0.569585 0.324 0.676
#> SRR1947561 2 0.000 0.738627 0.000 1.000
#> SRR1947557 1 0.855 0.741748 0.720 0.280
#> SRR1947558 2 0.997 0.453977 0.468 0.532
#> SRR1947556 1 0.855 0.741748 0.720 0.280
#> SRR1947553 2 0.204 0.712954 0.032 0.968
#> SRR1947554 1 0.909 0.713526 0.676 0.324
#> SRR1947555 2 0.781 0.621132 0.232 0.768
#> SRR1947550 2 0.242 0.705525 0.040 0.960
#> SRR1947552 1 0.909 0.713526 0.676 0.324
#> SRR1947549 2 0.990 0.484092 0.440 0.560
#> SRR1947551 2 0.990 0.484092 0.440 0.560
#> SRR1947548 2 0.671 0.498844 0.176 0.824
#> SRR1947506 1 0.000 0.649221 1.000 0.000
#> SRR1947507 1 0.855 0.741748 0.720 0.280
#> SRR1947504 1 0.876 0.733286 0.704 0.296
#> SRR1947503 1 0.909 0.713526 0.676 0.324
#> SRR1947502 2 0.000 0.738627 0.000 1.000
#> SRR1947501 2 0.000 0.738627 0.000 1.000
#> SRR1947499 1 0.000 0.649221 1.000 0.000
#> SRR1947498 1 0.866 0.174098 0.712 0.288
#> SRR1947508 1 0.118 0.640537 0.984 0.016
#> SRR1947505 1 1.000 0.485906 0.512 0.488
#> SRR1947497 2 0.000 0.738627 0.000 1.000
#> SRR1947496 1 0.855 0.741748 0.720 0.280
#> SRR1947495 2 0.000 0.738627 0.000 1.000
#> SRR1947494 1 0.975 0.604314 0.592 0.408
#> SRR1947493 1 0.000 0.649221 1.000 0.000
#> SRR1947492 1 0.861 0.740281 0.716 0.284
#> SRR1947500 2 0.999 -0.424559 0.480 0.520
#> SRR1947491 1 0.997 0.508439 0.532 0.468
#> SRR1947490 1 0.895 0.722470 0.688 0.312
#> SRR1947489 1 0.000 0.649221 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.611 0.3526 0.396 0.000 0.604
#> SRR1947546 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947545 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947544 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947542 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947541 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947540 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947539 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947538 1 0.630 0.1231 0.520 0.480 0.000
#> SRR1947537 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947536 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947535 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947534 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947533 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947532 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947531 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947530 1 0.129 0.8862 0.968 0.000 0.032
#> SRR1947529 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947528 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947527 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947526 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947525 2 0.186 0.9284 0.052 0.948 0.000
#> SRR1947524 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947523 1 0.621 0.3035 0.572 0.428 0.000
#> SRR1947521 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947520 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947519 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947518 1 0.613 0.3480 0.600 0.400 0.000
#> SRR1947517 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947516 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947515 1 0.164 0.8798 0.956 0.044 0.000
#> SRR1947514 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947513 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947512 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947511 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947510 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947572 1 0.418 0.7495 0.828 0.172 0.000
#> SRR1947611 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947509 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947644 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947643 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947642 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947640 1 0.375 0.7862 0.856 0.144 0.000
#> SRR1947641 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947639 2 0.455 0.7342 0.200 0.800 0.000
#> SRR1947638 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947637 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947636 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947635 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947634 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947633 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947632 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947631 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947629 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947630 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947627 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947628 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947626 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947625 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947624 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947623 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947622 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947621 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947620 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947619 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947617 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947618 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947616 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947615 3 0.375 0.8295 0.144 0.000 0.856
#> SRR1947614 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947613 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947610 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947612 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947609 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947608 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947606 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947607 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947604 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947605 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947603 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947602 1 0.418 0.7393 0.828 0.000 0.172
#> SRR1947600 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947601 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947598 1 0.630 0.1362 0.524 0.476 0.000
#> SRR1947599 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947597 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947596 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947595 2 0.369 0.8228 0.140 0.860 0.000
#> SRR1947594 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947592 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947591 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947590 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947588 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947587 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947586 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947585 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947584 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947583 2 0.129 0.9477 0.032 0.968 0.000
#> SRR1947582 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947580 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947581 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947576 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947575 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947579 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947578 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947573 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947574 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947571 1 0.630 0.1231 0.520 0.480 0.000
#> SRR1947577 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947570 1 0.175 0.8727 0.952 0.000 0.048
#> SRR1947569 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947566 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947567 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947568 2 0.455 0.7342 0.200 0.800 0.000
#> SRR1947564 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947563 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947562 2 0.129 0.9477 0.032 0.968 0.000
#> SRR1947565 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947559 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947560 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947561 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947557 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947558 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947556 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947553 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947554 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947555 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947550 2 0.175 0.9324 0.048 0.952 0.000
#> SRR1947552 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947549 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947551 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947548 1 0.630 0.1231 0.520 0.480 0.000
#> SRR1947506 1 0.497 0.6459 0.764 0.000 0.236
#> SRR1947507 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947504 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947503 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947502 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947501 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947499 1 0.418 0.7393 0.828 0.000 0.172
#> SRR1947498 3 0.000 0.9811 0.000 0.000 1.000
#> SRR1947508 3 0.375 0.8295 0.144 0.000 0.856
#> SRR1947505 2 0.629 0.0216 0.464 0.536 0.000
#> SRR1947497 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947496 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947495 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947494 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947493 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947492 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947500 2 0.000 0.9750 0.000 1.000 0.000
#> SRR1947491 1 0.626 0.2487 0.552 0.448 0.000
#> SRR1947490 1 0.000 0.9108 1.000 0.000 0.000
#> SRR1947489 3 0.382 0.8244 0.148 0.000 0.852
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.4961 0.146 0.552 0.000 0.448 0.000
#> SRR1947546 4 0.3837 0.713 0.000 0.224 0.000 0.776
#> SRR1947545 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947541 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947540 2 0.4277 0.586 0.000 0.720 0.000 0.280
#> SRR1947539 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947538 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947537 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947536 3 0.3649 0.749 0.204 0.000 0.796 0.000
#> SRR1947535 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947534 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947531 2 0.4277 0.586 0.000 0.720 0.000 0.280
#> SRR1947530 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947529 2 0.0188 0.962 0.000 0.996 0.000 0.004
#> SRR1947528 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947527 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947525 4 0.3764 0.722 0.000 0.216 0.000 0.784
#> SRR1947524 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947521 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947519 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947518 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947517 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947510 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.4624 0.402 0.340 0.000 0.000 0.660
#> SRR1947611 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947509 3 0.3726 0.737 0.212 0.000 0.788 0.000
#> SRR1947644 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947642 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947640 4 0.0592 0.904 0.016 0.000 0.000 0.984
#> SRR1947641 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947639 4 0.2921 0.809 0.000 0.140 0.000 0.860
#> SRR1947638 1 0.2011 0.852 0.920 0.000 0.000 0.080
#> SRR1947637 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947636 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947635 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947634 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947633 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947632 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947631 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947629 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947627 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947628 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947626 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947625 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947623 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947622 4 0.4985 0.160 0.000 0.468 0.000 0.532
#> SRR1947621 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947619 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947617 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947615 3 0.3219 0.800 0.164 0.000 0.836 0.000
#> SRR1947614 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.4746 0.447 0.000 0.368 0.000 0.632
#> SRR1947612 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.4989 0.160 0.528 0.000 0.000 0.472
#> SRR1947608 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947607 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947603 2 0.0188 0.962 0.000 0.996 0.000 0.004
#> SRR1947602 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947600 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947599 4 0.2408 0.813 0.104 0.000 0.000 0.896
#> SRR1947597 2 0.0188 0.962 0.000 0.996 0.000 0.004
#> SRR1947596 1 0.4981 0.191 0.536 0.000 0.000 0.464
#> SRR1947595 4 0.3311 0.780 0.000 0.172 0.000 0.828
#> SRR1947594 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947590 1 0.4981 0.191 0.536 0.000 0.000 0.464
#> SRR1947588 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947586 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947585 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.0817 0.903 0.000 0.024 0.000 0.976
#> SRR1947582 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947580 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947581 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.4382 0.560 0.000 0.704 0.000 0.296
#> SRR1947573 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947574 1 0.4866 0.306 0.596 0.000 0.000 0.404
#> SRR1947571 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947577 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947570 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947569 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947566 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947567 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947568 2 0.3610 0.733 0.200 0.800 0.000 0.000
#> SRR1947564 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947563 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947562 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947565 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947559 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947556 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947553 4 0.4804 0.408 0.000 0.384 0.000 0.616
#> SRR1947554 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947550 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947552 4 0.0188 0.911 0.004 0.000 0.000 0.996
#> SRR1947549 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947551 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947506 1 0.0336 0.918 0.992 0.000 0.008 0.000
#> SRR1947507 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947503 1 0.3528 0.718 0.808 0.000 0.000 0.192
#> SRR1947502 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947501 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947499 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947498 3 0.0000 0.977 0.000 0.000 1.000 0.000
#> SRR1947508 3 0.3801 0.725 0.220 0.000 0.780 0.000
#> SRR1947505 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.965 0.000 1.000 0.000 0.000
#> SRR1947494 4 0.0000 0.913 0.000 0.000 0.000 1.000
#> SRR1947493 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0817 0.903 0.000 0.024 0.000 0.976
#> SRR1947491 4 0.0817 0.899 0.024 0.000 0.000 0.976
#> SRR1947490 1 0.0000 0.925 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.3528 0.760 0.192 0.000 0.808 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 5 0.4546 0.616 0.008 0.000 0.460 0.000 0.532
#> SRR1947546 4 0.3491 0.737 0.000 0.228 0.000 0.768 0.004
#> SRR1947545 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947544 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.0162 0.885 0.000 0.000 0.000 0.996 0.004
#> SRR1947541 5 0.4302 0.606 0.000 0.000 0.480 0.000 0.520
#> SRR1947540 2 0.4165 0.476 0.000 0.672 0.000 0.320 0.008
#> SRR1947539 3 0.4268 0.572 0.000 0.000 0.556 0.000 0.444
#> SRR1947538 4 0.0404 0.884 0.000 0.000 0.000 0.988 0.012
#> SRR1947537 3 0.1043 0.637 0.000 0.000 0.960 0.000 0.040
#> SRR1947536 3 0.4450 -0.584 0.004 0.000 0.508 0.000 0.488
#> SRR1947535 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947534 1 0.0162 0.897 0.996 0.004 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 4 0.0404 0.884 0.000 0.000 0.000 0.988 0.012
#> SRR1947531 2 0.4165 0.476 0.000 0.672 0.000 0.320 0.008
#> SRR1947530 5 0.4302 0.196 0.480 0.000 0.000 0.000 0.520
#> SRR1947529 2 0.1041 0.928 0.000 0.964 0.000 0.032 0.004
#> SRR1947528 5 0.4302 0.606 0.000 0.000 0.480 0.000 0.520
#> SRR1947527 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 4 0.3210 0.754 0.000 0.212 0.000 0.788 0.000
#> SRR1947524 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947523 4 0.0510 0.884 0.000 0.000 0.000 0.984 0.016
#> SRR1947521 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947520 2 0.0162 0.950 0.000 0.996 0.000 0.000 0.004
#> SRR1947519 5 0.4294 0.609 0.000 0.000 0.468 0.000 0.532
#> SRR1947518 4 0.0566 0.883 0.004 0.000 0.000 0.984 0.012
#> SRR1947517 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947516 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.0404 0.884 0.000 0.000 0.000 0.988 0.012
#> SRR1947514 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947510 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947572 1 0.4653 0.188 0.516 0.000 0.000 0.472 0.012
#> SRR1947611 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947509 5 0.1608 0.206 0.000 0.000 0.072 0.000 0.928
#> SRR1947644 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947643 2 0.0162 0.950 0.000 0.996 0.000 0.000 0.004
#> SRR1947642 3 0.4268 -0.480 0.000 0.000 0.556 0.000 0.444
#> SRR1947640 4 0.3074 0.724 0.196 0.000 0.000 0.804 0.000
#> SRR1947641 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947639 4 0.2852 0.795 0.000 0.172 0.000 0.828 0.000
#> SRR1947638 1 0.0404 0.892 0.988 0.000 0.000 0.012 0.000
#> SRR1947637 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947636 3 0.1121 0.632 0.000 0.000 0.956 0.000 0.044
#> SRR1947635 4 0.0162 0.885 0.000 0.000 0.000 0.996 0.004
#> SRR1947634 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947633 3 0.4262 0.573 0.000 0.000 0.560 0.000 0.440
#> SRR1947632 4 0.0162 0.885 0.000 0.000 0.000 0.996 0.004
#> SRR1947631 3 0.1608 0.595 0.000 0.000 0.928 0.000 0.072
#> SRR1947629 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947630 2 0.0880 0.930 0.000 0.968 0.000 0.000 0.032
#> SRR1947627 5 0.4302 0.606 0.000 0.000 0.480 0.000 0.520
#> SRR1947628 4 0.0290 0.884 0.000 0.000 0.000 0.992 0.008
#> SRR1947626 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947624 2 0.0880 0.931 0.000 0.968 0.000 0.000 0.032
#> SRR1947623 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.4425 0.250 0.000 0.452 0.000 0.544 0.004
#> SRR1947621 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947619 3 0.1043 0.637 0.000 0.000 0.960 0.000 0.040
#> SRR1947617 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947616 2 0.0693 0.942 0.000 0.980 0.000 0.012 0.008
#> SRR1947615 5 0.4437 0.614 0.004 0.000 0.464 0.000 0.532
#> SRR1947614 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947613 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3884 0.641 0.000 0.288 0.000 0.708 0.004
#> SRR1947612 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 1 0.3942 0.620 0.728 0.000 0.000 0.260 0.012
#> SRR1947608 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947606 5 0.4302 0.606 0.000 0.000 0.480 0.000 0.520
#> SRR1947607 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.1012 0.875 0.020 0.000 0.000 0.968 0.012
#> SRR1947605 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947603 2 0.1041 0.928 0.000 0.964 0.000 0.032 0.004
#> SRR1947602 5 0.5685 0.418 0.396 0.000 0.084 0.000 0.520
#> SRR1947600 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947601 2 0.0162 0.950 0.000 0.996 0.000 0.000 0.004
#> SRR1947598 4 0.0609 0.884 0.000 0.000 0.000 0.980 0.020
#> SRR1947599 4 0.1914 0.842 0.060 0.000 0.000 0.924 0.016
#> SRR1947597 2 0.0963 0.928 0.000 0.964 0.000 0.036 0.000
#> SRR1947596 1 0.4632 0.295 0.540 0.000 0.000 0.448 0.012
#> SRR1947595 4 0.4540 0.624 0.016 0.300 0.000 0.676 0.008
#> SRR1947594 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.672 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 1 0.4641 0.274 0.532 0.000 0.000 0.456 0.012
#> SRR1947588 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.4262 -0.471 0.000 0.000 0.560 0.000 0.440
#> SRR1947586 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947585 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947584 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.3074 0.773 0.000 0.196 0.000 0.804 0.000
#> SRR1947582 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947580 2 0.0290 0.949 0.000 0.992 0.000 0.000 0.008
#> SRR1947581 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947575 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947579 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947578 2 0.4415 0.327 0.000 0.604 0.000 0.388 0.008
#> SRR1947573 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947574 1 0.4067 0.519 0.692 0.000 0.000 0.300 0.008
#> SRR1947571 4 0.0404 0.884 0.000 0.000 0.000 0.988 0.012
#> SRR1947577 1 0.1043 0.876 0.960 0.000 0.000 0.000 0.040
#> SRR1947570 5 0.6342 0.596 0.272 0.000 0.208 0.000 0.520
#> SRR1947569 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947566 2 0.0162 0.950 0.000 0.996 0.000 0.000 0.004
#> SRR1947567 4 0.1124 0.875 0.000 0.036 0.000 0.960 0.004
#> SRR1947568 2 0.3461 0.687 0.224 0.772 0.000 0.004 0.000
#> SRR1947564 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947562 4 0.0000 0.885 0.000 0.000 0.000 1.000 0.000
#> SRR1947565 3 0.1043 0.637 0.000 0.000 0.960 0.000 0.040
#> SRR1947559 2 0.0162 0.950 0.000 0.996 0.000 0.004 0.000
#> SRR1947560 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947561 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0404 0.669 0.000 0.000 0.988 0.000 0.012
#> SRR1947556 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.3949 0.619 0.000 0.300 0.000 0.696 0.004
#> SRR1947554 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0162 0.950 0.000 0.996 0.000 0.000 0.004
#> SRR1947550 4 0.0794 0.879 0.000 0.028 0.000 0.972 0.000
#> SRR1947552 4 0.1012 0.875 0.020 0.000 0.000 0.968 0.012
#> SRR1947549 3 0.0000 0.672 0.000 0.000 1.000 0.000 0.000
#> SRR1947551 3 0.4273 0.571 0.000 0.000 0.552 0.000 0.448
#> SRR1947548 4 0.0404 0.884 0.000 0.000 0.000 0.988 0.012
#> SRR1947506 5 0.6164 0.531 0.328 0.000 0.152 0.000 0.520
#> SRR1947507 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 1 0.2707 0.759 0.860 0.000 0.000 0.132 0.008
#> SRR1947502 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 4 0.0162 0.885 0.000 0.000 0.000 0.996 0.004
#> SRR1947499 5 0.5519 0.384 0.412 0.000 0.068 0.000 0.520
#> SRR1947498 3 0.0162 0.674 0.000 0.000 0.996 0.000 0.004
#> SRR1947508 5 0.4437 0.614 0.004 0.000 0.464 0.000 0.532
#> SRR1947505 4 0.0404 0.885 0.000 0.000 0.000 0.988 0.012
#> SRR1947497 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 4 0.0807 0.879 0.012 0.000 0.000 0.976 0.012
#> SRR1947493 5 0.4302 0.196 0.480 0.000 0.000 0.000 0.520
#> SRR1947492 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.3074 0.773 0.000 0.196 0.000 0.804 0.000
#> SRR1947491 4 0.3266 0.719 0.200 0.000 0.000 0.796 0.004
#> SRR1947490 1 0.0000 0.899 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 5 0.4546 0.616 0.008 0.000 0.460 0.000 0.532
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.6080 0.253 0.008 0.000 0.216 0.000 0.312 0.464
#> SRR1947546 6 0.5927 -0.263 0.000 0.212 0.000 0.376 0.000 0.412
#> SRR1947545 1 0.2752 0.852 0.856 0.000 0.000 0.000 0.036 0.108
#> SRR1947544 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.4703 0.423 0.000 0.048 0.000 0.544 0.000 0.408
#> SRR1947541 6 0.6021 0.197 0.000 0.000 0.264 0.000 0.312 0.424
#> SRR1947540 6 0.5721 -0.103 0.000 0.344 0.000 0.176 0.000 0.480
#> SRR1947539 5 0.3833 0.739 0.000 0.000 0.444 0.000 0.556 0.000
#> SRR1947538 4 0.1141 0.635 0.000 0.000 0.000 0.948 0.000 0.052
#> SRR1947537 3 0.2214 0.766 0.000 0.000 0.888 0.000 0.016 0.096
#> SRR1947536 3 0.6412 -0.132 0.012 0.000 0.348 0.000 0.304 0.336
#> SRR1947535 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947534 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947533 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947532 4 0.0000 0.642 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947531 6 0.5600 -0.107 0.000 0.304 0.000 0.172 0.000 0.524
#> SRR1947530 6 0.5887 0.309 0.224 0.000 0.000 0.000 0.312 0.464
#> SRR1947529 2 0.4851 0.312 0.000 0.536 0.000 0.060 0.000 0.404
#> SRR1947528 6 0.6021 0.197 0.000 0.000 0.264 0.000 0.312 0.424
#> SRR1947527 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947526 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947525 4 0.5552 0.405 0.000 0.196 0.000 0.552 0.000 0.252
#> SRR1947524 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947523 4 0.1075 0.639 0.000 0.000 0.000 0.952 0.000 0.048
#> SRR1947521 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947520 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947519 3 0.5694 0.202 0.000 0.000 0.504 0.000 0.312 0.184
#> SRR1947518 4 0.1285 0.635 0.004 0.000 0.000 0.944 0.000 0.052
#> SRR1947517 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947516 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 4 0.0000 0.642 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947514 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 1 0.1204 0.907 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947512 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947510 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947572 4 0.3923 0.150 0.416 0.000 0.000 0.580 0.000 0.004
#> SRR1947611 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947509 5 0.2538 0.321 0.000 0.000 0.016 0.000 0.860 0.124
#> SRR1947644 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947643 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947642 3 0.4989 0.440 0.000 0.000 0.628 0.000 0.252 0.120
#> SRR1947640 4 0.5503 0.421 0.132 0.000 0.000 0.484 0.000 0.384
#> SRR1947641 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947639 4 0.5522 0.411 0.000 0.188 0.000 0.556 0.000 0.256
#> SRR1947638 1 0.1950 0.875 0.912 0.000 0.000 0.064 0.000 0.024
#> SRR1947637 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947636 3 0.2214 0.766 0.000 0.000 0.888 0.000 0.016 0.096
#> SRR1947635 4 0.4681 0.416 0.000 0.044 0.000 0.524 0.000 0.432
#> SRR1947634 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947633 5 0.3851 0.709 0.000 0.000 0.460 0.000 0.540 0.000
#> SRR1947632 4 0.4763 0.418 0.000 0.052 0.000 0.536 0.000 0.412
#> SRR1947631 3 0.1411 0.791 0.000 0.000 0.936 0.000 0.060 0.004
#> SRR1947629 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947630 2 0.3190 0.754 0.000 0.820 0.000 0.000 0.136 0.044
#> SRR1947627 6 0.6137 0.202 0.004 0.000 0.260 0.000 0.312 0.424
#> SRR1947628 6 0.4705 -0.445 0.000 0.044 0.000 0.476 0.000 0.480
#> SRR1947626 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947625 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947624 2 0.3190 0.754 0.000 0.820 0.000 0.000 0.136 0.044
#> SRR1947623 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 6 0.6043 -0.197 0.000 0.268 0.000 0.320 0.000 0.412
#> SRR1947621 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 1 0.2798 0.851 0.852 0.000 0.000 0.000 0.036 0.112
#> SRR1947619 3 0.2214 0.766 0.000 0.000 0.888 0.000 0.016 0.096
#> SRR1947617 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 1 0.2798 0.851 0.852 0.000 0.000 0.000 0.036 0.112
#> SRR1947616 2 0.3823 0.375 0.000 0.564 0.000 0.000 0.000 0.436
#> SRR1947615 6 0.5887 0.244 0.000 0.000 0.224 0.000 0.312 0.464
#> SRR1947614 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947613 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 6 0.5873 -0.254 0.000 0.208 0.000 0.340 0.000 0.452
#> SRR1947612 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 4 0.4968 0.146 0.368 0.000 0.000 0.556 0.000 0.076
#> SRR1947608 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947606 6 0.6041 0.183 0.000 0.000 0.272 0.000 0.312 0.416
#> SRR1947607 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.1168 0.635 0.028 0.000 0.000 0.956 0.000 0.016
#> SRR1947605 1 0.2752 0.852 0.856 0.000 0.000 0.000 0.036 0.108
#> SRR1947603 2 0.4851 0.312 0.000 0.536 0.000 0.060 0.000 0.404
#> SRR1947602 6 0.6313 0.342 0.200 0.000 0.024 0.000 0.312 0.464
#> SRR1947600 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947601 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 4 0.1387 0.635 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947599 4 0.2962 0.579 0.068 0.000 0.000 0.848 0.000 0.084
#> SRR1947597 2 0.4851 0.312 0.000 0.536 0.000 0.060 0.000 0.404
#> SRR1947596 4 0.4497 0.266 0.328 0.000 0.000 0.624 0.000 0.048
#> SRR1947595 4 0.6437 0.316 0.012 0.252 0.000 0.408 0.004 0.324
#> SRR1947594 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0363 0.832 0.000 0.000 0.988 0.000 0.012 0.000
#> SRR1947591 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 4 0.4497 0.266 0.328 0.000 0.000 0.624 0.000 0.048
#> SRR1947588 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.4812 0.506 0.000 0.000 0.640 0.000 0.264 0.096
#> SRR1947586 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947585 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947584 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.5508 0.330 0.000 0.128 0.000 0.444 0.000 0.428
#> SRR1947582 1 0.2798 0.851 0.852 0.000 0.000 0.000 0.036 0.112
#> SRR1947580 2 0.1814 0.850 0.000 0.900 0.000 0.000 0.000 0.100
#> SRR1947581 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947575 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947579 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947578 6 0.5750 -0.112 0.000 0.336 0.000 0.184 0.000 0.480
#> SRR1947573 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947574 1 0.4168 0.559 0.696 0.000 0.000 0.256 0.000 0.048
#> SRR1947571 4 0.0000 0.642 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947577 1 0.2798 0.851 0.852 0.000 0.000 0.000 0.036 0.112
#> SRR1947570 6 0.6614 0.347 0.164 0.000 0.060 0.000 0.312 0.464
#> SRR1947569 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947566 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 6 0.5562 -0.351 0.000 0.136 0.000 0.432 0.000 0.432
#> SRR1947568 2 0.3646 0.535 0.292 0.700 0.000 0.004 0.000 0.004
#> SRR1947564 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947563 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947562 4 0.3743 0.548 0.000 0.024 0.000 0.724 0.000 0.252
#> SRR1947565 3 0.2214 0.766 0.000 0.000 0.888 0.000 0.016 0.096
#> SRR1947559 2 0.2135 0.774 0.000 0.872 0.000 0.000 0.000 0.128
#> SRR1947560 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947561 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0146 0.833 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947556 1 0.0458 0.922 0.984 0.000 0.000 0.016 0.000 0.000
#> SRR1947553 6 0.5894 -0.243 0.000 0.216 0.000 0.332 0.000 0.452
#> SRR1947554 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947550 4 0.5399 0.412 0.000 0.128 0.000 0.528 0.000 0.344
#> SRR1947552 4 0.2629 0.596 0.060 0.000 0.000 0.872 0.000 0.068
#> SRR1947549 3 0.0363 0.832 0.000 0.000 0.988 0.000 0.012 0.000
#> SRR1947551 5 0.3464 0.918 0.000 0.000 0.312 0.000 0.688 0.000
#> SRR1947548 4 0.0000 0.642 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947506 6 0.6741 0.331 0.128 0.000 0.096 0.000 0.312 0.464
#> SRR1947507 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947503 1 0.4230 0.431 0.612 0.000 0.000 0.364 0.000 0.024
#> SRR1947502 2 0.0000 0.882 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 4 0.4814 0.414 0.000 0.056 0.000 0.532 0.000 0.412
#> SRR1947499 6 0.6209 0.332 0.208 0.000 0.016 0.000 0.312 0.464
#> SRR1947498 3 0.0458 0.831 0.000 0.000 0.984 0.000 0.016 0.000
#> SRR1947508 6 0.6293 0.222 0.012 0.000 0.252 0.000 0.312 0.424
#> SRR1947505 4 0.3592 0.533 0.000 0.000 0.000 0.656 0.000 0.344
#> SRR1947497 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947496 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.1007 0.876 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947494 4 0.1408 0.634 0.020 0.000 0.000 0.944 0.000 0.036
#> SRR1947493 6 0.5887 0.309 0.224 0.000 0.000 0.000 0.312 0.464
#> SRR1947492 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 6 0.5508 -0.316 0.000 0.132 0.000 0.388 0.000 0.480
#> SRR1947491 6 0.5718 -0.384 0.164 0.000 0.000 0.396 0.000 0.440
#> SRR1947490 1 0.0000 0.932 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 6 0.5887 0.244 0.000 0.000 0.224 0.000 0.312 0.464
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 15148 rows and 152 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 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 0.874 0.899 0.956 0.5013 0.497 0.497
#> 3 3 0.940 0.943 0.976 0.2335 0.825 0.670
#> 4 4 0.807 0.836 0.878 0.1372 0.892 0.719
#> 5 5 0.960 0.913 0.952 0.0899 0.942 0.795
#> 6 6 0.912 0.794 0.911 0.0692 0.903 0.616
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] 3 5
There is also optional best \(k\) = 3 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
#> SRR1947547 1 0.0000 0.9390 1.000 0.000
#> SRR1947546 2 0.0000 0.9655 0.000 1.000
#> SRR1947545 1 0.3114 0.9184 0.944 0.056
#> SRR1947544 1 0.2948 0.9206 0.948 0.052
#> SRR1947542 2 0.0000 0.9655 0.000 1.000
#> SRR1947541 1 0.0000 0.9390 1.000 0.000
#> SRR1947540 2 0.0672 0.9624 0.008 0.992
#> SRR1947539 1 0.0000 0.9390 1.000 0.000
#> SRR1947538 2 0.0000 0.9655 0.000 1.000
#> SRR1947537 1 0.0000 0.9390 1.000 0.000
#> SRR1947536 1 0.0000 0.9390 1.000 0.000
#> SRR1947535 1 0.0000 0.9390 1.000 0.000
#> SRR1947534 2 0.0000 0.9655 0.000 1.000
#> SRR1947533 2 0.0672 0.9624 0.008 0.992
#> SRR1947532 2 0.0000 0.9655 0.000 1.000
#> SRR1947531 2 0.0672 0.9624 0.008 0.992
#> SRR1947530 1 0.0000 0.9390 1.000 0.000
#> SRR1947529 2 0.0672 0.9624 0.008 0.992
#> SRR1947528 1 0.0000 0.9390 1.000 0.000
#> SRR1947527 2 0.0000 0.9655 0.000 1.000
#> SRR1947526 2 0.0376 0.9642 0.004 0.996
#> SRR1947525 2 0.0000 0.9655 0.000 1.000
#> SRR1947524 1 0.0000 0.9390 1.000 0.000
#> SRR1947523 2 0.0000 0.9655 0.000 1.000
#> SRR1947521 1 0.0000 0.9390 1.000 0.000
#> SRR1947520 2 0.0672 0.9624 0.008 0.992
#> SRR1947519 1 0.0000 0.9390 1.000 0.000
#> SRR1947518 2 0.0000 0.9655 0.000 1.000
#> SRR1947517 1 0.0000 0.9390 1.000 0.000
#> SRR1947516 2 0.0000 0.9655 0.000 1.000
#> SRR1947515 2 0.0000 0.9655 0.000 1.000
#> SRR1947514 2 0.0000 0.9655 0.000 1.000
#> SRR1947513 1 0.7602 0.7449 0.780 0.220
#> SRR1947512 1 0.3114 0.9184 0.944 0.056
#> SRR1947511 2 0.0000 0.9655 0.000 1.000
#> SRR1947510 1 0.0000 0.9390 1.000 0.000
#> SRR1947572 2 0.0000 0.9655 0.000 1.000
#> SRR1947611 1 0.7528 0.7189 0.784 0.216
#> SRR1947509 1 0.0000 0.9390 1.000 0.000
#> SRR1947644 1 0.0000 0.9390 1.000 0.000
#> SRR1947643 2 0.0672 0.9624 0.008 0.992
#> SRR1947642 1 0.0000 0.9390 1.000 0.000
#> SRR1947640 2 0.0000 0.9655 0.000 1.000
#> SRR1947641 1 0.1414 0.9308 0.980 0.020
#> SRR1947639 2 0.0000 0.9655 0.000 1.000
#> SRR1947638 2 0.0376 0.9633 0.004 0.996
#> SRR1947637 1 0.9710 0.3364 0.600 0.400
#> SRR1947636 1 0.0000 0.9390 1.000 0.000
#> SRR1947635 2 0.0672 0.9624 0.008 0.992
#> SRR1947634 2 0.0376 0.9642 0.004 0.996
#> SRR1947633 1 0.0000 0.9390 1.000 0.000
#> SRR1947632 2 0.0000 0.9655 0.000 1.000
#> SRR1947631 1 0.3584 0.8987 0.932 0.068
#> SRR1947629 1 0.0000 0.9390 1.000 0.000
#> SRR1947630 2 0.0938 0.9596 0.012 0.988
#> SRR1947627 1 0.0000 0.9390 1.000 0.000
#> SRR1947628 2 0.0000 0.9655 0.000 1.000
#> SRR1947626 2 0.0000 0.9655 0.000 1.000
#> SRR1947625 1 0.9963 0.1423 0.536 0.464
#> SRR1947624 2 0.1414 0.9534 0.020 0.980
#> SRR1947623 1 0.3431 0.9134 0.936 0.064
#> SRR1947622 2 0.0000 0.9655 0.000 1.000
#> SRR1947621 2 0.0000 0.9655 0.000 1.000
#> SRR1947620 1 0.7219 0.7717 0.800 0.200
#> SRR1947619 1 0.0000 0.9390 1.000 0.000
#> SRR1947617 2 0.0000 0.9655 0.000 1.000
#> SRR1947618 1 0.7745 0.7339 0.772 0.228
#> SRR1947616 2 0.2778 0.9266 0.048 0.952
#> SRR1947615 1 0.0000 0.9390 1.000 0.000
#> SRR1947614 1 0.0000 0.9390 1.000 0.000
#> SRR1947613 1 0.3114 0.9184 0.944 0.056
#> SRR1947610 2 0.0000 0.9655 0.000 1.000
#> SRR1947612 2 0.0000 0.9655 0.000 1.000
#> SRR1947609 2 1.0000 -0.0755 0.496 0.504
#> SRR1947608 1 0.4161 0.8813 0.916 0.084
#> SRR1947606 1 0.0000 0.9390 1.000 0.000
#> SRR1947607 1 0.9522 0.4651 0.628 0.372
#> SRR1947604 2 0.0000 0.9655 0.000 1.000
#> SRR1947605 1 0.2948 0.9206 0.948 0.052
#> SRR1947603 2 0.0672 0.9624 0.008 0.992
#> SRR1947602 1 0.0000 0.9390 1.000 0.000
#> SRR1947600 1 0.0000 0.9390 1.000 0.000
#> SRR1947601 2 0.0672 0.9624 0.008 0.992
#> SRR1947598 2 0.1843 0.9448 0.028 0.972
#> SRR1947599 2 0.0000 0.9655 0.000 1.000
#> SRR1947597 2 0.0000 0.9655 0.000 1.000
#> SRR1947596 2 0.8555 0.5848 0.280 0.720
#> SRR1947595 2 0.4939 0.8547 0.108 0.892
#> SRR1947594 1 0.3114 0.9184 0.944 0.056
#> SRR1947592 1 0.0000 0.9390 1.000 0.000
#> SRR1947591 2 0.0376 0.9642 0.004 0.996
#> SRR1947590 1 0.9970 0.1847 0.532 0.468
#> SRR1947588 1 0.2948 0.9206 0.948 0.052
#> SRR1947587 1 0.0000 0.9390 1.000 0.000
#> SRR1947586 2 0.0000 0.9655 0.000 1.000
#> SRR1947585 1 0.0000 0.9390 1.000 0.000
#> SRR1947584 1 0.2948 0.9206 0.948 0.052
#> SRR1947583 2 0.0000 0.9655 0.000 1.000
#> SRR1947582 1 0.7745 0.7339 0.772 0.228
#> SRR1947580 2 0.0672 0.9624 0.008 0.992
#> SRR1947581 1 0.2948 0.9206 0.948 0.052
#> SRR1947576 1 0.3584 0.8964 0.932 0.068
#> SRR1947575 2 0.7745 0.7055 0.228 0.772
#> SRR1947579 1 0.0000 0.9390 1.000 0.000
#> SRR1947578 2 0.1414 0.9534 0.020 0.980
#> SRR1947573 1 0.0000 0.9390 1.000 0.000
#> SRR1947574 2 0.0000 0.9655 0.000 1.000
#> SRR1947571 2 0.0000 0.9655 0.000 1.000
#> SRR1947577 2 0.9522 0.3548 0.372 0.628
#> SRR1947570 1 0.0000 0.9390 1.000 0.000
#> SRR1947569 1 0.0000 0.9390 1.000 0.000
#> SRR1947566 2 0.1414 0.9534 0.020 0.980
#> SRR1947567 2 0.0000 0.9655 0.000 1.000
#> SRR1947568 2 0.0000 0.9655 0.000 1.000
#> SRR1947564 2 0.0000 0.9655 0.000 1.000
#> SRR1947563 2 0.9896 0.2117 0.440 0.560
#> SRR1947562 2 0.0000 0.9655 0.000 1.000
#> SRR1947565 1 0.0000 0.9390 1.000 0.000
#> SRR1947559 2 0.0000 0.9655 0.000 1.000
#> SRR1947560 1 0.0000 0.9390 1.000 0.000
#> SRR1947561 2 0.0376 0.9642 0.004 0.996
#> SRR1947557 1 0.2948 0.9206 0.948 0.052
#> SRR1947558 1 0.0000 0.9390 1.000 0.000
#> SRR1947556 1 0.2948 0.9206 0.948 0.052
#> SRR1947553 2 0.0000 0.9655 0.000 1.000
#> SRR1947554 2 0.7453 0.7014 0.212 0.788
#> SRR1947555 2 0.0938 0.9596 0.012 0.988
#> SRR1947550 2 0.0000 0.9655 0.000 1.000
#> SRR1947552 2 0.0000 0.9655 0.000 1.000
#> SRR1947549 1 0.0000 0.9390 1.000 0.000
#> SRR1947551 1 0.0000 0.9390 1.000 0.000
#> SRR1947548 2 0.0000 0.9655 0.000 1.000
#> SRR1947506 1 0.0000 0.9390 1.000 0.000
#> SRR1947507 1 0.2948 0.9206 0.948 0.052
#> SRR1947504 1 0.9358 0.5068 0.648 0.352
#> SRR1947503 2 0.0000 0.9655 0.000 1.000
#> SRR1947502 2 0.0000 0.9655 0.000 1.000
#> SRR1947501 2 0.0672 0.9624 0.008 0.992
#> SRR1947499 1 0.0000 0.9390 1.000 0.000
#> SRR1947498 1 0.0000 0.9390 1.000 0.000
#> SRR1947508 1 0.0000 0.9390 1.000 0.000
#> SRR1947505 2 0.2236 0.9386 0.036 0.964
#> SRR1947497 2 0.0000 0.9655 0.000 1.000
#> SRR1947496 1 0.3114 0.9184 0.944 0.056
#> SRR1947495 2 0.0000 0.9655 0.000 1.000
#> SRR1947494 2 0.0376 0.9639 0.004 0.996
#> SRR1947493 1 0.0672 0.9360 0.992 0.008
#> SRR1947492 1 0.3114 0.9184 0.944 0.056
#> SRR1947500 2 0.0000 0.9655 0.000 1.000
#> SRR1947491 2 0.0000 0.9655 0.000 1.000
#> SRR1947490 1 0.3114 0.9184 0.944 0.056
#> SRR1947489 1 0.0000 0.9390 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947546 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947541 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947540 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947539 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947538 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947537 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947536 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947535 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947534 1 0.6126 0.330 0.600 0.400 0.000
#> SRR1947533 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947532 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947531 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947530 1 0.4002 0.795 0.840 0.000 0.160
#> SRR1947529 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947528 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947527 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947524 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947523 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947521 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947519 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947518 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947517 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947515 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947514 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947513 2 0.6252 0.176 0.444 0.556 0.000
#> SRR1947512 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947510 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947572 2 0.6126 0.362 0.400 0.600 0.000
#> SRR1947611 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947509 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947644 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947642 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947640 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947641 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947639 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947638 2 0.5254 0.632 0.264 0.736 0.000
#> SRR1947637 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947636 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947633 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947632 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947631 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947629 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947630 2 0.3551 0.827 0.000 0.868 0.132
#> SRR1947627 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947628 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947625 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947624 2 0.3551 0.827 0.000 0.868 0.132
#> SRR1947623 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947622 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947619 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947618 2 0.5241 0.784 0.048 0.820 0.132
#> SRR1947616 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947615 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947614 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947609 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947608 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947606 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947604 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947605 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947602 1 0.6126 0.376 0.600 0.000 0.400
#> SRR1947600 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947598 2 0.3482 0.832 0.000 0.872 0.128
#> SRR1947599 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947597 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947596 2 0.4733 0.757 0.196 0.800 0.004
#> SRR1947595 2 0.1031 0.947 0.000 0.976 0.024
#> SRR1947594 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947592 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947590 2 0.4654 0.744 0.208 0.792 0.000
#> SRR1947588 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947587 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947585 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947583 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947582 1 0.5722 0.785 0.800 0.068 0.132
#> SRR1947580 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947576 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947575 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947579 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947578 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947573 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947574 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947571 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947577 2 0.2625 0.890 0.084 0.916 0.000
#> SRR1947570 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947569 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947567 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947568 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947564 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947563 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947565 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947560 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947558 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947554 1 0.1163 0.917 0.972 0.028 0.000
#> SRR1947555 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947550 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947552 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947549 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947551 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947548 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947506 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947507 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947503 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947502 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947499 1 0.5216 0.660 0.740 0.000 0.260
#> SRR1947498 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947508 3 0.0000 1.000 0.000 0.000 1.000
#> SRR1947505 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947497 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947494 2 0.0424 0.962 0.000 0.992 0.008
#> SRR1947493 1 0.0592 0.932 0.988 0.000 0.012
#> SRR1947492 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947491 2 0.0000 0.969 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.939 1.000 0.000 0.000
#> SRR1947489 3 0.0000 1.000 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947546 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947545 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947541 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947540 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947539 3 0.4697 0.8883 0.000 0.356 0.644 0.000
#> SRR1947538 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947537 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947536 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947535 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947534 1 0.7575 0.1525 0.444 0.356 0.000 0.200
#> SRR1947533 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947532 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947531 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947530 1 0.2973 0.7993 0.856 0.000 0.144 0.000
#> SRR1947529 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947528 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947527 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947526 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947525 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947524 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947523 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947521 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947520 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947519 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947518 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947517 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947516 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947515 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947513 4 0.4955 0.0985 0.444 0.000 0.000 0.556
#> SRR1947512 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947510 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947572 4 0.4855 0.1659 0.400 0.000 0.000 0.600
#> SRR1947611 3 0.2647 0.5930 0.000 0.120 0.880 0.000
#> SRR1947509 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947644 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947643 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947642 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947640 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947641 3 0.4905 0.8886 0.000 0.364 0.632 0.004
#> SRR1947639 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947638 4 0.4164 0.4866 0.264 0.000 0.000 0.736
#> SRR1947637 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947636 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947635 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947634 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947633 3 0.0000 0.6895 0.000 0.000 1.000 0.000
#> SRR1947632 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947631 3 0.5159 0.8814 0.000 0.364 0.624 0.012
#> SRR1947629 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947630 2 0.4730 0.3464 0.000 0.636 0.364 0.000
#> SRR1947627 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947628 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947626 4 0.4624 -0.2047 0.000 0.340 0.000 0.660
#> SRR1947625 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947624 2 0.4730 0.3464 0.000 0.636 0.364 0.000
#> SRR1947623 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947622 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947621 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947620 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947619 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947617 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947618 4 0.2926 0.7781 0.048 0.000 0.056 0.896
#> SRR1947616 4 0.0188 0.9143 0.000 0.004 0.000 0.996
#> SRR1947615 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947614 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947613 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947612 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947609 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947608 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947606 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947607 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947603 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947602 1 0.5138 0.3005 0.600 0.008 0.392 0.000
#> SRR1947600 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947601 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947598 4 0.1557 0.8298 0.000 0.000 0.056 0.944
#> SRR1947599 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947597 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947596 4 0.4332 0.5928 0.176 0.000 0.032 0.792
#> SRR1947595 4 0.0592 0.8968 0.000 0.000 0.016 0.984
#> SRR1947594 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947591 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947590 4 0.4137 0.5640 0.208 0.000 0.012 0.780
#> SRR1947588 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947586 2 0.4916 0.9179 0.000 0.576 0.000 0.424
#> SRR1947585 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947584 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947582 1 0.4465 0.7552 0.800 0.000 0.056 0.144
#> SRR1947580 2 0.4916 0.9179 0.000 0.576 0.000 0.424
#> SRR1947581 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.2149 0.6258 0.000 0.088 0.912 0.000
#> SRR1947575 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947579 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947578 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947573 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947574 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947571 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947577 4 0.2081 0.7933 0.084 0.000 0.000 0.916
#> SRR1947570 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947569 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947566 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947567 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947568 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947564 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947563 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947562 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947565 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947559 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947560 3 0.2921 0.5702 0.000 0.140 0.860 0.000
#> SRR1947561 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947557 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947556 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947553 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947554 1 0.0921 0.9069 0.972 0.000 0.000 0.028
#> SRR1947555 4 0.4477 -0.0429 0.000 0.312 0.000 0.688
#> SRR1947550 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947552 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947549 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947551 3 0.1557 0.6546 0.000 0.056 0.944 0.000
#> SRR1947548 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947506 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947507 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947503 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947502 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947501 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947499 1 0.4452 0.6135 0.732 0.008 0.260 0.000
#> SRR1947498 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947508 3 0.4730 0.8919 0.000 0.364 0.636 0.000
#> SRR1947505 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947496 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.4907 0.9245 0.000 0.580 0.000 0.420
#> SRR1947494 4 0.0188 0.9137 0.000 0.000 0.004 0.996
#> SRR1947493 1 0.1940 0.8735 0.924 0.000 0.076 0.000
#> SRR1947492 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947491 4 0.0000 0.9191 0.000 0.000 0.000 1.000
#> SRR1947490 1 0.0000 0.9295 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.4730 0.8919 0.000 0.364 0.636 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.1331 0.942 0.000 0.040 0.952 0.000 0.008
#> SRR1947546 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947545 1 0.1830 0.894 0.924 0.068 0.000 0.000 0.008
#> SRR1947544 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947540 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947539 3 0.4015 0.447 0.000 0.000 0.652 0.000 0.348
#> SRR1947538 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947537 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 3 0.1544 0.924 0.000 0.068 0.932 0.000 0.000
#> SRR1947535 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 2 0.6421 0.285 0.248 0.548 0.000 0.196 0.008
#> SRR1947533 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947532 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947531 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947530 1 0.2929 0.865 0.880 0.068 0.044 0.000 0.008
#> SRR1947529 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947528 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947527 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947526 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947525 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947521 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947520 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947519 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947518 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947517 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947516 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947515 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947514 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947513 4 0.5689 0.267 0.368 0.068 0.000 0.556 0.008
#> SRR1947512 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947510 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947572 4 0.4182 0.352 0.400 0.000 0.000 0.600 0.000
#> SRR1947611 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947509 5 0.0000 0.984 0.000 0.000 0.000 0.000 1.000
#> SRR1947644 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947643 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947642 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947640 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947641 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947638 4 0.4796 0.659 0.196 0.068 0.000 0.728 0.008
#> SRR1947637 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947636 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947634 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947633 5 0.1478 0.932 0.000 0.000 0.064 0.000 0.936
#> SRR1947632 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947629 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 2 0.1544 0.846 0.000 0.932 0.000 0.000 0.068
#> SRR1947627 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947628 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947626 2 0.3876 0.627 0.000 0.684 0.000 0.316 0.000
#> SRR1947625 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.1544 0.846 0.000 0.932 0.000 0.000 0.068
#> SRR1947623 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947621 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947620 1 0.1830 0.894 0.924 0.068 0.000 0.000 0.008
#> SRR1947619 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947617 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947618 4 0.2694 0.870 0.032 0.068 0.000 0.892 0.008
#> SRR1947616 4 0.0162 0.952 0.000 0.004 0.000 0.996 0.000
#> SRR1947615 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947614 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947613 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947612 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947609 4 0.1830 0.894 0.000 0.068 0.000 0.924 0.008
#> SRR1947608 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947606 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947607 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947605 1 0.1830 0.894 0.924 0.068 0.000 0.000 0.008
#> SRR1947603 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947602 1 0.5757 0.301 0.524 0.068 0.400 0.000 0.008
#> SRR1947600 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947598 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947599 4 0.1830 0.894 0.000 0.068 0.000 0.924 0.008
#> SRR1947597 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947596 4 0.3231 0.745 0.196 0.000 0.004 0.800 0.000
#> SRR1947595 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947594 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947590 4 0.3177 0.733 0.208 0.000 0.000 0.792 0.000
#> SRR1947588 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947586 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947585 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947582 1 0.4829 0.644 0.724 0.068 0.000 0.200 0.008
#> SRR1947580 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947581 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947575 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947579 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947578 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947573 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947571 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947577 4 0.3073 0.851 0.052 0.068 0.000 0.872 0.008
#> SRR1947570 3 0.1830 0.917 0.000 0.068 0.924 0.000 0.008
#> SRR1947569 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947567 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947568 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947564 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947562 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947560 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947561 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947557 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947554 1 0.2544 0.876 0.900 0.064 0.000 0.028 0.008
#> SRR1947555 2 0.4242 0.381 0.000 0.572 0.000 0.428 0.000
#> SRR1947550 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947552 4 0.1830 0.894 0.000 0.068 0.000 0.924 0.008
#> SRR1947549 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947551 5 0.0290 0.994 0.000 0.000 0.008 0.000 0.992
#> SRR1947548 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947506 3 0.1830 0.917 0.000 0.068 0.924 0.000 0.008
#> SRR1947507 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 4 0.1830 0.894 0.000 0.068 0.000 0.924 0.008
#> SRR1947502 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947501 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947499 1 0.5241 0.604 0.664 0.068 0.260 0.000 0.008
#> SRR1947498 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
#> SRR1947508 3 0.1544 0.924 0.000 0.068 0.932 0.000 0.000
#> SRR1947505 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947497 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947496 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.1544 0.936 0.000 0.932 0.000 0.068 0.000
#> SRR1947494 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947493 1 0.1990 0.893 0.920 0.068 0.004 0.000 0.008
#> SRR1947492 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947491 4 0.0000 0.955 0.000 0.000 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.926 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0000 0.979 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.5328 0.41798 0.000 0.000 0.596 0.204 0.000 0.200
#> SRR1947546 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947545 1 0.4916 0.38905 0.520 0.000 0.000 0.416 0.000 0.064
#> SRR1947544 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947541 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947540 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947539 3 0.3620 0.44412 0.000 0.000 0.648 0.000 0.352 0.000
#> SRR1947538 6 0.3804 -0.68101 0.000 0.000 0.000 0.424 0.000 0.576
#> SRR1947537 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947536 3 0.2854 0.74783 0.000 0.000 0.792 0.208 0.000 0.000
#> SRR1947535 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 4 0.3727 -0.34820 0.000 0.388 0.000 0.612 0.000 0.000
#> SRR1947533 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947531 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947530 6 0.5445 0.48014 0.120 0.000 0.000 0.416 0.000 0.464
#> SRR1947529 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947528 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947527 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947525 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947524 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947521 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947519 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947518 6 0.3727 -0.60210 0.000 0.000 0.000 0.388 0.000 0.612
#> SRR1947517 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947512 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 6 0.5742 -0.31127 0.356 0.000 0.000 0.176 0.000 0.468
#> SRR1947611 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947509 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947644 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947642 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947640 4 0.3854 0.88525 0.000 0.000 0.000 0.536 0.000 0.464
#> SRR1947641 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947638 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947637 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947636 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947635 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947634 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947633 5 0.1204 0.92955 0.000 0.000 0.056 0.000 0.944 0.000
#> SRR1947632 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947631 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947627 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947628 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947626 2 0.3126 0.67379 0.000 0.752 0.000 0.248 0.000 0.000
#> SRR1947625 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947623 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947621 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947619 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947617 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947616 4 0.3923 0.95309 0.000 0.004 0.000 0.580 0.000 0.416
#> SRR1947615 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947614 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947612 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947608 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947606 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947607 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.3789 0.49839 0.584 0.000 0.000 0.416 0.000 0.000
#> SRR1947603 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947602 6 0.4116 0.58841 0.000 0.000 0.012 0.416 0.000 0.572
#> SRR1947600 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947599 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947597 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947596 6 0.0458 0.47671 0.000 0.000 0.000 0.016 0.000 0.984
#> SRR1947595 6 0.2664 -0.00407 0.000 0.000 0.000 0.184 0.000 0.816
#> SRR1947594 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947591 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 6 0.0458 0.47671 0.000 0.000 0.000 0.016 0.000 0.984
#> SRR1947588 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947586 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947585 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947582 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947580 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947573 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947574 6 0.0260 0.44916 0.000 0.000 0.000 0.008 0.000 0.992
#> SRR1947571 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947577 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947570 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947569 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947568 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947564 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947563 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947562 6 0.3838 -0.73076 0.000 0.000 0.000 0.448 0.000 0.552
#> SRR1947565 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947559 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947560 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947554 6 0.6014 0.32293 0.240 0.000 0.000 0.368 0.000 0.392
#> SRR1947555 2 0.4775 0.44892 0.000 0.632 0.000 0.284 0.000 0.084
#> SRR1947550 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947552 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947549 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947551 5 0.0000 0.99424 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947548 6 0.3765 -0.64215 0.000 0.000 0.000 0.404 0.000 0.596
#> SRR1947506 6 0.5725 0.45079 0.000 0.000 0.164 0.416 0.000 0.420
#> SRR1947507 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947503 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947502 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947499 6 0.3789 0.59619 0.000 0.000 0.000 0.416 0.000 0.584
#> SRR1947498 3 0.0000 0.96247 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947508 3 0.2762 0.76208 0.000 0.000 0.804 0.196 0.000 0.000
#> SRR1947505 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.96906 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947494 6 0.0000 0.46205 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947493 1 0.3789 0.49839 0.584 0.000 0.000 0.416 0.000 0.000
#> SRR1947492 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947491 4 0.3789 0.95823 0.000 0.000 0.000 0.584 0.000 0.416
#> SRR1947490 1 0.0000 0.92061 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0000 0.96247 0.000 0.000 1.000 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 15148 rows and 152 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 1.000 0.997 0.996 0.4577 0.543 0.543
#> 3 3 0.655 0.748 0.860 0.2887 0.857 0.742
#> 4 4 0.687 0.765 0.855 0.1589 0.900 0.770
#> 5 5 0.848 0.718 0.884 0.1107 0.883 0.668
#> 6 6 0.840 0.853 0.914 0.0523 0.878 0.567
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
#> SRR1947547 2 0.0376 0.998 0.004 0.996
#> SRR1947546 1 0.0376 0.997 0.996 0.004
#> SRR1947545 1 0.0376 0.997 0.996 0.004
#> SRR1947544 1 0.0376 0.997 0.996 0.004
#> SRR1947542 1 0.0376 0.997 0.996 0.004
#> SRR1947541 2 0.0376 0.998 0.004 0.996
#> SRR1947540 1 0.0376 0.997 0.996 0.004
#> SRR1947539 2 0.0376 0.995 0.004 0.996
#> SRR1947538 1 0.0376 0.997 0.996 0.004
#> SRR1947537 2 0.0376 0.998 0.004 0.996
#> SRR1947536 2 0.0672 0.996 0.008 0.992
#> SRR1947535 2 0.0376 0.998 0.004 0.996
#> SRR1947534 1 0.0000 0.997 1.000 0.000
#> SRR1947533 1 0.0376 0.995 0.996 0.004
#> SRR1947532 1 0.0376 0.997 0.996 0.004
#> SRR1947531 1 0.0376 0.997 0.996 0.004
#> SRR1947530 2 0.0672 0.996 0.008 0.992
#> SRR1947529 1 0.0376 0.997 0.996 0.004
#> SRR1947528 2 0.0376 0.998 0.004 0.996
#> SRR1947527 1 0.0376 0.995 0.996 0.004
#> SRR1947526 1 0.0376 0.995 0.996 0.004
#> SRR1947525 1 0.0376 0.997 0.996 0.004
#> SRR1947524 2 0.0376 0.998 0.004 0.996
#> SRR1947523 1 0.0376 0.997 0.996 0.004
#> SRR1947521 2 0.0376 0.995 0.004 0.996
#> SRR1947520 1 0.0376 0.995 0.996 0.004
#> SRR1947519 2 0.0376 0.998 0.004 0.996
#> SRR1947518 1 0.0376 0.997 0.996 0.004
#> SRR1947517 2 0.0376 0.995 0.004 0.996
#> SRR1947516 1 0.0376 0.995 0.996 0.004
#> SRR1947515 1 0.0376 0.997 0.996 0.004
#> SRR1947514 1 0.0376 0.995 0.996 0.004
#> SRR1947513 1 0.0000 0.997 1.000 0.000
#> SRR1947512 1 0.0000 0.997 1.000 0.000
#> SRR1947511 1 0.0376 0.995 0.996 0.004
#> SRR1947510 2 0.0376 0.995 0.004 0.996
#> SRR1947572 1 0.0376 0.997 0.996 0.004
#> SRR1947611 2 0.0376 0.995 0.004 0.996
#> SRR1947509 2 0.0376 0.995 0.004 0.996
#> SRR1947644 2 0.0376 0.995 0.004 0.996
#> SRR1947643 1 0.0376 0.995 0.996 0.004
#> SRR1947642 2 0.0376 0.998 0.004 0.996
#> SRR1947640 1 0.0376 0.997 0.996 0.004
#> SRR1947641 2 0.0376 0.998 0.004 0.996
#> SRR1947639 1 0.0376 0.997 0.996 0.004
#> SRR1947638 1 0.0000 0.997 1.000 0.000
#> SRR1947637 2 0.0376 0.995 0.004 0.996
#> SRR1947636 2 0.0376 0.998 0.004 0.996
#> SRR1947635 1 0.0376 0.997 0.996 0.004
#> SRR1947634 1 0.0376 0.995 0.996 0.004
#> SRR1947633 2 0.0376 0.995 0.004 0.996
#> SRR1947632 1 0.0376 0.997 0.996 0.004
#> SRR1947631 2 0.0376 0.998 0.004 0.996
#> SRR1947629 2 0.0376 0.998 0.004 0.996
#> SRR1947630 1 0.0376 0.995 0.996 0.004
#> SRR1947627 2 0.0672 0.996 0.008 0.992
#> SRR1947628 1 0.0376 0.997 0.996 0.004
#> SRR1947626 1 0.0376 0.995 0.996 0.004
#> SRR1947625 2 0.0376 0.998 0.004 0.996
#> SRR1947624 1 0.0376 0.995 0.996 0.004
#> SRR1947623 1 0.0000 0.997 1.000 0.000
#> SRR1947622 1 0.0376 0.997 0.996 0.004
#> SRR1947621 1 0.0376 0.995 0.996 0.004
#> SRR1947620 1 0.0376 0.997 0.996 0.004
#> SRR1947619 2 0.0376 0.998 0.004 0.996
#> SRR1947617 1 0.0376 0.995 0.996 0.004
#> SRR1947618 1 0.0000 0.997 1.000 0.000
#> SRR1947616 1 0.0672 0.996 0.992 0.008
#> SRR1947615 2 0.0376 0.998 0.004 0.996
#> SRR1947614 2 0.0376 0.995 0.004 0.996
#> SRR1947613 1 0.0000 0.997 1.000 0.000
#> SRR1947610 1 0.0376 0.997 0.996 0.004
#> SRR1947612 1 0.0376 0.995 0.996 0.004
#> SRR1947609 1 0.0376 0.997 0.996 0.004
#> SRR1947608 2 0.0376 0.998 0.004 0.996
#> SRR1947606 2 0.0376 0.998 0.004 0.996
#> SRR1947607 1 0.0000 0.997 1.000 0.000
#> SRR1947604 1 0.0376 0.997 0.996 0.004
#> SRR1947605 1 0.0000 0.997 1.000 0.000
#> SRR1947603 1 0.0376 0.997 0.996 0.004
#> SRR1947602 2 0.0672 0.996 0.008 0.992
#> SRR1947600 2 0.0376 0.998 0.004 0.996
#> SRR1947601 1 0.0376 0.995 0.996 0.004
#> SRR1947598 1 0.0376 0.997 0.996 0.004
#> SRR1947599 1 0.0376 0.997 0.996 0.004
#> SRR1947597 1 0.0376 0.997 0.996 0.004
#> SRR1947596 1 0.0376 0.997 0.996 0.004
#> SRR1947595 1 0.0376 0.995 0.996 0.004
#> SRR1947594 1 0.0000 0.997 1.000 0.000
#> SRR1947592 2 0.0376 0.998 0.004 0.996
#> SRR1947591 1 0.0376 0.995 0.996 0.004
#> SRR1947590 1 0.0376 0.997 0.996 0.004
#> SRR1947588 1 0.0000 0.997 1.000 0.000
#> SRR1947587 2 0.0376 0.998 0.004 0.996
#> SRR1947586 1 0.0376 0.995 0.996 0.004
#> SRR1947585 2 0.0376 0.998 0.004 0.996
#> SRR1947584 1 0.0000 0.997 1.000 0.000
#> SRR1947583 1 0.0376 0.997 0.996 0.004
#> SRR1947582 1 0.0000 0.997 1.000 0.000
#> SRR1947580 1 0.0376 0.995 0.996 0.004
#> SRR1947581 1 0.0000 0.997 1.000 0.000
#> SRR1947576 2 0.0376 0.995 0.004 0.996
#> SRR1947575 2 0.0376 0.998 0.004 0.996
#> SRR1947579 2 0.0376 0.995 0.004 0.996
#> SRR1947578 1 0.0672 0.996 0.992 0.008
#> SRR1947573 2 0.0376 0.998 0.004 0.996
#> SRR1947574 1 0.0000 0.997 1.000 0.000
#> SRR1947571 1 0.0376 0.997 0.996 0.004
#> SRR1947577 1 0.0376 0.997 0.996 0.004
#> SRR1947570 2 0.0376 0.998 0.004 0.996
#> SRR1947569 2 0.0376 0.998 0.004 0.996
#> SRR1947566 1 0.0376 0.995 0.996 0.004
#> SRR1947567 1 0.0376 0.997 0.996 0.004
#> SRR1947568 1 0.0000 0.997 1.000 0.000
#> SRR1947564 1 0.0376 0.997 0.996 0.004
#> SRR1947563 2 0.0376 0.998 0.004 0.996
#> SRR1947562 1 0.0376 0.997 0.996 0.004
#> SRR1947565 2 0.0376 0.998 0.004 0.996
#> SRR1947559 1 0.0376 0.997 0.996 0.004
#> SRR1947560 2 0.0376 0.995 0.004 0.996
#> SRR1947561 1 0.0376 0.995 0.996 0.004
#> SRR1947557 1 0.0000 0.997 1.000 0.000
#> SRR1947558 2 0.0376 0.998 0.004 0.996
#> SRR1947556 1 0.0376 0.997 0.996 0.004
#> SRR1947553 1 0.0376 0.997 0.996 0.004
#> SRR1947554 1 0.0000 0.997 1.000 0.000
#> SRR1947555 1 0.0376 0.995 0.996 0.004
#> SRR1947550 1 0.0376 0.997 0.996 0.004
#> SRR1947552 1 0.0376 0.997 0.996 0.004
#> SRR1947549 2 0.0376 0.998 0.004 0.996
#> SRR1947551 2 0.0376 0.995 0.004 0.996
#> SRR1947548 1 0.0376 0.997 0.996 0.004
#> SRR1947506 2 0.0376 0.998 0.004 0.996
#> SRR1947507 1 0.0000 0.997 1.000 0.000
#> SRR1947504 1 0.0000 0.997 1.000 0.000
#> SRR1947503 1 0.0376 0.997 0.996 0.004
#> SRR1947502 1 0.0376 0.995 0.996 0.004
#> SRR1947501 1 0.0376 0.997 0.996 0.004
#> SRR1947499 2 0.0672 0.996 0.008 0.992
#> SRR1947498 2 0.0376 0.998 0.004 0.996
#> SRR1947508 2 0.0672 0.996 0.008 0.992
#> SRR1947505 1 0.0376 0.997 0.996 0.004
#> SRR1947497 1 0.0376 0.995 0.996 0.004
#> SRR1947496 1 0.0000 0.997 1.000 0.000
#> SRR1947495 1 0.0376 0.995 0.996 0.004
#> SRR1947494 1 0.0376 0.997 0.996 0.004
#> SRR1947493 2 0.0672 0.996 0.008 0.992
#> SRR1947492 1 0.0000 0.997 1.000 0.000
#> SRR1947500 1 0.0376 0.997 0.996 0.004
#> SRR1947491 1 0.0376 0.997 0.996 0.004
#> SRR1947490 1 0.0000 0.997 1.000 0.000
#> SRR1947489 2 0.0376 0.998 0.004 0.996
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947546 2 0.0592 0.844 0.012 0.988 0.000
#> SRR1947545 2 0.1411 0.835 0.036 0.964 0.000
#> SRR1947544 2 0.1411 0.835 0.036 0.964 0.000
#> SRR1947542 2 0.0237 0.844 0.004 0.996 0.000
#> SRR1947541 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947540 2 0.2165 0.825 0.064 0.936 0.000
#> SRR1947539 3 0.3752 0.808 0.144 0.000 0.856
#> SRR1947538 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947537 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947536 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947535 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947534 2 0.5058 0.784 0.244 0.756 0.000
#> SRR1947533 1 0.5859 0.347 0.656 0.344 0.000
#> SRR1947532 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947531 2 0.1529 0.837 0.040 0.960 0.000
#> SRR1947530 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947529 2 0.1643 0.835 0.044 0.956 0.000
#> SRR1947528 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947527 2 0.5363 0.755 0.276 0.724 0.000
#> SRR1947526 1 0.5785 0.364 0.668 0.332 0.000
#> SRR1947525 2 0.4702 0.791 0.212 0.788 0.000
#> SRR1947524 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947523 2 0.1031 0.842 0.024 0.976 0.000
#> SRR1947521 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947520 1 0.5926 0.369 0.644 0.356 0.000
#> SRR1947519 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947518 2 0.4452 0.802 0.192 0.808 0.000
#> SRR1947517 1 0.5882 0.305 0.652 0.000 0.348
#> SRR1947516 1 0.5859 0.347 0.656 0.344 0.000
#> SRR1947515 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947514 2 0.5497 0.717 0.292 0.708 0.000
#> SRR1947513 2 0.1289 0.837 0.032 0.968 0.000
#> SRR1947512 2 0.4750 0.795 0.216 0.784 0.000
#> SRR1947511 1 0.5650 0.394 0.688 0.312 0.000
#> SRR1947510 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947572 2 0.4605 0.797 0.204 0.796 0.000
#> SRR1947611 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947509 3 0.6252 0.299 0.444 0.000 0.556
#> SRR1947644 1 0.6180 0.129 0.584 0.000 0.416
#> SRR1947643 2 0.4002 0.719 0.160 0.840 0.000
#> SRR1947642 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947640 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947641 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947639 2 0.4654 0.790 0.208 0.792 0.000
#> SRR1947638 2 0.1289 0.837 0.032 0.968 0.000
#> SRR1947637 1 0.5706 0.365 0.680 0.000 0.320
#> SRR1947636 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947635 2 0.0747 0.843 0.016 0.984 0.000
#> SRR1947634 1 0.6079 0.314 0.612 0.388 0.000
#> SRR1947633 3 0.5058 0.704 0.244 0.000 0.756
#> SRR1947632 2 0.0424 0.843 0.008 0.992 0.000
#> SRR1947631 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947630 1 0.5291 0.486 0.732 0.268 0.000
#> SRR1947627 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947628 2 0.1411 0.839 0.036 0.964 0.000
#> SRR1947626 2 0.5178 0.760 0.256 0.744 0.000
#> SRR1947625 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947624 1 0.5138 0.492 0.748 0.252 0.000
#> SRR1947623 2 0.4796 0.790 0.220 0.780 0.000
#> SRR1947622 2 0.0592 0.844 0.012 0.988 0.000
#> SRR1947621 1 0.6307 -0.187 0.512 0.488 0.000
#> SRR1947620 2 0.1289 0.837 0.032 0.968 0.000
#> SRR1947619 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947617 2 0.5327 0.741 0.272 0.728 0.000
#> SRR1947618 2 0.1753 0.840 0.048 0.952 0.000
#> SRR1947616 2 0.6295 -0.159 0.472 0.528 0.000
#> SRR1947615 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947614 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947613 2 0.4931 0.786 0.232 0.768 0.000
#> SRR1947610 2 0.4887 0.785 0.228 0.772 0.000
#> SRR1947612 2 0.5465 0.723 0.288 0.712 0.000
#> SRR1947609 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947608 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947607 2 0.5058 0.784 0.244 0.756 0.000
#> SRR1947604 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947605 2 0.1411 0.835 0.036 0.964 0.000
#> SRR1947603 2 0.1529 0.837 0.040 0.960 0.000
#> SRR1947602 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947600 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947601 1 0.5785 0.364 0.668 0.332 0.000
#> SRR1947598 2 0.0892 0.843 0.020 0.980 0.000
#> SRR1947599 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947597 2 0.4654 0.790 0.208 0.792 0.000
#> SRR1947596 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947595 2 0.1860 0.832 0.052 0.948 0.000
#> SRR1947594 2 0.4796 0.793 0.220 0.780 0.000
#> SRR1947592 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947591 1 0.5859 0.347 0.656 0.344 0.000
#> SRR1947590 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947588 2 0.4750 0.795 0.216 0.784 0.000
#> SRR1947587 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947586 2 0.5254 0.763 0.264 0.736 0.000
#> SRR1947585 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947584 2 0.2878 0.835 0.096 0.904 0.000
#> SRR1947583 2 0.0892 0.848 0.020 0.980 0.000
#> SRR1947582 2 0.1753 0.840 0.048 0.952 0.000
#> SRR1947580 2 0.6305 0.265 0.484 0.516 0.000
#> SRR1947581 2 0.4750 0.795 0.216 0.784 0.000
#> SRR1947576 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947575 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947579 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947578 2 0.2537 0.814 0.080 0.920 0.000
#> SRR1947573 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947574 2 0.4555 0.797 0.200 0.800 0.000
#> SRR1947571 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947577 2 0.1289 0.837 0.032 0.968 0.000
#> SRR1947570 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947569 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947566 2 0.6295 -0.159 0.472 0.528 0.000
#> SRR1947567 2 0.0237 0.845 0.004 0.996 0.000
#> SRR1947568 2 0.5058 0.781 0.244 0.756 0.000
#> SRR1947564 2 0.4887 0.780 0.228 0.772 0.000
#> SRR1947563 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947559 2 0.4062 0.816 0.164 0.836 0.000
#> SRR1947560 1 0.5621 0.382 0.692 0.000 0.308
#> SRR1947561 1 0.6154 0.170 0.592 0.408 0.000
#> SRR1947557 2 0.3340 0.830 0.120 0.880 0.000
#> SRR1947558 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947556 2 0.1411 0.835 0.036 0.964 0.000
#> SRR1947553 2 0.4654 0.790 0.208 0.792 0.000
#> SRR1947554 2 0.4931 0.792 0.232 0.768 0.000
#> SRR1947555 2 0.6295 -0.159 0.472 0.528 0.000
#> SRR1947550 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947552 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947549 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947551 1 0.5882 0.311 0.652 0.000 0.348
#> SRR1947548 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947506 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947507 2 0.4750 0.795 0.216 0.784 0.000
#> SRR1947504 2 0.4796 0.792 0.220 0.780 0.000
#> SRR1947503 2 0.1289 0.837 0.032 0.968 0.000
#> SRR1947502 2 0.5216 0.756 0.260 0.740 0.000
#> SRR1947501 2 0.1860 0.828 0.052 0.948 0.000
#> SRR1947499 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947498 3 0.0000 0.959 0.000 0.000 1.000
#> SRR1947508 3 0.2959 0.890 0.100 0.000 0.900
#> SRR1947505 2 0.1529 0.837 0.040 0.960 0.000
#> SRR1947497 2 0.4974 0.775 0.236 0.764 0.000
#> SRR1947496 2 0.4796 0.793 0.220 0.780 0.000
#> SRR1947495 2 0.5098 0.766 0.248 0.752 0.000
#> SRR1947494 2 0.0892 0.843 0.020 0.980 0.000
#> SRR1947493 3 0.3293 0.889 0.088 0.012 0.900
#> SRR1947492 2 0.4750 0.796 0.216 0.784 0.000
#> SRR1947500 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947491 2 0.0000 0.845 0.000 1.000 0.000
#> SRR1947490 2 0.4842 0.791 0.224 0.776 0.000
#> SRR1947489 3 0.0000 0.959 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947546 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947545 4 0.1792 0.77266 0.068 0.000 0.000 0.932
#> SRR1947544 4 0.1792 0.77266 0.068 0.000 0.000 0.932
#> SRR1947542 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947541 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947540 4 0.3942 0.53849 0.000 0.236 0.000 0.764
#> SRR1947539 3 0.4072 0.44077 0.252 0.000 0.748 0.000
#> SRR1947538 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947537 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947536 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947535 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947534 4 0.7080 0.47440 0.236 0.196 0.000 0.568
#> SRR1947533 2 0.1022 0.81440 0.000 0.968 0.000 0.032
#> SRR1947532 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947531 4 0.3873 0.55292 0.000 0.228 0.000 0.772
#> SRR1947530 3 0.0779 0.94978 0.016 0.004 0.980 0.000
#> SRR1947529 4 0.3074 0.67152 0.000 0.152 0.000 0.848
#> SRR1947528 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947527 2 0.3610 0.77582 0.000 0.800 0.000 0.200
#> SRR1947526 2 0.1022 0.81440 0.000 0.968 0.000 0.032
#> SRR1947525 4 0.3688 0.65644 0.000 0.208 0.000 0.792
#> SRR1947524 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.0592 0.78083 0.000 0.016 0.000 0.984
#> SRR1947521 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947520 2 0.3907 0.69199 0.000 0.768 0.000 0.232
#> SRR1947519 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947518 4 0.4040 0.61066 0.000 0.248 0.000 0.752
#> SRR1947517 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947516 2 0.1637 0.83694 0.000 0.940 0.000 0.060
#> SRR1947515 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947514 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947513 4 0.1716 0.77341 0.064 0.000 0.000 0.936
#> SRR1947512 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947511 2 0.0707 0.80182 0.000 0.980 0.000 0.020
#> SRR1947510 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947572 4 0.4222 0.58349 0.000 0.272 0.000 0.728
#> SRR1947611 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947509 1 0.6202 0.98175 0.612 0.076 0.312 0.000
#> SRR1947644 1 0.6280 0.99334 0.612 0.084 0.304 0.000
#> SRR1947643 4 0.4898 0.07761 0.000 0.416 0.000 0.584
#> SRR1947642 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947640 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947641 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947639 4 0.4454 0.54082 0.000 0.308 0.000 0.692
#> SRR1947638 4 0.1716 0.77341 0.064 0.000 0.000 0.936
#> SRR1947637 1 0.6336 0.99349 0.608 0.088 0.304 0.000
#> SRR1947636 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947635 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947634 2 0.4008 0.67527 0.000 0.756 0.000 0.244
#> SRR1947633 3 0.4746 -0.07537 0.368 0.000 0.632 0.000
#> SRR1947632 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947631 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947629 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.3975 0.65704 0.000 0.760 0.000 0.240
#> SRR1947627 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947628 4 0.2921 0.68210 0.000 0.140 0.000 0.860
#> SRR1947626 2 0.3123 0.82020 0.000 0.844 0.000 0.156
#> SRR1947625 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.3610 0.70105 0.000 0.800 0.000 0.200
#> SRR1947623 4 0.5907 0.57613 0.080 0.252 0.000 0.668
#> SRR1947622 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947621 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947620 4 0.2011 0.76988 0.080 0.000 0.000 0.920
#> SRR1947619 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947617 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947618 4 0.2048 0.77384 0.064 0.008 0.000 0.928
#> SRR1947616 4 0.4981 -0.00946 0.000 0.464 0.000 0.536
#> SRR1947615 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947614 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947613 4 0.6417 0.50392 0.388 0.072 0.000 0.540
#> SRR1947610 4 0.4454 0.54082 0.000 0.308 0.000 0.692
#> SRR1947612 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947609 4 0.0188 0.78279 0.004 0.000 0.000 0.996
#> SRR1947608 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947607 4 0.7268 0.39523 0.372 0.152 0.000 0.476
#> SRR1947604 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947605 4 0.2266 0.76720 0.084 0.004 0.000 0.912
#> SRR1947603 4 0.2647 0.70773 0.000 0.120 0.000 0.880
#> SRR1947602 3 0.0779 0.94978 0.016 0.004 0.980 0.000
#> SRR1947600 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.0817 0.80636 0.000 0.976 0.000 0.024
#> SRR1947598 4 0.2197 0.74117 0.004 0.080 0.000 0.916
#> SRR1947599 4 0.0000 0.78316 0.000 0.000 0.000 1.000
#> SRR1947597 4 0.4543 0.51471 0.000 0.324 0.000 0.676
#> SRR1947596 4 0.0524 0.78343 0.004 0.008 0.000 0.988
#> SRR1947595 4 0.4655 0.37171 0.004 0.312 0.000 0.684
#> SRR1947594 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947592 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.1302 0.82535 0.000 0.956 0.000 0.044
#> SRR1947590 4 0.0524 0.78343 0.004 0.008 0.000 0.988
#> SRR1947588 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947587 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947586 2 0.3688 0.76593 0.000 0.792 0.000 0.208
#> SRR1947585 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947584 4 0.4991 0.58451 0.388 0.004 0.000 0.608
#> SRR1947583 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947582 4 0.2412 0.76745 0.084 0.008 0.000 0.908
#> SRR1947580 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947581 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947576 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947575 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947579 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947578 4 0.4730 0.23259 0.000 0.364 0.000 0.636
#> SRR1947573 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947574 4 0.1209 0.77968 0.004 0.032 0.000 0.964
#> SRR1947571 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947577 4 0.1637 0.77414 0.060 0.000 0.000 0.940
#> SRR1947570 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947569 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947566 4 0.4998 -0.10304 0.000 0.488 0.000 0.512
#> SRR1947567 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947568 2 0.4996 0.01036 0.000 0.516 0.000 0.484
#> SRR1947564 4 0.4989 0.13354 0.000 0.472 0.000 0.528
#> SRR1947563 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947562 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947565 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947559 4 0.1557 0.77201 0.000 0.056 0.000 0.944
#> SRR1947560 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947561 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947557 4 0.4991 0.58451 0.388 0.004 0.000 0.608
#> SRR1947558 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947556 4 0.1716 0.77357 0.064 0.000 0.000 0.936
#> SRR1947553 4 0.4431 0.54600 0.000 0.304 0.000 0.696
#> SRR1947554 4 0.5322 0.62649 0.312 0.028 0.000 0.660
#> SRR1947555 4 0.4996 -0.07737 0.000 0.484 0.000 0.516
#> SRR1947550 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947552 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947549 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947551 1 0.6316 0.99717 0.612 0.088 0.300 0.000
#> SRR1947548 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947506 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947507 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947504 4 0.6095 0.62345 0.224 0.108 0.000 0.668
#> SRR1947503 4 0.0592 0.78093 0.016 0.000 0.000 0.984
#> SRR1947502 2 0.2216 0.85326 0.000 0.908 0.000 0.092
#> SRR1947501 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947499 3 0.0779 0.94978 0.016 0.004 0.980 0.000
#> SRR1947498 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947508 3 0.0000 0.97434 0.000 0.000 1.000 0.000
#> SRR1947505 4 0.3791 0.59691 0.004 0.200 0.000 0.796
#> SRR1947497 2 0.3688 0.76593 0.000 0.792 0.000 0.208
#> SRR1947496 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947495 2 0.3688 0.76593 0.000 0.792 0.000 0.208
#> SRR1947494 4 0.2125 0.74444 0.004 0.076 0.000 0.920
#> SRR1947493 3 0.0779 0.94978 0.016 0.004 0.980 0.000
#> SRR1947492 4 0.5125 0.58160 0.388 0.008 0.000 0.604
#> SRR1947500 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947491 4 0.0336 0.78357 0.000 0.008 0.000 0.992
#> SRR1947490 4 0.5453 0.56929 0.388 0.020 0.000 0.592
#> SRR1947489 3 0.0000 0.97434 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947546 4 0.4522 0.81766 0.440 0.008 0.000 0.552 0.000
#> SRR1947545 4 0.0290 0.24290 0.008 0.000 0.000 0.992 0.000
#> SRR1947544 4 0.0162 0.25107 0.004 0.000 0.000 0.996 0.000
#> SRR1947542 4 0.4410 0.81828 0.440 0.004 0.000 0.556 0.000
#> SRR1947541 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947540 4 0.5320 0.78719 0.424 0.052 0.000 0.524 0.000
#> SRR1947539 3 0.4182 0.29914 0.000 0.000 0.600 0.000 0.400
#> SRR1947538 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947537 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 3 0.3003 0.74568 0.000 0.000 0.812 0.000 0.188
#> SRR1947535 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 1 0.4269 0.25059 0.776 0.116 0.000 0.108 0.000
#> SRR1947533 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947532 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947531 4 0.5211 0.79075 0.432 0.044 0.000 0.524 0.000
#> SRR1947530 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947529 1 0.6478 -0.59969 0.444 0.188 0.000 0.368 0.000
#> SRR1947528 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947527 2 0.0579 0.88256 0.008 0.984 0.000 0.008 0.000
#> SRR1947526 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 4 0.4434 0.81371 0.460 0.004 0.000 0.536 0.000
#> SRR1947524 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.4552 0.80730 0.468 0.008 0.000 0.524 0.000
#> SRR1947521 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947519 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947518 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947517 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947516 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947515 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947514 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947513 4 0.4262 0.69772 0.440 0.000 0.000 0.560 0.000
#> SRR1947512 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947511 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947572 4 0.5777 0.72753 0.444 0.088 0.000 0.468 0.000
#> SRR1947611 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947509 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947644 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947643 2 0.4287 0.00786 0.000 0.540 0.000 0.460 0.000
#> SRR1947642 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947640 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947641 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 1 0.6510 -0.26308 0.444 0.360 0.000 0.196 0.000
#> SRR1947638 4 0.4287 0.66192 0.460 0.000 0.000 0.540 0.000
#> SRR1947637 5 0.4210 0.26449 0.000 0.000 0.412 0.000 0.588
#> SRR1947636 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.4273 0.81824 0.448 0.000 0.000 0.552 0.000
#> SRR1947634 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947633 3 0.4300 0.04649 0.000 0.000 0.524 0.000 0.476
#> SRR1947632 4 0.4410 0.81828 0.440 0.004 0.000 0.556 0.000
#> SRR1947631 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947629 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947627 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947628 4 0.4648 0.80648 0.464 0.012 0.000 0.524 0.000
#> SRR1947626 2 0.0703 0.87510 0.024 0.976 0.000 0.000 0.000
#> SRR1947625 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947623 1 0.4133 0.11133 0.768 0.180 0.000 0.052 0.000
#> SRR1947622 4 0.4522 0.81766 0.440 0.008 0.000 0.552 0.000
#> SRR1947621 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947620 4 0.0794 0.19896 0.028 0.000 0.000 0.972 0.000
#> SRR1947619 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947617 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947618 4 0.3177 0.21770 0.208 0.000 0.000 0.792 0.000
#> SRR1947616 4 0.4552 0.16356 0.008 0.468 0.000 0.524 0.000
#> SRR1947615 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947614 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947613 1 0.4278 0.56595 0.548 0.000 0.000 0.452 0.000
#> SRR1947610 1 0.6424 -0.22543 0.444 0.380 0.000 0.176 0.000
#> SRR1947612 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947609 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947608 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947606 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947607 1 0.4268 0.55869 0.556 0.000 0.000 0.444 0.000
#> SRR1947604 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947605 4 0.2280 -0.04632 0.120 0.000 0.000 0.880 0.000
#> SRR1947603 4 0.4807 0.80908 0.448 0.020 0.000 0.532 0.000
#> SRR1947602 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947600 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.4182 0.76671 0.400 0.000 0.000 0.600 0.000
#> SRR1947599 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947597 1 0.6623 -0.50812 0.444 0.236 0.000 0.320 0.000
#> SRR1947596 4 0.4150 0.79238 0.388 0.000 0.000 0.612 0.000
#> SRR1947595 4 0.4630 0.76705 0.396 0.016 0.000 0.588 0.000
#> SRR1947594 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947592 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947590 4 0.3730 0.70051 0.288 0.000 0.000 0.712 0.000
#> SRR1947588 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947587 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947586 2 0.4387 0.37802 0.348 0.640 0.000 0.012 0.000
#> SRR1947585 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947583 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947582 4 0.3612 0.00275 0.268 0.000 0.000 0.732 0.000
#> SRR1947580 2 0.0000 0.89111 0.000 1.000 0.000 0.000 0.000
#> SRR1947581 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947576 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947579 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947578 4 0.6312 0.63905 0.276 0.200 0.000 0.524 0.000
#> SRR1947573 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 2 0.5736 0.17529 0.400 0.512 0.000 0.088 0.000
#> SRR1947571 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947577 4 0.2966 0.49519 0.184 0.000 0.000 0.816 0.000
#> SRR1947570 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947569 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 4 0.4559 0.12808 0.008 0.480 0.000 0.512 0.000
#> SRR1947567 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947568 2 0.5028 0.15700 0.444 0.524 0.000 0.032 0.000
#> SRR1947564 1 0.6161 -0.16533 0.444 0.424 0.000 0.132 0.000
#> SRR1947563 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947562 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947565 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 4 0.4549 0.80942 0.464 0.008 0.000 0.528 0.000
#> SRR1947560 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947561 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947557 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947558 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 4 0.0000 0.25887 0.000 0.000 0.000 1.000 0.000
#> SRR1947553 1 0.6405 -0.21852 0.444 0.384 0.000 0.172 0.000
#> SRR1947554 1 0.4161 0.55404 0.608 0.000 0.000 0.392 0.000
#> SRR1947555 4 0.4552 0.16356 0.008 0.468 0.000 0.524 0.000
#> SRR1947550 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947552 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947549 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947551 5 0.0000 0.95084 0.000 0.000 0.000 0.000 1.000
#> SRR1947548 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947506 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947507 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947504 1 0.4060 0.52681 0.640 0.000 0.000 0.360 0.000
#> SRR1947503 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947502 2 0.0162 0.89210 0.004 0.996 0.000 0.000 0.000
#> SRR1947501 4 0.4420 0.81653 0.448 0.004 0.000 0.548 0.000
#> SRR1947499 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947508 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947505 4 0.4473 0.77727 0.412 0.008 0.000 0.580 0.000
#> SRR1947497 2 0.0290 0.89029 0.008 0.992 0.000 0.000 0.000
#> SRR1947496 1 0.4300 0.58110 0.524 0.000 0.000 0.476 0.000
#> SRR1947495 2 0.0404 0.88667 0.012 0.988 0.000 0.000 0.000
#> SRR1947494 4 0.4182 0.76671 0.400 0.000 0.000 0.600 0.000
#> SRR1947493 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
#> SRR1947492 1 0.4278 0.56595 0.548 0.000 0.000 0.452 0.000
#> SRR1947500 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947491 4 0.4268 0.81909 0.444 0.000 0.000 0.556 0.000
#> SRR1947490 1 0.4278 0.56595 0.548 0.000 0.000 0.452 0.000
#> SRR1947489 3 0.0000 0.97158 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.3854 -0.333 0.000 0.000 0.536 0.000 0.000 0.464
#> SRR1947546 4 0.0146 0.897 0.000 0.004 0.000 0.996 0.000 0.000
#> SRR1947545 1 0.3555 0.726 0.776 0.000 0.000 0.184 0.000 0.040
#> SRR1947544 1 0.3709 0.703 0.756 0.000 0.000 0.204 0.000 0.040
#> SRR1947542 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947541 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947540 4 0.2783 0.819 0.000 0.016 0.000 0.836 0.000 0.148
#> SRR1947539 3 0.2793 0.650 0.000 0.000 0.800 0.000 0.200 0.000
#> SRR1947538 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947537 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947536 6 0.3163 0.924 0.000 0.000 0.232 0.000 0.004 0.764
#> SRR1947535 3 0.0146 0.927 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947534 1 0.4358 0.715 0.712 0.092 0.000 0.196 0.000 0.000
#> SRR1947533 2 0.0146 0.936 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947532 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947531 4 0.2783 0.819 0.000 0.016 0.000 0.836 0.000 0.148
#> SRR1947530 6 0.2883 0.930 0.000 0.000 0.212 0.000 0.000 0.788
#> SRR1947529 4 0.3620 0.431 0.000 0.352 0.000 0.648 0.000 0.000
#> SRR1947528 3 0.3482 0.294 0.000 0.000 0.684 0.000 0.000 0.316
#> SRR1947527 2 0.2053 0.860 0.000 0.888 0.000 0.108 0.000 0.004
#> SRR1947526 2 0.0000 0.935 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947525 4 0.0777 0.893 0.000 0.004 0.000 0.972 0.000 0.024
#> SRR1947524 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 4 0.3089 0.814 0.004 0.008 0.000 0.800 0.000 0.188
#> SRR1947521 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0146 0.935 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947519 3 0.0146 0.928 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947518 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947517 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0291 0.936 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1947515 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947514 2 0.0291 0.936 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1947513 1 0.2941 0.756 0.780 0.000 0.000 0.220 0.000 0.000
#> SRR1947512 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.935 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.0146 0.897 0.000 0.004 0.000 0.996 0.000 0.000
#> SRR1947611 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947509 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947644 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.2134 0.882 0.000 0.904 0.000 0.044 0.000 0.052
#> SRR1947642 3 0.0363 0.926 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947640 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947641 3 0.0146 0.928 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947639 4 0.1327 0.866 0.000 0.064 0.000 0.936 0.000 0.000
#> SRR1947638 1 0.3171 0.762 0.784 0.000 0.000 0.204 0.000 0.012
#> SRR1947637 5 0.0547 0.971 0.000 0.000 0.020 0.000 0.980 0.000
#> SRR1947636 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947635 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947634 2 0.0146 0.935 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947633 3 0.3737 0.326 0.000 0.000 0.608 0.000 0.392 0.000
#> SRR1947632 4 0.1082 0.894 0.000 0.004 0.000 0.956 0.000 0.040
#> SRR1947631 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 2 0.0146 0.935 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947627 6 0.2996 0.926 0.000 0.000 0.228 0.000 0.000 0.772
#> SRR1947628 4 0.2980 0.817 0.000 0.012 0.000 0.808 0.000 0.180
#> SRR1947626 2 0.2219 0.832 0.000 0.864 0.000 0.136 0.000 0.000
#> SRR1947625 3 0.0146 0.927 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947624 2 0.0146 0.935 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947623 1 0.2664 0.781 0.816 0.000 0.000 0.184 0.000 0.000
#> SRR1947622 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0146 0.936 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947620 1 0.3738 0.754 0.752 0.000 0.000 0.208 0.000 0.040
#> SRR1947619 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947617 2 0.0790 0.922 0.000 0.968 0.000 0.032 0.000 0.000
#> SRR1947618 1 0.4023 0.776 0.752 0.008 0.000 0.052 0.000 0.188
#> SRR1947616 4 0.3786 0.757 0.000 0.168 0.000 0.768 0.000 0.064
#> SRR1947615 3 0.0713 0.913 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1947614 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0405 0.852 0.988 0.000 0.000 0.008 0.000 0.004
#> SRR1947610 4 0.0937 0.881 0.000 0.040 0.000 0.960 0.000 0.000
#> SRR1947612 2 0.1556 0.886 0.000 0.920 0.000 0.080 0.000 0.000
#> SRR1947609 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947608 3 0.0146 0.927 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947606 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947607 1 0.3017 0.810 0.848 0.052 0.000 0.004 0.000 0.096
#> SRR1947604 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947605 1 0.1265 0.843 0.948 0.000 0.000 0.008 0.000 0.044
#> SRR1947603 4 0.3337 0.620 0.000 0.260 0.000 0.736 0.000 0.004
#> SRR1947602 6 0.2854 0.928 0.000 0.000 0.208 0.000 0.000 0.792
#> SRR1947600 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0000 0.935 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 4 0.3386 0.804 0.016 0.008 0.000 0.788 0.000 0.188
#> SRR1947599 4 0.1082 0.893 0.004 0.000 0.000 0.956 0.000 0.040
#> SRR1947597 4 0.2664 0.740 0.000 0.184 0.000 0.816 0.000 0.000
#> SRR1947596 4 0.1564 0.886 0.024 0.000 0.000 0.936 0.000 0.040
#> SRR1947595 4 0.3134 0.812 0.016 0.012 0.000 0.824 0.000 0.148
#> SRR1947594 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0363 0.926 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947591 2 0.0291 0.936 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1947590 4 0.1794 0.880 0.036 0.000 0.000 0.924 0.000 0.040
#> SRR1947588 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0146 0.928 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947586 2 0.2558 0.809 0.000 0.840 0.000 0.156 0.000 0.004
#> SRR1947585 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 1 0.0363 0.850 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1947583 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947582 1 0.3534 0.796 0.792 0.008 0.000 0.032 0.000 0.168
#> SRR1947580 2 0.0000 0.935 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0146 0.927 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947579 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 4 0.3344 0.800 0.000 0.044 0.000 0.804 0.000 0.152
#> SRR1947573 3 0.0363 0.927 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947574 4 0.6326 0.471 0.080 0.252 0.000 0.548 0.000 0.120
#> SRR1947571 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947577 1 0.3925 0.727 0.724 0.000 0.000 0.236 0.000 0.040
#> SRR1947570 6 0.3868 0.385 0.000 0.000 0.496 0.000 0.000 0.504
#> SRR1947569 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.1863 0.893 0.000 0.920 0.000 0.044 0.000 0.036
#> SRR1947567 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947568 2 0.2793 0.755 0.000 0.800 0.000 0.200 0.000 0.000
#> SRR1947564 4 0.3862 0.321 0.000 0.388 0.000 0.608 0.000 0.004
#> SRR1947563 3 0.0146 0.927 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947562 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947565 3 0.0458 0.925 0.000 0.000 0.984 0.000 0.000 0.016
#> SRR1947559 4 0.0146 0.898 0.000 0.004 0.000 0.996 0.000 0.000
#> SRR1947560 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0291 0.936 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1947557 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 1 0.4493 0.409 0.596 0.000 0.000 0.364 0.000 0.040
#> SRR1947553 4 0.1663 0.847 0.000 0.088 0.000 0.912 0.000 0.000
#> SRR1947554 1 0.2993 0.808 0.844 0.008 0.000 0.028 0.000 0.120
#> SRR1947555 2 0.4428 0.597 0.000 0.684 0.000 0.244 0.000 0.072
#> SRR1947550 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947552 4 0.1082 0.893 0.004 0.000 0.000 0.956 0.000 0.040
#> SRR1947549 3 0.0363 0.926 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947551 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947506 6 0.2941 0.930 0.000 0.000 0.220 0.000 0.000 0.780
#> SRR1947507 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0146 0.851 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947503 4 0.0937 0.894 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947502 2 0.0146 0.936 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947501 4 0.0790 0.897 0.000 0.000 0.000 0.968 0.000 0.032
#> SRR1947499 6 0.2883 0.930 0.000 0.000 0.212 0.000 0.000 0.788
#> SRR1947498 3 0.0000 0.928 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947508 6 0.3309 0.874 0.000 0.000 0.280 0.000 0.000 0.720
#> SRR1947505 4 0.3296 0.808 0.012 0.008 0.000 0.792 0.000 0.188
#> SRR1947497 2 0.1082 0.918 0.000 0.956 0.000 0.004 0.000 0.040
#> SRR1947496 1 0.0000 0.850 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0291 0.936 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1947494 4 0.3386 0.804 0.016 0.008 0.000 0.788 0.000 0.188
#> SRR1947493 6 0.2854 0.928 0.000 0.000 0.208 0.000 0.000 0.792
#> SRR1947492 1 0.0291 0.851 0.992 0.000 0.000 0.004 0.000 0.004
#> SRR1947500 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947491 4 0.0000 0.898 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947490 1 0.1036 0.848 0.964 0.004 0.000 0.008 0.000 0.024
#> SRR1947489 3 0.0713 0.913 0.000 0.000 0.972 0.000 0.000 0.028
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 15148 rows and 152 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 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 0.816 0.915 0.962 0.4712 0.528 0.528
#> 3 3 0.973 0.936 0.974 0.4036 0.699 0.484
#> 4 4 0.751 0.738 0.889 0.1044 0.855 0.614
#> 5 5 0.683 0.651 0.831 0.0681 0.867 0.572
#> 6 6 0.702 0.621 0.800 0.0462 0.895 0.586
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
#> SRR1947547 1 0.0000 0.9455 1.000 0.000
#> SRR1947546 2 0.0000 0.9677 0.000 1.000
#> SRR1947545 1 0.0000 0.9455 1.000 0.000
#> SRR1947544 1 0.0000 0.9455 1.000 0.000
#> SRR1947542 2 0.0000 0.9677 0.000 1.000
#> SRR1947541 1 0.5842 0.8384 0.860 0.140
#> SRR1947540 2 0.0000 0.9677 0.000 1.000
#> SRR1947539 2 0.0000 0.9677 0.000 1.000
#> SRR1947538 2 0.9661 0.3571 0.392 0.608
#> SRR1947537 2 0.0672 0.9619 0.008 0.992
#> SRR1947536 1 0.7219 0.7727 0.800 0.200
#> SRR1947535 2 0.0000 0.9677 0.000 1.000
#> SRR1947534 1 0.0000 0.9455 1.000 0.000
#> SRR1947533 2 0.0000 0.9677 0.000 1.000
#> SRR1947532 1 0.0000 0.9455 1.000 0.000
#> SRR1947531 2 0.0000 0.9677 0.000 1.000
#> SRR1947530 1 0.0000 0.9455 1.000 0.000
#> SRR1947529 2 0.0000 0.9677 0.000 1.000
#> SRR1947528 1 0.1184 0.9365 0.984 0.016
#> SRR1947527 2 0.0000 0.9677 0.000 1.000
#> SRR1947526 2 0.0000 0.9677 0.000 1.000
#> SRR1947525 2 0.1414 0.9525 0.020 0.980
#> SRR1947524 2 0.0000 0.9677 0.000 1.000
#> SRR1947523 2 0.3114 0.9178 0.056 0.944
#> SRR1947521 2 0.0000 0.9677 0.000 1.000
#> SRR1947520 2 0.0000 0.9677 0.000 1.000
#> SRR1947519 2 0.9248 0.4578 0.340 0.660
#> SRR1947518 1 0.6048 0.8209 0.852 0.148
#> SRR1947517 2 0.8555 0.5928 0.280 0.720
#> SRR1947516 2 0.0000 0.9677 0.000 1.000
#> SRR1947515 1 0.8909 0.5655 0.692 0.308
#> SRR1947514 2 0.0000 0.9677 0.000 1.000
#> SRR1947513 1 0.0000 0.9455 1.000 0.000
#> SRR1947512 1 0.0000 0.9455 1.000 0.000
#> SRR1947511 2 0.0000 0.9677 0.000 1.000
#> SRR1947510 2 0.0000 0.9677 0.000 1.000
#> SRR1947572 1 0.6438 0.8016 0.836 0.164
#> SRR1947611 2 0.0000 0.9677 0.000 1.000
#> SRR1947509 1 0.7528 0.7520 0.784 0.216
#> SRR1947644 2 0.0000 0.9677 0.000 1.000
#> SRR1947643 2 0.0000 0.9677 0.000 1.000
#> SRR1947642 2 0.1843 0.9447 0.028 0.972
#> SRR1947640 1 0.9993 0.0753 0.516 0.484
#> SRR1947641 2 0.0000 0.9677 0.000 1.000
#> SRR1947639 2 0.7219 0.7443 0.200 0.800
#> SRR1947638 1 0.0000 0.9455 1.000 0.000
#> SRR1947637 2 0.0000 0.9677 0.000 1.000
#> SRR1947636 2 0.4562 0.8752 0.096 0.904
#> SRR1947635 2 0.0000 0.9677 0.000 1.000
#> SRR1947634 2 0.0000 0.9677 0.000 1.000
#> SRR1947633 2 0.0000 0.9677 0.000 1.000
#> SRR1947632 2 0.0000 0.9677 0.000 1.000
#> SRR1947631 2 0.0000 0.9677 0.000 1.000
#> SRR1947629 2 0.0000 0.9677 0.000 1.000
#> SRR1947630 2 0.0000 0.9677 0.000 1.000
#> SRR1947627 1 0.7219 0.7727 0.800 0.200
#> SRR1947628 2 0.0000 0.9677 0.000 1.000
#> SRR1947626 2 0.0000 0.9677 0.000 1.000
#> SRR1947625 2 0.0000 0.9677 0.000 1.000
#> SRR1947624 2 0.0000 0.9677 0.000 1.000
#> SRR1947623 1 0.0000 0.9455 1.000 0.000
#> SRR1947622 2 0.0000 0.9677 0.000 1.000
#> SRR1947621 2 0.0000 0.9677 0.000 1.000
#> SRR1947620 1 0.0000 0.9455 1.000 0.000
#> SRR1947619 2 0.3274 0.9146 0.060 0.940
#> SRR1947617 2 0.0000 0.9677 0.000 1.000
#> SRR1947618 1 0.0000 0.9455 1.000 0.000
#> SRR1947616 2 0.0000 0.9677 0.000 1.000
#> SRR1947615 1 0.1184 0.9364 0.984 0.016
#> SRR1947614 2 0.0000 0.9677 0.000 1.000
#> SRR1947613 1 0.0000 0.9455 1.000 0.000
#> SRR1947610 2 0.1414 0.9524 0.020 0.980
#> SRR1947612 2 0.0000 0.9677 0.000 1.000
#> SRR1947609 1 0.0000 0.9455 1.000 0.000
#> SRR1947608 2 0.0000 0.9677 0.000 1.000
#> SRR1947606 1 0.6148 0.8262 0.848 0.152
#> SRR1947607 1 0.0000 0.9455 1.000 0.000
#> SRR1947604 1 0.1414 0.9332 0.980 0.020
#> SRR1947605 1 0.0000 0.9455 1.000 0.000
#> SRR1947603 2 0.0000 0.9677 0.000 1.000
#> SRR1947602 1 0.0000 0.9455 1.000 0.000
#> SRR1947600 2 0.0000 0.9677 0.000 1.000
#> SRR1947601 2 0.0000 0.9677 0.000 1.000
#> SRR1947598 2 0.0000 0.9677 0.000 1.000
#> SRR1947599 1 0.0000 0.9455 1.000 0.000
#> SRR1947597 2 0.0000 0.9677 0.000 1.000
#> SRR1947596 1 0.0000 0.9455 1.000 0.000
#> SRR1947595 2 0.0000 0.9677 0.000 1.000
#> SRR1947594 1 0.0000 0.9455 1.000 0.000
#> SRR1947592 2 0.0000 0.9677 0.000 1.000
#> SRR1947591 2 0.0000 0.9677 0.000 1.000
#> SRR1947590 1 0.0000 0.9455 1.000 0.000
#> SRR1947588 1 0.0000 0.9455 1.000 0.000
#> SRR1947587 1 0.7674 0.7420 0.776 0.224
#> SRR1947586 2 0.0000 0.9677 0.000 1.000
#> SRR1947585 2 0.0000 0.9677 0.000 1.000
#> SRR1947584 1 0.0000 0.9455 1.000 0.000
#> SRR1947583 2 0.0672 0.9618 0.008 0.992
#> SRR1947582 1 0.0000 0.9455 1.000 0.000
#> SRR1947580 2 0.0000 0.9677 0.000 1.000
#> SRR1947581 1 0.0000 0.9455 1.000 0.000
#> SRR1947576 2 0.0000 0.9677 0.000 1.000
#> SRR1947575 2 0.0000 0.9677 0.000 1.000
#> SRR1947579 2 0.0000 0.9677 0.000 1.000
#> SRR1947578 2 0.0000 0.9677 0.000 1.000
#> SRR1947573 2 0.0000 0.9677 0.000 1.000
#> SRR1947574 1 0.6531 0.8085 0.832 0.168
#> SRR1947571 2 0.8327 0.6431 0.264 0.736
#> SRR1947577 1 0.0000 0.9455 1.000 0.000
#> SRR1947570 1 0.0000 0.9455 1.000 0.000
#> SRR1947569 2 0.0000 0.9677 0.000 1.000
#> SRR1947566 2 0.0000 0.9677 0.000 1.000
#> SRR1947567 2 0.0000 0.9677 0.000 1.000
#> SRR1947568 2 0.8207 0.6577 0.256 0.744
#> SRR1947564 2 0.0000 0.9677 0.000 1.000
#> SRR1947563 2 0.0000 0.9677 0.000 1.000
#> SRR1947562 2 0.1184 0.9556 0.016 0.984
#> SRR1947565 2 0.0000 0.9677 0.000 1.000
#> SRR1947559 2 0.0000 0.9677 0.000 1.000
#> SRR1947560 2 0.0000 0.9677 0.000 1.000
#> SRR1947561 2 0.0000 0.9677 0.000 1.000
#> SRR1947557 1 0.0000 0.9455 1.000 0.000
#> SRR1947558 2 0.0000 0.9677 0.000 1.000
#> SRR1947556 1 0.0000 0.9455 1.000 0.000
#> SRR1947553 2 0.0000 0.9677 0.000 1.000
#> SRR1947554 1 0.0000 0.9455 1.000 0.000
#> SRR1947555 2 0.0000 0.9677 0.000 1.000
#> SRR1947550 2 0.1414 0.9525 0.020 0.980
#> SRR1947552 1 0.0000 0.9455 1.000 0.000
#> SRR1947549 2 0.0000 0.9677 0.000 1.000
#> SRR1947551 2 0.0000 0.9677 0.000 1.000
#> SRR1947548 2 0.6887 0.7685 0.184 0.816
#> SRR1947506 1 0.0000 0.9455 1.000 0.000
#> SRR1947507 1 0.0000 0.9455 1.000 0.000
#> SRR1947504 1 0.0000 0.9455 1.000 0.000
#> SRR1947503 1 0.0000 0.9455 1.000 0.000
#> SRR1947502 2 0.0000 0.9677 0.000 1.000
#> SRR1947501 2 0.0000 0.9677 0.000 1.000
#> SRR1947499 1 0.0000 0.9455 1.000 0.000
#> SRR1947498 2 0.6623 0.7765 0.172 0.828
#> SRR1947508 1 0.7219 0.7727 0.800 0.200
#> SRR1947505 2 0.0672 0.9617 0.008 0.992
#> SRR1947497 2 0.0000 0.9677 0.000 1.000
#> SRR1947496 1 0.0000 0.9455 1.000 0.000
#> SRR1947495 2 0.0000 0.9677 0.000 1.000
#> SRR1947494 1 0.7883 0.7225 0.764 0.236
#> SRR1947493 1 0.0000 0.9455 1.000 0.000
#> SRR1947492 1 0.0000 0.9455 1.000 0.000
#> SRR1947500 2 0.0000 0.9677 0.000 1.000
#> SRR1947491 2 0.9608 0.3432 0.384 0.616
#> SRR1947490 1 0.0000 0.9455 1.000 0.000
#> SRR1947489 1 0.0376 0.9433 0.996 0.004
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.6260 0.189 0.448 0.000 0.552
#> SRR1947546 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947541 3 0.0424 0.966 0.008 0.000 0.992
#> SRR1947540 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947539 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947538 2 0.0892 0.963 0.020 0.980 0.000
#> SRR1947537 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947536 3 0.1529 0.942 0.040 0.000 0.960
#> SRR1947535 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947534 1 0.6140 0.346 0.596 0.404 0.000
#> SRR1947533 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947532 1 0.1529 0.932 0.960 0.040 0.000
#> SRR1947531 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947530 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947529 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947528 3 0.0892 0.958 0.020 0.000 0.980
#> SRR1947527 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947523 2 0.1964 0.927 0.056 0.944 0.000
#> SRR1947521 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947518 2 0.4842 0.700 0.224 0.776 0.000
#> SRR1947517 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947515 1 0.4370 0.857 0.868 0.076 0.056
#> SRR1947514 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947572 2 0.6111 0.324 0.396 0.604 0.000
#> SRR1947611 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947509 3 0.1031 0.955 0.024 0.000 0.976
#> SRR1947644 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947640 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947641 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947639 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947638 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947637 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947632 2 0.0747 0.968 0.000 0.984 0.016
#> SRR1947631 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947627 3 0.0747 0.961 0.016 0.000 0.984
#> SRR1947628 2 0.0424 0.974 0.000 0.992 0.008
#> SRR1947626 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947624 2 0.0237 0.977 0.000 0.996 0.004
#> SRR1947623 1 0.1411 0.936 0.964 0.036 0.000
#> SRR1947622 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947619 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947616 2 0.0892 0.965 0.000 0.980 0.020
#> SRR1947615 3 0.2959 0.882 0.100 0.000 0.900
#> SRR1947614 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947609 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947606 3 0.0592 0.964 0.012 0.000 0.988
#> SRR1947607 1 0.0892 0.949 0.980 0.020 0.000
#> SRR1947604 1 0.6280 0.180 0.540 0.460 0.000
#> SRR1947605 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947603 2 0.0424 0.974 0.000 0.992 0.008
#> SRR1947602 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947600 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947601 2 0.0237 0.977 0.000 0.996 0.004
#> SRR1947598 3 0.6432 0.227 0.004 0.428 0.568
#> SRR1947599 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947597 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947596 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947595 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947594 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947590 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947588 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947587 3 0.0237 0.969 0.004 0.000 0.996
#> SRR1947586 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947583 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947582 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947578 2 0.0592 0.971 0.000 0.988 0.012
#> SRR1947573 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947574 2 0.1289 0.952 0.032 0.968 0.000
#> SRR1947571 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947577 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947570 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947569 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947566 2 0.0424 0.974 0.000 0.992 0.008
#> SRR1947567 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947568 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947564 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947560 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947554 1 0.0592 0.954 0.988 0.012 0.000
#> SRR1947555 2 0.0747 0.968 0.000 0.984 0.016
#> SRR1947550 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947552 1 0.1643 0.928 0.956 0.044 0.000
#> SRR1947549 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947551 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947548 2 0.1015 0.967 0.012 0.980 0.008
#> SRR1947506 1 0.2959 0.866 0.900 0.000 0.100
#> SRR1947507 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947504 1 0.0592 0.954 0.988 0.012 0.000
#> SRR1947503 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947501 2 0.0747 0.968 0.000 0.984 0.016
#> SRR1947499 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.971 0.000 0.000 1.000
#> SRR1947508 3 0.1860 0.931 0.052 0.000 0.948
#> SRR1947505 2 0.6819 0.473 0.028 0.644 0.328
#> SRR1947497 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947494 1 0.4452 0.759 0.808 0.192 0.000
#> SRR1947493 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.979 0.000 1.000 0.000
#> SRR1947491 2 0.1031 0.960 0.024 0.976 0.000
#> SRR1947490 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1947489 3 0.3551 0.845 0.132 0.000 0.868
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 4 0.4941 0.134 0.436 0.000 0.000 0.564
#> SRR1947546 2 0.2973 0.778 0.000 0.856 0.000 0.144
#> SRR1947545 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.4907 0.361 0.000 0.420 0.000 0.580
#> SRR1947541 4 0.4546 0.402 0.012 0.000 0.256 0.732
#> SRR1947540 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947539 3 0.3074 0.761 0.000 0.000 0.848 0.152
#> SRR1947538 2 0.5368 0.350 0.024 0.636 0.000 0.340
#> SRR1947537 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947536 3 0.5569 0.639 0.044 0.000 0.660 0.296
#> SRR1947535 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947534 1 0.4955 0.187 0.556 0.444 0.000 0.000
#> SRR1947533 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.5100 0.628 0.076 0.168 0.000 0.756
#> SRR1947531 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947530 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947529 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947528 4 0.7113 -0.301 0.128 0.000 0.416 0.456
#> SRR1947527 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0336 0.921 0.000 0.992 0.008 0.000
#> SRR1947525 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947524 3 0.4972 0.420 0.000 0.000 0.544 0.456
#> SRR1947523 4 0.4830 0.424 0.000 0.392 0.000 0.608
#> SRR1947521 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.4304 0.642 0.000 0.716 0.284 0.000
#> SRR1947519 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947518 2 0.4585 0.493 0.332 0.668 0.000 0.000
#> SRR1947517 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.4646 0.647 0.084 0.120 0.000 0.796
#> SRR1947514 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.3649 0.748 0.000 0.796 0.204 0.000
#> SRR1947510 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947572 1 0.4941 0.205 0.564 0.436 0.000 0.000
#> SRR1947611 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947509 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947644 3 0.1211 0.806 0.000 0.000 0.960 0.040
#> SRR1947643 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947642 4 0.0707 0.704 0.000 0.000 0.020 0.980
#> SRR1947640 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947641 4 0.2868 0.596 0.000 0.000 0.136 0.864
#> SRR1947639 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947638 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947637 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947636 4 0.1792 0.672 0.000 0.000 0.068 0.932
#> SRR1947635 2 0.1940 0.859 0.000 0.924 0.000 0.076
#> SRR1947634 2 0.3688 0.743 0.000 0.792 0.208 0.000
#> SRR1947633 3 0.3610 0.734 0.000 0.000 0.800 0.200
#> SRR1947632 4 0.4454 0.566 0.000 0.308 0.000 0.692
#> SRR1947631 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947629 4 0.2704 0.618 0.000 0.000 0.124 0.876
#> SRR1947630 2 0.4948 0.348 0.000 0.560 0.440 0.000
#> SRR1947627 3 0.5231 0.649 0.028 0.000 0.676 0.296
#> SRR1947628 4 0.4977 0.259 0.000 0.460 0.000 0.540
#> SRR1947626 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947625 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947624 2 0.4761 0.494 0.000 0.628 0.372 0.000
#> SRR1947623 1 0.0707 0.899 0.980 0.020 0.000 0.000
#> SRR1947622 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947619 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947615 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947614 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947610 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947612 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.1302 0.883 0.956 0.000 0.000 0.044
#> SRR1947608 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947606 4 0.4999 0.208 0.012 0.000 0.328 0.660
#> SRR1947607 1 0.0336 0.910 0.992 0.008 0.000 0.000
#> SRR1947604 4 0.5659 0.450 0.032 0.368 0.000 0.600
#> SRR1947605 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947603 2 0.0469 0.918 0.000 0.988 0.000 0.012
#> SRR1947602 1 0.1716 0.858 0.936 0.000 0.000 0.064
#> SRR1947600 4 0.4941 -0.151 0.000 0.000 0.436 0.564
#> SRR1947601 2 0.3123 0.799 0.000 0.844 0.156 0.000
#> SRR1947598 4 0.3751 0.640 0.004 0.196 0.000 0.800
#> SRR1947599 1 0.4624 0.462 0.660 0.000 0.000 0.340
#> SRR1947597 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947596 1 0.4679 0.428 0.648 0.000 0.000 0.352
#> SRR1947595 2 0.3444 0.770 0.000 0.816 0.184 0.000
#> SRR1947594 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947592 4 0.4543 0.256 0.000 0.000 0.324 0.676
#> SRR1947591 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.4500 0.449 0.316 0.000 0.000 0.684
#> SRR1947588 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947587 4 0.0592 0.706 0.000 0.000 0.016 0.984
#> SRR1947586 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947585 3 0.4907 0.496 0.000 0.000 0.580 0.420
#> SRR1947584 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947583 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947582 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947580 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947581 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947575 4 0.0188 0.712 0.000 0.000 0.004 0.996
#> SRR1947579 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.0336 0.921 0.000 0.992 0.000 0.008
#> SRR1947573 3 0.4866 0.523 0.000 0.000 0.596 0.404
#> SRR1947574 2 0.3528 0.733 0.192 0.808 0.000 0.000
#> SRR1947571 4 0.4972 0.271 0.000 0.456 0.000 0.544
#> SRR1947577 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947570 1 0.4585 0.479 0.668 0.000 0.000 0.332
#> SRR1947569 4 0.0707 0.705 0.000 0.000 0.020 0.980
#> SRR1947566 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947567 2 0.0336 0.921 0.000 0.992 0.000 0.008
#> SRR1947568 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947564 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947563 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947562 2 0.4843 0.222 0.000 0.604 0.000 0.396
#> SRR1947565 4 0.1637 0.681 0.000 0.000 0.060 0.940
#> SRR1947559 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.0000 0.815 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947558 4 0.0000 0.713 0.000 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947553 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947554 1 0.0336 0.910 0.992 0.008 0.000 0.000
#> SRR1947555 2 0.0188 0.923 0.000 0.996 0.000 0.004
#> SRR1947550 2 0.0188 0.923 0.000 0.996 0.000 0.004
#> SRR1947552 4 0.5313 0.319 0.376 0.016 0.000 0.608
#> SRR1947549 4 0.3219 0.574 0.000 0.000 0.164 0.836
#> SRR1947551 3 0.0469 0.813 0.000 0.000 0.988 0.012
#> SRR1947548 4 0.3837 0.624 0.000 0.224 0.000 0.776
#> SRR1947506 1 0.2647 0.797 0.880 0.000 0.000 0.120
#> SRR1947507 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947503 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947502 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947501 4 0.4431 0.569 0.000 0.304 0.000 0.696
#> SRR1947499 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947498 3 0.4866 0.527 0.000 0.000 0.596 0.404
#> SRR1947508 3 0.7458 0.377 0.176 0.000 0.444 0.380
#> SRR1947505 4 0.4134 0.601 0.000 0.260 0.000 0.740
#> SRR1947497 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947494 1 0.5138 0.316 0.600 0.008 0.000 0.392
#> SRR1947493 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947500 2 0.0000 0.926 0.000 1.000 0.000 0.000
#> SRR1947491 2 0.0592 0.915 0.016 0.984 0.000 0.000
#> SRR1947490 1 0.0000 0.916 1.000 0.000 0.000 0.000
#> SRR1947489 4 0.0000 0.713 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 4 0.2648 0.6666 0.000 0.000 0.152 0.848 0.000
#> SRR1947546 2 0.3906 0.7838 0.000 0.804 0.084 0.112 0.000
#> SRR1947545 1 0.0703 0.8808 0.976 0.000 0.000 0.024 0.000
#> SRR1947544 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 3 0.4901 0.5547 0.000 0.168 0.716 0.116 0.000
#> SRR1947541 4 0.3318 0.6413 0.000 0.000 0.192 0.800 0.008
#> SRR1947540 2 0.2771 0.8190 0.000 0.860 0.012 0.128 0.000
#> SRR1947539 5 0.3992 0.6342 0.000 0.000 0.268 0.012 0.720
#> SRR1947538 1 0.7639 0.1029 0.444 0.116 0.320 0.120 0.000
#> SRR1947537 3 0.0404 0.6635 0.000 0.000 0.988 0.012 0.000
#> SRR1947536 4 0.3318 0.6348 0.000 0.000 0.192 0.800 0.008
#> SRR1947535 3 0.1043 0.6627 0.000 0.000 0.960 0.040 0.000
#> SRR1947534 2 0.4305 0.0626 0.488 0.512 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 3 0.6118 0.5108 0.084 0.060 0.648 0.208 0.000
#> SRR1947531 2 0.2612 0.8238 0.000 0.868 0.008 0.124 0.000
#> SRR1947530 4 0.2813 0.6840 0.168 0.000 0.000 0.832 0.000
#> SRR1947529 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947528 4 0.5589 0.4537 0.008 0.000 0.296 0.616 0.080
#> SRR1947527 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 2 0.5460 0.5376 0.196 0.656 0.148 0.000 0.000
#> SRR1947524 5 0.6114 0.4555 0.000 0.000 0.312 0.152 0.536
#> SRR1947523 4 0.4866 0.1594 0.000 0.392 0.028 0.580 0.000
#> SRR1947521 5 0.0451 0.7482 0.000 0.000 0.008 0.004 0.988
#> SRR1947520 2 0.3661 0.6644 0.000 0.724 0.000 0.000 0.276
#> SRR1947519 4 0.3452 0.5943 0.000 0.000 0.244 0.756 0.000
#> SRR1947518 1 0.1386 0.8605 0.952 0.032 0.000 0.016 0.000
#> SRR1947517 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947516 2 0.0162 0.8739 0.000 0.996 0.004 0.000 0.000
#> SRR1947515 3 0.4407 0.5789 0.004 0.064 0.760 0.172 0.000
#> SRR1947514 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 4 0.5480 0.4734 0.288 0.096 0.000 0.616 0.000
#> SRR1947512 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1908 0.8296 0.000 0.908 0.000 0.000 0.092
#> SRR1947510 5 0.0162 0.7479 0.000 0.000 0.004 0.000 0.996
#> SRR1947572 1 0.0162 0.8942 0.996 0.004 0.000 0.000 0.000
#> SRR1947611 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947509 5 0.0609 0.7460 0.000 0.000 0.000 0.020 0.980
#> SRR1947644 5 0.3596 0.6763 0.000 0.000 0.212 0.012 0.776
#> SRR1947643 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947642 4 0.3003 0.6480 0.000 0.000 0.188 0.812 0.000
#> SRR1947640 2 0.2719 0.8117 0.000 0.852 0.004 0.144 0.000
#> SRR1947641 3 0.5825 0.1789 0.000 0.000 0.536 0.360 0.104
#> SRR1947639 2 0.6691 0.2208 0.352 0.476 0.156 0.016 0.000
#> SRR1947638 4 0.5939 0.4798 0.276 0.148 0.000 0.576 0.000
#> SRR1947637 5 0.2516 0.7133 0.000 0.000 0.140 0.000 0.860
#> SRR1947636 3 0.2331 0.6203 0.000 0.000 0.900 0.020 0.080
#> SRR1947635 2 0.2516 0.8171 0.000 0.860 0.000 0.140 0.000
#> SRR1947634 2 0.1792 0.8354 0.000 0.916 0.000 0.000 0.084
#> SRR1947633 5 0.4157 0.6326 0.000 0.000 0.264 0.020 0.716
#> SRR1947632 3 0.4723 0.5707 0.000 0.136 0.736 0.128 0.000
#> SRR1947631 4 0.4161 0.3676 0.000 0.000 0.392 0.608 0.000
#> SRR1947629 3 0.4871 0.4080 0.000 0.000 0.704 0.084 0.212
#> SRR1947630 2 0.4305 0.2387 0.000 0.512 0.000 0.000 0.488
#> SRR1947627 4 0.6655 -0.1032 0.000 0.000 0.228 0.404 0.368
#> SRR1947628 2 0.3081 0.8007 0.000 0.832 0.012 0.156 0.000
#> SRR1947626 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 3 0.1792 0.6498 0.000 0.000 0.916 0.084 0.000
#> SRR1947624 5 0.4306 -0.2365 0.000 0.492 0.000 0.000 0.508
#> SRR1947623 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.0898 0.8701 0.000 0.972 0.020 0.008 0.000
#> SRR1947621 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 4 0.3684 0.5791 0.280 0.000 0.000 0.720 0.000
#> SRR1947619 3 0.0404 0.6635 0.000 0.000 0.988 0.012 0.000
#> SRR1947617 2 0.0162 0.8739 0.000 0.996 0.004 0.000 0.000
#> SRR1947618 4 0.3241 0.6666 0.144 0.000 0.000 0.832 0.024
#> SRR1947616 2 0.1954 0.8605 0.000 0.932 0.008 0.032 0.028
#> SRR1947615 4 0.0880 0.6680 0.000 0.000 0.032 0.968 0.000
#> SRR1947614 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 2 0.0162 0.8739 0.000 0.996 0.000 0.004 0.000
#> SRR1947612 2 0.0290 0.8732 0.000 0.992 0.008 0.000 0.000
#> SRR1947609 1 0.3686 0.6959 0.780 0.012 0.004 0.204 0.000
#> SRR1947608 3 0.0404 0.6652 0.000 0.000 0.988 0.012 0.000
#> SRR1947606 3 0.6884 -0.0340 0.036 0.000 0.488 0.136 0.340
#> SRR1947607 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 3 0.8271 0.3014 0.208 0.208 0.400 0.184 0.000
#> SRR1947605 1 0.3109 0.6733 0.800 0.000 0.000 0.200 0.000
#> SRR1947603 2 0.4210 0.3196 0.000 0.588 0.412 0.000 0.000
#> SRR1947602 4 0.3193 0.6785 0.028 0.000 0.132 0.840 0.000
#> SRR1947600 5 0.6248 0.3116 0.000 0.000 0.384 0.148 0.468
#> SRR1947601 2 0.0963 0.8640 0.000 0.964 0.000 0.000 0.036
#> SRR1947598 4 0.5557 -0.2838 0.000 0.068 0.464 0.468 0.000
#> SRR1947599 4 0.1943 0.6693 0.056 0.020 0.000 0.924 0.000
#> SRR1947597 2 0.0609 0.8700 0.000 0.980 0.020 0.000 0.000
#> SRR1947596 1 0.2017 0.8293 0.912 0.000 0.080 0.008 0.000
#> SRR1947595 2 0.3563 0.7454 0.000 0.780 0.000 0.012 0.208
#> SRR1947594 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.4206 0.3480 0.000 0.000 0.708 0.020 0.272
#> SRR1947591 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 1 0.4682 0.2657 0.564 0.000 0.420 0.016 0.000
#> SRR1947588 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.4307 -0.1284 0.000 0.000 0.504 0.496 0.000
#> SRR1947586 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947585 5 0.5864 0.5000 0.000 0.000 0.300 0.128 0.572
#> SRR1947584 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 2 0.2179 0.8318 0.000 0.888 0.000 0.112 0.000
#> SRR1947582 4 0.2852 0.6829 0.172 0.000 0.000 0.828 0.000
#> SRR1947580 2 0.0451 0.8735 0.000 0.988 0.000 0.004 0.008
#> SRR1947581 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947575 3 0.0162 0.6643 0.000 0.000 0.996 0.004 0.000
#> SRR1947579 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947578 2 0.2864 0.8138 0.000 0.852 0.012 0.136 0.000
#> SRR1947573 3 0.4811 -0.1816 0.000 0.000 0.528 0.020 0.452
#> SRR1947574 2 0.3753 0.8013 0.080 0.832 0.000 0.012 0.076
#> SRR1947571 3 0.6468 0.3560 0.020 0.308 0.540 0.132 0.000
#> SRR1947577 4 0.1410 0.6818 0.060 0.000 0.000 0.940 0.000
#> SRR1947570 4 0.2929 0.6898 0.152 0.000 0.008 0.840 0.000
#> SRR1947569 3 0.2712 0.6302 0.000 0.000 0.880 0.088 0.032
#> SRR1947566 2 0.0290 0.8732 0.000 0.992 0.008 0.000 0.000
#> SRR1947567 2 0.2127 0.8332 0.000 0.892 0.000 0.108 0.000
#> SRR1947568 2 0.4528 0.2049 0.444 0.548 0.008 0.000 0.000
#> SRR1947564 2 0.2561 0.7821 0.000 0.856 0.144 0.000 0.000
#> SRR1947563 3 0.0404 0.6642 0.000 0.000 0.988 0.012 0.000
#> SRR1947562 3 0.5369 0.5122 0.000 0.216 0.660 0.124 0.000
#> SRR1947565 3 0.1943 0.6392 0.000 0.000 0.924 0.020 0.056
#> SRR1947559 2 0.0404 0.8724 0.000 0.988 0.012 0.000 0.000
#> SRR1947560 5 0.0000 0.7473 0.000 0.000 0.000 0.000 1.000
#> SRR1947561 2 0.0290 0.8732 0.000 0.992 0.008 0.000 0.000
#> SRR1947557 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.4227 0.1285 0.000 0.000 0.580 0.420 0.000
#> SRR1947556 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947553 2 0.0290 0.8734 0.000 0.992 0.000 0.008 0.000
#> SRR1947554 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.3906 0.6540 0.000 0.744 0.240 0.000 0.016
#> SRR1947550 2 0.5554 0.5305 0.000 0.628 0.252 0.120 0.000
#> SRR1947552 4 0.4320 0.6112 0.112 0.056 0.032 0.800 0.000
#> SRR1947549 3 0.1626 0.6471 0.000 0.000 0.940 0.016 0.044
#> SRR1947551 5 0.3551 0.6738 0.000 0.000 0.220 0.008 0.772
#> SRR1947548 3 0.4528 0.5795 0.000 0.104 0.752 0.144 0.000
#> SRR1947506 4 0.6059 0.5807 0.220 0.000 0.204 0.576 0.000
#> SRR1947507 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 1 0.3487 0.6758 0.780 0.008 0.000 0.212 0.000
#> SRR1947502 2 0.0162 0.8739 0.000 0.996 0.004 0.000 0.000
#> SRR1947501 3 0.4805 0.5657 0.000 0.144 0.728 0.128 0.000
#> SRR1947499 4 0.3416 0.6911 0.072 0.000 0.088 0.840 0.000
#> SRR1947498 5 0.6358 0.4416 0.000 0.000 0.276 0.208 0.516
#> SRR1947508 4 0.2561 0.6702 0.000 0.000 0.144 0.856 0.000
#> SRR1947505 4 0.2997 0.5723 0.000 0.148 0.012 0.840 0.000
#> SRR1947497 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 1 0.7698 0.1230 0.440 0.064 0.296 0.196 0.004
#> SRR1947493 4 0.4306 0.1491 0.492 0.000 0.000 0.508 0.000
#> SRR1947492 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 2 0.0000 0.8741 0.000 1.000 0.000 0.000 0.000
#> SRR1947491 2 0.2230 0.8316 0.000 0.884 0.000 0.116 0.000
#> SRR1947490 1 0.0000 0.8972 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 4 0.1851 0.6479 0.000 0.000 0.088 0.912 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.2378 0.6790 0.000 0.000 0.152 0.000 0.000 0.848
#> SRR1947546 2 0.4295 0.6947 0.000 0.720 0.020 0.224 0.000 0.036
#> SRR1947545 1 0.2520 0.7435 0.844 0.000 0.000 0.004 0.000 0.152
#> SRR1947544 1 0.0806 0.8770 0.972 0.000 0.000 0.020 0.000 0.008
#> SRR1947542 4 0.2454 0.6201 0.000 0.088 0.008 0.884 0.000 0.020
#> SRR1947541 6 0.2527 0.6661 0.000 0.000 0.168 0.000 0.000 0.832
#> SRR1947540 2 0.6252 0.5438 0.000 0.564 0.236 0.120 0.000 0.080
#> SRR1947539 5 0.4468 0.2567 0.000 0.000 0.316 0.028 0.644 0.012
#> SRR1947538 1 0.6906 0.3920 0.540 0.028 0.160 0.200 0.000 0.072
#> SRR1947537 4 0.3287 0.4658 0.000 0.000 0.220 0.768 0.000 0.012
#> SRR1947536 3 0.3512 0.5526 0.000 0.000 0.772 0.032 0.000 0.196
#> SRR1947535 3 0.4168 0.3062 0.000 0.000 0.584 0.400 0.000 0.016
#> SRR1947534 2 0.3198 0.6269 0.260 0.740 0.000 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 4 0.4277 0.4521 0.004 0.008 0.020 0.672 0.000 0.296
#> SRR1947531 2 0.5997 0.5989 0.000 0.604 0.204 0.116 0.000 0.076
#> SRR1947530 6 0.2910 0.7054 0.068 0.000 0.080 0.000 0.000 0.852
#> SRR1947529 2 0.0717 0.8497 0.000 0.976 0.016 0.008 0.000 0.000
#> SRR1947528 6 0.4371 0.3005 0.004 0.000 0.396 0.020 0.000 0.580
#> SRR1947527 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947526 2 0.0260 0.8510 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1947525 1 0.5956 0.2739 0.492 0.308 0.008 0.192 0.000 0.000
#> SRR1947524 3 0.2063 0.6749 0.000 0.000 0.912 0.020 0.060 0.008
#> SRR1947523 6 0.5267 0.5191 0.000 0.096 0.052 0.172 0.000 0.680
#> SRR1947521 5 0.0865 0.7747 0.000 0.000 0.036 0.000 0.964 0.000
#> SRR1947520 2 0.3802 0.5616 0.000 0.676 0.012 0.000 0.312 0.000
#> SRR1947519 6 0.4663 0.5103 0.000 0.000 0.252 0.088 0.000 0.660
#> SRR1947518 1 0.3325 0.7875 0.856 0.012 0.052 0.032 0.000 0.048
#> SRR1947517 5 0.0000 0.7942 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0717 0.8492 0.000 0.976 0.016 0.008 0.000 0.000
#> SRR1947515 4 0.3067 0.6055 0.000 0.020 0.020 0.844 0.000 0.116
#> SRR1947514 2 0.0260 0.8510 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1947513 6 0.3885 0.6844 0.068 0.012 0.040 0.060 0.000 0.820
#> SRR1947512 1 0.0000 0.8857 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1610 0.8133 0.000 0.916 0.000 0.000 0.084 0.000
#> SRR1947510 5 0.0146 0.7939 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947572 1 0.0790 0.8717 0.968 0.000 0.000 0.032 0.000 0.000
#> SRR1947611 5 0.0260 0.7928 0.000 0.000 0.008 0.000 0.992 0.000
#> SRR1947509 5 0.3624 0.6134 0.000 0.000 0.060 0.000 0.784 0.156
#> SRR1947644 3 0.3699 0.4259 0.000 0.000 0.660 0.000 0.336 0.004
#> SRR1947643 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947642 6 0.3819 0.4917 0.000 0.000 0.316 0.012 0.000 0.672
#> SRR1947640 2 0.4694 0.7069 0.004 0.740 0.044 0.148 0.000 0.064
#> SRR1947641 3 0.2380 0.6731 0.000 0.000 0.892 0.068 0.004 0.036
#> SRR1947639 1 0.5855 0.3816 0.556 0.220 0.008 0.212 0.000 0.004
#> SRR1947638 6 0.4944 0.6540 0.108 0.072 0.040 0.032 0.000 0.748
#> SRR1947637 5 0.2527 0.6865 0.000 0.000 0.108 0.024 0.868 0.000
#> SRR1947636 4 0.4551 -0.0355 0.000 0.000 0.436 0.536 0.012 0.016
#> SRR1947635 2 0.4347 0.7370 0.000 0.768 0.048 0.120 0.000 0.064
#> SRR1947634 2 0.2416 0.7492 0.000 0.844 0.000 0.000 0.156 0.000
#> SRR1947633 3 0.4563 0.1651 0.000 0.000 0.504 0.020 0.468 0.008
#> SRR1947632 4 0.2577 0.6213 0.000 0.072 0.012 0.884 0.000 0.032
#> SRR1947631 3 0.5461 0.4697 0.000 0.000 0.568 0.184 0.000 0.248
#> SRR1947629 3 0.1625 0.6707 0.000 0.000 0.928 0.060 0.012 0.000
#> SRR1947630 5 0.2527 0.6650 0.000 0.168 0.000 0.000 0.832 0.000
#> SRR1947627 6 0.4640 0.1480 0.000 0.000 0.444 0.016 0.016 0.524
#> SRR1947628 2 0.6910 0.3957 0.000 0.472 0.260 0.160 0.000 0.108
#> SRR1947626 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947625 3 0.3087 0.6133 0.000 0.000 0.808 0.176 0.004 0.012
#> SRR1947624 5 0.2260 0.6942 0.000 0.140 0.000 0.000 0.860 0.000
#> SRR1947623 1 0.0000 0.8857 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.2425 0.8258 0.000 0.884 0.024 0.088 0.000 0.004
#> SRR1947621 2 0.0458 0.8503 0.000 0.984 0.016 0.000 0.000 0.000
#> SRR1947620 6 0.1806 0.7122 0.088 0.000 0.000 0.004 0.000 0.908
#> SRR1947619 4 0.3171 0.4758 0.000 0.000 0.204 0.784 0.000 0.012
#> SRR1947617 2 0.0717 0.8492 0.000 0.976 0.016 0.008 0.000 0.000
#> SRR1947618 6 0.2942 0.7036 0.040 0.000 0.028 0.036 0.016 0.880
#> SRR1947616 3 0.6750 -0.2457 0.000 0.408 0.420 0.088 0.036 0.048
#> SRR1947615 6 0.2058 0.7090 0.000 0.000 0.036 0.056 0.000 0.908
#> SRR1947614 5 0.0000 0.7942 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947610 2 0.4291 0.7714 0.016 0.788 0.108 0.048 0.000 0.040
#> SRR1947612 2 0.0725 0.8493 0.000 0.976 0.012 0.012 0.000 0.000
#> SRR1947609 6 0.6101 0.0737 0.180 0.000 0.012 0.384 0.000 0.424
#> SRR1947608 4 0.3445 0.4626 0.000 0.000 0.244 0.744 0.000 0.012
#> SRR1947606 3 0.5784 0.2660 0.008 0.000 0.528 0.108 0.012 0.344
#> SRR1947607 1 0.0000 0.8857 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.5314 0.3315 0.004 0.052 0.024 0.572 0.000 0.348
#> SRR1947605 6 0.3782 0.3448 0.412 0.000 0.000 0.000 0.000 0.588
#> SRR1947603 4 0.4804 0.0307 0.000 0.456 0.052 0.492 0.000 0.000
#> SRR1947602 6 0.2531 0.6911 0.012 0.000 0.132 0.000 0.000 0.856
#> SRR1947600 3 0.1806 0.6798 0.000 0.000 0.928 0.020 0.044 0.008
#> SRR1947601 2 0.1461 0.8371 0.000 0.940 0.016 0.000 0.044 0.000
#> SRR1947598 4 0.6272 0.3585 0.000 0.032 0.228 0.516 0.000 0.224
#> SRR1947599 6 0.4082 0.5906 0.008 0.000 0.056 0.188 0.000 0.748
#> SRR1947597 2 0.1461 0.8366 0.000 0.940 0.016 0.044 0.000 0.000
#> SRR1947596 1 0.4323 0.4729 0.652 0.000 0.004 0.312 0.000 0.032
#> SRR1947595 5 0.6069 -0.1461 0.004 0.444 0.044 0.052 0.444 0.012
#> SRR1947594 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947592 3 0.5668 0.1921 0.000 0.000 0.452 0.428 0.108 0.012
#> SRR1947591 2 0.0363 0.8506 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1947590 4 0.4795 0.2134 0.392 0.000 0.008 0.560 0.000 0.040
#> SRR1947588 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947587 6 0.5649 0.0427 0.000 0.000 0.396 0.152 0.000 0.452
#> SRR1947586 2 0.0146 0.8510 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1947585 3 0.1845 0.6774 0.000 0.000 0.916 0.004 0.072 0.008
#> SRR1947584 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947583 2 0.3869 0.7588 0.004 0.796 0.040 0.136 0.000 0.024
#> SRR1947582 6 0.2162 0.7124 0.088 0.000 0.012 0.004 0.000 0.896
#> SRR1947580 2 0.2893 0.8147 0.000 0.872 0.056 0.028 0.000 0.044
#> SRR1947581 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947576 5 0.0146 0.7940 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947575 4 0.3608 0.4311 0.000 0.000 0.272 0.716 0.000 0.012
#> SRR1947579 5 0.0000 0.7942 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.5535 0.6766 0.000 0.672 0.112 0.120 0.000 0.096
#> SRR1947573 3 0.6189 0.2729 0.000 0.000 0.424 0.360 0.204 0.012
#> SRR1947574 2 0.5479 0.7277 0.072 0.728 0.044 0.032 0.104 0.020
#> SRR1947571 4 0.4967 0.5357 0.004 0.204 0.020 0.688 0.000 0.084
#> SRR1947577 6 0.2220 0.7084 0.036 0.000 0.012 0.044 0.000 0.908
#> SRR1947570 6 0.2506 0.7106 0.052 0.000 0.068 0.000 0.000 0.880
#> SRR1947569 3 0.1674 0.6676 0.000 0.000 0.924 0.068 0.004 0.004
#> SRR1947566 2 0.0632 0.8503 0.000 0.976 0.024 0.000 0.000 0.000
#> SRR1947567 2 0.3483 0.7818 0.000 0.828 0.044 0.100 0.000 0.028
#> SRR1947568 1 0.3756 0.4840 0.644 0.352 0.000 0.004 0.000 0.000
#> SRR1947564 2 0.3717 0.5411 0.000 0.708 0.016 0.276 0.000 0.000
#> SRR1947563 4 0.3141 0.5048 0.000 0.000 0.200 0.788 0.000 0.012
#> SRR1947562 4 0.3127 0.6146 0.000 0.100 0.004 0.840 0.000 0.056
#> SRR1947565 4 0.4121 0.3129 0.000 0.000 0.308 0.668 0.012 0.012
#> SRR1947559 2 0.1297 0.8431 0.000 0.948 0.012 0.040 0.000 0.000
#> SRR1947560 5 0.0000 0.7942 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.1003 0.8459 0.000 0.964 0.016 0.020 0.000 0.000
#> SRR1947557 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947558 3 0.3912 0.6196 0.000 0.000 0.760 0.164 0.000 0.076
#> SRR1947556 1 0.0935 0.8722 0.964 0.000 0.000 0.032 0.000 0.004
#> SRR1947553 2 0.5182 0.7140 0.024 0.716 0.152 0.064 0.000 0.044
#> SRR1947554 1 0.0000 0.8857 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.6092 0.1170 0.000 0.496 0.048 0.356 0.100 0.000
#> SRR1947550 4 0.4363 0.5160 0.004 0.240 0.012 0.708 0.000 0.036
#> SRR1947552 6 0.4289 0.5084 0.004 0.000 0.044 0.264 0.000 0.688
#> SRR1947549 4 0.3608 0.4343 0.000 0.000 0.248 0.736 0.004 0.012
#> SRR1947551 5 0.3857 -0.0734 0.000 0.000 0.468 0.000 0.532 0.000
#> SRR1947548 4 0.3291 0.6114 0.000 0.040 0.024 0.840 0.000 0.096
#> SRR1947506 6 0.4091 0.6061 0.052 0.000 0.212 0.004 0.000 0.732
#> SRR1947507 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947504 1 0.0260 0.8827 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1947503 6 0.5238 0.5710 0.220 0.004 0.024 0.092 0.000 0.660
#> SRR1947502 2 0.0914 0.8471 0.000 0.968 0.016 0.016 0.000 0.000
#> SRR1947501 4 0.2950 0.6183 0.000 0.080 0.028 0.864 0.000 0.028
#> SRR1947499 6 0.2784 0.6966 0.028 0.000 0.124 0.000 0.000 0.848
#> SRR1947498 3 0.2537 0.6732 0.000 0.000 0.888 0.016 0.068 0.028
#> SRR1947508 6 0.2178 0.6893 0.000 0.000 0.132 0.000 0.000 0.868
#> SRR1947505 6 0.7443 0.0408 0.000 0.208 0.280 0.148 0.000 0.364
#> SRR1947497 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947495 2 0.0000 0.8510 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947494 4 0.5712 -0.0093 0.016 0.016 0.044 0.468 0.008 0.448
#> SRR1947493 6 0.3109 0.6436 0.224 0.000 0.004 0.000 0.000 0.772
#> SRR1947492 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947500 2 0.0291 0.8513 0.004 0.992 0.000 0.004 0.000 0.000
#> SRR1947491 2 0.3873 0.7752 0.004 0.812 0.044 0.092 0.000 0.048
#> SRR1947490 1 0.0146 0.8866 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947489 6 0.2909 0.6794 0.000 0.000 0.028 0.136 0.000 0.836
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 15148 rows and 152 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 0.200 0.754 0.844 0.4379 0.514 0.514
#> 3 3 0.286 0.674 0.774 0.3670 0.832 0.674
#> 4 4 0.381 0.583 0.686 0.1401 0.933 0.807
#> 5 5 0.486 0.582 0.695 0.0915 0.928 0.755
#> 6 6 0.606 0.538 0.709 0.0501 0.952 0.799
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
#> SRR1947547 1 0.7815 0.7912 0.768 0.232
#> SRR1947546 2 0.2603 0.8471 0.044 0.956
#> SRR1947545 1 0.3274 0.7748 0.940 0.060
#> SRR1947544 1 0.5519 0.7724 0.872 0.128
#> SRR1947542 2 0.2603 0.8471 0.044 0.956
#> SRR1947541 1 0.7815 0.7912 0.768 0.232
#> SRR1947540 2 0.8207 0.6102 0.256 0.744
#> SRR1947539 2 0.5408 0.8311 0.124 0.876
#> SRR1947538 2 0.9044 0.5027 0.320 0.680
#> SRR1947537 1 0.7815 0.7912 0.768 0.232
#> SRR1947536 2 0.5059 0.8258 0.112 0.888
#> SRR1947535 2 0.4939 0.8384 0.108 0.892
#> SRR1947534 2 0.9129 0.4693 0.328 0.672
#> SRR1947533 2 0.0672 0.8408 0.008 0.992
#> SRR1947532 1 0.8861 0.6933 0.696 0.304
#> SRR1947531 2 0.8207 0.6102 0.256 0.744
#> SRR1947530 1 0.7299 0.8063 0.796 0.204
#> SRR1947529 2 0.6148 0.7732 0.152 0.848
#> SRR1947528 1 0.7815 0.7912 0.768 0.232
#> SRR1947527 2 0.8144 0.6154 0.252 0.748
#> SRR1947526 2 0.0672 0.8408 0.008 0.992
#> SRR1947525 2 0.7139 0.7298 0.196 0.804
#> SRR1947524 2 0.4939 0.8269 0.108 0.892
#> SRR1947523 1 0.9580 0.6013 0.620 0.380
#> SRR1947521 2 0.4815 0.8278 0.104 0.896
#> SRR1947520 2 0.0672 0.8408 0.008 0.992
#> SRR1947519 2 0.4939 0.8384 0.108 0.892
#> SRR1947518 2 0.9044 0.5027 0.320 0.680
#> SRR1947517 2 0.4815 0.8278 0.104 0.896
#> SRR1947516 2 0.0672 0.8381 0.008 0.992
#> SRR1947515 1 0.8861 0.6933 0.696 0.304
#> SRR1947514 2 0.0672 0.8381 0.008 0.992
#> SRR1947513 1 0.7219 0.8122 0.800 0.200
#> SRR1947512 1 0.2236 0.7616 0.964 0.036
#> SRR1947511 2 0.4562 0.8337 0.096 0.904
#> SRR1947510 2 0.4815 0.8278 0.104 0.896
#> SRR1947572 1 0.9775 0.3972 0.588 0.412
#> SRR1947611 2 0.4815 0.8278 0.104 0.896
#> SRR1947509 2 0.4815 0.8278 0.104 0.896
#> SRR1947644 2 0.4939 0.8269 0.108 0.892
#> SRR1947643 2 0.1843 0.8442 0.028 0.972
#> SRR1947642 1 0.9686 0.5138 0.604 0.396
#> SRR1947640 1 0.7219 0.8122 0.800 0.200
#> SRR1947641 2 0.4939 0.8384 0.108 0.892
#> SRR1947639 1 0.9775 0.3972 0.588 0.412
#> SRR1947638 1 0.9710 0.4811 0.600 0.400
#> SRR1947637 2 0.4815 0.8278 0.104 0.896
#> SRR1947636 1 0.7815 0.7912 0.768 0.232
#> SRR1947635 2 0.6247 0.7691 0.156 0.844
#> SRR1947634 2 0.4562 0.8337 0.096 0.904
#> SRR1947633 2 0.5408 0.8311 0.124 0.876
#> SRR1947632 2 0.2603 0.8471 0.044 0.956
#> SRR1947631 2 0.7453 0.7278 0.212 0.788
#> SRR1947629 2 0.4939 0.8269 0.108 0.892
#> SRR1947630 2 0.4562 0.8337 0.096 0.904
#> SRR1947627 2 0.8555 0.6409 0.280 0.720
#> SRR1947628 2 0.8267 0.6016 0.260 0.740
#> SRR1947626 2 0.4298 0.8179 0.088 0.912
#> SRR1947625 2 0.4939 0.8384 0.108 0.892
#> SRR1947624 2 0.4562 0.8337 0.096 0.904
#> SRR1947623 1 0.9732 0.4177 0.596 0.404
#> SRR1947622 2 0.6247 0.7724 0.156 0.844
#> SRR1947621 2 0.0672 0.8381 0.008 0.992
#> SRR1947620 1 0.7056 0.8120 0.808 0.192
#> SRR1947619 2 0.5629 0.8254 0.132 0.868
#> SRR1947617 2 0.0672 0.8381 0.008 0.992
#> SRR1947618 1 0.7056 0.8120 0.808 0.192
#> SRR1947616 2 0.2423 0.8440 0.040 0.960
#> SRR1947615 1 0.9209 0.6455 0.664 0.336
#> SRR1947614 2 0.4815 0.8278 0.104 0.896
#> SRR1947613 1 0.2603 0.7668 0.956 0.044
#> SRR1947610 2 0.9044 0.5027 0.320 0.680
#> SRR1947612 2 0.0672 0.8381 0.008 0.992
#> SRR1947609 1 0.7219 0.8122 0.800 0.200
#> SRR1947608 2 0.4939 0.8384 0.108 0.892
#> SRR1947606 1 0.7815 0.7912 0.768 0.232
#> SRR1947607 1 0.2603 0.7668 0.956 0.044
#> SRR1947604 2 0.7139 0.7298 0.196 0.804
#> SRR1947605 1 0.3274 0.7748 0.940 0.060
#> SRR1947603 2 0.2423 0.8467 0.040 0.960
#> SRR1947602 1 0.7299 0.8063 0.796 0.204
#> SRR1947600 2 0.4939 0.8269 0.108 0.892
#> SRR1947601 2 0.0672 0.8381 0.008 0.992
#> SRR1947598 2 0.8267 0.6016 0.260 0.740
#> SRR1947599 1 0.7139 0.8116 0.804 0.196
#> SRR1947597 2 0.7139 0.7298 0.196 0.804
#> SRR1947596 1 0.7139 0.7314 0.804 0.196
#> SRR1947595 1 0.7219 0.8122 0.800 0.200
#> SRR1947594 1 0.2236 0.7616 0.964 0.036
#> SRR1947592 2 0.5629 0.8254 0.132 0.868
#> SRR1947591 2 0.0672 0.8381 0.008 0.992
#> SRR1947590 1 0.7139 0.7314 0.804 0.196
#> SRR1947588 1 0.2236 0.7616 0.964 0.036
#> SRR1947587 1 0.7815 0.7912 0.768 0.232
#> SRR1947586 2 0.4298 0.8179 0.088 0.912
#> SRR1947585 2 0.4939 0.8269 0.108 0.892
#> SRR1947584 1 0.2236 0.7616 0.964 0.036
#> SRR1947583 1 0.7219 0.8122 0.800 0.200
#> SRR1947582 1 0.7056 0.8120 0.808 0.192
#> SRR1947580 2 0.4298 0.8179 0.088 0.912
#> SRR1947581 1 0.2236 0.7616 0.964 0.036
#> SRR1947576 2 0.4815 0.8278 0.104 0.896
#> SRR1947575 2 0.4939 0.8384 0.108 0.892
#> SRR1947579 2 0.4815 0.8278 0.104 0.896
#> SRR1947578 2 0.8267 0.6016 0.260 0.740
#> SRR1947573 2 0.5408 0.8311 0.124 0.876
#> SRR1947574 1 0.9732 0.4730 0.596 0.404
#> SRR1947571 2 0.9944 -0.0347 0.456 0.544
#> SRR1947577 1 0.7056 0.8120 0.808 0.192
#> SRR1947570 1 0.7815 0.7912 0.768 0.232
#> SRR1947569 2 0.4939 0.8269 0.108 0.892
#> SRR1947566 2 0.1843 0.8442 0.028 0.972
#> SRR1947567 2 0.6247 0.7691 0.156 0.844
#> SRR1947568 1 0.9977 0.2783 0.528 0.472
#> SRR1947564 2 0.0672 0.8381 0.008 0.992
#> SRR1947563 2 0.4939 0.8384 0.108 0.892
#> SRR1947562 2 0.7139 0.7298 0.196 0.804
#> SRR1947565 1 0.7815 0.7912 0.768 0.232
#> SRR1947559 2 0.7139 0.7298 0.196 0.804
#> SRR1947560 2 0.4815 0.8278 0.104 0.896
#> SRR1947561 2 0.0672 0.8381 0.008 0.992
#> SRR1947557 1 0.2236 0.7616 0.964 0.036
#> SRR1947558 2 0.5178 0.8352 0.116 0.884
#> SRR1947556 1 0.5737 0.7358 0.864 0.136
#> SRR1947553 2 0.9044 0.5027 0.320 0.680
#> SRR1947554 1 0.2603 0.7668 0.956 0.044
#> SRR1947555 2 0.2423 0.8467 0.040 0.960
#> SRR1947550 1 0.7219 0.8122 0.800 0.200
#> SRR1947552 1 0.7139 0.8116 0.804 0.196
#> SRR1947549 2 0.5629 0.8254 0.132 0.868
#> SRR1947551 2 0.4939 0.8269 0.108 0.892
#> SRR1947548 1 0.8861 0.6933 0.696 0.304
#> SRR1947506 1 0.7674 0.7962 0.776 0.224
#> SRR1947507 1 0.2236 0.7616 0.964 0.036
#> SRR1947504 1 0.4022 0.7600 0.920 0.080
#> SRR1947503 1 0.9710 0.4811 0.600 0.400
#> SRR1947502 2 0.0672 0.8381 0.008 0.992
#> SRR1947501 2 0.2603 0.8471 0.044 0.956
#> SRR1947499 1 0.7299 0.8063 0.796 0.204
#> SRR1947498 2 0.4939 0.8269 0.108 0.892
#> SRR1947508 1 0.9209 0.6455 0.664 0.336
#> SRR1947505 2 0.8267 0.6016 0.260 0.740
#> SRR1947497 2 0.0672 0.8408 0.008 0.992
#> SRR1947496 1 0.2236 0.7616 0.964 0.036
#> SRR1947495 2 0.0672 0.8408 0.008 0.992
#> SRR1947494 1 0.7299 0.8091 0.796 0.204
#> SRR1947493 1 0.7299 0.8066 0.796 0.204
#> SRR1947492 1 0.2603 0.7668 0.956 0.044
#> SRR1947500 2 0.7139 0.7298 0.196 0.804
#> SRR1947491 2 0.6247 0.7691 0.156 0.844
#> SRR1947490 1 0.3879 0.7810 0.924 0.076
#> SRR1947489 1 0.9170 0.6533 0.668 0.332
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947546 2 0.4485 0.727 0.020 0.844 0.136
#> SRR1947545 1 0.1832 0.719 0.956 0.036 0.008
#> SRR1947544 1 0.3995 0.715 0.868 0.116 0.016
#> SRR1947542 2 0.4485 0.727 0.020 0.844 0.136
#> SRR1947541 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947540 2 0.7144 0.622 0.220 0.700 0.080
#> SRR1947539 3 0.7467 0.588 0.056 0.320 0.624
#> SRR1947538 2 0.5986 0.601 0.284 0.704 0.012
#> SRR1947537 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947536 3 0.0475 0.765 0.004 0.004 0.992
#> SRR1947535 3 0.7163 0.584 0.040 0.332 0.628
#> SRR1947534 2 0.6228 0.557 0.316 0.672 0.012
#> SRR1947533 2 0.3038 0.731 0.000 0.896 0.104
#> SRR1947532 1 0.6684 0.604 0.676 0.292 0.032
#> SRR1947531 2 0.7144 0.622 0.220 0.700 0.080
#> SRR1947530 1 0.7437 0.761 0.692 0.108 0.200
#> SRR1947529 2 0.5403 0.763 0.124 0.816 0.060
#> SRR1947528 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947527 2 0.6066 0.673 0.248 0.728 0.024
#> SRR1947526 2 0.3038 0.731 0.000 0.896 0.104
#> SRR1947525 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947524 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947523 1 0.9001 0.573 0.548 0.280 0.172
#> SRR1947521 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947520 2 0.4062 0.699 0.000 0.836 0.164
#> SRR1947519 3 0.7163 0.584 0.040 0.332 0.628
#> SRR1947518 2 0.5986 0.601 0.284 0.704 0.012
#> SRR1947517 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947516 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947515 1 0.6684 0.604 0.676 0.292 0.032
#> SRR1947514 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947513 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947512 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947511 2 0.5859 0.392 0.000 0.656 0.344
#> SRR1947510 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947572 1 0.6824 0.225 0.576 0.408 0.016
#> SRR1947611 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947509 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947644 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947643 2 0.2537 0.756 0.000 0.920 0.080
#> SRR1947642 1 0.9468 0.526 0.488 0.212 0.300
#> SRR1947640 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947641 3 0.7208 0.570 0.040 0.340 0.620
#> SRR1947639 1 0.6824 0.225 0.576 0.408 0.016
#> SRR1947638 1 0.9162 0.456 0.500 0.340 0.160
#> SRR1947637 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947636 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947635 2 0.5471 0.762 0.128 0.812 0.060
#> SRR1947634 2 0.5859 0.392 0.000 0.656 0.344
#> SRR1947633 3 0.7467 0.588 0.056 0.320 0.624
#> SRR1947632 2 0.4485 0.727 0.020 0.844 0.136
#> SRR1947631 3 0.8821 0.480 0.144 0.304 0.552
#> SRR1947629 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947630 2 0.5859 0.392 0.000 0.656 0.344
#> SRR1947627 3 0.8590 0.540 0.164 0.236 0.600
#> SRR1947628 2 0.7186 0.616 0.224 0.696 0.080
#> SRR1947626 2 0.2486 0.767 0.060 0.932 0.008
#> SRR1947625 3 0.7208 0.570 0.040 0.340 0.620
#> SRR1947624 2 0.5859 0.392 0.000 0.656 0.344
#> SRR1947623 1 0.6798 0.245 0.584 0.400 0.016
#> SRR1947622 2 0.5588 0.759 0.124 0.808 0.068
#> SRR1947621 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947620 1 0.7192 0.773 0.716 0.120 0.164
#> SRR1947619 3 0.7613 0.586 0.064 0.316 0.620
#> SRR1947617 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947618 1 0.7192 0.773 0.716 0.120 0.164
#> SRR1947616 2 0.3031 0.764 0.012 0.912 0.076
#> SRR1947615 1 0.9110 0.620 0.544 0.196 0.260
#> SRR1947614 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947613 1 0.0592 0.704 0.988 0.012 0.000
#> SRR1947610 2 0.5986 0.601 0.284 0.704 0.012
#> SRR1947612 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947609 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947608 3 0.7163 0.584 0.040 0.332 0.628
#> SRR1947606 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947607 1 0.0592 0.704 0.988 0.012 0.000
#> SRR1947604 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947605 1 0.1832 0.719 0.956 0.036 0.008
#> SRR1947603 2 0.4277 0.727 0.016 0.852 0.132
#> SRR1947602 1 0.7437 0.761 0.692 0.108 0.200
#> SRR1947600 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947601 2 0.1289 0.759 0.000 0.968 0.032
#> SRR1947598 2 0.7186 0.616 0.224 0.696 0.080
#> SRR1947599 1 0.7297 0.772 0.708 0.120 0.172
#> SRR1947597 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947596 1 0.5455 0.668 0.788 0.184 0.028
#> SRR1947595 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947594 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947592 3 0.7613 0.586 0.064 0.316 0.620
#> SRR1947591 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947590 1 0.5455 0.668 0.788 0.184 0.028
#> SRR1947588 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947587 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947586 2 0.2486 0.767 0.060 0.932 0.008
#> SRR1947585 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947584 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947583 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947582 1 0.7245 0.773 0.712 0.120 0.168
#> SRR1947580 2 0.2651 0.768 0.060 0.928 0.012
#> SRR1947581 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947576 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947575 3 0.7163 0.584 0.040 0.332 0.628
#> SRR1947579 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947578 2 0.7186 0.616 0.224 0.696 0.080
#> SRR1947573 3 0.7467 0.588 0.056 0.320 0.624
#> SRR1947574 1 0.9243 0.452 0.492 0.340 0.168
#> SRR1947571 2 0.7715 0.129 0.428 0.524 0.048
#> SRR1947577 1 0.7192 0.773 0.716 0.120 0.164
#> SRR1947570 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947569 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947566 2 0.1643 0.767 0.000 0.956 0.044
#> SRR1947567 2 0.5471 0.762 0.128 0.812 0.060
#> SRR1947568 1 0.6676 0.086 0.516 0.476 0.008
#> SRR1947564 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947563 3 0.7163 0.584 0.040 0.332 0.628
#> SRR1947562 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947565 1 0.7769 0.744 0.660 0.108 0.232
#> SRR1947559 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947560 3 0.0592 0.769 0.000 0.012 0.988
#> SRR1947561 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947557 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947558 3 0.7401 0.564 0.048 0.340 0.612
#> SRR1947556 1 0.3412 0.663 0.876 0.124 0.000
#> SRR1947553 2 0.5986 0.601 0.284 0.704 0.012
#> SRR1947554 1 0.0592 0.704 0.988 0.012 0.000
#> SRR1947555 2 0.4277 0.727 0.016 0.852 0.132
#> SRR1947550 1 0.7424 0.772 0.700 0.128 0.172
#> SRR1947552 1 0.7297 0.772 0.708 0.120 0.172
#> SRR1947549 3 0.7613 0.586 0.064 0.316 0.620
#> SRR1947551 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947548 1 0.6684 0.604 0.676 0.292 0.032
#> SRR1947506 1 0.7731 0.747 0.664 0.108 0.228
#> SRR1947507 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947504 1 0.1753 0.683 0.952 0.048 0.000
#> SRR1947503 1 0.9162 0.456 0.500 0.340 0.160
#> SRR1947502 2 0.1031 0.756 0.000 0.976 0.024
#> SRR1947501 2 0.4485 0.727 0.020 0.844 0.136
#> SRR1947499 1 0.7437 0.761 0.692 0.108 0.200
#> SRR1947498 3 0.0237 0.768 0.000 0.004 0.996
#> SRR1947508 1 0.9110 0.620 0.544 0.196 0.260
#> SRR1947505 2 0.7186 0.616 0.224 0.696 0.080
#> SRR1947497 2 0.3038 0.731 0.000 0.896 0.104
#> SRR1947496 1 0.0000 0.697 1.000 0.000 0.000
#> SRR1947495 2 0.3038 0.731 0.000 0.896 0.104
#> SRR1947494 1 0.7281 0.766 0.712 0.148 0.140
#> SRR1947493 1 0.7525 0.759 0.684 0.108 0.208
#> SRR1947492 1 0.0592 0.704 0.988 0.012 0.000
#> SRR1947500 2 0.6027 0.730 0.164 0.776 0.060
#> SRR1947491 2 0.5471 0.762 0.128 0.812 0.060
#> SRR1947490 1 0.1989 0.719 0.948 0.048 0.004
#> SRR1947489 1 0.9072 0.626 0.548 0.192 0.260
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947546 2 0.579 0.5828 0.016 0.740 0.128 0.116
#> SRR1947545 4 0.510 -0.6036 0.380 0.000 0.008 0.612
#> SRR1947544 4 0.582 -0.4372 0.332 0.008 0.032 0.628
#> SRR1947542 2 0.579 0.5828 0.016 0.740 0.128 0.116
#> SRR1947541 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947540 2 0.900 0.3577 0.208 0.396 0.072 0.324
#> SRR1947539 3 0.725 0.6162 0.020 0.172 0.608 0.200
#> SRR1947538 2 0.798 0.3693 0.260 0.396 0.004 0.340
#> SRR1947537 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947536 3 0.200 0.7303 0.020 0.000 0.936 0.044
#> SRR1947535 3 0.723 0.6149 0.020 0.184 0.612 0.184
#> SRR1947534 2 0.746 0.4420 0.200 0.492 0.000 0.308
#> SRR1947533 2 0.492 0.5734 0.112 0.796 0.080 0.012
#> SRR1947532 4 0.404 0.4985 0.076 0.056 0.016 0.852
#> SRR1947531 2 0.900 0.3577 0.208 0.396 0.072 0.324
#> SRR1947530 4 0.355 0.6868 0.020 0.000 0.136 0.844
#> SRR1947529 2 0.627 0.6143 0.044 0.692 0.048 0.216
#> SRR1947528 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947527 2 0.687 0.5436 0.224 0.596 0.000 0.180
#> SRR1947526 2 0.492 0.5734 0.112 0.796 0.080 0.012
#> SRR1947525 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947524 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947523 4 0.609 0.5965 0.024 0.112 0.140 0.724
#> SRR1947521 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947520 2 0.599 0.5458 0.132 0.732 0.112 0.024
#> SRR1947519 3 0.723 0.6149 0.020 0.184 0.612 0.184
#> SRR1947518 2 0.798 0.3693 0.260 0.396 0.004 0.340
#> SRR1947517 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947516 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947515 4 0.404 0.4985 0.076 0.056 0.016 0.852
#> SRR1947514 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947513 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947512 1 0.493 0.9658 0.568 0.000 0.000 0.432
#> SRR1947511 2 0.792 0.3148 0.132 0.564 0.248 0.056
#> SRR1947510 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947572 4 0.786 0.0839 0.304 0.220 0.008 0.468
#> SRR1947611 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947509 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947644 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947643 2 0.696 0.5989 0.124 0.684 0.076 0.116
#> SRR1947642 4 0.647 0.5670 0.020 0.084 0.232 0.664
#> SRR1947640 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947641 3 0.736 0.6060 0.024 0.188 0.604 0.184
#> SRR1947639 4 0.786 0.0839 0.304 0.220 0.008 0.468
#> SRR1947638 4 0.707 0.5369 0.048 0.196 0.104 0.652
#> SRR1947637 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947636 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947635 2 0.630 0.6122 0.044 0.688 0.048 0.220
#> SRR1947634 2 0.792 0.3148 0.132 0.564 0.248 0.056
#> SRR1947633 3 0.725 0.6162 0.020 0.172 0.608 0.200
#> SRR1947632 2 0.579 0.5828 0.016 0.740 0.128 0.116
#> SRR1947631 3 0.771 0.4823 0.024 0.152 0.536 0.288
#> SRR1947629 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947630 2 0.792 0.3148 0.132 0.564 0.248 0.056
#> SRR1947627 3 0.762 0.4632 0.036 0.108 0.540 0.316
#> SRR1947628 2 0.901 0.3512 0.208 0.392 0.072 0.328
#> SRR1947626 2 0.650 0.6005 0.216 0.648 0.004 0.132
#> SRR1947625 3 0.736 0.6060 0.024 0.188 0.604 0.184
#> SRR1947624 2 0.792 0.3148 0.132 0.564 0.248 0.056
#> SRR1947623 4 0.783 0.0776 0.304 0.216 0.008 0.472
#> SRR1947622 2 0.693 0.5931 0.060 0.640 0.056 0.244
#> SRR1947621 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947620 4 0.292 0.6883 0.016 0.000 0.100 0.884
#> SRR1947619 3 0.728 0.6133 0.020 0.168 0.604 0.208
#> SRR1947617 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947618 4 0.292 0.6883 0.016 0.000 0.100 0.884
#> SRR1947616 2 0.765 0.5701 0.184 0.616 0.068 0.132
#> SRR1947615 4 0.567 0.6234 0.012 0.076 0.180 0.732
#> SRR1947614 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947613 1 0.495 0.9610 0.556 0.000 0.000 0.444
#> SRR1947610 2 0.798 0.3693 0.260 0.396 0.004 0.340
#> SRR1947612 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947609 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947608 3 0.723 0.6149 0.020 0.184 0.612 0.184
#> SRR1947606 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947607 1 0.495 0.9610 0.556 0.000 0.000 0.444
#> SRR1947604 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947605 4 0.510 -0.6036 0.380 0.000 0.008 0.612
#> SRR1947603 2 0.522 0.5930 0.008 0.772 0.112 0.108
#> SRR1947602 4 0.355 0.6868 0.020 0.000 0.136 0.844
#> SRR1947600 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947601 2 0.286 0.6042 0.112 0.880 0.000 0.008
#> SRR1947598 2 0.901 0.3512 0.208 0.392 0.072 0.328
#> SRR1947599 4 0.267 0.6932 0.008 0.000 0.100 0.892
#> SRR1947597 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947596 4 0.480 0.2528 0.176 0.016 0.028 0.780
#> SRR1947595 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947594 1 0.493 0.9658 0.568 0.000 0.000 0.432
#> SRR1947592 3 0.728 0.6133 0.020 0.168 0.604 0.208
#> SRR1947591 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947590 4 0.480 0.2528 0.176 0.016 0.028 0.780
#> SRR1947588 1 0.494 0.9668 0.564 0.000 0.000 0.436
#> SRR1947587 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947586 2 0.650 0.6005 0.216 0.648 0.004 0.132
#> SRR1947585 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947584 1 0.494 0.9668 0.564 0.000 0.000 0.436
#> SRR1947583 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947582 4 0.299 0.6894 0.016 0.000 0.104 0.880
#> SRR1947580 2 0.664 0.5987 0.216 0.644 0.008 0.132
#> SRR1947581 1 0.494 0.9668 0.564 0.000 0.000 0.436
#> SRR1947576 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947575 3 0.723 0.6149 0.020 0.184 0.612 0.184
#> SRR1947579 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947578 2 0.901 0.3512 0.208 0.392 0.072 0.328
#> SRR1947573 3 0.725 0.6162 0.020 0.172 0.608 0.200
#> SRR1947574 4 0.691 0.5397 0.040 0.196 0.104 0.660
#> SRR1947571 4 0.730 0.2095 0.104 0.260 0.036 0.600
#> SRR1947577 4 0.292 0.6883 0.016 0.000 0.100 0.884
#> SRR1947570 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947569 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947566 2 0.655 0.6088 0.144 0.700 0.040 0.116
#> SRR1947567 2 0.630 0.6122 0.044 0.688 0.048 0.220
#> SRR1947568 4 0.785 0.1474 0.252 0.260 0.008 0.480
#> SRR1947564 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947563 3 0.723 0.6149 0.020 0.184 0.612 0.184
#> SRR1947562 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947565 4 0.307 0.6963 0.000 0.000 0.152 0.848
#> SRR1947559 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947560 3 0.244 0.7372 0.020 0.004 0.920 0.056
#> SRR1947561 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947557 1 0.494 0.9668 0.564 0.000 0.000 0.436
#> SRR1947558 3 0.742 0.6005 0.024 0.188 0.596 0.192
#> SRR1947556 4 0.607 -0.6302 0.432 0.012 0.024 0.532
#> SRR1947553 2 0.798 0.3693 0.260 0.396 0.004 0.340
#> SRR1947554 1 0.495 0.9610 0.556 0.000 0.000 0.444
#> SRR1947555 2 0.522 0.5930 0.008 0.772 0.112 0.108
#> SRR1947550 4 0.337 0.6954 0.020 0.008 0.100 0.872
#> SRR1947552 4 0.267 0.6932 0.008 0.000 0.100 0.892
#> SRR1947549 3 0.728 0.6133 0.020 0.168 0.604 0.208
#> SRR1947551 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947548 4 0.404 0.4985 0.076 0.056 0.016 0.852
#> SRR1947506 4 0.360 0.6946 0.016 0.000 0.148 0.836
#> SRR1947507 1 0.493 0.9658 0.568 0.000 0.000 0.432
#> SRR1947504 1 0.535 0.8770 0.584 0.004 0.008 0.404
#> SRR1947503 4 0.707 0.5369 0.048 0.196 0.104 0.652
#> SRR1947502 2 0.253 0.6039 0.112 0.888 0.000 0.000
#> SRR1947501 2 0.579 0.5828 0.016 0.740 0.128 0.116
#> SRR1947499 4 0.355 0.6868 0.020 0.000 0.136 0.844
#> SRR1947498 3 0.162 0.7335 0.020 0.000 0.952 0.028
#> SRR1947508 4 0.567 0.6234 0.012 0.076 0.180 0.732
#> SRR1947505 2 0.901 0.3512 0.208 0.392 0.072 0.328
#> SRR1947497 2 0.492 0.5734 0.112 0.796 0.080 0.012
#> SRR1947496 1 0.495 0.9566 0.560 0.000 0.000 0.440
#> SRR1947495 2 0.492 0.5734 0.112 0.796 0.080 0.012
#> SRR1947494 4 0.305 0.6705 0.016 0.012 0.080 0.892
#> SRR1947493 4 0.334 0.6936 0.016 0.000 0.128 0.856
#> SRR1947492 1 0.495 0.9610 0.556 0.000 0.000 0.444
#> SRR1947500 2 0.725 0.5499 0.068 0.592 0.052 0.288
#> SRR1947491 2 0.630 0.6122 0.044 0.688 0.048 0.220
#> SRR1947490 1 0.516 0.8528 0.520 0.004 0.000 0.476
#> SRR1947489 4 0.560 0.6266 0.012 0.072 0.180 0.736
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947546 2 0.6100 0.459593 0.000 0.628 0.224 0.120 0.028
#> SRR1947545 1 0.5633 0.454417 0.476 0.000 0.020 0.468 0.036
#> SRR1947544 4 0.6594 -0.369726 0.408 0.000 0.036 0.464 0.092
#> SRR1947542 2 0.6100 0.459593 0.000 0.628 0.224 0.120 0.028
#> SRR1947541 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947540 5 0.6001 0.667343 0.000 0.252 0.048 0.068 0.632
#> SRR1947539 3 0.5265 0.615828 0.000 0.064 0.668 0.256 0.012
#> SRR1947538 5 0.5179 0.662098 0.020 0.252 0.000 0.048 0.680
#> SRR1947537 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947536 3 0.5540 0.600080 0.152 0.000 0.712 0.080 0.056
#> SRR1947535 3 0.5376 0.617618 0.000 0.072 0.672 0.240 0.016
#> SRR1947534 2 0.7259 0.033810 0.064 0.540 0.004 0.180 0.212
#> SRR1947533 2 0.2445 0.530645 0.000 0.908 0.020 0.016 0.056
#> SRR1947532 4 0.5754 0.619008 0.040 0.040 0.048 0.720 0.152
#> SRR1947531 5 0.6001 0.667343 0.000 0.252 0.048 0.068 0.632
#> SRR1947530 4 0.1869 0.812707 0.036 0.000 0.012 0.936 0.016
#> SRR1947529 2 0.7161 0.384712 0.000 0.572 0.136 0.140 0.152
#> SRR1947528 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947527 2 0.5783 0.207325 0.056 0.676 0.004 0.052 0.212
#> SRR1947526 2 0.2445 0.530645 0.000 0.908 0.020 0.016 0.056
#> SRR1947525 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947524 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947523 4 0.4119 0.701537 0.000 0.032 0.132 0.804 0.032
#> SRR1947521 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947520 2 0.3819 0.513338 0.008 0.840 0.044 0.020 0.088
#> SRR1947519 3 0.5376 0.617618 0.000 0.072 0.672 0.240 0.016
#> SRR1947518 5 0.5179 0.662098 0.020 0.252 0.000 0.048 0.680
#> SRR1947517 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947516 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.5754 0.619008 0.040 0.040 0.048 0.720 0.152
#> SRR1947514 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947512 1 0.3210 0.907727 0.788 0.000 0.000 0.212 0.000
#> SRR1947511 2 0.6343 0.383779 0.012 0.672 0.080 0.092 0.144
#> SRR1947510 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947572 5 0.8920 0.261743 0.264 0.196 0.016 0.232 0.292
#> SRR1947611 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947509 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947644 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947643 2 0.5380 0.073823 0.000 0.556 0.036 0.012 0.396
#> SRR1947642 4 0.3840 0.642776 0.000 0.008 0.196 0.780 0.016
#> SRR1947640 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947641 3 0.5521 0.610731 0.000 0.076 0.664 0.240 0.020
#> SRR1947639 5 0.8920 0.261743 0.264 0.196 0.016 0.232 0.292
#> SRR1947638 4 0.6607 0.512968 0.024 0.096 0.088 0.664 0.128
#> SRR1947637 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947636 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947635 2 0.7196 0.382980 0.000 0.568 0.136 0.148 0.148
#> SRR1947634 2 0.6343 0.383779 0.012 0.672 0.080 0.092 0.144
#> SRR1947633 3 0.5265 0.615828 0.000 0.064 0.668 0.256 0.012
#> SRR1947632 2 0.6100 0.459593 0.000 0.628 0.224 0.120 0.028
#> SRR1947631 3 0.5865 0.477987 0.000 0.072 0.568 0.344 0.016
#> SRR1947629 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947630 2 0.6343 0.383779 0.012 0.672 0.080 0.092 0.144
#> SRR1947627 3 0.5106 0.405086 0.020 0.000 0.560 0.408 0.012
#> SRR1947628 5 0.5978 0.670743 0.000 0.248 0.048 0.068 0.636
#> SRR1947626 2 0.5170 -0.194724 0.020 0.512 0.000 0.012 0.456
#> SRR1947625 3 0.5521 0.610731 0.000 0.076 0.664 0.240 0.020
#> SRR1947624 2 0.6343 0.383779 0.012 0.672 0.080 0.092 0.144
#> SRR1947623 5 0.8927 0.248911 0.268 0.196 0.016 0.236 0.284
#> SRR1947622 2 0.7571 0.359151 0.000 0.516 0.152 0.136 0.196
#> SRR1947621 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 4 0.1251 0.813329 0.036 0.000 0.000 0.956 0.008
#> SRR1947619 3 0.5311 0.609088 0.000 0.064 0.660 0.264 0.012
#> SRR1947617 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 4 0.1251 0.813329 0.036 0.000 0.000 0.956 0.008
#> SRR1947616 2 0.5969 -0.253630 0.000 0.476 0.044 0.032 0.448
#> SRR1947615 4 0.2818 0.738193 0.000 0.000 0.132 0.856 0.012
#> SRR1947614 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947613 1 0.3305 0.908008 0.776 0.000 0.000 0.224 0.000
#> SRR1947610 5 0.5179 0.662098 0.020 0.252 0.000 0.048 0.680
#> SRR1947612 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947608 3 0.5376 0.617618 0.000 0.072 0.672 0.240 0.016
#> SRR1947606 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947607 1 0.3305 0.908008 0.776 0.000 0.000 0.224 0.000
#> SRR1947604 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947605 1 0.5633 0.454417 0.476 0.000 0.020 0.468 0.036
#> SRR1947603 2 0.5711 0.470404 0.000 0.660 0.204 0.120 0.016
#> SRR1947602 4 0.1869 0.812707 0.036 0.000 0.012 0.936 0.016
#> SRR1947600 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947601 2 0.0451 0.544415 0.000 0.988 0.004 0.000 0.008
#> SRR1947598 5 0.5978 0.670743 0.000 0.248 0.048 0.068 0.636
#> SRR1947599 4 0.1082 0.817562 0.028 0.000 0.000 0.964 0.008
#> SRR1947597 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947596 4 0.6248 0.438314 0.148 0.000 0.044 0.640 0.168
#> SRR1947595 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947594 1 0.3210 0.907727 0.788 0.000 0.000 0.212 0.000
#> SRR1947592 3 0.5311 0.609088 0.000 0.064 0.660 0.264 0.012
#> SRR1947591 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.6248 0.438314 0.148 0.000 0.044 0.640 0.168
#> SRR1947588 1 0.3242 0.909720 0.784 0.000 0.000 0.216 0.000
#> SRR1947587 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947586 2 0.5170 -0.194724 0.020 0.512 0.000 0.012 0.456
#> SRR1947585 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947584 1 0.3242 0.909720 0.784 0.000 0.000 0.216 0.000
#> SRR1947583 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947582 4 0.1124 0.814149 0.036 0.000 0.000 0.960 0.004
#> SRR1947580 2 0.5316 -0.201301 0.020 0.508 0.004 0.012 0.456
#> SRR1947581 1 0.3242 0.909720 0.784 0.000 0.000 0.216 0.000
#> SRR1947576 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947575 3 0.5376 0.617618 0.000 0.072 0.672 0.240 0.016
#> SRR1947579 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947578 5 0.5978 0.670743 0.000 0.248 0.048 0.068 0.636
#> SRR1947573 3 0.5265 0.615828 0.000 0.064 0.668 0.256 0.012
#> SRR1947574 4 0.6432 0.515778 0.016 0.096 0.088 0.672 0.128
#> SRR1947571 4 0.8453 0.097254 0.024 0.144 0.140 0.424 0.268
#> SRR1947577 4 0.1251 0.813329 0.036 0.000 0.000 0.956 0.008
#> SRR1947570 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947569 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947566 2 0.5343 -0.000415 0.000 0.572 0.036 0.012 0.380
#> SRR1947567 2 0.7196 0.382980 0.000 0.568 0.136 0.148 0.148
#> SRR1947568 5 0.8944 0.302055 0.212 0.240 0.016 0.240 0.292
#> SRR1947564 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 3 0.5376 0.617618 0.000 0.072 0.672 0.240 0.016
#> SRR1947562 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947565 4 0.1251 0.821299 0.008 0.000 0.036 0.956 0.000
#> SRR1947559 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947560 3 0.6981 0.629970 0.132 0.000 0.592 0.128 0.148
#> SRR1947561 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.3242 0.909720 0.784 0.000 0.000 0.216 0.000
#> SRR1947558 3 0.5570 0.605909 0.000 0.076 0.656 0.248 0.020
#> SRR1947556 1 0.6675 0.638349 0.552 0.000 0.036 0.276 0.136
#> SRR1947553 5 0.5179 0.662098 0.020 0.252 0.000 0.048 0.680
#> SRR1947554 1 0.3305 0.908008 0.776 0.000 0.000 0.224 0.000
#> SRR1947555 2 0.5711 0.470404 0.000 0.660 0.204 0.120 0.016
#> SRR1947550 4 0.1116 0.818601 0.028 0.004 0.000 0.964 0.004
#> SRR1947552 4 0.1082 0.817562 0.028 0.000 0.000 0.964 0.008
#> SRR1947549 3 0.5311 0.609088 0.000 0.064 0.660 0.264 0.012
#> SRR1947551 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947548 4 0.5754 0.619008 0.040 0.040 0.048 0.720 0.152
#> SRR1947506 4 0.1386 0.820113 0.016 0.000 0.032 0.952 0.000
#> SRR1947507 1 0.3210 0.907727 0.788 0.000 0.000 0.212 0.000
#> SRR1947504 1 0.3885 0.851009 0.784 0.000 0.000 0.176 0.040
#> SRR1947503 4 0.6607 0.512968 0.024 0.096 0.088 0.664 0.128
#> SRR1947502 2 0.0000 0.544418 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 2 0.6100 0.459593 0.000 0.628 0.224 0.120 0.028
#> SRR1947499 4 0.1869 0.812707 0.036 0.000 0.012 0.936 0.016
#> SRR1947498 3 0.4321 0.615014 0.152 0.000 0.784 0.024 0.040
#> SRR1947508 4 0.2818 0.738193 0.000 0.000 0.132 0.856 0.012
#> SRR1947505 5 0.5978 0.670743 0.000 0.248 0.048 0.068 0.636
#> SRR1947497 2 0.2445 0.530645 0.000 0.908 0.020 0.016 0.056
#> SRR1947496 1 0.3398 0.904273 0.780 0.000 0.000 0.216 0.004
#> SRR1947495 2 0.2445 0.530645 0.000 0.908 0.020 0.016 0.056
#> SRR1947494 4 0.2275 0.798955 0.020 0.008 0.016 0.924 0.032
#> SRR1947493 4 0.1310 0.819605 0.024 0.000 0.020 0.956 0.000
#> SRR1947492 1 0.3305 0.908008 0.776 0.000 0.000 0.224 0.000
#> SRR1947500 2 0.7924 0.306030 0.004 0.480 0.132 0.188 0.196
#> SRR1947491 2 0.7196 0.382980 0.000 0.568 0.136 0.148 0.148
#> SRR1947490 1 0.3707 0.836736 0.716 0.000 0.000 0.284 0.000
#> SRR1947489 4 0.2707 0.742947 0.000 0.000 0.132 0.860 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947546 2 0.6015 0.4730 0.000 0.584 0.264 0.012 0.040 0.100
#> SRR1947545 1 0.5481 0.3337 0.488 0.000 0.072 0.020 0.000 0.420
#> SRR1947544 1 0.6591 0.3116 0.420 0.000 0.104 0.088 0.000 0.388
#> SRR1947542 2 0.6015 0.4730 0.000 0.584 0.264 0.012 0.040 0.100
#> SRR1947541 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947540 4 0.4399 0.6757 0.000 0.188 0.036 0.736 0.040 0.000
#> SRR1947539 5 0.6438 0.4584 0.000 0.024 0.376 0.000 0.388 0.212
#> SRR1947538 4 0.2762 0.6695 0.000 0.196 0.000 0.804 0.000 0.000
#> SRR1947537 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947536 3 0.6735 0.5263 0.048 0.000 0.448 0.036 0.380 0.088
#> SRR1947535 5 0.6380 0.4633 0.000 0.024 0.380 0.000 0.400 0.196
#> SRR1947534 2 0.7477 0.0889 0.044 0.488 0.116 0.216 0.000 0.136
#> SRR1947533 2 0.2339 0.5292 0.000 0.896 0.020 0.012 0.072 0.000
#> SRR1947532 6 0.5356 0.5866 0.008 0.016 0.196 0.124 0.000 0.656
#> SRR1947531 4 0.4399 0.6757 0.000 0.188 0.036 0.736 0.040 0.000
#> SRR1947530 6 0.1194 0.8407 0.008 0.000 0.004 0.032 0.000 0.956
#> SRR1947529 2 0.6450 0.4369 0.000 0.540 0.264 0.104 0.004 0.088
#> SRR1947528 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947527 2 0.5768 0.1943 0.036 0.624 0.116 0.216 0.000 0.008
#> SRR1947526 2 0.2339 0.5292 0.000 0.896 0.020 0.012 0.072 0.000
#> SRR1947525 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947524 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947523 6 0.4085 0.7049 0.000 0.016 0.168 0.028 0.016 0.772
#> SRR1947521 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947520 2 0.3141 0.5115 0.000 0.828 0.020 0.012 0.140 0.000
#> SRR1947519 5 0.6380 0.4633 0.000 0.024 0.380 0.000 0.400 0.196
#> SRR1947518 4 0.2762 0.6695 0.000 0.196 0.000 0.804 0.000 0.000
#> SRR1947517 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947516 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 6 0.5356 0.5866 0.008 0.016 0.196 0.124 0.000 0.656
#> SRR1947514 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947512 1 0.1267 0.8523 0.940 0.000 0.000 0.000 0.000 0.060
#> SRR1947511 2 0.4390 0.3987 0.000 0.668 0.004 0.000 0.284 0.044
#> SRR1947510 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947572 4 0.8612 0.1331 0.280 0.144 0.144 0.300 0.000 0.132
#> SRR1947611 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947509 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947644 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947643 2 0.5367 -0.0624 0.000 0.532 0.024 0.384 0.060 0.000
#> SRR1947642 6 0.3835 0.6605 0.000 0.000 0.164 0.004 0.060 0.772
#> SRR1947640 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947641 5 0.6506 0.4558 0.000 0.024 0.388 0.004 0.388 0.196
#> SRR1947639 4 0.8612 0.1331 0.280 0.144 0.144 0.300 0.000 0.132
#> SRR1947638 6 0.6023 0.5121 0.004 0.080 0.204 0.100 0.000 0.612
#> SRR1947637 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947636 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947635 2 0.6492 0.4365 0.000 0.536 0.264 0.100 0.004 0.096
#> SRR1947634 2 0.4390 0.3987 0.000 0.668 0.004 0.000 0.284 0.044
#> SRR1947633 5 0.6438 0.4584 0.000 0.024 0.376 0.000 0.388 0.212
#> SRR1947632 2 0.6015 0.4730 0.000 0.584 0.264 0.012 0.040 0.100
#> SRR1947631 3 0.6734 -0.3810 0.000 0.024 0.336 0.004 0.324 0.312
#> SRR1947629 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947630 2 0.4390 0.3987 0.000 0.668 0.004 0.000 0.284 0.044
#> SRR1947627 6 0.6562 -0.4359 0.004 0.000 0.268 0.016 0.340 0.372
#> SRR1947628 4 0.4368 0.6772 0.000 0.184 0.036 0.740 0.040 0.000
#> SRR1947626 2 0.3868 -0.2854 0.000 0.504 0.000 0.496 0.000 0.000
#> SRR1947625 5 0.6506 0.4558 0.000 0.024 0.388 0.004 0.388 0.196
#> SRR1947624 2 0.4390 0.3987 0.000 0.668 0.004 0.000 0.284 0.044
#> SRR1947623 4 0.8631 0.1203 0.284 0.144 0.144 0.292 0.000 0.136
#> SRR1947622 2 0.6811 0.4151 0.000 0.476 0.300 0.124 0.004 0.096
#> SRR1947621 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 6 0.1155 0.8412 0.004 0.000 0.004 0.036 0.000 0.956
#> SRR1947619 5 0.6462 0.4526 0.000 0.024 0.368 0.000 0.388 0.220
#> SRR1947617 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 6 0.1155 0.8412 0.004 0.000 0.004 0.036 0.000 0.956
#> SRR1947616 4 0.5306 0.3155 0.000 0.444 0.032 0.484 0.040 0.000
#> SRR1947615 6 0.2667 0.7515 0.000 0.000 0.128 0.000 0.020 0.852
#> SRR1947614 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947613 1 0.1913 0.8510 0.908 0.000 0.000 0.012 0.000 0.080
#> SRR1947610 4 0.2762 0.6695 0.000 0.196 0.000 0.804 0.000 0.000
#> SRR1947612 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947608 5 0.6380 0.4633 0.000 0.024 0.380 0.000 0.400 0.196
#> SRR1947606 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947607 1 0.1913 0.8510 0.908 0.000 0.000 0.012 0.000 0.080
#> SRR1947604 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947605 1 0.5481 0.3337 0.488 0.000 0.072 0.020 0.000 0.420
#> SRR1947603 2 0.5503 0.4881 0.000 0.632 0.228 0.000 0.040 0.100
#> SRR1947602 6 0.1194 0.8407 0.008 0.000 0.004 0.032 0.000 0.956
#> SRR1947600 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947601 2 0.0363 0.5461 0.000 0.988 0.000 0.000 0.012 0.000
#> SRR1947598 4 0.4368 0.6772 0.000 0.184 0.036 0.740 0.040 0.000
#> SRR1947599 6 0.1003 0.8434 0.004 0.000 0.004 0.028 0.000 0.964
#> SRR1947597 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947596 6 0.6397 0.4005 0.108 0.000 0.156 0.164 0.000 0.572
#> SRR1947595 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947594 1 0.1267 0.8523 0.940 0.000 0.000 0.000 0.000 0.060
#> SRR1947592 5 0.6462 0.4526 0.000 0.024 0.368 0.000 0.388 0.220
#> SRR1947591 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 6 0.6397 0.4005 0.108 0.000 0.156 0.164 0.000 0.572
#> SRR1947588 1 0.1327 0.8545 0.936 0.000 0.000 0.000 0.000 0.064
#> SRR1947587 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947586 2 0.3868 -0.2854 0.000 0.504 0.000 0.496 0.000 0.000
#> SRR1947585 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947584 1 0.1327 0.8545 0.936 0.000 0.000 0.000 0.000 0.064
#> SRR1947583 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947582 6 0.1080 0.8417 0.004 0.000 0.004 0.032 0.000 0.960
#> SRR1947580 4 0.3999 0.2363 0.000 0.496 0.004 0.500 0.000 0.000
#> SRR1947581 1 0.1327 0.8545 0.936 0.000 0.000 0.000 0.000 0.064
#> SRR1947576 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947575 5 0.6380 0.4633 0.000 0.024 0.380 0.000 0.400 0.196
#> SRR1947579 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947578 4 0.4368 0.6772 0.000 0.184 0.036 0.740 0.040 0.000
#> SRR1947573 5 0.6438 0.4584 0.000 0.024 0.376 0.000 0.388 0.212
#> SRR1947574 6 0.5940 0.5144 0.004 0.080 0.204 0.092 0.000 0.620
#> SRR1947571 3 0.7341 -0.1981 0.008 0.100 0.384 0.188 0.000 0.320
#> SRR1947577 6 0.1155 0.8412 0.004 0.000 0.004 0.036 0.000 0.956
#> SRR1947570 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947569 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947566 2 0.4810 -0.1227 0.000 0.552 0.024 0.404 0.020 0.000
#> SRR1947567 2 0.6492 0.4365 0.000 0.536 0.264 0.100 0.004 0.096
#> SRR1947568 4 0.8754 0.2047 0.224 0.188 0.140 0.300 0.000 0.148
#> SRR1947564 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947563 5 0.6380 0.4633 0.000 0.024 0.380 0.000 0.400 0.196
#> SRR1947562 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947565 6 0.1036 0.8456 0.004 0.000 0.024 0.000 0.008 0.964
#> SRR1947559 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947560 5 0.1204 0.3271 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1947561 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.1327 0.8545 0.936 0.000 0.000 0.000 0.000 0.064
#> SRR1947558 3 0.6548 -0.5105 0.000 0.024 0.392 0.004 0.372 0.208
#> SRR1947556 1 0.6058 0.6240 0.616 0.000 0.136 0.140 0.000 0.108
#> SRR1947553 4 0.2762 0.6695 0.000 0.196 0.000 0.804 0.000 0.000
#> SRR1947554 1 0.1913 0.8510 0.908 0.000 0.000 0.012 0.000 0.080
#> SRR1947555 2 0.5503 0.4881 0.000 0.632 0.228 0.000 0.040 0.100
#> SRR1947550 6 0.1294 0.8435 0.008 0.004 0.008 0.024 0.000 0.956
#> SRR1947552 6 0.1003 0.8434 0.004 0.000 0.004 0.028 0.000 0.964
#> SRR1947549 5 0.6462 0.4526 0.000 0.024 0.368 0.000 0.388 0.220
#> SRR1947551 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947548 6 0.5356 0.5866 0.008 0.016 0.196 0.124 0.000 0.656
#> SRR1947506 6 0.1138 0.8440 0.012 0.000 0.024 0.000 0.004 0.960
#> SRR1947507 1 0.1267 0.8523 0.940 0.000 0.000 0.000 0.000 0.060
#> SRR1947504 1 0.2706 0.8178 0.876 0.000 0.008 0.060 0.000 0.056
#> SRR1947503 6 0.6023 0.5121 0.004 0.080 0.204 0.100 0.000 0.612
#> SRR1947502 2 0.0000 0.5469 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 2 0.6015 0.4730 0.000 0.584 0.264 0.012 0.040 0.100
#> SRR1947499 6 0.1194 0.8407 0.008 0.000 0.004 0.032 0.000 0.956
#> SRR1947498 3 0.5338 0.6465 0.048 0.000 0.496 0.020 0.432 0.004
#> SRR1947508 6 0.2667 0.7515 0.000 0.000 0.128 0.000 0.020 0.852
#> SRR1947505 4 0.4368 0.6772 0.000 0.184 0.036 0.740 0.040 0.000
#> SRR1947497 2 0.2339 0.5292 0.000 0.896 0.020 0.012 0.072 0.000
#> SRR1947496 1 0.1728 0.8504 0.924 0.000 0.004 0.008 0.000 0.064
#> SRR1947495 2 0.2339 0.5292 0.000 0.896 0.020 0.012 0.072 0.000
#> SRR1947494 6 0.2208 0.8203 0.004 0.004 0.052 0.032 0.000 0.908
#> SRR1947493 6 0.0622 0.8440 0.012 0.000 0.008 0.000 0.000 0.980
#> SRR1947492 1 0.1913 0.8510 0.908 0.000 0.000 0.012 0.000 0.080
#> SRR1947500 2 0.7292 0.3784 0.004 0.440 0.276 0.128 0.004 0.148
#> SRR1947491 2 0.6492 0.4365 0.000 0.536 0.264 0.100 0.004 0.096
#> SRR1947490 1 0.2673 0.7906 0.852 0.000 0.004 0.012 0.000 0.132
#> SRR1947489 6 0.2624 0.7562 0.000 0.000 0.124 0.000 0.020 0.856
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 15148 rows and 152 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 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 0.228 0.564 0.718 0.4628 0.505 0.505
#> 3 3 0.656 0.848 0.891 0.4036 0.690 0.459
#> 4 4 0.584 0.559 0.761 0.1138 0.929 0.793
#> 5 5 0.556 0.657 0.716 0.0602 0.801 0.429
#> 6 6 0.639 0.673 0.737 0.0576 0.955 0.797
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
#> SRR1947547 1 0.8081 0.5829 0.752 0.248
#> SRR1947546 2 0.7883 0.6556 0.236 0.764
#> SRR1947545 1 0.0000 0.7699 1.000 0.000
#> SRR1947544 1 0.0000 0.7699 1.000 0.000
#> SRR1947542 2 0.8267 0.6423 0.260 0.740
#> SRR1947541 1 0.8443 0.5601 0.728 0.272
#> SRR1947540 2 0.7219 0.6456 0.200 0.800
#> SRR1947539 2 0.9170 0.4166 0.332 0.668
#> SRR1947538 1 0.8443 0.4566 0.728 0.272
#> SRR1947537 1 0.9909 0.2645 0.556 0.444
#> SRR1947536 2 0.9491 0.2932 0.368 0.632
#> SRR1947535 2 0.9044 0.4493 0.320 0.680
#> SRR1947534 1 0.8386 0.4023 0.732 0.268
#> SRR1947533 2 0.8016 0.6513 0.244 0.756
#> SRR1947532 1 0.1633 0.7590 0.976 0.024
#> SRR1947531 2 0.7219 0.6456 0.200 0.800
#> SRR1947530 1 0.8081 0.5829 0.752 0.248
#> SRR1947529 2 0.7815 0.6564 0.232 0.768
#> SRR1947528 1 0.9686 0.3638 0.604 0.396
#> SRR1947527 2 0.8327 0.6362 0.264 0.736
#> SRR1947526 2 0.7815 0.6564 0.232 0.768
#> SRR1947525 1 0.9170 0.3007 0.668 0.332
#> SRR1947524 2 0.8909 0.4162 0.308 0.692
#> SRR1947523 2 0.9944 0.4680 0.456 0.544
#> SRR1947521 2 0.8955 0.4451 0.312 0.688
#> SRR1947520 2 0.7815 0.6564 0.232 0.768
#> SRR1947519 2 0.9170 0.4334 0.332 0.668
#> SRR1947518 1 0.8443 0.4566 0.728 0.272
#> SRR1947517 2 0.8955 0.4451 0.312 0.688
#> SRR1947516 2 0.8144 0.6465 0.252 0.748
#> SRR1947515 1 0.3274 0.7315 0.940 0.060
#> SRR1947514 2 0.8327 0.6362 0.264 0.736
#> SRR1947513 1 0.2236 0.7561 0.964 0.036
#> SRR1947512 1 0.2043 0.7464 0.968 0.032
#> SRR1947511 2 0.7815 0.6564 0.232 0.768
#> SRR1947510 2 0.8955 0.4451 0.312 0.688
#> SRR1947572 1 0.2423 0.7399 0.960 0.040
#> SRR1947611 2 0.8267 0.4899 0.260 0.740
#> SRR1947509 2 0.9608 0.3101 0.384 0.616
#> SRR1947644 2 0.8555 0.4442 0.280 0.720
#> SRR1947643 2 0.7219 0.6456 0.200 0.800
#> SRR1947642 2 0.9170 0.4334 0.332 0.668
#> SRR1947640 1 0.7745 0.4660 0.772 0.228
#> SRR1947641 2 0.8955 0.4512 0.312 0.688
#> SRR1947639 1 0.8081 0.4665 0.752 0.248
#> SRR1947638 1 0.0376 0.7685 0.996 0.004
#> SRR1947637 2 0.7376 0.5216 0.208 0.792
#> SRR1947636 1 0.9909 0.2645 0.556 0.444
#> SRR1947635 2 0.7950 0.6545 0.240 0.760
#> SRR1947634 2 0.7815 0.6564 0.232 0.768
#> SRR1947633 2 0.9170 0.4166 0.332 0.668
#> SRR1947632 2 0.7950 0.6549 0.240 0.760
#> SRR1947631 2 0.9170 0.4334 0.332 0.668
#> SRR1947629 2 0.8909 0.4162 0.308 0.692
#> SRR1947630 2 0.7602 0.6552 0.220 0.780
#> SRR1947627 1 0.9732 0.3456 0.596 0.404
#> SRR1947628 2 0.7299 0.6463 0.204 0.796
#> SRR1947626 2 0.7815 0.6258 0.232 0.768
#> SRR1947625 2 0.8955 0.4512 0.312 0.688
#> SRR1947624 2 0.7602 0.6552 0.220 0.780
#> SRR1947623 1 0.0000 0.7699 1.000 0.000
#> SRR1947622 2 0.7950 0.6407 0.240 0.760
#> SRR1947621 2 0.8327 0.6362 0.264 0.736
#> SRR1947620 1 0.0000 0.7699 1.000 0.000
#> SRR1947619 1 0.9922 0.2529 0.552 0.448
#> SRR1947617 2 0.8144 0.6465 0.252 0.748
#> SRR1947618 1 0.2236 0.7561 0.964 0.036
#> SRR1947616 2 0.7056 0.6432 0.192 0.808
#> SRR1947615 2 0.9954 0.0795 0.460 0.540
#> SRR1947614 2 0.8955 0.4451 0.312 0.688
#> SRR1947613 1 0.0376 0.7687 0.996 0.004
#> SRR1947610 2 0.9775 0.3301 0.412 0.588
#> SRR1947612 2 0.8327 0.6362 0.264 0.736
#> SRR1947609 1 0.2236 0.7561 0.964 0.036
#> SRR1947608 2 0.9000 0.4538 0.316 0.684
#> SRR1947606 1 0.9686 0.3638 0.604 0.396
#> SRR1947607 1 0.0938 0.7651 0.988 0.012
#> SRR1947604 1 0.4562 0.7084 0.904 0.096
#> SRR1947605 1 0.0000 0.7699 1.000 0.000
#> SRR1947603 2 0.7815 0.6564 0.232 0.768
#> SRR1947602 1 0.8081 0.5829 0.752 0.248
#> SRR1947600 2 0.8909 0.4162 0.308 0.692
#> SRR1947601 2 0.7815 0.6564 0.232 0.768
#> SRR1947598 2 0.9954 0.4313 0.460 0.540
#> SRR1947599 1 0.2236 0.7561 0.964 0.036
#> SRR1947597 2 0.8144 0.6482 0.252 0.748
#> SRR1947596 1 0.0000 0.7699 1.000 0.000
#> SRR1947595 1 0.8608 0.3090 0.716 0.284
#> SRR1947594 1 0.0376 0.7687 0.996 0.004
#> SRR1947592 2 0.9896 0.1527 0.440 0.560
#> SRR1947591 2 0.8144 0.6465 0.252 0.748
#> SRR1947590 1 0.0000 0.7699 1.000 0.000
#> SRR1947588 1 0.0000 0.7699 1.000 0.000
#> SRR1947587 1 0.9896 0.2749 0.560 0.440
#> SRR1947586 2 0.7815 0.6258 0.232 0.768
#> SRR1947585 2 0.8909 0.4162 0.308 0.692
#> SRR1947584 1 0.0376 0.7687 0.996 0.004
#> SRR1947583 1 0.9732 0.0500 0.596 0.404
#> SRR1947582 1 0.2236 0.7561 0.964 0.036
#> SRR1947580 2 0.7528 0.6385 0.216 0.784
#> SRR1947581 1 0.0000 0.7699 1.000 0.000
#> SRR1947576 2 0.7674 0.5123 0.224 0.776
#> SRR1947575 2 0.7376 0.5294 0.208 0.792
#> SRR1947579 2 0.8955 0.4451 0.312 0.688
#> SRR1947578 2 0.7219 0.6456 0.200 0.800
#> SRR1947573 2 0.9209 0.4158 0.336 0.664
#> SRR1947574 1 0.2423 0.7392 0.960 0.040
#> SRR1947571 1 0.7602 0.5097 0.780 0.220
#> SRR1947577 1 0.2236 0.7561 0.964 0.036
#> SRR1947570 1 0.7453 0.5988 0.788 0.212
#> SRR1947569 2 0.8909 0.4162 0.308 0.692
#> SRR1947566 2 0.7056 0.6432 0.192 0.808
#> SRR1947567 2 0.8144 0.6482 0.252 0.748
#> SRR1947568 1 0.8861 0.3532 0.696 0.304
#> SRR1947564 2 0.8267 0.6396 0.260 0.740
#> SRR1947563 2 0.8267 0.4993 0.260 0.740
#> SRR1947562 2 0.9998 0.2237 0.492 0.508
#> SRR1947565 1 0.9909 0.2645 0.556 0.444
#> SRR1947559 2 0.8144 0.6482 0.252 0.748
#> SRR1947560 2 0.8144 0.4951 0.252 0.748
#> SRR1947561 2 0.7815 0.6564 0.232 0.768
#> SRR1947557 1 0.0000 0.7699 1.000 0.000
#> SRR1947558 2 0.9170 0.4334 0.332 0.668
#> SRR1947556 1 0.0000 0.7699 1.000 0.000
#> SRR1947553 2 0.9775 0.3301 0.412 0.588
#> SRR1947554 1 0.0376 0.7687 0.996 0.004
#> SRR1947555 2 0.7815 0.6564 0.232 0.768
#> SRR1947550 1 0.9732 0.0632 0.596 0.404
#> SRR1947552 1 0.2236 0.7561 0.964 0.036
#> SRR1947549 2 0.9850 0.1924 0.428 0.572
#> SRR1947551 2 0.8555 0.4442 0.280 0.720
#> SRR1947548 1 0.5842 0.6403 0.860 0.140
#> SRR1947506 1 0.8081 0.5829 0.752 0.248
#> SRR1947507 1 0.0376 0.7687 0.996 0.004
#> SRR1947504 1 0.0000 0.7699 1.000 0.000
#> SRR1947503 1 0.0376 0.7685 0.996 0.004
#> SRR1947502 2 0.7815 0.6564 0.232 0.768
#> SRR1947501 2 0.7883 0.6556 0.236 0.764
#> SRR1947499 1 0.8081 0.5829 0.752 0.248
#> SRR1947498 2 0.8909 0.4162 0.308 0.692
#> SRR1947508 2 0.9732 0.2898 0.404 0.596
#> SRR1947505 2 0.8608 0.6175 0.284 0.716
#> SRR1947497 2 0.8081 0.6489 0.248 0.752
#> SRR1947496 1 0.0000 0.7699 1.000 0.000
#> SRR1947495 2 0.8081 0.6489 0.248 0.752
#> SRR1947494 1 0.1633 0.7590 0.976 0.024
#> SRR1947493 1 0.7528 0.5965 0.784 0.216
#> SRR1947492 1 0.0376 0.7687 0.996 0.004
#> SRR1947500 2 0.8144 0.6482 0.252 0.748
#> SRR1947491 2 0.9129 0.6060 0.328 0.672
#> SRR1947490 1 0.0000 0.7699 1.000 0.000
#> SRR1947489 1 0.9686 0.3638 0.604 0.396
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.4047 0.8609 0.148 0.004 0.848
#> SRR1947546 2 0.2550 0.9237 0.024 0.936 0.040
#> SRR1947545 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947544 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947542 2 0.2681 0.9220 0.028 0.932 0.040
#> SRR1947541 3 0.3851 0.8712 0.136 0.004 0.860
#> SRR1947540 2 0.2625 0.8766 0.000 0.916 0.084
#> SRR1947539 3 0.3155 0.9043 0.040 0.044 0.916
#> SRR1947538 1 0.7758 0.6061 0.636 0.280 0.084
#> SRR1947537 3 0.3755 0.8823 0.120 0.008 0.872
#> SRR1947536 3 0.2550 0.8555 0.012 0.056 0.932
#> SRR1947535 3 0.3683 0.9045 0.044 0.060 0.896
#> SRR1947534 1 0.4291 0.8149 0.840 0.152 0.008
#> SRR1947533 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947532 1 0.4324 0.8497 0.860 0.112 0.028
#> SRR1947531 2 0.2625 0.8766 0.000 0.916 0.084
#> SRR1947530 3 0.6345 0.4813 0.400 0.004 0.596
#> SRR1947529 2 0.1999 0.9270 0.012 0.952 0.036
#> SRR1947528 3 0.3573 0.8830 0.120 0.004 0.876
#> SRR1947527 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947526 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947525 1 0.7377 0.1832 0.516 0.452 0.032
#> SRR1947524 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947523 2 0.4399 0.8633 0.092 0.864 0.044
#> SRR1947521 3 0.3337 0.8995 0.032 0.060 0.908
#> SRR1947520 2 0.2297 0.9239 0.020 0.944 0.036
#> SRR1947519 3 0.3683 0.9045 0.044 0.060 0.896
#> SRR1947518 1 0.7557 0.6285 0.656 0.264 0.080
#> SRR1947517 3 0.3337 0.8995 0.032 0.060 0.908
#> SRR1947516 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947515 1 0.5982 0.7250 0.744 0.228 0.028
#> SRR1947514 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947513 1 0.3472 0.8742 0.904 0.056 0.040
#> SRR1947512 1 0.2269 0.8614 0.944 0.016 0.040
#> SRR1947511 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947510 3 0.3310 0.8977 0.028 0.064 0.908
#> SRR1947572 1 0.1525 0.8847 0.964 0.032 0.004
#> SRR1947611 3 0.3129 0.8830 0.008 0.088 0.904
#> SRR1947509 3 0.3356 0.8999 0.036 0.056 0.908
#> SRR1947644 3 0.2173 0.8497 0.008 0.048 0.944
#> SRR1947643 2 0.0237 0.9106 0.000 0.996 0.004
#> SRR1947642 3 0.3683 0.9045 0.044 0.060 0.896
#> SRR1947640 2 0.7034 0.5675 0.284 0.668 0.048
#> SRR1947641 3 0.3572 0.9048 0.040 0.060 0.900
#> SRR1947639 1 0.6673 0.5224 0.636 0.344 0.020
#> SRR1947638 1 0.2879 0.8804 0.924 0.052 0.024
#> SRR1947637 3 0.3043 0.8846 0.008 0.084 0.908
#> SRR1947636 3 0.3682 0.8847 0.116 0.008 0.876
#> SRR1947635 2 0.2681 0.9220 0.028 0.932 0.040
#> SRR1947634 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947633 3 0.3155 0.9043 0.040 0.044 0.916
#> SRR1947632 2 0.2806 0.9196 0.032 0.928 0.040
#> SRR1947631 3 0.3683 0.9045 0.044 0.060 0.896
#> SRR1947629 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947630 2 0.2527 0.9201 0.020 0.936 0.044
#> SRR1947627 3 0.3295 0.8939 0.096 0.008 0.896
#> SRR1947628 2 0.2860 0.8760 0.004 0.912 0.084
#> SRR1947626 2 0.1989 0.8926 0.004 0.948 0.048
#> SRR1947625 3 0.3572 0.9048 0.040 0.060 0.900
#> SRR1947624 2 0.2636 0.9189 0.020 0.932 0.048
#> SRR1947623 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947622 2 0.1337 0.9193 0.012 0.972 0.016
#> SRR1947621 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947620 1 0.1620 0.8817 0.964 0.012 0.024
#> SRR1947619 3 0.3896 0.8797 0.128 0.008 0.864
#> SRR1947617 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947618 1 0.3472 0.8742 0.904 0.056 0.040
#> SRR1947616 2 0.2860 0.8726 0.004 0.912 0.084
#> SRR1947615 3 0.3918 0.8798 0.120 0.012 0.868
#> SRR1947614 3 0.3337 0.8995 0.032 0.060 0.908
#> SRR1947613 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947610 2 0.3043 0.8783 0.008 0.908 0.084
#> SRR1947612 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947609 1 0.3472 0.8742 0.904 0.056 0.040
#> SRR1947608 3 0.3791 0.9039 0.048 0.060 0.892
#> SRR1947606 3 0.3573 0.8830 0.120 0.004 0.876
#> SRR1947607 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947604 1 0.6335 0.6997 0.724 0.240 0.036
#> SRR1947605 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947603 2 0.2269 0.9253 0.016 0.944 0.040
#> SRR1947602 3 0.6148 0.5798 0.356 0.004 0.640
#> SRR1947600 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947601 2 0.2152 0.9256 0.016 0.948 0.036
#> SRR1947598 2 0.4007 0.8597 0.036 0.880 0.084
#> SRR1947599 1 0.4206 0.8622 0.872 0.088 0.040
#> SRR1947597 2 0.2550 0.9237 0.024 0.936 0.040
#> SRR1947596 1 0.1525 0.8847 0.964 0.032 0.004
#> SRR1947595 2 0.6937 0.5911 0.272 0.680 0.048
#> SRR1947594 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947592 3 0.3550 0.8994 0.080 0.024 0.896
#> SRR1947591 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947590 1 0.1525 0.8847 0.964 0.032 0.004
#> SRR1947588 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947587 3 0.3682 0.8847 0.116 0.008 0.876
#> SRR1947586 2 0.2096 0.8911 0.004 0.944 0.052
#> SRR1947585 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947584 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947583 2 0.6685 0.6463 0.244 0.708 0.048
#> SRR1947582 1 0.3472 0.8742 0.904 0.056 0.040
#> SRR1947580 2 0.2625 0.8751 0.000 0.916 0.084
#> SRR1947581 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947576 3 0.3129 0.8830 0.008 0.088 0.904
#> SRR1947575 3 0.3587 0.8912 0.020 0.088 0.892
#> SRR1947579 3 0.3337 0.8995 0.032 0.060 0.908
#> SRR1947578 2 0.2625 0.8766 0.000 0.916 0.084
#> SRR1947573 3 0.3589 0.9054 0.052 0.048 0.900
#> SRR1947574 1 0.3973 0.8665 0.880 0.088 0.032
#> SRR1947571 1 0.6066 0.6987 0.728 0.248 0.024
#> SRR1947577 1 0.3472 0.8742 0.904 0.056 0.040
#> SRR1947570 3 0.6495 0.3080 0.460 0.004 0.536
#> SRR1947569 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947566 2 0.1753 0.8924 0.000 0.952 0.048
#> SRR1947567 2 0.2681 0.9220 0.028 0.932 0.040
#> SRR1947568 1 0.5138 0.6859 0.748 0.252 0.000
#> SRR1947564 2 0.2313 0.9268 0.024 0.944 0.032
#> SRR1947563 3 0.3791 0.9039 0.048 0.060 0.892
#> SRR1947562 2 0.6546 0.6632 0.240 0.716 0.044
#> SRR1947565 3 0.3682 0.8847 0.116 0.008 0.876
#> SRR1947559 2 0.2806 0.9219 0.032 0.928 0.040
#> SRR1947560 3 0.3129 0.8830 0.008 0.088 0.904
#> SRR1947561 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947557 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947558 3 0.3683 0.9045 0.044 0.060 0.896
#> SRR1947556 1 0.0661 0.8839 0.988 0.008 0.004
#> SRR1947553 2 0.3043 0.8783 0.008 0.908 0.084
#> SRR1947554 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947555 2 0.2096 0.9189 0.004 0.944 0.052
#> SRR1947550 2 0.6967 0.5705 0.288 0.668 0.044
#> SRR1947552 1 0.4092 0.8615 0.876 0.088 0.036
#> SRR1947549 3 0.3713 0.9023 0.076 0.032 0.892
#> SRR1947551 3 0.2173 0.8497 0.008 0.048 0.944
#> SRR1947548 1 0.6148 0.7023 0.728 0.244 0.028
#> SRR1947506 3 0.5553 0.7136 0.272 0.004 0.724
#> SRR1947507 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947504 1 0.0661 0.8839 0.988 0.008 0.004
#> SRR1947503 1 0.2743 0.8806 0.928 0.052 0.020
#> SRR1947502 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947501 2 0.2550 0.9237 0.024 0.936 0.040
#> SRR1947499 3 0.6209 0.5550 0.368 0.004 0.628
#> SRR1947498 3 0.2651 0.8536 0.012 0.060 0.928
#> SRR1947508 3 0.3692 0.9047 0.056 0.048 0.896
#> SRR1947505 2 0.2711 0.8757 0.000 0.912 0.088
#> SRR1947497 2 0.2176 0.9270 0.020 0.948 0.032
#> SRR1947496 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947495 2 0.2050 0.9275 0.020 0.952 0.028
#> SRR1947494 1 0.4324 0.8497 0.860 0.112 0.028
#> SRR1947493 1 0.6280 -0.0795 0.540 0.000 0.460
#> SRR1947492 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947500 2 0.2681 0.9220 0.028 0.932 0.040
#> SRR1947491 2 0.3375 0.9025 0.048 0.908 0.044
#> SRR1947490 1 0.0848 0.8845 0.984 0.008 0.008
#> SRR1947489 3 0.4059 0.8737 0.128 0.012 0.860
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.4406 0.74025 0.044 0.004 0.808 0.144
#> SRR1947546 2 0.5626 0.37638 0.004 0.696 0.056 0.244
#> SRR1947545 1 0.0921 0.68937 0.972 0.000 0.000 0.028
#> SRR1947544 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947542 2 0.5848 0.32622 0.004 0.664 0.056 0.276
#> SRR1947541 3 0.4199 0.75222 0.044 0.004 0.824 0.128
#> SRR1947540 4 0.4941 0.38080 0.000 0.436 0.000 0.564
#> SRR1947539 3 0.1637 0.76870 0.000 0.000 0.940 0.060
#> SRR1947538 4 0.6430 0.28161 0.312 0.092 0.000 0.596
#> SRR1947537 3 0.3734 0.76832 0.044 0.004 0.856 0.096
#> SRR1947536 3 0.4920 0.57628 0.000 0.004 0.628 0.368
#> SRR1947535 3 0.1975 0.78669 0.012 0.016 0.944 0.028
#> SRR1947534 1 0.4770 0.38724 0.700 0.288 0.000 0.012
#> SRR1947533 2 0.0707 0.69670 0.000 0.980 0.000 0.020
#> SRR1947532 1 0.8441 0.31925 0.452 0.104 0.084 0.360
#> SRR1947531 4 0.4941 0.38080 0.000 0.436 0.000 0.564
#> SRR1947530 3 0.6755 0.53712 0.232 0.004 0.620 0.144
#> SRR1947529 2 0.2466 0.64928 0.000 0.900 0.004 0.096
#> SRR1947528 3 0.3917 0.76471 0.044 0.004 0.844 0.108
#> SRR1947527 2 0.0707 0.69703 0.000 0.980 0.000 0.020
#> SRR1947526 2 0.0469 0.69729 0.000 0.988 0.000 0.012
#> SRR1947525 2 0.8956 -0.32216 0.324 0.348 0.052 0.276
#> SRR1947524 3 0.4905 0.56740 0.000 0.004 0.632 0.364
#> SRR1947523 2 0.7737 -0.17329 0.016 0.444 0.144 0.396
#> SRR1947521 3 0.3933 0.72766 0.000 0.008 0.792 0.200
#> SRR1947520 2 0.0592 0.69671 0.000 0.984 0.000 0.016
#> SRR1947519 3 0.3680 0.77204 0.012 0.016 0.852 0.120
#> SRR1947518 4 0.6292 0.23934 0.332 0.076 0.000 0.592
#> SRR1947517 3 0.3933 0.72766 0.000 0.008 0.792 0.200
#> SRR1947516 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947515 1 0.8706 0.25939 0.424 0.132 0.084 0.360
#> SRR1947514 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947513 1 0.7523 0.48997 0.556 0.032 0.112 0.300
#> SRR1947512 1 0.0469 0.68137 0.988 0.000 0.000 0.012
#> SRR1947511 2 0.0592 0.69671 0.000 0.984 0.000 0.016
#> SRR1947510 3 0.3933 0.72766 0.000 0.008 0.792 0.200
#> SRR1947572 1 0.2988 0.63889 0.876 0.012 0.000 0.112
#> SRR1947611 3 0.4011 0.72689 0.000 0.008 0.784 0.208
#> SRR1947509 3 0.4011 0.72854 0.000 0.008 0.784 0.208
#> SRR1947644 3 0.4981 0.50315 0.000 0.000 0.536 0.464
#> SRR1947643 2 0.2149 0.65078 0.000 0.912 0.000 0.088
#> SRR1947642 3 0.3680 0.77204 0.012 0.016 0.852 0.120
#> SRR1947640 4 0.9052 0.26667 0.144 0.364 0.108 0.384
#> SRR1947641 3 0.2074 0.78662 0.012 0.016 0.940 0.032
#> SRR1947639 1 0.8908 -0.07092 0.384 0.272 0.052 0.292
#> SRR1947638 1 0.6362 0.56427 0.656 0.028 0.052 0.264
#> SRR1947637 3 0.3972 0.72695 0.000 0.008 0.788 0.204
#> SRR1947636 3 0.3670 0.77022 0.044 0.004 0.860 0.092
#> SRR1947635 2 0.5897 0.31133 0.004 0.656 0.056 0.284
#> SRR1947634 2 0.0592 0.69671 0.000 0.984 0.000 0.016
#> SRR1947633 3 0.1867 0.76562 0.000 0.000 0.928 0.072
#> SRR1947632 2 0.6399 0.24402 0.008 0.632 0.080 0.280
#> SRR1947631 3 0.3623 0.77211 0.012 0.016 0.856 0.116
#> SRR1947629 3 0.4905 0.56740 0.000 0.004 0.632 0.364
#> SRR1947630 2 0.2546 0.61867 0.000 0.900 0.008 0.092
#> SRR1947627 3 0.2310 0.78875 0.028 0.004 0.928 0.040
#> SRR1947628 4 0.4877 0.41660 0.000 0.408 0.000 0.592
#> SRR1947626 2 0.2281 0.64210 0.000 0.904 0.000 0.096
#> SRR1947625 3 0.2074 0.78662 0.012 0.016 0.940 0.032
#> SRR1947624 2 0.3443 0.55928 0.000 0.848 0.016 0.136
#> SRR1947623 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947622 2 0.4122 0.48017 0.000 0.760 0.004 0.236
#> SRR1947621 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947620 1 0.6227 0.55523 0.636 0.004 0.076 0.284
#> SRR1947619 3 0.3538 0.77279 0.044 0.004 0.868 0.084
#> SRR1947617 2 0.0707 0.69634 0.000 0.980 0.000 0.020
#> SRR1947618 1 0.7540 0.48655 0.552 0.032 0.112 0.304
#> SRR1947616 2 0.4916 -0.03567 0.000 0.576 0.000 0.424
#> SRR1947615 3 0.4517 0.73242 0.036 0.004 0.792 0.168
#> SRR1947614 3 0.3933 0.72766 0.000 0.008 0.792 0.200
#> SRR1947613 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.5571 0.42251 0.024 0.396 0.000 0.580
#> SRR1947612 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947609 1 0.7799 0.40327 0.476 0.032 0.116 0.376
#> SRR1947608 3 0.2074 0.78642 0.012 0.016 0.940 0.032
#> SRR1947606 3 0.3857 0.76698 0.044 0.004 0.848 0.104
#> SRR1947607 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.8779 -0.26529 0.388 0.128 0.092 0.392
#> SRR1947605 1 0.0707 0.69067 0.980 0.000 0.000 0.020
#> SRR1947603 2 0.1902 0.67086 0.000 0.932 0.004 0.064
#> SRR1947602 3 0.6667 0.55894 0.220 0.004 0.632 0.144
#> SRR1947600 3 0.4905 0.56740 0.000 0.004 0.632 0.364
#> SRR1947601 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947598 4 0.5072 0.48082 0.000 0.208 0.052 0.740
#> SRR1947599 1 0.8284 0.34072 0.432 0.060 0.116 0.392
#> SRR1947597 2 0.3933 0.51399 0.000 0.792 0.008 0.200
#> SRR1947596 1 0.5858 0.56961 0.656 0.008 0.044 0.292
#> SRR1947595 4 0.9316 0.28795 0.096 0.280 0.240 0.384
#> SRR1947594 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.1296 0.78861 0.028 0.004 0.964 0.004
#> SRR1947591 2 0.0592 0.69732 0.000 0.984 0.000 0.016
#> SRR1947590 1 0.6129 0.56354 0.644 0.012 0.052 0.292
#> SRR1947588 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.3770 0.76789 0.040 0.004 0.852 0.104
#> SRR1947586 2 0.2589 0.62494 0.000 0.884 0.000 0.116
#> SRR1947585 3 0.4905 0.56740 0.000 0.004 0.632 0.364
#> SRR1947584 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947583 2 0.8723 -0.26964 0.104 0.408 0.108 0.380
#> SRR1947582 1 0.7540 0.48655 0.552 0.032 0.112 0.304
#> SRR1947580 2 0.4679 0.15112 0.000 0.648 0.000 0.352
#> SRR1947581 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.4011 0.72689 0.000 0.008 0.784 0.208
#> SRR1947575 3 0.2057 0.78550 0.008 0.020 0.940 0.032
#> SRR1947579 3 0.3933 0.72766 0.000 0.008 0.792 0.200
#> SRR1947578 4 0.4941 0.38080 0.000 0.436 0.000 0.564
#> SRR1947573 3 0.1697 0.78339 0.016 0.004 0.952 0.028
#> SRR1947574 1 0.7558 0.42874 0.528 0.072 0.052 0.348
#> SRR1947571 1 0.8403 0.26573 0.444 0.140 0.056 0.360
#> SRR1947577 1 0.7523 0.48997 0.556 0.032 0.112 0.300
#> SRR1947570 3 0.6212 0.61403 0.164 0.004 0.684 0.148
#> SRR1947569 3 0.4889 0.56898 0.000 0.004 0.636 0.360
#> SRR1947566 2 0.2469 0.61342 0.000 0.892 0.000 0.108
#> SRR1947567 2 0.5742 0.34929 0.004 0.680 0.056 0.260
#> SRR1947568 1 0.5140 0.49559 0.760 0.144 0.000 0.096
#> SRR1947564 2 0.0707 0.69634 0.000 0.980 0.000 0.020
#> SRR1947563 3 0.2074 0.78642 0.012 0.016 0.940 0.032
#> SRR1947562 2 0.8360 -0.17173 0.104 0.472 0.080 0.344
#> SRR1947565 3 0.3670 0.77022 0.044 0.004 0.860 0.092
#> SRR1947559 2 0.5532 0.39418 0.004 0.708 0.056 0.232
#> SRR1947560 3 0.4011 0.72689 0.000 0.008 0.784 0.208
#> SRR1947561 2 0.0336 0.69807 0.000 0.992 0.000 0.008
#> SRR1947557 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.1975 0.78669 0.012 0.016 0.944 0.028
#> SRR1947556 1 0.0592 0.68823 0.984 0.000 0.000 0.016
#> SRR1947553 4 0.5571 0.42251 0.024 0.396 0.000 0.580
#> SRR1947554 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947555 2 0.0921 0.69262 0.000 0.972 0.000 0.028
#> SRR1947550 4 0.9024 0.25883 0.140 0.368 0.108 0.384
#> SRR1947552 1 0.8340 0.33193 0.428 0.064 0.116 0.392
#> SRR1947549 3 0.1296 0.78861 0.028 0.004 0.964 0.004
#> SRR1947551 3 0.4985 0.49789 0.000 0.000 0.532 0.468
#> SRR1947548 1 0.8843 0.19687 0.404 0.156 0.080 0.360
#> SRR1947506 3 0.4722 0.72793 0.060 0.004 0.792 0.144
#> SRR1947507 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0592 0.68823 0.984 0.000 0.000 0.016
#> SRR1947503 1 0.6786 0.49634 0.572 0.028 0.052 0.348
#> SRR1947502 2 0.0336 0.69807 0.000 0.992 0.000 0.008
#> SRR1947501 2 0.5626 0.37638 0.004 0.696 0.056 0.244
#> SRR1947499 3 0.6697 0.55127 0.224 0.004 0.628 0.144
#> SRR1947498 3 0.4905 0.56740 0.000 0.004 0.632 0.364
#> SRR1947508 3 0.3828 0.76787 0.020 0.008 0.840 0.132
#> SRR1947505 4 0.4819 0.46531 0.000 0.344 0.004 0.652
#> SRR1947497 2 0.0592 0.69671 0.000 0.984 0.000 0.016
#> SRR1947496 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0592 0.69671 0.000 0.984 0.000 0.016
#> SRR1947494 1 0.8452 0.31694 0.448 0.100 0.088 0.364
#> SRR1947493 3 0.7182 0.37964 0.300 0.004 0.548 0.148
#> SRR1947492 1 0.0000 0.69273 1.000 0.000 0.000 0.000
#> SRR1947500 2 0.5989 0.27705 0.004 0.640 0.056 0.300
#> SRR1947491 2 0.6918 -0.00166 0.016 0.532 0.072 0.380
#> SRR1947490 1 0.0188 0.69193 0.996 0.000 0.000 0.004
#> SRR1947489 3 0.4561 0.73160 0.036 0.004 0.788 0.172
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.1768 0.7052 0.004 0.000 0.924 0.072 0.000
#> SRR1947546 4 0.6435 0.5717 0.000 0.304 0.164 0.524 0.008
#> SRR1947545 1 0.2313 0.8820 0.912 0.000 0.044 0.040 0.004
#> SRR1947544 1 0.1153 0.9284 0.964 0.000 0.024 0.008 0.004
#> SRR1947542 4 0.6513 0.6196 0.000 0.232 0.160 0.580 0.028
#> SRR1947541 3 0.1173 0.7377 0.004 0.000 0.964 0.020 0.012
#> SRR1947540 4 0.6272 0.1474 0.000 0.236 0.004 0.560 0.200
#> SRR1947539 3 0.4101 -0.0650 0.000 0.000 0.628 0.000 0.372
#> SRR1947538 4 0.5659 0.4021 0.060 0.048 0.004 0.692 0.196
#> SRR1947537 3 0.2116 0.7399 0.004 0.000 0.912 0.008 0.076
#> SRR1947536 5 0.6744 0.5053 0.012 0.000 0.380 0.172 0.436
#> SRR1947535 3 0.3927 0.6630 0.000 0.004 0.792 0.040 0.164
#> SRR1947534 1 0.4600 0.4429 0.632 0.352 0.004 0.008 0.004
#> SRR1947533 2 0.0404 0.8892 0.000 0.988 0.000 0.012 0.000
#> SRR1947532 4 0.6926 0.6260 0.116 0.024 0.252 0.576 0.032
#> SRR1947531 4 0.6272 0.1474 0.000 0.236 0.004 0.560 0.200
#> SRR1947530 3 0.4054 0.5814 0.140 0.000 0.788 0.072 0.000
#> SRR1947529 2 0.4360 0.7112 0.000 0.760 0.016 0.192 0.032
#> SRR1947528 3 0.1173 0.7418 0.004 0.000 0.964 0.012 0.020
#> SRR1947527 2 0.0579 0.8904 0.000 0.984 0.000 0.008 0.008
#> SRR1947526 2 0.0162 0.8897 0.000 0.996 0.000 0.004 0.000
#> SRR1947525 4 0.7724 0.6500 0.100 0.176 0.144 0.552 0.028
#> SRR1947524 5 0.6693 0.5539 0.012 0.000 0.332 0.176 0.480
#> SRR1947523 4 0.6043 0.6091 0.000 0.128 0.308 0.560 0.004
#> SRR1947521 5 0.4165 0.6831 0.000 0.008 0.320 0.000 0.672
#> SRR1947520 2 0.0798 0.8873 0.000 0.976 0.000 0.016 0.008
#> SRR1947519 3 0.2390 0.7409 0.000 0.004 0.908 0.044 0.044
#> SRR1947518 4 0.5834 0.3987 0.072 0.048 0.004 0.680 0.196
#> SRR1947517 5 0.4165 0.6831 0.000 0.008 0.320 0.000 0.672
#> SRR1947516 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947515 4 0.6962 0.6277 0.112 0.028 0.252 0.576 0.032
#> SRR1947514 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947513 3 0.7118 -0.4565 0.224 0.012 0.380 0.380 0.004
#> SRR1947512 1 0.0693 0.9358 0.980 0.000 0.012 0.008 0.000
#> SRR1947511 2 0.0404 0.8892 0.000 0.988 0.000 0.012 0.000
#> SRR1947510 5 0.4165 0.6831 0.000 0.008 0.320 0.000 0.672
#> SRR1947572 1 0.4381 0.6846 0.764 0.004 0.012 0.188 0.032
#> SRR1947611 5 0.4260 0.6810 0.000 0.008 0.308 0.004 0.680
#> SRR1947509 5 0.4138 0.6185 0.000 0.000 0.384 0.000 0.616
#> SRR1947644 5 0.4011 0.6439 0.012 0.000 0.136 0.048 0.804
#> SRR1947643 2 0.3445 0.8022 0.000 0.824 0.000 0.140 0.036
#> SRR1947642 3 0.2234 0.7422 0.000 0.004 0.916 0.036 0.044
#> SRR1947640 4 0.6211 0.6113 0.012 0.120 0.316 0.552 0.000
#> SRR1947641 3 0.3961 0.6398 0.000 0.004 0.780 0.032 0.184
#> SRR1947639 4 0.7757 0.6581 0.120 0.128 0.172 0.552 0.028
#> SRR1947638 4 0.7159 0.4741 0.328 0.016 0.224 0.428 0.004
#> SRR1947637 5 0.4483 0.6726 0.000 0.012 0.308 0.008 0.672
#> SRR1947636 3 0.2054 0.7411 0.004 0.000 0.916 0.008 0.072
#> SRR1947635 4 0.6053 0.6390 0.000 0.228 0.196 0.576 0.000
#> SRR1947634 2 0.0404 0.8892 0.000 0.988 0.000 0.012 0.000
#> SRR1947633 3 0.4262 -0.2989 0.000 0.000 0.560 0.000 0.440
#> SRR1947632 4 0.6388 0.6193 0.000 0.252 0.188 0.552 0.008
#> SRR1947631 3 0.2504 0.7393 0.000 0.004 0.900 0.032 0.064
#> SRR1947629 5 0.6718 0.5502 0.012 0.000 0.332 0.180 0.476
#> SRR1947630 2 0.2069 0.8415 0.000 0.912 0.000 0.012 0.076
#> SRR1947627 3 0.1628 0.7371 0.000 0.000 0.936 0.008 0.056
#> SRR1947628 4 0.5566 0.3222 0.000 0.140 0.004 0.656 0.200
#> SRR1947626 2 0.4630 0.7350 0.000 0.736 0.000 0.176 0.088
#> SRR1947625 3 0.3966 0.6488 0.000 0.004 0.784 0.036 0.176
#> SRR1947624 2 0.2522 0.8166 0.000 0.880 0.000 0.012 0.108
#> SRR1947623 1 0.0566 0.9378 0.984 0.000 0.012 0.000 0.004
#> SRR1947622 4 0.5700 0.0297 0.000 0.456 0.004 0.472 0.068
#> SRR1947621 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947620 4 0.6866 0.4311 0.252 0.000 0.364 0.380 0.004
#> SRR1947619 3 0.2352 0.7317 0.004 0.000 0.896 0.008 0.092
#> SRR1947617 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947618 4 0.7155 0.4328 0.236 0.012 0.372 0.376 0.004
#> SRR1947616 2 0.6530 0.3489 0.000 0.440 0.000 0.360 0.200
#> SRR1947615 3 0.2248 0.7105 0.000 0.000 0.900 0.088 0.012
#> SRR1947614 5 0.4165 0.6831 0.000 0.008 0.320 0.000 0.672
#> SRR1947613 1 0.0727 0.9378 0.980 0.000 0.012 0.004 0.004
#> SRR1947610 4 0.6369 0.2489 0.020 0.172 0.004 0.608 0.196
#> SRR1947612 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947609 4 0.6426 0.5530 0.104 0.016 0.364 0.512 0.004
#> SRR1947608 3 0.3927 0.6630 0.000 0.004 0.792 0.040 0.164
#> SRR1947606 3 0.1173 0.7418 0.004 0.000 0.964 0.012 0.020
#> SRR1947607 1 0.0727 0.9378 0.980 0.000 0.012 0.004 0.004
#> SRR1947604 4 0.6703 0.6173 0.088 0.028 0.284 0.576 0.024
#> SRR1947605 1 0.1710 0.9109 0.940 0.000 0.040 0.016 0.004
#> SRR1947603 2 0.3352 0.7749 0.000 0.852 0.036 0.100 0.012
#> SRR1947602 3 0.3921 0.5951 0.128 0.000 0.800 0.072 0.000
#> SRR1947600 5 0.6693 0.5539 0.012 0.000 0.332 0.176 0.480
#> SRR1947601 2 0.0579 0.8903 0.000 0.984 0.000 0.008 0.008
#> SRR1947598 4 0.5047 0.4155 0.000 0.052 0.028 0.720 0.200
#> SRR1947599 4 0.6444 0.5916 0.096 0.020 0.328 0.548 0.008
#> SRR1947597 4 0.5746 0.2991 0.000 0.452 0.072 0.472 0.004
#> SRR1947596 4 0.7221 0.5446 0.248 0.004 0.224 0.492 0.032
#> SRR1947595 4 0.6289 0.5696 0.016 0.104 0.368 0.512 0.000
#> SRR1947594 1 0.0671 0.9382 0.980 0.000 0.016 0.004 0.000
#> SRR1947592 3 0.2848 0.6689 0.000 0.000 0.840 0.004 0.156
#> SRR1947591 2 0.0693 0.8898 0.000 0.980 0.000 0.012 0.008
#> SRR1947590 4 0.7242 0.5551 0.236 0.004 0.240 0.488 0.032
#> SRR1947588 1 0.0510 0.9383 0.984 0.000 0.016 0.000 0.000
#> SRR1947587 3 0.1788 0.7442 0.004 0.000 0.932 0.008 0.056
#> SRR1947586 2 0.4681 0.7237 0.000 0.728 0.000 0.188 0.084
#> SRR1947585 5 0.6693 0.5539 0.012 0.000 0.332 0.176 0.480
#> SRR1947584 1 0.0510 0.9383 0.984 0.000 0.016 0.000 0.000
#> SRR1947583 4 0.6242 0.6179 0.012 0.128 0.304 0.556 0.000
#> SRR1947582 4 0.7155 0.4328 0.236 0.012 0.372 0.376 0.004
#> SRR1947580 2 0.6317 0.4374 0.000 0.496 0.000 0.332 0.172
#> SRR1947581 1 0.0510 0.9383 0.984 0.000 0.016 0.000 0.000
#> SRR1947576 5 0.4260 0.6810 0.000 0.008 0.308 0.004 0.680
#> SRR1947575 3 0.4049 0.6575 0.000 0.008 0.788 0.040 0.164
#> SRR1947579 5 0.4165 0.6831 0.000 0.008 0.320 0.000 0.672
#> SRR1947578 4 0.6272 0.1474 0.000 0.236 0.004 0.560 0.200
#> SRR1947573 3 0.3455 0.5770 0.000 0.000 0.784 0.008 0.208
#> SRR1947574 4 0.7031 0.6324 0.188 0.036 0.216 0.552 0.008
#> SRR1947571 4 0.7206 0.6454 0.128 0.048 0.208 0.584 0.032
#> SRR1947577 4 0.7155 0.4384 0.236 0.012 0.368 0.380 0.004
#> SRR1947570 3 0.2367 0.6914 0.020 0.000 0.904 0.072 0.004
#> SRR1947569 5 0.6718 0.5502 0.012 0.000 0.332 0.180 0.476
#> SRR1947566 2 0.3477 0.7990 0.000 0.824 0.000 0.136 0.040
#> SRR1947567 4 0.6054 0.5906 0.000 0.280 0.160 0.560 0.000
#> SRR1947568 1 0.5881 0.5996 0.692 0.120 0.008 0.144 0.036
#> SRR1947564 2 0.1281 0.8786 0.000 0.956 0.000 0.032 0.012
#> SRR1947563 3 0.3927 0.6630 0.000 0.004 0.792 0.040 0.164
#> SRR1947562 4 0.6751 0.6515 0.012 0.180 0.212 0.576 0.020
#> SRR1947565 3 0.2116 0.7399 0.004 0.000 0.912 0.008 0.076
#> SRR1947559 4 0.6195 0.4989 0.000 0.360 0.128 0.508 0.004
#> SRR1947560 5 0.4260 0.6810 0.000 0.008 0.308 0.004 0.680
#> SRR1947561 2 0.0451 0.8900 0.000 0.988 0.000 0.008 0.004
#> SRR1947557 1 0.0510 0.9383 0.984 0.000 0.016 0.000 0.000
#> SRR1947558 3 0.3851 0.6652 0.000 0.004 0.796 0.036 0.164
#> SRR1947556 1 0.1518 0.9219 0.952 0.000 0.016 0.012 0.020
#> SRR1947553 4 0.6369 0.2489 0.020 0.172 0.004 0.608 0.196
#> SRR1947554 1 0.0727 0.9378 0.980 0.000 0.012 0.004 0.004
#> SRR1947555 2 0.2899 0.7950 0.000 0.880 0.036 0.076 0.008
#> SRR1947550 4 0.6282 0.6281 0.012 0.136 0.296 0.556 0.000
#> SRR1947552 4 0.6444 0.5916 0.096 0.020 0.328 0.548 0.008
#> SRR1947549 3 0.3053 0.6606 0.000 0.000 0.828 0.008 0.164
#> SRR1947551 5 0.4011 0.6439 0.012 0.000 0.136 0.048 0.804
#> SRR1947548 4 0.6942 0.6289 0.112 0.028 0.248 0.580 0.032
#> SRR1947506 3 0.1768 0.7052 0.004 0.000 0.924 0.072 0.000
#> SRR1947507 1 0.0671 0.9382 0.980 0.000 0.016 0.004 0.000
#> SRR1947504 1 0.1419 0.9229 0.956 0.000 0.016 0.012 0.016
#> SRR1947503 4 0.6969 0.6161 0.200 0.012 0.200 0.560 0.028
#> SRR1947502 2 0.0451 0.8900 0.000 0.988 0.000 0.008 0.004
#> SRR1947501 4 0.6407 0.5788 0.000 0.296 0.164 0.532 0.008
#> SRR1947499 3 0.3921 0.5951 0.128 0.000 0.800 0.072 0.000
#> SRR1947498 5 0.6693 0.5539 0.012 0.000 0.332 0.176 0.480
#> SRR1947508 3 0.2037 0.7262 0.000 0.004 0.920 0.064 0.012
#> SRR1947505 4 0.5836 0.3686 0.000 0.104 0.032 0.664 0.200
#> SRR1947497 2 0.0404 0.8892 0.000 0.988 0.000 0.012 0.000
#> SRR1947496 1 0.0510 0.9383 0.984 0.000 0.016 0.000 0.000
#> SRR1947495 2 0.0404 0.8892 0.000 0.988 0.000 0.012 0.000
#> SRR1947494 4 0.6945 0.6224 0.112 0.024 0.264 0.568 0.032
#> SRR1947493 3 0.4010 0.5861 0.136 0.000 0.792 0.072 0.000
#> SRR1947492 1 0.0727 0.9378 0.980 0.000 0.012 0.004 0.004
#> SRR1947500 4 0.6124 0.6359 0.000 0.236 0.200 0.564 0.000
#> SRR1947491 4 0.6141 0.6415 0.004 0.172 0.248 0.576 0.000
#> SRR1947490 1 0.0854 0.9362 0.976 0.000 0.012 0.008 0.004
#> SRR1947489 3 0.2193 0.7005 0.000 0.000 0.900 0.092 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.3223 0.6762 0.008 0.000 0.824 0.144 0.020 0.004
#> SRR1947546 4 0.5459 0.5830 0.000 0.120 0.056 0.692 0.012 0.120
#> SRR1947545 1 0.2848 0.8174 0.872 0.000 0.060 0.056 0.008 0.004
#> SRR1947544 1 0.0653 0.9098 0.980 0.000 0.012 0.004 0.004 0.000
#> SRR1947542 4 0.4602 0.6191 0.000 0.056 0.048 0.756 0.008 0.132
#> SRR1947541 3 0.3283 0.7017 0.004 0.000 0.832 0.112 0.048 0.004
#> SRR1947540 6 0.4895 0.8216 0.000 0.112 0.004 0.164 0.016 0.704
#> SRR1947539 3 0.3979 0.3588 0.000 0.000 0.628 0.000 0.360 0.012
#> SRR1947538 6 0.4591 0.7321 0.008 0.020 0.012 0.252 0.012 0.696
#> SRR1947537 3 0.4195 0.7086 0.004 0.000 0.764 0.088 0.136 0.008
#> SRR1947536 5 0.6511 0.5127 0.000 0.000 0.252 0.024 0.408 0.316
#> SRR1947535 3 0.5871 0.6014 0.000 0.008 0.636 0.112 0.184 0.060
#> SRR1947534 1 0.6473 0.3092 0.532 0.324 0.012 0.064 0.032 0.036
#> SRR1947533 2 0.1251 0.8150 0.000 0.956 0.000 0.008 0.012 0.024
#> SRR1947532 4 0.4194 0.6878 0.036 0.000 0.052 0.792 0.012 0.108
#> SRR1947531 6 0.4959 0.8180 0.000 0.112 0.004 0.172 0.016 0.696
#> SRR1947530 3 0.4542 0.5971 0.088 0.000 0.732 0.164 0.012 0.004
#> SRR1947529 2 0.6912 0.0821 0.000 0.448 0.040 0.292 0.016 0.204
#> SRR1947528 3 0.3078 0.7135 0.004 0.000 0.852 0.080 0.060 0.004
#> SRR1947527 2 0.2208 0.8115 0.000 0.916 0.012 0.012 0.024 0.036
#> SRR1947526 2 0.1180 0.8169 0.000 0.960 0.000 0.016 0.012 0.012
#> SRR1947525 4 0.4825 0.6416 0.036 0.040 0.016 0.760 0.020 0.128
#> SRR1947524 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947523 4 0.4672 0.6773 0.000 0.040 0.160 0.740 0.008 0.052
#> SRR1947521 5 0.2730 0.6551 0.000 0.000 0.192 0.000 0.808 0.000
#> SRR1947520 2 0.1448 0.8142 0.000 0.948 0.000 0.012 0.016 0.024
#> SRR1947519 3 0.4258 0.6946 0.000 0.008 0.780 0.120 0.064 0.028
#> SRR1947518 6 0.4591 0.7321 0.008 0.020 0.012 0.252 0.012 0.696
#> SRR1947517 5 0.2730 0.6551 0.000 0.000 0.192 0.000 0.808 0.000
#> SRR1947516 2 0.2108 0.8097 0.000 0.920 0.012 0.016 0.012 0.040
#> SRR1947515 4 0.4111 0.6873 0.028 0.000 0.056 0.796 0.012 0.108
#> SRR1947514 2 0.2108 0.8098 0.000 0.920 0.012 0.016 0.012 0.040
#> SRR1947513 4 0.5298 0.6072 0.112 0.000 0.276 0.604 0.004 0.004
#> SRR1947512 1 0.0582 0.9139 0.984 0.000 0.004 0.004 0.004 0.004
#> SRR1947511 2 0.1364 0.8152 0.000 0.952 0.000 0.012 0.016 0.020
#> SRR1947510 5 0.2730 0.6551 0.000 0.000 0.192 0.000 0.808 0.000
#> SRR1947572 1 0.4884 0.5409 0.660 0.000 0.000 0.248 0.012 0.080
#> SRR1947611 5 0.2933 0.6517 0.000 0.004 0.200 0.000 0.796 0.000
#> SRR1947509 5 0.3221 0.5836 0.000 0.000 0.264 0.000 0.736 0.000
#> SRR1947644 5 0.4114 0.6169 0.000 0.000 0.052 0.016 0.756 0.176
#> SRR1947643 2 0.3915 0.5374 0.000 0.696 0.000 0.008 0.012 0.284
#> SRR1947642 3 0.3902 0.7007 0.000 0.008 0.800 0.120 0.056 0.016
#> SRR1947640 4 0.4684 0.6940 0.012 0.036 0.144 0.756 0.008 0.044
#> SRR1947641 3 0.5556 0.6160 0.000 0.008 0.660 0.112 0.180 0.040
#> SRR1947639 4 0.4850 0.6481 0.044 0.036 0.020 0.760 0.016 0.124
#> SRR1947638 4 0.5482 0.6441 0.164 0.000 0.136 0.664 0.012 0.024
#> SRR1947637 5 0.3844 0.5949 0.000 0.004 0.224 0.004 0.744 0.024
#> SRR1947636 3 0.4017 0.7138 0.004 0.000 0.780 0.080 0.128 0.008
#> SRR1947635 4 0.4906 0.6511 0.000 0.056 0.096 0.744 0.012 0.092
#> SRR1947634 2 0.1364 0.8152 0.000 0.952 0.000 0.012 0.016 0.020
#> SRR1947633 3 0.4263 -0.0527 0.000 0.000 0.504 0.000 0.480 0.016
#> SRR1947632 4 0.5258 0.6042 0.000 0.092 0.060 0.712 0.012 0.124
#> SRR1947631 3 0.4385 0.6952 0.000 0.008 0.772 0.120 0.068 0.032
#> SRR1947629 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947630 2 0.2239 0.7893 0.000 0.900 0.000 0.008 0.072 0.020
#> SRR1947627 3 0.2979 0.7158 0.004 0.000 0.852 0.056 0.088 0.000
#> SRR1947628 6 0.4551 0.8149 0.000 0.060 0.004 0.200 0.016 0.720
#> SRR1947626 2 0.4862 0.1688 0.000 0.520 0.020 0.008 0.012 0.440
#> SRR1947625 3 0.5585 0.6138 0.000 0.008 0.656 0.112 0.184 0.040
#> SRR1947624 2 0.2402 0.7821 0.000 0.888 0.000 0.008 0.084 0.020
#> SRR1947623 1 0.0405 0.9153 0.988 0.000 0.000 0.004 0.008 0.000
#> SRR1947622 4 0.6469 -0.1819 0.000 0.148 0.032 0.448 0.008 0.364
#> SRR1947621 2 0.2196 0.8089 0.000 0.916 0.012 0.020 0.012 0.040
#> SRR1947620 4 0.5474 0.5933 0.120 0.000 0.276 0.592 0.004 0.008
#> SRR1947619 3 0.4717 0.6957 0.004 0.000 0.724 0.108 0.148 0.016
#> SRR1947617 2 0.2427 0.8071 0.000 0.904 0.012 0.028 0.012 0.044
#> SRR1947618 4 0.5201 0.6029 0.120 0.000 0.268 0.608 0.000 0.004
#> SRR1947616 6 0.4874 0.6801 0.000 0.212 0.004 0.072 0.020 0.692
#> SRR1947615 3 0.2755 0.6994 0.004 0.000 0.844 0.140 0.000 0.012
#> SRR1947614 5 0.2730 0.6551 0.000 0.000 0.192 0.000 0.808 0.000
#> SRR1947613 1 0.0912 0.9133 0.972 0.000 0.004 0.004 0.012 0.008
#> SRR1947610 6 0.4571 0.7813 0.000 0.068 0.012 0.200 0.004 0.716
#> SRR1947612 2 0.2279 0.8079 0.000 0.912 0.012 0.024 0.012 0.040
#> SRR1947609 4 0.4639 0.6665 0.048 0.000 0.240 0.692 0.004 0.016
#> SRR1947608 3 0.6054 0.5814 0.000 0.008 0.616 0.132 0.184 0.060
#> SRR1947606 3 0.3136 0.7143 0.004 0.000 0.848 0.080 0.064 0.004
#> SRR1947607 1 0.0912 0.9133 0.972 0.000 0.004 0.004 0.012 0.008
#> SRR1947604 4 0.3094 0.7100 0.032 0.000 0.060 0.860 0.000 0.048
#> SRR1947605 1 0.2052 0.8573 0.912 0.000 0.056 0.028 0.004 0.000
#> SRR1947603 2 0.5900 0.3618 0.000 0.572 0.052 0.304 0.012 0.060
#> SRR1947602 3 0.4495 0.6013 0.084 0.000 0.736 0.164 0.012 0.004
#> SRR1947600 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947601 2 0.0914 0.8171 0.000 0.968 0.000 0.016 0.000 0.016
#> SRR1947598 6 0.4214 0.7914 0.000 0.024 0.004 0.236 0.016 0.720
#> SRR1947599 4 0.4022 0.6920 0.040 0.000 0.188 0.756 0.000 0.016
#> SRR1947597 4 0.5301 0.4831 0.000 0.244 0.036 0.648 0.004 0.068
#> SRR1947596 4 0.6242 0.5169 0.208 0.000 0.080 0.600 0.012 0.100
#> SRR1947595 4 0.5026 0.6706 0.008 0.028 0.228 0.688 0.008 0.040
#> SRR1947594 1 0.0436 0.9153 0.988 0.000 0.004 0.000 0.004 0.004
#> SRR1947592 3 0.4548 0.6616 0.004 0.000 0.724 0.064 0.192 0.016
#> SRR1947591 2 0.2108 0.8097 0.000 0.920 0.012 0.016 0.012 0.040
#> SRR1947590 4 0.6282 0.5258 0.200 0.000 0.088 0.600 0.012 0.100
#> SRR1947588 1 0.0146 0.9153 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947587 3 0.3719 0.7199 0.004 0.000 0.808 0.088 0.092 0.008
#> SRR1947586 2 0.4958 0.1266 0.000 0.492 0.020 0.008 0.016 0.464
#> SRR1947585 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947584 1 0.0146 0.9153 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947583 4 0.4647 0.6942 0.012 0.036 0.140 0.760 0.008 0.044
#> SRR1947582 4 0.5254 0.5894 0.120 0.000 0.280 0.596 0.000 0.004
#> SRR1947580 6 0.4512 0.4975 0.000 0.304 0.008 0.020 0.012 0.656
#> SRR1947581 1 0.0146 0.9153 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947576 5 0.2871 0.6516 0.000 0.004 0.192 0.000 0.804 0.000
#> SRR1947575 3 0.6131 0.5713 0.000 0.008 0.608 0.132 0.188 0.064
#> SRR1947579 5 0.2730 0.6551 0.000 0.000 0.192 0.000 0.808 0.000
#> SRR1947578 6 0.4895 0.8216 0.000 0.112 0.004 0.164 0.016 0.704
#> SRR1947573 3 0.4896 0.5700 0.000 0.000 0.660 0.064 0.256 0.020
#> SRR1947574 4 0.5387 0.6954 0.072 0.016 0.100 0.732 0.024 0.056
#> SRR1947571 4 0.4321 0.6755 0.036 0.004 0.040 0.788 0.016 0.116
#> SRR1947577 4 0.5164 0.6127 0.120 0.000 0.260 0.616 0.000 0.004
#> SRR1947570 3 0.3313 0.6686 0.016 0.000 0.816 0.152 0.012 0.004
#> SRR1947569 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947566 2 0.3555 0.5454 0.000 0.712 0.000 0.008 0.000 0.280
#> SRR1947567 4 0.4673 0.6204 0.000 0.072 0.048 0.760 0.012 0.108
#> SRR1947568 1 0.6524 0.5050 0.604 0.064 0.012 0.192 0.020 0.108
#> SRR1947564 2 0.4125 0.7165 0.000 0.792 0.012 0.108 0.020 0.068
#> SRR1947563 3 0.6131 0.5713 0.000 0.008 0.608 0.132 0.188 0.064
#> SRR1947562 4 0.3649 0.6747 0.000 0.052 0.036 0.828 0.004 0.080
#> SRR1947565 3 0.4096 0.7107 0.004 0.000 0.772 0.080 0.136 0.008
#> SRR1947559 4 0.4990 0.5425 0.000 0.204 0.032 0.692 0.004 0.068
#> SRR1947560 5 0.2902 0.6538 0.000 0.004 0.196 0.000 0.800 0.000
#> SRR1947561 2 0.0935 0.8151 0.000 0.964 0.000 0.032 0.000 0.004
#> SRR1947557 1 0.0146 0.9153 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947558 3 0.5497 0.6237 0.000 0.008 0.668 0.112 0.172 0.040
#> SRR1947556 1 0.1065 0.8993 0.964 0.000 0.000 0.020 0.008 0.008
#> SRR1947553 6 0.4571 0.7813 0.000 0.068 0.012 0.200 0.004 0.716
#> SRR1947554 1 0.0912 0.9133 0.972 0.000 0.004 0.004 0.012 0.008
#> SRR1947555 2 0.5767 0.4813 0.000 0.636 0.056 0.228 0.020 0.060
#> SRR1947550 4 0.3683 0.7099 0.012 0.028 0.064 0.840 0.008 0.048
#> SRR1947552 4 0.3822 0.6979 0.032 0.000 0.180 0.772 0.000 0.016
#> SRR1947549 3 0.5056 0.6258 0.004 0.000 0.672 0.092 0.216 0.016
#> SRR1947551 5 0.4114 0.6169 0.000 0.000 0.052 0.016 0.756 0.176
#> SRR1947548 4 0.4191 0.6865 0.028 0.004 0.052 0.796 0.012 0.108
#> SRR1947506 3 0.3343 0.6691 0.008 0.000 0.816 0.148 0.024 0.004
#> SRR1947507 1 0.0436 0.9153 0.988 0.000 0.004 0.000 0.004 0.004
#> SRR1947504 1 0.0976 0.9022 0.968 0.000 0.000 0.016 0.008 0.008
#> SRR1947503 4 0.4420 0.6948 0.072 0.000 0.084 0.784 0.016 0.044
#> SRR1947502 2 0.1340 0.8122 0.000 0.948 0.000 0.040 0.004 0.008
#> SRR1947501 4 0.5338 0.5862 0.000 0.108 0.056 0.704 0.012 0.120
#> SRR1947499 3 0.4495 0.6013 0.084 0.000 0.736 0.164 0.012 0.004
#> SRR1947498 5 0.6385 0.5564 0.000 0.000 0.208 0.024 0.436 0.332
#> SRR1947508 3 0.3293 0.6871 0.000 0.004 0.828 0.132 0.020 0.016
#> SRR1947505 6 0.4716 0.7775 0.000 0.036 0.016 0.236 0.016 0.696
#> SRR1947497 2 0.1452 0.8158 0.000 0.948 0.000 0.020 0.012 0.020
#> SRR1947496 1 0.0146 0.9153 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947495 2 0.1452 0.8158 0.000 0.948 0.000 0.020 0.012 0.020
#> SRR1947494 4 0.4254 0.6862 0.036 0.000 0.056 0.792 0.016 0.100
#> SRR1947493 3 0.4432 0.5990 0.084 0.000 0.736 0.168 0.008 0.004
#> SRR1947492 1 0.0912 0.9133 0.972 0.000 0.004 0.004 0.012 0.008
#> SRR1947500 4 0.4490 0.6764 0.004 0.068 0.080 0.784 0.012 0.052
#> SRR1947491 4 0.5053 0.6736 0.008 0.044 0.144 0.732 0.012 0.060
#> SRR1947490 1 0.1396 0.9033 0.952 0.000 0.004 0.024 0.012 0.008
#> SRR1947489 3 0.3284 0.6797 0.004 0.000 0.804 0.172 0.004 0.016
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 15148 rows and 152 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 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 0.502 0.730 0.834 0.4766 0.539 0.539
#> 3 3 0.991 0.957 0.983 0.4067 0.782 0.598
#> 4 4 0.770 0.748 0.859 0.1036 0.895 0.700
#> 5 5 0.716 0.649 0.821 0.0671 0.923 0.720
#> 6 6 0.719 0.542 0.767 0.0493 0.909 0.606
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
#> SRR1947547 2 0.9491 0.640 0.368 0.632
#> SRR1947546 1 0.9491 0.708 0.632 0.368
#> SRR1947545 1 0.1184 0.733 0.984 0.016
#> SRR1947544 1 0.1184 0.733 0.984 0.016
#> SRR1947542 1 0.9491 0.708 0.632 0.368
#> SRR1947541 2 0.9491 0.640 0.368 0.632
#> SRR1947540 1 0.9491 0.708 0.632 0.368
#> SRR1947539 2 0.1184 0.795 0.016 0.984
#> SRR1947538 1 0.0000 0.740 1.000 0.000
#> SRR1947537 2 0.9491 0.640 0.368 0.632
#> SRR1947536 2 0.0000 0.801 0.000 1.000
#> SRR1947535 2 0.0000 0.801 0.000 1.000
#> SRR1947534 1 0.0000 0.740 1.000 0.000
#> SRR1947533 1 0.9491 0.708 0.632 0.368
#> SRR1947532 1 0.0000 0.740 1.000 0.000
#> SRR1947531 1 0.9491 0.708 0.632 0.368
#> SRR1947530 2 0.9491 0.640 0.368 0.632
#> SRR1947529 1 0.9491 0.708 0.632 0.368
#> SRR1947528 2 0.9491 0.640 0.368 0.632
#> SRR1947527 1 0.9491 0.708 0.632 0.368
#> SRR1947526 1 0.9491 0.708 0.632 0.368
#> SRR1947525 1 0.0000 0.740 1.000 0.000
#> SRR1947524 2 0.0000 0.801 0.000 1.000
#> SRR1947523 1 0.9129 0.709 0.672 0.328
#> SRR1947521 2 0.0000 0.801 0.000 1.000
#> SRR1947520 1 0.9491 0.708 0.632 0.368
#> SRR1947519 2 0.0000 0.801 0.000 1.000
#> SRR1947518 1 0.0000 0.740 1.000 0.000
#> SRR1947517 2 0.0000 0.801 0.000 1.000
#> SRR1947516 1 0.9491 0.708 0.632 0.368
#> SRR1947515 1 0.0000 0.740 1.000 0.000
#> SRR1947514 1 0.9491 0.708 0.632 0.368
#> SRR1947513 1 0.1184 0.733 0.984 0.016
#> SRR1947512 1 0.0672 0.738 0.992 0.008
#> SRR1947511 1 0.9491 0.708 0.632 0.368
#> SRR1947510 2 0.0000 0.801 0.000 1.000
#> SRR1947572 1 0.0000 0.740 1.000 0.000
#> SRR1947611 2 0.0000 0.801 0.000 1.000
#> SRR1947509 2 0.0000 0.801 0.000 1.000
#> SRR1947644 2 0.0000 0.801 0.000 1.000
#> SRR1947643 1 0.9491 0.708 0.632 0.368
#> SRR1947642 2 0.0000 0.801 0.000 1.000
#> SRR1947640 1 0.0000 0.740 1.000 0.000
#> SRR1947641 2 0.0000 0.801 0.000 1.000
#> SRR1947639 1 0.0000 0.740 1.000 0.000
#> SRR1947638 1 0.0000 0.740 1.000 0.000
#> SRR1947637 2 0.0000 0.801 0.000 1.000
#> SRR1947636 2 0.9491 0.640 0.368 0.632
#> SRR1947635 1 0.9491 0.708 0.632 0.368
#> SRR1947634 1 0.9491 0.708 0.632 0.368
#> SRR1947633 2 0.0000 0.801 0.000 1.000
#> SRR1947632 1 0.9491 0.708 0.632 0.368
#> SRR1947631 2 0.0000 0.801 0.000 1.000
#> SRR1947629 2 0.0000 0.801 0.000 1.000
#> SRR1947630 1 0.9491 0.708 0.632 0.368
#> SRR1947627 2 0.9491 0.640 0.368 0.632
#> SRR1947628 1 0.9491 0.708 0.632 0.368
#> SRR1947626 1 0.9491 0.708 0.632 0.368
#> SRR1947625 2 0.0000 0.801 0.000 1.000
#> SRR1947624 1 0.9552 0.698 0.624 0.376
#> SRR1947623 1 0.0672 0.738 0.992 0.008
#> SRR1947622 1 0.9491 0.708 0.632 0.368
#> SRR1947621 1 0.9491 0.708 0.632 0.368
#> SRR1947620 1 0.1184 0.733 0.984 0.016
#> SRR1947619 2 0.9491 0.640 0.368 0.632
#> SRR1947617 1 0.9491 0.708 0.632 0.368
#> SRR1947618 1 0.1184 0.733 0.984 0.016
#> SRR1947616 1 0.9491 0.708 0.632 0.368
#> SRR1947615 2 0.9491 0.640 0.368 0.632
#> SRR1947614 2 0.0000 0.801 0.000 1.000
#> SRR1947613 1 0.0938 0.736 0.988 0.012
#> SRR1947610 1 0.9491 0.708 0.632 0.368
#> SRR1947612 1 0.9491 0.708 0.632 0.368
#> SRR1947609 1 0.1184 0.733 0.984 0.016
#> SRR1947608 2 0.0000 0.801 0.000 1.000
#> SRR1947606 2 0.9491 0.640 0.368 0.632
#> SRR1947607 1 0.0000 0.740 1.000 0.000
#> SRR1947604 1 0.0000 0.740 1.000 0.000
#> SRR1947605 1 0.1184 0.733 0.984 0.016
#> SRR1947603 1 0.9491 0.708 0.632 0.368
#> SRR1947602 2 0.9491 0.640 0.368 0.632
#> SRR1947600 2 0.0000 0.801 0.000 1.000
#> SRR1947601 1 0.9491 0.708 0.632 0.368
#> SRR1947598 1 0.9491 0.708 0.632 0.368
#> SRR1947599 1 0.0376 0.739 0.996 0.004
#> SRR1947597 1 0.9491 0.708 0.632 0.368
#> SRR1947596 1 0.0672 0.738 0.992 0.008
#> SRR1947595 1 0.0938 0.736 0.988 0.012
#> SRR1947594 1 0.0938 0.736 0.988 0.012
#> SRR1947592 2 0.9491 0.640 0.368 0.632
#> SRR1947591 1 0.9491 0.708 0.632 0.368
#> SRR1947590 1 0.0938 0.736 0.988 0.012
#> SRR1947588 1 0.0938 0.736 0.988 0.012
#> SRR1947587 2 0.9491 0.640 0.368 0.632
#> SRR1947586 1 0.9491 0.708 0.632 0.368
#> SRR1947585 2 0.0000 0.801 0.000 1.000
#> SRR1947584 1 0.0938 0.736 0.988 0.012
#> SRR1947583 1 0.0000 0.740 1.000 0.000
#> SRR1947582 1 0.1184 0.733 0.984 0.016
#> SRR1947580 1 0.9491 0.708 0.632 0.368
#> SRR1947581 1 0.0938 0.736 0.988 0.012
#> SRR1947576 2 0.0000 0.801 0.000 1.000
#> SRR1947575 2 0.0000 0.801 0.000 1.000
#> SRR1947579 2 0.0000 0.801 0.000 1.000
#> SRR1947578 1 0.9491 0.708 0.632 0.368
#> SRR1947573 2 0.0000 0.801 0.000 1.000
#> SRR1947574 1 0.0000 0.740 1.000 0.000
#> SRR1947571 1 0.0000 0.740 1.000 0.000
#> SRR1947577 1 0.1184 0.733 0.984 0.016
#> SRR1947570 2 0.9491 0.640 0.368 0.632
#> SRR1947569 2 0.0000 0.801 0.000 1.000
#> SRR1947566 1 0.9491 0.708 0.632 0.368
#> SRR1947567 1 0.9491 0.708 0.632 0.368
#> SRR1947568 1 0.0000 0.740 1.000 0.000
#> SRR1947564 1 0.9491 0.708 0.632 0.368
#> SRR1947563 2 0.0000 0.801 0.000 1.000
#> SRR1947562 1 0.0000 0.740 1.000 0.000
#> SRR1947565 2 0.9491 0.640 0.368 0.632
#> SRR1947559 1 0.9460 0.708 0.636 0.364
#> SRR1947560 2 0.0000 0.801 0.000 1.000
#> SRR1947561 1 0.9491 0.708 0.632 0.368
#> SRR1947557 1 0.1184 0.733 0.984 0.016
#> SRR1947558 2 0.0000 0.801 0.000 1.000
#> SRR1947556 1 0.0938 0.736 0.988 0.012
#> SRR1947553 1 0.9491 0.708 0.632 0.368
#> SRR1947554 1 0.0000 0.740 1.000 0.000
#> SRR1947555 2 0.1184 0.783 0.016 0.984
#> SRR1947550 1 0.0000 0.740 1.000 0.000
#> SRR1947552 1 0.0376 0.739 0.996 0.004
#> SRR1947549 2 0.8813 0.668 0.300 0.700
#> SRR1947551 2 0.0000 0.801 0.000 1.000
#> SRR1947548 1 0.0000 0.740 1.000 0.000
#> SRR1947506 2 0.9491 0.640 0.368 0.632
#> SRR1947507 1 0.0938 0.736 0.988 0.012
#> SRR1947504 1 0.0672 0.738 0.992 0.008
#> SRR1947503 1 0.0000 0.740 1.000 0.000
#> SRR1947502 1 0.9491 0.708 0.632 0.368
#> SRR1947501 1 0.9491 0.708 0.632 0.368
#> SRR1947499 2 0.9491 0.640 0.368 0.632
#> SRR1947498 2 0.0000 0.801 0.000 1.000
#> SRR1947508 2 0.0000 0.801 0.000 1.000
#> SRR1947505 1 0.9491 0.708 0.632 0.368
#> SRR1947497 1 0.9491 0.708 0.632 0.368
#> SRR1947496 1 0.0938 0.736 0.988 0.012
#> SRR1947495 1 0.9491 0.708 0.632 0.368
#> SRR1947494 1 0.0000 0.740 1.000 0.000
#> SRR1947493 2 0.9491 0.640 0.368 0.632
#> SRR1947492 1 0.0938 0.736 0.988 0.012
#> SRR1947500 1 0.9460 0.708 0.636 0.364
#> SRR1947491 1 0.9491 0.708 0.632 0.368
#> SRR1947490 1 0.0938 0.736 0.988 0.012
#> SRR1947489 2 0.9491 0.640 0.368 0.632
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947546 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947540 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947539 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947538 1 0.0237 0.9699 0.996 0.004 0.000
#> SRR1947537 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947536 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947535 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947534 1 0.3482 0.8423 0.872 0.128 0.000
#> SRR1947533 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947532 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947531 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947530 3 0.0892 0.9734 0.020 0.000 0.980
#> SRR1947529 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947528 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947527 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947525 1 0.5016 0.6866 0.760 0.240 0.000
#> SRR1947524 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947523 2 0.0237 0.9784 0.004 0.996 0.000
#> SRR1947521 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947518 1 0.0237 0.9699 0.996 0.004 0.000
#> SRR1947517 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947515 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947514 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947572 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947611 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947509 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947644 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947640 1 0.3686 0.8309 0.860 0.140 0.000
#> SRR1947641 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947639 1 0.1031 0.9537 0.976 0.024 0.000
#> SRR1947638 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947637 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947632 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947627 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947628 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947624 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947623 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947622 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947619 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947616 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947615 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947614 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947609 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947604 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947605 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947602 3 0.0892 0.9734 0.020 0.000 0.980
#> SRR1947600 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947598 2 0.0237 0.9785 0.004 0.996 0.000
#> SRR1947599 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947597 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947596 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947595 1 0.4654 0.7391 0.792 0.208 0.000
#> SRR1947594 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947590 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947588 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947583 2 0.6299 0.0483 0.476 0.524 0.000
#> SRR1947582 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947578 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947573 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947574 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947571 1 0.0237 0.9699 0.996 0.004 0.000
#> SRR1947577 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947570 3 0.4702 0.7339 0.212 0.000 0.788
#> SRR1947569 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947567 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947568 1 0.0892 0.9570 0.980 0.020 0.000
#> SRR1947564 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947562 2 0.5926 0.4207 0.356 0.644 0.000
#> SRR1947565 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947560 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947554 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947550 1 0.6295 0.1161 0.528 0.472 0.000
#> SRR1947552 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947549 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947551 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947548 1 0.0237 0.9699 0.996 0.004 0.000
#> SRR1947506 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947507 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947503 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947499 3 0.0892 0.9734 0.020 0.000 0.980
#> SRR1947498 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947508 3 0.0000 0.9904 0.000 0.000 1.000
#> SRR1947505 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947497 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947494 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947493 3 0.4796 0.7211 0.220 0.000 0.780
#> SRR1947492 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.9822 0.000 1.000 0.000
#> SRR1947491 2 0.0424 0.9746 0.008 0.992 0.000
#> SRR1947490 1 0.0000 0.9725 1.000 0.000 0.000
#> SRR1947489 3 0.0000 0.9904 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.1474 0.8704 0.000 0.000 0.948 0.052
#> SRR1947546 2 0.2760 0.8349 0.000 0.872 0.000 0.128
#> SRR1947545 1 0.0336 0.8258 0.992 0.000 0.000 0.008
#> SRR1947544 1 0.0336 0.8258 0.992 0.000 0.000 0.008
#> SRR1947542 2 0.4730 0.5448 0.000 0.636 0.000 0.364
#> SRR1947541 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947540 4 0.4877 0.3596 0.000 0.408 0.000 0.592
#> SRR1947539 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947538 4 0.2149 0.4935 0.088 0.000 0.000 0.912
#> SRR1947537 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947536 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947535 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947534 1 0.3649 0.6466 0.796 0.204 0.000 0.000
#> SRR1947533 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947532 1 0.4730 0.6541 0.636 0.000 0.000 0.364
#> SRR1947531 4 0.4877 0.3596 0.000 0.408 0.000 0.592
#> SRR1947530 3 0.6110 0.3738 0.368 0.000 0.576 0.056
#> SRR1947529 2 0.1474 0.8784 0.000 0.948 0.000 0.052
#> SRR1947528 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947527 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947525 1 0.5682 0.6244 0.612 0.036 0.000 0.352
#> SRR1947524 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947523 2 0.4434 0.7531 0.016 0.772 0.004 0.208
#> SRR1947521 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947520 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947519 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947518 4 0.2149 0.4935 0.088 0.000 0.000 0.912
#> SRR1947517 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947516 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947515 1 0.4730 0.6541 0.636 0.000 0.000 0.364
#> SRR1947514 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.2053 0.8050 0.924 0.000 0.004 0.072
#> SRR1947512 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947510 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947572 1 0.4585 0.6673 0.668 0.000 0.000 0.332
#> SRR1947611 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947509 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947644 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947643 2 0.2011 0.8460 0.000 0.920 0.000 0.080
#> SRR1947642 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947640 1 0.5674 0.6463 0.724 0.176 0.004 0.096
#> SRR1947641 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947639 1 0.5323 0.6389 0.628 0.020 0.000 0.352
#> SRR1947638 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947637 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947636 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947635 2 0.2011 0.8701 0.000 0.920 0.000 0.080
#> SRR1947634 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947633 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947632 2 0.4134 0.6944 0.000 0.740 0.000 0.260
#> SRR1947631 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947629 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947630 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947627 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947628 4 0.4477 0.4046 0.000 0.312 0.000 0.688
#> SRR1947626 2 0.2149 0.8406 0.000 0.912 0.000 0.088
#> SRR1947625 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947624 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947623 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947622 2 0.3219 0.8227 0.000 0.836 0.000 0.164
#> SRR1947621 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.1867 0.8069 0.928 0.000 0.000 0.072
#> SRR1947619 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947617 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.1867 0.8069 0.928 0.000 0.000 0.072
#> SRR1947616 4 0.4877 0.3596 0.000 0.408 0.000 0.592
#> SRR1947615 3 0.1389 0.8745 0.000 0.000 0.952 0.048
#> SRR1947614 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947613 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.2466 0.5256 0.056 0.028 0.000 0.916
#> SRR1947612 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.2125 0.8042 0.920 0.000 0.004 0.076
#> SRR1947608 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947607 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947604 1 0.4888 0.6455 0.588 0.000 0.000 0.412
#> SRR1947605 1 0.0921 0.8210 0.972 0.000 0.000 0.028
#> SRR1947603 2 0.0707 0.8915 0.000 0.980 0.000 0.020
#> SRR1947602 3 0.6097 0.3831 0.364 0.000 0.580 0.056
#> SRR1947600 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947601 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.0336 0.5273 0.000 0.008 0.000 0.992
#> SRR1947599 1 0.1940 0.8062 0.924 0.000 0.000 0.076
#> SRR1947597 2 0.2647 0.8395 0.000 0.880 0.000 0.120
#> SRR1947596 1 0.4624 0.6686 0.660 0.000 0.000 0.340
#> SRR1947595 1 0.5632 0.6502 0.732 0.176 0.008 0.084
#> SRR1947594 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947590 1 0.4624 0.6686 0.660 0.000 0.000 0.340
#> SRR1947588 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947586 2 0.3172 0.7482 0.000 0.840 0.000 0.160
#> SRR1947585 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947584 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947583 1 0.6770 0.3876 0.560 0.340 0.004 0.096
#> SRR1947582 1 0.1867 0.8069 0.928 0.000 0.000 0.072
#> SRR1947580 4 0.4907 0.3467 0.000 0.420 0.000 0.580
#> SRR1947581 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947575 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947578 4 0.4877 0.3596 0.000 0.408 0.000 0.592
#> SRR1947573 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947574 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947571 1 0.4697 0.6506 0.644 0.000 0.000 0.356
#> SRR1947577 1 0.1867 0.8069 0.928 0.000 0.000 0.072
#> SRR1947570 3 0.6252 0.2018 0.432 0.000 0.512 0.056
#> SRR1947569 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947566 2 0.2345 0.8278 0.000 0.900 0.000 0.100
#> SRR1947567 2 0.3172 0.8264 0.000 0.840 0.000 0.160
#> SRR1947568 1 0.5658 0.6427 0.632 0.040 0.000 0.328
#> SRR1947564 2 0.3801 0.7279 0.000 0.780 0.000 0.220
#> SRR1947563 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947562 2 0.7554 0.2091 0.192 0.432 0.000 0.376
#> SRR1947565 3 0.0188 0.9145 0.000 0.000 0.996 0.004
#> SRR1947559 2 0.2589 0.8362 0.000 0.884 0.000 0.116
#> SRR1947560 3 0.0188 0.9151 0.000 0.000 0.996 0.004
#> SRR1947561 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947556 1 0.3688 0.7451 0.792 0.000 0.000 0.208
#> SRR1947553 4 0.2466 0.5256 0.056 0.028 0.000 0.916
#> SRR1947554 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947550 1 0.8066 0.1815 0.356 0.336 0.004 0.304
#> SRR1947552 1 0.2647 0.8059 0.880 0.000 0.000 0.120
#> SRR1947549 3 0.0000 0.9158 0.000 0.000 1.000 0.000
#> SRR1947551 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947548 1 0.4730 0.6541 0.636 0.000 0.000 0.364
#> SRR1947506 3 0.5936 0.4371 0.324 0.000 0.620 0.056
#> SRR1947507 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.3688 0.7451 0.792 0.000 0.000 0.208
#> SRR1947503 1 0.0817 0.8224 0.976 0.000 0.000 0.024
#> SRR1947502 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947501 2 0.3074 0.8154 0.000 0.848 0.000 0.152
#> SRR1947499 3 0.6097 0.3831 0.364 0.000 0.580 0.056
#> SRR1947498 4 0.4985 0.4458 0.000 0.000 0.468 0.532
#> SRR1947508 3 0.1118 0.8851 0.000 0.000 0.964 0.036
#> SRR1947505 4 0.4713 0.3974 0.000 0.360 0.000 0.640
#> SRR1947497 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.8989 0.000 1.000 0.000 0.000
#> SRR1947494 1 0.4661 0.6665 0.652 0.000 0.000 0.348
#> SRR1947493 1 0.6257 0.0261 0.508 0.000 0.436 0.056
#> SRR1947492 1 0.0000 0.8269 1.000 0.000 0.000 0.000
#> SRR1947500 2 0.1211 0.8856 0.000 0.960 0.000 0.040
#> SRR1947491 2 0.6050 0.5842 0.212 0.676 0.000 0.112
#> SRR1947490 1 0.0921 0.8201 0.972 0.000 0.000 0.028
#> SRR1947489 3 0.1557 0.8660 0.000 0.000 0.944 0.056
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.3209 0.7570 0.000 0.000 0.812 0.180 0.008
#> SRR1947546 4 0.5399 0.2181 0.000 0.448 0.000 0.496 0.056
#> SRR1947545 1 0.0963 0.7325 0.964 0.000 0.000 0.036 0.000
#> SRR1947544 1 0.0510 0.7422 0.984 0.000 0.000 0.016 0.000
#> SRR1947542 4 0.4806 0.5226 0.000 0.252 0.000 0.688 0.060
#> SRR1947541 3 0.2017 0.8389 0.000 0.000 0.912 0.080 0.008
#> SRR1947540 5 0.2074 0.6691 0.000 0.104 0.000 0.000 0.896
#> SRR1947539 3 0.1211 0.8520 0.000 0.000 0.960 0.024 0.016
#> SRR1947538 5 0.3919 0.5546 0.036 0.000 0.000 0.188 0.776
#> SRR1947537 3 0.1484 0.8553 0.000 0.000 0.944 0.048 0.008
#> SRR1947536 5 0.4430 0.6099 0.000 0.000 0.360 0.012 0.628
#> SRR1947535 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947534 1 0.3109 0.5526 0.800 0.200 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.8664 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 4 0.4270 0.5127 0.204 0.000 0.000 0.748 0.048
#> SRR1947531 5 0.2074 0.6691 0.000 0.104 0.000 0.000 0.896
#> SRR1947530 3 0.6706 0.1726 0.352 0.000 0.452 0.188 0.008
#> SRR1947529 2 0.4960 0.6135 0.000 0.668 0.000 0.064 0.268
#> SRR1947528 3 0.1628 0.8521 0.000 0.000 0.936 0.056 0.008
#> SRR1947527 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947526 2 0.0000 0.8664 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 4 0.5436 0.0330 0.456 0.004 0.000 0.492 0.048
#> SRR1947524 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947523 4 0.3993 0.5853 0.000 0.216 0.000 0.756 0.028
#> SRR1947521 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947520 2 0.1082 0.8461 0.000 0.964 0.000 0.008 0.028
#> SRR1947519 3 0.0671 0.8642 0.000 0.000 0.980 0.016 0.004
#> SRR1947518 5 0.4066 0.5474 0.044 0.000 0.000 0.188 0.768
#> SRR1947517 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947516 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947515 4 0.4270 0.5127 0.204 0.000 0.000 0.748 0.048
#> SRR1947514 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947513 1 0.4440 0.1875 0.528 0.000 0.000 0.468 0.004
#> SRR1947512 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0404 0.8613 0.000 0.988 0.000 0.000 0.012
#> SRR1947510 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947572 1 0.4787 0.3556 0.640 0.000 0.000 0.324 0.036
#> SRR1947611 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947509 3 0.2820 0.8296 0.000 0.004 0.884 0.056 0.056
#> SRR1947644 5 0.5094 0.5610 0.000 0.000 0.352 0.048 0.600
#> SRR1947643 2 0.3424 0.6936 0.000 0.760 0.000 0.000 0.240
#> SRR1947642 3 0.0566 0.8640 0.000 0.000 0.984 0.012 0.004
#> SRR1947640 4 0.5031 0.4189 0.260 0.032 0.000 0.684 0.024
#> SRR1947641 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947639 1 0.5440 -0.0470 0.476 0.004 0.000 0.472 0.048
#> SRR1947638 1 0.2813 0.6184 0.832 0.000 0.000 0.168 0.000
#> SRR1947637 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947636 3 0.1484 0.8553 0.000 0.000 0.944 0.048 0.008
#> SRR1947635 4 0.6626 0.3232 0.000 0.272 0.000 0.456 0.272
#> SRR1947634 2 0.0404 0.8613 0.000 0.988 0.000 0.000 0.012
#> SRR1947633 3 0.1579 0.8451 0.000 0.000 0.944 0.032 0.024
#> SRR1947632 4 0.5338 0.4543 0.000 0.324 0.000 0.604 0.072
#> SRR1947631 3 0.0566 0.8640 0.000 0.000 0.984 0.012 0.004
#> SRR1947629 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947630 2 0.1750 0.8255 0.000 0.936 0.000 0.036 0.028
#> SRR1947627 3 0.0566 0.8640 0.000 0.000 0.984 0.012 0.004
#> SRR1947628 5 0.1697 0.6669 0.000 0.060 0.000 0.008 0.932
#> SRR1947626 2 0.3661 0.6584 0.000 0.724 0.000 0.000 0.276
#> SRR1947625 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947624 2 0.1750 0.8255 0.000 0.936 0.000 0.036 0.028
#> SRR1947623 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.6063 0.4318 0.000 0.540 0.000 0.144 0.316
#> SRR1947621 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947620 1 0.4383 0.2900 0.572 0.000 0.000 0.424 0.004
#> SRR1947619 3 0.0963 0.8607 0.000 0.000 0.964 0.036 0.000
#> SRR1947617 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947618 1 0.4383 0.2900 0.572 0.000 0.000 0.424 0.004
#> SRR1947616 5 0.2127 0.6681 0.000 0.108 0.000 0.000 0.892
#> SRR1947615 3 0.3171 0.7665 0.000 0.000 0.816 0.176 0.008
#> SRR1947614 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947613 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 5 0.2787 0.6425 0.004 0.028 0.000 0.088 0.880
#> SRR1947612 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947609 4 0.4482 0.2047 0.376 0.000 0.000 0.612 0.012
#> SRR1947608 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947606 3 0.1628 0.8521 0.000 0.000 0.936 0.056 0.008
#> SRR1947607 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.3237 0.5715 0.104 0.000 0.000 0.848 0.048
#> SRR1947605 1 0.1121 0.7284 0.956 0.000 0.000 0.044 0.000
#> SRR1947603 2 0.2653 0.7860 0.000 0.880 0.000 0.096 0.024
#> SRR1947602 3 0.6650 0.2547 0.324 0.000 0.480 0.188 0.008
#> SRR1947600 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947601 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947598 5 0.1484 0.6611 0.000 0.008 0.000 0.048 0.944
#> SRR1947599 4 0.4323 0.2986 0.332 0.000 0.000 0.656 0.012
#> SRR1947597 2 0.4325 0.5816 0.000 0.736 0.000 0.220 0.044
#> SRR1947596 1 0.5151 0.2466 0.560 0.000 0.000 0.396 0.044
#> SRR1947595 4 0.6010 0.3961 0.248 0.052 0.008 0.644 0.048
#> SRR1947594 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947591 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947590 1 0.5188 0.1969 0.540 0.000 0.000 0.416 0.044
#> SRR1947588 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.1484 0.8553 0.000 0.000 0.944 0.048 0.008
#> SRR1947586 2 0.3774 0.6373 0.000 0.704 0.000 0.000 0.296
#> SRR1947585 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947584 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.5489 0.5796 0.096 0.188 0.000 0.692 0.024
#> SRR1947582 1 0.4383 0.2900 0.572 0.000 0.000 0.424 0.004
#> SRR1947580 5 0.2471 0.6556 0.000 0.136 0.000 0.000 0.864
#> SRR1947581 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947575 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947579 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947578 5 0.2074 0.6691 0.000 0.104 0.000 0.000 0.896
#> SRR1947573 3 0.0000 0.8634 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 1 0.2471 0.6502 0.864 0.000 0.000 0.136 0.000
#> SRR1947571 4 0.4615 0.4643 0.252 0.000 0.000 0.700 0.048
#> SRR1947577 1 0.4446 0.1727 0.520 0.000 0.000 0.476 0.004
#> SRR1947570 3 0.6341 0.4263 0.248 0.000 0.560 0.184 0.008
#> SRR1947569 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947566 2 0.3366 0.7023 0.000 0.768 0.000 0.000 0.232
#> SRR1947567 4 0.6638 0.3394 0.000 0.272 0.000 0.452 0.276
#> SRR1947568 1 0.6037 0.3668 0.632 0.092 0.000 0.240 0.036
#> SRR1947564 2 0.2359 0.7985 0.000 0.904 0.000 0.060 0.036
#> SRR1947563 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947562 4 0.3851 0.6198 0.016 0.108 0.000 0.824 0.052
#> SRR1947565 3 0.1484 0.8553 0.000 0.000 0.944 0.048 0.008
#> SRR1947559 2 0.4329 0.5302 0.000 0.716 0.000 0.252 0.032
#> SRR1947560 3 0.2609 0.8284 0.000 0.004 0.896 0.048 0.052
#> SRR1947561 2 0.0162 0.8670 0.000 0.996 0.000 0.004 0.000
#> SRR1947557 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0290 0.8638 0.000 0.000 0.992 0.008 0.000
#> SRR1947556 1 0.3039 0.5932 0.808 0.000 0.000 0.192 0.000
#> SRR1947553 5 0.2787 0.6425 0.004 0.028 0.000 0.088 0.880
#> SRR1947554 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0609 0.8593 0.000 0.980 0.000 0.020 0.000
#> SRR1947550 4 0.4761 0.6229 0.024 0.176 0.000 0.748 0.052
#> SRR1947552 4 0.3355 0.4892 0.184 0.000 0.000 0.804 0.012
#> SRR1947549 3 0.0162 0.8637 0.000 0.000 0.996 0.004 0.000
#> SRR1947551 5 0.5094 0.5610 0.000 0.000 0.352 0.048 0.600
#> SRR1947548 4 0.4237 0.5167 0.200 0.000 0.000 0.752 0.048
#> SRR1947506 3 0.5812 0.5570 0.168 0.000 0.640 0.184 0.008
#> SRR1947507 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.2966 0.6018 0.816 0.000 0.000 0.184 0.000
#> SRR1947503 1 0.3508 0.5521 0.748 0.000 0.000 0.252 0.000
#> SRR1947502 2 0.0290 0.8653 0.000 0.992 0.000 0.008 0.000
#> SRR1947501 4 0.5506 0.3155 0.000 0.404 0.000 0.528 0.068
#> SRR1947499 3 0.6650 0.2547 0.324 0.000 0.480 0.188 0.008
#> SRR1947498 5 0.4444 0.6110 0.000 0.000 0.364 0.012 0.624
#> SRR1947508 3 0.2358 0.8220 0.000 0.000 0.888 0.104 0.008
#> SRR1947505 5 0.2504 0.6646 0.000 0.064 0.000 0.040 0.896
#> SRR1947497 2 0.0000 0.8664 0.000 1.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.8664 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 4 0.4756 0.3917 0.288 0.000 0.000 0.668 0.044
#> SRR1947493 1 0.6743 -0.0288 0.412 0.000 0.392 0.188 0.008
#> SRR1947492 1 0.0000 0.7480 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 2 0.4980 -0.1915 0.000 0.488 0.000 0.484 0.028
#> SRR1947491 4 0.7258 0.5323 0.096 0.140 0.000 0.540 0.224
#> SRR1947490 1 0.0404 0.7430 0.988 0.000 0.000 0.012 0.000
#> SRR1947489 3 0.3246 0.7588 0.000 0.000 0.808 0.184 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.1801 0.63742 0.000 0.000 0.004 0.016 0.056 0.924
#> SRR1947546 4 0.4539 0.43740 0.000 0.264 0.032 0.684 0.012 0.008
#> SRR1947545 1 0.1950 0.78541 0.912 0.000 0.000 0.024 0.000 0.064
#> SRR1947544 1 0.0717 0.82504 0.976 0.000 0.000 0.008 0.000 0.016
#> SRR1947542 4 0.3246 0.54870 0.000 0.160 0.016 0.812 0.000 0.012
#> SRR1947541 6 0.2755 0.65277 0.000 0.000 0.004 0.012 0.140 0.844
#> SRR1947540 3 0.0458 0.66215 0.000 0.016 0.984 0.000 0.000 0.000
#> SRR1947539 5 0.2964 0.54664 0.000 0.000 0.004 0.000 0.792 0.204
#> SRR1947538 3 0.2020 0.62009 0.000 0.000 0.896 0.096 0.000 0.008
#> SRR1947537 6 0.3606 0.57684 0.000 0.000 0.004 0.004 0.284 0.708
#> SRR1947536 3 0.5720 0.15247 0.000 0.000 0.472 0.000 0.356 0.172
#> SRR1947535 5 0.4657 -0.00107 0.000 0.000 0.004 0.032 0.508 0.456
#> SRR1947534 1 0.2996 0.59222 0.772 0.228 0.000 0.000 0.000 0.000
#> SRR1947533 2 0.0146 0.86849 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947532 4 0.3286 0.58375 0.112 0.000 0.012 0.832 0.000 0.044
#> SRR1947531 3 0.0458 0.66215 0.000 0.016 0.984 0.000 0.000 0.000
#> SRR1947530 6 0.3734 0.53621 0.136 0.000 0.004 0.028 0.028 0.804
#> SRR1947529 3 0.5776 -0.11002 0.000 0.396 0.448 0.152 0.000 0.004
#> SRR1947528 6 0.2871 0.64605 0.000 0.000 0.000 0.004 0.192 0.804
#> SRR1947527 2 0.0146 0.86849 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947526 2 0.0146 0.86849 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947525 4 0.4933 0.00596 0.440 0.024 0.012 0.516 0.000 0.008
#> SRR1947524 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947523 4 0.3714 0.63905 0.000 0.044 0.020 0.800 0.000 0.136
#> SRR1947521 5 0.0937 0.64060 0.000 0.000 0.000 0.000 0.960 0.040
#> SRR1947520 2 0.1753 0.82228 0.000 0.912 0.000 0.000 0.084 0.004
#> SRR1947519 6 0.4523 0.41116 0.000 0.000 0.004 0.032 0.372 0.592
#> SRR1947518 3 0.2020 0.62009 0.000 0.000 0.896 0.096 0.000 0.008
#> SRR1947517 5 0.1007 0.63939 0.000 0.000 0.000 0.000 0.956 0.044
#> SRR1947516 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947515 4 0.3286 0.58375 0.112 0.000 0.012 0.832 0.000 0.044
#> SRR1947514 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947513 4 0.6203 0.36450 0.276 0.000 0.004 0.384 0.000 0.336
#> SRR1947512 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0603 0.86266 0.000 0.980 0.000 0.000 0.016 0.004
#> SRR1947510 5 0.0937 0.64060 0.000 0.000 0.000 0.000 0.960 0.040
#> SRR1947572 1 0.3437 0.60709 0.752 0.000 0.004 0.236 0.000 0.008
#> SRR1947611 5 0.0146 0.64038 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947509 5 0.2260 0.54782 0.000 0.000 0.000 0.000 0.860 0.140
#> SRR1947644 5 0.2697 0.43127 0.000 0.000 0.188 0.000 0.812 0.000
#> SRR1947643 2 0.3769 0.45329 0.000 0.640 0.356 0.000 0.000 0.004
#> SRR1947642 6 0.4570 0.36963 0.000 0.000 0.004 0.032 0.392 0.572
#> SRR1947640 4 0.5229 0.59529 0.096 0.004 0.020 0.656 0.000 0.224
#> SRR1947641 5 0.4648 0.03575 0.000 0.000 0.004 0.032 0.520 0.444
#> SRR1947639 1 0.4722 0.11172 0.508 0.012 0.012 0.460 0.000 0.008
#> SRR1947638 1 0.3133 0.60509 0.780 0.000 0.000 0.212 0.000 0.008
#> SRR1947637 5 0.0508 0.63508 0.000 0.000 0.000 0.004 0.984 0.012
#> SRR1947636 6 0.3405 0.58825 0.000 0.000 0.004 0.000 0.272 0.724
#> SRR1947635 4 0.5495 0.27792 0.000 0.064 0.392 0.516 0.000 0.028
#> SRR1947634 2 0.0603 0.86266 0.000 0.980 0.000 0.000 0.016 0.004
#> SRR1947633 5 0.2838 0.56049 0.000 0.000 0.004 0.000 0.808 0.188
#> SRR1947632 4 0.3981 0.53712 0.000 0.180 0.032 0.768 0.012 0.008
#> SRR1947631 6 0.4586 0.35022 0.000 0.000 0.004 0.032 0.400 0.564
#> SRR1947629 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947630 2 0.2146 0.79631 0.000 0.880 0.000 0.000 0.116 0.004
#> SRR1947627 6 0.3515 0.51884 0.000 0.000 0.000 0.000 0.324 0.676
#> SRR1947628 3 0.0260 0.66082 0.000 0.008 0.992 0.000 0.000 0.000
#> SRR1947626 2 0.3868 0.16159 0.000 0.508 0.492 0.000 0.000 0.000
#> SRR1947625 5 0.4651 0.02448 0.000 0.000 0.004 0.032 0.516 0.448
#> SRR1947624 2 0.2871 0.72294 0.000 0.804 0.000 0.000 0.192 0.004
#> SRR1947623 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 3 0.5726 0.07187 0.000 0.300 0.504 0.196 0.000 0.000
#> SRR1947621 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947620 1 0.6248 -0.29694 0.348 0.000 0.004 0.332 0.000 0.316
#> SRR1947619 6 0.3918 0.43659 0.000 0.000 0.004 0.004 0.360 0.632
#> SRR1947617 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947618 4 0.6250 0.27480 0.332 0.000 0.004 0.344 0.000 0.320
#> SRR1947616 3 0.0632 0.66155 0.000 0.024 0.976 0.000 0.000 0.000
#> SRR1947615 6 0.2882 0.63611 0.000 0.000 0.004 0.028 0.120 0.848
#> SRR1947614 5 0.1007 0.63939 0.000 0.000 0.000 0.000 0.956 0.044
#> SRR1947613 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 3 0.1411 0.64128 0.000 0.000 0.936 0.060 0.000 0.004
#> SRR1947612 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947609 4 0.5974 0.49572 0.168 0.000 0.012 0.484 0.000 0.336
#> SRR1947608 5 0.4657 -0.00107 0.000 0.000 0.004 0.032 0.508 0.456
#> SRR1947606 6 0.2823 0.64105 0.000 0.000 0.000 0.000 0.204 0.796
#> SRR1947607 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.1977 0.62751 0.032 0.000 0.008 0.920 0.000 0.040
#> SRR1947605 1 0.2039 0.77670 0.904 0.000 0.000 0.020 0.000 0.076
#> SRR1947603 2 0.4073 0.61945 0.000 0.728 0.016 0.236 0.012 0.008
#> SRR1947602 6 0.3727 0.54408 0.128 0.000 0.004 0.028 0.032 0.808
#> SRR1947600 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947601 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947598 3 0.0260 0.65850 0.000 0.000 0.992 0.008 0.000 0.000
#> SRR1947599 4 0.5559 0.55206 0.124 0.000 0.012 0.564 0.000 0.300
#> SRR1947597 2 0.3955 0.38509 0.000 0.608 0.008 0.384 0.000 0.000
#> SRR1947596 1 0.5218 0.06969 0.464 0.000 0.008 0.460 0.000 0.068
#> SRR1947595 4 0.7026 0.52512 0.044 0.016 0.020 0.484 0.128 0.308
#> SRR1947594 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 6 0.3979 0.16590 0.000 0.000 0.004 0.000 0.456 0.540
#> SRR1947591 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947590 4 0.5383 -0.07022 0.440 0.000 0.012 0.472 0.000 0.076
#> SRR1947588 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 6 0.3628 0.59245 0.000 0.000 0.004 0.008 0.268 0.720
#> SRR1947586 3 0.3868 -0.19850 0.000 0.496 0.504 0.000 0.000 0.000
#> SRR1947585 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947584 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.5313 0.62433 0.028 0.060 0.024 0.676 0.000 0.212
#> SRR1947582 4 0.6250 0.27480 0.332 0.000 0.004 0.344 0.000 0.320
#> SRR1947580 3 0.1141 0.65085 0.000 0.052 0.948 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0146 0.64038 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947575 5 0.4657 -0.00107 0.000 0.000 0.004 0.032 0.508 0.456
#> SRR1947579 5 0.0937 0.64060 0.000 0.000 0.000 0.000 0.960 0.040
#> SRR1947578 3 0.0458 0.66215 0.000 0.016 0.984 0.000 0.000 0.000
#> SRR1947573 5 0.3982 0.05245 0.000 0.000 0.004 0.000 0.536 0.460
#> SRR1947574 1 0.2772 0.65047 0.816 0.000 0.000 0.180 0.000 0.004
#> SRR1947571 4 0.3338 0.55505 0.152 0.000 0.012 0.812 0.000 0.024
#> SRR1947577 4 0.6170 0.38122 0.276 0.000 0.004 0.412 0.000 0.308
#> SRR1947570 6 0.1579 0.62233 0.008 0.000 0.004 0.020 0.024 0.944
#> SRR1947569 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947566 2 0.3592 0.48206 0.000 0.656 0.344 0.000 0.000 0.000
#> SRR1947567 4 0.5401 0.34660 0.000 0.116 0.332 0.548 0.000 0.004
#> SRR1947568 1 0.4472 0.60991 0.740 0.084 0.008 0.160 0.000 0.008
#> SRR1947564 2 0.2513 0.75666 0.000 0.852 0.008 0.140 0.000 0.000
#> SRR1947563 5 0.4657 -0.00107 0.000 0.000 0.004 0.032 0.508 0.456
#> SRR1947562 4 0.1218 0.63264 0.000 0.028 0.012 0.956 0.000 0.004
#> SRR1947565 6 0.3489 0.57216 0.000 0.000 0.004 0.000 0.288 0.708
#> SRR1947559 2 0.4018 0.31348 0.000 0.580 0.008 0.412 0.000 0.000
#> SRR1947560 5 0.0146 0.64038 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947561 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947557 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 5 0.4657 -0.00107 0.000 0.000 0.004 0.032 0.508 0.456
#> SRR1947556 1 0.1643 0.79130 0.924 0.000 0.000 0.068 0.000 0.008
#> SRR1947553 3 0.1411 0.64128 0.000 0.000 0.936 0.060 0.000 0.004
#> SRR1947554 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.2169 0.81151 0.000 0.900 0.000 0.080 0.012 0.008
#> SRR1947550 4 0.3203 0.64273 0.000 0.052 0.020 0.848 0.000 0.080
#> SRR1947552 4 0.4780 0.59359 0.056 0.000 0.012 0.644 0.000 0.288
#> SRR1947549 6 0.3993 0.08785 0.000 0.000 0.004 0.000 0.476 0.520
#> SRR1947551 5 0.2697 0.43127 0.000 0.000 0.188 0.000 0.812 0.000
#> SRR1947548 4 0.3241 0.58608 0.108 0.000 0.012 0.836 0.000 0.044
#> SRR1947506 6 0.1950 0.63036 0.008 0.000 0.004 0.020 0.044 0.924
#> SRR1947507 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.1524 0.79702 0.932 0.000 0.000 0.060 0.000 0.008
#> SRR1947503 1 0.4028 0.44018 0.668 0.000 0.000 0.308 0.000 0.024
#> SRR1947502 2 0.0146 0.86950 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947501 4 0.4233 0.50693 0.000 0.204 0.036 0.740 0.012 0.008
#> SRR1947499 6 0.3727 0.54408 0.128 0.000 0.004 0.028 0.032 0.808
#> SRR1947498 3 0.5380 0.15232 0.000 0.000 0.476 0.000 0.412 0.112
#> SRR1947508 6 0.3758 0.59837 0.000 0.000 0.004 0.040 0.192 0.764
#> SRR1947505 3 0.0520 0.65952 0.000 0.008 0.984 0.008 0.000 0.000
#> SRR1947497 2 0.0146 0.86849 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947496 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0146 0.86849 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947494 4 0.4345 0.50379 0.188 0.000 0.012 0.732 0.000 0.068
#> SRR1947493 6 0.3657 0.53790 0.136 0.000 0.004 0.024 0.028 0.808
#> SRR1947492 1 0.0000 0.83732 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.4443 0.38970 0.000 0.328 0.012 0.636 0.000 0.024
#> SRR1947491 4 0.6158 0.50492 0.048 0.016 0.236 0.592 0.000 0.108
#> SRR1947490 1 0.0363 0.83072 0.988 0.000 0.000 0.012 0.000 0.000
#> SRR1947489 6 0.2255 0.63604 0.000 0.000 0.004 0.016 0.088 0.892
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 15148 rows and 152 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 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 0.599 0.852 0.925 0.4831 0.522 0.522
#> 3 3 0.542 0.748 0.869 0.2754 0.681 0.482
#> 4 4 0.643 0.722 0.841 0.1518 0.747 0.457
#> 5 5 0.587 0.721 0.831 0.0612 0.921 0.743
#> 6 6 0.716 0.740 0.847 0.0614 0.922 0.701
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
#> SRR1947547 2 0.4022 0.868 0.080 0.920
#> SRR1947546 1 0.2948 0.900 0.948 0.052
#> SRR1947545 2 0.9754 0.451 0.408 0.592
#> SRR1947544 1 0.9170 0.528 0.668 0.332
#> SRR1947542 1 0.0672 0.913 0.992 0.008
#> SRR1947541 2 0.3879 0.871 0.076 0.924
#> SRR1947540 1 0.6801 0.802 0.820 0.180
#> SRR1947539 2 0.0000 0.917 0.000 1.000
#> SRR1947538 1 0.0000 0.912 1.000 0.000
#> SRR1947537 2 0.2948 0.886 0.052 0.948
#> SRR1947536 2 0.0000 0.917 0.000 1.000
#> SRR1947535 2 0.0000 0.917 0.000 1.000
#> SRR1947534 1 0.0000 0.912 1.000 0.000
#> SRR1947533 1 0.5408 0.855 0.876 0.124
#> SRR1947532 1 0.0000 0.912 1.000 0.000
#> SRR1947531 1 0.6712 0.806 0.824 0.176
#> SRR1947530 2 0.4022 0.868 0.080 0.920
#> SRR1947529 1 0.6712 0.806 0.824 0.176
#> SRR1947528 2 0.0000 0.917 0.000 1.000
#> SRR1947527 1 0.0672 0.913 0.992 0.008
#> SRR1947526 1 0.4022 0.884 0.920 0.080
#> SRR1947525 1 0.0000 0.912 1.000 0.000
#> SRR1947524 2 0.0000 0.917 0.000 1.000
#> SRR1947523 1 0.0938 0.913 0.988 0.012
#> SRR1947521 2 0.0000 0.917 0.000 1.000
#> SRR1947520 1 0.6531 0.815 0.832 0.168
#> SRR1947519 2 0.0000 0.917 0.000 1.000
#> SRR1947518 1 0.0000 0.912 1.000 0.000
#> SRR1947517 2 0.0000 0.917 0.000 1.000
#> SRR1947516 1 0.4298 0.880 0.912 0.088
#> SRR1947515 1 0.2603 0.896 0.956 0.044
#> SRR1947514 1 0.1633 0.910 0.976 0.024
#> SRR1947513 1 0.1184 0.910 0.984 0.016
#> SRR1947512 1 0.0000 0.912 1.000 0.000
#> SRR1947511 1 0.5294 0.858 0.880 0.120
#> SRR1947510 2 0.0000 0.917 0.000 1.000
#> SRR1947572 1 0.8499 0.630 0.724 0.276
#> SRR1947611 2 0.0000 0.917 0.000 1.000
#> SRR1947509 2 0.0000 0.917 0.000 1.000
#> SRR1947644 2 0.0000 0.917 0.000 1.000
#> SRR1947643 1 0.6712 0.806 0.824 0.176
#> SRR1947642 2 0.7602 0.718 0.220 0.780
#> SRR1947640 1 0.0672 0.913 0.992 0.008
#> SRR1947641 2 0.7602 0.718 0.220 0.780
#> SRR1947639 1 0.0000 0.912 1.000 0.000
#> SRR1947638 1 0.0000 0.912 1.000 0.000
#> SRR1947637 2 0.0000 0.917 0.000 1.000
#> SRR1947636 2 0.0000 0.917 0.000 1.000
#> SRR1947635 1 0.6712 0.806 0.824 0.176
#> SRR1947634 1 0.2423 0.904 0.960 0.040
#> SRR1947633 2 0.0000 0.917 0.000 1.000
#> SRR1947632 1 0.0672 0.913 0.992 0.008
#> SRR1947631 2 0.7602 0.718 0.220 0.780
#> SRR1947629 2 0.0000 0.917 0.000 1.000
#> SRR1947630 1 0.2948 0.899 0.948 0.052
#> SRR1947627 2 0.0000 0.917 0.000 1.000
#> SRR1947628 2 0.9866 0.272 0.432 0.568
#> SRR1947626 1 0.0672 0.913 0.992 0.008
#> SRR1947625 2 0.7376 0.734 0.208 0.792
#> SRR1947624 1 0.5519 0.854 0.872 0.128
#> SRR1947623 1 0.7815 0.697 0.768 0.232
#> SRR1947622 1 0.3431 0.895 0.936 0.064
#> SRR1947621 1 0.0672 0.913 0.992 0.008
#> SRR1947620 1 0.0672 0.911 0.992 0.008
#> SRR1947619 2 0.2603 0.892 0.044 0.956
#> SRR1947617 1 0.1414 0.911 0.980 0.020
#> SRR1947618 1 0.1184 0.910 0.984 0.016
#> SRR1947616 2 0.9170 0.530 0.332 0.668
#> SRR1947615 2 0.7602 0.718 0.220 0.780
#> SRR1947614 2 0.0000 0.917 0.000 1.000
#> SRR1947613 1 0.0672 0.911 0.992 0.008
#> SRR1947610 1 0.0672 0.913 0.992 0.008
#> SRR1947612 1 0.0672 0.913 0.992 0.008
#> SRR1947609 1 0.8713 0.605 0.708 0.292
#> SRR1947608 2 0.0000 0.917 0.000 1.000
#> SRR1947606 2 0.0000 0.917 0.000 1.000
#> SRR1947607 1 0.0000 0.912 1.000 0.000
#> SRR1947604 1 0.0000 0.912 1.000 0.000
#> SRR1947605 1 0.6247 0.800 0.844 0.156
#> SRR1947603 1 0.5408 0.855 0.876 0.124
#> SRR1947602 2 0.2236 0.899 0.036 0.964
#> SRR1947600 2 0.0000 0.917 0.000 1.000
#> SRR1947601 1 0.2423 0.904 0.960 0.040
#> SRR1947598 2 0.9323 0.510 0.348 0.652
#> SRR1947599 1 0.0000 0.912 1.000 0.000
#> SRR1947597 1 0.0672 0.913 0.992 0.008
#> SRR1947596 1 0.7602 0.711 0.780 0.220
#> SRR1947595 2 0.7602 0.709 0.220 0.780
#> SRR1947594 1 0.1184 0.909 0.984 0.016
#> SRR1947592 2 0.0000 0.917 0.000 1.000
#> SRR1947591 1 0.0938 0.913 0.988 0.012
#> SRR1947590 1 0.9087 0.542 0.676 0.324
#> SRR1947588 1 0.8813 0.590 0.700 0.300
#> SRR1947587 2 0.0000 0.917 0.000 1.000
#> SRR1947586 1 0.0672 0.913 0.992 0.008
#> SRR1947585 2 0.0000 0.917 0.000 1.000
#> SRR1947584 1 0.3879 0.874 0.924 0.076
#> SRR1947583 1 0.0672 0.913 0.992 0.008
#> SRR1947582 1 0.0672 0.911 0.992 0.008
#> SRR1947580 1 0.5519 0.852 0.872 0.128
#> SRR1947581 1 0.7745 0.703 0.772 0.228
#> SRR1947576 2 0.0000 0.917 0.000 1.000
#> SRR1947575 2 0.0000 0.917 0.000 1.000
#> SRR1947579 2 0.0000 0.917 0.000 1.000
#> SRR1947578 1 0.8608 0.640 0.716 0.284
#> SRR1947573 2 0.0000 0.917 0.000 1.000
#> SRR1947574 1 0.0000 0.912 1.000 0.000
#> SRR1947571 1 0.0000 0.912 1.000 0.000
#> SRR1947577 1 0.0000 0.912 1.000 0.000
#> SRR1947570 2 0.4298 0.861 0.088 0.912
#> SRR1947569 2 0.0000 0.917 0.000 1.000
#> SRR1947566 1 0.6712 0.806 0.824 0.176
#> SRR1947567 1 0.4431 0.879 0.908 0.092
#> SRR1947568 1 0.0000 0.912 1.000 0.000
#> SRR1947564 1 0.0672 0.913 0.992 0.008
#> SRR1947563 2 0.0000 0.917 0.000 1.000
#> SRR1947562 1 0.0000 0.912 1.000 0.000
#> SRR1947565 2 0.0376 0.915 0.004 0.996
#> SRR1947559 1 0.0672 0.913 0.992 0.008
#> SRR1947560 2 0.2778 0.890 0.048 0.952
#> SRR1947561 1 0.4815 0.870 0.896 0.104
#> SRR1947557 1 0.9170 0.528 0.668 0.332
#> SRR1947558 2 0.4431 0.855 0.092 0.908
#> SRR1947556 1 0.9044 0.553 0.680 0.320
#> SRR1947553 1 0.0672 0.913 0.992 0.008
#> SRR1947554 1 0.0000 0.912 1.000 0.000
#> SRR1947555 1 0.6973 0.792 0.812 0.188
#> SRR1947550 1 0.0376 0.913 0.996 0.004
#> SRR1947552 1 0.0000 0.912 1.000 0.000
#> SRR1947549 2 0.0000 0.917 0.000 1.000
#> SRR1947551 2 0.0000 0.917 0.000 1.000
#> SRR1947548 1 0.0000 0.912 1.000 0.000
#> SRR1947506 2 0.2423 0.896 0.040 0.960
#> SRR1947507 1 0.2043 0.902 0.968 0.032
#> SRR1947504 1 0.7745 0.703 0.772 0.228
#> SRR1947503 1 0.0000 0.912 1.000 0.000
#> SRR1947502 1 0.4022 0.884 0.920 0.080
#> SRR1947501 1 0.5294 0.859 0.880 0.120
#> SRR1947499 2 0.3879 0.871 0.076 0.924
#> SRR1947498 2 0.0000 0.917 0.000 1.000
#> SRR1947508 2 0.7528 0.723 0.216 0.784
#> SRR1947505 2 0.9286 0.515 0.344 0.656
#> SRR1947497 1 0.0672 0.913 0.992 0.008
#> SRR1947496 1 0.5059 0.840 0.888 0.112
#> SRR1947495 1 0.5408 0.855 0.876 0.124
#> SRR1947494 1 0.0376 0.912 0.996 0.004
#> SRR1947493 2 0.5294 0.834 0.120 0.880
#> SRR1947492 1 0.0938 0.910 0.988 0.012
#> SRR1947500 1 0.0672 0.913 0.992 0.008
#> SRR1947491 1 0.4022 0.886 0.920 0.080
#> SRR1947490 1 0.0938 0.910 0.988 0.012
#> SRR1947489 2 0.0000 0.917 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.4504 0.7163 0.196 0.000 0.804
#> SRR1947546 2 0.5635 0.7807 0.036 0.784 0.180
#> SRR1947545 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947542 2 0.6100 0.7972 0.096 0.784 0.120
#> SRR1947541 3 0.3879 0.7449 0.152 0.000 0.848
#> SRR1947540 2 0.5356 0.7713 0.020 0.784 0.196
#> SRR1947539 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947538 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947537 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947536 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947535 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947534 2 0.6180 0.1776 0.416 0.584 0.000
#> SRR1947533 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947532 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947531 3 0.7597 0.2729 0.048 0.384 0.568
#> SRR1947530 3 0.4555 0.7128 0.200 0.000 0.800
#> SRR1947529 2 0.3752 0.7989 0.000 0.856 0.144
#> SRR1947528 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947527 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947525 2 0.4931 0.7553 0.212 0.784 0.004
#> SRR1947524 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947523 3 0.7319 0.6434 0.128 0.164 0.708
#> SRR1947521 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947518 2 0.5397 0.7003 0.280 0.720 0.000
#> SRR1947517 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947515 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947514 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947513 3 0.6781 0.6391 0.244 0.052 0.704
#> SRR1947512 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947572 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947611 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947509 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947644 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947643 2 0.0747 0.8184 0.000 0.984 0.016
#> SRR1947642 3 0.1860 0.8198 0.000 0.052 0.948
#> SRR1947640 3 0.9076 0.1740 0.144 0.368 0.488
#> SRR1947641 3 0.1860 0.8198 0.000 0.052 0.948
#> SRR1947639 2 0.4750 0.7534 0.216 0.784 0.000
#> SRR1947638 3 0.9827 0.0476 0.244 0.372 0.384
#> SRR1947637 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947635 3 0.7874 0.2929 0.064 0.368 0.568
#> SRR1947634 2 0.1289 0.8147 0.032 0.968 0.000
#> SRR1947633 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947632 2 0.6100 0.7972 0.096 0.784 0.120
#> SRR1947631 3 0.3009 0.8129 0.028 0.052 0.920
#> SRR1947629 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947630 3 0.7394 0.2690 0.032 0.472 0.496
#> SRR1947627 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947628 2 0.6490 0.7731 0.076 0.752 0.172
#> SRR1947626 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947625 3 0.1860 0.8198 0.000 0.052 0.948
#> SRR1947624 2 0.4291 0.6686 0.000 0.820 0.180
#> SRR1947623 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947622 2 0.1453 0.8249 0.008 0.968 0.024
#> SRR1947621 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947620 3 0.7303 0.6246 0.244 0.076 0.680
#> SRR1947619 3 0.0237 0.8376 0.004 0.000 0.996
#> SRR1947617 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947618 3 0.7458 0.6191 0.244 0.084 0.672
#> SRR1947616 2 0.5016 0.7294 0.000 0.760 0.240
#> SRR1947615 3 0.3009 0.8129 0.028 0.052 0.920
#> SRR1947614 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947610 2 0.4479 0.8156 0.096 0.860 0.044
#> SRR1947612 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947609 3 0.6685 0.6370 0.244 0.048 0.708
#> SRR1947608 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947604 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947605 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947603 2 0.4504 0.7725 0.000 0.804 0.196
#> SRR1947602 3 0.4121 0.7390 0.168 0.000 0.832
#> SRR1947600 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947598 3 0.5554 0.7487 0.112 0.076 0.812
#> SRR1947599 3 0.9825 0.0627 0.244 0.368 0.388
#> SRR1947597 2 0.6100 0.7972 0.096 0.784 0.120
#> SRR1947596 2 0.7824 0.4668 0.376 0.564 0.060
#> SRR1947595 3 0.3644 0.7778 0.124 0.004 0.872
#> SRR1947594 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947590 2 0.7807 0.3375 0.432 0.516 0.052
#> SRR1947588 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947587 3 0.0424 0.8357 0.008 0.000 0.992
#> SRR1947586 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947583 2 0.6662 0.7805 0.128 0.752 0.120
#> SRR1947582 3 0.7458 0.6191 0.244 0.084 0.672
#> SRR1947580 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947578 2 0.7047 0.7395 0.084 0.712 0.204
#> SRR1947573 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947574 3 0.9825 0.0627 0.244 0.368 0.388
#> SRR1947571 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947577 3 0.9664 0.2826 0.244 0.296 0.460
#> SRR1947570 3 0.5016 0.6733 0.240 0.000 0.760
#> SRR1947569 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947567 2 0.6063 0.7950 0.084 0.784 0.132
#> SRR1947568 1 0.6309 -0.2171 0.504 0.496 0.000
#> SRR1947564 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947562 2 0.4931 0.7553 0.212 0.784 0.004
#> SRR1947565 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947559 2 0.6100 0.7972 0.096 0.784 0.120
#> SRR1947560 3 0.0424 0.8367 0.000 0.008 0.992
#> SRR1947561 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947558 3 0.1529 0.8253 0.000 0.040 0.960
#> SRR1947556 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947553 2 0.5663 0.8068 0.096 0.808 0.096
#> SRR1947554 1 0.1031 0.9380 0.976 0.024 0.000
#> SRR1947555 2 0.4605 0.7664 0.000 0.796 0.204
#> SRR1947550 2 0.6587 0.7774 0.156 0.752 0.092
#> SRR1947552 3 0.9827 0.0319 0.244 0.376 0.380
#> SRR1947549 3 0.3340 0.7462 0.000 0.120 0.880
#> SRR1947551 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947548 2 0.5285 0.7308 0.244 0.752 0.004
#> SRR1947506 3 0.2448 0.8052 0.076 0.000 0.924
#> SRR1947507 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947503 2 0.9823 0.2289 0.288 0.428 0.284
#> SRR1947502 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947501 2 0.5574 0.7781 0.032 0.784 0.184
#> SRR1947499 3 0.4346 0.7263 0.184 0.000 0.816
#> SRR1947498 3 0.0000 0.8387 0.000 0.000 1.000
#> SRR1947508 3 0.2187 0.8256 0.028 0.024 0.948
#> SRR1947505 3 0.8386 0.3877 0.112 0.304 0.584
#> SRR1947497 2 0.0000 0.8223 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947495 2 0.4805 0.6786 0.012 0.812 0.176
#> SRR1947494 3 0.9825 0.0627 0.244 0.368 0.388
#> SRR1947493 3 0.4291 0.7300 0.180 0.000 0.820
#> SRR1947492 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947500 2 0.6107 0.7975 0.100 0.784 0.116
#> SRR1947491 3 0.8676 0.2162 0.112 0.368 0.520
#> SRR1947490 1 0.0000 0.9686 1.000 0.000 0.000
#> SRR1947489 3 0.1163 0.8303 0.028 0.000 0.972
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.5016 0.3242 0.000 0.004 0.600 0.396
#> SRR1947546 4 0.7175 0.1006 0.000 0.144 0.360 0.496
#> SRR1947545 4 0.4855 0.3466 0.400 0.000 0.000 0.600
#> SRR1947544 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.2973 0.5516 0.000 0.144 0.000 0.856
#> SRR1947541 3 0.4252 0.6182 0.000 0.004 0.744 0.252
#> SRR1947540 3 0.7335 0.0943 0.000 0.400 0.444 0.156
#> SRR1947539 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947538 4 0.2408 0.6552 0.000 0.104 0.000 0.896
#> SRR1947537 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947536 3 0.1118 0.8684 0.000 0.036 0.964 0.000
#> SRR1947535 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947534 2 0.6080 0.6013 0.100 0.664 0.000 0.236
#> SRR1947533 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947532 4 0.0000 0.6794 0.000 0.000 0.000 1.000
#> SRR1947531 3 0.7657 0.1238 0.000 0.256 0.464 0.280
#> SRR1947530 3 0.5364 0.3063 0.000 0.016 0.592 0.392
#> SRR1947529 2 0.6490 0.4381 0.000 0.640 0.204 0.156
#> SRR1947528 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947527 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947526 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947525 4 0.4431 0.5992 0.000 0.304 0.000 0.696
#> SRR1947524 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947523 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947521 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947520 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947519 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947518 4 0.2281 0.6580 0.000 0.096 0.000 0.904
#> SRR1947517 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947516 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947515 4 0.0000 0.6794 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947513 4 0.5056 0.7124 0.000 0.164 0.076 0.760
#> SRR1947512 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947510 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947572 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947611 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947509 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947644 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947643 2 0.1118 0.7886 0.000 0.964 0.000 0.036
#> SRR1947642 3 0.2216 0.8199 0.000 0.000 0.908 0.092
#> SRR1947640 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947641 3 0.2216 0.8199 0.000 0.000 0.908 0.092
#> SRR1947639 4 0.2973 0.5516 0.000 0.144 0.000 0.856
#> SRR1947638 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947637 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947636 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947635 3 0.7362 -0.1022 0.000 0.160 0.444 0.396
#> SRR1947634 2 0.4250 0.6507 0.000 0.724 0.000 0.276
#> SRR1947633 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947632 4 0.2973 0.5516 0.000 0.144 0.000 0.856
#> SRR1947631 3 0.3123 0.7764 0.000 0.000 0.844 0.156
#> SRR1947629 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947630 2 0.4250 0.6507 0.000 0.724 0.000 0.276
#> SRR1947627 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947628 4 0.6990 0.4687 0.000 0.304 0.144 0.552
#> SRR1947626 2 0.3569 0.7419 0.000 0.804 0.000 0.196
#> SRR1947625 3 0.2216 0.8199 0.000 0.000 0.908 0.092
#> SRR1947624 2 0.3497 0.8161 0.000 0.852 0.024 0.124
#> SRR1947623 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947622 2 0.5313 0.6422 0.000 0.608 0.016 0.376
#> SRR1947621 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947620 4 0.4462 0.7229 0.000 0.164 0.044 0.792
#> SRR1947619 3 0.1978 0.8363 0.000 0.004 0.928 0.068
#> SRR1947617 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947618 4 0.4462 0.7229 0.000 0.164 0.044 0.792
#> SRR1947616 3 0.6285 0.5267 0.000 0.284 0.624 0.092
#> SRR1947615 3 0.3123 0.7764 0.000 0.000 0.844 0.156
#> SRR1947614 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947613 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.3975 0.5429 0.000 0.240 0.000 0.760
#> SRR1947612 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947609 4 0.5897 0.6693 0.000 0.164 0.136 0.700
#> SRR1947608 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947607 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.3172 0.7068 0.000 0.160 0.000 0.840
#> SRR1947605 4 0.4888 0.3249 0.412 0.000 0.000 0.588
#> SRR1947603 3 0.7720 -0.0580 0.000 0.228 0.412 0.360
#> SRR1947602 3 0.3945 0.6893 0.000 0.004 0.780 0.216
#> SRR1947600 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947601 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947598 4 0.6245 0.5308 0.000 0.096 0.268 0.636
#> SRR1947599 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947597 4 0.4431 0.5992 0.000 0.304 0.000 0.696
#> SRR1947596 4 0.5265 0.6825 0.000 0.160 0.092 0.748
#> SRR1947595 4 0.6663 0.5910 0.000 0.144 0.244 0.612
#> SRR1947594 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947591 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947590 4 0.2216 0.6433 0.000 0.000 0.092 0.908
#> SRR1947588 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0376 0.8735 0.000 0.004 0.992 0.004
#> SRR1947586 2 0.1118 0.7886 0.000 0.964 0.000 0.036
#> SRR1947585 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947584 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.4152 0.7207 0.000 0.160 0.032 0.808
#> SRR1947582 4 0.4701 0.7189 0.000 0.164 0.056 0.780
#> SRR1947580 2 0.1302 0.7869 0.000 0.956 0.000 0.044
#> SRR1947581 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947578 4 0.7855 0.3668 0.000 0.300 0.300 0.400
#> SRR1947573 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947574 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947571 4 0.0000 0.6794 0.000 0.000 0.000 1.000
#> SRR1947577 4 0.4417 0.7233 0.000 0.160 0.044 0.796
#> SRR1947570 4 0.4978 0.3662 0.000 0.004 0.384 0.612
#> SRR1947569 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947566 2 0.2921 0.7775 0.000 0.860 0.000 0.140
#> SRR1947567 4 0.6783 0.4920 0.000 0.304 0.124 0.572
#> SRR1947568 1 0.6911 0.1634 0.560 0.304 0.000 0.136
#> SRR1947564 2 0.4522 0.7786 0.000 0.680 0.000 0.320
#> SRR1947563 3 0.0000 0.8744 0.000 0.000 1.000 0.000
#> SRR1947562 4 0.4431 0.5992 0.000 0.304 0.000 0.696
#> SRR1947565 3 0.0188 0.8746 0.000 0.004 0.996 0.000
#> SRR1947559 4 0.4431 0.5992 0.000 0.304 0.000 0.696
#> SRR1947560 3 0.1978 0.8387 0.000 0.068 0.928 0.004
#> SRR1947561 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947557 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.1940 0.8323 0.000 0.000 0.924 0.076
#> SRR1947556 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947553 4 0.3975 0.5429 0.000 0.240 0.000 0.760
#> SRR1947554 4 0.4761 0.4282 0.372 0.000 0.000 0.628
#> SRR1947555 3 0.7619 0.0289 0.000 0.208 0.436 0.356
#> SRR1947550 4 0.3172 0.7068 0.000 0.160 0.000 0.840
#> SRR1947552 4 0.3172 0.7068 0.000 0.160 0.000 0.840
#> SRR1947549 3 0.0188 0.8738 0.000 0.000 0.996 0.004
#> SRR1947551 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947548 4 0.0000 0.6794 0.000 0.000 0.000 1.000
#> SRR1947506 3 0.2831 0.7923 0.000 0.004 0.876 0.120
#> SRR1947507 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947503 4 0.3680 0.7122 0.004 0.160 0.008 0.828
#> SRR1947502 2 0.4356 0.7943 0.000 0.708 0.000 0.292
#> SRR1947501 4 0.7184 0.0935 0.000 0.144 0.364 0.492
#> SRR1947499 3 0.4608 0.5457 0.000 0.004 0.692 0.304
#> SRR1947498 3 0.1022 0.8681 0.000 0.032 0.968 0.000
#> SRR1947508 3 0.2814 0.7986 0.000 0.000 0.868 0.132
#> SRR1947505 4 0.6570 0.5077 0.000 0.116 0.280 0.604
#> SRR1947497 2 0.2814 0.8253 0.000 0.868 0.000 0.132
#> SRR1947496 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.3208 0.8149 0.000 0.848 0.004 0.148
#> SRR1947494 4 0.0000 0.6794 0.000 0.000 0.000 1.000
#> SRR1947493 3 0.5005 0.5988 0.020 0.004 0.712 0.264
#> SRR1947492 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.4431 0.5992 0.000 0.304 0.000 0.696
#> SRR1947491 4 0.5902 0.6692 0.000 0.160 0.140 0.700
#> SRR1947490 1 0.0000 0.9706 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.1716 0.8420 0.000 0.000 0.936 0.064
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.4318 0.571 0.000 0.000 0.688 0.292 0.020
#> SRR1947546 4 0.6744 0.300 0.000 0.332 0.268 0.400 0.000
#> SRR1947545 4 0.4256 0.282 0.436 0.000 0.000 0.564 0.000
#> SRR1947544 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.3949 0.587 0.000 0.332 0.000 0.668 0.000
#> SRR1947541 3 0.2377 0.773 0.000 0.000 0.872 0.128 0.000
#> SRR1947540 4 0.6781 0.236 0.000 0.176 0.332 0.476 0.016
#> SRR1947539 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947538 4 0.3274 0.658 0.000 0.220 0.000 0.780 0.000
#> SRR1947537 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947535 3 0.0703 0.835 0.000 0.000 0.976 0.000 0.024
#> SRR1947534 2 0.5820 0.575 0.100 0.524 0.000 0.376 0.000
#> SRR1947533 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947532 4 0.3242 0.679 0.000 0.216 0.000 0.784 0.000
#> SRR1947531 4 0.5218 0.288 0.000 0.060 0.336 0.604 0.000
#> SRR1947530 3 0.4425 0.186 0.000 0.000 0.544 0.452 0.004
#> SRR1947529 2 0.6177 0.469 0.000 0.464 0.136 0.400 0.000
#> SRR1947528 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947527 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947526 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947525 4 0.2852 0.639 0.000 0.172 0.000 0.828 0.000
#> SRR1947524 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947523 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947521 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947520 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947519 3 0.0865 0.835 0.000 0.000 0.972 0.004 0.024
#> SRR1947518 4 0.3274 0.658 0.000 0.220 0.000 0.780 0.000
#> SRR1947517 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947516 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947515 4 0.3242 0.679 0.000 0.216 0.000 0.784 0.000
#> SRR1947514 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947513 4 0.1965 0.714 0.000 0.000 0.096 0.904 0.000
#> SRR1947512 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947510 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947572 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947611 3 0.2233 0.824 0.000 0.004 0.892 0.000 0.104
#> SRR1947509 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947644 5 0.0703 0.836 0.000 0.000 0.024 0.000 0.976
#> SRR1947643 2 0.3242 0.740 0.000 0.784 0.000 0.216 0.000
#> SRR1947642 3 0.3368 0.737 0.000 0.000 0.820 0.156 0.024
#> SRR1947640 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947641 3 0.3012 0.758 0.000 0.000 0.852 0.124 0.024
#> SRR1947639 4 0.3949 0.587 0.000 0.332 0.000 0.668 0.000
#> SRR1947638 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947637 3 0.1732 0.832 0.000 0.000 0.920 0.000 0.080
#> SRR1947636 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.4045 0.380 0.000 0.000 0.356 0.644 0.000
#> SRR1947634 2 0.3966 0.672 0.000 0.664 0.000 0.336 0.000
#> SRR1947633 3 0.2179 0.822 0.000 0.000 0.888 0.000 0.112
#> SRR1947632 4 0.3949 0.587 0.000 0.332 0.000 0.668 0.000
#> SRR1947631 3 0.4193 0.628 0.000 0.000 0.720 0.256 0.024
#> SRR1947629 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947630 2 0.5258 0.701 0.000 0.664 0.000 0.232 0.104
#> SRR1947627 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947628 4 0.5288 0.567 0.000 0.244 0.100 0.656 0.000
#> SRR1947626 2 0.1341 0.688 0.000 0.944 0.000 0.056 0.000
#> SRR1947625 3 0.4410 0.694 0.000 0.000 0.764 0.124 0.112
#> SRR1947624 2 0.4844 0.756 0.000 0.740 0.008 0.148 0.104
#> SRR1947623 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.4269 0.547 0.000 0.684 0.016 0.300 0.000
#> SRR1947621 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947620 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947619 3 0.2139 0.795 0.000 0.052 0.916 0.032 0.000
#> SRR1947617 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947618 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947616 5 0.6220 0.636 0.000 0.180 0.056 0.116 0.648
#> SRR1947615 3 0.4575 0.476 0.000 0.000 0.648 0.328 0.024
#> SRR1947614 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947613 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3966 0.578 0.000 0.336 0.000 0.664 0.000
#> SRR1947612 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947609 4 0.3109 0.640 0.000 0.000 0.200 0.800 0.000
#> SRR1947608 3 0.0703 0.835 0.000 0.000 0.976 0.000 0.024
#> SRR1947606 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947607 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.1341 0.709 0.000 0.056 0.000 0.944 0.000
#> SRR1947605 4 0.4283 0.237 0.456 0.000 0.000 0.544 0.000
#> SRR1947603 2 0.6309 0.231 0.000 0.520 0.288 0.192 0.000
#> SRR1947602 3 0.3970 0.668 0.000 0.000 0.744 0.236 0.020
#> SRR1947600 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947601 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947598 4 0.5213 0.584 0.000 0.060 0.216 0.700 0.024
#> SRR1947599 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947597 4 0.2852 0.639 0.000 0.172 0.000 0.828 0.000
#> SRR1947596 4 0.3622 0.661 0.000 0.056 0.124 0.820 0.000
#> SRR1947595 4 0.3857 0.497 0.000 0.000 0.312 0.688 0.000
#> SRR1947594 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947590 4 0.5565 0.609 0.000 0.216 0.144 0.640 0.000
#> SRR1947588 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0162 0.841 0.000 0.000 0.996 0.004 0.000
#> SRR1947586 2 0.3242 0.740 0.000 0.784 0.000 0.216 0.000
#> SRR1947585 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947584 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.1522 0.726 0.000 0.012 0.044 0.944 0.000
#> SRR1947582 4 0.1608 0.723 0.000 0.000 0.072 0.928 0.000
#> SRR1947580 2 0.3305 0.740 0.000 0.776 0.000 0.224 0.000
#> SRR1947581 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947575 3 0.0703 0.835 0.000 0.000 0.976 0.000 0.024
#> SRR1947579 3 0.2074 0.826 0.000 0.000 0.896 0.000 0.104
#> SRR1947578 4 0.4923 0.546 0.000 0.088 0.212 0.700 0.000
#> SRR1947573 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947571 4 0.3242 0.679 0.000 0.216 0.000 0.784 0.000
#> SRR1947577 4 0.1341 0.728 0.000 0.000 0.056 0.944 0.000
#> SRR1947570 4 0.4752 0.284 0.000 0.000 0.412 0.568 0.020
#> SRR1947569 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947566 2 0.2179 0.726 0.000 0.888 0.000 0.112 0.000
#> SRR1947567 4 0.4595 0.595 0.000 0.172 0.088 0.740 0.000
#> SRR1947568 1 0.6014 0.222 0.576 0.172 0.000 0.252 0.000
#> SRR1947564 2 0.2230 0.741 0.000 0.884 0.000 0.116 0.000
#> SRR1947563 3 0.0703 0.835 0.000 0.000 0.976 0.000 0.024
#> SRR1947562 4 0.2852 0.639 0.000 0.172 0.000 0.828 0.000
#> SRR1947565 3 0.0000 0.841 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 4 0.2852 0.639 0.000 0.172 0.000 0.828 0.000
#> SRR1947560 3 0.5258 0.581 0.000 0.232 0.664 0.000 0.104
#> SRR1947561 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947557 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.2597 0.787 0.000 0.000 0.884 0.092 0.024
#> SRR1947556 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.3966 0.578 0.000 0.336 0.000 0.664 0.000
#> SRR1947554 4 0.4182 0.392 0.400 0.000 0.000 0.600 0.000
#> SRR1947555 2 0.6337 0.201 0.000 0.500 0.320 0.180 0.000
#> SRR1947550 4 0.1341 0.709 0.000 0.056 0.000 0.944 0.000
#> SRR1947552 4 0.1341 0.709 0.000 0.056 0.000 0.944 0.000
#> SRR1947549 3 0.0162 0.841 0.000 0.004 0.996 0.000 0.000
#> SRR1947551 5 0.0703 0.836 0.000 0.000 0.024 0.000 0.976
#> SRR1947548 4 0.3242 0.679 0.000 0.216 0.000 0.784 0.000
#> SRR1947506 3 0.0963 0.839 0.000 0.000 0.964 0.036 0.000
#> SRR1947507 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 4 0.1630 0.718 0.004 0.036 0.016 0.944 0.000
#> SRR1947502 2 0.1410 0.767 0.000 0.940 0.000 0.060 0.000
#> SRR1947501 4 0.6827 0.328 0.000 0.332 0.248 0.416 0.004
#> SRR1947499 3 0.4511 0.429 0.000 0.000 0.628 0.356 0.016
#> SRR1947498 5 0.2074 0.930 0.000 0.000 0.104 0.000 0.896
#> SRR1947508 3 0.4000 0.673 0.000 0.000 0.748 0.228 0.024
#> SRR1947505 4 0.4263 0.629 0.000 0.060 0.180 0.760 0.000
#> SRR1947497 2 0.3274 0.791 0.000 0.780 0.000 0.220 0.000
#> SRR1947496 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.3395 0.783 0.000 0.764 0.000 0.236 0.000
#> SRR1947494 4 0.3242 0.679 0.000 0.216 0.000 0.784 0.000
#> SRR1947493 3 0.5004 0.650 0.092 0.000 0.692 0.216 0.000
#> SRR1947492 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.2852 0.639 0.000 0.172 0.000 0.828 0.000
#> SRR1947491 4 0.2605 0.689 0.000 0.000 0.148 0.852 0.000
#> SRR1947490 1 0.0000 0.965 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.3152 0.764 0.000 0.000 0.840 0.136 0.024
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.5592 0.33206 0.000 0.008 0.488 0.404 0.004 0.096
#> SRR1947546 2 0.6213 0.00828 0.000 0.384 0.324 0.288 0.000 0.004
#> SRR1947545 4 0.2562 0.72330 0.172 0.000 0.000 0.828 0.000 0.000
#> SRR1947544 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.3955 0.49175 0.000 0.384 0.000 0.608 0.000 0.008
#> SRR1947541 3 0.2823 0.69359 0.000 0.000 0.796 0.204 0.000 0.000
#> SRR1947540 6 0.2003 0.82439 0.000 0.000 0.000 0.116 0.000 0.884
#> SRR1947539 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947538 6 0.2146 0.82005 0.000 0.116 0.000 0.004 0.000 0.880
#> SRR1947537 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947536 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947535 3 0.2163 0.81455 0.000 0.008 0.892 0.000 0.004 0.096
#> SRR1947534 2 0.5169 0.52459 0.136 0.604 0.000 0.260 0.000 0.000
#> SRR1947533 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947532 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947531 6 0.2048 0.82351 0.000 0.000 0.000 0.120 0.000 0.880
#> SRR1947530 4 0.5052 0.38776 0.000 0.008 0.264 0.632 0.000 0.096
#> SRR1947529 6 0.5529 0.65374 0.000 0.104 0.096 0.128 0.000 0.672
#> SRR1947528 3 0.1524 0.82402 0.000 0.008 0.932 0.000 0.000 0.060
#> SRR1947527 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947526 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947525 4 0.3468 0.56727 0.000 0.264 0.000 0.728 0.000 0.008
#> SRR1947524 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947523 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947521 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947520 2 0.2234 0.74046 0.000 0.872 0.004 0.124 0.000 0.000
#> SRR1947519 3 0.2418 0.81327 0.000 0.008 0.884 0.008 0.004 0.096
#> SRR1947518 6 0.2146 0.82005 0.000 0.116 0.000 0.004 0.000 0.880
#> SRR1947517 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947516 2 0.0260 0.72398 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1947515 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947514 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947513 4 0.0146 0.81071 0.000 0.000 0.004 0.996 0.000 0.000
#> SRR1947512 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947510 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947572 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947611 3 0.3808 0.81199 0.000 0.008 0.792 0.000 0.088 0.112
#> SRR1947509 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947644 5 0.0146 0.88031 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947643 2 0.5127 0.34732 0.000 0.588 0.000 0.112 0.000 0.300
#> SRR1947642 3 0.3666 0.77600 0.000 0.008 0.812 0.080 0.004 0.096
#> SRR1947640 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947641 3 0.2306 0.81440 0.000 0.008 0.888 0.004 0.004 0.096
#> SRR1947639 4 0.3945 0.49788 0.000 0.380 0.000 0.612 0.000 0.008
#> SRR1947638 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947637 3 0.1838 0.81752 0.000 0.000 0.916 0.000 0.068 0.016
#> SRR1947636 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947635 4 0.3607 0.32213 0.000 0.000 0.348 0.652 0.000 0.000
#> SRR1947634 2 0.3727 0.46401 0.000 0.612 0.000 0.388 0.000 0.000
#> SRR1947633 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947632 4 0.3955 0.49175 0.000 0.384 0.000 0.608 0.000 0.008
#> SRR1947631 3 0.5017 0.63258 0.000 0.008 0.660 0.232 0.004 0.096
#> SRR1947629 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947630 2 0.5252 0.52569 0.000 0.608 0.000 0.288 0.088 0.016
#> SRR1947627 3 0.1663 0.81662 0.000 0.000 0.912 0.000 0.088 0.000
#> SRR1947628 6 0.2250 0.84332 0.000 0.040 0.000 0.064 0.000 0.896
#> SRR1947626 2 0.3330 0.35988 0.000 0.716 0.000 0.000 0.000 0.284
#> SRR1947625 3 0.4188 0.72165 0.000 0.008 0.756 0.000 0.140 0.096
#> SRR1947624 2 0.4202 0.68916 0.000 0.780 0.008 0.108 0.088 0.016
#> SRR1947623 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 6 0.4066 0.44411 0.000 0.392 0.000 0.012 0.000 0.596
#> SRR1947621 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947620 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947619 3 0.0937 0.81266 0.000 0.000 0.960 0.040 0.000 0.000
#> SRR1947617 2 0.0260 0.72398 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1947618 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947616 6 0.1910 0.77969 0.000 0.000 0.000 0.000 0.108 0.892
#> SRR1947615 3 0.5529 0.36436 0.000 0.008 0.528 0.364 0.004 0.096
#> SRR1947614 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947613 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 6 0.2100 0.82292 0.000 0.112 0.000 0.004 0.000 0.884
#> SRR1947612 2 0.0405 0.72305 0.000 0.988 0.000 0.008 0.000 0.004
#> SRR1947609 4 0.0458 0.80819 0.000 0.000 0.016 0.984 0.000 0.000
#> SRR1947608 3 0.2163 0.81455 0.000 0.008 0.892 0.000 0.004 0.096
#> SRR1947606 3 0.2020 0.81590 0.000 0.008 0.896 0.000 0.000 0.096
#> SRR1947607 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947605 4 0.2762 0.70681 0.196 0.000 0.000 0.804 0.000 0.000
#> SRR1947603 2 0.4794 0.28663 0.000 0.596 0.344 0.056 0.000 0.004
#> SRR1947602 3 0.5472 0.49847 0.000 0.008 0.552 0.340 0.004 0.096
#> SRR1947600 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947601 2 0.0405 0.72305 0.000 0.988 0.000 0.008 0.000 0.004
#> SRR1947598 6 0.0748 0.79606 0.000 0.004 0.000 0.016 0.004 0.976
#> SRR1947599 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947597 4 0.3383 0.56295 0.000 0.268 0.000 0.728 0.000 0.004
#> SRR1947596 4 0.0146 0.81097 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1947595 4 0.2520 0.74370 0.000 0.008 0.108 0.872 0.000 0.012
#> SRR1947594 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947591 2 0.0260 0.72398 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1947590 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947588 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947586 6 0.4732 0.59765 0.000 0.220 0.000 0.112 0.000 0.668
#> SRR1947585 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947584 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947582 4 0.0260 0.80919 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947580 6 0.2212 0.82386 0.000 0.008 0.000 0.112 0.000 0.880
#> SRR1947581 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947575 3 0.2526 0.81476 0.000 0.024 0.876 0.000 0.004 0.096
#> SRR1947579 3 0.2112 0.81222 0.000 0.000 0.896 0.000 0.088 0.016
#> SRR1947578 6 0.2048 0.82351 0.000 0.000 0.000 0.120 0.000 0.880
#> SRR1947573 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947574 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947571 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947577 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947570 4 0.3391 0.72339 0.000 0.008 0.060 0.832 0.004 0.096
#> SRR1947569 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947566 6 0.2658 0.83897 0.000 0.100 0.000 0.036 0.000 0.864
#> SRR1947567 4 0.5108 0.42829 0.000 0.264 0.112 0.620 0.000 0.004
#> SRR1947568 1 0.5533 0.25114 0.568 0.264 0.000 0.164 0.000 0.004
#> SRR1947564 2 0.1049 0.71395 0.000 0.960 0.000 0.032 0.000 0.008
#> SRR1947563 3 0.2526 0.81476 0.000 0.024 0.876 0.000 0.004 0.096
#> SRR1947562 4 0.3360 0.56817 0.000 0.264 0.000 0.732 0.000 0.004
#> SRR1947565 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947559 4 0.3383 0.56295 0.000 0.268 0.000 0.728 0.000 0.004
#> SRR1947560 3 0.4795 0.59968 0.000 0.204 0.692 0.000 0.088 0.016
#> SRR1947561 2 0.0260 0.72398 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1947557 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.2163 0.81455 0.000 0.008 0.892 0.000 0.004 0.096
#> SRR1947556 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947553 6 0.2100 0.82292 0.000 0.112 0.000 0.004 0.000 0.884
#> SRR1947554 4 0.3390 0.58944 0.296 0.000 0.000 0.704 0.000 0.000
#> SRR1947555 2 0.4245 0.23751 0.000 0.604 0.376 0.016 0.000 0.004
#> SRR1947550 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947552 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947549 3 0.0000 0.82666 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947551 5 0.0146 0.88031 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947548 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947506 3 0.3675 0.79490 0.000 0.008 0.804 0.092 0.000 0.096
#> SRR1947507 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947503 4 0.0000 0.81185 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947502 2 0.0405 0.72305 0.000 0.988 0.000 0.008 0.000 0.004
#> SRR1947501 2 0.6300 -0.05384 0.000 0.384 0.284 0.324 0.000 0.008
#> SRR1947499 4 0.5266 0.23889 0.000 0.008 0.316 0.580 0.000 0.096
#> SRR1947498 5 0.1663 0.96657 0.000 0.000 0.088 0.000 0.912 0.000
#> SRR1947508 3 0.5017 0.63265 0.000 0.008 0.660 0.232 0.004 0.096
#> SRR1947505 6 0.0632 0.79874 0.000 0.000 0.000 0.024 0.000 0.976
#> SRR1947497 2 0.2092 0.74129 0.000 0.876 0.000 0.124 0.000 0.000
#> SRR1947496 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.2520 0.72812 0.000 0.844 0.004 0.152 0.000 0.000
#> SRR1947494 4 0.2146 0.76831 0.000 0.116 0.000 0.880 0.000 0.004
#> SRR1947493 3 0.5438 0.51977 0.004 0.008 0.564 0.328 0.000 0.096
#> SRR1947492 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.3360 0.56817 0.000 0.264 0.000 0.732 0.000 0.004
#> SRR1947491 4 0.2048 0.73382 0.000 0.000 0.120 0.880 0.000 0.000
#> SRR1947490 1 0.0000 0.96744 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.5187 0.58993 0.000 0.008 0.628 0.264 0.004 0.096
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 15148 rows and 152 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 0.452 0.834 0.879 0.3984 0.556 0.556
#> 3 3 0.635 0.696 0.847 0.5851 0.745 0.566
#> 4 4 0.635 0.653 0.808 0.1034 0.887 0.713
#> 5 5 0.567 0.544 0.738 0.0624 0.941 0.814
#> 6 6 0.607 0.561 0.709 0.0784 0.874 0.560
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
#> SRR1947547 2 0.7883 0.901 0.236 0.764
#> SRR1947546 1 0.0000 0.920 1.000 0.000
#> SRR1947545 1 0.0000 0.920 1.000 0.000
#> SRR1947544 1 0.0000 0.920 1.000 0.000
#> SRR1947542 1 0.0000 0.920 1.000 0.000
#> SRR1947541 2 0.7883 0.901 0.236 0.764
#> SRR1947540 1 0.7815 0.703 0.768 0.232
#> SRR1947539 2 0.7883 0.901 0.236 0.764
#> SRR1947538 1 0.7815 0.703 0.768 0.232
#> SRR1947537 2 0.7883 0.901 0.236 0.764
#> SRR1947536 2 0.8661 0.489 0.288 0.712
#> SRR1947535 2 0.7883 0.901 0.236 0.764
#> SRR1947534 1 0.0000 0.920 1.000 0.000
#> SRR1947533 1 0.0000 0.920 1.000 0.000
#> SRR1947532 1 0.0000 0.920 1.000 0.000
#> SRR1947531 1 0.7815 0.703 0.768 0.232
#> SRR1947530 2 0.7883 0.901 0.236 0.764
#> SRR1947529 1 0.0000 0.920 1.000 0.000
#> SRR1947528 2 0.7883 0.901 0.236 0.764
#> SRR1947527 1 0.0000 0.920 1.000 0.000
#> SRR1947526 1 0.0000 0.920 1.000 0.000
#> SRR1947525 1 0.0000 0.920 1.000 0.000
#> SRR1947524 2 0.8661 0.489 0.288 0.712
#> SRR1947523 1 0.0000 0.920 1.000 0.000
#> SRR1947521 2 0.7883 0.901 0.236 0.764
#> SRR1947520 1 0.0000 0.920 1.000 0.000
#> SRR1947519 2 0.7883 0.901 0.236 0.764
#> SRR1947518 1 0.7815 0.703 0.768 0.232
#> SRR1947517 2 0.7883 0.901 0.236 0.764
#> SRR1947516 1 0.0000 0.920 1.000 0.000
#> SRR1947515 1 0.0000 0.920 1.000 0.000
#> SRR1947514 1 0.0000 0.920 1.000 0.000
#> SRR1947513 1 0.0000 0.920 1.000 0.000
#> SRR1947512 1 0.7883 0.699 0.764 0.236
#> SRR1947511 1 0.0000 0.920 1.000 0.000
#> SRR1947510 2 0.7883 0.901 0.236 0.764
#> SRR1947572 1 0.0000 0.920 1.000 0.000
#> SRR1947611 2 0.7883 0.901 0.236 0.764
#> SRR1947509 2 0.7883 0.901 0.236 0.764
#> SRR1947644 2 0.8661 0.489 0.288 0.712
#> SRR1947643 1 0.7602 0.714 0.780 0.220
#> SRR1947642 2 0.8016 0.896 0.244 0.756
#> SRR1947640 1 0.0000 0.920 1.000 0.000
#> SRR1947641 1 0.9993 -0.455 0.516 0.484
#> SRR1947639 1 0.0000 0.920 1.000 0.000
#> SRR1947638 1 0.0000 0.920 1.000 0.000
#> SRR1947637 2 0.8813 0.846 0.300 0.700
#> SRR1947636 2 0.7883 0.901 0.236 0.764
#> SRR1947635 1 0.0000 0.920 1.000 0.000
#> SRR1947634 1 0.0000 0.920 1.000 0.000
#> SRR1947633 2 0.9000 0.828 0.316 0.684
#> SRR1947632 1 0.0000 0.920 1.000 0.000
#> SRR1947631 2 0.9044 0.823 0.320 0.680
#> SRR1947629 2 0.8661 0.489 0.288 0.712
#> SRR1947630 1 0.0000 0.920 1.000 0.000
#> SRR1947627 2 0.7883 0.901 0.236 0.764
#> SRR1947628 1 0.7815 0.703 0.768 0.232
#> SRR1947626 1 0.7815 0.703 0.768 0.232
#> SRR1947625 1 0.9988 -0.444 0.520 0.480
#> SRR1947624 1 0.0000 0.920 1.000 0.000
#> SRR1947623 1 0.0000 0.920 1.000 0.000
#> SRR1947622 1 0.7376 0.725 0.792 0.208
#> SRR1947621 1 0.0000 0.920 1.000 0.000
#> SRR1947620 1 0.0000 0.920 1.000 0.000
#> SRR1947619 2 0.7883 0.901 0.236 0.764
#> SRR1947617 1 0.0000 0.920 1.000 0.000
#> SRR1947618 1 0.0000 0.920 1.000 0.000
#> SRR1947616 1 0.7815 0.703 0.768 0.232
#> SRR1947615 1 0.9988 -0.444 0.520 0.480
#> SRR1947614 2 0.7883 0.901 0.236 0.764
#> SRR1947613 1 0.0000 0.920 1.000 0.000
#> SRR1947610 1 0.7815 0.703 0.768 0.232
#> SRR1947612 1 0.0000 0.920 1.000 0.000
#> SRR1947609 1 0.0000 0.920 1.000 0.000
#> SRR1947608 2 0.7883 0.901 0.236 0.764
#> SRR1947606 2 0.7883 0.901 0.236 0.764
#> SRR1947607 1 0.0000 0.920 1.000 0.000
#> SRR1947604 1 0.0000 0.920 1.000 0.000
#> SRR1947605 1 0.0000 0.920 1.000 0.000
#> SRR1947603 1 0.0000 0.920 1.000 0.000
#> SRR1947602 2 0.7883 0.901 0.236 0.764
#> SRR1947600 2 0.8661 0.489 0.288 0.712
#> SRR1947601 1 0.0000 0.920 1.000 0.000
#> SRR1947598 1 0.7815 0.703 0.768 0.232
#> SRR1947599 1 0.0000 0.920 1.000 0.000
#> SRR1947597 1 0.0000 0.920 1.000 0.000
#> SRR1947596 1 0.0000 0.920 1.000 0.000
#> SRR1947595 1 0.0000 0.920 1.000 0.000
#> SRR1947594 1 0.0376 0.917 0.996 0.004
#> SRR1947592 2 0.7883 0.901 0.236 0.764
#> SRR1947591 1 0.0000 0.920 1.000 0.000
#> SRR1947590 1 0.0000 0.920 1.000 0.000
#> SRR1947588 1 0.0376 0.917 0.996 0.004
#> SRR1947587 2 0.7883 0.901 0.236 0.764
#> SRR1947586 1 0.7815 0.703 0.768 0.232
#> SRR1947585 2 0.8661 0.489 0.288 0.712
#> SRR1947584 1 0.0376 0.917 0.996 0.004
#> SRR1947583 1 0.0000 0.920 1.000 0.000
#> SRR1947582 1 0.0000 0.920 1.000 0.000
#> SRR1947580 1 0.7815 0.703 0.768 0.232
#> SRR1947581 1 0.0376 0.917 0.996 0.004
#> SRR1947576 2 0.8327 0.880 0.264 0.736
#> SRR1947575 2 0.8016 0.895 0.244 0.756
#> SRR1947579 2 0.7883 0.901 0.236 0.764
#> SRR1947578 1 0.7815 0.703 0.768 0.232
#> SRR1947573 2 0.7883 0.901 0.236 0.764
#> SRR1947574 1 0.0000 0.920 1.000 0.000
#> SRR1947571 1 0.0000 0.920 1.000 0.000
#> SRR1947577 1 0.0000 0.920 1.000 0.000
#> SRR1947570 2 0.7883 0.901 0.236 0.764
#> SRR1947569 2 0.8661 0.489 0.288 0.712
#> SRR1947566 1 0.7815 0.703 0.768 0.232
#> SRR1947567 1 0.0000 0.920 1.000 0.000
#> SRR1947568 1 0.0000 0.920 1.000 0.000
#> SRR1947564 1 0.0000 0.920 1.000 0.000
#> SRR1947563 2 0.7883 0.901 0.236 0.764
#> SRR1947562 1 0.0000 0.920 1.000 0.000
#> SRR1947565 2 0.7883 0.901 0.236 0.764
#> SRR1947559 1 0.0000 0.920 1.000 0.000
#> SRR1947560 2 0.8016 0.896 0.244 0.756
#> SRR1947561 1 0.0000 0.920 1.000 0.000
#> SRR1947557 1 0.0376 0.917 0.996 0.004
#> SRR1947558 2 0.8955 0.833 0.312 0.688
#> SRR1947556 1 0.0000 0.920 1.000 0.000
#> SRR1947553 1 0.7815 0.703 0.768 0.232
#> SRR1947554 1 0.0000 0.920 1.000 0.000
#> SRR1947555 1 0.0000 0.920 1.000 0.000
#> SRR1947550 1 0.0000 0.920 1.000 0.000
#> SRR1947552 1 0.0000 0.920 1.000 0.000
#> SRR1947549 2 0.7883 0.901 0.236 0.764
#> SRR1947551 2 0.8661 0.489 0.288 0.712
#> SRR1947548 1 0.0000 0.920 1.000 0.000
#> SRR1947506 2 0.7883 0.901 0.236 0.764
#> SRR1947507 1 0.0376 0.917 0.996 0.004
#> SRR1947504 1 0.0000 0.920 1.000 0.000
#> SRR1947503 1 0.0000 0.920 1.000 0.000
#> SRR1947502 1 0.0000 0.920 1.000 0.000
#> SRR1947501 1 0.0000 0.920 1.000 0.000
#> SRR1947499 2 0.7883 0.901 0.236 0.764
#> SRR1947498 2 0.8661 0.489 0.288 0.712
#> SRR1947508 2 0.7883 0.901 0.236 0.764
#> SRR1947505 1 0.7815 0.703 0.768 0.232
#> SRR1947497 1 0.0000 0.920 1.000 0.000
#> SRR1947496 1 0.0376 0.917 0.996 0.004
#> SRR1947495 1 0.0000 0.920 1.000 0.000
#> SRR1947494 1 0.0000 0.920 1.000 0.000
#> SRR1947493 2 0.7883 0.901 0.236 0.764
#> SRR1947492 1 0.0376 0.917 0.996 0.004
#> SRR1947500 1 0.0000 0.920 1.000 0.000
#> SRR1947491 1 0.0000 0.920 1.000 0.000
#> SRR1947490 1 0.0000 0.920 1.000 0.000
#> SRR1947489 2 0.8955 0.833 0.312 0.688
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947546 1 0.6126 0.5762 0.600 0.400 0.000
#> SRR1947545 1 0.0475 0.7595 0.992 0.004 0.004
#> SRR1947544 1 0.1753 0.7238 0.952 0.000 0.048
#> SRR1947542 1 0.6204 0.4837 0.576 0.424 0.000
#> SRR1947541 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947540 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947539 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947538 2 0.5529 0.4569 0.296 0.704 0.000
#> SRR1947537 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947536 2 0.6111 0.2679 0.000 0.604 0.396
#> SRR1947535 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947534 1 0.4555 0.7102 0.800 0.200 0.000
#> SRR1947533 1 0.6204 0.5417 0.576 0.424 0.000
#> SRR1947532 1 0.3193 0.7738 0.896 0.100 0.004
#> SRR1947531 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947530 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947529 2 0.5497 0.3003 0.292 0.708 0.000
#> SRR1947528 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947527 2 0.6274 -0.2975 0.456 0.544 0.000
#> SRR1947526 1 0.6126 0.5762 0.600 0.400 0.000
#> SRR1947525 1 0.5835 0.6461 0.660 0.340 0.000
#> SRR1947524 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947523 1 0.4931 0.7218 0.768 0.232 0.000
#> SRR1947521 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947520 1 0.6282 0.5882 0.612 0.384 0.004
#> SRR1947519 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947518 2 0.5529 0.4569 0.296 0.704 0.000
#> SRR1947517 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947516 2 0.5948 0.0628 0.360 0.640 0.000
#> SRR1947515 1 0.3193 0.7738 0.896 0.100 0.004
#> SRR1947514 2 0.5948 0.0628 0.360 0.640 0.000
#> SRR1947513 1 0.0237 0.7612 0.996 0.000 0.004
#> SRR1947512 1 0.6126 0.0048 0.600 0.400 0.000
#> SRR1947511 1 0.6062 0.5903 0.616 0.384 0.000
#> SRR1947510 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947572 1 0.3272 0.7738 0.892 0.104 0.004
#> SRR1947611 3 0.1289 0.9683 0.000 0.032 0.968
#> SRR1947509 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947644 2 0.6111 0.2679 0.000 0.604 0.396
#> SRR1947643 2 0.2537 0.6195 0.080 0.920 0.000
#> SRR1947642 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947640 1 0.2860 0.7750 0.912 0.084 0.004
#> SRR1947641 3 0.1765 0.9489 0.004 0.040 0.956
#> SRR1947639 1 0.4974 0.7226 0.764 0.236 0.000
#> SRR1947638 1 0.0000 0.7620 1.000 0.000 0.000
#> SRR1947637 3 0.1289 0.9683 0.000 0.032 0.968
#> SRR1947636 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947635 1 0.5926 0.6127 0.644 0.356 0.000
#> SRR1947634 1 0.6062 0.5903 0.616 0.384 0.000
#> SRR1947633 3 0.1031 0.9693 0.000 0.024 0.976
#> SRR1947632 1 0.5733 0.6446 0.676 0.324 0.000
#> SRR1947631 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947629 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947630 1 0.6062 0.5903 0.616 0.384 0.000
#> SRR1947627 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947628 2 0.3816 0.5853 0.148 0.852 0.000
#> SRR1947626 2 0.0592 0.6292 0.012 0.988 0.000
#> SRR1947625 3 0.2945 0.8850 0.004 0.088 0.908
#> SRR1947624 1 0.6282 0.5882 0.612 0.384 0.004
#> SRR1947623 1 0.0661 0.7590 0.988 0.004 0.008
#> SRR1947622 2 0.2261 0.6289 0.068 0.932 0.000
#> SRR1947621 2 0.5948 0.0628 0.360 0.640 0.000
#> SRR1947620 1 0.0592 0.7578 0.988 0.000 0.012
#> SRR1947619 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947617 2 0.6192 -0.1744 0.420 0.580 0.000
#> SRR1947618 1 0.0592 0.7578 0.988 0.000 0.012
#> SRR1947616 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947615 3 0.0592 0.9782 0.012 0.000 0.988
#> SRR1947614 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947613 1 0.0475 0.7605 0.992 0.004 0.004
#> SRR1947610 2 0.1529 0.6342 0.040 0.960 0.000
#> SRR1947612 2 0.5948 0.0628 0.360 0.640 0.000
#> SRR1947609 1 0.3207 0.7740 0.904 0.084 0.012
#> SRR1947608 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947607 1 0.0829 0.7582 0.984 0.012 0.004
#> SRR1947604 1 0.3193 0.7738 0.896 0.100 0.004
#> SRR1947605 1 0.0661 0.7577 0.988 0.004 0.008
#> SRR1947603 1 0.6302 0.4058 0.520 0.480 0.000
#> SRR1947602 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947600 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947601 2 0.6111 -0.0274 0.396 0.604 0.000
#> SRR1947598 2 0.5560 0.4562 0.300 0.700 0.000
#> SRR1947599 1 0.2945 0.7751 0.908 0.088 0.004
#> SRR1947597 1 0.6126 0.5762 0.600 0.400 0.000
#> SRR1947596 1 0.3539 0.7725 0.888 0.100 0.012
#> SRR1947595 1 0.5360 0.7282 0.768 0.220 0.012
#> SRR1947594 1 0.0661 0.7585 0.988 0.008 0.004
#> SRR1947592 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947591 2 0.5948 0.0628 0.360 0.640 0.000
#> SRR1947590 1 0.4335 0.7610 0.864 0.100 0.036
#> SRR1947588 1 0.0661 0.7585 0.988 0.008 0.004
#> SRR1947587 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947586 2 0.0592 0.6292 0.012 0.988 0.000
#> SRR1947585 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947584 1 0.0661 0.7585 0.988 0.008 0.004
#> SRR1947583 1 0.4555 0.7375 0.800 0.200 0.000
#> SRR1947582 1 0.0237 0.7612 0.996 0.000 0.004
#> SRR1947580 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947581 1 0.0848 0.7564 0.984 0.008 0.008
#> SRR1947576 3 0.1289 0.9683 0.000 0.032 0.968
#> SRR1947575 3 0.1031 0.9693 0.000 0.024 0.976
#> SRR1947579 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947578 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947573 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947574 1 0.2625 0.7754 0.916 0.084 0.000
#> SRR1947571 1 0.2959 0.7734 0.900 0.100 0.000
#> SRR1947577 1 0.0237 0.7612 0.996 0.000 0.004
#> SRR1947570 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947569 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947566 2 0.1964 0.6344 0.056 0.944 0.000
#> SRR1947567 1 0.6140 0.5705 0.596 0.404 0.000
#> SRR1947568 1 0.6204 0.5634 0.576 0.424 0.000
#> SRR1947564 1 0.6225 0.5361 0.568 0.432 0.000
#> SRR1947563 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947562 1 0.2959 0.7734 0.900 0.100 0.000
#> SRR1947565 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947559 1 0.6079 0.5929 0.612 0.388 0.000
#> SRR1947560 3 0.1289 0.9683 0.000 0.032 0.968
#> SRR1947561 1 0.6215 0.5367 0.572 0.428 0.000
#> SRR1947557 1 0.0848 0.7564 0.984 0.008 0.008
#> SRR1947558 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947556 1 0.1182 0.7571 0.976 0.012 0.012
#> SRR1947553 2 0.1529 0.6342 0.040 0.960 0.000
#> SRR1947554 1 0.0237 0.7613 0.996 0.004 0.000
#> SRR1947555 1 0.6126 0.5762 0.600 0.400 0.000
#> SRR1947550 1 0.4629 0.7459 0.808 0.188 0.004
#> SRR1947552 1 0.3112 0.7744 0.900 0.096 0.004
#> SRR1947549 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947551 2 0.6111 0.2679 0.000 0.604 0.396
#> SRR1947548 1 0.3193 0.7738 0.896 0.100 0.004
#> SRR1947506 3 0.0000 0.9888 0.000 0.000 1.000
#> SRR1947507 1 0.0661 0.7585 0.988 0.008 0.004
#> SRR1947504 1 0.0661 0.7590 0.988 0.004 0.008
#> SRR1947503 1 0.1267 0.7664 0.972 0.024 0.004
#> SRR1947502 1 0.6168 0.5646 0.588 0.412 0.000
#> SRR1947501 1 0.6260 0.4272 0.552 0.448 0.000
#> SRR1947499 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947498 2 0.6140 0.2660 0.000 0.596 0.404
#> SRR1947508 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947505 2 0.4399 0.5571 0.188 0.812 0.000
#> SRR1947497 1 0.6062 0.5903 0.616 0.384 0.000
#> SRR1947496 1 0.0848 0.7564 0.984 0.008 0.008
#> SRR1947495 1 0.6062 0.5903 0.616 0.384 0.000
#> SRR1947494 1 0.3193 0.7738 0.896 0.100 0.004
#> SRR1947493 3 0.0424 0.9871 0.000 0.008 0.992
#> SRR1947492 1 0.0475 0.7605 0.992 0.004 0.004
#> SRR1947500 1 0.4974 0.7193 0.764 0.236 0.000
#> SRR1947491 1 0.2625 0.7754 0.916 0.084 0.000
#> SRR1947490 1 0.0475 0.7605 0.992 0.004 0.004
#> SRR1947489 3 0.0424 0.9824 0.008 0.000 0.992
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.0000 0.96206 0.000 0.000 1.000 0.000
#> SRR1947546 1 0.3356 0.63418 0.824 0.176 0.000 0.000
#> SRR1947545 1 0.1854 0.70304 0.940 0.000 0.012 0.048
#> SRR1947544 1 0.3818 0.66671 0.844 0.000 0.108 0.048
#> SRR1947542 1 0.3052 0.67243 0.860 0.136 0.000 0.004
#> SRR1947541 3 0.0000 0.96206 0.000 0.000 1.000 0.000
#> SRR1947540 4 0.5440 0.46759 0.384 0.020 0.000 0.596
#> SRR1947539 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947538 4 0.5866 0.47519 0.324 0.052 0.000 0.624
#> SRR1947537 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947536 4 0.5400 0.44406 0.000 0.020 0.372 0.608
#> SRR1947535 3 0.0895 0.95752 0.000 0.020 0.976 0.004
#> SRR1947534 2 0.8082 0.02434 0.348 0.392 0.008 0.252
#> SRR1947533 2 0.3479 0.72533 0.148 0.840 0.000 0.012
#> SRR1947532 1 0.1022 0.71070 0.968 0.032 0.000 0.000
#> SRR1947531 4 0.5440 0.46056 0.384 0.020 0.000 0.596
#> SRR1947530 3 0.1109 0.95633 0.000 0.004 0.968 0.028
#> SRR1947529 1 0.4655 0.29939 0.684 0.312 0.000 0.004
#> SRR1947528 3 0.0000 0.96206 0.000 0.000 1.000 0.000
#> SRR1947527 2 0.2021 0.71418 0.056 0.932 0.000 0.012
#> SRR1947526 2 0.5300 0.42374 0.408 0.580 0.000 0.012
#> SRR1947525 1 0.2675 0.68961 0.892 0.100 0.000 0.008
#> SRR1947524 4 0.4843 0.46516 0.000 0.000 0.396 0.604
#> SRR1947523 1 0.2342 0.69782 0.912 0.080 0.000 0.008
#> SRR1947521 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947520 1 0.4792 0.37678 0.680 0.312 0.000 0.008
#> SRR1947519 3 0.1004 0.95603 0.000 0.024 0.972 0.004
#> SRR1947518 4 0.6027 0.43444 0.124 0.192 0.000 0.684
#> SRR1947517 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947516 2 0.1474 0.72051 0.052 0.948 0.000 0.000
#> SRR1947515 1 0.0921 0.70920 0.972 0.028 0.000 0.000
#> SRR1947514 2 0.1661 0.71919 0.052 0.944 0.000 0.004
#> SRR1947513 1 0.4168 0.69981 0.852 0.064 0.036 0.048
#> SRR1947512 4 0.4957 0.00898 0.320 0.012 0.000 0.668
#> SRR1947511 2 0.5366 0.35607 0.440 0.548 0.000 0.012
#> SRR1947510 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947572 1 0.4422 0.56395 0.736 0.008 0.000 0.256
#> SRR1947611 3 0.2623 0.93096 0.000 0.064 0.908 0.028
#> SRR1947509 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947644 4 0.5773 0.47066 0.000 0.044 0.336 0.620
#> SRR1947643 1 0.5546 0.26271 0.664 0.292 0.000 0.044
#> SRR1947642 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947640 1 0.2124 0.70253 0.924 0.068 0.000 0.008
#> SRR1947641 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947639 1 0.3577 0.62656 0.832 0.156 0.000 0.012
#> SRR1947638 1 0.1557 0.69985 0.944 0.000 0.000 0.056
#> SRR1947637 3 0.3862 0.83998 0.000 0.152 0.824 0.024
#> SRR1947636 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947635 1 0.2198 0.69013 0.920 0.072 0.000 0.008
#> SRR1947634 1 0.5329 0.03316 0.568 0.420 0.000 0.012
#> SRR1947633 3 0.1474 0.94825 0.000 0.052 0.948 0.000
#> SRR1947632 1 0.2973 0.66509 0.856 0.144 0.000 0.000
#> SRR1947631 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947629 4 0.4843 0.46516 0.000 0.000 0.396 0.604
#> SRR1947630 1 0.5372 -0.06795 0.544 0.444 0.000 0.012
#> SRR1947627 3 0.1109 0.95633 0.000 0.004 0.968 0.028
#> SRR1947628 4 0.5440 0.46759 0.384 0.020 0.000 0.596
#> SRR1947626 4 0.6060 0.27553 0.044 0.440 0.000 0.516
#> SRR1947625 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947624 1 0.5764 0.12474 0.588 0.384 0.016 0.012
#> SRR1947623 1 0.4661 0.51635 0.652 0.000 0.000 0.348
#> SRR1947622 1 0.7442 -0.12885 0.504 0.284 0.000 0.212
#> SRR1947621 2 0.1474 0.72051 0.052 0.948 0.000 0.000
#> SRR1947620 1 0.3758 0.67061 0.848 0.000 0.104 0.048
#> SRR1947619 3 0.1398 0.93032 0.040 0.000 0.956 0.004
#> SRR1947617 2 0.1474 0.72051 0.052 0.948 0.000 0.000
#> SRR1947618 1 0.4125 0.68297 0.848 0.020 0.084 0.048
#> SRR1947616 4 0.5699 0.46027 0.380 0.032 0.000 0.588
#> SRR1947615 3 0.1396 0.93676 0.032 0.004 0.960 0.004
#> SRR1947614 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947613 1 0.4713 0.50613 0.640 0.000 0.000 0.360
#> SRR1947610 4 0.6508 0.40330 0.104 0.296 0.000 0.600
#> SRR1947612 2 0.1474 0.72051 0.052 0.948 0.000 0.000
#> SRR1947609 1 0.2926 0.69274 0.896 0.048 0.056 0.000
#> SRR1947608 3 0.1004 0.95603 0.000 0.024 0.972 0.004
#> SRR1947606 3 0.0000 0.96206 0.000 0.000 1.000 0.000
#> SRR1947607 1 0.6058 0.46705 0.604 0.060 0.000 0.336
#> SRR1947604 1 0.1792 0.70437 0.932 0.068 0.000 0.000
#> SRR1947605 1 0.3312 0.69087 0.876 0.000 0.072 0.052
#> SRR1947603 1 0.4356 0.46074 0.708 0.292 0.000 0.000
#> SRR1947602 3 0.1109 0.95633 0.000 0.004 0.968 0.028
#> SRR1947600 4 0.4843 0.46516 0.000 0.000 0.396 0.604
#> SRR1947601 2 0.4428 0.65494 0.276 0.720 0.000 0.004
#> SRR1947598 4 0.5440 0.46759 0.384 0.020 0.000 0.596
#> SRR1947599 1 0.2363 0.70469 0.920 0.056 0.024 0.000
#> SRR1947597 1 0.3982 0.58473 0.776 0.220 0.000 0.004
#> SRR1947596 1 0.1767 0.70880 0.944 0.012 0.044 0.000
#> SRR1947595 1 0.3928 0.66610 0.852 0.056 0.084 0.008
#> SRR1947594 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947592 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947591 2 0.1474 0.72051 0.052 0.948 0.000 0.000
#> SRR1947590 1 0.3048 0.66844 0.876 0.016 0.108 0.000
#> SRR1947588 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947587 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947586 4 0.6044 0.27723 0.044 0.428 0.000 0.528
#> SRR1947585 4 0.4843 0.46516 0.000 0.000 0.396 0.604
#> SRR1947584 1 0.4872 0.50662 0.640 0.004 0.000 0.356
#> SRR1947583 1 0.2198 0.70093 0.920 0.072 0.000 0.008
#> SRR1947582 1 0.4258 0.69799 0.848 0.064 0.040 0.048
#> SRR1947580 4 0.6538 0.45725 0.292 0.108 0.000 0.600
#> SRR1947581 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947576 3 0.3962 0.83746 0.000 0.152 0.820 0.028
#> SRR1947575 3 0.1209 0.95139 0.000 0.032 0.964 0.004
#> SRR1947579 3 0.2466 0.93470 0.000 0.056 0.916 0.028
#> SRR1947578 4 0.5626 0.46114 0.384 0.028 0.000 0.588
#> SRR1947573 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947574 1 0.0895 0.70935 0.976 0.004 0.000 0.020
#> SRR1947571 1 0.1209 0.70710 0.964 0.032 0.000 0.004
#> SRR1947577 1 0.3135 0.70908 0.896 0.044 0.012 0.048
#> SRR1947570 3 0.0000 0.96206 0.000 0.000 1.000 0.000
#> SRR1947569 4 0.4843 0.46516 0.000 0.000 0.396 0.604
#> SRR1947566 1 0.7073 -0.10515 0.504 0.132 0.000 0.364
#> SRR1947567 1 0.1867 0.69452 0.928 0.072 0.000 0.000
#> SRR1947568 2 0.5558 0.45249 0.324 0.640 0.036 0.000
#> SRR1947564 2 0.3972 0.70827 0.204 0.788 0.000 0.008
#> SRR1947563 3 0.0895 0.95752 0.000 0.020 0.976 0.004
#> SRR1947562 1 0.2216 0.69793 0.908 0.092 0.000 0.000
#> SRR1947565 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947559 1 0.3751 0.61162 0.800 0.196 0.000 0.004
#> SRR1947560 3 0.2699 0.92825 0.000 0.068 0.904 0.028
#> SRR1947561 2 0.3710 0.71349 0.192 0.804 0.000 0.004
#> SRR1947557 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947558 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947556 1 0.4608 0.54612 0.692 0.004 0.000 0.304
#> SRR1947553 4 0.6641 0.41012 0.124 0.276 0.000 0.600
#> SRR1947554 1 0.4605 0.52598 0.664 0.000 0.000 0.336
#> SRR1947555 1 0.4220 0.53235 0.748 0.248 0.004 0.000
#> SRR1947550 1 0.2198 0.70093 0.920 0.072 0.000 0.008
#> SRR1947552 1 0.2256 0.70572 0.924 0.056 0.020 0.000
#> SRR1947549 3 0.0188 0.96167 0.000 0.000 0.996 0.004
#> SRR1947551 4 0.5773 0.47066 0.000 0.044 0.336 0.620
#> SRR1947548 1 0.0921 0.70809 0.972 0.028 0.000 0.000
#> SRR1947506 3 0.0779 0.95962 0.000 0.004 0.980 0.016
#> SRR1947507 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947504 1 0.4781 0.52361 0.660 0.004 0.000 0.336
#> SRR1947503 1 0.1302 0.70386 0.956 0.000 0.000 0.044
#> SRR1947502 2 0.4053 0.69374 0.228 0.768 0.000 0.004
#> SRR1947501 1 0.3893 0.60469 0.796 0.196 0.008 0.000
#> SRR1947499 3 0.1109 0.95633 0.000 0.004 0.968 0.028
#> SRR1947498 4 0.5004 0.46700 0.000 0.004 0.392 0.604
#> SRR1947508 3 0.1256 0.95613 0.000 0.008 0.964 0.028
#> SRR1947505 4 0.5125 0.46446 0.388 0.008 0.000 0.604
#> SRR1947497 1 0.5408 -0.22166 0.500 0.488 0.000 0.012
#> SRR1947496 1 0.4889 0.50303 0.636 0.004 0.000 0.360
#> SRR1947495 2 0.5366 0.35562 0.440 0.548 0.000 0.012
#> SRR1947494 1 0.2816 0.69608 0.900 0.064 0.036 0.000
#> SRR1947493 3 0.1004 0.95757 0.000 0.004 0.972 0.024
#> SRR1947492 1 0.4713 0.50613 0.640 0.000 0.000 0.360
#> SRR1947500 1 0.2473 0.69872 0.908 0.080 0.000 0.012
#> SRR1947491 1 0.0804 0.70901 0.980 0.012 0.000 0.008
#> SRR1947490 1 0.4781 0.52718 0.660 0.004 0.000 0.336
#> SRR1947489 3 0.1443 0.94785 0.008 0.028 0.960 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.5509 0.79960 0.104 0.004 0.644 0.000 0.248
#> SRR1947546 4 0.3835 0.48850 0.008 0.260 0.000 0.732 0.000
#> SRR1947545 4 0.4037 0.33321 0.224 0.004 0.020 0.752 0.000
#> SRR1947544 4 0.4013 0.44388 0.084 0.004 0.108 0.804 0.000
#> SRR1947542 4 0.5125 0.52688 0.156 0.148 0.000 0.696 0.000
#> SRR1947541 3 0.5600 0.80111 0.104 0.004 0.628 0.000 0.264
#> SRR1947540 5 0.4446 0.48777 0.008 0.000 0.000 0.400 0.592
#> SRR1947539 3 0.4009 0.80425 0.004 0.000 0.684 0.000 0.312
#> SRR1947538 5 0.6804 0.42829 0.292 0.008 0.000 0.236 0.464
#> SRR1947537 3 0.5687 0.79388 0.104 0.000 0.580 0.000 0.316
#> SRR1947536 5 0.4909 0.40069 0.000 0.028 0.412 0.000 0.560
#> SRR1947535 3 0.5158 0.76100 0.036 0.004 0.568 0.000 0.392
#> SRR1947534 4 0.5841 0.07015 0.212 0.180 0.000 0.608 0.000
#> SRR1947533 2 0.4375 0.41181 0.004 0.576 0.000 0.420 0.000
#> SRR1947532 4 0.2806 0.55524 0.152 0.004 0.000 0.844 0.000
#> SRR1947531 5 0.4446 0.48777 0.008 0.000 0.000 0.400 0.592
#> SRR1947530 3 0.2629 0.72268 0.104 0.004 0.880 0.000 0.012
#> SRR1947529 4 0.5133 0.25521 0.000 0.384 0.012 0.580 0.024
#> SRR1947528 3 0.4915 0.79170 0.104 0.004 0.724 0.000 0.168
#> SRR1947527 2 0.2291 0.64751 0.036 0.908 0.000 0.056 0.000
#> SRR1947526 2 0.4434 0.31770 0.004 0.536 0.000 0.460 0.000
#> SRR1947525 4 0.3319 0.54884 0.160 0.020 0.000 0.820 0.000
#> SRR1947524 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947523 4 0.1704 0.61910 0.004 0.068 0.000 0.928 0.000
#> SRR1947521 3 0.0000 0.74254 0.000 0.000 1.000 0.000 0.000
#> SRR1947520 4 0.4623 0.31354 0.012 0.340 0.008 0.640 0.000
#> SRR1947519 3 0.5065 0.80524 0.036 0.016 0.664 0.000 0.284
#> SRR1947518 5 0.7262 0.44128 0.292 0.040 0.000 0.204 0.464
#> SRR1947517 3 0.0000 0.74254 0.000 0.000 1.000 0.000 0.000
#> SRR1947516 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947515 4 0.2763 0.55663 0.148 0.004 0.000 0.848 0.000
#> SRR1947514 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947513 4 0.0451 0.61855 0.008 0.004 0.000 0.988 0.000
#> SRR1947512 1 0.6863 0.10190 0.416 0.004 0.000 0.280 0.300
#> SRR1947511 2 0.4446 0.28085 0.004 0.520 0.000 0.476 0.000
#> SRR1947510 3 0.0162 0.74390 0.000 0.000 0.996 0.000 0.004
#> SRR1947572 4 0.3897 0.50045 0.204 0.028 0.000 0.768 0.000
#> SRR1947611 3 0.1538 0.73650 0.036 0.008 0.948 0.000 0.008
#> SRR1947509 3 0.0000 0.74254 0.000 0.000 1.000 0.000 0.000
#> SRR1947644 5 0.4310 0.43517 0.000 0.004 0.392 0.000 0.604
#> SRR1947643 4 0.6080 0.20499 0.008 0.360 0.012 0.548 0.072
#> SRR1947642 3 0.5361 0.80172 0.036 0.040 0.672 0.000 0.252
#> SRR1947640 4 0.0566 0.62263 0.004 0.012 0.000 0.984 0.000
#> SRR1947641 3 0.5685 0.78568 0.036 0.040 0.608 0.000 0.316
#> SRR1947639 4 0.3495 0.53990 0.160 0.028 0.000 0.812 0.000
#> SRR1947638 4 0.1750 0.59105 0.028 0.036 0.000 0.936 0.000
#> SRR1947637 3 0.5537 0.78472 0.036 0.068 0.684 0.000 0.212
#> SRR1947636 3 0.5640 0.79680 0.104 0.000 0.592 0.000 0.304
#> SRR1947635 4 0.3750 0.54311 0.000 0.232 0.012 0.756 0.000
#> SRR1947634 4 0.4415 -0.05731 0.004 0.444 0.000 0.552 0.000
#> SRR1947633 3 0.4435 0.78138 0.000 0.016 0.648 0.000 0.336
#> SRR1947632 4 0.5547 0.48520 0.148 0.208 0.000 0.644 0.000
#> SRR1947631 3 0.5579 0.79364 0.036 0.040 0.632 0.000 0.292
#> SRR1947629 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947630 4 0.4632 -0.06961 0.012 0.448 0.000 0.540 0.000
#> SRR1947627 3 0.2392 0.72616 0.104 0.004 0.888 0.000 0.004
#> SRR1947628 5 0.4768 0.49395 0.024 0.000 0.000 0.384 0.592
#> SRR1947626 5 0.4883 0.35018 0.016 0.464 0.000 0.004 0.516
#> SRR1947625 3 0.5918 0.73491 0.036 0.040 0.528 0.000 0.396
#> SRR1947624 4 0.4617 -0.00405 0.012 0.436 0.000 0.552 0.000
#> SRR1947623 4 0.4445 -0.11938 0.300 0.024 0.000 0.676 0.000
#> SRR1947622 4 0.8622 0.01756 0.160 0.272 0.012 0.360 0.196
#> SRR1947621 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947620 4 0.0671 0.61496 0.016 0.000 0.004 0.980 0.000
#> SRR1947619 3 0.5600 0.79705 0.096 0.000 0.588 0.000 0.316
#> SRR1947617 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947618 4 0.0867 0.61985 0.008 0.008 0.008 0.976 0.000
#> SRR1947616 5 0.4446 0.48777 0.008 0.000 0.000 0.400 0.592
#> SRR1947615 3 0.5815 0.79711 0.036 0.024 0.632 0.020 0.288
#> SRR1947614 3 0.0000 0.74254 0.000 0.000 1.000 0.000 0.000
#> SRR1947613 4 0.4238 -0.33393 0.368 0.004 0.000 0.628 0.000
#> SRR1947610 5 0.7556 0.46272 0.108 0.212 0.000 0.172 0.508
#> SRR1947612 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947609 4 0.0324 0.62015 0.004 0.004 0.000 0.992 0.000
#> SRR1947608 3 0.5158 0.76100 0.036 0.004 0.568 0.000 0.392
#> SRR1947606 3 0.5435 0.80073 0.104 0.004 0.656 0.000 0.236
#> SRR1947607 4 0.5091 -0.04765 0.244 0.084 0.000 0.672 0.000
#> SRR1947604 4 0.0290 0.62166 0.000 0.008 0.000 0.992 0.000
#> SRR1947605 4 0.4834 0.19399 0.252 0.004 0.052 0.692 0.000
#> SRR1947603 4 0.5048 0.22971 0.040 0.380 0.000 0.580 0.000
#> SRR1947602 3 0.2629 0.72268 0.104 0.004 0.880 0.000 0.012
#> SRR1947600 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947601 2 0.4474 0.49459 0.012 0.652 0.004 0.332 0.000
#> SRR1947598 5 0.4537 0.48523 0.012 0.000 0.000 0.396 0.592
#> SRR1947599 4 0.0162 0.61859 0.004 0.000 0.000 0.996 0.000
#> SRR1947597 4 0.6140 0.24719 0.152 0.320 0.000 0.528 0.000
#> SRR1947596 4 0.3484 0.54730 0.152 0.004 0.024 0.820 0.000
#> SRR1947595 4 0.1728 0.62097 0.004 0.036 0.020 0.940 0.000
#> SRR1947594 1 0.4166 0.78017 0.648 0.004 0.000 0.348 0.000
#> SRR1947592 3 0.4957 0.80070 0.044 0.000 0.624 0.000 0.332
#> SRR1947591 2 0.1341 0.66593 0.000 0.944 0.000 0.056 0.000
#> SRR1947590 4 0.4472 0.48420 0.160 0.004 0.076 0.760 0.000
#> SRR1947588 1 0.4288 0.79532 0.612 0.004 0.000 0.384 0.000
#> SRR1947587 3 0.5804 0.78077 0.104 0.000 0.544 0.000 0.352
#> SRR1947586 5 0.4881 0.35248 0.016 0.460 0.000 0.004 0.520
#> SRR1947585 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947584 1 0.4299 0.77760 0.608 0.004 0.000 0.388 0.000
#> SRR1947583 4 0.0510 0.62433 0.000 0.016 0.000 0.984 0.000
#> SRR1947582 4 0.0451 0.61855 0.008 0.004 0.000 0.988 0.000
#> SRR1947580 5 0.5674 0.49140 0.020 0.052 0.000 0.344 0.584
#> SRR1947581 1 0.4288 0.79532 0.612 0.004 0.000 0.384 0.000
#> SRR1947576 3 0.2775 0.69235 0.036 0.068 0.888 0.000 0.008
#> SRR1947575 3 0.5372 0.75798 0.036 0.012 0.560 0.000 0.392
#> SRR1947579 3 0.0000 0.74254 0.000 0.000 1.000 0.000 0.000
#> SRR1947578 5 0.4446 0.48777 0.008 0.000 0.000 0.400 0.592
#> SRR1947573 3 0.4161 0.77174 0.000 0.000 0.608 0.000 0.392
#> SRR1947574 4 0.1549 0.60195 0.016 0.040 0.000 0.944 0.000
#> SRR1947571 4 0.3771 0.53353 0.164 0.040 0.000 0.796 0.000
#> SRR1947577 4 0.0290 0.61663 0.008 0.000 0.000 0.992 0.000
#> SRR1947570 3 0.5509 0.79960 0.104 0.004 0.644 0.000 0.248
#> SRR1947569 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947566 4 0.6737 -0.24798 0.024 0.132 0.000 0.440 0.404
#> SRR1947567 4 0.4012 0.55061 0.012 0.216 0.012 0.760 0.000
#> SRR1947568 2 0.5708 0.12303 0.088 0.528 0.000 0.384 0.000
#> SRR1947564 2 0.4063 0.60444 0.012 0.708 0.000 0.280 0.000
#> SRR1947563 3 0.5158 0.76100 0.036 0.004 0.568 0.000 0.392
#> SRR1947562 4 0.3495 0.55926 0.152 0.032 0.000 0.816 0.000
#> SRR1947565 3 0.5672 0.79484 0.104 0.000 0.584 0.000 0.312
#> SRR1947559 4 0.5798 0.41130 0.156 0.236 0.000 0.608 0.000
#> SRR1947560 3 0.1412 0.73794 0.036 0.004 0.952 0.000 0.008
#> SRR1947561 2 0.4130 0.60066 0.012 0.696 0.000 0.292 0.000
#> SRR1947557 1 0.4299 0.79472 0.608 0.004 0.000 0.388 0.000
#> SRR1947558 3 0.5911 0.73837 0.036 0.040 0.532 0.000 0.392
#> SRR1947556 1 0.4449 0.12869 0.512 0.004 0.000 0.484 0.000
#> SRR1947553 5 0.7248 0.48013 0.244 0.056 0.000 0.192 0.508
#> SRR1947554 4 0.4010 0.17376 0.208 0.032 0.000 0.760 0.000
#> SRR1947555 4 0.3999 0.33707 0.000 0.344 0.000 0.656 0.000
#> SRR1947550 4 0.0404 0.62365 0.000 0.012 0.000 0.988 0.000
#> SRR1947552 4 0.0162 0.61859 0.004 0.000 0.000 0.996 0.000
#> SRR1947549 3 0.4940 0.77262 0.032 0.000 0.576 0.000 0.392
#> SRR1947551 5 0.3586 0.51108 0.000 0.000 0.264 0.000 0.736
#> SRR1947548 4 0.2929 0.55556 0.152 0.008 0.000 0.840 0.000
#> SRR1947506 3 0.4841 0.78763 0.104 0.004 0.732 0.000 0.160
#> SRR1947507 1 0.4166 0.77956 0.648 0.004 0.000 0.348 0.000
#> SRR1947504 1 0.5002 0.52170 0.612 0.044 0.000 0.344 0.000
#> SRR1947503 4 0.1211 0.60486 0.024 0.016 0.000 0.960 0.000
#> SRR1947502 2 0.4309 0.58445 0.016 0.676 0.000 0.308 0.000
#> SRR1947501 4 0.6433 0.27730 0.144 0.320 0.012 0.524 0.000
#> SRR1947499 3 0.2629 0.72268 0.104 0.004 0.880 0.000 0.012
#> SRR1947498 5 0.0290 0.50184 0.000 0.000 0.008 0.000 0.992
#> SRR1947508 3 0.1525 0.73880 0.036 0.004 0.948 0.000 0.012
#> SRR1947505 5 0.4537 0.48523 0.012 0.000 0.000 0.396 0.592
#> SRR1947497 4 0.4449 -0.20787 0.004 0.484 0.000 0.512 0.000
#> SRR1947496 1 0.4436 0.78561 0.596 0.008 0.000 0.396 0.000
#> SRR1947495 2 0.4437 0.31451 0.004 0.532 0.000 0.464 0.000
#> SRR1947494 4 0.0324 0.62015 0.004 0.004 0.000 0.992 0.000
#> SRR1947493 3 0.4642 0.78190 0.104 0.004 0.752 0.000 0.140
#> SRR1947492 1 0.4420 0.71740 0.548 0.004 0.000 0.448 0.000
#> SRR1947500 4 0.1484 0.62277 0.008 0.048 0.000 0.944 0.000
#> SRR1947491 4 0.1408 0.60578 0.008 0.044 0.000 0.948 0.000
#> SRR1947490 4 0.3790 0.01284 0.272 0.004 0.000 0.724 0.000
#> SRR1947489 3 0.6353 0.80415 0.108 0.024 0.584 0.004 0.280
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.2883 0.82592 0.000 0.000 0.212 0.000 0.000 0.788
#> SRR1947546 4 0.4097 -0.37731 0.000 0.492 0.000 0.500 0.008 0.000
#> SRR1947545 1 0.4902 0.29367 0.572 0.000 0.000 0.364 0.060 0.004
#> SRR1947544 4 0.4994 0.11067 0.412 0.000 0.000 0.524 0.060 0.004
#> SRR1947542 4 0.6075 0.19317 0.020 0.296 0.000 0.508 0.176 0.000
#> SRR1947541 6 0.3023 0.82074 0.000 0.000 0.232 0.000 0.000 0.768
#> SRR1947540 5 0.3756 0.53505 0.000 0.000 0.000 0.400 0.600 0.000
#> SRR1947539 3 0.3652 0.63202 0.000 0.000 0.768 0.000 0.044 0.188
#> SRR1947538 5 0.3834 0.56147 0.048 0.008 0.000 0.172 0.772 0.000
#> SRR1947537 6 0.3446 0.76616 0.000 0.000 0.308 0.000 0.000 0.692
#> SRR1947536 5 0.5539 0.35175 0.024 0.000 0.072 0.000 0.496 0.408
#> SRR1947535 3 0.3344 0.64522 0.000 0.000 0.804 0.000 0.044 0.152
#> SRR1947534 4 0.6552 0.12758 0.348 0.124 0.008 0.468 0.052 0.000
#> SRR1947533 2 0.3896 0.78242 0.000 0.744 0.000 0.204 0.052 0.000
#> SRR1947532 4 0.2668 0.64737 0.004 0.000 0.000 0.828 0.168 0.000
#> SRR1947531 5 0.3747 0.53684 0.000 0.000 0.000 0.396 0.604 0.000
#> SRR1947530 6 0.2048 0.78154 0.000 0.000 0.120 0.000 0.000 0.880
#> SRR1947529 4 0.5595 -0.26326 0.000 0.392 0.000 0.464 0.144 0.000
#> SRR1947528 6 0.2730 0.82642 0.000 0.000 0.192 0.000 0.000 0.808
#> SRR1947527 2 0.0653 0.68709 0.012 0.980 0.000 0.004 0.004 0.000
#> SRR1947526 2 0.3864 0.78216 0.000 0.744 0.000 0.208 0.048 0.000
#> SRR1947525 4 0.4945 0.60704 0.056 0.060 0.000 0.704 0.180 0.000
#> SRR1947524 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947523 4 0.3837 0.55004 0.044 0.180 0.000 0.768 0.008 0.000
#> SRR1947521 3 0.3754 0.59081 0.000 0.000 0.776 0.000 0.072 0.152
#> SRR1947520 2 0.4352 0.71074 0.000 0.668 0.000 0.280 0.052 0.000
#> SRR1947519 3 0.3076 0.59999 0.000 0.000 0.760 0.000 0.000 0.240
#> SRR1947518 5 0.3834 0.56147 0.048 0.008 0.000 0.172 0.772 0.000
#> SRR1947517 3 0.3754 0.59081 0.000 0.000 0.776 0.000 0.072 0.152
#> SRR1947516 2 0.0937 0.67910 0.000 0.960 0.000 0.000 0.040 0.000
#> SRR1947515 4 0.2668 0.64737 0.004 0.000 0.000 0.828 0.168 0.000
#> SRR1947514 2 0.0000 0.68788 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 4 0.2685 0.64198 0.072 0.000 0.000 0.868 0.060 0.000
#> SRR1947512 1 0.4971 0.02458 0.508 0.000 0.000 0.068 0.424 0.000
#> SRR1947511 2 0.3952 0.78169 0.000 0.736 0.000 0.212 0.052 0.000
#> SRR1947510 3 0.3754 0.59081 0.000 0.000 0.776 0.000 0.072 0.152
#> SRR1947572 4 0.5535 0.40145 0.252 0.004 0.000 0.572 0.172 0.000
#> SRR1947611 3 0.3641 0.59192 0.000 0.000 0.788 0.000 0.072 0.140
#> SRR1947509 3 0.3790 0.58886 0.000 0.000 0.772 0.000 0.072 0.156
#> SRR1947644 5 0.6211 0.40628 0.024 0.000 0.224 0.000 0.508 0.244
#> SRR1947643 4 0.5958 -0.20645 0.000 0.220 0.000 0.396 0.384 0.000
#> SRR1947642 3 0.3390 0.55827 0.000 0.000 0.704 0.000 0.000 0.296
#> SRR1947640 4 0.1075 0.67857 0.048 0.000 0.000 0.952 0.000 0.000
#> SRR1947641 3 0.3487 0.64508 0.000 0.000 0.788 0.000 0.044 0.168
#> SRR1947639 4 0.4867 0.58937 0.080 0.036 0.000 0.708 0.176 0.000
#> SRR1947638 4 0.2573 0.66347 0.132 0.004 0.000 0.856 0.008 0.000
#> SRR1947637 3 0.1088 0.62535 0.000 0.000 0.960 0.000 0.016 0.024
#> SRR1947636 6 0.3351 0.78488 0.000 0.000 0.288 0.000 0.000 0.712
#> SRR1947635 4 0.3547 0.30624 0.004 0.300 0.000 0.696 0.000 0.000
#> SRR1947634 2 0.3952 0.78169 0.000 0.736 0.000 0.212 0.052 0.000
#> SRR1947633 3 0.2597 0.65099 0.000 0.000 0.824 0.000 0.000 0.176
#> SRR1947632 4 0.5266 0.07771 0.000 0.344 0.000 0.544 0.112 0.000
#> SRR1947631 3 0.3050 0.60171 0.000 0.000 0.764 0.000 0.000 0.236
#> SRR1947629 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947630 2 0.4011 0.78012 0.000 0.732 0.000 0.212 0.056 0.000
#> SRR1947627 6 0.2300 0.78459 0.000 0.000 0.144 0.000 0.000 0.856
#> SRR1947628 5 0.3695 0.53344 0.000 0.000 0.000 0.376 0.624 0.000
#> SRR1947626 5 0.3672 0.46273 0.000 0.368 0.000 0.000 0.632 0.000
#> SRR1947625 3 0.3453 0.63364 0.000 0.000 0.792 0.000 0.044 0.164
#> SRR1947624 2 0.4038 0.77838 0.000 0.728 0.000 0.216 0.056 0.000
#> SRR1947623 1 0.3807 0.32889 0.628 0.000 0.000 0.368 0.004 0.000
#> SRR1947622 5 0.4700 0.41373 0.000 0.084 0.000 0.268 0.648 0.000
#> SRR1947621 2 0.0000 0.68788 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 4 0.3475 0.61143 0.140 0.000 0.000 0.800 0.060 0.000
#> SRR1947619 6 0.3659 0.69397 0.000 0.000 0.364 0.000 0.000 0.636
#> SRR1947617 2 0.0000 0.68788 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 4 0.2685 0.64198 0.072 0.000 0.000 0.868 0.060 0.000
#> SRR1947616 5 0.3881 0.53709 0.000 0.004 0.000 0.396 0.600 0.000
#> SRR1947615 3 0.5563 0.31354 0.000 0.000 0.576 0.120 0.016 0.288
#> SRR1947614 3 0.3754 0.59081 0.000 0.000 0.776 0.000 0.072 0.152
#> SRR1947613 1 0.2838 0.66117 0.808 0.000 0.000 0.188 0.004 0.000
#> SRR1947610 5 0.4587 0.53758 0.048 0.128 0.000 0.076 0.748 0.000
#> SRR1947612 2 0.0000 0.68788 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 4 0.2685 0.64198 0.072 0.000 0.000 0.868 0.060 0.000
#> SRR1947608 3 0.3344 0.64522 0.000 0.000 0.804 0.000 0.044 0.152
#> SRR1947606 6 0.2823 0.82741 0.000 0.000 0.204 0.000 0.000 0.796
#> SRR1947607 4 0.5451 0.02201 0.424 0.032 0.000 0.492 0.052 0.000
#> SRR1947604 4 0.0777 0.68135 0.004 0.000 0.000 0.972 0.024 0.000
#> SRR1947605 1 0.4870 0.32118 0.584 0.000 0.000 0.352 0.060 0.004
#> SRR1947603 2 0.4086 0.41381 0.000 0.528 0.000 0.464 0.008 0.000
#> SRR1947602 6 0.2048 0.78154 0.000 0.000 0.120 0.000 0.000 0.880
#> SRR1947600 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947601 2 0.3052 0.76237 0.000 0.780 0.000 0.216 0.004 0.000
#> SRR1947598 5 0.3872 0.53471 0.004 0.000 0.000 0.392 0.604 0.000
#> SRR1947599 4 0.2039 0.66609 0.076 0.000 0.000 0.904 0.020 0.000
#> SRR1947597 2 0.5610 0.47856 0.000 0.516 0.000 0.316 0.168 0.000
#> SRR1947596 4 0.4141 0.61421 0.092 0.000 0.000 0.740 0.168 0.000
#> SRR1947595 4 0.2030 0.67867 0.048 0.016 0.004 0.920 0.012 0.000
#> SRR1947594 1 0.0632 0.79525 0.976 0.000 0.000 0.024 0.000 0.000
#> SRR1947592 3 0.4371 0.10283 0.000 0.000 0.580 0.000 0.028 0.392
#> SRR1947591 2 0.1204 0.67287 0.000 0.944 0.000 0.000 0.056 0.000
#> SRR1947590 4 0.4520 0.58456 0.128 0.000 0.000 0.704 0.168 0.000
#> SRR1947588 1 0.0713 0.79702 0.972 0.000 0.000 0.028 0.000 0.000
#> SRR1947587 6 0.4438 0.68599 0.000 0.000 0.328 0.000 0.044 0.628
#> SRR1947586 5 0.3890 0.44438 0.000 0.400 0.000 0.004 0.596 0.000
#> SRR1947585 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947584 1 0.0865 0.79607 0.964 0.000 0.000 0.036 0.000 0.000
#> SRR1947583 4 0.1010 0.68170 0.036 0.004 0.000 0.960 0.000 0.000
#> SRR1947582 4 0.2685 0.64198 0.072 0.000 0.000 0.868 0.060 0.000
#> SRR1947580 5 0.4957 0.50191 0.000 0.148 0.000 0.204 0.648 0.000
#> SRR1947581 1 0.0713 0.79702 0.972 0.000 0.000 0.028 0.000 0.000
#> SRR1947576 3 0.3602 0.59065 0.000 0.000 0.792 0.000 0.072 0.136
#> SRR1947575 3 0.3344 0.64522 0.000 0.000 0.804 0.000 0.044 0.152
#> SRR1947579 3 0.3754 0.59081 0.000 0.000 0.776 0.000 0.072 0.152
#> SRR1947578 5 0.3756 0.53505 0.000 0.000 0.000 0.400 0.600 0.000
#> SRR1947573 3 0.3381 0.64354 0.000 0.000 0.800 0.000 0.044 0.156
#> SRR1947574 4 0.2760 0.67913 0.076 0.052 0.000 0.868 0.004 0.000
#> SRR1947571 4 0.4137 0.63494 0.048 0.020 0.000 0.756 0.176 0.000
#> SRR1947577 4 0.2740 0.64086 0.076 0.000 0.000 0.864 0.060 0.000
#> SRR1947570 6 0.4579 0.77469 0.020 0.000 0.212 0.060 0.000 0.708
#> SRR1947569 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947566 5 0.4750 0.48432 0.000 0.052 0.000 0.404 0.544 0.000
#> SRR1947567 4 0.4158 0.35060 0.012 0.280 0.000 0.688 0.020 0.000
#> SRR1947568 4 0.7163 0.28178 0.104 0.312 0.008 0.428 0.148 0.000
#> SRR1947564 2 0.4728 0.69019 0.000 0.680 0.000 0.176 0.144 0.000
#> SRR1947563 3 0.3344 0.64522 0.000 0.000 0.804 0.000 0.044 0.152
#> SRR1947562 4 0.3551 0.65107 0.012 0.040 0.000 0.804 0.144 0.000
#> SRR1947565 6 0.3446 0.76616 0.000 0.000 0.308 0.000 0.000 0.692
#> SRR1947559 4 0.5814 -0.07368 0.012 0.376 0.004 0.492 0.116 0.000
#> SRR1947560 3 0.3602 0.59065 0.000 0.000 0.792 0.000 0.072 0.136
#> SRR1947561 2 0.2805 0.77705 0.000 0.812 0.000 0.184 0.004 0.000
#> SRR1947557 1 0.0858 0.79478 0.968 0.000 0.000 0.028 0.000 0.004
#> SRR1947558 3 0.3307 0.64423 0.000 0.000 0.808 0.000 0.044 0.148
#> SRR1947556 1 0.4340 0.55085 0.720 0.000 0.000 0.176 0.104 0.000
#> SRR1947553 5 0.3897 0.56235 0.048 0.012 0.000 0.168 0.772 0.000
#> SRR1947554 4 0.4107 0.11142 0.452 0.004 0.000 0.540 0.004 0.000
#> SRR1947555 2 0.3860 0.42141 0.000 0.528 0.000 0.472 0.000 0.000
#> SRR1947550 4 0.0000 0.68086 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947552 4 0.1745 0.67237 0.068 0.000 0.000 0.920 0.012 0.000
#> SRR1947549 3 0.4234 0.42713 0.000 0.000 0.676 0.000 0.044 0.280
#> SRR1947551 5 0.6054 0.43516 0.024 0.000 0.308 0.000 0.512 0.156
#> SRR1947548 4 0.3003 0.64378 0.016 0.000 0.000 0.812 0.172 0.000
#> SRR1947506 6 0.2738 0.82236 0.004 0.000 0.176 0.000 0.000 0.820
#> SRR1947507 1 0.0777 0.79509 0.972 0.000 0.000 0.024 0.000 0.004
#> SRR1947504 1 0.2452 0.74780 0.884 0.004 0.000 0.084 0.028 0.000
#> SRR1947503 4 0.2573 0.66150 0.132 0.004 0.000 0.856 0.008 0.000
#> SRR1947502 2 0.4075 0.74762 0.000 0.740 0.000 0.184 0.076 0.000
#> SRR1947501 2 0.5334 0.44289 0.000 0.512 0.000 0.376 0.112 0.000
#> SRR1947499 6 0.2048 0.78154 0.000 0.000 0.120 0.000 0.000 0.880
#> SRR1947498 5 0.6245 0.36838 0.024 0.000 0.212 0.000 0.496 0.268
#> SRR1947508 3 0.3833 0.43255 0.000 0.000 0.556 0.000 0.000 0.444
#> SRR1947505 5 0.4458 0.51428 0.040 0.000 0.000 0.352 0.608 0.000
#> SRR1947497 2 0.3952 0.78169 0.000 0.736 0.000 0.212 0.052 0.000
#> SRR1947496 1 0.0790 0.79673 0.968 0.000 0.000 0.032 0.000 0.000
#> SRR1947495 2 0.3952 0.78169 0.000 0.736 0.000 0.212 0.052 0.000
#> SRR1947494 4 0.1524 0.67779 0.060 0.000 0.000 0.932 0.008 0.000
#> SRR1947493 6 0.4354 0.72538 0.028 0.000 0.144 0.072 0.000 0.756
#> SRR1947492 1 0.1444 0.77737 0.928 0.000 0.000 0.072 0.000 0.000
#> SRR1947500 4 0.2393 0.63784 0.020 0.092 0.000 0.884 0.004 0.000
#> SRR1947491 4 0.2856 0.66779 0.068 0.076 0.000 0.856 0.000 0.000
#> SRR1947490 4 0.3998 -0.00667 0.492 0.000 0.000 0.504 0.004 0.000
#> SRR1947489 6 0.5635 0.17875 0.000 0.000 0.420 0.148 0.000 0.432
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 15148 rows and 152 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 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 0.853 0.913 0.964 0.4933 0.505 0.505
#> 3 3 0.957 0.938 0.975 0.3563 0.698 0.469
#> 4 4 0.743 0.467 0.741 0.1079 0.802 0.511
#> 5 5 0.837 0.828 0.905 0.0661 0.861 0.557
#> 6 6 0.723 0.667 0.813 0.0471 0.899 0.579
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
#> SRR1947547 1 0.0000 0.951 1.000 0.000
#> SRR1947546 2 0.0000 0.968 0.000 1.000
#> SRR1947545 1 0.0000 0.951 1.000 0.000
#> SRR1947544 1 0.0000 0.951 1.000 0.000
#> SRR1947542 2 0.0000 0.968 0.000 1.000
#> SRR1947541 1 0.0000 0.951 1.000 0.000
#> SRR1947540 2 0.0000 0.968 0.000 1.000
#> SRR1947539 2 0.0000 0.968 0.000 1.000
#> SRR1947538 1 0.0000 0.951 1.000 0.000
#> SRR1947537 1 0.8443 0.647 0.728 0.272
#> SRR1947536 1 0.9963 0.117 0.536 0.464
#> SRR1947535 2 0.0000 0.968 0.000 1.000
#> SRR1947534 1 0.0000 0.951 1.000 0.000
#> SRR1947533 2 0.0000 0.968 0.000 1.000
#> SRR1947532 1 0.0000 0.951 1.000 0.000
#> SRR1947531 2 0.0000 0.968 0.000 1.000
#> SRR1947530 1 0.0000 0.951 1.000 0.000
#> SRR1947529 2 0.0000 0.968 0.000 1.000
#> SRR1947528 1 0.0000 0.951 1.000 0.000
#> SRR1947527 2 0.0376 0.965 0.004 0.996
#> SRR1947526 2 0.0000 0.968 0.000 1.000
#> SRR1947525 1 0.8608 0.626 0.716 0.284
#> SRR1947524 2 0.0000 0.968 0.000 1.000
#> SRR1947523 2 0.0000 0.968 0.000 1.000
#> SRR1947521 2 0.0000 0.968 0.000 1.000
#> SRR1947520 2 0.0000 0.968 0.000 1.000
#> SRR1947519 2 0.0000 0.968 0.000 1.000
#> SRR1947518 1 0.0000 0.951 1.000 0.000
#> SRR1947517 2 0.0000 0.968 0.000 1.000
#> SRR1947516 2 0.0000 0.968 0.000 1.000
#> SRR1947515 1 0.0000 0.951 1.000 0.000
#> SRR1947514 2 0.0000 0.968 0.000 1.000
#> SRR1947513 1 0.0000 0.951 1.000 0.000
#> SRR1947512 1 0.0000 0.951 1.000 0.000
#> SRR1947511 2 0.0000 0.968 0.000 1.000
#> SRR1947510 2 0.0000 0.968 0.000 1.000
#> SRR1947572 1 0.0000 0.951 1.000 0.000
#> SRR1947611 2 0.0000 0.968 0.000 1.000
#> SRR1947509 2 0.7453 0.725 0.212 0.788
#> SRR1947644 2 0.0000 0.968 0.000 1.000
#> SRR1947643 2 0.0000 0.968 0.000 1.000
#> SRR1947642 2 0.0000 0.968 0.000 1.000
#> SRR1947640 1 0.0376 0.948 0.996 0.004
#> SRR1947641 2 0.0000 0.968 0.000 1.000
#> SRR1947639 1 0.2043 0.925 0.968 0.032
#> SRR1947638 1 0.0000 0.951 1.000 0.000
#> SRR1947637 2 0.0000 0.968 0.000 1.000
#> SRR1947636 1 0.8327 0.659 0.736 0.264
#> SRR1947635 2 0.0000 0.968 0.000 1.000
#> SRR1947634 2 0.0000 0.968 0.000 1.000
#> SRR1947633 2 0.0000 0.968 0.000 1.000
#> SRR1947632 2 0.0000 0.968 0.000 1.000
#> SRR1947631 2 0.0000 0.968 0.000 1.000
#> SRR1947629 2 0.0000 0.968 0.000 1.000
#> SRR1947630 2 0.0000 0.968 0.000 1.000
#> SRR1947627 1 0.1414 0.935 0.980 0.020
#> SRR1947628 2 0.0000 0.968 0.000 1.000
#> SRR1947626 2 0.0000 0.968 0.000 1.000
#> SRR1947625 2 0.0000 0.968 0.000 1.000
#> SRR1947624 2 0.0000 0.968 0.000 1.000
#> SRR1947623 1 0.0000 0.951 1.000 0.000
#> SRR1947622 2 0.0000 0.968 0.000 1.000
#> SRR1947621 2 0.0000 0.968 0.000 1.000
#> SRR1947620 1 0.0000 0.951 1.000 0.000
#> SRR1947619 1 0.9491 0.458 0.632 0.368
#> SRR1947617 2 0.0000 0.968 0.000 1.000
#> SRR1947618 1 0.0000 0.951 1.000 0.000
#> SRR1947616 2 0.0000 0.968 0.000 1.000
#> SRR1947615 1 0.8763 0.607 0.704 0.296
#> SRR1947614 2 0.0000 0.968 0.000 1.000
#> SRR1947613 1 0.0000 0.951 1.000 0.000
#> SRR1947610 2 0.7950 0.683 0.240 0.760
#> SRR1947612 2 0.0000 0.968 0.000 1.000
#> SRR1947609 1 0.0000 0.951 1.000 0.000
#> SRR1947608 2 0.0000 0.968 0.000 1.000
#> SRR1947606 1 0.0000 0.951 1.000 0.000
#> SRR1947607 1 0.0000 0.951 1.000 0.000
#> SRR1947604 1 0.0000 0.951 1.000 0.000
#> SRR1947605 1 0.0000 0.951 1.000 0.000
#> SRR1947603 2 0.0000 0.968 0.000 1.000
#> SRR1947602 1 0.0000 0.951 1.000 0.000
#> SRR1947600 2 0.0000 0.968 0.000 1.000
#> SRR1947601 2 0.0000 0.968 0.000 1.000
#> SRR1947598 2 0.0000 0.968 0.000 1.000
#> SRR1947599 1 0.0000 0.951 1.000 0.000
#> SRR1947597 2 0.0000 0.968 0.000 1.000
#> SRR1947596 1 0.0000 0.951 1.000 0.000
#> SRR1947595 2 0.8327 0.624 0.264 0.736
#> SRR1947594 1 0.0000 0.951 1.000 0.000
#> SRR1947592 2 0.8861 0.541 0.304 0.696
#> SRR1947591 2 0.0000 0.968 0.000 1.000
#> SRR1947590 1 0.0000 0.951 1.000 0.000
#> SRR1947588 1 0.0000 0.951 1.000 0.000
#> SRR1947587 1 0.5059 0.851 0.888 0.112
#> SRR1947586 2 0.0000 0.968 0.000 1.000
#> SRR1947585 2 0.0000 0.968 0.000 1.000
#> SRR1947584 1 0.0000 0.951 1.000 0.000
#> SRR1947583 2 0.7745 0.698 0.228 0.772
#> SRR1947582 1 0.0000 0.951 1.000 0.000
#> SRR1947580 2 0.0000 0.968 0.000 1.000
#> SRR1947581 1 0.0000 0.951 1.000 0.000
#> SRR1947576 2 0.0000 0.968 0.000 1.000
#> SRR1947575 2 0.0000 0.968 0.000 1.000
#> SRR1947579 2 0.0000 0.968 0.000 1.000
#> SRR1947578 2 0.0000 0.968 0.000 1.000
#> SRR1947573 2 0.0000 0.968 0.000 1.000
#> SRR1947574 1 0.0000 0.951 1.000 0.000
#> SRR1947571 1 0.0000 0.951 1.000 0.000
#> SRR1947577 1 0.0000 0.951 1.000 0.000
#> SRR1947570 1 0.0000 0.951 1.000 0.000
#> SRR1947569 2 0.0672 0.962 0.008 0.992
#> SRR1947566 2 0.0000 0.968 0.000 1.000
#> SRR1947567 2 0.0000 0.968 0.000 1.000
#> SRR1947568 1 0.0000 0.951 1.000 0.000
#> SRR1947564 2 0.0000 0.968 0.000 1.000
#> SRR1947563 2 0.0000 0.968 0.000 1.000
#> SRR1947562 2 0.9608 0.339 0.384 0.616
#> SRR1947565 1 0.9248 0.520 0.660 0.340
#> SRR1947559 2 0.0000 0.968 0.000 1.000
#> SRR1947560 2 0.0000 0.968 0.000 1.000
#> SRR1947561 2 0.0000 0.968 0.000 1.000
#> SRR1947557 1 0.0000 0.951 1.000 0.000
#> SRR1947558 2 0.0000 0.968 0.000 1.000
#> SRR1947556 1 0.0000 0.951 1.000 0.000
#> SRR1947553 2 0.6048 0.815 0.148 0.852
#> SRR1947554 1 0.0000 0.951 1.000 0.000
#> SRR1947555 2 0.0000 0.968 0.000 1.000
#> SRR1947550 1 0.9775 0.345 0.588 0.412
#> SRR1947552 1 0.0000 0.951 1.000 0.000
#> SRR1947549 2 0.4161 0.886 0.084 0.916
#> SRR1947551 2 0.0000 0.968 0.000 1.000
#> SRR1947548 1 0.6801 0.774 0.820 0.180
#> SRR1947506 1 0.0000 0.951 1.000 0.000
#> SRR1947507 1 0.0000 0.951 1.000 0.000
#> SRR1947504 1 0.0000 0.951 1.000 0.000
#> SRR1947503 1 0.0000 0.951 1.000 0.000
#> SRR1947502 2 0.0000 0.968 0.000 1.000
#> SRR1947501 2 0.0000 0.968 0.000 1.000
#> SRR1947499 1 0.0000 0.951 1.000 0.000
#> SRR1947498 2 0.0000 0.968 0.000 1.000
#> SRR1947508 2 0.9129 0.516 0.328 0.672
#> SRR1947505 2 0.0000 0.968 0.000 1.000
#> SRR1947497 2 0.0000 0.968 0.000 1.000
#> SRR1947496 1 0.0000 0.951 1.000 0.000
#> SRR1947495 2 0.0000 0.968 0.000 1.000
#> SRR1947494 1 0.0000 0.951 1.000 0.000
#> SRR1947493 1 0.0000 0.951 1.000 0.000
#> SRR1947492 1 0.0000 0.951 1.000 0.000
#> SRR1947500 2 0.0376 0.965 0.004 0.996
#> SRR1947491 2 0.8555 0.613 0.280 0.720
#> SRR1947490 1 0.0000 0.951 1.000 0.000
#> SRR1947489 1 0.0000 0.951 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.3941 0.8009 0.844 0.000 0.156
#> SRR1947546 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947541 3 0.2165 0.9204 0.064 0.000 0.936
#> SRR1947540 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947539 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947538 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947537 3 0.3340 0.8587 0.120 0.000 0.880
#> SRR1947536 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947535 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947534 2 0.5835 0.4783 0.340 0.660 0.000
#> SRR1947533 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947532 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947531 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947530 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947529 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947528 3 0.0237 0.9759 0.004 0.000 0.996
#> SRR1947527 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947525 2 0.0892 0.9552 0.020 0.980 0.000
#> SRR1947524 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947523 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947521 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947518 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947517 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947515 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947514 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947572 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947611 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947509 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947644 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947640 2 0.1163 0.9479 0.028 0.972 0.000
#> SRR1947641 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947639 2 0.6126 0.3327 0.400 0.600 0.000
#> SRR1947638 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947637 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947632 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947627 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947628 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947624 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947623 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947622 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947619 3 0.3879 0.8177 0.152 0.000 0.848
#> SRR1947617 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947616 2 0.0424 0.9653 0.000 0.992 0.008
#> SRR1947615 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947614 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947609 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947604 1 0.2796 0.8799 0.908 0.092 0.000
#> SRR1947605 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947602 1 0.3192 0.8568 0.888 0.000 0.112
#> SRR1947600 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947598 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947599 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947597 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947596 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947595 2 0.5397 0.6077 0.280 0.720 0.000
#> SRR1947594 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947590 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947588 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947583 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947582 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947578 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947573 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947574 1 0.6235 0.2163 0.564 0.436 0.000
#> SRR1947571 1 0.5678 0.5430 0.684 0.316 0.000
#> SRR1947577 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947570 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947569 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947567 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947568 2 0.5835 0.4841 0.340 0.660 0.000
#> SRR1947564 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947560 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947554 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947550 2 0.1753 0.9281 0.048 0.952 0.000
#> SRR1947552 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947549 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947551 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947548 1 0.5327 0.6214 0.728 0.272 0.000
#> SRR1947506 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947507 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947503 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947499 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947508 3 0.0000 0.9793 0.000 0.000 1.000
#> SRR1947505 3 0.6308 0.0363 0.000 0.492 0.508
#> SRR1947497 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947494 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947493 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947491 2 0.0000 0.9721 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.9691 1.000 0.000 0.000
#> SRR1947489 3 0.2959 0.8820 0.100 0.000 0.900
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.5000 -0.6686 0.496 0.000 0.504 0.000
#> SRR1947546 2 0.5478 0.2898 0.444 0.540 0.000 0.016
#> SRR1947545 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947544 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947542 1 0.6316 -0.3116 0.476 0.472 0.004 0.048
#> SRR1947541 3 0.7295 0.5213 0.188 0.000 0.524 0.288
#> SRR1947540 4 0.4994 0.0126 0.000 0.480 0.000 0.520
#> SRR1947539 3 0.4994 0.6087 0.000 0.000 0.520 0.480
#> SRR1947538 4 0.5604 0.0180 0.020 0.000 0.476 0.504
#> SRR1947537 3 0.4999 0.3889 0.492 0.000 0.508 0.000
#> SRR1947536 4 0.1637 0.3583 0.000 0.000 0.060 0.940
#> SRR1947535 1 0.6277 -0.4836 0.476 0.000 0.468 0.056
#> SRR1947534 2 0.2589 0.7965 0.044 0.912 0.044 0.000
#> SRR1947533 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947532 1 0.0927 0.3576 0.976 0.000 0.016 0.008
#> SRR1947531 4 0.4994 0.0130 0.000 0.480 0.000 0.520
#> SRR1947530 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947529 2 0.0817 0.8620 0.000 0.976 0.000 0.024
#> SRR1947528 3 0.5220 0.5790 0.008 0.000 0.568 0.424
#> SRR1947527 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947525 2 0.3751 0.6561 0.196 0.800 0.004 0.000
#> SRR1947524 4 0.0469 0.4089 0.000 0.000 0.012 0.988
#> SRR1947523 2 0.5677 0.2383 0.476 0.504 0.004 0.016
#> SRR1947521 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947520 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947519 1 0.6277 -0.4836 0.476 0.000 0.468 0.056
#> SRR1947518 4 0.5938 -0.0153 0.036 0.000 0.476 0.488
#> SRR1947517 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947516 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947515 1 0.1610 0.3349 0.952 0.000 0.016 0.032
#> SRR1947514 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947512 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947511 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947510 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947572 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947611 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947509 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947644 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947643 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947642 4 0.5189 -0.4001 0.012 0.000 0.372 0.616
#> SRR1947640 2 0.4630 0.6200 0.196 0.768 0.036 0.000
#> SRR1947641 4 0.4888 -0.4938 0.000 0.000 0.412 0.588
#> SRR1947639 1 0.7034 0.1556 0.468 0.412 0.120 0.000
#> SRR1947638 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947637 3 0.6235 0.5895 0.056 0.000 0.524 0.420
#> SRR1947636 3 0.5158 0.4026 0.472 0.000 0.524 0.004
#> SRR1947635 2 0.4855 0.2780 0.000 0.600 0.000 0.400
#> SRR1947634 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947633 3 0.4999 0.6099 0.000 0.000 0.508 0.492
#> SRR1947632 1 0.6839 -0.2827 0.476 0.448 0.016 0.060
#> SRR1947631 4 0.7811 -0.1475 0.368 0.000 0.252 0.380
#> SRR1947629 4 0.0000 0.4152 0.000 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947627 3 0.4996 0.6096 0.000 0.000 0.516 0.484
#> SRR1947628 4 0.4994 0.0126 0.000 0.480 0.000 0.520
#> SRR1947626 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947625 4 0.4964 -0.4133 0.004 0.000 0.380 0.616
#> SRR1947624 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947623 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947622 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947619 1 0.5564 -0.4300 0.544 0.000 0.436 0.020
#> SRR1947617 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947616 4 0.4941 0.1144 0.000 0.436 0.000 0.564
#> SRR1947615 1 0.6149 -0.3295 0.476 0.000 0.048 0.476
#> SRR1947614 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947613 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947610 2 0.5000 -0.0176 0.000 0.500 0.000 0.500
#> SRR1947612 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947608 1 0.6277 -0.4836 0.476 0.000 0.468 0.056
#> SRR1947606 3 0.6483 0.5783 0.076 0.000 0.532 0.392
#> SRR1947607 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947604 1 0.0000 0.3803 1.000 0.000 0.000 0.000
#> SRR1947605 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947603 2 0.2814 0.7512 0.132 0.868 0.000 0.000
#> SRR1947602 3 0.4746 -0.5715 0.368 0.000 0.632 0.000
#> SRR1947600 4 0.0188 0.4137 0.000 0.000 0.004 0.996
#> SRR1947601 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.3975 0.3071 0.240 0.000 0.000 0.760
#> SRR1947599 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947597 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947596 1 0.3074 0.4996 0.848 0.000 0.152 0.000
#> SRR1947595 2 0.5149 0.4328 0.336 0.648 0.016 0.000
#> SRR1947594 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947592 3 0.6292 0.4278 0.416 0.000 0.524 0.060
#> SRR1947591 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947590 1 0.0707 0.3760 0.980 0.000 0.020 0.000
#> SRR1947588 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947587 3 0.5158 0.4026 0.472 0.000 0.524 0.004
#> SRR1947586 2 0.0336 0.8738 0.000 0.992 0.000 0.008
#> SRR1947585 4 0.0921 0.3960 0.000 0.000 0.028 0.972
#> SRR1947584 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947583 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947582 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947580 2 0.4925 0.1924 0.000 0.572 0.000 0.428
#> SRR1947581 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947576 3 0.4999 0.6099 0.000 0.000 0.508 0.492
#> SRR1947575 1 0.6214 -0.4862 0.476 0.000 0.472 0.052
#> SRR1947579 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947578 4 0.4994 0.0126 0.000 0.480 0.000 0.520
#> SRR1947573 3 0.6400 0.4310 0.408 0.000 0.524 0.068
#> SRR1947574 1 0.7706 0.3514 0.436 0.328 0.236 0.000
#> SRR1947571 1 0.2899 0.4674 0.880 0.004 0.112 0.004
#> SRR1947577 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947570 1 0.4989 0.6797 0.528 0.000 0.472 0.000
#> SRR1947569 4 0.0000 0.4152 0.000 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947567 2 0.2081 0.8120 0.000 0.916 0.000 0.084
#> SRR1947568 2 0.5055 0.3876 0.368 0.624 0.008 0.000
#> SRR1947564 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947563 1 0.6337 -0.4816 0.476 0.000 0.464 0.060
#> SRR1947562 1 0.5511 -0.3177 0.500 0.484 0.000 0.016
#> SRR1947565 3 0.5158 0.4026 0.472 0.000 0.524 0.004
#> SRR1947559 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947561 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947558 4 0.5921 -0.5440 0.036 0.000 0.448 0.516
#> SRR1947556 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947553 4 0.5000 -0.0374 0.000 0.496 0.000 0.504
#> SRR1947554 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947555 2 0.1637 0.8291 0.060 0.940 0.000 0.000
#> SRR1947550 1 0.4356 0.0779 0.708 0.292 0.000 0.000
#> SRR1947552 1 0.4967 0.6740 0.548 0.000 0.452 0.000
#> SRR1947549 3 0.4992 0.3995 0.476 0.000 0.524 0.000
#> SRR1947551 3 0.5000 0.6092 0.000 0.000 0.504 0.496
#> SRR1947548 1 0.2222 0.3060 0.924 0.000 0.016 0.060
#> SRR1947506 1 0.4996 0.6805 0.516 0.000 0.484 0.000
#> SRR1947507 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947504 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947503 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947502 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947501 1 0.7104 -0.2696 0.476 0.428 0.016 0.080
#> SRR1947499 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947498 4 0.0921 0.3962 0.000 0.000 0.028 0.972
#> SRR1947508 3 0.4998 0.6100 0.000 0.000 0.512 0.488
#> SRR1947505 4 0.0000 0.4152 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947495 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947494 1 0.2081 0.4505 0.916 0.000 0.084 0.000
#> SRR1947493 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947492 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947500 2 0.0000 0.8791 0.000 1.000 0.000 0.000
#> SRR1947491 2 0.2530 0.7792 0.000 0.888 0.000 0.112
#> SRR1947490 1 0.4992 0.6847 0.524 0.000 0.476 0.000
#> SRR1947489 1 0.6212 -0.3833 0.560 0.000 0.380 0.060
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 1 0.2392 0.8563 0.888 0.000 0.104 0.004 0.004
#> SRR1947546 3 0.2074 0.7894 0.000 0.104 0.896 0.000 0.000
#> SRR1947545 1 0.0162 0.9508 0.996 0.000 0.004 0.000 0.000
#> SRR1947544 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947542 3 0.1851 0.7989 0.000 0.088 0.912 0.000 0.000
#> SRR1947541 5 0.2570 0.8786 0.008 0.000 0.108 0.004 0.880
#> SRR1947540 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947539 5 0.1671 0.8965 0.000 0.000 0.076 0.000 0.924
#> SRR1947538 4 0.0162 0.9577 0.004 0.000 0.000 0.996 0.000
#> SRR1947537 3 0.3910 0.5241 0.008 0.000 0.720 0.000 0.272
#> SRR1947536 4 0.0290 0.9591 0.000 0.000 0.000 0.992 0.008
#> SRR1947535 3 0.0162 0.8150 0.000 0.000 0.996 0.000 0.004
#> SRR1947534 2 0.3561 0.6322 0.260 0.740 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 3 0.1478 0.8073 0.064 0.000 0.936 0.000 0.000
#> SRR1947531 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947530 1 0.0324 0.9495 0.992 0.000 0.004 0.004 0.000
#> SRR1947529 2 0.2723 0.8270 0.000 0.864 0.124 0.012 0.000
#> SRR1947528 5 0.2136 0.8906 0.008 0.000 0.088 0.000 0.904
#> SRR1947527 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 2 0.5455 0.5638 0.292 0.624 0.080 0.004 0.000
#> SRR1947524 4 0.0693 0.9531 0.000 0.000 0.012 0.980 0.008
#> SRR1947523 3 0.2020 0.7934 0.000 0.100 0.900 0.000 0.000
#> SRR1947521 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947520 2 0.1671 0.8534 0.000 0.924 0.000 0.000 0.076
#> SRR1947519 3 0.0162 0.8150 0.000 0.000 0.996 0.000 0.004
#> SRR1947518 4 0.0162 0.9577 0.004 0.000 0.000 0.996 0.000
#> SRR1947517 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 3 0.1478 0.8073 0.064 0.000 0.936 0.000 0.000
#> SRR1947514 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 1 0.0162 0.9508 0.996 0.000 0.000 0.004 0.000
#> SRR1947512 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947511 2 0.1270 0.8678 0.000 0.948 0.000 0.000 0.052
#> SRR1947510 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947572 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947611 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947509 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947644 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947642 3 0.4221 0.6419 0.004 0.000 0.764 0.044 0.188
#> SRR1947640 2 0.6201 0.4780 0.232 0.552 0.216 0.000 0.000
#> SRR1947641 5 0.5595 0.5956 0.000 0.000 0.124 0.252 0.624
#> SRR1947639 1 0.3920 0.5900 0.724 0.268 0.004 0.004 0.000
#> SRR1947638 1 0.0324 0.9495 0.992 0.000 0.004 0.004 0.000
#> SRR1947637 5 0.0162 0.9063 0.000 0.000 0.004 0.000 0.996
#> SRR1947636 5 0.3913 0.5714 0.000 0.000 0.324 0.000 0.676
#> SRR1947635 4 0.6185 0.1736 0.000 0.348 0.148 0.504 0.000
#> SRR1947634 2 0.1270 0.8678 0.000 0.948 0.000 0.000 0.052
#> SRR1947633 5 0.1608 0.8974 0.000 0.000 0.072 0.000 0.928
#> SRR1947632 3 0.1410 0.8093 0.000 0.060 0.940 0.000 0.000
#> SRR1947631 3 0.0771 0.8124 0.004 0.000 0.976 0.020 0.000
#> SRR1947629 4 0.0290 0.9591 0.000 0.000 0.000 0.992 0.008
#> SRR1947630 2 0.1908 0.8427 0.000 0.908 0.000 0.000 0.092
#> SRR1947627 5 0.1732 0.8953 0.000 0.000 0.080 0.000 0.920
#> SRR1947628 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947626 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 3 0.2951 0.7420 0.000 0.000 0.860 0.028 0.112
#> SRR1947624 2 0.1908 0.8427 0.000 0.908 0.000 0.000 0.092
#> SRR1947623 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947622 2 0.2471 0.8226 0.000 0.864 0.136 0.000 0.000
#> SRR1947621 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.0324 0.9495 0.992 0.000 0.004 0.004 0.000
#> SRR1947619 3 0.3055 0.7489 0.064 0.000 0.864 0.000 0.072
#> SRR1947617 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.0162 0.9508 0.996 0.000 0.000 0.004 0.000
#> SRR1947616 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947615 3 0.2389 0.7583 0.004 0.000 0.880 0.116 0.000
#> SRR1947614 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947613 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947610 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947612 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 1 0.0000 0.9516 1.000 0.000 0.000 0.000 0.000
#> SRR1947608 3 0.0162 0.8150 0.000 0.000 0.996 0.000 0.004
#> SRR1947606 5 0.2068 0.8896 0.004 0.000 0.092 0.000 0.904
#> SRR1947607 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947604 3 0.1965 0.7901 0.096 0.000 0.904 0.000 0.000
#> SRR1947605 1 0.0000 0.9516 1.000 0.000 0.000 0.000 0.000
#> SRR1947603 3 0.4273 0.0186 0.000 0.448 0.552 0.000 0.000
#> SRR1947602 1 0.3937 0.7528 0.804 0.000 0.060 0.004 0.132
#> SRR1947600 4 0.0693 0.9530 0.000 0.000 0.012 0.980 0.008
#> SRR1947601 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.0162 0.9583 0.000 0.000 0.004 0.996 0.000
#> SRR1947599 1 0.2068 0.8676 0.904 0.000 0.092 0.004 0.000
#> SRR1947597 2 0.2929 0.7843 0.000 0.820 0.180 0.000 0.000
#> SRR1947596 1 0.4150 0.2913 0.612 0.000 0.388 0.000 0.000
#> SRR1947595 2 0.4946 0.6043 0.276 0.664 0.000 0.000 0.060
#> SRR1947594 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947592 5 0.2424 0.8626 0.000 0.000 0.132 0.000 0.868
#> SRR1947591 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 3 0.3949 0.5185 0.332 0.000 0.668 0.000 0.000
#> SRR1947588 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947587 3 0.4580 0.0084 0.004 0.000 0.532 0.004 0.460
#> SRR1947586 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947585 4 0.0566 0.9556 0.000 0.000 0.004 0.984 0.012
#> SRR1947584 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947583 2 0.3274 0.7406 0.000 0.780 0.220 0.000 0.000
#> SRR1947582 1 0.0162 0.9508 0.996 0.000 0.000 0.004 0.000
#> SRR1947580 4 0.1792 0.8822 0.000 0.084 0.000 0.916 0.000
#> SRR1947581 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947576 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947575 3 0.0162 0.8150 0.000 0.000 0.996 0.000 0.004
#> SRR1947579 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947578 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947573 5 0.2127 0.8824 0.000 0.000 0.108 0.000 0.892
#> SRR1947574 1 0.3837 0.5444 0.692 0.308 0.000 0.000 0.000
#> SRR1947571 3 0.3353 0.7096 0.196 0.008 0.796 0.000 0.000
#> SRR1947577 1 0.0324 0.9495 0.992 0.000 0.004 0.004 0.000
#> SRR1947570 1 0.0566 0.9454 0.984 0.000 0.012 0.004 0.000
#> SRR1947569 4 0.0290 0.9591 0.000 0.000 0.000 0.992 0.008
#> SRR1947566 2 0.0510 0.8847 0.000 0.984 0.000 0.016 0.000
#> SRR1947567 2 0.3857 0.6111 0.000 0.688 0.312 0.000 0.000
#> SRR1947568 2 0.3635 0.6779 0.248 0.748 0.000 0.004 0.000
#> SRR1947564 2 0.0290 0.8877 0.000 0.992 0.008 0.000 0.000
#> SRR1947563 3 0.0162 0.8150 0.000 0.000 0.996 0.000 0.004
#> SRR1947562 3 0.1908 0.7965 0.000 0.092 0.908 0.000 0.000
#> SRR1947565 5 0.4300 0.1534 0.000 0.000 0.476 0.000 0.524
#> SRR1947559 2 0.2230 0.8379 0.000 0.884 0.116 0.000 0.000
#> SRR1947560 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947558 3 0.3160 0.6634 0.000 0.000 0.808 0.004 0.188
#> SRR1947556 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947553 4 0.0290 0.9604 0.000 0.008 0.000 0.992 0.000
#> SRR1947554 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947555 2 0.3949 0.5778 0.000 0.668 0.332 0.000 0.000
#> SRR1947550 3 0.2305 0.7954 0.012 0.092 0.896 0.000 0.000
#> SRR1947552 1 0.2286 0.8486 0.888 0.000 0.108 0.004 0.000
#> SRR1947549 3 0.4192 0.2222 0.000 0.000 0.596 0.000 0.404
#> SRR1947551 5 0.0000 0.9076 0.000 0.000 0.000 0.000 1.000
#> SRR1947548 3 0.1484 0.8128 0.048 0.008 0.944 0.000 0.000
#> SRR1947506 1 0.0451 0.9467 0.988 0.000 0.008 0.004 0.000
#> SRR1947507 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947504 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947503 1 0.0162 0.9508 0.996 0.000 0.004 0.000 0.000
#> SRR1947502 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 3 0.1671 0.8042 0.000 0.076 0.924 0.000 0.000
#> SRR1947499 1 0.1757 0.9048 0.936 0.000 0.048 0.004 0.012
#> SRR1947498 4 0.0290 0.9591 0.000 0.000 0.000 0.992 0.008
#> SRR1947508 5 0.2228 0.8884 0.004 0.000 0.092 0.004 0.900
#> SRR1947505 4 0.0162 0.9598 0.000 0.004 0.000 0.996 0.000
#> SRR1947497 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947496 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947495 2 0.0000 0.8909 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 3 0.4278 0.2235 0.452 0.000 0.548 0.000 0.000
#> SRR1947493 1 0.0162 0.9508 0.996 0.000 0.000 0.004 0.000
#> SRR1947492 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947500 2 0.2471 0.8226 0.000 0.864 0.136 0.000 0.000
#> SRR1947491 2 0.2629 0.8214 0.000 0.860 0.136 0.004 0.000
#> SRR1947490 1 0.0162 0.9522 0.996 0.000 0.000 0.004 0.000
#> SRR1947489 3 0.0162 0.8149 0.004 0.000 0.996 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.0972 0.6199 0.028 0.000 0.000 0.008 0.000 0.964
#> SRR1947546 4 0.2219 0.6465 0.000 0.136 0.000 0.864 0.000 0.000
#> SRR1947545 6 0.3853 0.6078 0.304 0.000 0.000 0.016 0.000 0.680
#> SRR1947544 1 0.0146 0.9001 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947542 4 0.2003 0.6562 0.000 0.116 0.000 0.884 0.000 0.000
#> SRR1947541 6 0.1624 0.5999 0.004 0.000 0.000 0.020 0.040 0.936
#> SRR1947540 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947539 5 0.4625 0.6427 0.000 0.000 0.000 0.104 0.680 0.216
#> SRR1947538 3 0.0725 0.8465 0.012 0.000 0.976 0.012 0.000 0.000
#> SRR1947537 4 0.5154 0.4514 0.004 0.000 0.000 0.600 0.104 0.292
#> SRR1947536 3 0.1471 0.8392 0.000 0.000 0.932 0.004 0.000 0.064
#> SRR1947535 4 0.2631 0.5972 0.000 0.000 0.000 0.820 0.000 0.180
#> SRR1947534 2 0.4064 0.4388 0.336 0.644 0.000 0.000 0.000 0.020
#> SRR1947533 2 0.0146 0.8290 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947532 4 0.3071 0.6239 0.016 0.000 0.000 0.804 0.000 0.180
#> SRR1947531 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947530 6 0.2996 0.6709 0.228 0.000 0.000 0.000 0.000 0.772
#> SRR1947529 2 0.2890 0.7661 0.000 0.844 0.024 0.128 0.000 0.004
#> SRR1947528 6 0.5035 0.3182 0.012 0.000 0.000 0.104 0.228 0.656
#> SRR1947527 2 0.0146 0.8290 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947526 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947525 1 0.4683 0.6211 0.728 0.156 0.000 0.084 0.000 0.032
#> SRR1947524 3 0.4396 0.6963 0.000 0.000 0.704 0.088 0.000 0.208
#> SRR1947523 4 0.5630 0.3237 0.000 0.232 0.000 0.540 0.000 0.228
#> SRR1947521 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.3265 0.6859 0.000 0.748 0.000 0.000 0.248 0.004
#> SRR1947519 4 0.3198 0.5341 0.000 0.000 0.000 0.740 0.000 0.260
#> SRR1947518 3 0.2362 0.7496 0.136 0.000 0.860 0.004 0.000 0.000
#> SRR1947517 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 4 0.3509 0.5879 0.016 0.000 0.000 0.744 0.000 0.240
#> SRR1947514 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 6 0.3828 0.4210 0.440 0.000 0.000 0.000 0.000 0.560
#> SRR1947512 1 0.0146 0.9027 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947511 2 0.1806 0.7893 0.000 0.908 0.000 0.000 0.088 0.004
#> SRR1947510 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 1 0.0717 0.8886 0.976 0.000 0.000 0.016 0.000 0.008
#> SRR1947611 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947509 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947644 5 0.1745 0.7975 0.000 0.000 0.000 0.056 0.924 0.020
#> SRR1947643 2 0.0508 0.8263 0.000 0.984 0.012 0.000 0.000 0.004
#> SRR1947642 6 0.5326 0.4067 0.000 0.000 0.064 0.196 0.072 0.668
#> SRR1947640 2 0.6837 0.4117 0.136 0.504 0.000 0.220 0.000 0.140
#> SRR1947641 3 0.7016 0.3726 0.000 0.000 0.472 0.164 0.132 0.232
#> SRR1947639 1 0.1802 0.8630 0.932 0.024 0.000 0.020 0.000 0.024
#> SRR1947638 6 0.4382 0.5291 0.360 0.008 0.000 0.020 0.000 0.612
#> SRR1947637 5 0.0692 0.8217 0.000 0.000 0.000 0.020 0.976 0.004
#> SRR1947636 5 0.6006 0.2098 0.000 0.000 0.000 0.332 0.420 0.248
#> SRR1947635 2 0.6433 0.4211 0.000 0.488 0.248 0.228 0.000 0.036
#> SRR1947634 2 0.1806 0.7893 0.000 0.908 0.000 0.000 0.088 0.004
#> SRR1947633 5 0.4582 0.6451 0.000 0.000 0.000 0.100 0.684 0.216
#> SRR1947632 4 0.2218 0.6593 0.000 0.104 0.000 0.884 0.000 0.012
#> SRR1947631 6 0.5144 0.1090 0.000 0.000 0.092 0.372 0.000 0.536
#> SRR1947629 3 0.3829 0.7477 0.000 0.000 0.760 0.060 0.000 0.180
#> SRR1947630 2 0.3699 0.5872 0.000 0.660 0.000 0.000 0.336 0.004
#> SRR1947627 5 0.4727 0.6271 0.000 0.000 0.000 0.100 0.660 0.240
#> SRR1947628 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947626 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947625 4 0.6437 0.3593 0.000 0.000 0.172 0.532 0.064 0.232
#> SRR1947624 2 0.3756 0.5639 0.000 0.644 0.000 0.000 0.352 0.004
#> SRR1947623 1 0.0000 0.9019 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.3245 0.6947 0.000 0.764 0.008 0.228 0.000 0.000
#> SRR1947621 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 6 0.3405 0.6353 0.272 0.000 0.000 0.004 0.000 0.724
#> SRR1947619 4 0.4131 0.4812 0.020 0.000 0.000 0.624 0.000 0.356
#> SRR1947617 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 6 0.3330 0.6244 0.284 0.000 0.000 0.000 0.000 0.716
#> SRR1947616 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947615 6 0.3963 0.5072 0.000 0.000 0.080 0.164 0.000 0.756
#> SRR1947614 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0547 0.9008 0.980 0.000 0.000 0.000 0.000 0.020
#> SRR1947610 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947612 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 6 0.4326 0.4728 0.404 0.000 0.000 0.024 0.000 0.572
#> SRR1947608 4 0.2092 0.6314 0.000 0.000 0.000 0.876 0.000 0.124
#> SRR1947606 6 0.5645 -0.1289 0.004 0.000 0.000 0.136 0.372 0.488
#> SRR1947607 1 0.0790 0.8951 0.968 0.000 0.000 0.000 0.000 0.032
#> SRR1947604 4 0.4039 0.4698 0.016 0.000 0.000 0.632 0.000 0.352
#> SRR1947605 6 0.3446 0.6163 0.308 0.000 0.000 0.000 0.000 0.692
#> SRR1947603 4 0.2597 0.6113 0.000 0.176 0.000 0.824 0.000 0.000
#> SRR1947602 6 0.2568 0.6226 0.068 0.000 0.000 0.056 0.000 0.876
#> SRR1947600 3 0.4422 0.6914 0.000 0.000 0.700 0.088 0.000 0.212
#> SRR1947601 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947599 6 0.4281 0.6081 0.132 0.000 0.000 0.136 0.000 0.732
#> SRR1947597 2 0.3515 0.5802 0.000 0.676 0.000 0.324 0.000 0.000
#> SRR1947596 1 0.6112 -0.1510 0.372 0.000 0.000 0.320 0.000 0.308
#> SRR1947595 2 0.6488 0.4287 0.144 0.484 0.000 0.000 0.312 0.060
#> SRR1947594 1 0.0458 0.9017 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947592 5 0.5318 0.5489 0.000 0.000 0.000 0.160 0.588 0.252
#> SRR1947591 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 4 0.5464 0.3720 0.176 0.000 0.000 0.564 0.000 0.260
#> SRR1947588 1 0.0458 0.9017 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947587 6 0.2572 0.5360 0.000 0.000 0.000 0.136 0.012 0.852
#> SRR1947586 2 0.0363 0.8271 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1947585 3 0.4278 0.7044 0.000 0.000 0.712 0.076 0.000 0.212
#> SRR1947584 1 0.0000 0.9019 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 2 0.5011 0.5963 0.032 0.648 0.000 0.268 0.000 0.052
#> SRR1947582 6 0.3151 0.6403 0.252 0.000 0.000 0.000 0.000 0.748
#> SRR1947580 3 0.0146 0.8570 0.000 0.004 0.996 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.9019 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947575 4 0.1556 0.6502 0.000 0.000 0.000 0.920 0.000 0.080
#> SRR1947579 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947573 5 0.4884 0.6182 0.000 0.000 0.000 0.128 0.652 0.220
#> SRR1947574 2 0.5291 0.3577 0.328 0.552 0.000 0.000 0.000 0.120
#> SRR1947571 4 0.4412 0.5505 0.048 0.008 0.000 0.688 0.000 0.256
#> SRR1947577 6 0.3911 0.6365 0.256 0.000 0.000 0.032 0.000 0.712
#> SRR1947570 6 0.2402 0.6660 0.120 0.000 0.000 0.012 0.000 0.868
#> SRR1947569 3 0.3053 0.7808 0.000 0.000 0.812 0.020 0.000 0.168
#> SRR1947566 2 0.0547 0.8247 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1947567 2 0.4264 0.5542 0.000 0.636 0.000 0.332 0.000 0.032
#> SRR1947568 1 0.3468 0.5486 0.712 0.284 0.000 0.004 0.000 0.000
#> SRR1947564 2 0.3578 0.3855 0.000 0.660 0.000 0.340 0.000 0.000
#> SRR1947563 4 0.1556 0.6499 0.000 0.000 0.000 0.920 0.000 0.080
#> SRR1947562 4 0.3352 0.6298 0.016 0.012 0.000 0.800 0.000 0.172
#> SRR1947565 4 0.5963 0.0305 0.000 0.000 0.000 0.440 0.320 0.240
#> SRR1947559 2 0.2219 0.7698 0.000 0.864 0.000 0.136 0.000 0.000
#> SRR1947560 5 0.0000 0.8281 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0458 0.9017 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947558 4 0.5391 0.3558 0.000 0.000 0.000 0.580 0.176 0.244
#> SRR1947556 1 0.1895 0.8294 0.912 0.000 0.000 0.016 0.000 0.072
#> SRR1947553 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947554 1 0.0713 0.8975 0.972 0.000 0.000 0.000 0.000 0.028
#> SRR1947555 4 0.3607 0.2939 0.000 0.348 0.000 0.652 0.000 0.000
#> SRR1947550 4 0.3956 0.6279 0.028 0.132 0.000 0.788 0.000 0.052
#> SRR1947552 6 0.4232 0.6379 0.168 0.000 0.000 0.100 0.000 0.732
#> SRR1947549 4 0.5718 0.2775 0.000 0.000 0.000 0.520 0.228 0.252
#> SRR1947551 5 0.0260 0.8266 0.000 0.000 0.000 0.008 0.992 0.000
#> SRR1947548 4 0.2783 0.6363 0.016 0.000 0.000 0.836 0.000 0.148
#> SRR1947506 6 0.3314 0.6211 0.224 0.000 0.000 0.012 0.000 0.764
#> SRR1947507 1 0.0458 0.9017 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947504 1 0.0725 0.8879 0.976 0.000 0.000 0.012 0.000 0.012
#> SRR1947503 6 0.3974 0.6009 0.296 0.000 0.000 0.024 0.000 0.680
#> SRR1947502 2 0.0000 0.8295 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 4 0.2257 0.6572 0.000 0.116 0.000 0.876 0.000 0.008
#> SRR1947499 6 0.1556 0.6494 0.080 0.000 0.000 0.000 0.000 0.920
#> SRR1947498 3 0.3939 0.7407 0.000 0.000 0.752 0.068 0.000 0.180
#> SRR1947508 6 0.4095 0.4736 0.000 0.000 0.000 0.100 0.152 0.748
#> SRR1947505 3 0.0000 0.8592 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947497 2 0.0146 0.8290 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947496 1 0.0363 0.9026 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1947495 2 0.0146 0.8290 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947494 4 0.5603 0.2078 0.148 0.000 0.000 0.476 0.000 0.376
#> SRR1947493 6 0.3774 0.5044 0.408 0.000 0.000 0.000 0.000 0.592
#> SRR1947492 1 0.0458 0.9017 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947500 2 0.3284 0.7340 0.000 0.800 0.000 0.168 0.000 0.032
#> SRR1947491 2 0.4350 0.6952 0.000 0.736 0.020 0.188 0.000 0.056
#> SRR1947490 1 0.0937 0.8887 0.960 0.000 0.000 0.000 0.000 0.040
#> SRR1947489 6 0.3330 0.4432 0.000 0.000 0.000 0.284 0.000 0.716
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 15148 rows and 152 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 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 0.442 0.663 0.866 0.4307 0.560 0.560
#> 3 3 0.333 0.529 0.718 0.4682 0.682 0.483
#> 4 4 0.659 0.794 0.877 0.1751 0.858 0.617
#> 5 5 0.664 0.638 0.819 0.0456 0.965 0.863
#> 6 6 0.721 0.768 0.840 0.0368 0.951 0.791
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
#> SRR1947547 1 0.5842 0.7543 0.860 0.140
#> SRR1947546 2 0.0672 0.8258 0.008 0.992
#> SRR1947545 1 0.0000 0.7995 1.000 0.000
#> SRR1947544 1 0.9909 0.2086 0.556 0.444
#> SRR1947542 2 0.0672 0.8258 0.008 0.992
#> SRR1947541 1 0.5842 0.7543 0.860 0.140
#> SRR1947540 2 0.8443 0.5672 0.272 0.728
#> SRR1947539 2 0.0000 0.8297 0.000 1.000
#> SRR1947538 2 0.9661 0.3587 0.392 0.608
#> SRR1947537 2 0.5946 0.7188 0.144 0.856
#> SRR1947536 1 0.5842 0.7320 0.860 0.140
#> SRR1947535 2 0.0000 0.8297 0.000 1.000
#> SRR1947534 2 1.0000 -0.0387 0.496 0.504
#> SRR1947533 2 0.0000 0.8297 0.000 1.000
#> SRR1947532 2 0.9661 0.3587 0.392 0.608
#> SRR1947531 2 0.8443 0.5672 0.272 0.728
#> SRR1947530 1 0.0376 0.8000 0.996 0.004
#> SRR1947529 2 0.0000 0.8297 0.000 1.000
#> SRR1947528 1 0.6148 0.7462 0.848 0.152
#> SRR1947527 2 0.1633 0.8162 0.024 0.976
#> SRR1947526 2 0.0000 0.8297 0.000 1.000
#> SRR1947525 2 0.9522 0.4011 0.372 0.628
#> SRR1947524 2 0.0000 0.8297 0.000 1.000
#> SRR1947523 2 0.9795 0.2922 0.416 0.584
#> SRR1947521 2 0.0000 0.8297 0.000 1.000
#> SRR1947520 2 0.0000 0.8297 0.000 1.000
#> SRR1947519 2 0.0000 0.8297 0.000 1.000
#> SRR1947518 2 0.9661 0.3587 0.392 0.608
#> SRR1947517 2 0.9754 0.2361 0.408 0.592
#> SRR1947516 2 0.0000 0.8297 0.000 1.000
#> SRR1947515 2 0.9661 0.3587 0.392 0.608
#> SRR1947514 2 0.0000 0.8297 0.000 1.000
#> SRR1947513 1 0.6531 0.7062 0.832 0.168
#> SRR1947512 1 0.0000 0.7995 1.000 0.000
#> SRR1947511 2 0.0000 0.8297 0.000 1.000
#> SRR1947510 2 0.0000 0.8297 0.000 1.000
#> SRR1947572 1 0.9977 0.1093 0.528 0.472
#> SRR1947611 2 0.0000 0.8297 0.000 1.000
#> SRR1947509 2 0.9754 0.2361 0.408 0.592
#> SRR1947644 2 0.0000 0.8297 0.000 1.000
#> SRR1947643 2 0.2603 0.8021 0.044 0.956
#> SRR1947642 2 0.2423 0.8016 0.040 0.960
#> SRR1947640 2 0.9608 0.3765 0.384 0.616
#> SRR1947641 2 0.0000 0.8297 0.000 1.000
#> SRR1947639 2 0.9686 0.3478 0.396 0.604
#> SRR1947638 1 0.7139 0.6952 0.804 0.196
#> SRR1947637 2 0.0000 0.8297 0.000 1.000
#> SRR1947636 2 0.5946 0.7188 0.144 0.856
#> SRR1947635 2 0.9087 0.4831 0.324 0.676
#> SRR1947634 2 0.0000 0.8297 0.000 1.000
#> SRR1947633 2 0.0000 0.8297 0.000 1.000
#> SRR1947632 2 0.0672 0.8258 0.008 0.992
#> SRR1947631 2 0.0000 0.8297 0.000 1.000
#> SRR1947629 2 0.0000 0.8297 0.000 1.000
#> SRR1947630 2 0.0000 0.8297 0.000 1.000
#> SRR1947627 1 0.4022 0.7746 0.920 0.080
#> SRR1947628 2 0.9661 0.3587 0.392 0.608
#> SRR1947626 2 0.0000 0.8297 0.000 1.000
#> SRR1947625 2 0.0000 0.8297 0.000 1.000
#> SRR1947624 2 0.0000 0.8297 0.000 1.000
#> SRR1947623 1 0.9944 0.1698 0.544 0.456
#> SRR1947622 2 0.0000 0.8297 0.000 1.000
#> SRR1947621 2 0.0000 0.8297 0.000 1.000
#> SRR1947620 1 0.1184 0.7995 0.984 0.016
#> SRR1947619 2 0.5178 0.7403 0.116 0.884
#> SRR1947617 2 0.0000 0.8297 0.000 1.000
#> SRR1947618 1 0.1184 0.7995 0.984 0.016
#> SRR1947616 2 0.0000 0.8297 0.000 1.000
#> SRR1947615 1 0.5294 0.7640 0.880 0.120
#> SRR1947614 2 0.0000 0.8297 0.000 1.000
#> SRR1947613 1 0.0000 0.7995 1.000 0.000
#> SRR1947610 2 0.9661 0.3587 0.392 0.608
#> SRR1947612 2 0.0000 0.8297 0.000 1.000
#> SRR1947609 2 0.9815 0.2807 0.420 0.580
#> SRR1947608 2 0.0000 0.8297 0.000 1.000
#> SRR1947606 1 0.9795 0.3252 0.584 0.416
#> SRR1947607 1 0.0000 0.7995 1.000 0.000
#> SRR1947604 2 0.9661 0.3587 0.392 0.608
#> SRR1947605 1 0.0000 0.7995 1.000 0.000
#> SRR1947603 2 0.0000 0.8297 0.000 1.000
#> SRR1947602 1 0.0376 0.8000 0.996 0.004
#> SRR1947600 2 0.0000 0.8297 0.000 1.000
#> SRR1947601 2 0.0000 0.8297 0.000 1.000
#> SRR1947598 2 0.9661 0.3587 0.392 0.608
#> SRR1947599 1 0.9983 0.0965 0.524 0.476
#> SRR1947597 2 0.0376 0.8278 0.004 0.996
#> SRR1947596 1 0.9909 0.2086 0.556 0.444
#> SRR1947595 2 0.9661 0.3587 0.392 0.608
#> SRR1947594 1 0.0000 0.7995 1.000 0.000
#> SRR1947592 2 0.0000 0.8297 0.000 1.000
#> SRR1947591 2 0.0000 0.8297 0.000 1.000
#> SRR1947590 1 0.9909 0.2086 0.556 0.444
#> SRR1947588 1 0.0000 0.7995 1.000 0.000
#> SRR1947587 1 0.5842 0.7543 0.860 0.140
#> SRR1947586 2 0.0000 0.8297 0.000 1.000
#> SRR1947585 2 0.0000 0.8297 0.000 1.000
#> SRR1947584 1 0.0000 0.7995 1.000 0.000
#> SRR1947583 2 0.9608 0.3765 0.384 0.616
#> SRR1947582 1 0.1184 0.7995 0.984 0.016
#> SRR1947580 2 0.0000 0.8297 0.000 1.000
#> SRR1947581 1 0.0000 0.7995 1.000 0.000
#> SRR1947576 2 0.0000 0.8297 0.000 1.000
#> SRR1947575 2 0.0000 0.8297 0.000 1.000
#> SRR1947579 2 0.0000 0.8297 0.000 1.000
#> SRR1947578 2 0.9661 0.3587 0.392 0.608
#> SRR1947573 2 0.0000 0.8297 0.000 1.000
#> SRR1947574 1 0.9833 0.2787 0.576 0.424
#> SRR1947571 2 0.9661 0.3587 0.392 0.608
#> SRR1947577 1 0.1184 0.7995 0.984 0.016
#> SRR1947570 1 0.5842 0.7543 0.860 0.140
#> SRR1947569 2 0.0000 0.8297 0.000 1.000
#> SRR1947566 2 0.0000 0.8297 0.000 1.000
#> SRR1947567 2 0.9087 0.4831 0.324 0.676
#> SRR1947568 2 1.0000 -0.0144 0.496 0.504
#> SRR1947564 2 0.0000 0.8297 0.000 1.000
#> SRR1947563 2 0.0000 0.8297 0.000 1.000
#> SRR1947562 2 0.9393 0.4307 0.356 0.644
#> SRR1947565 2 0.5946 0.7188 0.144 0.856
#> SRR1947559 2 0.0376 0.8278 0.004 0.996
#> SRR1947560 2 0.0000 0.8297 0.000 1.000
#> SRR1947561 2 0.0000 0.8297 0.000 1.000
#> SRR1947557 1 0.0000 0.7995 1.000 0.000
#> SRR1947558 2 0.0000 0.8297 0.000 1.000
#> SRR1947556 1 0.9909 0.2086 0.556 0.444
#> SRR1947553 2 0.9661 0.3587 0.392 0.608
#> SRR1947554 1 0.5946 0.7355 0.856 0.144
#> SRR1947555 2 0.0000 0.8297 0.000 1.000
#> SRR1947550 2 0.9608 0.3765 0.384 0.616
#> SRR1947552 1 0.9983 0.0965 0.524 0.476
#> SRR1947549 2 0.0000 0.8297 0.000 1.000
#> SRR1947551 2 0.0000 0.8297 0.000 1.000
#> SRR1947548 2 0.9661 0.3587 0.392 0.608
#> SRR1947506 1 0.1184 0.7987 0.984 0.016
#> SRR1947507 1 0.0000 0.7995 1.000 0.000
#> SRR1947504 1 0.9922 0.1953 0.552 0.448
#> SRR1947503 1 0.7139 0.6952 0.804 0.196
#> SRR1947502 2 0.0000 0.8297 0.000 1.000
#> SRR1947501 2 0.0672 0.8258 0.008 0.992
#> SRR1947499 1 0.0376 0.8000 0.996 0.004
#> SRR1947498 2 0.0000 0.8297 0.000 1.000
#> SRR1947508 1 0.3584 0.7806 0.932 0.068
#> SRR1947505 2 0.9661 0.3587 0.392 0.608
#> SRR1947497 2 0.0000 0.8297 0.000 1.000
#> SRR1947496 1 0.0000 0.7995 1.000 0.000
#> SRR1947495 2 0.0000 0.8297 0.000 1.000
#> SRR1947494 1 0.9993 0.0652 0.516 0.484
#> SRR1947493 1 0.0376 0.8000 0.996 0.004
#> SRR1947492 1 0.0000 0.7995 1.000 0.000
#> SRR1947500 2 0.9087 0.4831 0.324 0.676
#> SRR1947491 2 0.9087 0.4831 0.324 0.676
#> SRR1947490 1 0.0000 0.7995 1.000 0.000
#> SRR1947489 1 0.5294 0.7640 0.880 0.120
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.4345 0.78967 0.848 0.136 0.016
#> SRR1947546 2 0.6192 0.32670 0.000 0.580 0.420
#> SRR1947545 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947544 2 0.6565 0.18428 0.416 0.576 0.008
#> SRR1947542 2 0.6192 0.32670 0.000 0.580 0.420
#> SRR1947541 1 0.4345 0.78967 0.848 0.136 0.016
#> SRR1947540 2 0.9491 0.37113 0.220 0.488 0.292
#> SRR1947539 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947538 2 0.6264 0.45026 0.244 0.724 0.032
#> SRR1947537 3 0.8790 0.58429 0.132 0.328 0.540
#> SRR1947536 1 0.4139 0.78220 0.860 0.016 0.124
#> SRR1947535 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947534 1 0.8983 0.07335 0.480 0.388 0.132
#> SRR1947533 2 0.6299 0.29312 0.000 0.524 0.476
#> SRR1947532 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947531 2 0.9491 0.37113 0.220 0.488 0.292
#> SRR1947530 1 0.0237 0.88087 0.996 0.000 0.004
#> SRR1947529 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947528 1 0.4615 0.77758 0.836 0.144 0.020
#> SRR1947527 2 0.6584 0.32435 0.012 0.608 0.380
#> SRR1947526 2 0.6305 0.28897 0.000 0.516 0.484
#> SRR1947525 2 0.6056 0.45242 0.224 0.744 0.032
#> SRR1947524 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947523 2 0.6373 0.43048 0.268 0.704 0.028
#> SRR1947521 3 0.3752 0.64721 0.000 0.144 0.856
#> SRR1947520 3 0.6274 -0.22511 0.000 0.456 0.544
#> SRR1947519 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947518 2 0.6264 0.45026 0.244 0.724 0.032
#> SRR1947517 3 0.9102 0.14912 0.408 0.140 0.452
#> SRR1947516 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947515 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947514 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947513 1 0.4873 0.72070 0.824 0.152 0.024
#> SRR1947512 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947511 3 0.6274 -0.22511 0.000 0.456 0.544
#> SRR1947510 3 0.3752 0.64721 0.000 0.144 0.856
#> SRR1947572 2 0.6434 0.25787 0.380 0.612 0.008
#> SRR1947611 3 0.1529 0.47663 0.000 0.040 0.960
#> SRR1947509 3 0.9102 0.14912 0.408 0.140 0.452
#> SRR1947644 3 0.5529 0.74454 0.000 0.296 0.704
#> SRR1947643 2 0.5529 0.31728 0.000 0.704 0.296
#> SRR1947642 3 0.6867 0.72946 0.040 0.288 0.672
#> SRR1947640 2 0.6183 0.45876 0.236 0.732 0.032
#> SRR1947641 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947639 2 0.6303 0.44901 0.248 0.720 0.032
#> SRR1947638 1 0.5216 0.62708 0.740 0.260 0.000
#> SRR1947637 3 0.1529 0.47663 0.000 0.040 0.960
#> SRR1947636 3 0.8790 0.58429 0.132 0.328 0.540
#> SRR1947635 2 0.5689 0.44270 0.184 0.780 0.036
#> SRR1947634 3 0.5835 0.00917 0.000 0.340 0.660
#> SRR1947633 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947632 2 0.6192 0.32670 0.000 0.580 0.420
#> SRR1947631 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947629 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947630 3 0.5835 0.00917 0.000 0.340 0.660
#> SRR1947627 1 0.2845 0.83884 0.920 0.012 0.068
#> SRR1947628 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947626 2 0.6095 0.31358 0.000 0.608 0.392
#> SRR1947625 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947624 3 0.5835 0.00917 0.000 0.340 0.660
#> SRR1947623 2 0.6498 0.22199 0.396 0.596 0.008
#> SRR1947622 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947621 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947620 1 0.1031 0.87396 0.976 0.024 0.000
#> SRR1947619 3 0.8468 0.63379 0.116 0.308 0.576
#> SRR1947617 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947618 1 0.1031 0.87396 0.976 0.024 0.000
#> SRR1947616 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947615 1 0.3715 0.80118 0.868 0.128 0.004
#> SRR1947614 3 0.3752 0.64721 0.000 0.144 0.856
#> SRR1947613 1 0.0237 0.88082 0.996 0.004 0.000
#> SRR1947610 2 0.6264 0.45026 0.244 0.724 0.032
#> SRR1947612 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947609 2 0.6632 0.42384 0.272 0.692 0.036
#> SRR1947608 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947606 1 0.8749 0.37283 0.572 0.152 0.276
#> SRR1947607 1 0.0237 0.88082 0.996 0.004 0.000
#> SRR1947604 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947605 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947603 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947602 1 0.0237 0.88087 0.996 0.000 0.004
#> SRR1947600 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947601 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947598 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947599 2 0.6566 0.27371 0.376 0.612 0.012
#> SRR1947597 2 0.6215 0.33796 0.000 0.572 0.428
#> SRR1947596 2 0.6565 0.18428 0.416 0.576 0.008
#> SRR1947595 2 0.6264 0.45337 0.244 0.724 0.032
#> SRR1947594 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947592 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947591 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947590 2 0.6565 0.18428 0.416 0.576 0.008
#> SRR1947588 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947587 1 0.4345 0.78967 0.848 0.136 0.016
#> SRR1947586 2 0.6095 0.31358 0.000 0.608 0.392
#> SRR1947585 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947584 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947583 2 0.6183 0.45876 0.236 0.732 0.032
#> SRR1947582 1 0.1031 0.87396 0.976 0.024 0.000
#> SRR1947580 2 0.6095 0.31358 0.000 0.608 0.392
#> SRR1947581 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947576 3 0.1529 0.47663 0.000 0.040 0.960
#> SRR1947575 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947579 3 0.3752 0.64721 0.000 0.144 0.856
#> SRR1947578 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947573 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947574 1 0.7984 0.04729 0.496 0.444 0.060
#> SRR1947571 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947577 1 0.1031 0.87396 0.976 0.024 0.000
#> SRR1947570 1 0.4345 0.78967 0.848 0.136 0.016
#> SRR1947569 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947566 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947567 2 0.5689 0.44270 0.184 0.780 0.036
#> SRR1947568 2 0.6427 0.31193 0.348 0.640 0.012
#> SRR1947564 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947563 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947562 2 0.8423 0.43815 0.228 0.616 0.156
#> SRR1947565 3 0.8790 0.58429 0.132 0.328 0.540
#> SRR1947559 2 0.6215 0.33796 0.000 0.572 0.428
#> SRR1947560 3 0.1529 0.47663 0.000 0.040 0.960
#> SRR1947561 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947557 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947558 3 0.5678 0.75106 0.000 0.316 0.684
#> SRR1947556 2 0.6565 0.18428 0.416 0.576 0.008
#> SRR1947553 2 0.6264 0.45026 0.244 0.724 0.032
#> SRR1947554 1 0.4887 0.75728 0.844 0.096 0.060
#> SRR1947555 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947550 2 0.6183 0.45876 0.236 0.732 0.032
#> SRR1947552 2 0.6566 0.27371 0.376 0.612 0.012
#> SRR1947549 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947551 3 0.5529 0.74454 0.000 0.296 0.704
#> SRR1947548 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947506 1 0.0829 0.87670 0.984 0.004 0.012
#> SRR1947507 1 0.0000 0.88069 1.000 0.000 0.000
#> SRR1947504 2 0.6540 0.19880 0.408 0.584 0.008
#> SRR1947503 1 0.5216 0.62708 0.740 0.260 0.000
#> SRR1947502 2 0.6280 0.33067 0.000 0.540 0.460
#> SRR1947501 2 0.6192 0.32670 0.000 0.580 0.420
#> SRR1947499 1 0.0237 0.88087 0.996 0.000 0.004
#> SRR1947498 3 0.5650 0.75116 0.000 0.312 0.688
#> SRR1947508 1 0.2550 0.84778 0.932 0.012 0.056
#> SRR1947505 2 0.6375 0.45011 0.244 0.720 0.036
#> SRR1947497 2 0.6299 0.29312 0.000 0.524 0.476
#> SRR1947496 1 0.0237 0.88082 0.996 0.004 0.000
#> SRR1947495 2 0.6299 0.29312 0.000 0.524 0.476
#> SRR1947494 2 0.6529 0.27688 0.368 0.620 0.012
#> SRR1947493 1 0.0237 0.88087 0.996 0.000 0.004
#> SRR1947492 1 0.0237 0.88082 0.996 0.004 0.000
#> SRR1947500 2 0.5798 0.44211 0.184 0.776 0.040
#> SRR1947491 2 0.5689 0.44270 0.184 0.780 0.036
#> SRR1947490 1 0.0237 0.88082 0.996 0.004 0.000
#> SRR1947489 1 0.3715 0.80118 0.868 0.128 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.3528 0.7803 0.808 0.000 0.000 0.192
#> SRR1947546 2 0.4059 0.7627 0.000 0.788 0.012 0.200
#> SRR1947545 1 0.0188 0.8768 0.996 0.000 0.000 0.004
#> SRR1947544 4 0.3764 0.7300 0.216 0.000 0.000 0.784
#> SRR1947542 2 0.4059 0.7627 0.000 0.788 0.012 0.200
#> SRR1947541 1 0.3528 0.7803 0.808 0.000 0.000 0.192
#> SRR1947540 4 0.5943 0.3632 0.000 0.360 0.048 0.592
#> SRR1947539 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947538 4 0.0336 0.8539 0.000 0.008 0.000 0.992
#> SRR1947537 3 0.5944 0.6131 0.104 0.000 0.684 0.212
#> SRR1947536 1 0.3697 0.7878 0.852 0.000 0.100 0.048
#> SRR1947535 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947534 1 0.6921 0.0368 0.468 0.424 0.000 0.108
#> SRR1947533 2 0.2174 0.8869 0.000 0.928 0.052 0.020
#> SRR1947532 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947531 4 0.5943 0.3632 0.000 0.360 0.048 0.592
#> SRR1947530 1 0.0817 0.8769 0.976 0.000 0.000 0.024
#> SRR1947529 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947528 1 0.4121 0.7741 0.796 0.000 0.020 0.184
#> SRR1947527 2 0.2408 0.8531 0.000 0.896 0.000 0.104
#> SRR1947526 2 0.2300 0.8792 0.000 0.920 0.064 0.016
#> SRR1947525 4 0.1637 0.8463 0.000 0.060 0.000 0.940
#> SRR1947524 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947523 4 0.2742 0.8571 0.028 0.024 0.032 0.916
#> SRR1947521 3 0.3074 0.7489 0.000 0.152 0.848 0.000
#> SRR1947520 2 0.2918 0.8292 0.000 0.876 0.116 0.008
#> SRR1947519 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947518 4 0.0336 0.8539 0.000 0.008 0.000 0.992
#> SRR1947517 3 0.4877 0.2559 0.408 0.000 0.592 0.000
#> SRR1947516 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947515 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947514 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947513 1 0.5016 0.4327 0.600 0.004 0.000 0.396
#> SRR1947512 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947511 2 0.2918 0.8292 0.000 0.876 0.116 0.008
#> SRR1947510 3 0.3074 0.7489 0.000 0.152 0.848 0.000
#> SRR1947572 4 0.3852 0.7660 0.180 0.012 0.000 0.808
#> SRR1947611 3 0.4564 0.4989 0.000 0.328 0.672 0.000
#> SRR1947509 3 0.4877 0.2559 0.408 0.000 0.592 0.000
#> SRR1947644 3 0.0707 0.8564 0.000 0.000 0.980 0.020
#> SRR1947643 2 0.4957 0.6602 0.000 0.748 0.048 0.204
#> SRR1947642 3 0.2936 0.8532 0.040 0.004 0.900 0.056
#> SRR1947640 4 0.2494 0.8575 0.000 0.036 0.048 0.916
#> SRR1947641 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947639 4 0.1118 0.8517 0.000 0.036 0.000 0.964
#> SRR1947638 1 0.4564 0.5658 0.672 0.000 0.000 0.328
#> SRR1947637 3 0.4564 0.4989 0.000 0.328 0.672 0.000
#> SRR1947636 3 0.5944 0.6131 0.104 0.000 0.684 0.212
#> SRR1947635 4 0.5136 0.7274 0.000 0.224 0.048 0.728
#> SRR1947634 2 0.4331 0.5869 0.000 0.712 0.288 0.000
#> SRR1947633 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947632 2 0.4059 0.7627 0.000 0.788 0.012 0.200
#> SRR1947631 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947629 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947630 2 0.4331 0.5869 0.000 0.712 0.288 0.000
#> SRR1947627 1 0.2675 0.8449 0.908 0.000 0.044 0.048
#> SRR1947628 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947626 2 0.1940 0.8755 0.000 0.924 0.000 0.076
#> SRR1947625 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947624 2 0.4331 0.5869 0.000 0.712 0.288 0.000
#> SRR1947623 4 0.3751 0.7519 0.196 0.004 0.000 0.800
#> SRR1947622 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947621 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947620 1 0.2011 0.8588 0.920 0.000 0.000 0.080
#> SRR1947619 3 0.4144 0.7845 0.104 0.000 0.828 0.068
#> SRR1947617 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947618 1 0.2011 0.8588 0.920 0.000 0.000 0.080
#> SRR1947616 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947615 1 0.3311 0.7893 0.828 0.000 0.000 0.172
#> SRR1947614 3 0.3074 0.7489 0.000 0.152 0.848 0.000
#> SRR1947613 1 0.0336 0.8774 0.992 0.000 0.000 0.008
#> SRR1947610 4 0.0336 0.8539 0.000 0.008 0.000 0.992
#> SRR1947612 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947609 4 0.2269 0.8561 0.028 0.008 0.032 0.932
#> SRR1947608 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947606 1 0.7241 0.4221 0.540 0.000 0.264 0.196
#> SRR1947607 1 0.0707 0.8756 0.980 0.000 0.000 0.020
#> SRR1947604 4 0.1890 0.8581 0.000 0.008 0.056 0.936
#> SRR1947605 1 0.0188 0.8768 0.996 0.000 0.000 0.004
#> SRR1947603 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947602 1 0.0817 0.8769 0.976 0.000 0.000 0.024
#> SRR1947600 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947601 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947598 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947599 4 0.4129 0.8118 0.132 0.008 0.032 0.828
#> SRR1947597 2 0.2412 0.8723 0.000 0.908 0.008 0.084
#> SRR1947596 4 0.3764 0.7300 0.216 0.000 0.000 0.784
#> SRR1947595 4 0.2300 0.8584 0.000 0.028 0.048 0.924
#> SRR1947594 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947592 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947591 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947590 4 0.3764 0.7300 0.216 0.000 0.000 0.784
#> SRR1947588 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947587 1 0.3528 0.7803 0.808 0.000 0.000 0.192
#> SRR1947586 2 0.1940 0.8755 0.000 0.924 0.000 0.076
#> SRR1947585 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947584 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947583 4 0.2494 0.8575 0.000 0.036 0.048 0.916
#> SRR1947582 1 0.2011 0.8588 0.920 0.000 0.000 0.080
#> SRR1947580 2 0.1940 0.8755 0.000 0.924 0.000 0.076
#> SRR1947581 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947576 3 0.4564 0.4989 0.000 0.328 0.672 0.000
#> SRR1947575 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947579 3 0.3074 0.7489 0.000 0.152 0.848 0.000
#> SRR1947578 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947573 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947574 4 0.6350 0.5768 0.252 0.112 0.000 0.636
#> SRR1947571 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947577 1 0.2011 0.8588 0.920 0.000 0.000 0.080
#> SRR1947570 1 0.3528 0.7803 0.808 0.000 0.000 0.192
#> SRR1947569 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947566 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947567 4 0.5136 0.7274 0.000 0.224 0.048 0.728
#> SRR1947568 4 0.4224 0.7832 0.144 0.044 0.000 0.812
#> SRR1947564 2 0.0817 0.9029 0.000 0.976 0.000 0.024
#> SRR1947563 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947562 4 0.4614 0.7481 0.000 0.144 0.064 0.792
#> SRR1947565 3 0.5944 0.6131 0.104 0.000 0.684 0.212
#> SRR1947559 2 0.2412 0.8723 0.000 0.908 0.008 0.084
#> SRR1947560 3 0.4564 0.4989 0.000 0.328 0.672 0.000
#> SRR1947561 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947557 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947558 3 0.1743 0.8719 0.000 0.004 0.940 0.056
#> SRR1947556 4 0.3764 0.7300 0.216 0.000 0.000 0.784
#> SRR1947553 4 0.0336 0.8539 0.000 0.008 0.000 0.992
#> SRR1947554 1 0.4130 0.7625 0.828 0.108 0.000 0.064
#> SRR1947555 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947550 4 0.2494 0.8575 0.000 0.036 0.048 0.916
#> SRR1947552 4 0.4129 0.8118 0.132 0.008 0.032 0.828
#> SRR1947549 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947551 3 0.0707 0.8564 0.000 0.000 0.980 0.020
#> SRR1947548 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947506 1 0.1211 0.8742 0.960 0.000 0.000 0.040
#> SRR1947507 1 0.0188 0.8770 0.996 0.000 0.000 0.004
#> SRR1947504 4 0.3908 0.7368 0.212 0.004 0.000 0.784
#> SRR1947503 1 0.4564 0.5658 0.672 0.000 0.000 0.328
#> SRR1947502 2 0.0336 0.9067 0.000 0.992 0.000 0.008
#> SRR1947501 2 0.4059 0.7627 0.000 0.788 0.012 0.200
#> SRR1947499 1 0.0817 0.8769 0.976 0.000 0.000 0.024
#> SRR1947498 3 0.1557 0.8719 0.000 0.000 0.944 0.056
#> SRR1947508 1 0.2578 0.8512 0.912 0.000 0.036 0.052
#> SRR1947505 4 0.2048 0.8570 0.000 0.008 0.064 0.928
#> SRR1947497 2 0.2174 0.8869 0.000 0.928 0.052 0.020
#> SRR1947496 1 0.0336 0.8774 0.992 0.000 0.000 0.008
#> SRR1947495 2 0.2174 0.8869 0.000 0.928 0.052 0.020
#> SRR1947494 4 0.4680 0.8127 0.124 0.008 0.064 0.804
#> SRR1947493 1 0.0921 0.8766 0.972 0.000 0.000 0.028
#> SRR1947492 1 0.0336 0.8774 0.992 0.000 0.000 0.008
#> SRR1947500 4 0.4801 0.7620 0.000 0.188 0.048 0.764
#> SRR1947491 4 0.5136 0.7274 0.000 0.224 0.048 0.728
#> SRR1947490 1 0.0707 0.8756 0.980 0.000 0.000 0.020
#> SRR1947489 1 0.3311 0.7893 0.828 0.000 0.000 0.172
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 1 0.3141 0.4698 0.832 0.000 0.016 0.152 0.000
#> SRR1947546 2 0.4039 0.7342 0.000 0.776 0.036 0.184 0.004
#> SRR1947545 1 0.1671 0.3654 0.924 0.000 0.000 0.000 0.076
#> SRR1947544 4 0.4138 0.7207 0.160 0.000 0.000 0.776 0.064
#> SRR1947542 2 0.4039 0.7342 0.000 0.776 0.036 0.184 0.004
#> SRR1947541 1 0.3141 0.4698 0.832 0.000 0.016 0.152 0.000
#> SRR1947540 4 0.5447 0.3736 0.000 0.356 0.072 0.572 0.000
#> SRR1947539 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947538 4 0.0609 0.8475 0.000 0.000 0.020 0.980 0.000
#> SRR1947537 3 0.4789 0.6246 0.116 0.000 0.728 0.156 0.000
#> SRR1947536 1 0.3320 0.3845 0.844 0.000 0.124 0.016 0.016
#> SRR1947535 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947534 2 0.8057 -0.0997 0.236 0.412 0.000 0.116 0.236
#> SRR1947533 2 0.2395 0.8520 0.000 0.912 0.048 0.016 0.024
#> SRR1947532 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947531 4 0.5447 0.3736 0.000 0.356 0.072 0.572 0.000
#> SRR1947530 1 0.0671 0.4449 0.980 0.000 0.000 0.004 0.016
#> SRR1947529 2 0.0566 0.8717 0.000 0.984 0.000 0.012 0.004
#> SRR1947528 1 0.3412 0.4623 0.820 0.000 0.028 0.152 0.000
#> SRR1947527 2 0.2561 0.8300 0.000 0.884 0.000 0.096 0.020
#> SRR1947526 2 0.3831 0.8027 0.000 0.824 0.048 0.016 0.112
#> SRR1947525 4 0.2103 0.8399 0.000 0.056 0.020 0.920 0.004
#> SRR1947524 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947523 4 0.2625 0.8507 0.028 0.016 0.056 0.900 0.000
#> SRR1947521 3 0.4774 0.5951 0.000 0.020 0.556 0.000 0.424
#> SRR1947520 2 0.4220 0.7479 0.000 0.768 0.048 0.004 0.180
#> SRR1947519 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947518 4 0.0609 0.8475 0.000 0.000 0.020 0.980 0.000
#> SRR1947517 1 0.6767 0.0713 0.392 0.000 0.328 0.000 0.280
#> SRR1947516 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947515 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947514 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947513 1 0.5029 0.1569 0.592 0.000 0.020 0.376 0.012
#> SRR1947512 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947511 2 0.4220 0.7479 0.000 0.768 0.048 0.004 0.180
#> SRR1947510 3 0.4774 0.5951 0.000 0.020 0.556 0.000 0.424
#> SRR1947572 4 0.3421 0.7653 0.016 0.008 0.000 0.824 0.152
#> SRR1947611 3 0.6275 0.5154 0.000 0.180 0.520 0.000 0.300
#> SRR1947509 1 0.6767 0.0713 0.392 0.000 0.328 0.000 0.280
#> SRR1947644 3 0.0703 0.8424 0.000 0.000 0.976 0.000 0.024
#> SRR1947643 2 0.4337 0.6413 0.000 0.744 0.052 0.204 0.000
#> SRR1947642 3 0.1605 0.8346 0.040 0.000 0.944 0.012 0.004
#> SRR1947640 4 0.2388 0.8523 0.000 0.028 0.072 0.900 0.000
#> SRR1947641 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947639 4 0.1646 0.8455 0.000 0.032 0.020 0.944 0.004
#> SRR1947638 1 0.5811 0.1985 0.552 0.000 0.000 0.340 0.108
#> SRR1947637 3 0.6275 0.5154 0.000 0.180 0.520 0.000 0.300
#> SRR1947636 3 0.4789 0.6246 0.116 0.000 0.728 0.156 0.000
#> SRR1947635 4 0.4555 0.7366 0.000 0.212 0.052 0.732 0.004
#> SRR1947634 2 0.6049 0.4723 0.000 0.564 0.164 0.000 0.272
#> SRR1947633 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947632 2 0.4039 0.7342 0.000 0.776 0.036 0.184 0.004
#> SRR1947631 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947629 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947630 2 0.6049 0.4723 0.000 0.564 0.164 0.000 0.272
#> SRR1947627 1 0.2444 0.4373 0.904 0.000 0.068 0.012 0.016
#> SRR1947628 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947626 2 0.2006 0.8472 0.000 0.916 0.000 0.072 0.012
#> SRR1947625 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947624 2 0.6049 0.4723 0.000 0.564 0.164 0.000 0.272
#> SRR1947623 4 0.3304 0.7524 0.016 0.000 0.000 0.816 0.168
#> SRR1947622 2 0.0566 0.8717 0.000 0.984 0.000 0.012 0.004
#> SRR1947621 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947620 1 0.3967 0.3083 0.800 0.000 0.000 0.092 0.108
#> SRR1947619 3 0.2624 0.7678 0.116 0.000 0.872 0.012 0.000
#> SRR1947617 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947618 1 0.3967 0.3083 0.800 0.000 0.000 0.092 0.108
#> SRR1947616 2 0.0798 0.8690 0.000 0.976 0.000 0.008 0.016
#> SRR1947615 1 0.2605 0.4664 0.852 0.000 0.000 0.148 0.000
#> SRR1947614 3 0.4774 0.5951 0.000 0.020 0.556 0.000 0.424
#> SRR1947613 5 0.4821 0.9005 0.464 0.000 0.000 0.020 0.516
#> SRR1947610 4 0.0609 0.8475 0.000 0.000 0.020 0.980 0.000
#> SRR1947612 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947609 4 0.2124 0.8494 0.028 0.000 0.056 0.916 0.000
#> SRR1947608 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947606 1 0.6056 0.2614 0.556 0.000 0.288 0.156 0.000
#> SRR1947607 5 0.4894 0.8992 0.456 0.000 0.000 0.024 0.520
#> SRR1947604 4 0.1732 0.8519 0.000 0.000 0.080 0.920 0.000
#> SRR1947605 1 0.1671 0.3654 0.924 0.000 0.000 0.000 0.076
#> SRR1947603 2 0.0566 0.8717 0.000 0.984 0.000 0.012 0.004
#> SRR1947602 1 0.0671 0.4449 0.980 0.000 0.000 0.004 0.016
#> SRR1947600 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947601 2 0.0798 0.8690 0.000 0.976 0.000 0.008 0.016
#> SRR1947598 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947599 4 0.3664 0.8140 0.056 0.000 0.036 0.848 0.060
#> SRR1947597 2 0.2248 0.8417 0.000 0.900 0.012 0.088 0.000
#> SRR1947596 4 0.4138 0.7207 0.160 0.000 0.000 0.776 0.064
#> SRR1947595 4 0.2208 0.8531 0.000 0.020 0.072 0.908 0.000
#> SRR1947594 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947592 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947591 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947590 4 0.4138 0.7207 0.160 0.000 0.000 0.776 0.064
#> SRR1947588 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947587 1 0.3141 0.4698 0.832 0.000 0.016 0.152 0.000
#> SRR1947586 2 0.2006 0.8472 0.000 0.916 0.000 0.072 0.012
#> SRR1947585 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947584 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947583 4 0.2388 0.8523 0.000 0.028 0.072 0.900 0.000
#> SRR1947582 1 0.3967 0.3083 0.800 0.000 0.000 0.092 0.108
#> SRR1947580 2 0.2006 0.8472 0.000 0.916 0.000 0.072 0.012
#> SRR1947581 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947576 3 0.6275 0.5154 0.000 0.180 0.520 0.000 0.300
#> SRR1947575 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947579 3 0.4774 0.5951 0.000 0.020 0.556 0.000 0.424
#> SRR1947578 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947573 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947574 4 0.6252 0.6188 0.088 0.104 0.000 0.660 0.148
#> SRR1947571 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947577 1 0.3967 0.3083 0.800 0.000 0.000 0.092 0.108
#> SRR1947570 1 0.3141 0.4698 0.832 0.000 0.016 0.152 0.000
#> SRR1947569 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947566 2 0.0798 0.8690 0.000 0.976 0.000 0.008 0.016
#> SRR1947567 4 0.4555 0.7366 0.000 0.212 0.052 0.732 0.004
#> SRR1947568 4 0.3682 0.7778 0.012 0.040 0.000 0.828 0.120
#> SRR1947564 2 0.0794 0.8696 0.000 0.972 0.000 0.028 0.000
#> SRR1947563 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947562 4 0.4291 0.7585 0.000 0.136 0.092 0.772 0.000
#> SRR1947565 3 0.4789 0.6246 0.116 0.000 0.728 0.156 0.000
#> SRR1947559 2 0.2248 0.8417 0.000 0.900 0.012 0.088 0.000
#> SRR1947560 3 0.6275 0.5154 0.000 0.180 0.520 0.000 0.300
#> SRR1947561 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947557 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947558 3 0.0566 0.8604 0.000 0.000 0.984 0.012 0.004
#> SRR1947556 4 0.4138 0.7207 0.160 0.000 0.000 0.776 0.064
#> SRR1947553 4 0.0609 0.8475 0.000 0.000 0.020 0.980 0.000
#> SRR1947554 5 0.7139 0.6112 0.360 0.104 0.000 0.072 0.464
#> SRR1947555 2 0.0566 0.8717 0.000 0.984 0.000 0.012 0.004
#> SRR1947550 4 0.2388 0.8523 0.000 0.028 0.072 0.900 0.000
#> SRR1947552 4 0.3664 0.8140 0.056 0.000 0.036 0.848 0.060
#> SRR1947549 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947551 3 0.0703 0.8424 0.000 0.000 0.976 0.000 0.024
#> SRR1947548 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947506 1 0.0579 0.4483 0.984 0.000 0.008 0.008 0.000
#> SRR1947507 1 0.4278 -0.6625 0.548 0.000 0.000 0.000 0.452
#> SRR1947504 4 0.3456 0.7385 0.016 0.000 0.000 0.800 0.184
#> SRR1947503 1 0.5811 0.1985 0.552 0.000 0.000 0.340 0.108
#> SRR1947502 2 0.0404 0.8716 0.000 0.988 0.000 0.012 0.000
#> SRR1947501 2 0.4039 0.7342 0.000 0.776 0.036 0.184 0.004
#> SRR1947499 1 0.0671 0.4449 0.980 0.000 0.000 0.004 0.016
#> SRR1947498 3 0.0404 0.8608 0.000 0.000 0.988 0.012 0.000
#> SRR1947508 1 0.2199 0.4410 0.916 0.000 0.060 0.008 0.016
#> SRR1947505 4 0.1908 0.8507 0.000 0.000 0.092 0.908 0.000
#> SRR1947497 2 0.2395 0.8520 0.000 0.912 0.048 0.016 0.024
#> SRR1947496 5 0.4821 0.9005 0.464 0.000 0.000 0.020 0.516
#> SRR1947495 2 0.2395 0.8520 0.000 0.912 0.048 0.016 0.024
#> SRR1947494 4 0.4089 0.8153 0.032 0.000 0.072 0.820 0.076
#> SRR1947493 1 0.0162 0.4413 0.996 0.000 0.000 0.004 0.000
#> SRR1947492 5 0.4821 0.9005 0.464 0.000 0.000 0.020 0.516
#> SRR1947500 4 0.4252 0.7717 0.000 0.176 0.052 0.768 0.004
#> SRR1947491 4 0.4555 0.7366 0.000 0.212 0.052 0.732 0.004
#> SRR1947490 5 0.4894 0.8992 0.456 0.000 0.000 0.024 0.520
#> SRR1947489 1 0.2605 0.4664 0.852 0.000 0.000 0.148 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.2536 0.750 0.000 0.000 0.020 0.116 0.000 0.864
#> SRR1947546 2 0.3409 0.702 0.000 0.780 0.028 0.192 0.000 0.000
#> SRR1947545 6 0.3799 0.641 0.276 0.000 0.000 0.000 0.020 0.704
#> SRR1947544 4 0.4218 0.725 0.116 0.000 0.000 0.768 0.020 0.096
#> SRR1947542 2 0.3409 0.702 0.000 0.780 0.028 0.192 0.000 0.000
#> SRR1947541 6 0.2536 0.750 0.000 0.000 0.020 0.116 0.000 0.864
#> SRR1947540 4 0.5539 0.421 0.012 0.324 0.060 0.580 0.024 0.000
#> SRR1947539 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947538 4 0.0260 0.841 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947537 3 0.4232 0.634 0.000 0.000 0.736 0.116 0.000 0.148
#> SRR1947536 6 0.4128 0.677 0.056 0.000 0.136 0.000 0.032 0.776
#> SRR1947535 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 1 0.6765 0.135 0.420 0.376 0.000 0.084 0.116 0.004
#> SRR1947533 2 0.2257 0.826 0.028 0.904 0.000 0.004 0.060 0.004
#> SRR1947532 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947531 4 0.5539 0.421 0.012 0.324 0.060 0.580 0.024 0.000
#> SRR1947530 6 0.1984 0.746 0.056 0.000 0.000 0.000 0.032 0.912
#> SRR1947529 2 0.0291 0.853 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1947528 6 0.2771 0.743 0.000 0.000 0.032 0.116 0.000 0.852
#> SRR1947527 2 0.3322 0.787 0.028 0.848 0.000 0.076 0.044 0.004
#> SRR1947526 2 0.3580 0.710 0.028 0.772 0.000 0.004 0.196 0.000
#> SRR1947525 4 0.2128 0.828 0.004 0.064 0.008 0.912 0.004 0.008
#> SRR1947524 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947523 4 0.2327 0.845 0.008 0.012 0.044 0.908 0.000 0.028
#> SRR1947521 5 0.3791 0.805 0.000 0.004 0.180 0.000 0.768 0.048
#> SRR1947520 2 0.3929 0.615 0.028 0.700 0.000 0.000 0.272 0.000
#> SRR1947519 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947518 4 0.0260 0.841 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947517 5 0.5449 0.307 0.000 0.000 0.120 0.000 0.456 0.424
#> SRR1947516 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947515 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947514 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947513 6 0.5995 0.403 0.152 0.000 0.008 0.388 0.004 0.448
#> SRR1947512 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947511 2 0.3929 0.615 0.028 0.700 0.000 0.000 0.272 0.000
#> SRR1947510 5 0.3791 0.805 0.000 0.004 0.180 0.000 0.768 0.048
#> SRR1947572 4 0.4050 0.753 0.108 0.016 0.000 0.792 0.076 0.008
#> SRR1947611 5 0.4377 0.791 0.000 0.120 0.160 0.000 0.720 0.000
#> SRR1947509 5 0.5449 0.307 0.000 0.000 0.120 0.000 0.456 0.424
#> SRR1947644 3 0.2527 0.742 0.000 0.000 0.832 0.000 0.168 0.000
#> SRR1947643 2 0.4742 0.612 0.012 0.720 0.052 0.192 0.024 0.000
#> SRR1947642 3 0.0937 0.893 0.000 0.000 0.960 0.000 0.000 0.040
#> SRR1947640 4 0.2164 0.847 0.012 0.020 0.060 0.908 0.000 0.000
#> SRR1947641 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 4 0.1742 0.835 0.004 0.040 0.008 0.936 0.004 0.008
#> SRR1947638 6 0.6495 0.471 0.116 0.000 0.000 0.328 0.076 0.480
#> SRR1947637 5 0.4377 0.791 0.000 0.120 0.160 0.000 0.720 0.000
#> SRR1947636 3 0.4232 0.634 0.000 0.000 0.736 0.116 0.000 0.148
#> SRR1947635 4 0.4297 0.738 0.012 0.204 0.056 0.728 0.000 0.000
#> SRR1947634 2 0.3868 0.151 0.000 0.504 0.000 0.000 0.496 0.000
#> SRR1947633 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947632 2 0.3409 0.702 0.000 0.780 0.028 0.192 0.000 0.000
#> SRR1947631 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947630 2 0.3868 0.151 0.000 0.504 0.000 0.000 0.496 0.000
#> SRR1947627 6 0.3444 0.725 0.056 0.000 0.076 0.000 0.032 0.836
#> SRR1947628 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947626 2 0.2811 0.807 0.028 0.880 0.000 0.060 0.028 0.004
#> SRR1947625 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.3868 0.151 0.000 0.504 0.000 0.000 0.496 0.000
#> SRR1947623 4 0.3784 0.745 0.124 0.000 0.000 0.792 0.076 0.008
#> SRR1947622 2 0.0291 0.853 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1947621 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947620 6 0.5650 0.645 0.208 0.000 0.000 0.080 0.076 0.636
#> SRR1947619 3 0.2048 0.816 0.000 0.000 0.880 0.000 0.000 0.120
#> SRR1947617 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947618 6 0.5650 0.645 0.208 0.000 0.000 0.080 0.076 0.636
#> SRR1947616 2 0.0458 0.849 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1947615 6 0.2003 0.750 0.000 0.000 0.000 0.116 0.000 0.884
#> SRR1947614 5 0.3791 0.805 0.000 0.004 0.180 0.000 0.768 0.048
#> SRR1947613 1 0.2401 0.857 0.892 0.000 0.000 0.008 0.072 0.028
#> SRR1947610 4 0.0260 0.841 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947612 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947609 4 0.1777 0.845 0.000 0.000 0.044 0.928 0.004 0.024
#> SRR1947608 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947606 6 0.5148 0.436 0.000 0.000 0.296 0.116 0.000 0.588
#> SRR1947607 1 0.2563 0.855 0.880 0.000 0.000 0.008 0.084 0.028
#> SRR1947604 4 0.1387 0.848 0.000 0.000 0.068 0.932 0.000 0.000
#> SRR1947605 6 0.3799 0.641 0.276 0.000 0.000 0.000 0.020 0.704
#> SRR1947603 2 0.0291 0.853 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1947602 6 0.1984 0.746 0.056 0.000 0.000 0.000 0.032 0.912
#> SRR1947600 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947601 2 0.0458 0.849 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1947598 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947599 4 0.3704 0.810 0.024 0.000 0.036 0.836 0.064 0.040
#> SRR1947597 2 0.1967 0.815 0.000 0.904 0.012 0.084 0.000 0.000
#> SRR1947596 4 0.4218 0.725 0.116 0.000 0.000 0.768 0.020 0.096
#> SRR1947595 4 0.1983 0.848 0.012 0.012 0.060 0.916 0.000 0.000
#> SRR1947594 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947592 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947591 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947590 4 0.4218 0.725 0.116 0.000 0.000 0.768 0.020 0.096
#> SRR1947588 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947587 6 0.2536 0.750 0.000 0.000 0.020 0.116 0.000 0.864
#> SRR1947586 2 0.2811 0.807 0.028 0.880 0.000 0.060 0.028 0.004
#> SRR1947585 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947584 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947583 4 0.2164 0.847 0.012 0.020 0.060 0.908 0.000 0.000
#> SRR1947582 6 0.5650 0.645 0.208 0.000 0.000 0.080 0.076 0.636
#> SRR1947580 2 0.2811 0.807 0.028 0.880 0.000 0.060 0.028 0.004
#> SRR1947581 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947576 5 0.4377 0.791 0.000 0.120 0.160 0.000 0.720 0.000
#> SRR1947575 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 5 0.3791 0.805 0.000 0.004 0.180 0.000 0.768 0.048
#> SRR1947578 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947573 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947574 4 0.6126 0.620 0.164 0.076 0.000 0.640 0.092 0.028
#> SRR1947571 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947577 6 0.5650 0.645 0.208 0.000 0.000 0.080 0.076 0.636
#> SRR1947570 6 0.2536 0.750 0.000 0.000 0.020 0.116 0.000 0.864
#> SRR1947569 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947566 2 0.0458 0.849 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1947567 4 0.4297 0.738 0.012 0.204 0.056 0.728 0.000 0.000
#> SRR1947568 4 0.4193 0.764 0.072 0.048 0.000 0.796 0.076 0.008
#> SRR1947564 2 0.0632 0.849 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1947563 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947562 4 0.3707 0.754 0.000 0.136 0.080 0.784 0.000 0.000
#> SRR1947565 3 0.4232 0.634 0.000 0.000 0.736 0.116 0.000 0.148
#> SRR1947559 2 0.1967 0.815 0.000 0.904 0.012 0.084 0.000 0.000
#> SRR1947560 5 0.4377 0.791 0.000 0.120 0.160 0.000 0.720 0.000
#> SRR1947561 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947557 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947558 3 0.0000 0.931 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 4 0.4218 0.725 0.116 0.000 0.000 0.768 0.020 0.096
#> SRR1947553 4 0.0260 0.841 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947554 1 0.4539 0.739 0.768 0.076 0.000 0.048 0.100 0.008
#> SRR1947555 2 0.0291 0.853 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1947550 4 0.2164 0.847 0.012 0.020 0.060 0.908 0.000 0.000
#> SRR1947552 4 0.3704 0.810 0.024 0.000 0.036 0.836 0.064 0.040
#> SRR1947549 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947551 3 0.2527 0.742 0.000 0.000 0.832 0.000 0.168 0.000
#> SRR1947548 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947506 6 0.2620 0.746 0.108 0.000 0.012 0.000 0.012 0.868
#> SRR1947507 1 0.1204 0.873 0.944 0.000 0.000 0.000 0.000 0.056
#> SRR1947504 4 0.3943 0.731 0.140 0.000 0.000 0.776 0.076 0.008
#> SRR1947503 6 0.6495 0.471 0.116 0.000 0.000 0.328 0.076 0.480
#> SRR1947502 2 0.0146 0.853 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947501 2 0.3409 0.702 0.000 0.780 0.028 0.192 0.000 0.000
#> SRR1947499 6 0.1984 0.746 0.056 0.000 0.000 0.000 0.032 0.912
#> SRR1947498 3 0.0146 0.932 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947508 6 0.3278 0.730 0.056 0.000 0.064 0.000 0.032 0.848
#> SRR1947505 4 0.1556 0.847 0.000 0.000 0.080 0.920 0.000 0.000
#> SRR1947497 2 0.2257 0.826 0.028 0.904 0.000 0.004 0.060 0.004
#> SRR1947496 1 0.2401 0.857 0.892 0.000 0.000 0.008 0.072 0.028
#> SRR1947495 2 0.2257 0.826 0.028 0.904 0.000 0.004 0.060 0.004
#> SRR1947494 4 0.4040 0.808 0.028 0.000 0.072 0.808 0.076 0.016
#> SRR1947493 6 0.2266 0.743 0.108 0.000 0.000 0.000 0.012 0.880
#> SRR1947492 1 0.2401 0.857 0.892 0.000 0.000 0.008 0.072 0.028
#> SRR1947500 4 0.4017 0.769 0.012 0.168 0.056 0.764 0.000 0.000
#> SRR1947491 4 0.4297 0.738 0.012 0.204 0.056 0.728 0.000 0.000
#> SRR1947490 1 0.2563 0.855 0.880 0.000 0.000 0.008 0.084 0.028
#> SRR1947489 6 0.2003 0.750 0.000 0.000 0.000 0.116 0.000 0.884
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 15148 rows and 152 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 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 0.299 0.625 0.802 0.4621 0.535 0.535
#> 3 3 0.907 0.918 0.963 0.4194 0.680 0.468
#> 4 4 0.686 0.774 0.814 0.1128 0.867 0.638
#> 5 5 0.776 0.662 0.828 0.0724 0.983 0.935
#> 6 6 0.772 0.763 0.810 0.0419 0.916 0.675
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
#> SRR1947547 1 0.7219 0.6998 0.800 0.200
#> SRR1947546 2 0.7219 0.7533 0.200 0.800
#> SRR1947545 1 0.0000 0.7885 1.000 0.000
#> SRR1947544 1 0.0000 0.7885 1.000 0.000
#> SRR1947542 2 0.7219 0.7533 0.200 0.800
#> SRR1947541 1 0.7219 0.6998 0.800 0.200
#> SRR1947540 2 0.7219 0.7533 0.200 0.800
#> SRR1947539 2 0.8661 0.4302 0.288 0.712
#> SRR1947538 2 0.9815 0.5540 0.420 0.580
#> SRR1947537 2 0.9170 0.3445 0.332 0.668
#> SRR1947536 1 0.8144 0.6670 0.748 0.252
#> SRR1947535 2 0.8661 0.4302 0.288 0.712
#> SRR1947534 1 0.6247 0.5960 0.844 0.156
#> SRR1947533 2 0.7219 0.7533 0.200 0.800
#> SRR1947532 1 0.9460 -0.0352 0.636 0.364
#> SRR1947531 2 0.7219 0.7533 0.200 0.800
#> SRR1947530 1 0.7219 0.6998 0.800 0.200
#> SRR1947529 2 0.7219 0.7533 0.200 0.800
#> SRR1947528 1 0.7219 0.6998 0.800 0.200
#> SRR1947527 2 0.7219 0.7533 0.200 0.800
#> SRR1947526 2 0.7219 0.7533 0.200 0.800
#> SRR1947525 2 0.7219 0.7533 0.200 0.800
#> SRR1947524 2 0.8661 0.4302 0.288 0.712
#> SRR1947523 2 0.9754 0.5783 0.408 0.592
#> SRR1947521 2 0.8661 0.4302 0.288 0.712
#> SRR1947520 2 0.7219 0.7533 0.200 0.800
#> SRR1947519 2 0.8661 0.4302 0.288 0.712
#> SRR1947518 2 0.9963 0.4656 0.464 0.536
#> SRR1947517 1 0.9881 0.3919 0.564 0.436
#> SRR1947516 2 0.7219 0.7533 0.200 0.800
#> SRR1947515 1 0.9710 -0.1747 0.600 0.400
#> SRR1947514 2 0.7219 0.7533 0.200 0.800
#> SRR1947513 1 0.1414 0.7814 0.980 0.020
#> SRR1947512 1 0.0672 0.7879 0.992 0.008
#> SRR1947511 2 0.7219 0.7533 0.200 0.800
#> SRR1947510 2 0.6887 0.5426 0.184 0.816
#> SRR1947572 1 1.0000 -0.3838 0.504 0.496
#> SRR1947611 2 0.1414 0.6342 0.020 0.980
#> SRR1947509 1 0.8327 0.6565 0.736 0.264
#> SRR1947644 2 0.8661 0.4302 0.288 0.712
#> SRR1947643 2 0.7219 0.7533 0.200 0.800
#> SRR1947642 2 0.8661 0.4302 0.288 0.712
#> SRR1947640 2 0.9608 0.5865 0.384 0.616
#> SRR1947641 2 0.8555 0.4408 0.280 0.720
#> SRR1947639 2 0.8608 0.6741 0.284 0.716
#> SRR1947638 1 0.1414 0.7814 0.980 0.020
#> SRR1947637 2 0.1414 0.6342 0.020 0.980
#> SRR1947636 2 0.9087 0.3611 0.324 0.676
#> SRR1947635 2 0.7219 0.7533 0.200 0.800
#> SRR1947634 2 0.7219 0.7533 0.200 0.800
#> SRR1947633 2 0.8661 0.4302 0.288 0.712
#> SRR1947632 2 0.7219 0.7533 0.200 0.800
#> SRR1947631 2 0.8661 0.4302 0.288 0.712
#> SRR1947629 2 0.8661 0.4302 0.288 0.712
#> SRR1947630 2 0.7219 0.7533 0.200 0.800
#> SRR1947627 1 0.8144 0.6670 0.748 0.252
#> SRR1947628 2 0.7219 0.7533 0.200 0.800
#> SRR1947626 2 0.7219 0.7533 0.200 0.800
#> SRR1947625 2 0.7602 0.5095 0.220 0.780
#> SRR1947624 2 0.7219 0.7533 0.200 0.800
#> SRR1947623 1 0.1414 0.7814 0.980 0.020
#> SRR1947622 2 0.7219 0.7533 0.200 0.800
#> SRR1947621 2 0.7219 0.7533 0.200 0.800
#> SRR1947620 1 0.0672 0.7879 0.992 0.008
#> SRR1947619 2 0.9170 0.3445 0.332 0.668
#> SRR1947617 2 0.7219 0.7533 0.200 0.800
#> SRR1947618 1 0.0938 0.7861 0.988 0.012
#> SRR1947616 2 0.7219 0.7533 0.200 0.800
#> SRR1947615 1 0.7299 0.6989 0.796 0.204
#> SRR1947614 2 0.8661 0.4302 0.288 0.712
#> SRR1947613 1 0.1414 0.7814 0.980 0.020
#> SRR1947610 2 0.7219 0.7533 0.200 0.800
#> SRR1947612 2 0.7219 0.7533 0.200 0.800
#> SRR1947609 1 0.1414 0.7814 0.980 0.020
#> SRR1947608 2 0.6973 0.5394 0.188 0.812
#> SRR1947606 1 0.7883 0.6787 0.764 0.236
#> SRR1947607 1 0.2948 0.7466 0.948 0.052
#> SRR1947604 1 0.9460 -0.0352 0.636 0.364
#> SRR1947605 1 0.0000 0.7885 1.000 0.000
#> SRR1947603 2 0.7219 0.7533 0.200 0.800
#> SRR1947602 1 0.7219 0.6998 0.800 0.200
#> SRR1947600 2 0.8661 0.4302 0.288 0.712
#> SRR1947601 2 0.7219 0.7533 0.200 0.800
#> SRR1947598 1 0.9944 -0.3464 0.544 0.456
#> SRR1947599 1 0.1414 0.7814 0.980 0.020
#> SRR1947597 2 0.7219 0.7533 0.200 0.800
#> SRR1947596 1 0.6048 0.6085 0.852 0.148
#> SRR1947595 2 0.7453 0.7446 0.212 0.788
#> SRR1947594 1 0.0672 0.7879 0.992 0.008
#> SRR1947592 2 0.8661 0.4302 0.288 0.712
#> SRR1947591 2 0.7219 0.7533 0.200 0.800
#> SRR1947590 1 0.6623 0.5508 0.828 0.172
#> SRR1947588 1 0.0672 0.7879 0.992 0.008
#> SRR1947587 2 0.9661 0.1700 0.392 0.608
#> SRR1947586 2 0.7219 0.7533 0.200 0.800
#> SRR1947585 2 0.8661 0.4302 0.288 0.712
#> SRR1947584 1 0.0000 0.7885 1.000 0.000
#> SRR1947583 2 0.7453 0.7446 0.212 0.788
#> SRR1947582 1 0.0672 0.7879 0.992 0.008
#> SRR1947580 2 0.7219 0.7533 0.200 0.800
#> SRR1947581 1 0.0000 0.7885 1.000 0.000
#> SRR1947576 2 0.1414 0.6342 0.020 0.980
#> SRR1947575 2 0.1414 0.6342 0.020 0.980
#> SRR1947579 2 0.8661 0.4302 0.288 0.712
#> SRR1947578 2 0.7219 0.7533 0.200 0.800
#> SRR1947573 2 0.6973 0.5394 0.188 0.812
#> SRR1947574 2 1.0000 0.3730 0.496 0.504
#> SRR1947571 2 0.9815 0.5540 0.420 0.580
#> SRR1947577 1 0.1184 0.7839 0.984 0.016
#> SRR1947570 1 0.7219 0.6998 0.800 0.200
#> SRR1947569 2 0.8661 0.4302 0.288 0.712
#> SRR1947566 2 0.7219 0.7533 0.200 0.800
#> SRR1947567 2 0.7219 0.7533 0.200 0.800
#> SRR1947568 2 0.8608 0.6741 0.284 0.716
#> SRR1947564 2 0.7219 0.7533 0.200 0.800
#> SRR1947563 2 0.6148 0.5667 0.152 0.848
#> SRR1947562 2 0.7950 0.7203 0.240 0.760
#> SRR1947565 2 0.9087 0.3611 0.324 0.676
#> SRR1947559 2 0.7219 0.7533 0.200 0.800
#> SRR1947560 2 0.1414 0.6342 0.020 0.980
#> SRR1947561 2 0.7219 0.7533 0.200 0.800
#> SRR1947557 1 0.0000 0.7885 1.000 0.000
#> SRR1947558 2 0.8661 0.4302 0.288 0.712
#> SRR1947556 1 0.0000 0.7885 1.000 0.000
#> SRR1947553 2 0.7219 0.7533 0.200 0.800
#> SRR1947554 1 0.1414 0.7814 0.980 0.020
#> SRR1947555 2 0.7219 0.7533 0.200 0.800
#> SRR1947550 2 0.7950 0.7203 0.240 0.760
#> SRR1947552 1 0.6343 0.5961 0.840 0.160
#> SRR1947549 2 0.6973 0.5394 0.188 0.812
#> SRR1947551 2 0.6887 0.5426 0.184 0.816
#> SRR1947548 2 0.9998 0.4430 0.492 0.508
#> SRR1947506 1 0.7219 0.6998 0.800 0.200
#> SRR1947507 1 0.0000 0.7885 1.000 0.000
#> SRR1947504 1 0.0938 0.7861 0.988 0.012
#> SRR1947503 1 0.1414 0.7814 0.980 0.020
#> SRR1947502 2 0.7219 0.7533 0.200 0.800
#> SRR1947501 2 0.7219 0.7533 0.200 0.800
#> SRR1947499 1 0.7219 0.6998 0.800 0.200
#> SRR1947498 2 0.8661 0.4302 0.288 0.712
#> SRR1947508 1 0.8386 0.6528 0.732 0.268
#> SRR1947505 2 0.9732 0.5837 0.404 0.596
#> SRR1947497 2 0.7219 0.7533 0.200 0.800
#> SRR1947496 1 0.0672 0.7879 0.992 0.008
#> SRR1947495 2 0.7219 0.7533 0.200 0.800
#> SRR1947494 1 0.9710 -0.1747 0.600 0.400
#> SRR1947493 1 0.7219 0.6998 0.800 0.200
#> SRR1947492 1 0.0672 0.7879 0.992 0.008
#> SRR1947500 2 0.7219 0.7533 0.200 0.800
#> SRR1947491 2 0.9286 0.6425 0.344 0.656
#> SRR1947490 1 0.1414 0.7814 0.980 0.020
#> SRR1947489 1 0.7219 0.6998 0.800 0.200
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.5706 0.554 0.320 0.000 0.680
#> SRR1947546 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947545 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947544 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947542 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947540 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947539 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947538 2 0.5016 0.707 0.240 0.760 0.000
#> SRR1947537 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947536 3 0.3619 0.850 0.136 0.000 0.864
#> SRR1947535 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947534 1 0.1643 0.932 0.956 0.044 0.000
#> SRR1947533 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947532 2 0.6154 0.385 0.408 0.592 0.000
#> SRR1947531 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947530 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947529 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947528 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947527 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947523 2 0.1289 0.921 0.032 0.968 0.000
#> SRR1947521 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947520 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947518 2 0.5216 0.678 0.260 0.740 0.000
#> SRR1947517 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947516 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947515 2 0.6062 0.445 0.384 0.616 0.000
#> SRR1947514 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947513 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947512 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947511 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947510 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947572 2 0.6180 0.364 0.416 0.584 0.000
#> SRR1947611 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947509 3 0.3686 0.850 0.140 0.000 0.860
#> SRR1947644 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947643 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947640 2 0.1643 0.912 0.044 0.956 0.000
#> SRR1947641 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947639 2 0.0747 0.933 0.016 0.984 0.000
#> SRR1947638 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947637 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947636 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947633 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947632 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947627 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947628 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947624 2 0.0237 0.939 0.004 0.996 0.000
#> SRR1947623 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947622 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947620 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947619 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947618 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947616 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947615 3 0.1643 0.942 0.044 0.000 0.956
#> SRR1947614 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947613 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947610 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947609 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947608 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947607 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947604 2 0.6062 0.445 0.384 0.616 0.000
#> SRR1947605 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947603 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947602 1 0.0892 0.953 0.980 0.000 0.020
#> SRR1947600 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947598 2 0.5016 0.707 0.240 0.760 0.000
#> SRR1947599 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947597 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947596 1 0.4504 0.734 0.804 0.196 0.000
#> SRR1947595 2 0.0237 0.940 0.004 0.996 0.000
#> SRR1947594 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947592 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947590 1 0.4682 0.737 0.804 0.192 0.004
#> SRR1947588 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947587 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947584 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947583 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947582 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947580 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947581 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947576 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947575 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947579 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947578 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947573 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947574 2 0.4887 0.723 0.228 0.772 0.000
#> SRR1947571 2 0.4931 0.718 0.232 0.768 0.000
#> SRR1947577 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947570 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947569 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947567 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947568 2 0.0747 0.933 0.016 0.984 0.000
#> SRR1947564 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947560 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947561 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947557 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947558 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947556 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947553 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947554 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947555 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947550 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947552 1 0.6062 0.309 0.616 0.384 0.000
#> SRR1947549 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947551 3 0.0237 0.980 0.004 0.000 0.996
#> SRR1947548 2 0.5016 0.707 0.240 0.760 0.000
#> SRR1947506 1 0.3816 0.798 0.852 0.000 0.148
#> SRR1947507 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947504 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947503 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947502 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947499 1 0.0892 0.953 0.980 0.000 0.020
#> SRR1947498 3 0.0000 0.981 0.000 0.000 1.000
#> SRR1947508 3 0.3619 0.850 0.136 0.000 0.864
#> SRR1947505 2 0.1289 0.921 0.032 0.968 0.000
#> SRR1947497 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947496 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947495 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947494 2 0.6062 0.445 0.384 0.616 0.000
#> SRR1947493 1 0.0237 0.966 0.996 0.000 0.004
#> SRR1947492 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947500 2 0.0000 0.942 0.000 1.000 0.000
#> SRR1947491 2 0.1163 0.924 0.028 0.972 0.000
#> SRR1947490 1 0.0237 0.969 0.996 0.004 0.000
#> SRR1947489 3 0.1643 0.942 0.044 0.000 0.956
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.6139 0.601 0.100 0.000 0.656 0.244
#> SRR1947546 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947545 1 0.3074 0.843 0.848 0.000 0.000 0.152
#> SRR1947544 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947541 3 0.3356 0.799 0.000 0.000 0.824 0.176
#> SRR1947540 4 0.4996 0.633 0.000 0.484 0.000 0.516
#> SRR1947539 3 0.2647 0.847 0.000 0.000 0.880 0.120
#> SRR1947538 4 0.6483 0.682 0.092 0.324 0.000 0.584
#> SRR1947537 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947536 3 0.6080 0.644 0.160 0.000 0.684 0.156
#> SRR1947535 3 0.0469 0.881 0.000 0.000 0.988 0.012
#> SRR1947534 1 0.3323 0.810 0.876 0.064 0.000 0.060
#> SRR1947533 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.6887 0.570 0.136 0.076 0.100 0.688
#> SRR1947531 4 0.4996 0.633 0.000 0.484 0.000 0.516
#> SRR1947530 1 0.4468 0.808 0.752 0.000 0.016 0.232
#> SRR1947529 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947528 3 0.3266 0.805 0.000 0.000 0.832 0.168
#> SRR1947527 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947525 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947524 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.6467 0.643 0.028 0.188 0.096 0.688
#> SRR1947521 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947520 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947519 3 0.3219 0.810 0.000 0.000 0.836 0.164
#> SRR1947518 4 0.6519 0.681 0.096 0.320 0.000 0.584
#> SRR1947517 3 0.3942 0.800 0.000 0.000 0.764 0.236
#> SRR1947516 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.6927 0.587 0.124 0.088 0.100 0.688
#> SRR1947514 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.4164 0.759 0.736 0.000 0.000 0.264
#> SRR1947512 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947510 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947572 4 0.7458 0.623 0.240 0.252 0.000 0.508
#> SRR1947611 3 0.3942 0.800 0.000 0.000 0.764 0.236
#> SRR1947509 3 0.6867 0.598 0.108 0.000 0.508 0.384
#> SRR1947644 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947643 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947642 3 0.2281 0.849 0.000 0.000 0.904 0.096
#> SRR1947640 4 0.5936 0.678 0.044 0.380 0.000 0.576
#> SRR1947641 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947639 4 0.5590 0.653 0.020 0.456 0.000 0.524
#> SRR1947638 1 0.4222 0.749 0.728 0.000 0.000 0.272
#> SRR1947637 3 0.3942 0.800 0.000 0.000 0.764 0.236
#> SRR1947636 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947635 4 0.4989 0.645 0.000 0.472 0.000 0.528
#> SRR1947634 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947633 3 0.3219 0.829 0.000 0.000 0.836 0.164
#> SRR1947632 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947631 3 0.0707 0.879 0.000 0.000 0.980 0.020
#> SRR1947629 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.1302 0.894 0.000 0.956 0.000 0.044
#> SRR1947627 3 0.3266 0.805 0.000 0.000 0.832 0.168
#> SRR1947628 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947626 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947625 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947624 2 0.1302 0.894 0.000 0.956 0.000 0.044
#> SRR1947623 1 0.1302 0.853 0.956 0.000 0.000 0.044
#> SRR1947622 4 0.5000 0.608 0.000 0.496 0.000 0.504
#> SRR1947621 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.3266 0.835 0.832 0.000 0.000 0.168
#> SRR1947619 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947617 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.4222 0.760 0.728 0.000 0.000 0.272
#> SRR1947616 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947615 3 0.4040 0.733 0.000 0.000 0.752 0.248
#> SRR1947614 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947613 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947612 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947609 4 0.5816 0.421 0.224 0.000 0.088 0.688
#> SRR1947608 3 0.0469 0.881 0.000 0.000 0.988 0.012
#> SRR1947606 3 0.3219 0.807 0.000 0.000 0.836 0.164
#> SRR1947607 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.6929 0.591 0.124 0.092 0.096 0.688
#> SRR1947605 1 0.3074 0.844 0.848 0.000 0.000 0.152
#> SRR1947603 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947602 1 0.5279 0.786 0.716 0.000 0.052 0.232
#> SRR1947600 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.6929 0.628 0.092 0.124 0.096 0.688
#> SRR1947599 4 0.5867 0.427 0.216 0.000 0.096 0.688
#> SRR1947597 2 0.1302 0.889 0.000 0.956 0.000 0.044
#> SRR1947596 4 0.7190 0.273 0.308 0.024 0.096 0.572
#> SRR1947595 4 0.5472 0.661 0.016 0.440 0.000 0.544
#> SRR1947594 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0188 0.881 0.000 0.000 0.996 0.004
#> SRR1947591 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.7050 0.250 0.296 0.008 0.124 0.572
#> SRR1947588 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.1389 0.869 0.000 0.000 0.952 0.048
#> SRR1947586 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947585 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.4992 0.643 0.000 0.476 0.000 0.524
#> SRR1947582 1 0.3311 0.835 0.828 0.000 0.000 0.172
#> SRR1947580 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947581 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.3942 0.800 0.000 0.000 0.764 0.236
#> SRR1947575 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947579 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947578 4 0.4996 0.633 0.000 0.484 0.000 0.516
#> SRR1947573 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947574 4 0.6587 0.681 0.100 0.324 0.000 0.576
#> SRR1947571 4 0.6735 0.680 0.092 0.288 0.012 0.608
#> SRR1947577 1 0.4250 0.755 0.724 0.000 0.000 0.276
#> SRR1947570 1 0.7499 0.495 0.500 0.000 0.256 0.244
#> SRR1947569 3 0.0188 0.881 0.000 0.000 0.996 0.004
#> SRR1947566 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947567 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947568 2 0.4426 0.473 0.024 0.772 0.000 0.204
#> SRR1947564 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947563 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947562 4 0.4977 0.653 0.000 0.460 0.000 0.540
#> SRR1947565 3 0.0336 0.881 0.000 0.000 0.992 0.008
#> SRR1947559 2 0.4985 -0.547 0.000 0.532 0.000 0.468
#> SRR1947560 3 0.3942 0.800 0.000 0.000 0.764 0.236
#> SRR1947561 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0469 0.881 0.000 0.000 0.988 0.012
#> SRR1947556 1 0.1474 0.851 0.948 0.000 0.000 0.052
#> SRR1947553 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947554 1 0.1940 0.836 0.924 0.000 0.000 0.076
#> SRR1947555 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947550 4 0.4981 0.651 0.000 0.464 0.000 0.536
#> SRR1947552 4 0.6758 0.536 0.160 0.056 0.096 0.688
#> SRR1947549 3 0.0188 0.881 0.000 0.000 0.996 0.004
#> SRR1947551 3 0.3907 0.801 0.000 0.000 0.768 0.232
#> SRR1947548 4 0.7373 0.650 0.092 0.164 0.096 0.648
#> SRR1947506 1 0.7771 0.242 0.408 0.000 0.348 0.244
#> SRR1947507 1 0.0188 0.872 0.996 0.000 0.000 0.004
#> SRR1947504 1 0.1302 0.853 0.956 0.000 0.000 0.044
#> SRR1947503 4 0.4543 0.296 0.324 0.000 0.000 0.676
#> SRR1947502 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947501 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947499 1 0.5279 0.786 0.716 0.000 0.052 0.232
#> SRR1947498 3 0.0000 0.881 0.000 0.000 1.000 0.000
#> SRR1947508 3 0.5889 0.653 0.100 0.000 0.688 0.212
#> SRR1947505 4 0.6504 0.644 0.028 0.192 0.096 0.684
#> SRR1947497 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.956 0.000 1.000 0.000 0.000
#> SRR1947494 4 0.6920 0.586 0.128 0.088 0.096 0.688
#> SRR1947493 1 0.4353 0.810 0.756 0.000 0.012 0.232
#> SRR1947492 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.4994 0.639 0.000 0.480 0.000 0.520
#> SRR1947491 4 0.5573 0.677 0.028 0.368 0.000 0.604
#> SRR1947490 1 0.0000 0.873 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.4040 0.733 0.000 0.000 0.752 0.248
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.7332 -0.036791 0.300 0.004 0.492 0.060 0.144
#> SRR1947546 4 0.3058 0.895323 0.000 0.096 0.000 0.860 0.044
#> SRR1947545 1 0.1341 0.608830 0.944 0.000 0.000 0.056 0.000
#> SRR1947544 1 0.4219 0.746124 0.716 0.000 0.000 0.024 0.260
#> SRR1947542 4 0.2754 0.903638 0.000 0.080 0.000 0.880 0.040
#> SRR1947541 3 0.6271 0.184653 0.228 0.004 0.612 0.020 0.136
#> SRR1947540 4 0.3030 0.899298 0.000 0.088 0.004 0.868 0.040
#> SRR1947539 3 0.2648 0.490500 0.000 0.000 0.848 0.000 0.152
#> SRR1947538 4 0.2619 0.908916 0.004 0.052 0.004 0.900 0.040
#> SRR1947537 3 0.1168 0.613510 0.000 0.000 0.960 0.008 0.032
#> SRR1947536 3 0.6347 0.096503 0.272 0.004 0.580 0.016 0.128
#> SRR1947535 3 0.1106 0.617731 0.000 0.000 0.964 0.012 0.024
#> SRR1947534 1 0.5919 0.698999 0.620 0.028 0.000 0.080 0.272
#> SRR1947533 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947532 4 0.2060 0.883133 0.008 0.000 0.016 0.924 0.052
#> SRR1947531 4 0.3289 0.896082 0.000 0.096 0.004 0.852 0.048
#> SRR1947530 1 0.4174 0.450847 0.808 0.004 0.016 0.056 0.116
#> SRR1947529 2 0.2228 0.909722 0.000 0.912 0.000 0.048 0.040
#> SRR1947528 3 0.6200 0.205634 0.216 0.004 0.628 0.024 0.128
#> SRR1947527 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947526 2 0.1168 0.942288 0.000 0.960 0.000 0.008 0.032
#> SRR1947525 4 0.2595 0.909217 0.000 0.080 0.000 0.888 0.032
#> SRR1947524 3 0.0671 0.618286 0.000 0.000 0.980 0.004 0.016
#> SRR1947523 4 0.1659 0.889822 0.004 0.008 0.016 0.948 0.024
#> SRR1947521 3 0.4425 0.000697 0.000 0.004 0.544 0.000 0.452
#> SRR1947520 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947519 3 0.5150 0.381289 0.116 0.000 0.724 0.016 0.144
#> SRR1947518 4 0.2695 0.908404 0.004 0.052 0.004 0.896 0.044
#> SRR1947517 3 0.4425 0.000697 0.000 0.004 0.544 0.000 0.452
#> SRR1947516 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947515 4 0.1934 0.885420 0.004 0.000 0.016 0.928 0.052
#> SRR1947514 2 0.0609 0.946130 0.000 0.980 0.000 0.020 0.000
#> SRR1947513 1 0.3849 0.494300 0.752 0.000 0.000 0.232 0.016
#> SRR1947512 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947511 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947510 3 0.4425 0.000697 0.000 0.004 0.544 0.000 0.452
#> SRR1947572 4 0.4960 0.774064 0.124 0.028 0.000 0.752 0.096
#> SRR1947611 3 0.4437 -0.005408 0.000 0.004 0.532 0.000 0.464
#> SRR1947509 5 0.6625 0.000000 0.260 0.000 0.204 0.012 0.524
#> SRR1947644 3 0.4434 -0.009292 0.000 0.004 0.536 0.000 0.460
#> SRR1947643 2 0.1893 0.935889 0.000 0.928 0.000 0.024 0.048
#> SRR1947642 3 0.2833 0.553728 0.004 0.000 0.864 0.012 0.120
#> SRR1947640 4 0.1809 0.910611 0.000 0.060 0.000 0.928 0.012
#> SRR1947641 3 0.1106 0.618177 0.000 0.000 0.964 0.012 0.024
#> SRR1947639 4 0.2775 0.909553 0.004 0.076 0.000 0.884 0.036
#> SRR1947638 1 0.4114 0.472923 0.712 0.000 0.000 0.272 0.016
#> SRR1947637 3 0.4440 -0.012585 0.000 0.004 0.528 0.000 0.468
#> SRR1947636 3 0.1251 0.611984 0.000 0.000 0.956 0.008 0.036
#> SRR1947635 4 0.2712 0.905927 0.000 0.088 0.000 0.880 0.032
#> SRR1947634 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947633 3 0.2690 0.485549 0.000 0.000 0.844 0.000 0.156
#> SRR1947632 4 0.3003 0.897474 0.000 0.092 0.000 0.864 0.044
#> SRR1947631 3 0.1740 0.606473 0.000 0.000 0.932 0.012 0.056
#> SRR1947629 3 0.0671 0.618286 0.000 0.000 0.980 0.004 0.016
#> SRR1947630 2 0.1408 0.935678 0.000 0.948 0.000 0.008 0.044
#> SRR1947627 3 0.6156 0.202895 0.216 0.004 0.628 0.020 0.132
#> SRR1947628 4 0.2775 0.903713 0.000 0.076 0.004 0.884 0.036
#> SRR1947626 2 0.0992 0.944617 0.000 0.968 0.000 0.024 0.008
#> SRR1947625 3 0.1106 0.618177 0.000 0.000 0.964 0.012 0.024
#> SRR1947624 2 0.1124 0.938699 0.000 0.960 0.000 0.004 0.036
#> SRR1947623 1 0.4786 0.712171 0.652 0.000 0.000 0.040 0.308
#> SRR1947622 4 0.3413 0.877454 0.000 0.124 0.000 0.832 0.044
#> SRR1947621 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947620 1 0.2130 0.593293 0.908 0.000 0.000 0.080 0.012
#> SRR1947619 3 0.1168 0.613510 0.000 0.000 0.960 0.008 0.032
#> SRR1947617 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947618 1 0.3563 0.505406 0.780 0.000 0.000 0.208 0.012
#> SRR1947616 2 0.2387 0.907337 0.000 0.908 0.004 0.048 0.040
#> SRR1947615 3 0.7358 0.049335 0.260 0.004 0.512 0.064 0.160
#> SRR1947614 3 0.4425 0.000697 0.000 0.004 0.544 0.000 0.452
#> SRR1947613 1 0.3942 0.749258 0.728 0.000 0.000 0.012 0.260
#> SRR1947610 4 0.3133 0.906470 0.000 0.080 0.004 0.864 0.052
#> SRR1947612 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947609 4 0.2228 0.875604 0.020 0.000 0.016 0.920 0.044
#> SRR1947608 3 0.1106 0.618177 0.000 0.000 0.964 0.012 0.024
#> SRR1947606 3 0.5818 0.281028 0.176 0.004 0.672 0.020 0.128
#> SRR1947607 1 0.4040 0.743172 0.712 0.000 0.000 0.012 0.276
#> SRR1947604 4 0.1756 0.885542 0.008 0.000 0.016 0.940 0.036
#> SRR1947605 1 0.1341 0.608830 0.944 0.000 0.000 0.056 0.000
#> SRR1947603 2 0.1915 0.923222 0.000 0.928 0.000 0.032 0.040
#> SRR1947602 1 0.5476 0.307901 0.732 0.004 0.092 0.056 0.116
#> SRR1947600 3 0.0671 0.618286 0.000 0.000 0.980 0.004 0.016
#> SRR1947601 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947598 4 0.1560 0.890107 0.004 0.000 0.020 0.948 0.028
#> SRR1947599 4 0.2072 0.877868 0.020 0.000 0.016 0.928 0.036
#> SRR1947597 2 0.3445 0.808393 0.000 0.824 0.000 0.140 0.036
#> SRR1947596 4 0.4751 0.708079 0.188 0.000 0.016 0.740 0.056
#> SRR1947595 4 0.2570 0.908897 0.000 0.084 0.000 0.888 0.028
#> SRR1947594 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947592 3 0.0451 0.618253 0.000 0.000 0.988 0.004 0.008
#> SRR1947591 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947590 4 0.4974 0.686989 0.204 0.000 0.020 0.720 0.056
#> SRR1947588 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947587 3 0.2358 0.560417 0.000 0.000 0.888 0.008 0.104
#> SRR1947586 2 0.1597 0.939971 0.000 0.940 0.000 0.012 0.048
#> SRR1947585 3 0.0671 0.618286 0.000 0.000 0.980 0.004 0.016
#> SRR1947584 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947583 4 0.2540 0.906704 0.000 0.088 0.000 0.888 0.024
#> SRR1947582 1 0.2351 0.590108 0.896 0.000 0.000 0.088 0.016
#> SRR1947580 2 0.1670 0.939086 0.000 0.936 0.000 0.012 0.052
#> SRR1947581 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947576 3 0.4440 -0.012585 0.000 0.004 0.528 0.000 0.468
#> SRR1947575 3 0.1281 0.616584 0.000 0.000 0.956 0.012 0.032
#> SRR1947579 3 0.4425 0.000697 0.000 0.004 0.544 0.000 0.452
#> SRR1947578 4 0.2972 0.899743 0.000 0.084 0.004 0.872 0.040
#> SRR1947573 3 0.0510 0.615197 0.000 0.000 0.984 0.000 0.016
#> SRR1947574 4 0.3012 0.902643 0.008 0.056 0.000 0.876 0.060
#> SRR1947571 4 0.2073 0.899683 0.004 0.016 0.008 0.928 0.044
#> SRR1947577 1 0.3563 0.505406 0.780 0.000 0.000 0.208 0.012
#> SRR1947570 3 0.7452 -0.176543 0.392 0.004 0.404 0.060 0.140
#> SRR1947569 3 0.0671 0.618286 0.000 0.000 0.980 0.004 0.016
#> SRR1947566 2 0.1106 0.942987 0.000 0.964 0.000 0.024 0.012
#> SRR1947567 4 0.2616 0.904082 0.000 0.076 0.000 0.888 0.036
#> SRR1947568 2 0.6070 0.316097 0.024 0.560 0.000 0.340 0.076
#> SRR1947564 2 0.0865 0.945267 0.000 0.972 0.000 0.024 0.004
#> SRR1947563 3 0.1281 0.616584 0.000 0.000 0.956 0.012 0.032
#> SRR1947562 4 0.1768 0.911409 0.000 0.072 0.000 0.924 0.004
#> SRR1947565 3 0.1168 0.613510 0.000 0.000 0.960 0.008 0.032
#> SRR1947559 4 0.3409 0.853269 0.000 0.160 0.000 0.816 0.024
#> SRR1947560 3 0.4437 -0.005408 0.000 0.004 0.532 0.000 0.464
#> SRR1947561 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947557 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947558 3 0.1106 0.617731 0.000 0.000 0.964 0.012 0.024
#> SRR1947556 1 0.4748 0.714705 0.660 0.000 0.000 0.040 0.300
#> SRR1947553 4 0.3133 0.906470 0.000 0.080 0.004 0.864 0.052
#> SRR1947554 1 0.5104 0.717457 0.648 0.000 0.000 0.068 0.284
#> SRR1947555 2 0.0992 0.944066 0.000 0.968 0.000 0.024 0.008
#> SRR1947550 4 0.1608 0.911397 0.000 0.072 0.000 0.928 0.000
#> SRR1947552 4 0.1869 0.883054 0.012 0.000 0.016 0.936 0.036
#> SRR1947549 3 0.0671 0.616683 0.000 0.000 0.980 0.004 0.016
#> SRR1947551 3 0.4434 -0.009292 0.000 0.004 0.536 0.000 0.460
#> SRR1947548 4 0.2220 0.890657 0.004 0.008 0.016 0.920 0.052
#> SRR1947506 1 0.7335 -0.350809 0.428 0.004 0.384 0.060 0.124
#> SRR1947507 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947504 1 0.4797 0.713996 0.660 0.000 0.000 0.044 0.296
#> SRR1947503 4 0.2291 0.866358 0.036 0.000 0.000 0.908 0.056
#> SRR1947502 2 0.0703 0.946215 0.000 0.976 0.000 0.024 0.000
#> SRR1947501 4 0.3003 0.897474 0.000 0.092 0.000 0.864 0.044
#> SRR1947499 1 0.5476 0.307901 0.732 0.004 0.092 0.056 0.116
#> SRR1947498 3 0.0566 0.618830 0.000 0.000 0.984 0.004 0.012
#> SRR1947508 3 0.7217 0.025683 0.276 0.004 0.520 0.060 0.140
#> SRR1947505 4 0.2150 0.897063 0.004 0.016 0.020 0.928 0.032
#> SRR1947497 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947496 1 0.3916 0.749747 0.732 0.000 0.000 0.012 0.256
#> SRR1947495 2 0.1444 0.940626 0.000 0.948 0.000 0.012 0.040
#> SRR1947494 4 0.2060 0.883133 0.008 0.000 0.016 0.924 0.052
#> SRR1947493 1 0.3964 0.462629 0.816 0.004 0.008 0.056 0.116
#> SRR1947492 1 0.3942 0.749258 0.728 0.000 0.000 0.012 0.260
#> SRR1947500 4 0.2540 0.906704 0.000 0.088 0.000 0.888 0.024
#> SRR1947491 4 0.1800 0.908007 0.000 0.048 0.000 0.932 0.020
#> SRR1947490 1 0.3942 0.749258 0.728 0.000 0.000 0.012 0.260
#> SRR1947489 3 0.7284 0.040852 0.268 0.004 0.512 0.056 0.160
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.3964 0.580 0.008 0.000 0.308 0.004 0.004 0.676
#> SRR1947546 4 0.4436 0.775 0.000 0.104 0.000 0.764 0.048 0.084
#> SRR1947545 1 0.4761 -0.162 0.492 0.000 0.000 0.008 0.032 0.468
#> SRR1947544 1 0.1789 0.849 0.924 0.000 0.000 0.000 0.044 0.032
#> SRR1947542 4 0.3156 0.828 0.000 0.024 0.000 0.852 0.044 0.080
#> SRR1947541 6 0.4214 0.327 0.000 0.000 0.460 0.004 0.008 0.528
#> SRR1947540 4 0.3300 0.827 0.000 0.016 0.000 0.840 0.068 0.076
#> SRR1947539 3 0.2743 0.648 0.000 0.000 0.828 0.000 0.164 0.008
#> SRR1947538 4 0.2822 0.843 0.000 0.004 0.000 0.864 0.076 0.056
#> SRR1947537 3 0.1364 0.869 0.000 0.000 0.944 0.004 0.004 0.048
#> SRR1947536 6 0.4679 0.468 0.020 0.000 0.376 0.000 0.020 0.584
#> SRR1947535 3 0.1148 0.877 0.000 0.000 0.960 0.004 0.020 0.016
#> SRR1947534 1 0.4089 0.756 0.812 0.032 0.000 0.076 0.040 0.040
#> SRR1947533 2 0.2912 0.865 0.000 0.852 0.000 0.000 0.072 0.076
#> SRR1947532 4 0.3260 0.829 0.000 0.000 0.004 0.832 0.092 0.072
#> SRR1947531 4 0.3910 0.822 0.000 0.028 0.000 0.800 0.088 0.084
#> SRR1947530 6 0.4408 0.508 0.292 0.000 0.028 0.008 0.004 0.668
#> SRR1947529 2 0.4756 0.729 0.000 0.736 0.000 0.128 0.056 0.080
#> SRR1947528 6 0.4067 0.370 0.000 0.000 0.444 0.000 0.008 0.548
#> SRR1947527 2 0.3072 0.864 0.000 0.840 0.000 0.000 0.084 0.076
#> SRR1947526 2 0.2744 0.867 0.000 0.864 0.000 0.000 0.064 0.072
#> SRR1947525 4 0.2103 0.853 0.000 0.024 0.000 0.916 0.040 0.020
#> SRR1947524 3 0.1408 0.867 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1947523 4 0.3047 0.838 0.000 0.004 0.000 0.848 0.084 0.064
#> SRR1947521 5 0.4039 0.913 0.000 0.000 0.352 0.000 0.632 0.016
#> SRR1947520 2 0.2965 0.864 0.000 0.848 0.000 0.000 0.072 0.080
#> SRR1947519 3 0.3705 0.594 0.000 0.000 0.748 0.004 0.024 0.224
#> SRR1947518 4 0.3165 0.843 0.000 0.008 0.000 0.844 0.076 0.072
#> SRR1947517 5 0.4105 0.911 0.000 0.000 0.348 0.000 0.632 0.020
#> SRR1947516 2 0.0508 0.877 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947515 4 0.3148 0.833 0.000 0.000 0.004 0.840 0.092 0.064
#> SRR1947514 2 0.0767 0.876 0.000 0.976 0.000 0.012 0.008 0.004
#> SRR1947513 6 0.6801 0.275 0.324 0.000 0.000 0.144 0.088 0.444
#> SRR1947512 1 0.0000 0.882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.2965 0.864 0.000 0.848 0.000 0.000 0.072 0.080
#> SRR1947510 5 0.3756 0.912 0.000 0.000 0.352 0.000 0.644 0.004
#> SRR1947572 4 0.5148 0.758 0.108 0.004 0.000 0.716 0.096 0.076
#> SRR1947611 5 0.3912 0.909 0.000 0.000 0.340 0.000 0.648 0.012
#> SRR1947509 5 0.5765 0.150 0.016 0.000 0.112 0.000 0.468 0.404
#> SRR1947644 5 0.3898 0.898 0.000 0.000 0.336 0.000 0.652 0.012
#> SRR1947643 2 0.4270 0.844 0.000 0.772 0.000 0.032 0.096 0.100
#> SRR1947642 3 0.2320 0.828 0.000 0.000 0.892 0.004 0.024 0.080
#> SRR1947640 4 0.2303 0.851 0.000 0.020 0.000 0.904 0.052 0.024
#> SRR1947641 3 0.0951 0.879 0.000 0.000 0.968 0.004 0.020 0.008
#> SRR1947639 4 0.2103 0.853 0.000 0.024 0.000 0.916 0.040 0.020
#> SRR1947638 6 0.6961 0.237 0.324 0.000 0.000 0.188 0.080 0.408
#> SRR1947637 5 0.4078 0.905 0.000 0.000 0.340 0.000 0.640 0.020
#> SRR1947636 3 0.1606 0.863 0.000 0.000 0.932 0.004 0.008 0.056
#> SRR1947635 4 0.3356 0.836 0.000 0.024 0.000 0.840 0.072 0.064
#> SRR1947634 2 0.2965 0.864 0.000 0.848 0.000 0.000 0.072 0.080
#> SRR1947633 3 0.2877 0.634 0.000 0.000 0.820 0.000 0.168 0.012
#> SRR1947632 4 0.4509 0.767 0.000 0.112 0.000 0.756 0.044 0.088
#> SRR1947631 3 0.1708 0.865 0.000 0.000 0.932 0.004 0.024 0.040
#> SRR1947629 3 0.1408 0.867 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1947630 2 0.3068 0.862 0.000 0.840 0.000 0.000 0.072 0.088
#> SRR1947627 6 0.4057 0.385 0.000 0.000 0.436 0.000 0.008 0.556
#> SRR1947628 4 0.2908 0.834 0.000 0.012 0.000 0.864 0.048 0.076
#> SRR1947626 2 0.1710 0.872 0.000 0.936 0.000 0.016 0.028 0.020
#> SRR1947625 3 0.0951 0.879 0.000 0.000 0.968 0.004 0.020 0.008
#> SRR1947624 2 0.2962 0.864 0.000 0.848 0.000 0.000 0.068 0.084
#> SRR1947623 1 0.2532 0.837 0.892 0.000 0.000 0.020 0.036 0.052
#> SRR1947622 4 0.4848 0.739 0.000 0.144 0.000 0.724 0.052 0.080
#> SRR1947621 2 0.0767 0.876 0.000 0.976 0.000 0.012 0.008 0.004
#> SRR1947620 6 0.5646 0.264 0.396 0.000 0.000 0.052 0.048 0.504
#> SRR1947619 3 0.1364 0.869 0.000 0.000 0.944 0.004 0.004 0.048
#> SRR1947617 2 0.0767 0.876 0.000 0.976 0.000 0.012 0.008 0.004
#> SRR1947618 6 0.6648 0.297 0.320 0.000 0.000 0.128 0.084 0.468
#> SRR1947616 2 0.4885 0.728 0.000 0.728 0.000 0.120 0.064 0.088
#> SRR1947615 6 0.4457 0.532 0.000 0.000 0.332 0.012 0.024 0.632
#> SRR1947614 5 0.4039 0.913 0.000 0.000 0.352 0.000 0.632 0.016
#> SRR1947613 1 0.0806 0.877 0.972 0.000 0.000 0.000 0.020 0.008
#> SRR1947610 4 0.3264 0.841 0.000 0.012 0.000 0.840 0.076 0.072
#> SRR1947612 2 0.0767 0.876 0.000 0.976 0.000 0.012 0.008 0.004
#> SRR1947609 4 0.3832 0.809 0.000 0.000 0.000 0.776 0.120 0.104
#> SRR1947608 3 0.1059 0.878 0.000 0.000 0.964 0.004 0.016 0.016
#> SRR1947606 3 0.4009 0.264 0.000 0.000 0.632 0.004 0.008 0.356
#> SRR1947607 1 0.1485 0.868 0.944 0.000 0.000 0.004 0.028 0.024
#> SRR1947604 4 0.3264 0.827 0.000 0.000 0.004 0.832 0.088 0.076
#> SRR1947605 1 0.4697 -0.150 0.500 0.000 0.000 0.008 0.028 0.464
#> SRR1947603 2 0.3966 0.775 0.000 0.800 0.000 0.072 0.040 0.088
#> SRR1947602 6 0.4830 0.557 0.248 0.000 0.072 0.008 0.004 0.668
#> SRR1947600 3 0.1408 0.867 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1947601 2 0.0622 0.877 0.000 0.980 0.000 0.012 0.000 0.008
#> SRR1947598 4 0.2789 0.841 0.000 0.000 0.004 0.864 0.088 0.044
#> SRR1947599 4 0.3607 0.815 0.000 0.000 0.000 0.796 0.112 0.092
#> SRR1947597 2 0.5313 0.573 0.000 0.644 0.000 0.236 0.036 0.084
#> SRR1947596 4 0.5786 0.681 0.064 0.000 0.004 0.644 0.124 0.164
#> SRR1947595 4 0.2818 0.850 0.000 0.024 0.000 0.876 0.052 0.048
#> SRR1947594 1 0.0000 0.882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0551 0.879 0.000 0.000 0.984 0.004 0.008 0.004
#> SRR1947591 2 0.0881 0.877 0.000 0.972 0.000 0.012 0.008 0.008
#> SRR1947590 4 0.5890 0.673 0.076 0.000 0.004 0.636 0.116 0.168
#> SRR1947588 1 0.0000 0.882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.2213 0.815 0.000 0.000 0.888 0.004 0.008 0.100
#> SRR1947586 2 0.3516 0.861 0.000 0.812 0.000 0.004 0.096 0.088
#> SRR1947585 3 0.1408 0.867 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1947584 1 0.0146 0.882 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947583 4 0.2818 0.847 0.000 0.024 0.000 0.876 0.048 0.052
#> SRR1947582 6 0.5637 0.264 0.392 0.000 0.000 0.056 0.044 0.508
#> SRR1947580 2 0.3838 0.849 0.000 0.784 0.000 0.004 0.116 0.096
#> SRR1947581 1 0.0146 0.882 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947576 5 0.3912 0.909 0.000 0.000 0.340 0.000 0.648 0.012
#> SRR1947575 3 0.1642 0.865 0.000 0.000 0.936 0.004 0.032 0.028
#> SRR1947579 5 0.4039 0.913 0.000 0.000 0.352 0.000 0.632 0.016
#> SRR1947578 4 0.3300 0.827 0.000 0.016 0.000 0.840 0.068 0.076
#> SRR1947573 3 0.1168 0.871 0.000 0.000 0.956 0.000 0.028 0.016
#> SRR1947574 4 0.4419 0.822 0.000 0.020 0.000 0.748 0.136 0.096
#> SRR1947571 4 0.2794 0.839 0.000 0.000 0.000 0.860 0.080 0.060
#> SRR1947577 6 0.6664 0.291 0.328 0.000 0.000 0.128 0.084 0.460
#> SRR1947570 6 0.4400 0.606 0.032 0.000 0.276 0.008 0.004 0.680
#> SRR1947569 3 0.1408 0.867 0.000 0.000 0.944 0.000 0.036 0.020
#> SRR1947566 2 0.1657 0.865 0.000 0.936 0.000 0.012 0.012 0.040
#> SRR1947567 4 0.2916 0.831 0.000 0.012 0.000 0.864 0.052 0.072
#> SRR1947568 2 0.6550 0.296 0.052 0.512 0.000 0.328 0.068 0.040
#> SRR1947564 2 0.1448 0.870 0.000 0.948 0.000 0.016 0.012 0.024
#> SRR1947563 3 0.1313 0.874 0.000 0.000 0.952 0.004 0.028 0.016
#> SRR1947562 4 0.0964 0.857 0.000 0.012 0.000 0.968 0.016 0.004
#> SRR1947565 3 0.1364 0.869 0.000 0.000 0.944 0.004 0.004 0.048
#> SRR1947559 4 0.4485 0.721 0.000 0.188 0.000 0.728 0.024 0.060
#> SRR1947560 5 0.3912 0.909 0.000 0.000 0.340 0.000 0.648 0.012
#> SRR1947561 2 0.0508 0.877 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947557 1 0.0146 0.882 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1947558 3 0.1148 0.877 0.000 0.000 0.960 0.004 0.020 0.016
#> SRR1947556 1 0.2322 0.831 0.904 0.000 0.000 0.024 0.048 0.024
#> SRR1947553 4 0.3264 0.841 0.000 0.012 0.000 0.840 0.076 0.072
#> SRR1947554 1 0.3070 0.794 0.860 0.000 0.000 0.068 0.028 0.044
#> SRR1947555 2 0.1793 0.862 0.000 0.928 0.000 0.012 0.012 0.048
#> SRR1947550 4 0.1167 0.856 0.000 0.012 0.000 0.960 0.020 0.008
#> SRR1947552 4 0.3699 0.815 0.000 0.000 0.004 0.796 0.112 0.088
#> SRR1947549 3 0.1232 0.873 0.000 0.000 0.956 0.004 0.024 0.016
#> SRR1947551 5 0.3898 0.898 0.000 0.000 0.336 0.000 0.652 0.012
#> SRR1947548 4 0.3098 0.834 0.000 0.000 0.004 0.844 0.088 0.064
#> SRR1947506 6 0.4621 0.615 0.056 0.000 0.268 0.004 0.004 0.668
#> SRR1947507 1 0.0000 0.882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.1949 0.846 0.924 0.000 0.000 0.020 0.020 0.036
#> SRR1947503 4 0.3918 0.807 0.000 0.000 0.000 0.768 0.124 0.108
#> SRR1947502 2 0.0767 0.876 0.000 0.976 0.000 0.012 0.008 0.004
#> SRR1947501 4 0.4655 0.757 0.000 0.120 0.000 0.744 0.048 0.088
#> SRR1947499 6 0.4802 0.554 0.252 0.000 0.068 0.008 0.004 0.668
#> SRR1947498 3 0.1421 0.872 0.000 0.000 0.944 0.000 0.028 0.028
#> SRR1947508 6 0.4601 0.527 0.020 0.000 0.348 0.000 0.020 0.612
#> SRR1947505 4 0.3362 0.849 0.000 0.000 0.004 0.824 0.096 0.076
#> SRR1947497 2 0.3072 0.864 0.000 0.840 0.000 0.000 0.084 0.076
#> SRR1947496 1 0.0000 0.882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.3072 0.864 0.000 0.840 0.000 0.000 0.084 0.076
#> SRR1947494 4 0.3415 0.825 0.000 0.000 0.004 0.820 0.096 0.080
#> SRR1947493 6 0.4354 0.502 0.296 0.000 0.024 0.008 0.004 0.668
#> SRR1947492 1 0.0806 0.877 0.972 0.000 0.000 0.000 0.020 0.008
#> SRR1947500 4 0.2944 0.847 0.000 0.024 0.000 0.868 0.056 0.052
#> SRR1947491 4 0.2981 0.848 0.000 0.020 0.000 0.864 0.064 0.052
#> SRR1947490 1 0.0972 0.875 0.964 0.000 0.000 0.000 0.028 0.008
#> SRR1947489 6 0.4364 0.561 0.000 0.000 0.308 0.012 0.024 0.656
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 15148 rows and 152 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 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 0.460 0.760 0.887 0.4975 0.497 0.497
#> 3 3 0.904 0.909 0.962 0.3456 0.694 0.460
#> 4 4 0.902 0.850 0.942 0.1179 0.871 0.637
#> 5 5 0.818 0.746 0.854 0.0586 0.920 0.701
#> 6 6 0.751 0.685 0.755 0.0410 0.922 0.656
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] 3
There is also optional best \(k\) = 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
#> SRR1947547 1 0.0000 0.813 1.000 0.000
#> SRR1947546 2 0.0000 0.904 0.000 1.000
#> SRR1947545 1 0.2778 0.809 0.952 0.048
#> SRR1947544 1 0.3431 0.806 0.936 0.064
#> SRR1947542 2 0.0000 0.904 0.000 1.000
#> SRR1947541 1 0.0000 0.813 1.000 0.000
#> SRR1947540 2 0.0000 0.904 0.000 1.000
#> SRR1947539 1 0.8144 0.681 0.748 0.252
#> SRR1947538 2 0.0672 0.898 0.008 0.992
#> SRR1947537 1 0.8144 0.681 0.748 0.252
#> SRR1947536 1 0.0000 0.813 1.000 0.000
#> SRR1947535 1 0.8144 0.681 0.748 0.252
#> SRR1947534 2 0.9710 0.313 0.400 0.600
#> SRR1947533 2 0.0000 0.904 0.000 1.000
#> SRR1947532 1 0.8267 0.644 0.740 0.260
#> SRR1947531 2 0.0000 0.904 0.000 1.000
#> SRR1947530 1 0.0000 0.813 1.000 0.000
#> SRR1947529 2 0.0000 0.904 0.000 1.000
#> SRR1947528 1 0.0000 0.813 1.000 0.000
#> SRR1947527 2 0.0000 0.904 0.000 1.000
#> SRR1947526 2 0.0000 0.904 0.000 1.000
#> SRR1947525 2 0.0000 0.904 0.000 1.000
#> SRR1947524 1 0.8144 0.681 0.748 0.252
#> SRR1947523 2 0.9775 0.281 0.412 0.588
#> SRR1947521 1 0.0672 0.812 0.992 0.008
#> SRR1947520 2 0.0000 0.904 0.000 1.000
#> SRR1947519 1 0.0000 0.813 1.000 0.000
#> SRR1947518 2 0.0672 0.898 0.008 0.992
#> SRR1947517 1 0.0000 0.813 1.000 0.000
#> SRR1947516 2 0.0000 0.904 0.000 1.000
#> SRR1947515 1 1.0000 0.304 0.504 0.496
#> SRR1947514 2 0.0000 0.904 0.000 1.000
#> SRR1947513 1 0.8267 0.644 0.740 0.260
#> SRR1947512 1 0.4939 0.787 0.892 0.108
#> SRR1947511 2 0.0000 0.904 0.000 1.000
#> SRR1947510 1 0.9635 0.459 0.612 0.388
#> SRR1947572 2 0.1633 0.885 0.024 0.976
#> SRR1947611 2 0.8267 0.564 0.260 0.740
#> SRR1947509 1 0.0000 0.813 1.000 0.000
#> SRR1947644 1 0.8144 0.681 0.748 0.252
#> SRR1947643 2 0.0000 0.904 0.000 1.000
#> SRR1947642 1 0.0000 0.813 1.000 0.000
#> SRR1947640 2 0.8144 0.601 0.252 0.748
#> SRR1947641 1 0.8144 0.681 0.748 0.252
#> SRR1947639 2 0.0000 0.904 0.000 1.000
#> SRR1947638 1 0.8267 0.644 0.740 0.260
#> SRR1947637 2 0.8267 0.564 0.260 0.740
#> SRR1947636 1 0.0000 0.813 1.000 0.000
#> SRR1947635 2 0.0000 0.904 0.000 1.000
#> SRR1947634 2 0.0000 0.904 0.000 1.000
#> SRR1947633 1 0.8144 0.681 0.748 0.252
#> SRR1947632 2 0.0000 0.904 0.000 1.000
#> SRR1947631 1 0.0672 0.812 0.992 0.008
#> SRR1947629 1 0.8144 0.681 0.748 0.252
#> SRR1947630 2 0.0000 0.904 0.000 1.000
#> SRR1947627 1 0.0000 0.813 1.000 0.000
#> SRR1947628 2 0.0000 0.904 0.000 1.000
#> SRR1947626 2 0.0000 0.904 0.000 1.000
#> SRR1947625 1 0.8661 0.633 0.712 0.288
#> SRR1947624 2 0.0000 0.904 0.000 1.000
#> SRR1947623 2 0.9710 0.313 0.400 0.600
#> SRR1947622 2 0.0000 0.904 0.000 1.000
#> SRR1947621 2 0.0000 0.904 0.000 1.000
#> SRR1947620 1 0.3733 0.803 0.928 0.072
#> SRR1947619 1 0.8144 0.681 0.748 0.252
#> SRR1947617 2 0.0000 0.904 0.000 1.000
#> SRR1947618 1 0.7299 0.709 0.796 0.204
#> SRR1947616 2 0.0000 0.904 0.000 1.000
#> SRR1947615 1 0.0000 0.813 1.000 0.000
#> SRR1947614 1 0.0672 0.812 0.992 0.008
#> SRR1947613 1 0.8267 0.644 0.740 0.260
#> SRR1947610 2 0.0000 0.904 0.000 1.000
#> SRR1947612 2 0.0000 0.904 0.000 1.000
#> SRR1947609 1 0.8267 0.644 0.740 0.260
#> SRR1947608 1 0.9710 0.434 0.600 0.400
#> SRR1947606 1 0.0000 0.813 1.000 0.000
#> SRR1947607 2 0.9710 0.313 0.400 0.600
#> SRR1947604 2 0.9686 0.324 0.396 0.604
#> SRR1947605 1 0.2236 0.811 0.964 0.036
#> SRR1947603 2 0.0000 0.904 0.000 1.000
#> SRR1947602 1 0.0000 0.813 1.000 0.000
#> SRR1947600 1 0.8144 0.681 0.748 0.252
#> SRR1947601 2 0.0000 0.904 0.000 1.000
#> SRR1947598 2 0.4298 0.815 0.088 0.912
#> SRR1947599 1 0.8267 0.644 0.740 0.260
#> SRR1947597 2 0.0000 0.904 0.000 1.000
#> SRR1947596 1 0.4161 0.798 0.916 0.084
#> SRR1947595 2 0.0000 0.904 0.000 1.000
#> SRR1947594 1 0.4939 0.787 0.892 0.108
#> SRR1947592 1 0.8144 0.681 0.748 0.252
#> SRR1947591 2 0.0000 0.904 0.000 1.000
#> SRR1947590 1 0.2778 0.809 0.952 0.048
#> SRR1947588 1 0.4939 0.787 0.892 0.108
#> SRR1947587 1 0.0000 0.813 1.000 0.000
#> SRR1947586 2 0.0000 0.904 0.000 1.000
#> SRR1947585 1 0.8144 0.681 0.748 0.252
#> SRR1947584 1 0.3431 0.806 0.936 0.064
#> SRR1947583 2 0.0000 0.904 0.000 1.000
#> SRR1947582 1 0.5059 0.784 0.888 0.112
#> SRR1947580 2 0.0000 0.904 0.000 1.000
#> SRR1947581 1 0.3431 0.806 0.936 0.064
#> SRR1947576 2 0.8267 0.564 0.260 0.740
#> SRR1947575 2 0.8443 0.543 0.272 0.728
#> SRR1947579 1 0.8144 0.681 0.748 0.252
#> SRR1947578 2 0.0000 0.904 0.000 1.000
#> SRR1947573 1 0.9710 0.434 0.600 0.400
#> SRR1947574 2 0.8144 0.601 0.252 0.748
#> SRR1947571 2 0.0672 0.898 0.008 0.992
#> SRR1947577 1 0.7453 0.701 0.788 0.212
#> SRR1947570 1 0.0000 0.813 1.000 0.000
#> SRR1947569 1 0.8144 0.681 0.748 0.252
#> SRR1947566 2 0.0000 0.904 0.000 1.000
#> SRR1947567 2 0.0000 0.904 0.000 1.000
#> SRR1947568 2 0.0000 0.904 0.000 1.000
#> SRR1947564 2 0.0000 0.904 0.000 1.000
#> SRR1947563 1 0.9710 0.434 0.600 0.400
#> SRR1947562 2 0.0000 0.904 0.000 1.000
#> SRR1947565 1 0.8081 0.684 0.752 0.248
#> SRR1947559 2 0.0000 0.904 0.000 1.000
#> SRR1947560 2 0.8267 0.564 0.260 0.740
#> SRR1947561 2 0.0000 0.904 0.000 1.000
#> SRR1947557 1 0.3431 0.806 0.936 0.064
#> SRR1947558 1 0.8144 0.681 0.748 0.252
#> SRR1947556 1 0.3431 0.806 0.936 0.064
#> SRR1947553 2 0.0000 0.904 0.000 1.000
#> SRR1947554 2 0.9710 0.313 0.400 0.600
#> SRR1947555 2 0.2236 0.869 0.036 0.964
#> SRR1947550 2 0.0000 0.904 0.000 1.000
#> SRR1947552 1 0.8267 0.644 0.740 0.260
#> SRR1947549 1 0.9710 0.434 0.600 0.400
#> SRR1947551 1 0.9710 0.434 0.600 0.400
#> SRR1947548 2 0.2236 0.875 0.036 0.964
#> SRR1947506 1 0.0000 0.813 1.000 0.000
#> SRR1947507 1 0.3431 0.806 0.936 0.064
#> SRR1947504 1 0.7602 0.693 0.780 0.220
#> SRR1947503 1 0.8267 0.644 0.740 0.260
#> SRR1947502 2 0.0000 0.904 0.000 1.000
#> SRR1947501 2 0.0000 0.904 0.000 1.000
#> SRR1947499 1 0.0000 0.813 1.000 0.000
#> SRR1947498 1 0.0376 0.812 0.996 0.004
#> SRR1947508 1 0.0000 0.813 1.000 0.000
#> SRR1947505 2 0.9754 0.292 0.408 0.592
#> SRR1947497 2 0.0000 0.904 0.000 1.000
#> SRR1947496 1 0.4939 0.787 0.892 0.108
#> SRR1947495 2 0.0000 0.904 0.000 1.000
#> SRR1947494 1 0.8267 0.644 0.740 0.260
#> SRR1947493 1 0.0000 0.813 1.000 0.000
#> SRR1947492 1 0.6712 0.736 0.824 0.176
#> SRR1947500 2 0.7745 0.636 0.228 0.772
#> SRR1947491 2 0.8144 0.601 0.252 0.748
#> SRR1947490 1 0.8267 0.644 0.740 0.260
#> SRR1947489 1 0.0000 0.813 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.5926 0.4484 0.356 0.000 0.644
#> SRR1947546 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947540 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947539 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947538 1 0.6126 0.3814 0.600 0.400 0.000
#> SRR1947537 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947536 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947535 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947534 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947533 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947532 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947531 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947530 1 0.1964 0.8665 0.944 0.000 0.056
#> SRR1947529 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947528 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947527 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947523 1 0.4555 0.7346 0.800 0.200 0.000
#> SRR1947521 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947519 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947518 1 0.6126 0.3814 0.600 0.400 0.000
#> SRR1947517 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947515 1 0.2625 0.8500 0.916 0.084 0.000
#> SRR1947514 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947572 1 0.5905 0.4851 0.648 0.352 0.000
#> SRR1947611 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947509 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947644 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947640 1 0.3941 0.7804 0.844 0.156 0.000
#> SRR1947641 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947639 2 0.4504 0.7388 0.196 0.804 0.000
#> SRR1947638 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947637 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947632 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947627 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947628 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947624 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947623 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947622 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947619 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947616 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947615 3 0.0237 0.9740 0.004 0.000 0.996
#> SRR1947614 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947609 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947604 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947605 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947602 1 0.4555 0.7058 0.800 0.000 0.200
#> SRR1947600 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947598 1 0.6126 0.3814 0.600 0.400 0.000
#> SRR1947599 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947597 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947596 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947595 2 0.4504 0.7388 0.196 0.804 0.000
#> SRR1947594 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947590 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947588 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947583 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947582 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947578 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947573 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947574 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947571 1 0.6126 0.3814 0.600 0.400 0.000
#> SRR1947577 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947570 1 0.4399 0.7222 0.812 0.000 0.188
#> SRR1947569 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947566 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947567 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947568 2 0.4399 0.7515 0.188 0.812 0.000
#> SRR1947564 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947560 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947554 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947550 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947552 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947549 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947551 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947548 1 0.6126 0.3814 0.600 0.400 0.000
#> SRR1947506 3 0.6302 0.0872 0.480 0.000 0.520
#> SRR1947507 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947503 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947499 1 0.4555 0.7058 0.800 0.000 0.200
#> SRR1947498 3 0.0000 0.9775 0.000 0.000 1.000
#> SRR1947508 3 0.3752 0.8193 0.144 0.000 0.856
#> SRR1947505 1 0.5948 0.4835 0.640 0.360 0.000
#> SRR1947497 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947494 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947493 1 0.0237 0.9075 0.996 0.000 0.004
#> SRR1947492 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.9873 0.000 1.000 0.000
#> SRR1947491 1 0.6126 0.3938 0.600 0.400 0.000
#> SRR1947490 1 0.0000 0.9103 1.000 0.000 0.000
#> SRR1947489 3 0.1163 0.9513 0.028 0.000 0.972
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.4790 0.4196 0.380 0.000 0.620 0.000
#> SRR1947546 4 0.4877 0.3069 0.000 0.408 0.000 0.592
#> SRR1947545 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947541 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947540 2 0.4103 0.6166 0.000 0.744 0.000 0.256
#> SRR1947539 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947538 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947537 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947536 3 0.4697 0.4721 0.356 0.000 0.644 0.000
#> SRR1947535 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947534 1 0.0188 0.9639 0.996 0.004 0.000 0.000
#> SRR1947533 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947531 2 0.4040 0.6300 0.000 0.752 0.000 0.248
#> SRR1947530 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947529 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947528 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947527 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947525 4 0.4961 0.1869 0.000 0.448 0.000 0.552
#> SRR1947524 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947521 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947519 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947518 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947517 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947510 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.4406 0.5037 0.300 0.000 0.000 0.700
#> SRR1947611 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947509 3 0.4790 0.4196 0.380 0.000 0.620 0.000
#> SRR1947644 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947642 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947640 4 0.3726 0.6726 0.212 0.000 0.000 0.788
#> SRR1947641 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947639 4 0.4830 0.3480 0.000 0.392 0.000 0.608
#> SRR1947638 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947637 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947636 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947635 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947634 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947633 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947632 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947631 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947629 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947627 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947628 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947626 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947625 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947623 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947622 2 0.4888 0.2696 0.000 0.588 0.000 0.412
#> SRR1947621 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947619 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947617 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947615 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947614 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947610 2 0.4992 0.0527 0.000 0.524 0.000 0.476
#> SRR1947612 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.4977 0.1003 0.540 0.000 0.000 0.460
#> SRR1947608 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947607 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947602 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947600 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947599 4 0.0469 0.8436 0.012 0.000 0.000 0.988
#> SRR1947597 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947596 4 0.4933 0.1876 0.432 0.000 0.000 0.568
#> SRR1947595 4 0.4999 0.0588 0.000 0.492 0.000 0.508
#> SRR1947594 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.4933 0.1876 0.432 0.000 0.000 0.568
#> SRR1947588 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947586 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947585 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.4454 0.5250 0.000 0.308 0.000 0.692
#> SRR1947582 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947581 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.4916 0.2658 0.000 0.576 0.000 0.424
#> SRR1947573 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947574 1 0.4331 0.5475 0.712 0.000 0.000 0.288
#> SRR1947571 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947577 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947570 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947569 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947566 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947567 4 0.1716 0.8110 0.000 0.064 0.000 0.936
#> SRR1947568 2 0.1474 0.8764 0.052 0.948 0.000 0.000
#> SRR1947564 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947563 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947562 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947565 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947559 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947556 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947553 2 0.4955 0.1697 0.000 0.556 0.000 0.444
#> SRR1947554 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947550 4 0.1474 0.8195 0.000 0.052 0.000 0.948
#> SRR1947552 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947549 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947551 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947506 1 0.1716 0.8951 0.936 0.000 0.064 0.000
#> SRR1947507 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947503 1 0.3123 0.7809 0.844 0.000 0.000 0.156
#> SRR1947502 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947501 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947499 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947498 3 0.0000 0.9646 0.000 0.000 1.000 0.000
#> SRR1947508 3 0.4790 0.4196 0.380 0.000 0.620 0.000
#> SRR1947505 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9281 0.000 1.000 0.000 0.000
#> SRR1947494 4 0.0000 0.8499 0.000 0.000 0.000 1.000
#> SRR1947493 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.4454 0.5250 0.000 0.308 0.000 0.692
#> SRR1947491 4 0.3726 0.6726 0.212 0.000 0.000 0.788
#> SRR1947490 1 0.0000 0.9677 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.0000 0.9646 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.0324 0.7902 0.004 0.000 0.992 0.000 0.004
#> SRR1947546 4 0.4403 0.2294 0.000 0.436 0.004 0.560 0.000
#> SRR1947545 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947544 1 0.0880 0.9156 0.968 0.000 0.032 0.000 0.000
#> SRR1947542 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947541 3 0.1121 0.7861 0.000 0.000 0.956 0.000 0.044
#> SRR1947540 2 0.3715 0.5884 0.000 0.736 0.004 0.260 0.000
#> SRR1947539 5 0.0404 0.7181 0.000 0.000 0.012 0.000 0.988
#> SRR1947538 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947537 5 0.4138 0.7097 0.000 0.000 0.384 0.000 0.616
#> SRR1947536 3 0.1430 0.7819 0.004 0.000 0.944 0.000 0.052
#> SRR1947535 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947534 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947531 2 0.3662 0.6025 0.000 0.744 0.004 0.252 0.000
#> SRR1947530 3 0.3913 0.4123 0.324 0.000 0.676 0.000 0.000
#> SRR1947529 2 0.0162 0.9175 0.000 0.996 0.004 0.000 0.000
#> SRR1947528 3 0.1121 0.7861 0.000 0.000 0.956 0.000 0.044
#> SRR1947527 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 4 0.4446 0.0995 0.000 0.476 0.004 0.520 0.000
#> SRR1947524 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947523 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947521 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947519 3 0.1197 0.7822 0.000 0.000 0.952 0.000 0.048
#> SRR1947518 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947517 5 0.3336 0.3958 0.000 0.000 0.228 0.000 0.772
#> SRR1947516 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947514 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 1 0.0963 0.9137 0.964 0.000 0.036 0.000 0.000
#> SRR1947512 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947572 1 0.4219 0.2919 0.584 0.000 0.000 0.416 0.000
#> SRR1947611 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947509 3 0.4321 0.4631 0.004 0.000 0.600 0.000 0.396
#> SRR1947644 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947642 3 0.2690 0.6429 0.000 0.000 0.844 0.000 0.156
#> SRR1947640 4 0.4299 0.3567 0.388 0.000 0.004 0.608 0.000
#> SRR1947641 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947639 4 0.4425 0.1804 0.000 0.452 0.004 0.544 0.000
#> SRR1947638 1 0.0162 0.9272 0.996 0.000 0.004 0.000 0.000
#> SRR1947637 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947636 5 0.4138 0.7097 0.000 0.000 0.384 0.000 0.616
#> SRR1947635 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947634 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947633 5 0.0404 0.7181 0.000 0.000 0.012 0.000 0.988
#> SRR1947632 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947631 3 0.4305 -0.4428 0.000 0.000 0.512 0.000 0.488
#> SRR1947629 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947630 2 0.0404 0.9101 0.000 0.988 0.000 0.000 0.012
#> SRR1947627 3 0.1121 0.7861 0.000 0.000 0.956 0.000 0.044
#> SRR1947628 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947626 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947624 2 0.0404 0.9101 0.000 0.988 0.000 0.000 0.012
#> SRR1947623 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.4390 0.1935 0.000 0.568 0.004 0.428 0.000
#> SRR1947621 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947619 5 0.4138 0.7097 0.000 0.000 0.384 0.000 0.616
#> SRR1947617 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947616 2 0.0162 0.9175 0.000 0.996 0.004 0.000 0.000
#> SRR1947615 3 0.0162 0.7901 0.000 0.000 0.996 0.000 0.004
#> SRR1947614 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 2 0.4437 0.0686 0.000 0.532 0.004 0.464 0.000
#> SRR1947612 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 1 0.4240 0.6777 0.736 0.000 0.036 0.228 0.000
#> SRR1947608 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947606 3 0.1121 0.7861 0.000 0.000 0.956 0.000 0.044
#> SRR1947607 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947605 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947603 2 0.0162 0.9175 0.000 0.996 0.004 0.000 0.000
#> SRR1947602 3 0.3305 0.6138 0.224 0.000 0.776 0.000 0.000
#> SRR1947600 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947601 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947599 4 0.0963 0.7905 0.000 0.000 0.036 0.964 0.000
#> SRR1947597 2 0.0162 0.9175 0.000 0.996 0.004 0.000 0.000
#> SRR1947596 4 0.5036 0.0830 0.404 0.000 0.036 0.560 0.000
#> SRR1947595 2 0.4585 0.2555 0.008 0.592 0.004 0.396 0.000
#> SRR1947594 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947591 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.5028 0.0962 0.400 0.000 0.036 0.564 0.000
#> SRR1947588 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.2561 0.6459 0.000 0.000 0.856 0.000 0.144
#> SRR1947586 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947585 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947584 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.4359 0.2940 0.000 0.412 0.004 0.584 0.000
#> SRR1947582 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947580 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947575 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947579 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947578 4 0.4440 0.1054 0.000 0.468 0.004 0.528 0.000
#> SRR1947573 5 0.3857 0.7852 0.000 0.000 0.312 0.000 0.688
#> SRR1947574 1 0.2773 0.7597 0.836 0.000 0.000 0.164 0.000
#> SRR1947571 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947577 1 0.2377 0.8577 0.872 0.000 0.128 0.000 0.000
#> SRR1947570 3 0.0290 0.7892 0.008 0.000 0.992 0.000 0.000
#> SRR1947569 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947566 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 4 0.2763 0.7176 0.000 0.148 0.004 0.848 0.000
#> SRR1947568 2 0.2966 0.7223 0.184 0.816 0.000 0.000 0.000
#> SRR1947564 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947562 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947565 5 0.4138 0.7097 0.000 0.000 0.384 0.000 0.616
#> SRR1947559 2 0.0162 0.9175 0.000 0.996 0.004 0.000 0.000
#> SRR1947560 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 5 0.3895 0.7841 0.000 0.000 0.320 0.000 0.680
#> SRR1947556 1 0.0162 0.9263 0.996 0.000 0.000 0.004 0.000
#> SRR1947553 2 0.4415 0.1414 0.000 0.552 0.004 0.444 0.000
#> SRR1947554 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947550 4 0.2488 0.7404 0.000 0.124 0.004 0.872 0.000
#> SRR1947552 4 0.0963 0.7905 0.000 0.000 0.036 0.964 0.000
#> SRR1947549 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947551 5 0.0000 0.7145 0.000 0.000 0.000 0.000 1.000
#> SRR1947548 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947506 3 0.1410 0.7650 0.060 0.000 0.940 0.000 0.000
#> SRR1947507 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 1 0.3093 0.7680 0.824 0.000 0.008 0.168 0.000
#> SRR1947502 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 4 0.0162 0.8120 0.000 0.000 0.004 0.996 0.000
#> SRR1947499 3 0.3395 0.5943 0.236 0.000 0.764 0.000 0.000
#> SRR1947498 5 0.3876 0.7851 0.000 0.000 0.316 0.000 0.684
#> SRR1947508 3 0.0955 0.7900 0.004 0.000 0.968 0.000 0.028
#> SRR1947505 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947497 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9194 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000
#> SRR1947493 3 0.3913 0.4123 0.324 0.000 0.676 0.000 0.000
#> SRR1947492 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.4359 0.2940 0.000 0.412 0.004 0.584 0.000
#> SRR1947491 4 0.4225 0.4002 0.364 0.000 0.004 0.632 0.000
#> SRR1947490 1 0.0000 0.9285 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0162 0.7901 0.000 0.000 0.996 0.000 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.2823 0.8370 0.000 0.000 0.204 0.000 0.000 0.796
#> SRR1947546 4 0.2964 0.7363 0.000 0.204 0.000 0.792 0.004 0.000
#> SRR1947545 1 0.3743 0.6762 0.724 0.000 0.000 0.000 0.024 0.252
#> SRR1947544 1 0.0865 0.8739 0.964 0.000 0.000 0.000 0.000 0.036
#> SRR1947542 4 0.0717 0.6228 0.000 0.016 0.000 0.976 0.008 0.000
#> SRR1947541 6 0.3101 0.8255 0.000 0.000 0.244 0.000 0.000 0.756
#> SRR1947540 4 0.3634 0.6375 0.000 0.296 0.000 0.696 0.008 0.000
#> SRR1947539 3 0.5022 0.5987 0.000 0.000 0.640 0.000 0.156 0.204
#> SRR1947538 5 0.3717 0.7949 0.000 0.000 0.000 0.384 0.616 0.000
#> SRR1947537 3 0.2003 0.6342 0.000 0.000 0.884 0.000 0.000 0.116
#> SRR1947536 6 0.3672 0.7758 0.008 0.000 0.304 0.000 0.000 0.688
#> SRR1947535 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947534 1 0.0260 0.8829 0.992 0.008 0.000 0.000 0.000 0.000
#> SRR1947533 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 5 0.3706 0.7999 0.000 0.000 0.000 0.380 0.620 0.000
#> SRR1947531 4 0.4032 0.5611 0.000 0.420 0.000 0.572 0.008 0.000
#> SRR1947530 6 0.2823 0.6691 0.204 0.000 0.000 0.000 0.000 0.796
#> SRR1947529 4 0.3765 0.4315 0.000 0.404 0.000 0.596 0.000 0.000
#> SRR1947528 6 0.3101 0.8255 0.000 0.000 0.244 0.000 0.000 0.756
#> SRR1947527 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947525 4 0.4120 0.7322 0.000 0.204 0.000 0.728 0.068 0.000
#> SRR1947524 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947523 5 0.3881 0.7819 0.000 0.000 0.000 0.396 0.600 0.004
#> SRR1947521 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947520 2 0.0260 0.8446 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1947519 6 0.4086 0.5025 0.000 0.000 0.464 0.000 0.008 0.528
#> SRR1947518 5 0.3717 0.7949 0.000 0.000 0.000 0.384 0.616 0.000
#> SRR1947517 5 0.6120 -0.5080 0.000 0.000 0.344 0.000 0.352 0.304
#> SRR1947516 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947515 5 0.3706 0.7999 0.000 0.000 0.000 0.380 0.620 0.000
#> SRR1947514 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947513 1 0.2308 0.8384 0.892 0.000 0.000 0.000 0.068 0.040
#> SRR1947512 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947510 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947572 1 0.5465 -0.0695 0.508 0.000 0.000 0.132 0.360 0.000
#> SRR1947611 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947509 6 0.3532 0.4693 0.000 0.000 0.064 0.000 0.140 0.796
#> SRR1947644 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947643 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947642 3 0.4025 -0.2383 0.000 0.000 0.576 0.000 0.008 0.416
#> SRR1947640 4 0.5633 0.4518 0.196 0.104 0.000 0.640 0.060 0.000
#> SRR1947641 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947639 4 0.4258 0.7312 0.004 0.204 0.000 0.724 0.068 0.000
#> SRR1947638 1 0.2101 0.8317 0.892 0.000 0.000 0.004 0.100 0.004
#> SRR1947637 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947636 3 0.2003 0.6342 0.000 0.000 0.884 0.000 0.000 0.116
#> SRR1947635 4 0.1225 0.5721 0.000 0.012 0.000 0.952 0.036 0.000
#> SRR1947634 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947633 3 0.4707 0.6110 0.000 0.000 0.676 0.000 0.120 0.204
#> SRR1947632 4 0.0603 0.6236 0.000 0.016 0.000 0.980 0.004 0.000
#> SRR1947631 3 0.2302 0.5701 0.000 0.000 0.872 0.000 0.008 0.120
#> SRR1947629 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947630 2 0.2597 0.6696 0.000 0.824 0.000 0.000 0.176 0.000
#> SRR1947627 6 0.3101 0.8255 0.000 0.000 0.244 0.000 0.000 0.756
#> SRR1947628 4 0.0405 0.6079 0.000 0.004 0.000 0.988 0.008 0.000
#> SRR1947626 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947625 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947624 2 0.2597 0.6696 0.000 0.824 0.000 0.000 0.176 0.000
#> SRR1947623 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.3109 0.7245 0.000 0.224 0.000 0.772 0.004 0.000
#> SRR1947621 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947620 1 0.4522 0.6468 0.672 0.000 0.000 0.000 0.076 0.252
#> SRR1947619 3 0.2003 0.6342 0.000 0.000 0.884 0.000 0.000 0.116
#> SRR1947617 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947618 1 0.4522 0.6468 0.672 0.000 0.000 0.000 0.076 0.252
#> SRR1947616 2 0.4039 0.1410 0.000 0.568 0.000 0.424 0.008 0.000
#> SRR1947615 6 0.3103 0.8373 0.000 0.000 0.208 0.000 0.008 0.784
#> SRR1947614 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947613 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3602 0.7343 0.000 0.208 0.000 0.760 0.032 0.000
#> SRR1947612 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947609 5 0.5663 0.5729 0.240 0.000 0.000 0.116 0.608 0.036
#> SRR1947608 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947606 6 0.3126 0.8223 0.000 0.000 0.248 0.000 0.000 0.752
#> SRR1947607 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 5 0.4047 0.7984 0.000 0.000 0.000 0.384 0.604 0.012
#> SRR1947605 1 0.3582 0.6812 0.732 0.000 0.000 0.000 0.016 0.252
#> SRR1947603 4 0.3737 0.4559 0.000 0.392 0.000 0.608 0.000 0.000
#> SRR1947602 6 0.3279 0.7106 0.176 0.000 0.028 0.000 0.000 0.796
#> SRR1947600 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947601 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947598 5 0.3945 0.7971 0.000 0.000 0.000 0.380 0.612 0.008
#> SRR1947599 5 0.4659 0.7816 0.004 0.000 0.000 0.336 0.612 0.048
#> SRR1947597 4 0.3727 0.4649 0.000 0.388 0.000 0.612 0.000 0.000
#> SRR1947596 5 0.6172 0.6774 0.168 0.000 0.000 0.236 0.552 0.044
#> SRR1947595 2 0.5602 -0.1111 0.016 0.544 0.000 0.332 0.108 0.000
#> SRR1947594 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947591 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947590 5 0.6172 0.6774 0.168 0.000 0.000 0.236 0.552 0.044
#> SRR1947588 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.3727 -0.0577 0.000 0.000 0.612 0.000 0.000 0.388
#> SRR1947586 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947585 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947584 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.3725 0.6910 0.000 0.316 0.000 0.676 0.008 0.000
#> SRR1947582 1 0.4392 0.6508 0.680 0.000 0.000 0.000 0.064 0.256
#> SRR1947580 2 0.0260 0.8467 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1947581 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947575 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947579 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947578 4 0.3323 0.6960 0.000 0.240 0.000 0.752 0.008 0.000
#> SRR1947573 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947574 1 0.3426 0.7326 0.816 0.004 0.000 0.064 0.116 0.000
#> SRR1947571 5 0.3727 0.7943 0.000 0.000 0.000 0.388 0.612 0.000
#> SRR1947577 1 0.4522 0.6468 0.672 0.000 0.000 0.000 0.076 0.252
#> SRR1947570 6 0.2933 0.8371 0.004 0.000 0.200 0.000 0.000 0.796
#> SRR1947569 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947566 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947567 4 0.2454 0.7456 0.000 0.160 0.000 0.840 0.000 0.000
#> SRR1947568 2 0.4513 0.6432 0.172 0.704 0.000 0.124 0.000 0.000
#> SRR1947564 2 0.2048 0.8423 0.000 0.880 0.000 0.120 0.000 0.000
#> SRR1947563 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947562 4 0.2597 0.2938 0.000 0.000 0.000 0.824 0.176 0.000
#> SRR1947565 3 0.2003 0.6342 0.000 0.000 0.884 0.000 0.000 0.116
#> SRR1947559 2 0.3547 0.4664 0.000 0.668 0.000 0.332 0.000 0.000
#> SRR1947560 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947561 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947557 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0260 0.7134 0.000 0.000 0.992 0.000 0.008 0.000
#> SRR1947556 1 0.1411 0.8455 0.936 0.000 0.000 0.004 0.060 0.000
#> SRR1947553 4 0.3658 0.7289 0.000 0.216 0.000 0.752 0.032 0.000
#> SRR1947554 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947550 4 0.3190 0.7189 0.000 0.136 0.000 0.820 0.044 0.000
#> SRR1947552 5 0.4396 0.7893 0.000 0.000 0.000 0.352 0.612 0.036
#> SRR1947549 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947551 3 0.5873 0.5289 0.000 0.000 0.444 0.000 0.352 0.204
#> SRR1947548 5 0.3706 0.7999 0.000 0.000 0.000 0.380 0.620 0.000
#> SRR1947506 6 0.3417 0.8239 0.044 0.000 0.160 0.000 0.000 0.796
#> SRR1947507 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947503 5 0.5303 0.2936 0.376 0.000 0.000 0.084 0.532 0.008
#> SRR1947502 2 0.1863 0.8561 0.000 0.896 0.000 0.104 0.000 0.000
#> SRR1947501 4 0.0858 0.6390 0.000 0.028 0.000 0.968 0.004 0.000
#> SRR1947499 6 0.3189 0.6994 0.184 0.000 0.020 0.000 0.000 0.796
#> SRR1947498 3 0.0146 0.7156 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947508 6 0.3545 0.8309 0.008 0.000 0.236 0.000 0.008 0.748
#> SRR1947505 4 0.3797 -0.4900 0.000 0.000 0.000 0.580 0.420 0.000
#> SRR1947497 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.8500 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947494 5 0.3695 0.8004 0.000 0.000 0.000 0.376 0.624 0.000
#> SRR1947493 6 0.2823 0.6691 0.204 0.000 0.000 0.000 0.000 0.796
#> SRR1947492 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.3725 0.6910 0.000 0.316 0.000 0.676 0.008 0.000
#> SRR1947491 4 0.4178 0.4483 0.248 0.036 0.000 0.708 0.008 0.000
#> SRR1947490 1 0.0000 0.8882 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 6 0.3103 0.8373 0.000 0.000 0.208 0.000 0.008 0.784
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 15148 rows and 152 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 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 0.880 0.913 0.966 0.5024 0.498 0.498
#> 3 3 0.966 0.934 0.974 0.2353 0.810 0.644
#> 4 4 0.794 0.870 0.908 0.1626 0.878 0.684
#> 5 5 0.801 0.750 0.858 0.0785 0.942 0.790
#> 6 6 0.900 0.852 0.935 0.0545 0.922 0.675
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] 3
There is also optional best \(k\) = 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
#> SRR1947547 1 0.0000 0.9641 1.000 0.000
#> SRR1947546 2 0.0000 0.9633 0.000 1.000
#> SRR1947545 1 0.0376 0.9625 0.996 0.004
#> SRR1947544 1 0.0376 0.9625 0.996 0.004
#> SRR1947542 2 0.0000 0.9633 0.000 1.000
#> SRR1947541 1 0.0000 0.9641 1.000 0.000
#> SRR1947540 2 0.0000 0.9633 0.000 1.000
#> SRR1947539 1 0.0000 0.9641 1.000 0.000
#> SRR1947538 2 0.0000 0.9633 0.000 1.000
#> SRR1947537 1 0.0000 0.9641 1.000 0.000
#> SRR1947536 1 0.0000 0.9641 1.000 0.000
#> SRR1947535 1 0.0000 0.9641 1.000 0.000
#> SRR1947534 2 0.0000 0.9633 0.000 1.000
#> SRR1947533 2 0.0000 0.9633 0.000 1.000
#> SRR1947532 2 0.0000 0.9633 0.000 1.000
#> SRR1947531 2 0.0000 0.9633 0.000 1.000
#> SRR1947530 1 0.0000 0.9641 1.000 0.000
#> SRR1947529 2 0.0000 0.9633 0.000 1.000
#> SRR1947528 1 0.0000 0.9641 1.000 0.000
#> SRR1947527 2 0.0000 0.9633 0.000 1.000
#> SRR1947526 2 0.0000 0.9633 0.000 1.000
#> SRR1947525 2 0.0000 0.9633 0.000 1.000
#> SRR1947524 1 0.0000 0.9641 1.000 0.000
#> SRR1947523 2 0.0000 0.9633 0.000 1.000
#> SRR1947521 1 0.0000 0.9641 1.000 0.000
#> SRR1947520 2 0.0000 0.9633 0.000 1.000
#> SRR1947519 1 0.0000 0.9641 1.000 0.000
#> SRR1947518 2 0.0000 0.9633 0.000 1.000
#> SRR1947517 1 0.0000 0.9641 1.000 0.000
#> SRR1947516 2 0.0000 0.9633 0.000 1.000
#> SRR1947515 2 0.0000 0.9633 0.000 1.000
#> SRR1947514 2 0.0000 0.9633 0.000 1.000
#> SRR1947513 1 0.6887 0.7655 0.816 0.184
#> SRR1947512 1 0.0376 0.9625 0.996 0.004
#> SRR1947511 2 0.0000 0.9633 0.000 1.000
#> SRR1947510 1 0.0000 0.9641 1.000 0.000
#> SRR1947572 2 0.0000 0.9633 0.000 1.000
#> SRR1947611 1 0.5408 0.8421 0.876 0.124
#> SRR1947509 1 0.0000 0.9641 1.000 0.000
#> SRR1947644 1 0.0000 0.9641 1.000 0.000
#> SRR1947643 2 0.0000 0.9633 0.000 1.000
#> SRR1947642 1 0.0000 0.9641 1.000 0.000
#> SRR1947640 2 0.0000 0.9633 0.000 1.000
#> SRR1947641 1 0.0376 0.9619 0.996 0.004
#> SRR1947639 2 0.0000 0.9633 0.000 1.000
#> SRR1947638 2 0.0000 0.9633 0.000 1.000
#> SRR1947637 1 0.9850 0.2377 0.572 0.428
#> SRR1947636 1 0.0000 0.9641 1.000 0.000
#> SRR1947635 2 0.0000 0.9633 0.000 1.000
#> SRR1947634 2 0.0000 0.9633 0.000 1.000
#> SRR1947633 1 0.0000 0.9641 1.000 0.000
#> SRR1947632 2 0.0000 0.9633 0.000 1.000
#> SRR1947631 1 0.0000 0.9641 1.000 0.000
#> SRR1947629 1 0.0000 0.9641 1.000 0.000
#> SRR1947630 2 0.0000 0.9633 0.000 1.000
#> SRR1947627 1 0.0000 0.9641 1.000 0.000
#> SRR1947628 2 0.0000 0.9633 0.000 1.000
#> SRR1947626 2 0.0000 0.9633 0.000 1.000
#> SRR1947625 1 0.4690 0.8731 0.900 0.100
#> SRR1947624 2 0.0000 0.9633 0.000 1.000
#> SRR1947623 2 0.8207 0.6483 0.256 0.744
#> SRR1947622 2 0.0000 0.9633 0.000 1.000
#> SRR1947621 2 0.0000 0.9633 0.000 1.000
#> SRR1947620 1 0.2236 0.9353 0.964 0.036
#> SRR1947619 1 0.0000 0.9641 1.000 0.000
#> SRR1947617 2 0.0000 0.9633 0.000 1.000
#> SRR1947618 1 0.7219 0.7428 0.800 0.200
#> SRR1947616 2 0.0376 0.9599 0.004 0.996
#> SRR1947615 1 0.0000 0.9641 1.000 0.000
#> SRR1947614 1 0.0000 0.9641 1.000 0.000
#> SRR1947613 1 0.0376 0.9625 0.996 0.004
#> SRR1947610 2 0.0000 0.9633 0.000 1.000
#> SRR1947612 2 0.0000 0.9633 0.000 1.000
#> SRR1947609 1 0.9963 0.1316 0.536 0.464
#> SRR1947608 1 0.0000 0.9641 1.000 0.000
#> SRR1947606 1 0.0000 0.9641 1.000 0.000
#> SRR1947607 2 0.9732 0.3084 0.404 0.596
#> SRR1947604 2 0.0000 0.9633 0.000 1.000
#> SRR1947605 1 0.0376 0.9625 0.996 0.004
#> SRR1947603 2 0.0000 0.9633 0.000 1.000
#> SRR1947602 1 0.0000 0.9641 1.000 0.000
#> SRR1947600 1 0.0000 0.9641 1.000 0.000
#> SRR1947601 2 0.0000 0.9633 0.000 1.000
#> SRR1947598 2 0.0376 0.9599 0.004 0.996
#> SRR1947599 2 0.0000 0.9633 0.000 1.000
#> SRR1947597 2 0.0000 0.9633 0.000 1.000
#> SRR1947596 2 0.9170 0.4971 0.332 0.668
#> SRR1947595 2 0.0000 0.9633 0.000 1.000
#> SRR1947594 1 0.0376 0.9625 0.996 0.004
#> SRR1947592 1 0.0000 0.9641 1.000 0.000
#> SRR1947591 2 0.0000 0.9633 0.000 1.000
#> SRR1947590 1 0.9795 0.2781 0.584 0.416
#> SRR1947588 1 0.0376 0.9625 0.996 0.004
#> SRR1947587 1 0.0000 0.9641 1.000 0.000
#> SRR1947586 2 0.0000 0.9633 0.000 1.000
#> SRR1947585 1 0.0000 0.9641 1.000 0.000
#> SRR1947584 1 0.0376 0.9625 0.996 0.004
#> SRR1947583 2 0.0000 0.9633 0.000 1.000
#> SRR1947582 1 0.7219 0.7428 0.800 0.200
#> SRR1947580 2 0.0000 0.9633 0.000 1.000
#> SRR1947581 1 0.0376 0.9625 0.996 0.004
#> SRR1947576 1 0.6712 0.7741 0.824 0.176
#> SRR1947575 2 0.7453 0.7169 0.212 0.788
#> SRR1947579 1 0.0000 0.9641 1.000 0.000
#> SRR1947578 2 0.0000 0.9633 0.000 1.000
#> SRR1947573 1 0.0000 0.9641 1.000 0.000
#> SRR1947574 2 0.0000 0.9633 0.000 1.000
#> SRR1947571 2 0.0000 0.9633 0.000 1.000
#> SRR1947577 2 0.9815 0.2612 0.420 0.580
#> SRR1947570 1 0.0000 0.9641 1.000 0.000
#> SRR1947569 1 0.0000 0.9641 1.000 0.000
#> SRR1947566 2 0.0000 0.9633 0.000 1.000
#> SRR1947567 2 0.0000 0.9633 0.000 1.000
#> SRR1947568 2 0.0000 0.9633 0.000 1.000
#> SRR1947564 2 0.0000 0.9633 0.000 1.000
#> SRR1947563 2 0.9983 0.0908 0.476 0.524
#> SRR1947562 2 0.0000 0.9633 0.000 1.000
#> SRR1947565 1 0.0000 0.9641 1.000 0.000
#> SRR1947559 2 0.0000 0.9633 0.000 1.000
#> SRR1947560 1 0.0000 0.9641 1.000 0.000
#> SRR1947561 2 0.0000 0.9633 0.000 1.000
#> SRR1947557 1 0.0376 0.9625 0.996 0.004
#> SRR1947558 1 0.0000 0.9641 1.000 0.000
#> SRR1947556 1 0.0376 0.9625 0.996 0.004
#> SRR1947553 2 0.0000 0.9633 0.000 1.000
#> SRR1947554 2 0.5842 0.8130 0.140 0.860
#> SRR1947555 2 0.0000 0.9633 0.000 1.000
#> SRR1947550 2 0.0000 0.9633 0.000 1.000
#> SRR1947552 2 0.0000 0.9633 0.000 1.000
#> SRR1947549 1 0.0000 0.9641 1.000 0.000
#> SRR1947551 1 0.0000 0.9641 1.000 0.000
#> SRR1947548 2 0.0000 0.9633 0.000 1.000
#> SRR1947506 1 0.0000 0.9641 1.000 0.000
#> SRR1947507 1 0.0376 0.9625 0.996 0.004
#> SRR1947504 2 0.9988 0.0725 0.480 0.520
#> SRR1947503 2 0.0000 0.9633 0.000 1.000
#> SRR1947502 2 0.0000 0.9633 0.000 1.000
#> SRR1947501 2 0.0000 0.9633 0.000 1.000
#> SRR1947499 1 0.0000 0.9641 1.000 0.000
#> SRR1947498 1 0.0000 0.9641 1.000 0.000
#> SRR1947508 1 0.0000 0.9641 1.000 0.000
#> SRR1947505 2 0.0376 0.9599 0.004 0.996
#> SRR1947497 2 0.0000 0.9633 0.000 1.000
#> SRR1947496 1 0.0376 0.9625 0.996 0.004
#> SRR1947495 2 0.0000 0.9633 0.000 1.000
#> SRR1947494 2 0.0000 0.9633 0.000 1.000
#> SRR1947493 1 0.0000 0.9641 1.000 0.000
#> SRR1947492 1 0.0376 0.9625 0.996 0.004
#> SRR1947500 2 0.0000 0.9633 0.000 1.000
#> SRR1947491 2 0.0000 0.9633 0.000 1.000
#> SRR1947490 1 0.0376 0.9625 0.996 0.004
#> SRR1947489 1 0.0000 0.9641 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947546 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947545 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947544 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947542 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947541 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947540 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947539 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947538 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947537 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947536 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947535 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947534 1 0.595 0.445 0.640 0.360 0.000
#> SRR1947533 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947532 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947531 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947530 1 0.334 0.820 0.880 0.000 0.120
#> SRR1947529 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947528 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947527 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947526 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947525 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947524 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947523 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947521 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947520 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947519 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947518 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947517 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947516 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947515 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947514 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947513 1 0.611 0.357 0.604 0.396 0.000
#> SRR1947512 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947511 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947510 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947572 2 0.613 0.340 0.400 0.600 0.000
#> SRR1947611 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947509 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947644 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947643 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947642 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947640 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947641 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947639 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947638 2 0.613 0.296 0.400 0.600 0.000
#> SRR1947637 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947636 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947635 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947634 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947633 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947632 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947631 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947629 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947630 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947627 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947628 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947626 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947625 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947624 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947623 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947622 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947621 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947620 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947619 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947617 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947618 2 0.776 0.225 0.380 0.564 0.056
#> SRR1947616 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947615 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947614 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947613 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947610 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947612 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947609 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947608 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947606 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947607 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947604 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947605 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947603 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947602 1 0.627 0.232 0.548 0.000 0.452
#> SRR1947600 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947601 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947598 2 0.116 0.941 0.000 0.972 0.028
#> SRR1947599 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947597 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947596 2 0.541 0.763 0.136 0.812 0.052
#> SRR1947595 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947594 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947592 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947591 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947590 2 0.573 0.703 0.196 0.772 0.032
#> SRR1947588 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947587 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947586 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947585 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947584 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947583 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947582 1 0.604 0.744 0.772 0.172 0.056
#> SRR1947580 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947581 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947576 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947575 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947579 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947578 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947573 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947574 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947571 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947577 2 0.583 0.454 0.340 0.660 0.000
#> SRR1947570 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947569 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947566 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947567 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947568 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947564 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947563 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947562 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947565 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947559 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947560 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947561 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947557 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947558 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947556 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947553 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947554 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947555 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947550 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947552 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947549 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947551 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947548 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947506 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947507 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947504 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947503 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947502 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947501 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947499 1 0.610 0.391 0.608 0.000 0.392
#> SRR1947498 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947508 3 0.000 1.000 0.000 0.000 1.000
#> SRR1947505 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947497 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947496 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947495 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947494 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947493 1 0.196 0.878 0.944 0.000 0.056
#> SRR1947492 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947500 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947491 2 0.000 0.971 0.000 1.000 0.000
#> SRR1947490 1 0.000 0.918 1.000 0.000 0.000
#> SRR1947489 3 0.000 1.000 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.1557 0.916 0.000 0.000 0.944 0.056
#> SRR1947546 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947545 1 0.1557 0.869 0.944 0.000 0.000 0.056
#> SRR1947544 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947541 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947540 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947539 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947538 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947537 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947536 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947535 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947534 2 0.4866 0.250 0.404 0.596 0.000 0.000
#> SRR1947533 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947532 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947531 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947530 1 0.2760 0.801 0.872 0.000 0.128 0.000
#> SRR1947529 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947528 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947527 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947526 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947525 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947524 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947521 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947520 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947519 3 0.0921 0.938 0.000 0.000 0.972 0.028
#> SRR1947518 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947517 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947516 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947515 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947513 1 0.4967 0.226 0.548 0.000 0.000 0.452
#> SRR1947512 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947510 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947572 4 0.6197 0.344 0.400 0.056 0.000 0.544
#> SRR1947611 3 0.3610 0.835 0.000 0.200 0.800 0.000
#> SRR1947509 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947644 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947643 2 0.4164 0.816 0.000 0.736 0.000 0.264
#> SRR1947642 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947640 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947641 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947639 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947638 4 0.4643 0.396 0.344 0.000 0.000 0.656
#> SRR1947637 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947636 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947635 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947634 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947633 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947632 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947631 3 0.0707 0.943 0.000 0.000 0.980 0.020
#> SRR1947629 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.0000 0.749 0.000 1.000 0.000 0.000
#> SRR1947627 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947628 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947626 2 0.4277 0.794 0.000 0.720 0.000 0.280
#> SRR1947625 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.0000 0.749 0.000 1.000 0.000 0.000
#> SRR1947623 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947622 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947621 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947620 1 0.1557 0.869 0.944 0.000 0.000 0.056
#> SRR1947619 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947617 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947618 4 0.5558 0.385 0.324 0.000 0.036 0.640
#> SRR1947616 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947615 3 0.0921 0.938 0.000 0.000 0.972 0.028
#> SRR1947614 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947613 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947612 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947609 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947608 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947607 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947603 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947602 1 0.6271 0.125 0.492 0.000 0.452 0.056
#> SRR1947600 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947598 4 0.0707 0.901 0.000 0.000 0.020 0.980
#> SRR1947599 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947597 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947596 4 0.5119 0.651 0.112 0.000 0.124 0.764
#> SRR1947595 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947594 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947590 4 0.5346 0.616 0.192 0.000 0.076 0.732
#> SRR1947588 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947586 2 0.4250 0.800 0.000 0.724 0.000 0.276
#> SRR1947585 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947582 1 0.4988 0.666 0.728 0.000 0.036 0.236
#> SRR1947580 2 0.4250 0.800 0.000 0.724 0.000 0.276
#> SRR1947581 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.4804 0.577 0.000 0.384 0.616 0.000
#> SRR1947575 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947578 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947573 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947574 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947571 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947577 4 0.4304 0.532 0.284 0.000 0.000 0.716
#> SRR1947570 3 0.1557 0.916 0.000 0.000 0.944 0.056
#> SRR1947569 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947566 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947567 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947568 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947564 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947563 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947562 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947565 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947559 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947560 2 0.4164 0.398 0.000 0.736 0.264 0.000
#> SRR1947561 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947557 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947556 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947553 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947554 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947555 2 0.3486 0.898 0.000 0.812 0.000 0.188
#> SRR1947550 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947552 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947549 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947551 3 0.3172 0.870 0.000 0.160 0.840 0.000
#> SRR1947548 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947506 3 0.1557 0.916 0.000 0.000 0.944 0.056
#> SRR1947507 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947503 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947502 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947501 4 0.1557 0.914 0.000 0.056 0.000 0.944
#> SRR1947499 1 0.5660 0.326 0.576 0.000 0.396 0.028
#> SRR1947498 3 0.0000 0.953 0.000 0.000 1.000 0.000
#> SRR1947508 3 0.0921 0.938 0.000 0.000 0.972 0.028
#> SRR1947505 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947497 2 0.3172 0.922 0.000 0.840 0.000 0.160
#> SRR1947496 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.3219 0.919 0.000 0.836 0.000 0.164
#> SRR1947494 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947493 1 0.2868 0.793 0.864 0.000 0.136 0.000
#> SRR1947492 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947491 4 0.0000 0.916 0.000 0.000 0.000 1.000
#> SRR1947490 1 0.0000 0.905 1.000 0.000 0.000 0.000
#> SRR1947489 3 0.0921 0.938 0.000 0.000 0.972 0.028
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.2291 0.8353 0.000 0.000 0.908 0.036 0.056
#> SRR1947546 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947545 5 0.4990 0.3680 0.384 0.000 0.000 0.036 0.580
#> SRR1947544 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947541 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947540 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947539 3 0.2966 0.8078 0.000 0.000 0.816 0.000 0.184
#> SRR1947538 4 0.0162 0.8262 0.000 0.000 0.000 0.996 0.004
#> SRR1947537 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947536 3 0.3003 0.6799 0.000 0.000 0.812 0.000 0.188
#> SRR1947535 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 2 0.5886 0.4286 0.176 0.600 0.000 0.000 0.224
#> SRR1947533 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947532 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947531 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947530 5 0.4942 0.1869 0.432 0.000 0.028 0.000 0.540
#> SRR1947529 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947528 3 0.1410 0.8581 0.000 0.000 0.940 0.000 0.060
#> SRR1947527 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947526 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947525 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947524 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947521 3 0.4825 0.6320 0.000 0.024 0.568 0.000 0.408
#> SRR1947520 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947519 3 0.0162 0.8600 0.000 0.000 0.996 0.000 0.004
#> SRR1947518 4 0.0290 0.8242 0.000 0.000 0.000 0.992 0.008
#> SRR1947517 3 0.4825 0.6320 0.000 0.024 0.568 0.000 0.408
#> SRR1947516 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947515 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947514 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947513 5 0.5941 0.6378 0.180 0.000 0.000 0.228 0.592
#> SRR1947512 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947510 3 0.4825 0.6320 0.000 0.024 0.568 0.000 0.408
#> SRR1947572 4 0.5028 0.3047 0.400 0.036 0.000 0.564 0.000
#> SRR1947611 3 0.4709 0.6379 0.000 0.024 0.612 0.000 0.364
#> SRR1947509 5 0.4722 -0.3536 0.000 0.024 0.368 0.000 0.608
#> SRR1947644 3 0.4709 0.6379 0.000 0.024 0.612 0.000 0.364
#> SRR1947643 2 0.2773 0.7956 0.000 0.836 0.000 0.164 0.000
#> SRR1947642 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947640 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947641 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947638 5 0.5831 0.6185 0.140 0.000 0.000 0.268 0.592
#> SRR1947637 3 0.4709 0.6379 0.000 0.024 0.612 0.000 0.364
#> SRR1947636 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947635 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947634 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947633 3 0.3336 0.7815 0.000 0.000 0.772 0.000 0.228
#> SRR1947632 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947631 3 0.0162 0.8600 0.000 0.000 0.996 0.004 0.000
#> SRR1947629 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 2 0.0963 0.8719 0.000 0.964 0.000 0.000 0.036
#> SRR1947627 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947628 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947626 2 0.3039 0.7601 0.000 0.808 0.000 0.192 0.000
#> SRR1947625 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.0963 0.8719 0.000 0.964 0.000 0.000 0.036
#> SRR1947623 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947621 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947620 5 0.4958 0.3879 0.372 0.000 0.000 0.036 0.592
#> SRR1947619 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947617 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947618 5 0.5831 0.6185 0.140 0.000 0.000 0.268 0.592
#> SRR1947616 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947615 3 0.2179 0.7653 0.000 0.000 0.888 0.000 0.112
#> SRR1947614 3 0.4825 0.6320 0.000 0.024 0.568 0.000 0.408
#> SRR1947613 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947612 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947609 5 0.4201 0.4031 0.000 0.000 0.000 0.408 0.592
#> SRR1947608 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947606 3 0.1410 0.8581 0.000 0.000 0.940 0.000 0.060
#> SRR1947607 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947605 1 0.3305 0.6738 0.776 0.000 0.000 0.000 0.224
#> SRR1947603 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947602 5 0.6248 0.5344 0.172 0.000 0.160 0.036 0.632
#> SRR1947600 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947598 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947599 5 0.4201 0.4031 0.000 0.000 0.000 0.408 0.592
#> SRR1947597 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947596 4 0.6202 -0.0295 0.108 0.000 0.008 0.476 0.408
#> SRR1947595 4 0.0609 0.8169 0.000 0.000 0.000 0.980 0.020
#> SRR1947594 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947591 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947590 4 0.6420 -0.0911 0.176 0.000 0.000 0.448 0.376
#> SRR1947588 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.1121 0.8562 0.000 0.000 0.956 0.000 0.044
#> SRR1947586 2 0.2891 0.7816 0.000 0.824 0.000 0.176 0.000
#> SRR1947585 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947582 5 0.5950 0.6353 0.188 0.000 0.000 0.220 0.592
#> SRR1947580 2 0.2891 0.7816 0.000 0.824 0.000 0.176 0.000
#> SRR1947581 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.6451 0.4390 0.000 0.184 0.452 0.000 0.364
#> SRR1947575 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947579 3 0.4825 0.6320 0.000 0.024 0.568 0.000 0.408
#> SRR1947578 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947573 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947574 4 0.3424 0.5751 0.000 0.000 0.000 0.760 0.240
#> SRR1947571 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947577 5 0.5797 0.6106 0.132 0.000 0.000 0.276 0.592
#> SRR1947570 5 0.4820 0.4293 0.000 0.000 0.332 0.036 0.632
#> SRR1947569 3 0.0162 0.8616 0.000 0.000 0.996 0.000 0.004
#> SRR1947566 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947567 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947568 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947564 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947563 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947562 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947565 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947559 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947560 2 0.6058 0.3622 0.000 0.508 0.128 0.000 0.364
#> SRR1947561 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947557 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947554 1 0.0510 0.9499 0.984 0.000 0.000 0.000 0.016
#> SRR1947555 2 0.1270 0.9057 0.000 0.948 0.000 0.052 0.000
#> SRR1947550 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947552 5 0.4201 0.4031 0.000 0.000 0.000 0.408 0.592
#> SRR1947549 3 0.1544 0.8582 0.000 0.000 0.932 0.000 0.068
#> SRR1947551 3 0.4709 0.6379 0.000 0.024 0.612 0.000 0.364
#> SRR1947548 4 0.3561 0.5442 0.000 0.000 0.000 0.740 0.260
#> SRR1947506 5 0.5112 0.0923 0.000 0.000 0.468 0.036 0.496
#> SRR1947507 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947503 5 0.4201 0.4031 0.000 0.000 0.000 0.408 0.592
#> SRR1947502 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947501 4 0.0963 0.8426 0.000 0.036 0.000 0.964 0.000
#> SRR1947499 5 0.5992 0.5133 0.200 0.000 0.152 0.016 0.632
#> SRR1947498 3 0.0000 0.8615 0.000 0.000 1.000 0.000 0.000
#> SRR1947508 3 0.2377 0.7655 0.000 0.000 0.872 0.000 0.128
#> SRR1947505 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947497 2 0.0703 0.9256 0.000 0.976 0.000 0.024 0.000
#> SRR1947496 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.1121 0.9119 0.000 0.956 0.000 0.044 0.000
#> SRR1947494 4 0.4088 0.3461 0.000 0.000 0.000 0.632 0.368
#> SRR1947493 1 0.4040 0.5865 0.712 0.000 0.012 0.000 0.276
#> SRR1947492 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947491 4 0.0000 0.8279 0.000 0.000 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.9655 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.2127 0.7698 0.000 0.000 0.892 0.000 0.108
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.1531 0.8691 0.000 0.000 0.928 0.000 0.004 0.068
#> SRR1947546 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947545 6 0.2260 0.6360 0.140 0.000 0.000 0.000 0.000 0.860
#> SRR1947544 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947542 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947541 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947540 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947539 3 0.3499 0.6071 0.000 0.000 0.680 0.000 0.320 0.000
#> SRR1947538 4 0.1075 0.8945 0.000 0.000 0.000 0.952 0.000 0.048
#> SRR1947537 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947536 3 0.3409 0.5737 0.000 0.000 0.700 0.000 0.000 0.300
#> SRR1947535 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 2 0.4433 0.4732 0.040 0.616 0.000 0.000 0.000 0.344
#> SRR1947533 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947531 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947530 6 0.2491 0.6048 0.164 0.000 0.000 0.000 0.000 0.836
#> SRR1947529 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947528 3 0.2092 0.8689 0.000 0.000 0.876 0.000 0.124 0.000
#> SRR1947527 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947525 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947524 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947521 5 0.0000 0.9511 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947519 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947518 4 0.0937 0.9032 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947517 5 0.0000 0.9511 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947514 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947512 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.9511 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.3756 0.3620 0.400 0.000 0.000 0.600 0.000 0.000
#> SRR1947611 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947509 5 0.0146 0.9487 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947644 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947643 2 0.0146 0.9769 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947642 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947640 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947641 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947638 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947637 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947636 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947635 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947634 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947633 5 0.3833 0.0465 0.000 0.000 0.444 0.000 0.556 0.000
#> SRR1947632 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947631 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947627 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947628 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947626 2 0.0790 0.9449 0.000 0.968 0.000 0.032 0.000 0.000
#> SRR1947625 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947623 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947622 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947619 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947617 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947616 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947615 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947614 5 0.0000 0.9511 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947612 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 6 0.0713 0.7678 0.000 0.000 0.000 0.028 0.000 0.972
#> SRR1947608 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947606 3 0.1387 0.8943 0.000 0.000 0.932 0.000 0.068 0.000
#> SRR1947607 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947605 1 0.3684 0.5134 0.628 0.000 0.000 0.000 0.000 0.372
#> SRR1947603 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947602 6 0.1152 0.7382 0.000 0.000 0.044 0.000 0.004 0.952
#> SRR1947600 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947599 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947597 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947596 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947595 4 0.2823 0.6685 0.000 0.000 0.000 0.796 0.000 0.204
#> SRR1947594 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947591 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947588 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0146 0.9152 0.000 0.000 0.996 0.000 0.004 0.000
#> SRR1947586 2 0.0146 0.9769 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947585 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947582 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947580 2 0.0146 0.9769 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947581 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947575 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 5 0.0000 0.9511 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947573 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947574 4 0.3843 -0.0570 0.000 0.000 0.000 0.548 0.000 0.452
#> SRR1947571 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947577 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947570 6 0.0146 0.7676 0.000 0.000 0.000 0.000 0.004 0.996
#> SRR1947569 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947568 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947564 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947563 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947562 4 0.0146 0.9385 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1947565 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947559 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947560 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947561 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947553 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947554 1 0.2454 0.7694 0.840 0.000 0.000 0.000 0.000 0.160
#> SRR1947555 2 0.0713 0.9516 0.000 0.972 0.000 0.028 0.000 0.000
#> SRR1947550 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947552 6 0.0713 0.7678 0.000 0.000 0.000 0.028 0.000 0.972
#> SRR1947549 3 0.2378 0.8534 0.000 0.000 0.848 0.000 0.152 0.000
#> SRR1947551 5 0.0146 0.9513 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947548 4 0.3857 -0.1187 0.000 0.000 0.000 0.532 0.000 0.468
#> SRR1947506 6 0.3271 0.5220 0.000 0.000 0.232 0.000 0.008 0.760
#> SRR1947507 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947503 6 0.0000 0.7694 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947502 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947499 6 0.0146 0.7676 0.000 0.000 0.000 0.000 0.004 0.996
#> SRR1947498 3 0.0000 0.9167 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947508 3 0.2762 0.7211 0.000 0.000 0.804 0.000 0.000 0.196
#> SRR1947505 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947497 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9802 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947494 6 0.3684 0.5434 0.000 0.000 0.000 0.372 0.000 0.628
#> SRR1947493 1 0.3841 0.4943 0.616 0.000 0.000 0.000 0.004 0.380
#> SRR1947492 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947491 4 0.0000 0.9420 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947490 1 0.0000 0.9433 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0000 0.9167 0.000 0.000 1.000 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 15148 rows and 152 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 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 1.000 1.000 0.4578 0.543 0.543
#> 3 3 0.609 0.729 0.830 0.2805 0.941 0.893
#> 4 4 0.665 0.667 0.816 0.1835 0.739 0.504
#> 5 5 0.872 0.884 0.946 0.1107 0.866 0.595
#> 6 6 0.811 0.786 0.890 0.0245 0.901 0.636
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
#> SRR1947547 2 0 1 0 1
#> SRR1947546 1 0 1 1 0
#> SRR1947545 1 0 1 1 0
#> SRR1947544 1 0 1 1 0
#> SRR1947542 1 0 1 1 0
#> SRR1947541 2 0 1 0 1
#> SRR1947540 1 0 1 1 0
#> SRR1947539 2 0 1 0 1
#> SRR1947538 1 0 1 1 0
#> SRR1947537 2 0 1 0 1
#> SRR1947536 2 0 1 0 1
#> SRR1947535 2 0 1 0 1
#> SRR1947534 1 0 1 1 0
#> SRR1947533 1 0 1 1 0
#> SRR1947532 1 0 1 1 0
#> SRR1947531 1 0 1 1 0
#> SRR1947530 2 0 1 0 1
#> SRR1947529 1 0 1 1 0
#> SRR1947528 2 0 1 0 1
#> SRR1947527 1 0 1 1 0
#> SRR1947526 1 0 1 1 0
#> SRR1947525 1 0 1 1 0
#> SRR1947524 2 0 1 0 1
#> SRR1947523 1 0 1 1 0
#> SRR1947521 2 0 1 0 1
#> SRR1947520 1 0 1 1 0
#> SRR1947519 2 0 1 0 1
#> SRR1947518 1 0 1 1 0
#> SRR1947517 2 0 1 0 1
#> SRR1947516 1 0 1 1 0
#> SRR1947515 1 0 1 1 0
#> SRR1947514 1 0 1 1 0
#> SRR1947513 1 0 1 1 0
#> SRR1947512 1 0 1 1 0
#> SRR1947511 1 0 1 1 0
#> SRR1947510 2 0 1 0 1
#> SRR1947572 1 0 1 1 0
#> SRR1947611 2 0 1 0 1
#> SRR1947509 2 0 1 0 1
#> SRR1947644 2 0 1 0 1
#> SRR1947643 1 0 1 1 0
#> SRR1947642 2 0 1 0 1
#> SRR1947640 1 0 1 1 0
#> SRR1947641 2 0 1 0 1
#> SRR1947639 1 0 1 1 0
#> SRR1947638 1 0 1 1 0
#> SRR1947637 2 0 1 0 1
#> SRR1947636 2 0 1 0 1
#> SRR1947635 1 0 1 1 0
#> SRR1947634 1 0 1 1 0
#> SRR1947633 2 0 1 0 1
#> SRR1947632 1 0 1 1 0
#> SRR1947631 2 0 1 0 1
#> SRR1947629 2 0 1 0 1
#> SRR1947630 1 0 1 1 0
#> SRR1947627 2 0 1 0 1
#> SRR1947628 1 0 1 1 0
#> SRR1947626 1 0 1 1 0
#> SRR1947625 2 0 1 0 1
#> SRR1947624 1 0 1 1 0
#> SRR1947623 1 0 1 1 0
#> SRR1947622 1 0 1 1 0
#> SRR1947621 1 0 1 1 0
#> SRR1947620 1 0 1 1 0
#> SRR1947619 2 0 1 0 1
#> SRR1947617 1 0 1 1 0
#> SRR1947618 1 0 1 1 0
#> SRR1947616 1 0 1 1 0
#> SRR1947615 2 0 1 0 1
#> SRR1947614 2 0 1 0 1
#> SRR1947613 1 0 1 1 0
#> SRR1947610 1 0 1 1 0
#> SRR1947612 1 0 1 1 0
#> SRR1947609 1 0 1 1 0
#> SRR1947608 2 0 1 0 1
#> SRR1947606 2 0 1 0 1
#> SRR1947607 1 0 1 1 0
#> SRR1947604 1 0 1 1 0
#> SRR1947605 1 0 1 1 0
#> SRR1947603 1 0 1 1 0
#> SRR1947602 2 0 1 0 1
#> SRR1947600 2 0 1 0 1
#> SRR1947601 1 0 1 1 0
#> SRR1947598 1 0 1 1 0
#> SRR1947599 1 0 1 1 0
#> SRR1947597 1 0 1 1 0
#> SRR1947596 1 0 1 1 0
#> SRR1947595 1 0 1 1 0
#> SRR1947594 1 0 1 1 0
#> SRR1947592 2 0 1 0 1
#> SRR1947591 1 0 1 1 0
#> SRR1947590 1 0 1 1 0
#> SRR1947588 1 0 1 1 0
#> SRR1947587 2 0 1 0 1
#> SRR1947586 1 0 1 1 0
#> SRR1947585 2 0 1 0 1
#> SRR1947584 1 0 1 1 0
#> SRR1947583 1 0 1 1 0
#> SRR1947582 1 0 1 1 0
#> SRR1947580 1 0 1 1 0
#> SRR1947581 1 0 1 1 0
#> SRR1947576 2 0 1 0 1
#> SRR1947575 2 0 1 0 1
#> SRR1947579 2 0 1 0 1
#> SRR1947578 1 0 1 1 0
#> SRR1947573 2 0 1 0 1
#> SRR1947574 1 0 1 1 0
#> SRR1947571 1 0 1 1 0
#> SRR1947577 1 0 1 1 0
#> SRR1947570 2 0 1 0 1
#> SRR1947569 2 0 1 0 1
#> SRR1947566 1 0 1 1 0
#> SRR1947567 1 0 1 1 0
#> SRR1947568 1 0 1 1 0
#> SRR1947564 1 0 1 1 0
#> SRR1947563 2 0 1 0 1
#> SRR1947562 1 0 1 1 0
#> SRR1947565 2 0 1 0 1
#> SRR1947559 1 0 1 1 0
#> SRR1947560 2 0 1 0 1
#> SRR1947561 1 0 1 1 0
#> SRR1947557 1 0 1 1 0
#> SRR1947558 2 0 1 0 1
#> SRR1947556 1 0 1 1 0
#> SRR1947553 1 0 1 1 0
#> SRR1947554 1 0 1 1 0
#> SRR1947555 1 0 1 1 0
#> SRR1947550 1 0 1 1 0
#> SRR1947552 1 0 1 1 0
#> SRR1947549 2 0 1 0 1
#> SRR1947551 2 0 1 0 1
#> SRR1947548 1 0 1 1 0
#> SRR1947506 2 0 1 0 1
#> SRR1947507 1 0 1 1 0
#> SRR1947504 1 0 1 1 0
#> SRR1947503 1 0 1 1 0
#> SRR1947502 1 0 1 1 0
#> SRR1947501 1 0 1 1 0
#> SRR1947499 2 0 1 0 1
#> SRR1947498 2 0 1 0 1
#> SRR1947508 2 0 1 0 1
#> SRR1947505 1 0 1 1 0
#> SRR1947497 1 0 1 1 0
#> SRR1947496 1 0 1 1 0
#> SRR1947495 1 0 1 1 0
#> SRR1947494 1 0 1 1 0
#> SRR1947493 2 0 1 0 1
#> SRR1947492 1 0 1 1 0
#> SRR1947500 1 0 1 1 0
#> SRR1947491 1 0 1 1 0
#> SRR1947490 1 0 1 1 0
#> SRR1947489 2 0 1 0 1
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947546 2 0.2537 0.8022 0.080 0.920 0.000
#> SRR1947545 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947544 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947542 2 0.0747 0.8118 0.016 0.984 0.000
#> SRR1947541 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947540 2 0.3116 0.7901 0.108 0.892 0.000
#> SRR1947539 3 0.0424 0.9291 0.008 0.000 0.992
#> SRR1947538 2 0.0592 0.8125 0.012 0.988 0.000
#> SRR1947537 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947536 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947535 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947534 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947533 2 0.6295 0.4352 0.472 0.528 0.000
#> SRR1947532 2 0.1031 0.8116 0.024 0.976 0.000
#> SRR1947531 2 0.3116 0.7901 0.108 0.892 0.000
#> SRR1947530 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947529 2 0.3752 0.7904 0.144 0.856 0.000
#> SRR1947528 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947527 2 0.5216 0.7848 0.260 0.740 0.000
#> SRR1947526 2 0.6299 0.4295 0.476 0.524 0.000
#> SRR1947525 2 0.4062 0.7971 0.164 0.836 0.000
#> SRR1947524 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947523 2 0.1411 0.8111 0.036 0.964 0.000
#> SRR1947521 1 0.6309 0.2223 0.504 0.000 0.496
#> SRR1947520 1 0.6305 -0.4006 0.516 0.484 0.000
#> SRR1947519 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947518 2 0.4002 0.8069 0.160 0.840 0.000
#> SRR1947517 3 0.6295 -0.1822 0.472 0.000 0.528
#> SRR1947516 2 0.6302 0.4328 0.480 0.520 0.000
#> SRR1947515 2 0.1031 0.8116 0.024 0.976 0.000
#> SRR1947514 2 0.6026 0.6346 0.376 0.624 0.000
#> SRR1947513 2 0.3941 0.7782 0.156 0.844 0.000
#> SRR1947512 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947511 2 0.6299 0.4295 0.476 0.524 0.000
#> SRR1947510 1 0.6291 0.3181 0.532 0.000 0.468
#> SRR1947572 2 0.4291 0.8038 0.180 0.820 0.000
#> SRR1947611 1 0.5988 0.4709 0.632 0.000 0.368
#> SRR1947509 3 0.6260 -0.0826 0.448 0.000 0.552
#> SRR1947644 3 0.6215 -0.0132 0.428 0.000 0.572
#> SRR1947643 2 0.5560 0.6013 0.300 0.700 0.000
#> SRR1947642 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947640 2 0.2959 0.8180 0.100 0.900 0.000
#> SRR1947641 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947639 2 0.4399 0.8049 0.188 0.812 0.000
#> SRR1947638 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947637 1 0.6008 0.4671 0.628 0.000 0.372
#> SRR1947636 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947635 2 0.2448 0.8027 0.076 0.924 0.000
#> SRR1947634 2 0.6299 0.4295 0.476 0.524 0.000
#> SRR1947633 3 0.2625 0.8499 0.084 0.000 0.916
#> SRR1947632 2 0.1163 0.8117 0.028 0.972 0.000
#> SRR1947631 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947630 1 0.6154 -0.2069 0.592 0.408 0.000
#> SRR1947627 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947628 2 0.2711 0.7996 0.088 0.912 0.000
#> SRR1947626 2 0.4654 0.7828 0.208 0.792 0.000
#> SRR1947625 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947624 1 0.6154 -0.2069 0.592 0.408 0.000
#> SRR1947623 2 0.4796 0.7829 0.220 0.780 0.000
#> SRR1947622 2 0.2959 0.8010 0.100 0.900 0.000
#> SRR1947621 2 0.6274 0.4809 0.456 0.544 0.000
#> SRR1947620 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947619 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947617 2 0.6062 0.6005 0.384 0.616 0.000
#> SRR1947618 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947616 2 0.6062 0.4549 0.384 0.616 0.000
#> SRR1947615 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947614 1 0.6291 0.3181 0.532 0.000 0.468
#> SRR1947613 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947610 2 0.4702 0.8017 0.212 0.788 0.000
#> SRR1947612 2 0.5706 0.6904 0.320 0.680 0.000
#> SRR1947609 2 0.2796 0.7970 0.092 0.908 0.000
#> SRR1947608 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947607 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947604 2 0.0892 0.8117 0.020 0.980 0.000
#> SRR1947605 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947603 2 0.3412 0.7869 0.124 0.876 0.000
#> SRR1947602 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947600 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947601 2 0.6299 0.4295 0.476 0.524 0.000
#> SRR1947598 2 0.0747 0.8128 0.016 0.984 0.000
#> SRR1947599 2 0.2261 0.8028 0.068 0.932 0.000
#> SRR1947597 2 0.4235 0.7926 0.176 0.824 0.000
#> SRR1947596 2 0.1860 0.8061 0.052 0.948 0.000
#> SRR1947595 2 0.2711 0.7986 0.088 0.912 0.000
#> SRR1947594 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947592 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947591 2 0.6302 0.4328 0.480 0.520 0.000
#> SRR1947590 2 0.1643 0.8079 0.044 0.956 0.000
#> SRR1947588 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947587 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947586 2 0.5098 0.7885 0.248 0.752 0.000
#> SRR1947585 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947584 2 0.4750 0.7786 0.216 0.784 0.000
#> SRR1947583 2 0.3038 0.8116 0.104 0.896 0.000
#> SRR1947582 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947580 2 0.6267 0.4752 0.452 0.548 0.000
#> SRR1947581 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947576 1 0.5882 0.4817 0.652 0.000 0.348
#> SRR1947575 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947579 1 0.6291 0.3181 0.532 0.000 0.468
#> SRR1947578 2 0.3116 0.7901 0.108 0.892 0.000
#> SRR1947573 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947574 2 0.3752 0.8081 0.144 0.856 0.000
#> SRR1947571 2 0.0592 0.8119 0.012 0.988 0.000
#> SRR1947577 2 0.3686 0.7751 0.140 0.860 0.000
#> SRR1947570 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947569 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947566 2 0.6062 0.4549 0.384 0.616 0.000
#> SRR1947567 2 0.2356 0.8042 0.072 0.928 0.000
#> SRR1947568 2 0.4555 0.8052 0.200 0.800 0.000
#> SRR1947564 2 0.4605 0.7789 0.204 0.796 0.000
#> SRR1947563 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947562 2 0.0892 0.8119 0.020 0.980 0.000
#> SRR1947565 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947559 2 0.3116 0.8017 0.108 0.892 0.000
#> SRR1947560 1 0.5882 0.4817 0.652 0.000 0.348
#> SRR1947561 2 0.6302 0.4328 0.480 0.520 0.000
#> SRR1947557 2 0.4750 0.7786 0.216 0.784 0.000
#> SRR1947558 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947556 2 0.3551 0.7796 0.132 0.868 0.000
#> SRR1947553 2 0.4291 0.8068 0.180 0.820 0.000
#> SRR1947554 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947555 2 0.6111 0.4311 0.396 0.604 0.000
#> SRR1947550 2 0.1163 0.8118 0.028 0.972 0.000
#> SRR1947552 2 0.0892 0.8110 0.020 0.980 0.000
#> SRR1947549 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947551 3 0.6260 -0.1012 0.448 0.000 0.552
#> SRR1947548 2 0.1031 0.8116 0.024 0.976 0.000
#> SRR1947506 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947507 2 0.4887 0.7775 0.228 0.772 0.000
#> SRR1947504 2 0.4796 0.7829 0.220 0.780 0.000
#> SRR1947503 2 0.3116 0.7911 0.108 0.892 0.000
#> SRR1947502 2 0.6026 0.6119 0.376 0.624 0.000
#> SRR1947501 2 0.2625 0.8010 0.084 0.916 0.000
#> SRR1947499 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947498 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947508 3 0.1289 0.9114 0.032 0.000 0.968
#> SRR1947505 2 0.2537 0.8011 0.080 0.920 0.000
#> SRR1947497 2 0.4504 0.7811 0.196 0.804 0.000
#> SRR1947496 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947495 2 0.4555 0.7824 0.200 0.800 0.000
#> SRR1947494 2 0.0747 0.8114 0.016 0.984 0.000
#> SRR1947493 3 0.0000 0.9355 0.000 0.000 1.000
#> SRR1947492 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947500 2 0.2796 0.8150 0.092 0.908 0.000
#> SRR1947491 2 0.0747 0.8120 0.016 0.984 0.000
#> SRR1947490 2 0.4931 0.7767 0.232 0.768 0.000
#> SRR1947489 3 0.0000 0.9355 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947546 4 0.0921 0.7004 0.000 0.028 0.000 0.972
#> SRR1947545 4 0.4576 0.1680 0.260 0.012 0.000 0.728
#> SRR1947544 4 0.4576 0.1680 0.260 0.012 0.000 0.728
#> SRR1947542 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947541 3 0.0188 0.8953 0.004 0.000 0.996 0.000
#> SRR1947540 4 0.1940 0.6742 0.000 0.076 0.000 0.924
#> SRR1947539 3 0.1302 0.8796 0.044 0.000 0.956 0.000
#> SRR1947538 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947537 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947536 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947535 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947534 4 0.7535 -0.4285 0.336 0.200 0.000 0.464
#> SRR1947533 2 0.2469 0.7461 0.000 0.892 0.000 0.108
#> SRR1947532 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947531 4 0.2081 0.6708 0.000 0.084 0.000 0.916
#> SRR1947530 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947529 4 0.4948 -0.1368 0.000 0.440 0.000 0.560
#> SRR1947528 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947527 2 0.4477 0.6529 0.000 0.688 0.000 0.312
#> SRR1947526 2 0.0188 0.6840 0.000 0.996 0.000 0.004
#> SRR1947525 4 0.4697 0.2851 0.000 0.356 0.000 0.644
#> SRR1947524 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947523 4 0.0469 0.7056 0.000 0.012 0.000 0.988
#> SRR1947521 3 0.6600 0.5908 0.396 0.084 0.520 0.000
#> SRR1947520 2 0.2081 0.6788 0.000 0.916 0.000 0.084
#> SRR1947519 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947518 4 0.4522 0.3660 0.000 0.320 0.000 0.680
#> SRR1947517 3 0.5746 0.6358 0.396 0.032 0.572 0.000
#> SRR1947516 2 0.3837 0.7431 0.000 0.776 0.000 0.224
#> SRR1947515 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947514 2 0.3610 0.7507 0.000 0.800 0.000 0.200
#> SRR1947513 4 0.3672 0.4537 0.164 0.012 0.000 0.824
#> SRR1947512 1 0.5339 0.9636 0.600 0.016 0.000 0.384
#> SRR1947511 2 0.0188 0.6840 0.000 0.996 0.000 0.004
#> SRR1947510 3 0.6600 0.5908 0.396 0.084 0.520 0.000
#> SRR1947572 4 0.5055 0.2557 0.008 0.368 0.000 0.624
#> SRR1947611 3 0.7328 0.5108 0.392 0.156 0.452 0.000
#> SRR1947509 3 0.5016 0.6580 0.396 0.004 0.600 0.000
#> SRR1947644 3 0.5016 0.6580 0.396 0.004 0.600 0.000
#> SRR1947643 4 0.4877 0.0681 0.000 0.408 0.000 0.592
#> SRR1947642 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947640 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947641 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947639 4 0.4746 0.2588 0.000 0.368 0.000 0.632
#> SRR1947638 4 0.3672 0.4537 0.164 0.012 0.000 0.824
#> SRR1947637 3 0.7328 0.5108 0.392 0.156 0.452 0.000
#> SRR1947636 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947635 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947634 2 0.2011 0.6805 0.000 0.920 0.000 0.080
#> SRR1947633 3 0.4122 0.7665 0.236 0.004 0.760 0.000
#> SRR1947632 4 0.0921 0.7004 0.000 0.028 0.000 0.972
#> SRR1947631 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947629 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947630 2 0.2408 0.6670 0.000 0.896 0.000 0.104
#> SRR1947627 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947628 4 0.0592 0.7060 0.000 0.016 0.000 0.984
#> SRR1947626 2 0.4103 0.7191 0.000 0.744 0.000 0.256
#> SRR1947625 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947624 2 0.1302 0.6882 0.000 0.956 0.000 0.044
#> SRR1947623 4 0.7855 -0.3796 0.284 0.320 0.000 0.396
#> SRR1947622 4 0.3024 0.6048 0.000 0.148 0.000 0.852
#> SRR1947621 2 0.3172 0.7523 0.000 0.840 0.000 0.160
#> SRR1947620 4 0.4319 0.2788 0.228 0.012 0.000 0.760
#> SRR1947619 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947617 2 0.3873 0.7407 0.000 0.772 0.000 0.228
#> SRR1947618 4 0.4248 0.3034 0.220 0.012 0.000 0.768
#> SRR1947616 2 0.4994 0.0888 0.000 0.520 0.000 0.480
#> SRR1947615 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947614 3 0.6600 0.5908 0.396 0.084 0.520 0.000
#> SRR1947613 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947610 4 0.4746 0.2588 0.000 0.368 0.000 0.632
#> SRR1947612 2 0.3610 0.7507 0.000 0.800 0.000 0.200
#> SRR1947609 4 0.1488 0.6786 0.032 0.012 0.000 0.956
#> SRR1947608 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947606 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947607 1 0.6219 0.8804 0.588 0.068 0.000 0.344
#> SRR1947604 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947605 4 0.4576 0.1680 0.260 0.012 0.000 0.728
#> SRR1947603 4 0.4304 0.3507 0.000 0.284 0.000 0.716
#> SRR1947602 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947600 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947601 2 0.1022 0.7047 0.000 0.968 0.000 0.032
#> SRR1947598 4 0.0469 0.7056 0.000 0.012 0.000 0.988
#> SRR1947599 4 0.0937 0.6974 0.012 0.012 0.000 0.976
#> SRR1947597 4 0.4898 0.1064 0.000 0.416 0.000 0.584
#> SRR1947596 4 0.1389 0.6707 0.048 0.000 0.000 0.952
#> SRR1947595 4 0.3015 0.6527 0.024 0.092 0.000 0.884
#> SRR1947594 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947592 3 0.0000 0.8952 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.3444 0.7534 0.000 0.816 0.000 0.184
#> SRR1947590 4 0.1637 0.6580 0.060 0.000 0.000 0.940
#> SRR1947588 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947587 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947586 2 0.4730 0.5815 0.000 0.636 0.000 0.364
#> SRR1947585 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947584 1 0.5339 0.9636 0.600 0.016 0.000 0.384
#> SRR1947583 4 0.2973 0.5885 0.000 0.144 0.000 0.856
#> SRR1947582 4 0.4319 0.2788 0.228 0.012 0.000 0.760
#> SRR1947580 2 0.2469 0.7461 0.000 0.892 0.000 0.108
#> SRR1947581 1 0.5339 0.9636 0.600 0.016 0.000 0.384
#> SRR1947576 3 0.7328 0.5108 0.392 0.156 0.452 0.000
#> SRR1947575 3 0.0000 0.8952 0.000 0.000 1.000 0.000
#> SRR1947579 3 0.6600 0.5908 0.396 0.084 0.520 0.000
#> SRR1947578 4 0.3400 0.5681 0.000 0.180 0.000 0.820
#> SRR1947573 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947574 4 0.4857 0.4165 0.016 0.284 0.000 0.700
#> SRR1947571 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947577 4 0.3672 0.4537 0.164 0.012 0.000 0.824
#> SRR1947570 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947569 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947566 2 0.4992 0.1018 0.000 0.524 0.000 0.476
#> SRR1947567 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947568 2 0.5132 0.3921 0.004 0.548 0.000 0.448
#> SRR1947564 2 0.4994 0.2736 0.000 0.520 0.000 0.480
#> SRR1947563 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947562 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947565 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947559 4 0.4661 0.3163 0.000 0.348 0.000 0.652
#> SRR1947560 3 0.7328 0.5108 0.392 0.156 0.452 0.000
#> SRR1947561 2 0.3907 0.7380 0.000 0.768 0.000 0.232
#> SRR1947557 1 0.5339 0.9636 0.600 0.016 0.000 0.384
#> SRR1947558 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947556 4 0.4485 0.2140 0.248 0.012 0.000 0.740
#> SRR1947553 4 0.4746 0.2588 0.000 0.368 0.000 0.632
#> SRR1947554 1 0.5517 0.9111 0.568 0.020 0.000 0.412
#> SRR1947555 2 0.4992 0.1018 0.000 0.524 0.000 0.476
#> SRR1947550 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947552 4 0.0188 0.7092 0.000 0.004 0.000 0.996
#> SRR1947549 3 0.0000 0.8952 0.000 0.000 1.000 0.000
#> SRR1947551 3 0.6600 0.5908 0.396 0.084 0.520 0.000
#> SRR1947548 4 0.0000 0.7101 0.000 0.000 0.000 1.000
#> SRR1947506 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947507 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947504 1 0.7162 0.7625 0.472 0.136 0.000 0.392
#> SRR1947503 4 0.0469 0.7037 0.012 0.000 0.000 0.988
#> SRR1947502 2 0.3764 0.7461 0.000 0.784 0.000 0.216
#> SRR1947501 4 0.0921 0.7004 0.000 0.028 0.000 0.972
#> SRR1947499 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947498 3 0.0188 0.8950 0.004 0.000 0.996 0.000
#> SRR1947508 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947505 4 0.0469 0.7056 0.000 0.012 0.000 0.988
#> SRR1947497 2 0.4697 0.5767 0.000 0.644 0.000 0.356
#> SRR1947496 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947495 2 0.4679 0.5845 0.000 0.648 0.000 0.352
#> SRR1947494 4 0.1174 0.6909 0.020 0.012 0.000 0.968
#> SRR1947493 3 0.0336 0.8952 0.008 0.000 0.992 0.000
#> SRR1947492 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947500 4 0.0188 0.7094 0.000 0.004 0.000 0.996
#> SRR1947491 4 0.0188 0.7092 0.000 0.004 0.000 0.996
#> SRR1947490 1 0.5428 0.9666 0.600 0.020 0.000 0.380
#> SRR1947489 3 0.0336 0.8952 0.008 0.000 0.992 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947546 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947545 1 0.3143 0.763 0.796 0.000 0.000 0.204 0.000
#> SRR1947544 1 0.3143 0.763 0.796 0.000 0.000 0.204 0.000
#> SRR1947542 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947540 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947539 3 0.3366 0.686 0.000 0.000 0.768 0.000 0.232
#> SRR1947538 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947537 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 3 0.2329 0.862 0.000 0.000 0.876 0.000 0.124
#> SRR1947535 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 1 0.3455 0.678 0.784 0.008 0.000 0.208 0.000
#> SRR1947533 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947532 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947531 4 0.0510 0.922 0.000 0.016 0.000 0.984 0.000
#> SRR1947530 3 0.1851 0.903 0.000 0.000 0.912 0.000 0.088
#> SRR1947529 2 0.3752 0.564 0.000 0.708 0.000 0.292 0.000
#> SRR1947528 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947527 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947526 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947525 4 0.2179 0.858 0.000 0.112 0.000 0.888 0.000
#> SRR1947524 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947521 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947520 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947519 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947518 4 0.0324 0.927 0.004 0.004 0.000 0.992 0.000
#> SRR1947517 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947514 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 1 0.4171 0.552 0.604 0.000 0.000 0.396 0.000
#> SRR1947512 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947510 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947572 4 0.2674 0.830 0.004 0.140 0.000 0.856 0.000
#> SRR1947611 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947509 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947644 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947643 2 0.0290 0.940 0.000 0.992 0.000 0.008 0.000
#> SRR1947642 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947640 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947641 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 4 0.3196 0.786 0.004 0.192 0.000 0.804 0.000
#> SRR1947638 1 0.4182 0.546 0.600 0.000 0.000 0.400 0.000
#> SRR1947637 5 0.2648 0.813 0.000 0.000 0.152 0.000 0.848
#> SRR1947636 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947634 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947633 5 0.3210 0.742 0.000 0.000 0.212 0.000 0.788
#> SRR1947632 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947629 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947627 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947628 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947623 4 0.5002 0.491 0.312 0.052 0.000 0.636 0.000
#> SRR1947622 4 0.1043 0.907 0.000 0.040 0.000 0.960 0.000
#> SRR1947621 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.3143 0.763 0.796 0.000 0.000 0.204 0.000
#> SRR1947619 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947617 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.3177 0.761 0.792 0.000 0.000 0.208 0.000
#> SRR1947616 2 0.2648 0.774 0.000 0.848 0.000 0.152 0.000
#> SRR1947615 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947614 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.2966 0.794 0.000 0.184 0.000 0.816 0.000
#> SRR1947612 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947608 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947606 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947607 1 0.1410 0.763 0.940 0.060 0.000 0.000 0.000
#> SRR1947604 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947605 1 0.3143 0.763 0.796 0.000 0.000 0.204 0.000
#> SRR1947603 2 0.4101 0.398 0.000 0.628 0.000 0.372 0.000
#> SRR1947602 3 0.1043 0.950 0.000 0.000 0.960 0.000 0.040
#> SRR1947600 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947599 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947597 4 0.3039 0.786 0.000 0.192 0.000 0.808 0.000
#> SRR1947596 4 0.0290 0.926 0.008 0.000 0.000 0.992 0.000
#> SRR1947595 4 0.1942 0.884 0.012 0.068 0.000 0.920 0.000
#> SRR1947594 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.3003 0.688 0.188 0.000 0.000 0.812 0.000
#> SRR1947588 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947586 2 0.0794 0.920 0.000 0.972 0.000 0.028 0.000
#> SRR1947585 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.0880 0.792 0.968 0.000 0.000 0.032 0.000
#> SRR1947583 4 0.2471 0.837 0.000 0.136 0.000 0.864 0.000
#> SRR1947582 1 0.3177 0.761 0.792 0.000 0.000 0.208 0.000
#> SRR1947580 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947579 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947578 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947573 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 4 0.3266 0.773 0.004 0.200 0.000 0.796 0.000
#> SRR1947571 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947577 1 0.4201 0.531 0.592 0.000 0.000 0.408 0.000
#> SRR1947570 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947569 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 2 0.1851 0.856 0.000 0.912 0.000 0.088 0.000
#> SRR1947567 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947568 4 0.3300 0.772 0.004 0.204 0.000 0.792 0.000
#> SRR1947564 4 0.3074 0.782 0.000 0.196 0.000 0.804 0.000
#> SRR1947563 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947562 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 4 0.1121 0.906 0.000 0.044 0.000 0.956 0.000
#> SRR1947560 5 0.0000 0.961 0.000 0.000 0.000 0.000 1.000
#> SRR1947561 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 1 0.4235 0.467 0.576 0.000 0.000 0.424 0.000
#> SRR1947553 4 0.3003 0.790 0.000 0.188 0.000 0.812 0.000
#> SRR1947554 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.2424 0.801 0.000 0.868 0.000 0.132 0.000
#> SRR1947550 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947552 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947549 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947551 5 0.0162 0.958 0.000 0.000 0.004 0.000 0.996
#> SRR1947548 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947506 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947507 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.4430 0.118 0.540 0.004 0.000 0.456 0.000
#> SRR1947503 4 0.0162 0.928 0.004 0.000 0.000 0.996 0.000
#> SRR1947502 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947499 3 0.1732 0.911 0.000 0.000 0.920 0.000 0.080
#> SRR1947498 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947508 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947505 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947497 2 0.0162 0.943 0.004 0.996 0.000 0.000 0.000
#> SRR1947496 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.945 0.000 1.000 0.000 0.000 0.000
#> SRR1947494 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947493 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.0404 0.924 0.000 0.012 0.000 0.988 0.000
#> SRR1947491 4 0.0000 0.929 0.000 0.000 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.794 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0000 0.985 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.3464 0.5172 0.000 0.000 0.688 0.000 0.000 0.312
#> SRR1947546 4 0.0000 0.8205 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947545 4 0.5228 0.4194 0.308 0.000 0.000 0.572 0.000 0.120
#> SRR1947544 4 0.5228 0.4194 0.308 0.000 0.000 0.572 0.000 0.120
#> SRR1947542 4 0.0146 0.8206 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1947541 3 0.0146 0.9015 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947540 4 0.0260 0.8203 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1947539 3 0.2416 0.7029 0.000 0.000 0.844 0.000 0.156 0.000
#> SRR1947538 4 0.0937 0.8233 0.000 0.000 0.000 0.960 0.000 0.040
#> SRR1947537 3 0.0363 0.8967 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947536 6 0.4116 0.7712 0.000 0.000 0.416 0.000 0.012 0.572
#> SRR1947535 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 1 0.4321 0.6734 0.744 0.108 0.000 0.140 0.000 0.008
#> SRR1947533 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 4 0.1387 0.8205 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947531 4 0.1524 0.8007 0.000 0.060 0.000 0.932 0.000 0.008
#> SRR1947530 6 0.3198 0.9032 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1947529 2 0.4076 0.4118 0.000 0.620 0.000 0.364 0.000 0.016
#> SRR1947528 3 0.2823 0.6510 0.000 0.000 0.796 0.000 0.000 0.204
#> SRR1947527 2 0.0260 0.9060 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1947526 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947525 4 0.2597 0.7086 0.000 0.176 0.000 0.824 0.000 0.000
#> SRR1947524 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 4 0.1387 0.8210 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947521 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947519 3 0.0146 0.9015 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947518 4 0.0508 0.8194 0.000 0.012 0.000 0.984 0.000 0.004
#> SRR1947517 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 4 0.1387 0.8205 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947514 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 1 0.4096 -0.0362 0.508 0.000 0.000 0.484 0.000 0.008
#> SRR1947512 1 0.0146 0.9011 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947511 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947510 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.2982 0.7317 0.012 0.152 0.000 0.828 0.000 0.008
#> SRR1947611 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947509 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947644 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.2623 0.8003 0.000 0.852 0.000 0.132 0.000 0.016
#> SRR1947642 3 0.0146 0.9015 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947640 4 0.0405 0.8199 0.000 0.008 0.000 0.988 0.000 0.004
#> SRR1947641 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 4 0.3862 0.3364 0.000 0.388 0.000 0.608 0.000 0.004
#> SRR1947638 4 0.4543 0.3578 0.384 0.000 0.000 0.576 0.000 0.040
#> SRR1947637 5 0.3409 0.4609 0.000 0.000 0.300 0.000 0.700 0.000
#> SRR1947636 3 0.0260 0.8993 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1947635 4 0.0260 0.8203 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1947634 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947633 3 0.3737 0.3051 0.000 0.000 0.608 0.000 0.392 0.000
#> SRR1947632 4 0.1267 0.8216 0.000 0.000 0.000 0.940 0.000 0.060
#> SRR1947631 3 0.0146 0.9015 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947629 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947627 6 0.3828 0.7335 0.000 0.000 0.440 0.000 0.000 0.560
#> SRR1947628 4 0.1267 0.8225 0.000 0.000 0.000 0.940 0.000 0.060
#> SRR1947626 2 0.0363 0.9038 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947625 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947623 1 0.1983 0.8371 0.916 0.012 0.000 0.060 0.000 0.012
#> SRR1947622 4 0.0865 0.8119 0.000 0.036 0.000 0.964 0.000 0.000
#> SRR1947621 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 4 0.5253 0.4291 0.296 0.000 0.000 0.576 0.000 0.128
#> SRR1947619 3 0.0363 0.8967 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1947617 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 4 0.4954 0.5155 0.260 0.000 0.000 0.628 0.000 0.112
#> SRR1947616 4 0.3969 0.4486 0.000 0.332 0.000 0.652 0.000 0.016
#> SRR1947615 3 0.3390 0.5485 0.000 0.000 0.704 0.000 0.000 0.296
#> SRR1947614 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3647 0.4040 0.000 0.360 0.000 0.640 0.000 0.000
#> SRR1947612 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 4 0.1444 0.8197 0.000 0.000 0.000 0.928 0.000 0.072
#> SRR1947608 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947606 3 0.2260 0.7477 0.000 0.000 0.860 0.000 0.000 0.140
#> SRR1947607 1 0.1471 0.8491 0.932 0.064 0.000 0.000 0.000 0.004
#> SRR1947604 4 0.1327 0.8212 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1947605 4 0.5206 0.4159 0.312 0.000 0.000 0.572 0.000 0.116
#> SRR1947603 4 0.4242 0.1742 0.000 0.448 0.000 0.536 0.000 0.016
#> SRR1947602 6 0.3198 0.9032 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1947600 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0458 0.9053 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1947598 4 0.1387 0.8210 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947599 4 0.1387 0.8205 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947597 4 0.3499 0.4891 0.000 0.320 0.000 0.680 0.000 0.000
#> SRR1947596 4 0.2048 0.7977 0.000 0.000 0.000 0.880 0.000 0.120
#> SRR1947595 4 0.3359 0.6803 0.008 0.196 0.000 0.784 0.000 0.012
#> SRR1947594 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0146 0.9015 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1947591 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 4 0.3916 0.7011 0.064 0.000 0.000 0.752 0.000 0.184
#> SRR1947588 1 0.0146 0.9011 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947587 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947586 2 0.0547 0.8979 0.000 0.980 0.000 0.020 0.000 0.000
#> SRR1947585 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 1 0.0260 0.8981 0.992 0.000 0.000 0.000 0.000 0.008
#> SRR1947583 4 0.2697 0.6920 0.000 0.188 0.000 0.812 0.000 0.000
#> SRR1947582 1 0.4847 0.5392 0.656 0.000 0.000 0.220 0.000 0.124
#> SRR1947580 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947581 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 4 0.0260 0.8203 0.000 0.000 0.000 0.992 0.000 0.008
#> SRR1947573 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947574 2 0.4345 0.3954 0.012 0.604 0.000 0.372 0.000 0.012
#> SRR1947571 4 0.1327 0.8212 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1947577 4 0.3927 0.6747 0.172 0.000 0.000 0.756 0.000 0.072
#> SRR1947570 3 0.3499 0.5001 0.000 0.000 0.680 0.000 0.000 0.320
#> SRR1947569 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.3534 0.6607 0.000 0.740 0.000 0.244 0.000 0.016
#> SRR1947567 4 0.0000 0.8205 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947568 2 0.3619 0.4890 0.000 0.680 0.000 0.316 0.000 0.004
#> SRR1947564 4 0.3727 0.3440 0.000 0.388 0.000 0.612 0.000 0.000
#> SRR1947563 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947562 4 0.0146 0.8206 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1947565 3 0.0260 0.8993 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1947559 4 0.2697 0.6954 0.000 0.188 0.000 0.812 0.000 0.000
#> SRR1947560 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 4 0.5241 0.4111 0.312 0.000 0.000 0.568 0.000 0.120
#> SRR1947553 4 0.3890 0.3019 0.000 0.400 0.000 0.596 0.000 0.004
#> SRR1947554 1 0.0458 0.8947 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1947555 2 0.3606 0.6398 0.000 0.728 0.000 0.256 0.000 0.016
#> SRR1947550 4 0.0146 0.8206 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1947552 4 0.1327 0.8212 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1947549 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947551 5 0.0000 0.9609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.1387 0.8205 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947506 6 0.3244 0.9019 0.000 0.000 0.268 0.000 0.000 0.732
#> SRR1947507 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0146 0.9011 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947503 4 0.1327 0.8212 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1947502 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 4 0.1204 0.8230 0.000 0.000 0.000 0.944 0.000 0.056
#> SRR1947499 6 0.3198 0.9032 0.000 0.000 0.260 0.000 0.000 0.740
#> SRR1947498 3 0.0000 0.9028 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947508 6 0.3592 0.8575 0.000 0.000 0.344 0.000 0.000 0.656
#> SRR1947505 4 0.1387 0.8210 0.000 0.000 0.000 0.932 0.000 0.068
#> SRR1947497 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0146 0.9011 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947495 2 0.0000 0.9097 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947494 4 0.1444 0.8205 0.000 0.000 0.000 0.928 0.000 0.072
#> SRR1947493 6 0.3023 0.8739 0.000 0.000 0.232 0.000 0.000 0.768
#> SRR1947492 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.1663 0.7846 0.000 0.088 0.000 0.912 0.000 0.000
#> SRR1947491 4 0.0000 0.8205 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947490 1 0.0000 0.9014 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.3390 0.5484 0.000 0.000 0.704 0.000 0.000 0.296
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 15148 rows and 152 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 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 0.803 0.882 0.952 0.4849 0.516 0.516
#> 3 3 0.917 0.919 0.964 0.3714 0.690 0.466
#> 4 4 0.791 0.789 0.904 0.1004 0.868 0.640
#> 5 5 0.740 0.725 0.857 0.0653 0.879 0.602
#> 6 6 0.684 0.605 0.782 0.0487 0.905 0.627
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
#> SRR1947547 1 0.0000 0.940 1.000 0.000
#> SRR1947546 2 0.0000 0.951 0.000 1.000
#> SRR1947545 1 0.0000 0.940 1.000 0.000
#> SRR1947544 1 0.0000 0.940 1.000 0.000
#> SRR1947542 2 0.0000 0.951 0.000 1.000
#> SRR1947541 1 0.0000 0.940 1.000 0.000
#> SRR1947540 2 0.0000 0.951 0.000 1.000
#> SRR1947539 2 0.0000 0.951 0.000 1.000
#> SRR1947538 2 0.9129 0.519 0.328 0.672
#> SRR1947537 2 0.9732 0.338 0.404 0.596
#> SRR1947536 1 0.0000 0.940 1.000 0.000
#> SRR1947535 2 0.0000 0.951 0.000 1.000
#> SRR1947534 1 0.1633 0.923 0.976 0.024
#> SRR1947533 2 0.0000 0.951 0.000 1.000
#> SRR1947532 1 0.0000 0.940 1.000 0.000
#> SRR1947531 2 0.0000 0.951 0.000 1.000
#> SRR1947530 1 0.0000 0.940 1.000 0.000
#> SRR1947529 2 0.0000 0.951 0.000 1.000
#> SRR1947528 1 0.0000 0.940 1.000 0.000
#> SRR1947527 2 0.0000 0.951 0.000 1.000
#> SRR1947526 2 0.0000 0.951 0.000 1.000
#> SRR1947525 2 0.0000 0.951 0.000 1.000
#> SRR1947524 2 0.2778 0.912 0.048 0.952
#> SRR1947523 2 0.9460 0.393 0.364 0.636
#> SRR1947521 2 0.0000 0.951 0.000 1.000
#> SRR1947520 2 0.0000 0.951 0.000 1.000
#> SRR1947519 1 0.7376 0.733 0.792 0.208
#> SRR1947518 1 0.9775 0.283 0.588 0.412
#> SRR1947517 1 0.9608 0.402 0.616 0.384
#> SRR1947516 2 0.0000 0.951 0.000 1.000
#> SRR1947515 1 0.9000 0.527 0.684 0.316
#> SRR1947514 2 0.0000 0.951 0.000 1.000
#> SRR1947513 1 0.0000 0.940 1.000 0.000
#> SRR1947512 1 0.0000 0.940 1.000 0.000
#> SRR1947511 2 0.0000 0.951 0.000 1.000
#> SRR1947510 2 0.0000 0.951 0.000 1.000
#> SRR1947572 1 0.9909 0.180 0.556 0.444
#> SRR1947611 2 0.0000 0.951 0.000 1.000
#> SRR1947509 1 0.6531 0.783 0.832 0.168
#> SRR1947644 2 0.0000 0.951 0.000 1.000
#> SRR1947643 2 0.0000 0.951 0.000 1.000
#> SRR1947642 1 0.9427 0.466 0.640 0.360
#> SRR1947640 2 0.8909 0.539 0.308 0.692
#> SRR1947641 2 0.0000 0.951 0.000 1.000
#> SRR1947639 2 0.1414 0.936 0.020 0.980
#> SRR1947638 1 0.0000 0.940 1.000 0.000
#> SRR1947637 2 0.0000 0.951 0.000 1.000
#> SRR1947636 1 0.8267 0.641 0.740 0.260
#> SRR1947635 2 0.0000 0.951 0.000 1.000
#> SRR1947634 2 0.0000 0.951 0.000 1.000
#> SRR1947633 2 0.0000 0.951 0.000 1.000
#> SRR1947632 2 0.0000 0.951 0.000 1.000
#> SRR1947631 2 0.2043 0.927 0.032 0.968
#> SRR1947629 2 0.0000 0.951 0.000 1.000
#> SRR1947630 2 0.0000 0.951 0.000 1.000
#> SRR1947627 1 0.0376 0.937 0.996 0.004
#> SRR1947628 2 0.0000 0.951 0.000 1.000
#> SRR1947626 2 0.0000 0.951 0.000 1.000
#> SRR1947625 2 0.0000 0.951 0.000 1.000
#> SRR1947624 2 0.0000 0.951 0.000 1.000
#> SRR1947623 1 0.0000 0.940 1.000 0.000
#> SRR1947622 2 0.0000 0.951 0.000 1.000
#> SRR1947621 2 0.0000 0.951 0.000 1.000
#> SRR1947620 1 0.0000 0.940 1.000 0.000
#> SRR1947619 2 0.9686 0.359 0.396 0.604
#> SRR1947617 2 0.0000 0.951 0.000 1.000
#> SRR1947618 1 0.0000 0.940 1.000 0.000
#> SRR1947616 2 0.0000 0.951 0.000 1.000
#> SRR1947615 1 0.0000 0.940 1.000 0.000
#> SRR1947614 2 0.0000 0.951 0.000 1.000
#> SRR1947613 1 0.0000 0.940 1.000 0.000
#> SRR1947610 2 0.0000 0.951 0.000 1.000
#> SRR1947612 2 0.0000 0.951 0.000 1.000
#> SRR1947609 1 0.0000 0.940 1.000 0.000
#> SRR1947608 2 0.0000 0.951 0.000 1.000
#> SRR1947606 1 0.0000 0.940 1.000 0.000
#> SRR1947607 1 0.0000 0.940 1.000 0.000
#> SRR1947604 1 0.2778 0.903 0.952 0.048
#> SRR1947605 1 0.0000 0.940 1.000 0.000
#> SRR1947603 2 0.0000 0.951 0.000 1.000
#> SRR1947602 1 0.0000 0.940 1.000 0.000
#> SRR1947600 2 0.1633 0.933 0.024 0.976
#> SRR1947601 2 0.0000 0.951 0.000 1.000
#> SRR1947598 2 0.8327 0.637 0.264 0.736
#> SRR1947599 1 0.0000 0.940 1.000 0.000
#> SRR1947597 2 0.0000 0.951 0.000 1.000
#> SRR1947596 1 0.0000 0.940 1.000 0.000
#> SRR1947595 2 0.0000 0.951 0.000 1.000
#> SRR1947594 1 0.0000 0.940 1.000 0.000
#> SRR1947592 2 0.1633 0.933 0.024 0.976
#> SRR1947591 2 0.0000 0.951 0.000 1.000
#> SRR1947590 1 0.0000 0.940 1.000 0.000
#> SRR1947588 1 0.0000 0.940 1.000 0.000
#> SRR1947587 1 0.0000 0.940 1.000 0.000
#> SRR1947586 2 0.0000 0.951 0.000 1.000
#> SRR1947585 2 0.2043 0.926 0.032 0.968
#> SRR1947584 1 0.0000 0.940 1.000 0.000
#> SRR1947583 2 0.0000 0.951 0.000 1.000
#> SRR1947582 1 0.0000 0.940 1.000 0.000
#> SRR1947580 2 0.0000 0.951 0.000 1.000
#> SRR1947581 1 0.0000 0.940 1.000 0.000
#> SRR1947576 2 0.0000 0.951 0.000 1.000
#> SRR1947575 2 0.0000 0.951 0.000 1.000
#> SRR1947579 2 0.0000 0.951 0.000 1.000
#> SRR1947578 2 0.0000 0.951 0.000 1.000
#> SRR1947573 2 0.0000 0.951 0.000 1.000
#> SRR1947574 1 0.8555 0.622 0.720 0.280
#> SRR1947571 2 0.8909 0.559 0.308 0.692
#> SRR1947577 1 0.0000 0.940 1.000 0.000
#> SRR1947570 1 0.0000 0.940 1.000 0.000
#> SRR1947569 2 0.4690 0.861 0.100 0.900
#> SRR1947566 2 0.0000 0.951 0.000 1.000
#> SRR1947567 2 0.0000 0.951 0.000 1.000
#> SRR1947568 2 0.5178 0.840 0.116 0.884
#> SRR1947564 2 0.0000 0.951 0.000 1.000
#> SRR1947563 2 0.0000 0.951 0.000 1.000
#> SRR1947562 2 0.0000 0.951 0.000 1.000
#> SRR1947565 2 0.9732 0.337 0.404 0.596
#> SRR1947559 2 0.0000 0.951 0.000 1.000
#> SRR1947560 2 0.0000 0.951 0.000 1.000
#> SRR1947561 2 0.0000 0.951 0.000 1.000
#> SRR1947557 1 0.0000 0.940 1.000 0.000
#> SRR1947558 2 0.0000 0.951 0.000 1.000
#> SRR1947556 1 0.0000 0.940 1.000 0.000
#> SRR1947553 2 0.0000 0.951 0.000 1.000
#> SRR1947554 1 0.0000 0.940 1.000 0.000
#> SRR1947555 2 0.0000 0.951 0.000 1.000
#> SRR1947550 2 0.0000 0.951 0.000 1.000
#> SRR1947552 1 0.0000 0.940 1.000 0.000
#> SRR1947549 2 0.0000 0.951 0.000 1.000
#> SRR1947551 2 0.0000 0.951 0.000 1.000
#> SRR1947548 2 0.9552 0.411 0.376 0.624
#> SRR1947506 1 0.0000 0.940 1.000 0.000
#> SRR1947507 1 0.0000 0.940 1.000 0.000
#> SRR1947504 1 0.0000 0.940 1.000 0.000
#> SRR1947503 1 0.0000 0.940 1.000 0.000
#> SRR1947502 2 0.0000 0.951 0.000 1.000
#> SRR1947501 2 0.0000 0.951 0.000 1.000
#> SRR1947499 1 0.0000 0.940 1.000 0.000
#> SRR1947498 1 0.7219 0.745 0.800 0.200
#> SRR1947508 1 0.6712 0.773 0.824 0.176
#> SRR1947505 2 0.4298 0.869 0.088 0.912
#> SRR1947497 2 0.0000 0.951 0.000 1.000
#> SRR1947496 1 0.0000 0.940 1.000 0.000
#> SRR1947495 2 0.0000 0.951 0.000 1.000
#> SRR1947494 1 0.1633 0.923 0.976 0.024
#> SRR1947493 1 0.0000 0.940 1.000 0.000
#> SRR1947492 1 0.0000 0.940 1.000 0.000
#> SRR1947500 2 0.0000 0.951 0.000 1.000
#> SRR1947491 2 0.9686 0.305 0.396 0.604
#> SRR1947490 1 0.0000 0.940 1.000 0.000
#> SRR1947489 1 0.0000 0.940 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.5678 0.5600 0.316 0.000 0.684
#> SRR1947546 2 0.0592 0.9602 0.000 0.988 0.012
#> SRR1947545 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947542 2 0.0747 0.9579 0.000 0.984 0.016
#> SRR1947541 3 0.1289 0.9461 0.032 0.000 0.968
#> SRR1947540 2 0.0592 0.9602 0.000 0.988 0.012
#> SRR1947539 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947538 2 0.4796 0.7117 0.220 0.780 0.000
#> SRR1947537 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947536 3 0.2261 0.9188 0.068 0.000 0.932
#> SRR1947535 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947534 1 0.6180 0.2922 0.584 0.416 0.000
#> SRR1947533 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947532 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947531 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947530 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947529 2 0.0237 0.9636 0.000 0.996 0.004
#> SRR1947528 3 0.1643 0.9380 0.044 0.000 0.956
#> SRR1947527 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947526 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947523 2 0.5678 0.5391 0.316 0.684 0.000
#> SRR1947521 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947520 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947519 3 0.0424 0.9610 0.008 0.000 0.992
#> SRR1947518 2 0.5591 0.5604 0.304 0.696 0.000
#> SRR1947517 3 0.0237 0.9631 0.004 0.000 0.996
#> SRR1947516 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947515 1 0.5678 0.5202 0.684 0.000 0.316
#> SRR1947514 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947512 1 0.0237 0.9520 0.996 0.004 0.000
#> SRR1947511 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947572 2 0.5859 0.4701 0.344 0.656 0.000
#> SRR1947611 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947509 3 0.3192 0.8734 0.112 0.000 0.888
#> SRR1947644 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947642 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947640 2 0.0424 0.9606 0.008 0.992 0.000
#> SRR1947641 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947639 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947638 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947637 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947635 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947634 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947632 2 0.1529 0.9405 0.000 0.960 0.040
#> SRR1947631 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947627 3 0.1529 0.9407 0.040 0.000 0.960
#> SRR1947628 2 0.1163 0.9500 0.000 0.972 0.028
#> SRR1947626 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947624 2 0.0592 0.9602 0.000 0.988 0.012
#> SRR1947623 1 0.2625 0.8894 0.916 0.084 0.000
#> SRR1947622 2 0.0424 0.9620 0.000 0.992 0.008
#> SRR1947621 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947619 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947617 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947616 2 0.1529 0.9407 0.000 0.960 0.040
#> SRR1947615 3 0.1753 0.9355 0.048 0.000 0.952
#> SRR1947614 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947613 1 0.0424 0.9495 0.992 0.008 0.000
#> SRR1947610 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947612 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947609 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947606 3 0.1289 0.9461 0.032 0.000 0.968
#> SRR1947607 1 0.3412 0.8476 0.876 0.124 0.000
#> SRR1947604 1 0.3192 0.8605 0.888 0.112 0.000
#> SRR1947605 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947603 2 0.0892 0.9554 0.000 0.980 0.020
#> SRR1947602 1 0.0237 0.9515 0.996 0.000 0.004
#> SRR1947600 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947601 2 0.0592 0.9602 0.000 0.988 0.012
#> SRR1947598 3 0.6057 0.7010 0.196 0.044 0.760
#> SRR1947599 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947597 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947596 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947595 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947594 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947590 1 0.0237 0.9514 0.996 0.000 0.004
#> SRR1947588 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947587 3 0.0424 0.9610 0.008 0.000 0.992
#> SRR1947586 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947583 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947582 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947576 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947575 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947579 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947578 2 0.1163 0.9500 0.000 0.972 0.028
#> SRR1947573 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947574 2 0.3482 0.8425 0.128 0.872 0.000
#> SRR1947571 2 0.3816 0.8154 0.148 0.852 0.000
#> SRR1947577 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947570 1 0.0592 0.9453 0.988 0.000 0.012
#> SRR1947569 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947566 2 0.1031 0.9528 0.000 0.976 0.024
#> SRR1947567 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947568 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947564 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947563 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947562 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947560 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947561 2 0.0592 0.9602 0.000 0.988 0.012
#> SRR1947557 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947553 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947554 1 0.2066 0.9109 0.940 0.060 0.000
#> SRR1947555 2 0.1289 0.9471 0.000 0.968 0.032
#> SRR1947550 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947552 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947549 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947551 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947548 1 0.9460 0.0770 0.424 0.396 0.180
#> SRR1947506 1 0.3192 0.8454 0.888 0.000 0.112
#> SRR1947507 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947504 1 0.1411 0.9291 0.964 0.036 0.000
#> SRR1947503 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947501 2 0.1643 0.9371 0.000 0.956 0.044
#> SRR1947499 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.9653 0.000 0.000 1.000
#> SRR1947508 3 0.3116 0.8782 0.108 0.000 0.892
#> SRR1947505 3 0.8737 0.0784 0.108 0.428 0.464
#> SRR1947497 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947494 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947493 1 0.0000 0.9540 1.000 0.000 0.000
#> SRR1947492 1 0.0237 0.9520 0.996 0.004 0.000
#> SRR1947500 2 0.0000 0.9652 0.000 1.000 0.000
#> SRR1947491 2 0.3340 0.8514 0.120 0.880 0.000
#> SRR1947490 1 0.0237 0.9520 0.996 0.004 0.000
#> SRR1947489 3 0.1964 0.9292 0.056 0.000 0.944
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 4 0.4722 0.4978 0.300 0.000 0.008 0.692
#> SRR1947546 2 0.1118 0.9092 0.000 0.964 0.000 0.036
#> SRR1947545 1 0.0336 0.9718 0.992 0.000 0.000 0.008
#> SRR1947544 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947542 2 0.4941 0.1848 0.000 0.564 0.000 0.436
#> SRR1947541 4 0.4621 0.4444 0.008 0.000 0.284 0.708
#> SRR1947540 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947539 3 0.0469 0.8135 0.000 0.000 0.988 0.012
#> SRR1947538 2 0.5363 0.6176 0.064 0.720 0.000 0.216
#> SRR1947537 4 0.2760 0.6830 0.000 0.000 0.128 0.872
#> SRR1947536 3 0.5536 0.7147 0.096 0.000 0.724 0.180
#> SRR1947535 4 0.0188 0.7502 0.000 0.000 0.004 0.996
#> SRR1947534 1 0.4304 0.5810 0.716 0.284 0.000 0.000
#> SRR1947533 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.1174 0.7497 0.012 0.020 0.000 0.968
#> SRR1947531 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947530 1 0.0188 0.9736 0.996 0.000 0.000 0.004
#> SRR1947529 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947528 3 0.5966 0.6476 0.072 0.000 0.648 0.280
#> SRR1947527 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947526 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947525 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947524 3 0.4454 0.6621 0.000 0.000 0.692 0.308
#> SRR1947523 4 0.4456 0.5640 0.004 0.280 0.000 0.716
#> SRR1947521 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947520 2 0.3074 0.8094 0.000 0.848 0.152 0.000
#> SRR1947519 4 0.0000 0.7504 0.000 0.000 0.000 1.000
#> SRR1947518 2 0.3726 0.7181 0.212 0.788 0.000 0.000
#> SRR1947517 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.1209 0.7466 0.032 0.004 0.000 0.964
#> SRR1947514 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.1474 0.8988 0.000 0.948 0.052 0.000
#> SRR1947510 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947572 2 0.4898 0.2997 0.416 0.584 0.000 0.000
#> SRR1947611 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947509 3 0.0336 0.8122 0.008 0.000 0.992 0.000
#> SRR1947644 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947643 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947642 4 0.2589 0.6769 0.000 0.000 0.116 0.884
#> SRR1947640 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947641 3 0.4977 0.3681 0.000 0.000 0.540 0.460
#> SRR1947639 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947638 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947637 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947636 4 0.4898 0.0897 0.000 0.000 0.416 0.584
#> SRR1947635 2 0.0921 0.9155 0.000 0.972 0.000 0.028
#> SRR1947634 2 0.0817 0.9206 0.000 0.976 0.024 0.000
#> SRR1947633 3 0.0592 0.8128 0.000 0.000 0.984 0.016
#> SRR1947632 4 0.3907 0.6057 0.000 0.232 0.000 0.768
#> SRR1947631 4 0.0000 0.7504 0.000 0.000 0.000 1.000
#> SRR1947629 4 0.4761 0.2393 0.000 0.000 0.372 0.628
#> SRR1947630 2 0.4277 0.6501 0.000 0.720 0.280 0.000
#> SRR1947627 3 0.4735 0.7486 0.068 0.000 0.784 0.148
#> SRR1947628 2 0.4998 -0.0149 0.000 0.512 0.000 0.488
#> SRR1947626 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947625 4 0.0469 0.7496 0.000 0.000 0.012 0.988
#> SRR1947624 2 0.4072 0.6894 0.000 0.748 0.252 0.000
#> SRR1947623 1 0.1211 0.9356 0.960 0.040 0.000 0.000
#> SRR1947622 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.0336 0.9718 0.992 0.000 0.000 0.008
#> SRR1947619 4 0.2760 0.6834 0.000 0.000 0.128 0.872
#> SRR1947617 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.0188 0.9736 0.996 0.000 0.000 0.004
#> SRR1947616 2 0.0336 0.9297 0.000 0.992 0.008 0.000
#> SRR1947615 4 0.0000 0.7504 0.000 0.000 0.000 1.000
#> SRR1947614 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947610 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947612 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947609 1 0.3074 0.8015 0.848 0.000 0.000 0.152
#> SRR1947608 4 0.0336 0.7500 0.000 0.000 0.008 0.992
#> SRR1947606 3 0.5130 0.6206 0.016 0.000 0.652 0.332
#> SRR1947607 1 0.0817 0.9540 0.976 0.024 0.000 0.000
#> SRR1947604 4 0.4252 0.5837 0.004 0.252 0.000 0.744
#> SRR1947605 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947603 2 0.0336 0.9286 0.000 0.992 0.000 0.008
#> SRR1947602 1 0.1302 0.9388 0.956 0.000 0.000 0.044
#> SRR1947600 3 0.4776 0.5544 0.000 0.000 0.624 0.376
#> SRR1947601 2 0.0592 0.9256 0.000 0.984 0.016 0.000
#> SRR1947598 4 0.0817 0.7496 0.000 0.024 0.000 0.976
#> SRR1947599 4 0.4722 0.5485 0.300 0.008 0.000 0.692
#> SRR1947597 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947596 4 0.4961 0.2643 0.448 0.000 0.000 0.552
#> SRR1947595 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947594 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.4713 0.5786 0.000 0.000 0.640 0.360
#> SRR1947591 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.3975 0.6228 0.240 0.000 0.000 0.760
#> SRR1947588 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947587 4 0.1940 0.7206 0.000 0.000 0.076 0.924
#> SRR1947586 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947585 3 0.4356 0.6797 0.000 0.000 0.708 0.292
#> SRR1947584 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947583 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947582 1 0.0188 0.9736 0.996 0.000 0.000 0.004
#> SRR1947580 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947581 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947575 4 0.1209 0.7449 0.000 0.004 0.032 0.964
#> SRR1947579 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.0469 0.9260 0.000 0.988 0.000 0.012
#> SRR1947573 3 0.4193 0.7013 0.000 0.000 0.732 0.268
#> SRR1947574 2 0.4222 0.6245 0.272 0.728 0.000 0.000
#> SRR1947571 4 0.4985 0.1372 0.000 0.468 0.000 0.532
#> SRR1947577 1 0.0592 0.9663 0.984 0.000 0.000 0.016
#> SRR1947570 4 0.4277 0.5606 0.280 0.000 0.000 0.720
#> SRR1947569 4 0.3356 0.6313 0.000 0.000 0.176 0.824
#> SRR1947566 2 0.0336 0.9297 0.000 0.992 0.008 0.000
#> SRR1947567 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947568 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947564 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947563 4 0.0592 0.7489 0.000 0.000 0.016 0.984
#> SRR1947562 2 0.4304 0.5724 0.000 0.716 0.000 0.284
#> SRR1947565 4 0.4522 0.3853 0.000 0.000 0.320 0.680
#> SRR1947559 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947558 4 0.0921 0.7453 0.000 0.000 0.028 0.972
#> SRR1947556 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947553 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947554 1 0.0336 0.9691 0.992 0.008 0.000 0.000
#> SRR1947555 2 0.1211 0.9097 0.000 0.960 0.040 0.000
#> SRR1947550 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947552 4 0.3652 0.7049 0.092 0.052 0.000 0.856
#> SRR1947549 4 0.4866 0.1469 0.000 0.000 0.404 0.596
#> SRR1947551 3 0.0000 0.8147 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.1302 0.7431 0.000 0.044 0.000 0.956
#> SRR1947506 1 0.1661 0.9279 0.944 0.000 0.004 0.052
#> SRR1947507 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.0336 0.9694 0.992 0.008 0.000 0.000
#> SRR1947503 1 0.0188 0.9736 0.996 0.000 0.000 0.004
#> SRR1947502 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947501 4 0.4454 0.5285 0.000 0.308 0.000 0.692
#> SRR1947499 1 0.0336 0.9715 0.992 0.000 0.000 0.008
#> SRR1947498 3 0.4222 0.6993 0.000 0.000 0.728 0.272
#> SRR1947508 3 0.7597 0.3387 0.204 0.000 0.440 0.356
#> SRR1947505 4 0.2408 0.7113 0.000 0.104 0.000 0.896
#> SRR1947497 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947496 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947494 4 0.5050 0.3635 0.408 0.004 0.000 0.588
#> SRR1947493 1 0.0188 0.9729 0.996 0.000 0.000 0.004
#> SRR1947492 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947500 2 0.0000 0.9333 0.000 1.000 0.000 0.000
#> SRR1947491 2 0.1557 0.8904 0.056 0.944 0.000 0.000
#> SRR1947490 1 0.0000 0.9747 1.000 0.000 0.000 0.000
#> SRR1947489 4 0.0000 0.7504 0.000 0.000 0.000 1.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.1331 0.80640 0.000 0.000 0.952 0.040 0.008
#> SRR1947546 2 0.1851 0.85076 0.000 0.912 0.000 0.088 0.000
#> SRR1947545 1 0.2280 0.81908 0.880 0.000 0.120 0.000 0.000
#> SRR1947544 1 0.0162 0.89737 0.996 0.000 0.004 0.000 0.000
#> SRR1947542 4 0.3210 0.63978 0.000 0.212 0.000 0.788 0.000
#> SRR1947541 3 0.2813 0.76827 0.000 0.000 0.876 0.084 0.040
#> SRR1947540 2 0.0898 0.89496 0.000 0.972 0.020 0.008 0.000
#> SRR1947539 5 0.2813 0.81450 0.000 0.000 0.000 0.168 0.832
#> SRR1947538 1 0.6365 0.02798 0.468 0.116 0.012 0.404 0.000
#> SRR1947537 4 0.0794 0.68656 0.000 0.000 0.000 0.972 0.028
#> SRR1947536 3 0.3752 0.71689 0.000 0.000 0.812 0.124 0.064
#> SRR1947535 4 0.2193 0.67264 0.000 0.000 0.092 0.900 0.008
#> SRR1947534 2 0.4595 0.06349 0.488 0.504 0.004 0.004 0.000
#> SRR1947533 2 0.0451 0.89900 0.000 0.988 0.004 0.008 0.000
#> SRR1947532 4 0.5280 0.37762 0.024 0.020 0.372 0.584 0.000
#> SRR1947531 2 0.1059 0.89384 0.004 0.968 0.020 0.008 0.000
#> SRR1947530 3 0.1043 0.80614 0.040 0.000 0.960 0.000 0.000
#> SRR1947529 2 0.0162 0.90001 0.000 0.996 0.000 0.004 0.000
#> SRR1947528 3 0.6669 -0.00424 0.008 0.000 0.472 0.188 0.332
#> SRR1947527 2 0.0162 0.90018 0.000 0.996 0.000 0.004 0.000
#> SRR1947526 2 0.0451 0.89921 0.000 0.988 0.000 0.004 0.008
#> SRR1947525 2 0.6114 0.34506 0.244 0.564 0.000 0.192 0.000
#> SRR1947524 5 0.4398 0.76749 0.000 0.000 0.040 0.240 0.720
#> SRR1947523 3 0.3967 0.55500 0.000 0.264 0.724 0.012 0.000
#> SRR1947521 5 0.0404 0.80092 0.000 0.000 0.000 0.012 0.988
#> SRR1947520 2 0.3500 0.76562 0.000 0.808 0.004 0.016 0.172
#> SRR1947519 3 0.3266 0.69849 0.000 0.000 0.796 0.200 0.004
#> SRR1947518 1 0.0771 0.88556 0.976 0.020 0.004 0.000 0.000
#> SRR1947517 5 0.0000 0.79456 0.000 0.000 0.000 0.000 1.000
#> SRR1947516 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.3900 0.64700 0.016 0.032 0.144 0.808 0.000
#> SRR1947514 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 3 0.4786 0.61119 0.092 0.188 0.720 0.000 0.000
#> SRR1947512 1 0.0000 0.89778 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.3111 0.79437 0.000 0.840 0.004 0.012 0.144
#> SRR1947510 5 0.0162 0.79771 0.000 0.000 0.000 0.004 0.996
#> SRR1947572 1 0.0162 0.89703 0.996 0.004 0.000 0.000 0.000
#> SRR1947611 5 0.0404 0.80091 0.000 0.000 0.000 0.012 0.988
#> SRR1947509 5 0.1952 0.75622 0.000 0.000 0.084 0.004 0.912
#> SRR1947644 5 0.2648 0.81744 0.000 0.000 0.000 0.152 0.848
#> SRR1947643 2 0.0613 0.89829 0.004 0.984 0.004 0.008 0.000
#> SRR1947642 3 0.2068 0.78417 0.000 0.000 0.904 0.092 0.004
#> SRR1947640 2 0.0955 0.89275 0.004 0.968 0.028 0.000 0.000
#> SRR1947641 5 0.6596 0.42452 0.000 0.000 0.236 0.308 0.456
#> SRR1947639 2 0.6234 0.27279 0.304 0.524 0.000 0.172 0.000
#> SRR1947638 3 0.5159 0.59462 0.124 0.188 0.688 0.000 0.000
#> SRR1947637 5 0.2813 0.81543 0.000 0.000 0.000 0.168 0.832
#> SRR1947636 4 0.4225 0.10924 0.000 0.000 0.004 0.632 0.364
#> SRR1947635 2 0.1012 0.89246 0.000 0.968 0.020 0.012 0.000
#> SRR1947634 2 0.2629 0.83061 0.000 0.880 0.004 0.012 0.104
#> SRR1947633 5 0.2773 0.81572 0.000 0.000 0.000 0.164 0.836
#> SRR1947632 4 0.3419 0.65702 0.000 0.180 0.016 0.804 0.000
#> SRR1947631 3 0.3861 0.59734 0.000 0.000 0.712 0.284 0.004
#> SRR1947629 4 0.4736 -0.09686 0.000 0.000 0.020 0.576 0.404
#> SRR1947630 2 0.4184 0.64288 0.000 0.700 0.000 0.016 0.284
#> SRR1947627 5 0.5832 0.61123 0.000 0.000 0.248 0.152 0.600
#> SRR1947628 2 0.1893 0.87426 0.000 0.928 0.048 0.024 0.000
#> SRR1947626 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 4 0.2110 0.67591 0.000 0.000 0.072 0.912 0.016
#> SRR1947624 2 0.4161 0.64860 0.000 0.704 0.000 0.016 0.280
#> SRR1947623 1 0.0162 0.89703 0.996 0.004 0.000 0.000 0.000
#> SRR1947622 2 0.1410 0.86981 0.000 0.940 0.000 0.060 0.000
#> SRR1947621 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 3 0.0794 0.80891 0.028 0.000 0.972 0.000 0.000
#> SRR1947619 4 0.1082 0.68685 0.008 0.000 0.000 0.964 0.028
#> SRR1947617 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 3 0.1095 0.80666 0.008 0.012 0.968 0.012 0.000
#> SRR1947616 2 0.0960 0.89548 0.000 0.972 0.008 0.016 0.004
#> SRR1947615 3 0.0609 0.80892 0.000 0.000 0.980 0.020 0.000
#> SRR1947614 5 0.0162 0.79771 0.000 0.000 0.000 0.004 0.996
#> SRR1947613 1 0.0404 0.89389 0.988 0.000 0.012 0.000 0.000
#> SRR1947610 2 0.0162 0.89998 0.000 0.996 0.000 0.004 0.000
#> SRR1947612 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 1 0.3632 0.75788 0.800 0.004 0.176 0.020 0.000
#> SRR1947608 4 0.0693 0.69250 0.000 0.000 0.008 0.980 0.012
#> SRR1947606 5 0.5026 0.74669 0.008 0.000 0.060 0.244 0.688
#> SRR1947607 1 0.1095 0.88263 0.968 0.008 0.012 0.012 0.000
#> SRR1947604 4 0.6982 0.34045 0.012 0.280 0.268 0.440 0.000
#> SRR1947605 1 0.4015 0.46645 0.652 0.000 0.348 0.000 0.000
#> SRR1947603 2 0.4182 0.34650 0.000 0.600 0.000 0.400 0.000
#> SRR1947602 3 0.1179 0.81148 0.016 0.000 0.964 0.016 0.004
#> SRR1947600 5 0.4801 0.72108 0.000 0.000 0.048 0.284 0.668
#> SRR1947601 2 0.0162 0.90018 0.000 0.996 0.000 0.004 0.000
#> SRR1947598 3 0.4867 -0.01815 0.000 0.024 0.544 0.432 0.000
#> SRR1947599 3 0.0613 0.80911 0.004 0.004 0.984 0.008 0.000
#> SRR1947597 2 0.0404 0.89712 0.000 0.988 0.000 0.012 0.000
#> SRR1947596 1 0.4101 0.68542 0.768 0.000 0.048 0.184 0.000
#> SRR1947595 2 0.3249 0.82149 0.008 0.860 0.012 0.016 0.104
#> SRR1947594 1 0.0000 0.89778 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 5 0.4138 0.59700 0.000 0.000 0.000 0.384 0.616
#> SRR1947591 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.5505 0.33929 0.328 0.000 0.084 0.588 0.000
#> SRR1947588 1 0.0000 0.89778 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.4920 0.35289 0.000 0.000 0.584 0.384 0.032
#> SRR1947586 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947585 5 0.4113 0.77840 0.000 0.000 0.028 0.232 0.740
#> SRR1947584 1 0.0162 0.89737 0.996 0.000 0.004 0.000 0.000
#> SRR1947583 2 0.0324 0.89999 0.004 0.992 0.004 0.000 0.000
#> SRR1947582 3 0.0693 0.80902 0.008 0.000 0.980 0.012 0.000
#> SRR1947580 2 0.0807 0.89612 0.000 0.976 0.012 0.012 0.000
#> SRR1947581 1 0.0162 0.89737 0.996 0.000 0.004 0.000 0.000
#> SRR1947576 5 0.0162 0.79771 0.000 0.000 0.000 0.004 0.996
#> SRR1947575 4 0.0510 0.69050 0.000 0.000 0.000 0.984 0.016
#> SRR1947579 5 0.0162 0.79771 0.000 0.000 0.000 0.004 0.996
#> SRR1947578 2 0.1195 0.89037 0.000 0.960 0.028 0.012 0.000
#> SRR1947573 5 0.3837 0.71839 0.000 0.000 0.000 0.308 0.692
#> SRR1947574 2 0.1969 0.87712 0.032 0.936 0.012 0.012 0.008
#> SRR1947571 4 0.5208 0.48358 0.028 0.328 0.020 0.624 0.000
#> SRR1947577 3 0.0290 0.80878 0.008 0.000 0.992 0.000 0.000
#> SRR1947570 3 0.0898 0.81108 0.020 0.000 0.972 0.008 0.000
#> SRR1947569 4 0.3152 0.59438 0.000 0.000 0.024 0.840 0.136
#> SRR1947566 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 2 0.0404 0.89872 0.000 0.988 0.000 0.012 0.000
#> SRR1947568 2 0.4268 0.23477 0.444 0.556 0.000 0.000 0.000
#> SRR1947564 2 0.3366 0.67330 0.000 0.768 0.000 0.232 0.000
#> SRR1947563 4 0.0693 0.69250 0.000 0.000 0.008 0.980 0.012
#> SRR1947562 4 0.4297 0.56876 0.000 0.288 0.020 0.692 0.000
#> SRR1947565 4 0.2966 0.54756 0.000 0.000 0.000 0.816 0.184
#> SRR1947559 2 0.0162 0.89975 0.000 0.996 0.000 0.004 0.000
#> SRR1947560 5 0.0162 0.79112 0.000 0.000 0.000 0.004 0.996
#> SRR1947561 2 0.0162 0.89975 0.000 0.996 0.000 0.004 0.000
#> SRR1947557 1 0.0162 0.89737 0.996 0.000 0.004 0.000 0.000
#> SRR1947558 4 0.4907 -0.14539 0.000 0.000 0.488 0.488 0.024
#> SRR1947556 1 0.0162 0.89737 0.996 0.000 0.004 0.000 0.000
#> SRR1947553 2 0.0162 0.90004 0.004 0.996 0.000 0.000 0.000
#> SRR1947554 1 0.0404 0.89389 0.988 0.000 0.012 0.000 0.000
#> SRR1947555 2 0.3596 0.71187 0.000 0.784 0.000 0.200 0.016
#> SRR1947550 2 0.3093 0.75527 0.000 0.824 0.008 0.168 0.000
#> SRR1947552 3 0.1648 0.79225 0.000 0.020 0.940 0.040 0.000
#> SRR1947549 4 0.2471 0.60815 0.000 0.000 0.000 0.864 0.136
#> SRR1947551 5 0.2648 0.81759 0.000 0.000 0.000 0.152 0.848
#> SRR1947548 4 0.3601 0.67512 0.000 0.128 0.052 0.820 0.000
#> SRR1947506 3 0.4870 0.70360 0.152 0.000 0.748 0.080 0.020
#> SRR1947507 1 0.0000 0.89778 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.0162 0.89703 0.996 0.004 0.000 0.000 0.000
#> SRR1947503 1 0.4229 0.60877 0.704 0.020 0.276 0.000 0.000
#> SRR1947502 2 0.0000 0.90020 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 4 0.3282 0.65372 0.000 0.188 0.008 0.804 0.000
#> SRR1947499 3 0.1173 0.81148 0.020 0.000 0.964 0.012 0.004
#> SRR1947498 5 0.4670 0.77193 0.000 0.000 0.076 0.200 0.724
#> SRR1947508 3 0.0955 0.80989 0.000 0.000 0.968 0.028 0.004
#> SRR1947505 3 0.2848 0.69326 0.000 0.156 0.840 0.004 0.000
#> SRR1947497 2 0.0162 0.90018 0.000 0.996 0.000 0.004 0.000
#> SRR1947496 1 0.0000 0.89778 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 2 0.0324 0.89996 0.004 0.992 0.000 0.004 0.000
#> SRR1947494 1 0.7551 0.02945 0.396 0.048 0.228 0.328 0.000
#> SRR1947493 3 0.4150 0.35084 0.388 0.000 0.612 0.000 0.000
#> SRR1947492 1 0.0162 0.89697 0.996 0.000 0.004 0.000 0.000
#> SRR1947500 2 0.0162 0.90017 0.004 0.996 0.000 0.000 0.000
#> SRR1947491 2 0.0324 0.89999 0.004 0.992 0.004 0.000 0.000
#> SRR1947490 1 0.0566 0.89217 0.984 0.000 0.012 0.004 0.000
#> SRR1947489 3 0.1043 0.80488 0.000 0.000 0.960 0.040 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.1387 0.70273 0.000 0.000 0.068 0.000 0.000 0.932
#> SRR1947546 2 0.3943 0.74698 0.000 0.756 0.056 0.184 0.000 0.004
#> SRR1947545 1 0.4468 -0.09815 0.488 0.000 0.004 0.020 0.000 0.488
#> SRR1947544 1 0.1411 0.81278 0.936 0.000 0.004 0.060 0.000 0.000
#> SRR1947542 4 0.2868 0.63594 0.000 0.112 0.032 0.852 0.000 0.004
#> SRR1947541 6 0.2308 0.69534 0.000 0.000 0.076 0.012 0.016 0.896
#> SRR1947540 2 0.5019 0.64556 0.000 0.656 0.188 0.152 0.000 0.004
#> SRR1947539 5 0.4210 0.13154 0.000 0.000 0.336 0.028 0.636 0.000
#> SRR1947538 1 0.6031 0.35216 0.548 0.028 0.136 0.284 0.000 0.004
#> SRR1947537 4 0.3314 0.49117 0.000 0.000 0.256 0.740 0.004 0.000
#> SRR1947536 3 0.4174 0.44279 0.000 0.000 0.628 0.016 0.004 0.352
#> SRR1947535 3 0.3770 0.54634 0.000 0.000 0.728 0.244 0.000 0.028
#> SRR1947534 2 0.3380 0.64735 0.244 0.748 0.004 0.004 0.000 0.000
#> SRR1947533 2 0.0000 0.81939 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947532 4 0.4995 0.00844 0.008 0.000 0.052 0.528 0.000 0.412
#> SRR1947531 2 0.4795 0.68777 0.004 0.696 0.168 0.128 0.000 0.004
#> SRR1947530 6 0.1370 0.71047 0.012 0.000 0.036 0.004 0.000 0.948
#> SRR1947529 2 0.1812 0.81239 0.000 0.912 0.080 0.008 0.000 0.000
#> SRR1947528 6 0.5659 0.00309 0.008 0.000 0.380 0.020 0.072 0.520
#> SRR1947527 2 0.0146 0.81956 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947526 2 0.0632 0.81961 0.000 0.976 0.024 0.000 0.000 0.000
#> SRR1947525 1 0.6725 0.10871 0.408 0.268 0.040 0.284 0.000 0.000
#> SRR1947524 3 0.3352 0.66535 0.000 0.000 0.800 0.012 0.172 0.016
#> SRR1947523 6 0.6125 0.47413 0.000 0.164 0.084 0.152 0.000 0.600
#> SRR1947521 5 0.0713 0.76763 0.000 0.000 0.028 0.000 0.972 0.000
#> SRR1947520 2 0.3713 0.68080 0.000 0.744 0.032 0.000 0.224 0.000
#> SRR1947519 6 0.4002 0.46908 0.000 0.000 0.260 0.036 0.000 0.704
#> SRR1947518 1 0.3023 0.75780 0.864 0.028 0.052 0.056 0.000 0.000
#> SRR1947517 5 0.0458 0.77267 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1947516 2 0.1563 0.81391 0.000 0.932 0.056 0.012 0.000 0.000
#> SRR1947515 4 0.3207 0.62210 0.012 0.004 0.048 0.848 0.000 0.088
#> SRR1947514 2 0.0937 0.81827 0.000 0.960 0.040 0.000 0.000 0.000
#> SRR1947513 6 0.4019 0.66572 0.008 0.044 0.076 0.064 0.000 0.808
#> SRR1947512 1 0.0000 0.83737 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 2 0.1866 0.79858 0.000 0.908 0.008 0.000 0.084 0.000
#> SRR1947510 5 0.0547 0.77220 0.000 0.000 0.020 0.000 0.980 0.000
#> SRR1947572 1 0.1501 0.80474 0.924 0.000 0.000 0.076 0.000 0.000
#> SRR1947611 5 0.0632 0.77038 0.000 0.000 0.024 0.000 0.976 0.000
#> SRR1947509 5 0.4882 0.26613 0.000 0.000 0.072 0.000 0.576 0.352
#> SRR1947644 3 0.3961 0.36797 0.000 0.000 0.556 0.000 0.440 0.004
#> SRR1947643 2 0.0508 0.81969 0.000 0.984 0.012 0.004 0.000 0.000
#> SRR1947642 6 0.3448 0.46081 0.000 0.000 0.280 0.004 0.000 0.716
#> SRR1947640 2 0.4508 0.71785 0.004 0.752 0.076 0.140 0.000 0.028
#> SRR1947641 3 0.4213 0.67836 0.000 0.000 0.780 0.100 0.040 0.080
#> SRR1947639 1 0.6435 0.26631 0.488 0.232 0.036 0.244 0.000 0.000
#> SRR1947638 6 0.5604 0.62310 0.084 0.088 0.060 0.060 0.000 0.708
#> SRR1947637 5 0.3307 0.60017 0.000 0.000 0.148 0.044 0.808 0.000
#> SRR1947636 3 0.5314 0.46749 0.000 0.000 0.544 0.336 0.120 0.000
#> SRR1947635 2 0.3919 0.74743 0.000 0.788 0.072 0.124 0.000 0.016
#> SRR1947634 2 0.2743 0.73629 0.000 0.828 0.008 0.000 0.164 0.000
#> SRR1947633 3 0.4336 0.30416 0.000 0.000 0.504 0.020 0.476 0.000
#> SRR1947632 4 0.3190 0.63815 0.000 0.068 0.068 0.848 0.000 0.016
#> SRR1947631 3 0.4866 0.44886 0.000 0.000 0.568 0.068 0.000 0.364
#> SRR1947629 3 0.2615 0.62600 0.000 0.000 0.852 0.136 0.008 0.004
#> SRR1947630 5 0.3398 0.53867 0.000 0.252 0.008 0.000 0.740 0.000
#> SRR1947627 6 0.5676 -0.23042 0.000 0.000 0.420 0.016 0.100 0.464
#> SRR1947628 2 0.6565 0.34581 0.000 0.464 0.240 0.256 0.000 0.040
#> SRR1947626 2 0.0405 0.82010 0.000 0.988 0.008 0.004 0.000 0.000
#> SRR1947625 3 0.3281 0.59284 0.000 0.000 0.784 0.200 0.004 0.012
#> SRR1947624 5 0.3221 0.53070 0.000 0.264 0.000 0.000 0.736 0.000
#> SRR1947623 1 0.0146 0.83724 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947622 2 0.3307 0.78808 0.000 0.820 0.108 0.072 0.000 0.000
#> SRR1947621 2 0.1462 0.81459 0.000 0.936 0.056 0.008 0.000 0.000
#> SRR1947620 6 0.1036 0.71948 0.004 0.000 0.008 0.024 0.000 0.964
#> SRR1947619 4 0.3302 0.51380 0.004 0.000 0.232 0.760 0.004 0.000
#> SRR1947617 2 0.1657 0.81359 0.000 0.928 0.056 0.016 0.000 0.000
#> SRR1947618 6 0.2962 0.68263 0.000 0.000 0.068 0.084 0.000 0.848
#> SRR1947616 2 0.5691 0.55650 0.000 0.568 0.316 0.080 0.032 0.004
#> SRR1947615 6 0.1151 0.71873 0.000 0.000 0.032 0.012 0.000 0.956
#> SRR1947614 5 0.0458 0.77298 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1947613 1 0.0725 0.83434 0.976 0.000 0.000 0.012 0.000 0.012
#> SRR1947610 2 0.4056 0.75331 0.020 0.780 0.124 0.076 0.000 0.000
#> SRR1947612 2 0.1745 0.81303 0.000 0.924 0.056 0.020 0.000 0.000
#> SRR1947609 6 0.6095 0.27248 0.124 0.000 0.032 0.376 0.000 0.468
#> SRR1947608 4 0.3756 0.42005 0.000 0.000 0.352 0.644 0.000 0.004
#> SRR1947606 3 0.6568 0.56642 0.012 0.000 0.532 0.048 0.168 0.240
#> SRR1947607 1 0.1887 0.81487 0.932 0.016 0.020 0.024 0.000 0.008
#> SRR1947604 6 0.5686 0.14916 0.004 0.032 0.060 0.444 0.000 0.460
#> SRR1947605 6 0.3314 0.57453 0.256 0.000 0.004 0.000 0.000 0.740
#> SRR1947603 2 0.5556 0.26412 0.000 0.512 0.152 0.336 0.000 0.000
#> SRR1947602 6 0.1531 0.70085 0.000 0.000 0.068 0.004 0.000 0.928
#> SRR1947600 3 0.3357 0.67874 0.000 0.000 0.832 0.064 0.092 0.012
#> SRR1947601 2 0.2645 0.80323 0.000 0.880 0.056 0.008 0.056 0.000
#> SRR1947598 4 0.5985 0.25814 0.000 0.012 0.224 0.520 0.000 0.244
#> SRR1947599 6 0.4956 0.54163 0.000 0.004 0.116 0.228 0.000 0.652
#> SRR1947597 2 0.2263 0.80461 0.000 0.896 0.056 0.048 0.000 0.000
#> SRR1947596 1 0.4901 0.07914 0.484 0.000 0.000 0.456 0.000 0.060
#> SRR1947595 2 0.6515 0.32555 0.004 0.480 0.076 0.100 0.340 0.000
#> SRR1947594 1 0.0146 0.83729 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947592 3 0.5335 0.57462 0.000 0.000 0.568 0.140 0.292 0.000
#> SRR1947591 2 0.1285 0.81584 0.000 0.944 0.052 0.004 0.000 0.000
#> SRR1947590 4 0.5001 0.46687 0.248 0.000 0.028 0.660 0.000 0.064
#> SRR1947588 1 0.0436 0.83748 0.988 0.000 0.004 0.004 0.000 0.004
#> SRR1947587 6 0.5715 0.00532 0.000 0.000 0.364 0.148 0.004 0.484
#> SRR1947586 2 0.0291 0.81977 0.004 0.992 0.000 0.004 0.000 0.000
#> SRR1947585 3 0.3406 0.66510 0.000 0.000 0.792 0.008 0.180 0.020
#> SRR1947584 1 0.0291 0.83739 0.992 0.000 0.004 0.004 0.000 0.000
#> SRR1947583 2 0.3123 0.77575 0.000 0.836 0.076 0.088 0.000 0.000
#> SRR1947582 6 0.0551 0.71715 0.004 0.000 0.008 0.004 0.000 0.984
#> SRR1947580 2 0.3045 0.78887 0.004 0.860 0.076 0.052 0.004 0.004
#> SRR1947581 1 0.0291 0.83739 0.992 0.000 0.004 0.004 0.000 0.000
#> SRR1947576 5 0.0146 0.76682 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1947575 4 0.3797 0.33214 0.000 0.000 0.420 0.580 0.000 0.000
#> SRR1947579 5 0.0458 0.77298 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1947578 2 0.5205 0.65353 0.000 0.664 0.148 0.168 0.000 0.020
#> SRR1947573 3 0.5528 0.48486 0.000 0.000 0.508 0.144 0.348 0.000
#> SRR1947574 2 0.5182 0.70765 0.116 0.724 0.076 0.068 0.016 0.000
#> SRR1947571 4 0.4941 0.57425 0.052 0.144 0.044 0.736 0.000 0.024
#> SRR1947577 6 0.1624 0.71358 0.000 0.004 0.020 0.040 0.000 0.936
#> SRR1947570 6 0.0951 0.71701 0.004 0.000 0.020 0.008 0.000 0.968
#> SRR1947569 3 0.2402 0.62012 0.000 0.000 0.856 0.140 0.000 0.004
#> SRR1947566 2 0.2431 0.78694 0.000 0.860 0.132 0.008 0.000 0.000
#> SRR1947567 2 0.2672 0.78786 0.000 0.868 0.052 0.080 0.000 0.000
#> SRR1947568 1 0.4500 0.36105 0.592 0.376 0.024 0.008 0.000 0.000
#> SRR1947564 2 0.4893 0.24280 0.000 0.536 0.064 0.400 0.000 0.000
#> SRR1947563 4 0.3508 0.48404 0.000 0.000 0.292 0.704 0.004 0.000
#> SRR1947562 4 0.2617 0.64096 0.004 0.080 0.004 0.880 0.000 0.032
#> SRR1947565 4 0.4905 -0.00612 0.000 0.000 0.408 0.528 0.064 0.000
#> SRR1947559 2 0.2509 0.79213 0.000 0.876 0.036 0.088 0.000 0.000
#> SRR1947560 5 0.0000 0.76529 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.2058 0.80872 0.000 0.908 0.056 0.036 0.000 0.000
#> SRR1947557 1 0.0436 0.83748 0.988 0.000 0.004 0.004 0.000 0.004
#> SRR1947558 3 0.5051 0.61458 0.000 0.000 0.660 0.140 0.008 0.192
#> SRR1947556 1 0.1531 0.80770 0.928 0.000 0.004 0.068 0.000 0.000
#> SRR1947553 2 0.4719 0.72885 0.040 0.736 0.152 0.068 0.000 0.004
#> SRR1947554 1 0.0922 0.83079 0.968 0.000 0.004 0.024 0.000 0.004
#> SRR1947555 2 0.7098 0.22954 0.000 0.460 0.144 0.232 0.164 0.000
#> SRR1947550 4 0.3646 0.42971 0.000 0.292 0.004 0.700 0.000 0.004
#> SRR1947552 6 0.5123 0.44970 0.004 0.000 0.092 0.316 0.000 0.588
#> SRR1947549 4 0.4593 0.21308 0.000 0.000 0.380 0.576 0.044 0.000
#> SRR1947551 5 0.3955 -0.13895 0.000 0.000 0.436 0.004 0.560 0.000
#> SRR1947548 4 0.3358 0.62842 0.004 0.020 0.060 0.844 0.000 0.072
#> SRR1947506 6 0.3999 0.63135 0.056 0.000 0.124 0.024 0.004 0.792
#> SRR1947507 1 0.0508 0.83592 0.984 0.000 0.004 0.000 0.000 0.012
#> SRR1947504 1 0.0146 0.83724 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1947503 6 0.6271 0.51360 0.188 0.012 0.060 0.144 0.000 0.596
#> SRR1947502 2 0.1745 0.81319 0.000 0.924 0.056 0.020 0.000 0.000
#> SRR1947501 4 0.3347 0.62661 0.000 0.068 0.104 0.824 0.000 0.004
#> SRR1947499 6 0.1471 0.70250 0.000 0.000 0.064 0.004 0.000 0.932
#> SRR1947498 3 0.4374 0.65756 0.000 0.000 0.732 0.008 0.172 0.088
#> SRR1947508 6 0.1327 0.70435 0.000 0.000 0.064 0.000 0.000 0.936
#> SRR1947505 6 0.6764 0.35316 0.000 0.072 0.252 0.200 0.000 0.476
#> SRR1947497 2 0.0000 0.81939 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947496 1 0.0291 0.83737 0.992 0.000 0.004 0.000 0.000 0.004
#> SRR1947495 2 0.0146 0.81956 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1947494 6 0.6161 0.28919 0.044 0.008 0.084 0.384 0.000 0.480
#> SRR1947493 6 0.2446 0.67916 0.124 0.000 0.012 0.000 0.000 0.864
#> SRR1947492 1 0.0405 0.83652 0.988 0.000 0.004 0.000 0.000 0.008
#> SRR1947500 2 0.0291 0.82016 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1947491 2 0.3844 0.77698 0.000 0.812 0.072 0.056 0.000 0.060
#> SRR1947490 1 0.1616 0.82178 0.940 0.000 0.020 0.028 0.000 0.012
#> SRR1947489 6 0.1657 0.71327 0.000 0.000 0.016 0.056 0.000 0.928
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 15148 rows and 152 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 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 0.636 0.839 0.925 0.4434 0.535 0.535
#> 3 3 0.473 0.626 0.768 0.3387 0.819 0.675
#> 4 4 0.500 0.645 0.769 0.1462 0.785 0.524
#> 5 5 0.584 0.563 0.725 0.1143 0.833 0.491
#> 6 6 0.694 0.558 0.749 0.0609 0.937 0.721
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
#> SRR1947547 1 0.5629 0.842 0.868 0.132
#> SRR1947546 2 0.0000 0.941 0.000 1.000
#> SRR1947545 1 0.0000 0.865 1.000 0.000
#> SRR1947544 1 0.3274 0.861 0.940 0.060
#> SRR1947542 2 0.0000 0.941 0.000 1.000
#> SRR1947541 1 0.7056 0.804 0.808 0.192
#> SRR1947540 2 0.0000 0.941 0.000 1.000
#> SRR1947539 2 0.0000 0.941 0.000 1.000
#> SRR1947538 2 0.2043 0.922 0.032 0.968
#> SRR1947537 2 0.0000 0.941 0.000 1.000
#> SRR1947536 1 0.0000 0.865 1.000 0.000
#> SRR1947535 2 0.0000 0.941 0.000 1.000
#> SRR1947534 1 0.0000 0.865 1.000 0.000
#> SRR1947533 2 0.0938 0.935 0.012 0.988
#> SRR1947532 1 0.9686 0.499 0.604 0.396
#> SRR1947531 2 0.4815 0.844 0.104 0.896
#> SRR1947530 1 0.0000 0.865 1.000 0.000
#> SRR1947529 2 0.0000 0.941 0.000 1.000
#> SRR1947528 1 0.5737 0.840 0.864 0.136
#> SRR1947527 2 0.2603 0.911 0.044 0.956
#> SRR1947526 2 0.0000 0.941 0.000 1.000
#> SRR1947525 2 0.0376 0.939 0.004 0.996
#> SRR1947524 2 0.0000 0.941 0.000 1.000
#> SRR1947523 1 0.9686 0.499 0.604 0.396
#> SRR1947521 2 0.9491 0.333 0.368 0.632
#> SRR1947520 2 0.1843 0.924 0.028 0.972
#> SRR1947519 1 0.7602 0.780 0.780 0.220
#> SRR1947518 2 0.0938 0.935 0.012 0.988
#> SRR1947517 2 0.9580 0.299 0.380 0.620
#> SRR1947516 2 0.0000 0.941 0.000 1.000
#> SRR1947515 2 0.2423 0.915 0.040 0.960
#> SRR1947514 2 0.0000 0.941 0.000 1.000
#> SRR1947513 1 0.1184 0.866 0.984 0.016
#> SRR1947512 1 0.2043 0.866 0.968 0.032
#> SRR1947511 2 0.0938 0.935 0.012 0.988
#> SRR1947510 2 0.0376 0.939 0.004 0.996
#> SRR1947572 2 0.0672 0.937 0.008 0.992
#> SRR1947611 2 0.0376 0.939 0.004 0.996
#> SRR1947509 1 0.0000 0.865 1.000 0.000
#> SRR1947644 2 0.0672 0.937 0.008 0.992
#> SRR1947643 2 0.2043 0.922 0.032 0.968
#> SRR1947642 1 0.7602 0.780 0.780 0.220
#> SRR1947640 2 0.9522 0.315 0.372 0.628
#> SRR1947641 2 0.0000 0.941 0.000 1.000
#> SRR1947639 2 0.0376 0.939 0.004 0.996
#> SRR1947638 1 0.1184 0.866 0.984 0.016
#> SRR1947637 2 0.0000 0.941 0.000 1.000
#> SRR1947636 2 0.0000 0.941 0.000 1.000
#> SRR1947635 2 0.9522 0.315 0.372 0.628
#> SRR1947634 2 0.1633 0.927 0.024 0.976
#> SRR1947633 2 0.0000 0.941 0.000 1.000
#> SRR1947632 2 0.0000 0.941 0.000 1.000
#> SRR1947631 2 0.9815 0.135 0.420 0.580
#> SRR1947629 2 0.0000 0.941 0.000 1.000
#> SRR1947630 2 0.1633 0.927 0.024 0.976
#> SRR1947627 1 0.5737 0.840 0.864 0.136
#> SRR1947628 2 0.0000 0.941 0.000 1.000
#> SRR1947626 2 0.0000 0.941 0.000 1.000
#> SRR1947625 2 0.0000 0.941 0.000 1.000
#> SRR1947624 2 0.0000 0.941 0.000 1.000
#> SRR1947623 1 0.8661 0.696 0.712 0.288
#> SRR1947622 2 0.0000 0.941 0.000 1.000
#> SRR1947621 2 0.0000 0.941 0.000 1.000
#> SRR1947620 1 0.0000 0.865 1.000 0.000
#> SRR1947619 2 0.0000 0.941 0.000 1.000
#> SRR1947617 2 0.0000 0.941 0.000 1.000
#> SRR1947618 1 0.1184 0.866 0.984 0.016
#> SRR1947616 2 0.0000 0.941 0.000 1.000
#> SRR1947615 1 0.7674 0.777 0.776 0.224
#> SRR1947614 2 0.9491 0.333 0.368 0.632
#> SRR1947613 1 0.0000 0.865 1.000 0.000
#> SRR1947610 2 0.0376 0.939 0.004 0.996
#> SRR1947612 2 0.0000 0.941 0.000 1.000
#> SRR1947609 1 0.9358 0.593 0.648 0.352
#> SRR1947608 2 0.0000 0.941 0.000 1.000
#> SRR1947606 1 0.6801 0.814 0.820 0.180
#> SRR1947607 1 0.0000 0.865 1.000 0.000
#> SRR1947604 2 0.3274 0.897 0.060 0.940
#> SRR1947605 1 0.0000 0.865 1.000 0.000
#> SRR1947603 2 0.0000 0.941 0.000 1.000
#> SRR1947602 1 0.0000 0.865 1.000 0.000
#> SRR1947600 2 0.0000 0.941 0.000 1.000
#> SRR1947601 2 0.0000 0.941 0.000 1.000
#> SRR1947598 2 0.2043 0.922 0.032 0.968
#> SRR1947599 1 0.9427 0.578 0.640 0.360
#> SRR1947597 2 0.0000 0.941 0.000 1.000
#> SRR1947596 2 0.3274 0.897 0.060 0.940
#> SRR1947595 2 0.4562 0.858 0.096 0.904
#> SRR1947594 1 0.0000 0.865 1.000 0.000
#> SRR1947592 2 0.0000 0.941 0.000 1.000
#> SRR1947591 2 0.0000 0.941 0.000 1.000
#> SRR1947590 2 0.2423 0.915 0.040 0.960
#> SRR1947588 1 0.0000 0.865 1.000 0.000
#> SRR1947587 1 0.8443 0.728 0.728 0.272
#> SRR1947586 2 0.1414 0.930 0.020 0.980
#> SRR1947585 2 0.0000 0.941 0.000 1.000
#> SRR1947584 1 0.2043 0.866 0.968 0.032
#> SRR1947583 2 0.9522 0.315 0.372 0.628
#> SRR1947582 1 0.0000 0.865 1.000 0.000
#> SRR1947580 2 0.1414 0.930 0.020 0.980
#> SRR1947581 1 0.2043 0.866 0.968 0.032
#> SRR1947576 2 0.0000 0.941 0.000 1.000
#> SRR1947575 2 0.0000 0.941 0.000 1.000
#> SRR1947579 2 0.9491 0.333 0.368 0.632
#> SRR1947578 2 0.0000 0.941 0.000 1.000
#> SRR1947573 2 0.0000 0.941 0.000 1.000
#> SRR1947574 2 0.9983 -0.064 0.476 0.524
#> SRR1947571 2 0.2423 0.915 0.040 0.960
#> SRR1947577 1 0.1184 0.866 0.984 0.016
#> SRR1947570 1 0.5629 0.842 0.868 0.132
#> SRR1947569 2 0.0000 0.941 0.000 1.000
#> SRR1947566 2 0.0000 0.941 0.000 1.000
#> SRR1947567 2 0.0000 0.941 0.000 1.000
#> SRR1947568 2 0.0376 0.939 0.004 0.996
#> SRR1947564 2 0.0000 0.941 0.000 1.000
#> SRR1947563 2 0.0000 0.941 0.000 1.000
#> SRR1947562 2 0.0000 0.941 0.000 1.000
#> SRR1947565 2 0.0000 0.941 0.000 1.000
#> SRR1947559 2 0.0000 0.941 0.000 1.000
#> SRR1947560 2 0.0376 0.939 0.004 0.996
#> SRR1947561 2 0.0000 0.941 0.000 1.000
#> SRR1947557 1 0.0000 0.865 1.000 0.000
#> SRR1947558 2 0.0000 0.941 0.000 1.000
#> SRR1947556 1 0.5842 0.838 0.860 0.140
#> SRR1947553 2 0.0376 0.939 0.004 0.996
#> SRR1947554 1 0.0000 0.865 1.000 0.000
#> SRR1947555 2 0.0000 0.941 0.000 1.000
#> SRR1947550 2 0.0000 0.941 0.000 1.000
#> SRR1947552 1 0.9427 0.578 0.640 0.360
#> SRR1947549 2 0.0000 0.941 0.000 1.000
#> SRR1947551 2 0.0376 0.939 0.004 0.996
#> SRR1947548 2 0.2423 0.915 0.040 0.960
#> SRR1947506 1 0.5737 0.840 0.864 0.136
#> SRR1947507 1 0.0000 0.865 1.000 0.000
#> SRR1947504 1 0.5842 0.838 0.860 0.140
#> SRR1947503 1 0.8081 0.746 0.752 0.248
#> SRR1947502 2 0.0000 0.941 0.000 1.000
#> SRR1947501 2 0.0000 0.941 0.000 1.000
#> SRR1947499 1 0.0000 0.865 1.000 0.000
#> SRR1947498 1 0.9909 0.350 0.556 0.444
#> SRR1947508 1 0.5737 0.840 0.864 0.136
#> SRR1947505 1 0.9427 0.578 0.640 0.360
#> SRR1947497 2 0.2603 0.911 0.044 0.956
#> SRR1947496 1 0.0000 0.865 1.000 0.000
#> SRR1947495 2 0.2603 0.911 0.044 0.956
#> SRR1947494 1 0.9686 0.499 0.604 0.396
#> SRR1947493 1 0.0000 0.865 1.000 0.000
#> SRR1947492 1 0.0000 0.865 1.000 0.000
#> SRR1947500 2 0.9522 0.315 0.372 0.628
#> SRR1947491 1 0.8327 0.728 0.736 0.264
#> SRR1947490 1 0.0000 0.865 1.000 0.000
#> SRR1947489 1 0.6531 0.821 0.832 0.168
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.6307 0.0834 0.512 0.000 0.488
#> SRR1947546 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947545 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947544 1 0.4399 0.6892 0.812 0.000 0.188
#> SRR1947542 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947541 3 0.6267 0.1145 0.452 0.000 0.548
#> SRR1947540 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947539 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947538 2 0.5982 0.7116 0.004 0.668 0.328
#> SRR1947537 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947536 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947535 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947534 1 0.2066 0.8151 0.940 0.000 0.060
#> SRR1947533 2 0.4887 0.7955 0.000 0.772 0.228
#> SRR1947532 3 0.7607 0.5250 0.280 0.076 0.644
#> SRR1947531 2 0.6155 0.6878 0.008 0.664 0.328
#> SRR1947530 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947529 2 0.3038 0.8089 0.000 0.896 0.104
#> SRR1947528 1 0.6309 0.0716 0.504 0.000 0.496
#> SRR1947527 2 0.5517 0.7699 0.004 0.728 0.268
#> SRR1947526 2 0.3879 0.8094 0.000 0.848 0.152
#> SRR1947525 2 0.4796 0.7987 0.000 0.780 0.220
#> SRR1947524 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947523 3 0.7607 0.5250 0.280 0.076 0.644
#> SRR1947521 3 0.0661 0.5214 0.004 0.008 0.988
#> SRR1947520 2 0.5138 0.7835 0.000 0.748 0.252
#> SRR1947519 3 0.6598 0.2021 0.428 0.008 0.564
#> SRR1947518 2 0.5517 0.7740 0.004 0.728 0.268
#> SRR1947517 3 0.0747 0.5182 0.016 0.000 0.984
#> SRR1947516 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947515 2 0.6229 0.6931 0.008 0.652 0.340
#> SRR1947514 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947513 1 0.2356 0.8069 0.928 0.000 0.072
#> SRR1947512 1 0.1753 0.8193 0.952 0.000 0.048
#> SRR1947511 2 0.4887 0.7955 0.000 0.772 0.228
#> SRR1947510 3 0.6126 -0.2624 0.000 0.400 0.600
#> SRR1947572 2 0.4974 0.7923 0.000 0.764 0.236
#> SRR1947611 3 0.6126 -0.2624 0.000 0.400 0.600
#> SRR1947509 1 0.0237 0.8381 0.996 0.000 0.004
#> SRR1947644 3 0.6111 -0.2509 0.000 0.396 0.604
#> SRR1947643 2 0.5404 0.7788 0.004 0.740 0.256
#> SRR1947642 3 0.6598 0.2021 0.428 0.008 0.564
#> SRR1947640 3 0.7764 0.3028 0.068 0.328 0.604
#> SRR1947641 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947639 2 0.4887 0.7951 0.000 0.772 0.228
#> SRR1947638 1 0.0892 0.8348 0.980 0.000 0.020
#> SRR1947637 2 0.0747 0.7708 0.000 0.984 0.016
#> SRR1947636 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947635 3 0.7764 0.3028 0.068 0.328 0.604
#> SRR1947634 2 0.5058 0.7879 0.000 0.756 0.244
#> SRR1947633 2 0.6095 0.6631 0.000 0.608 0.392
#> SRR1947632 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947631 2 0.9850 -0.2892 0.252 0.392 0.356
#> SRR1947629 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947630 2 0.5058 0.7879 0.000 0.756 0.244
#> SRR1947627 1 0.6307 0.0928 0.512 0.000 0.488
#> SRR1947628 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947626 2 0.4654 0.8002 0.000 0.792 0.208
#> SRR1947625 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947624 2 0.4504 0.8017 0.000 0.804 0.196
#> SRR1947623 3 0.7291 0.3950 0.356 0.040 0.604
#> SRR1947622 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947621 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947619 2 0.1643 0.7917 0.000 0.956 0.044
#> SRR1947617 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947618 1 0.0892 0.8348 0.980 0.000 0.020
#> SRR1947616 2 0.2261 0.8002 0.000 0.932 0.068
#> SRR1947615 3 0.6745 0.2071 0.428 0.012 0.560
#> SRR1947614 3 0.0661 0.5214 0.004 0.008 0.988
#> SRR1947613 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947610 2 0.4796 0.7971 0.000 0.780 0.220
#> SRR1947612 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947609 3 0.6772 0.4974 0.304 0.032 0.664
#> SRR1947608 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947606 3 0.6495 0.0740 0.460 0.004 0.536
#> SRR1947607 1 0.2066 0.8151 0.940 0.000 0.060
#> SRR1947604 2 0.6416 0.6456 0.008 0.616 0.376
#> SRR1947605 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947602 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947600 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947601 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947598 2 0.6180 0.7037 0.008 0.660 0.332
#> SRR1947599 3 0.6684 0.5065 0.292 0.032 0.676
#> SRR1947597 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947596 2 0.6416 0.6456 0.008 0.616 0.376
#> SRR1947595 2 0.6867 0.7142 0.040 0.672 0.288
#> SRR1947594 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947592 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947591 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947590 2 0.6229 0.6931 0.008 0.652 0.340
#> SRR1947588 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947587 3 0.7956 0.2509 0.424 0.060 0.516
#> SRR1947586 2 0.5016 0.7900 0.000 0.760 0.240
#> SRR1947585 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947584 1 0.1753 0.8193 0.952 0.000 0.048
#> SRR1947583 3 0.7764 0.3028 0.068 0.328 0.604
#> SRR1947582 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947580 2 0.5016 0.7900 0.000 0.760 0.240
#> SRR1947581 1 0.1753 0.8193 0.952 0.000 0.048
#> SRR1947576 2 0.0747 0.7708 0.000 0.984 0.016
#> SRR1947575 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947579 3 0.0661 0.5214 0.004 0.008 0.988
#> SRR1947578 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947573 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947574 3 0.8821 0.4327 0.144 0.304 0.552
#> SRR1947571 2 0.6229 0.6931 0.008 0.652 0.340
#> SRR1947577 1 0.0892 0.8348 0.980 0.000 0.020
#> SRR1947570 1 0.6307 0.0834 0.512 0.000 0.488
#> SRR1947569 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947566 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947567 2 0.3340 0.8081 0.000 0.880 0.120
#> SRR1947568 2 0.4931 0.7940 0.000 0.768 0.232
#> SRR1947564 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947563 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947562 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947565 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947559 2 0.2959 0.8088 0.000 0.900 0.100
#> SRR1947560 3 0.6126 -0.2624 0.000 0.400 0.600
#> SRR1947561 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947558 2 0.6079 0.6682 0.000 0.612 0.388
#> SRR1947556 1 0.6518 0.0841 0.512 0.004 0.484
#> SRR1947553 2 0.4796 0.7971 0.000 0.780 0.220
#> SRR1947554 1 0.2066 0.8151 0.940 0.000 0.060
#> SRR1947555 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947550 2 0.3340 0.8081 0.000 0.880 0.120
#> SRR1947552 3 0.6684 0.5065 0.292 0.032 0.676
#> SRR1947549 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947551 3 0.6126 -0.2624 0.000 0.400 0.600
#> SRR1947548 2 0.6229 0.6931 0.008 0.652 0.340
#> SRR1947506 1 0.5859 0.4084 0.656 0.000 0.344
#> SRR1947507 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947504 1 0.6518 0.0841 0.512 0.004 0.484
#> SRR1947503 3 0.6330 0.3152 0.396 0.004 0.600
#> SRR1947502 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.7718 0.000 1.000 0.000
#> SRR1947499 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947498 3 0.4963 0.4167 0.200 0.008 0.792
#> SRR1947508 1 0.6307 0.0928 0.512 0.000 0.488
#> SRR1947505 3 0.6684 0.5065 0.292 0.032 0.676
#> SRR1947497 2 0.5517 0.7699 0.004 0.728 0.268
#> SRR1947496 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947495 2 0.5517 0.7699 0.004 0.728 0.268
#> SRR1947494 3 0.7607 0.5250 0.280 0.076 0.644
#> SRR1947493 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947500 3 0.7764 0.3028 0.068 0.328 0.604
#> SRR1947491 3 0.6617 0.3448 0.388 0.012 0.600
#> SRR1947490 1 0.0000 0.8404 1.000 0.000 0.000
#> SRR1947489 3 0.6299 0.0253 0.476 0.000 0.524
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 4 0.2675 0.68110 0.100 0.000 0.008 0.892
#> SRR1947546 2 0.2814 0.55446 0.000 0.868 0.132 0.000
#> SRR1947545 1 0.0336 0.89060 0.992 0.000 0.000 0.008
#> SRR1947544 4 0.5050 0.00438 0.408 0.004 0.000 0.588
#> SRR1947542 2 0.2814 0.55446 0.000 0.868 0.132 0.000
#> SRR1947541 4 0.2010 0.72128 0.040 0.012 0.008 0.940
#> SRR1947540 2 0.2281 0.60795 0.000 0.904 0.096 0.000
#> SRR1947539 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947538 2 0.3808 0.66330 0.000 0.812 0.012 0.176
#> SRR1947537 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947536 1 0.0188 0.89143 0.996 0.000 0.000 0.004
#> SRR1947535 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947534 1 0.4008 0.73415 0.756 0.000 0.000 0.244
#> SRR1947533 2 0.1970 0.71032 0.000 0.932 0.008 0.060
#> SRR1947532 4 0.4420 0.70344 0.012 0.204 0.008 0.776
#> SRR1947531 2 0.3764 0.62727 0.000 0.816 0.012 0.172
#> SRR1947530 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947529 2 0.2868 0.55564 0.000 0.864 0.136 0.000
#> SRR1947528 4 0.2924 0.67995 0.100 0.000 0.016 0.884
#> SRR1947527 2 0.2867 0.69519 0.000 0.884 0.012 0.104
#> SRR1947526 2 0.3266 0.61861 0.000 0.868 0.108 0.024
#> SRR1947525 2 0.2489 0.70588 0.000 0.912 0.020 0.068
#> SRR1947524 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947523 4 0.4420 0.70344 0.012 0.204 0.008 0.776
#> SRR1947521 3 0.7140 -0.36496 0.000 0.132 0.464 0.404
#> SRR1947520 2 0.2473 0.70496 0.000 0.908 0.012 0.080
#> SRR1947519 4 0.1739 0.73204 0.016 0.024 0.008 0.952
#> SRR1947518 2 0.2737 0.70427 0.000 0.888 0.008 0.104
#> SRR1947517 3 0.7541 -0.37484 0.012 0.132 0.452 0.404
#> SRR1947516 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947515 2 0.3978 0.65169 0.000 0.796 0.012 0.192
#> SRR1947514 2 0.2868 0.54695 0.000 0.864 0.136 0.000
#> SRR1947513 1 0.4103 0.71986 0.744 0.000 0.000 0.256
#> SRR1947512 1 0.4967 0.38094 0.548 0.000 0.000 0.452
#> SRR1947511 2 0.1970 0.71032 0.000 0.932 0.008 0.060
#> SRR1947510 2 0.5750 0.39924 0.000 0.532 0.440 0.028
#> SRR1947572 2 0.2271 0.70900 0.000 0.916 0.008 0.076
#> SRR1947611 2 0.5750 0.39924 0.000 0.532 0.440 0.028
#> SRR1947509 1 0.0376 0.88998 0.992 0.000 0.004 0.004
#> SRR1947644 2 0.5833 0.39471 0.000 0.528 0.440 0.032
#> SRR1947643 2 0.2676 0.70217 0.000 0.896 0.012 0.092
#> SRR1947642 4 0.1739 0.73204 0.016 0.024 0.008 0.952
#> SRR1947640 4 0.5583 0.18177 0.008 0.468 0.008 0.516
#> SRR1947641 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947639 2 0.2522 0.70573 0.000 0.908 0.016 0.076
#> SRR1947638 1 0.3311 0.79672 0.828 0.000 0.000 0.172
#> SRR1947637 3 0.5147 0.75153 0.000 0.460 0.536 0.004
#> SRR1947636 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947635 4 0.5583 0.18177 0.008 0.468 0.008 0.516
#> SRR1947634 2 0.2329 0.70782 0.000 0.916 0.012 0.072
#> SRR1947633 2 0.4678 0.63459 0.000 0.744 0.232 0.024
#> SRR1947632 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947631 4 0.5773 0.22686 0.004 0.408 0.024 0.564
#> SRR1947629 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947630 2 0.2329 0.70782 0.000 0.916 0.012 0.072
#> SRR1947627 4 0.3048 0.67454 0.108 0.000 0.016 0.876
#> SRR1947628 2 0.2216 0.61290 0.000 0.908 0.092 0.000
#> SRR1947626 2 0.1938 0.70908 0.000 0.936 0.012 0.052
#> SRR1947625 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947624 2 0.1936 0.70036 0.000 0.940 0.028 0.032
#> SRR1947623 4 0.4586 0.73137 0.068 0.136 0.000 0.796
#> SRR1947622 2 0.2814 0.55446 0.000 0.868 0.132 0.000
#> SRR1947621 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947620 1 0.0336 0.89060 0.992 0.000 0.000 0.008
#> SRR1947619 2 0.3569 0.39973 0.000 0.804 0.196 0.000
#> SRR1947617 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947618 1 0.2345 0.84902 0.900 0.000 0.000 0.100
#> SRR1947616 2 0.3219 0.47974 0.000 0.836 0.164 0.000
#> SRR1947615 4 0.1975 0.73340 0.016 0.028 0.012 0.944
#> SRR1947614 3 0.7140 -0.36496 0.000 0.132 0.464 0.404
#> SRR1947613 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947610 2 0.1938 0.71102 0.000 0.936 0.012 0.052
#> SRR1947612 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947609 4 0.4270 0.73189 0.020 0.168 0.008 0.804
#> SRR1947608 3 0.4981 0.76939 0.000 0.464 0.536 0.000
#> SRR1947606 4 0.2725 0.71703 0.056 0.016 0.016 0.912
#> SRR1947607 1 0.4008 0.73415 0.756 0.000 0.000 0.244
#> SRR1947604 2 0.4194 0.61942 0.000 0.764 0.008 0.228
#> SRR1947605 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947603 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947602 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947600 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947601 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947598 2 0.3895 0.65945 0.000 0.804 0.012 0.184
#> SRR1947599 4 0.3916 0.72991 0.008 0.168 0.008 0.816
#> SRR1947597 2 0.2814 0.55446 0.000 0.868 0.132 0.000
#> SRR1947596 2 0.4194 0.61942 0.000 0.764 0.008 0.228
#> SRR1947595 2 0.3903 0.66751 0.008 0.824 0.012 0.156
#> SRR1947594 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947592 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947591 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947590 2 0.3978 0.65169 0.000 0.796 0.012 0.192
#> SRR1947588 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947587 4 0.2923 0.72940 0.016 0.080 0.008 0.896
#> SRR1947586 2 0.2329 0.70785 0.000 0.916 0.012 0.072
#> SRR1947585 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947584 1 0.4967 0.38094 0.548 0.000 0.000 0.452
#> SRR1947583 4 0.5583 0.18177 0.008 0.468 0.008 0.516
#> SRR1947582 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947580 2 0.2329 0.70785 0.000 0.916 0.012 0.072
#> SRR1947581 1 0.4967 0.38094 0.548 0.000 0.000 0.452
#> SRR1947576 3 0.5147 0.75153 0.000 0.460 0.536 0.004
#> SRR1947575 3 0.4981 0.76939 0.000 0.464 0.536 0.000
#> SRR1947579 3 0.7140 -0.36496 0.000 0.132 0.464 0.404
#> SRR1947578 2 0.2216 0.61290 0.000 0.908 0.092 0.000
#> SRR1947573 3 0.4981 0.76939 0.000 0.464 0.536 0.000
#> SRR1947574 4 0.6151 0.36661 0.044 0.396 0.004 0.556
#> SRR1947571 2 0.3978 0.65169 0.000 0.796 0.012 0.192
#> SRR1947577 1 0.2345 0.84902 0.900 0.000 0.000 0.100
#> SRR1947570 4 0.2675 0.68110 0.100 0.000 0.008 0.892
#> SRR1947569 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947566 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947567 2 0.2909 0.62306 0.000 0.888 0.092 0.020
#> SRR1947568 2 0.2125 0.70933 0.000 0.920 0.004 0.076
#> SRR1947564 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947563 3 0.4981 0.76939 0.000 0.464 0.536 0.000
#> SRR1947562 2 0.2149 0.61697 0.000 0.912 0.088 0.000
#> SRR1947565 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947559 2 0.2814 0.55446 0.000 0.868 0.132 0.000
#> SRR1947560 2 0.5750 0.39924 0.000 0.532 0.440 0.028
#> SRR1947561 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947557 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947558 2 0.4644 0.63851 0.000 0.748 0.228 0.024
#> SRR1947556 4 0.3232 0.68138 0.108 0.016 0.004 0.872
#> SRR1947553 2 0.1938 0.71102 0.000 0.936 0.012 0.052
#> SRR1947554 1 0.4008 0.73415 0.756 0.000 0.000 0.244
#> SRR1947555 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947550 2 0.2909 0.62306 0.000 0.888 0.092 0.020
#> SRR1947552 4 0.3916 0.72991 0.008 0.168 0.008 0.816
#> SRR1947549 3 0.4981 0.76939 0.000 0.464 0.536 0.000
#> SRR1947551 2 0.5750 0.39924 0.000 0.532 0.440 0.028
#> SRR1947548 2 0.3978 0.65169 0.000 0.796 0.012 0.192
#> SRR1947506 4 0.4630 0.47676 0.252 0.000 0.016 0.732
#> SRR1947507 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947504 4 0.3232 0.68138 0.108 0.016 0.004 0.872
#> SRR1947503 4 0.4022 0.73514 0.068 0.096 0.000 0.836
#> SRR1947502 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947501 3 0.4989 0.77331 0.000 0.472 0.528 0.000
#> SRR1947499 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947498 4 0.5543 0.59603 0.008 0.040 0.256 0.696
#> SRR1947508 4 0.3048 0.67454 0.108 0.000 0.016 0.876
#> SRR1947505 4 0.3916 0.72991 0.008 0.168 0.008 0.816
#> SRR1947497 2 0.2867 0.69519 0.000 0.884 0.012 0.104
#> SRR1947496 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.2867 0.69519 0.000 0.884 0.012 0.104
#> SRR1947494 4 0.4420 0.70344 0.012 0.204 0.008 0.776
#> SRR1947493 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.5583 0.18177 0.008 0.468 0.008 0.516
#> SRR1947491 4 0.3996 0.73867 0.060 0.104 0.000 0.836
#> SRR1947490 1 0.0000 0.89291 1.000 0.000 0.000 0.000
#> SRR1947489 4 0.2234 0.70974 0.064 0.004 0.008 0.924
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.1502 0.7155 0.056 0.000 0.940 0.000 0.004
#> SRR1947546 2 0.6133 0.2327 0.000 0.524 0.000 0.148 0.328
#> SRR1947545 1 0.0794 0.8738 0.972 0.000 0.028 0.000 0.000
#> SRR1947544 3 0.4921 0.1274 0.360 0.000 0.604 0.036 0.000
#> SRR1947542 2 0.6133 0.2327 0.000 0.524 0.000 0.148 0.328
#> SRR1947541 3 0.1095 0.7434 0.012 0.000 0.968 0.008 0.012
#> SRR1947540 2 0.6225 0.1345 0.000 0.484 0.000 0.148 0.368
#> SRR1947539 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947538 4 0.8182 0.5973 0.000 0.188 0.136 0.364 0.312
#> SRR1947537 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947536 1 0.0162 0.8791 0.996 0.000 0.004 0.000 0.000
#> SRR1947535 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947534 1 0.4040 0.7054 0.724 0.000 0.260 0.016 0.000
#> SRR1947533 4 0.6683 0.5985 0.000 0.164 0.012 0.456 0.368
#> SRR1947532 3 0.4455 0.6830 0.000 0.012 0.740 0.216 0.032
#> SRR1947531 4 0.7702 0.6209 0.000 0.160 0.120 0.484 0.236
#> SRR1947530 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947529 2 0.6164 0.2258 0.000 0.520 0.000 0.152 0.328
#> SRR1947528 3 0.1788 0.7140 0.056 0.000 0.932 0.004 0.008
#> SRR1947527 4 0.6996 0.6625 0.000 0.160 0.044 0.520 0.276
#> SRR1947526 2 0.6942 -0.2696 0.000 0.364 0.004 0.300 0.332
#> SRR1947525 5 0.7639 -0.5415 0.000 0.236 0.052 0.344 0.368
#> SRR1947524 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947523 3 0.4455 0.6830 0.000 0.012 0.740 0.216 0.032
#> SRR1947521 4 0.6097 -0.2379 0.000 0.000 0.124 0.456 0.420
#> SRR1947520 4 0.6730 0.6593 0.000 0.164 0.024 0.524 0.288
#> SRR1947519 3 0.1469 0.7518 0.000 0.000 0.948 0.036 0.016
#> SRR1947518 4 0.7436 0.6440 0.000 0.156 0.068 0.452 0.324
#> SRR1947517 4 0.6296 -0.2312 0.004 0.000 0.132 0.456 0.408
#> SRR1947516 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.8260 0.5847 0.000 0.180 0.156 0.352 0.312
#> SRR1947514 2 0.6089 0.2441 0.000 0.532 0.000 0.144 0.324
#> SRR1947513 1 0.4114 0.6920 0.712 0.000 0.272 0.016 0.000
#> SRR1947512 1 0.4905 0.2731 0.500 0.000 0.476 0.024 0.000
#> SRR1947511 4 0.6683 0.5985 0.000 0.164 0.012 0.456 0.368
#> SRR1947510 5 0.2930 0.6403 0.000 0.000 0.004 0.164 0.832
#> SRR1947572 4 0.7654 0.5814 0.000 0.212 0.060 0.388 0.340
#> SRR1947611 5 0.2930 0.6403 0.000 0.000 0.004 0.164 0.832
#> SRR1947509 1 0.0566 0.8750 0.984 0.000 0.012 0.004 0.000
#> SRR1947644 5 0.2970 0.6367 0.000 0.000 0.004 0.168 0.828
#> SRR1947643 4 0.6899 0.6628 0.000 0.160 0.036 0.520 0.284
#> SRR1947642 3 0.1469 0.7518 0.000 0.000 0.948 0.036 0.016
#> SRR1947640 3 0.7146 0.2001 0.000 0.160 0.472 0.324 0.044
#> SRR1947641 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947639 5 0.7699 -0.5532 0.000 0.224 0.060 0.348 0.368
#> SRR1947638 1 0.3109 0.7705 0.800 0.000 0.200 0.000 0.000
#> SRR1947637 2 0.3003 0.4969 0.000 0.812 0.000 0.000 0.188
#> SRR1947636 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947635 3 0.7146 0.2001 0.000 0.160 0.472 0.324 0.044
#> SRR1947634 4 0.6693 0.6316 0.000 0.164 0.016 0.492 0.328
#> SRR1947633 5 0.1357 0.7830 0.000 0.048 0.000 0.004 0.948
#> SRR1947632 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947631 3 0.5431 0.2637 0.000 0.020 0.548 0.028 0.404
#> SRR1947629 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947630 4 0.6693 0.6316 0.000 0.164 0.016 0.492 0.328
#> SRR1947627 3 0.1924 0.7092 0.064 0.000 0.924 0.004 0.008
#> SRR1947628 2 0.6232 0.1241 0.000 0.480 0.000 0.148 0.372
#> SRR1947626 4 0.6853 0.6397 0.000 0.176 0.020 0.476 0.328
#> SRR1947625 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947624 5 0.6672 -0.5255 0.000 0.196 0.004 0.384 0.416
#> SRR1947623 3 0.4679 0.7368 0.040 0.036 0.772 0.148 0.004
#> SRR1947622 2 0.6133 0.2327 0.000 0.524 0.000 0.148 0.328
#> SRR1947621 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.0794 0.8738 0.972 0.000 0.028 0.000 0.000
#> SRR1947619 5 0.5439 -0.1001 0.000 0.432 0.000 0.060 0.508
#> SRR1947617 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.2280 0.8315 0.880 0.000 0.120 0.000 0.000
#> SRR1947616 2 0.5772 0.2835 0.000 0.564 0.000 0.108 0.328
#> SRR1947615 3 0.1568 0.7535 0.000 0.000 0.944 0.036 0.020
#> SRR1947614 4 0.6097 -0.2379 0.000 0.000 0.124 0.456 0.420
#> SRR1947613 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.6765 0.6510 0.000 0.164 0.020 0.492 0.324
#> SRR1947612 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 3 0.3707 0.7169 0.004 0.000 0.768 0.220 0.008
#> SRR1947608 2 0.2891 0.5083 0.000 0.824 0.000 0.000 0.176
#> SRR1947606 3 0.1978 0.7412 0.032 0.000 0.932 0.024 0.012
#> SRR1947607 1 0.4040 0.7054 0.724 0.000 0.260 0.016 0.000
#> SRR1947604 4 0.8335 0.5753 0.000 0.176 0.184 0.360 0.280
#> SRR1947605 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947602 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947600 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947601 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.8267 0.5826 0.000 0.180 0.156 0.340 0.324
#> SRR1947599 3 0.3551 0.7131 0.000 0.000 0.772 0.220 0.008
#> SRR1947597 2 0.6133 0.2327 0.000 0.524 0.000 0.148 0.328
#> SRR1947596 4 0.8335 0.5753 0.000 0.176 0.184 0.360 0.280
#> SRR1947595 4 0.7404 0.6391 0.000 0.140 0.092 0.504 0.264
#> SRR1947594 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947591 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.8260 0.5847 0.000 0.180 0.156 0.352 0.312
#> SRR1947588 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.2388 0.7430 0.000 0.000 0.900 0.028 0.072
#> SRR1947586 4 0.6680 0.6580 0.000 0.164 0.020 0.520 0.296
#> SRR1947585 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947584 1 0.4900 0.2892 0.512 0.000 0.464 0.024 0.000
#> SRR1947583 3 0.7146 0.2001 0.000 0.160 0.472 0.324 0.044
#> SRR1947582 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947580 4 0.6680 0.6580 0.000 0.164 0.020 0.520 0.296
#> SRR1947581 1 0.4905 0.2731 0.500 0.000 0.476 0.024 0.000
#> SRR1947576 2 0.3003 0.4969 0.000 0.812 0.000 0.000 0.188
#> SRR1947575 2 0.2891 0.5083 0.000 0.824 0.000 0.000 0.176
#> SRR1947579 4 0.6097 -0.2379 0.000 0.000 0.124 0.456 0.420
#> SRR1947578 2 0.6232 0.1241 0.000 0.480 0.000 0.148 0.372
#> SRR1947573 2 0.2891 0.5083 0.000 0.824 0.000 0.000 0.176
#> SRR1947574 3 0.7353 0.3589 0.024 0.140 0.516 0.284 0.036
#> SRR1947571 4 0.8260 0.5847 0.000 0.180 0.156 0.352 0.312
#> SRR1947577 1 0.2280 0.8315 0.880 0.000 0.120 0.000 0.000
#> SRR1947570 3 0.1502 0.7155 0.056 0.000 0.940 0.000 0.004
#> SRR1947569 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947566 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 2 0.6874 0.0312 0.000 0.444 0.020 0.168 0.368
#> SRR1947568 4 0.7657 0.5764 0.000 0.212 0.060 0.384 0.344
#> SRR1947564 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 2 0.2891 0.5083 0.000 0.824 0.000 0.000 0.176
#> SRR1947562 2 0.6360 0.0797 0.000 0.476 0.000 0.172 0.352
#> SRR1947565 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947559 2 0.6133 0.2327 0.000 0.524 0.000 0.148 0.328
#> SRR1947560 5 0.2930 0.6403 0.000 0.000 0.004 0.164 0.832
#> SRR1947561 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 5 0.1197 0.7851 0.000 0.048 0.000 0.000 0.952
#> SRR1947556 3 0.3180 0.7118 0.068 0.000 0.856 0.076 0.000
#> SRR1947553 4 0.6765 0.6510 0.000 0.164 0.020 0.492 0.324
#> SRR1947554 1 0.4040 0.7054 0.724 0.000 0.260 0.016 0.000
#> SRR1947555 2 0.0162 0.6338 0.000 0.996 0.000 0.000 0.004
#> SRR1947550 2 0.6874 0.0312 0.000 0.444 0.020 0.168 0.368
#> SRR1947552 3 0.3551 0.7131 0.000 0.000 0.772 0.220 0.008
#> SRR1947549 2 0.2891 0.5083 0.000 0.824 0.000 0.000 0.176
#> SRR1947551 5 0.2930 0.6403 0.000 0.000 0.004 0.164 0.832
#> SRR1947548 4 0.8260 0.5847 0.000 0.180 0.156 0.352 0.312
#> SRR1947506 3 0.3611 0.5405 0.208 0.000 0.780 0.004 0.008
#> SRR1947507 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 3 0.3180 0.7118 0.068 0.000 0.856 0.076 0.000
#> SRR1947503 3 0.3639 0.7519 0.044 0.000 0.812 0.144 0.000
#> SRR1947502 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 2 0.0000 0.6353 0.000 1.000 0.000 0.000 0.000
#> SRR1947499 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947498 3 0.5414 0.5641 0.000 0.000 0.660 0.140 0.200
#> SRR1947508 3 0.1924 0.7092 0.064 0.000 0.924 0.004 0.008
#> SRR1947505 3 0.3551 0.7131 0.000 0.000 0.772 0.220 0.008
#> SRR1947497 4 0.6996 0.6625 0.000 0.160 0.044 0.520 0.276
#> SRR1947496 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.6996 0.6625 0.000 0.160 0.044 0.520 0.276
#> SRR1947494 3 0.4455 0.6830 0.000 0.012 0.740 0.216 0.032
#> SRR1947493 1 0.0290 0.8789 0.992 0.000 0.008 0.000 0.000
#> SRR1947492 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 3 0.7146 0.2001 0.000 0.160 0.472 0.324 0.044
#> SRR1947491 3 0.3615 0.7529 0.036 0.000 0.808 0.156 0.000
#> SRR1947490 1 0.0000 0.8805 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0771 0.7352 0.020 0.000 0.976 0.000 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.3121 0.6675 0.020 0.008 0.000 0.000 0.148 0.824
#> SRR1947546 2 0.5993 0.3448 0.000 0.472 0.296 0.228 0.004 0.000
#> SRR1947545 1 0.1480 0.8254 0.940 0.000 0.000 0.000 0.020 0.040
#> SRR1947544 6 0.7058 0.1057 0.260 0.040 0.000 0.016 0.272 0.412
#> SRR1947542 2 0.5993 0.3448 0.000 0.472 0.296 0.228 0.004 0.000
#> SRR1947541 6 0.2853 0.6811 0.000 0.008 0.008 0.008 0.124 0.852
#> SRR1947540 2 0.6087 0.2800 0.000 0.428 0.336 0.232 0.004 0.000
#> SRR1947539 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947538 4 0.8684 0.0818 0.000 0.136 0.244 0.284 0.116 0.220
#> SRR1947537 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947536 1 0.0146 0.8393 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947535 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947534 1 0.5111 0.6470 0.624 0.000 0.000 0.000 0.224 0.152
#> SRR1947533 4 0.3480 0.6244 0.000 0.016 0.200 0.776 0.008 0.000
#> SRR1947532 6 0.2668 0.6789 0.000 0.000 0.000 0.168 0.004 0.828
#> SRR1947531 4 0.2121 0.6174 0.000 0.012 0.000 0.892 0.000 0.096
#> SRR1947530 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947529 2 0.6044 0.3242 0.000 0.460 0.292 0.244 0.004 0.000
#> SRR1947528 6 0.3257 0.6651 0.020 0.012 0.000 0.000 0.152 0.816
#> SRR1947527 4 0.0820 0.6875 0.000 0.012 0.000 0.972 0.000 0.016
#> SRR1947526 4 0.6047 0.2596 0.000 0.220 0.292 0.480 0.008 0.000
#> SRR1947525 4 0.7959 0.2200 0.000 0.176 0.312 0.356 0.104 0.052
#> SRR1947524 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947523 6 0.2668 0.6789 0.000 0.000 0.000 0.168 0.004 0.828
#> SRR1947521 5 0.4504 0.9936 0.000 0.000 0.392 0.004 0.576 0.028
#> SRR1947520 4 0.1121 0.6901 0.000 0.016 0.008 0.964 0.008 0.004
#> SRR1947519 6 0.3569 0.6852 0.000 0.008 0.008 0.044 0.124 0.816
#> SRR1947518 4 0.4802 0.6019 0.000 0.104 0.044 0.760 0.060 0.032
#> SRR1947517 5 0.4930 0.9809 0.004 0.008 0.388 0.004 0.564 0.032
#> SRR1947516 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947515 3 0.8794 -0.0877 0.000 0.136 0.248 0.240 0.140 0.236
#> SRR1947514 2 0.5859 0.3488 0.000 0.480 0.288 0.232 0.000 0.000
#> SRR1947513 1 0.5186 0.6373 0.616 0.000 0.000 0.000 0.216 0.168
#> SRR1947512 1 0.7070 0.2603 0.400 0.040 0.000 0.016 0.244 0.300
#> SRR1947511 4 0.3480 0.6244 0.000 0.016 0.200 0.776 0.008 0.000
#> SRR1947510 3 0.2631 0.3427 0.000 0.000 0.820 0.000 0.180 0.000
#> SRR1947572 4 0.7778 0.3142 0.000 0.152 0.240 0.444 0.104 0.060
#> SRR1947611 3 0.2631 0.3427 0.000 0.000 0.820 0.000 0.180 0.000
#> SRR1947509 1 0.0520 0.8344 0.984 0.008 0.000 0.000 0.000 0.008
#> SRR1947644 3 0.2664 0.3330 0.000 0.000 0.816 0.000 0.184 0.000
#> SRR1947643 4 0.0870 0.6913 0.000 0.012 0.004 0.972 0.000 0.012
#> SRR1947642 6 0.3569 0.6852 0.000 0.008 0.008 0.044 0.124 0.816
#> SRR1947640 6 0.4262 0.3537 0.000 0.012 0.000 0.424 0.004 0.560
#> SRR1947641 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947639 4 0.7992 0.2208 0.000 0.164 0.312 0.360 0.104 0.060
#> SRR1947638 1 0.4530 0.7104 0.704 0.000 0.000 0.000 0.160 0.136
#> SRR1947637 2 0.2730 0.5678 0.000 0.808 0.192 0.000 0.000 0.000
#> SRR1947636 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947635 6 0.4262 0.3537 0.000 0.012 0.000 0.424 0.004 0.560
#> SRR1947634 4 0.2565 0.6773 0.000 0.016 0.104 0.872 0.008 0.000
#> SRR1947633 3 0.1152 0.6398 0.000 0.044 0.952 0.000 0.004 0.000
#> SRR1947632 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947631 6 0.6208 0.1929 0.000 0.020 0.400 0.032 0.080 0.468
#> SRR1947629 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947630 4 0.2565 0.6773 0.000 0.016 0.104 0.872 0.008 0.000
#> SRR1947627 6 0.3415 0.6618 0.028 0.012 0.000 0.000 0.152 0.808
#> SRR1947628 2 0.6095 0.2765 0.000 0.428 0.332 0.236 0.004 0.000
#> SRR1947626 4 0.2358 0.6962 0.000 0.028 0.056 0.900 0.016 0.000
#> SRR1947625 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947624 4 0.4554 0.5249 0.000 0.052 0.272 0.668 0.008 0.000
#> SRR1947623 6 0.4176 0.6635 0.000 0.024 0.000 0.076 0.128 0.772
#> SRR1947622 2 0.5993 0.3448 0.000 0.472 0.296 0.228 0.004 0.000
#> SRR1947621 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947620 1 0.1480 0.8254 0.940 0.000 0.000 0.000 0.020 0.040
#> SRR1947619 3 0.4975 -0.1724 0.000 0.428 0.504 0.068 0.000 0.000
#> SRR1947617 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947618 1 0.3608 0.7633 0.788 0.000 0.000 0.000 0.148 0.064
#> SRR1947616 2 0.5801 0.3878 0.000 0.512 0.296 0.188 0.004 0.000
#> SRR1947615 6 0.3633 0.6872 0.000 0.008 0.008 0.048 0.124 0.812
#> SRR1947614 5 0.4504 0.9936 0.000 0.000 0.392 0.004 0.576 0.028
#> SRR1947613 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.1844 0.6995 0.000 0.016 0.040 0.928 0.016 0.000
#> SRR1947612 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947609 6 0.2706 0.6863 0.000 0.000 0.000 0.124 0.024 0.852
#> SRR1947608 2 0.2631 0.5829 0.000 0.820 0.180 0.000 0.000 0.000
#> SRR1947606 6 0.3700 0.6827 0.016 0.012 0.000 0.028 0.136 0.808
#> SRR1947607 1 0.5111 0.6470 0.624 0.000 0.000 0.000 0.224 0.152
#> SRR1947604 6 0.8782 -0.2233 0.000 0.132 0.216 0.252 0.144 0.256
#> SRR1947605 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947602 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947600 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947601 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947598 3 0.8785 -0.0945 0.000 0.136 0.260 0.244 0.140 0.220
#> SRR1947599 6 0.2709 0.6852 0.000 0.000 0.000 0.132 0.020 0.848
#> SRR1947597 2 0.5993 0.3448 0.000 0.472 0.296 0.228 0.004 0.000
#> SRR1947596 6 0.8782 -0.2233 0.000 0.132 0.216 0.252 0.144 0.256
#> SRR1947595 4 0.1444 0.6344 0.000 0.000 0.000 0.928 0.000 0.072
#> SRR1947594 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947591 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947590 3 0.8794 -0.0877 0.000 0.136 0.248 0.240 0.140 0.236
#> SRR1947588 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 6 0.4441 0.6622 0.000 0.008 0.064 0.036 0.124 0.768
#> SRR1947586 4 0.1078 0.6917 0.000 0.016 0.008 0.964 0.012 0.000
#> SRR1947585 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947584 1 0.7022 0.2889 0.424 0.040 0.000 0.016 0.244 0.276
#> SRR1947583 6 0.4262 0.3537 0.000 0.012 0.000 0.424 0.004 0.560
#> SRR1947582 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947580 4 0.1078 0.6917 0.000 0.016 0.008 0.964 0.012 0.000
#> SRR1947581 1 0.7070 0.2603 0.400 0.040 0.000 0.016 0.244 0.300
#> SRR1947576 2 0.2730 0.5678 0.000 0.808 0.192 0.000 0.000 0.000
#> SRR1947575 2 0.2631 0.5829 0.000 0.820 0.180 0.000 0.000 0.000
#> SRR1947579 5 0.4504 0.9936 0.000 0.000 0.392 0.004 0.576 0.028
#> SRR1947578 2 0.6095 0.2765 0.000 0.428 0.332 0.236 0.004 0.000
#> SRR1947573 2 0.2631 0.5829 0.000 0.820 0.180 0.000 0.000 0.000
#> SRR1947574 6 0.4885 0.4363 0.000 0.000 0.000 0.372 0.068 0.560
#> SRR1947571 3 0.8794 -0.0877 0.000 0.136 0.248 0.240 0.140 0.236
#> SRR1947577 1 0.3608 0.7633 0.788 0.000 0.000 0.000 0.148 0.064
#> SRR1947570 6 0.3121 0.6675 0.020 0.008 0.000 0.000 0.148 0.824
#> SRR1947569 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947566 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947567 4 0.6665 -0.0379 0.000 0.296 0.336 0.344 0.004 0.020
#> SRR1947568 4 0.7816 0.3025 0.000 0.152 0.252 0.432 0.104 0.060
#> SRR1947564 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947563 2 0.2631 0.5829 0.000 0.820 0.180 0.000 0.000 0.000
#> SRR1947562 2 0.6146 0.2270 0.000 0.424 0.300 0.272 0.004 0.000
#> SRR1947565 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947559 2 0.5993 0.3448 0.000 0.472 0.296 0.228 0.004 0.000
#> SRR1947560 3 0.2631 0.3427 0.000 0.000 0.820 0.000 0.180 0.000
#> SRR1947561 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947557 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.1007 0.6431 0.000 0.044 0.956 0.000 0.000 0.000
#> SRR1947556 6 0.5103 0.6201 0.000 0.040 0.000 0.048 0.272 0.640
#> SRR1947553 4 0.1844 0.6995 0.000 0.016 0.040 0.928 0.016 0.000
#> SRR1947554 1 0.5111 0.6470 0.624 0.000 0.000 0.000 0.224 0.152
#> SRR1947555 2 0.1398 0.6834 0.000 0.940 0.008 0.052 0.000 0.000
#> SRR1947550 4 0.6665 -0.0379 0.000 0.296 0.336 0.344 0.004 0.020
#> SRR1947552 6 0.2709 0.6852 0.000 0.000 0.000 0.132 0.020 0.848
#> SRR1947549 2 0.2631 0.5829 0.000 0.820 0.180 0.000 0.000 0.000
#> SRR1947551 3 0.2631 0.3427 0.000 0.000 0.820 0.000 0.180 0.000
#> SRR1947548 3 0.8794 -0.0877 0.000 0.136 0.248 0.240 0.140 0.236
#> SRR1947506 6 0.5068 0.5346 0.172 0.012 0.000 0.000 0.148 0.668
#> SRR1947507 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 6 0.5103 0.6201 0.000 0.040 0.000 0.048 0.272 0.640
#> SRR1947503 6 0.2741 0.6826 0.008 0.000 0.000 0.032 0.092 0.868
#> SRR1947502 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947501 2 0.1141 0.6865 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947499 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947498 6 0.6504 0.3325 0.000 0.012 0.188 0.040 0.224 0.536
#> SRR1947508 6 0.3415 0.6618 0.028 0.012 0.000 0.000 0.152 0.808
#> SRR1947505 6 0.2709 0.6852 0.000 0.000 0.000 0.132 0.020 0.848
#> SRR1947497 4 0.0820 0.6875 0.000 0.012 0.000 0.972 0.000 0.016
#> SRR1947496 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.0820 0.6875 0.000 0.012 0.000 0.972 0.000 0.016
#> SRR1947494 6 0.2668 0.6789 0.000 0.000 0.000 0.168 0.004 0.828
#> SRR1947493 1 0.0405 0.8390 0.988 0.000 0.000 0.000 0.008 0.004
#> SRR1947492 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 6 0.4262 0.3537 0.000 0.012 0.000 0.424 0.004 0.560
#> SRR1947491 6 0.2966 0.6863 0.008 0.000 0.000 0.048 0.088 0.856
#> SRR1947490 1 0.0000 0.8411 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 6 0.2615 0.6795 0.000 0.008 0.000 0.004 0.136 0.852
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 15148 rows and 152 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 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 0.968 0.986 0.4571 0.539 0.539
#> 3 3 0.667 0.870 0.910 0.4024 0.645 0.436
#> 4 4 0.630 0.706 0.837 0.1561 0.856 0.626
#> 5 5 0.709 0.691 0.819 0.0705 0.870 0.561
#> 6 6 0.724 0.543 0.734 0.0415 0.923 0.665
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
#> SRR1947547 1 0.0000 0.969 1.000 0.000
#> SRR1947546 2 0.0000 0.994 0.000 1.000
#> SRR1947545 1 0.0376 0.970 0.996 0.004
#> SRR1947544 1 0.0376 0.970 0.996 0.004
#> SRR1947542 2 0.0000 0.994 0.000 1.000
#> SRR1947541 1 0.0000 0.969 1.000 0.000
#> SRR1947540 2 0.0000 0.994 0.000 1.000
#> SRR1947539 2 0.0376 0.993 0.004 0.996
#> SRR1947538 2 0.0000 0.994 0.000 1.000
#> SRR1947537 2 0.0376 0.993 0.004 0.996
#> SRR1947536 1 0.0000 0.969 1.000 0.000
#> SRR1947535 2 0.0376 0.993 0.004 0.996
#> SRR1947534 1 0.0376 0.970 0.996 0.004
#> SRR1947533 2 0.0000 0.994 0.000 1.000
#> SRR1947532 2 0.0000 0.994 0.000 1.000
#> SRR1947531 2 0.0000 0.994 0.000 1.000
#> SRR1947530 1 0.0000 0.969 1.000 0.000
#> SRR1947529 2 0.0000 0.994 0.000 1.000
#> SRR1947528 1 0.0000 0.969 1.000 0.000
#> SRR1947527 2 0.0000 0.994 0.000 1.000
#> SRR1947526 2 0.0000 0.994 0.000 1.000
#> SRR1947525 2 0.0000 0.994 0.000 1.000
#> SRR1947524 2 0.0376 0.993 0.004 0.996
#> SRR1947523 1 0.8713 0.618 0.708 0.292
#> SRR1947521 1 0.8555 0.634 0.720 0.280
#> SRR1947520 2 0.0000 0.994 0.000 1.000
#> SRR1947519 1 0.8608 0.626 0.716 0.284
#> SRR1947518 2 0.0000 0.994 0.000 1.000
#> SRR1947517 1 0.0000 0.969 1.000 0.000
#> SRR1947516 2 0.0000 0.994 0.000 1.000
#> SRR1947515 2 0.0000 0.994 0.000 1.000
#> SRR1947514 2 0.0000 0.994 0.000 1.000
#> SRR1947513 1 0.0376 0.970 0.996 0.004
#> SRR1947512 1 0.0376 0.970 0.996 0.004
#> SRR1947511 2 0.0000 0.994 0.000 1.000
#> SRR1947510 2 0.0376 0.993 0.004 0.996
#> SRR1947572 2 0.0000 0.994 0.000 1.000
#> SRR1947611 2 0.0376 0.993 0.004 0.996
#> SRR1947509 1 0.0000 0.969 1.000 0.000
#> SRR1947644 2 0.0376 0.993 0.004 0.996
#> SRR1947643 2 0.0000 0.994 0.000 1.000
#> SRR1947642 2 0.0376 0.993 0.004 0.996
#> SRR1947640 1 0.0376 0.970 0.996 0.004
#> SRR1947641 2 0.0376 0.993 0.004 0.996
#> SRR1947639 2 0.0000 0.994 0.000 1.000
#> SRR1947638 1 0.0376 0.970 0.996 0.004
#> SRR1947637 2 0.0376 0.993 0.004 0.996
#> SRR1947636 2 0.0376 0.993 0.004 0.996
#> SRR1947635 2 0.0000 0.994 0.000 1.000
#> SRR1947634 2 0.0000 0.994 0.000 1.000
#> SRR1947633 2 0.0376 0.993 0.004 0.996
#> SRR1947632 2 0.0000 0.994 0.000 1.000
#> SRR1947631 2 0.0376 0.993 0.004 0.996
#> SRR1947629 2 0.0376 0.993 0.004 0.996
#> SRR1947630 2 0.0000 0.994 0.000 1.000
#> SRR1947627 1 0.0000 0.969 1.000 0.000
#> SRR1947628 2 0.0000 0.994 0.000 1.000
#> SRR1947626 2 0.0000 0.994 0.000 1.000
#> SRR1947625 2 0.0376 0.993 0.004 0.996
#> SRR1947624 2 0.0000 0.994 0.000 1.000
#> SRR1947623 1 0.0376 0.970 0.996 0.004
#> SRR1947622 2 0.0000 0.994 0.000 1.000
#> SRR1947621 2 0.0000 0.994 0.000 1.000
#> SRR1947620 1 0.0376 0.970 0.996 0.004
#> SRR1947619 2 0.0376 0.993 0.004 0.996
#> SRR1947617 2 0.0000 0.994 0.000 1.000
#> SRR1947618 1 0.0376 0.970 0.996 0.004
#> SRR1947616 2 0.0000 0.994 0.000 1.000
#> SRR1947615 2 0.9881 0.182 0.436 0.564
#> SRR1947614 1 0.0000 0.969 1.000 0.000
#> SRR1947613 1 0.0376 0.970 0.996 0.004
#> SRR1947610 2 0.0000 0.994 0.000 1.000
#> SRR1947612 2 0.0000 0.994 0.000 1.000
#> SRR1947609 1 0.0376 0.970 0.996 0.004
#> SRR1947608 2 0.0376 0.993 0.004 0.996
#> SRR1947606 1 0.0000 0.969 1.000 0.000
#> SRR1947607 1 0.0376 0.970 0.996 0.004
#> SRR1947604 2 0.0000 0.994 0.000 1.000
#> SRR1947605 1 0.0376 0.970 0.996 0.004
#> SRR1947603 2 0.0000 0.994 0.000 1.000
#> SRR1947602 1 0.0000 0.969 1.000 0.000
#> SRR1947600 2 0.0376 0.993 0.004 0.996
#> SRR1947601 2 0.0000 0.994 0.000 1.000
#> SRR1947598 2 0.0000 0.994 0.000 1.000
#> SRR1947599 1 0.0376 0.970 0.996 0.004
#> SRR1947597 2 0.0000 0.994 0.000 1.000
#> SRR1947596 2 0.0000 0.994 0.000 1.000
#> SRR1947595 2 0.0000 0.994 0.000 1.000
#> SRR1947594 1 0.0376 0.970 0.996 0.004
#> SRR1947592 2 0.0376 0.993 0.004 0.996
#> SRR1947591 2 0.0000 0.994 0.000 1.000
#> SRR1947590 2 0.0000 0.994 0.000 1.000
#> SRR1947588 1 0.0376 0.970 0.996 0.004
#> SRR1947587 2 0.0376 0.993 0.004 0.996
#> SRR1947586 2 0.0000 0.994 0.000 1.000
#> SRR1947585 2 0.0376 0.993 0.004 0.996
#> SRR1947584 1 0.0376 0.970 0.996 0.004
#> SRR1947583 2 0.0000 0.994 0.000 1.000
#> SRR1947582 1 0.0376 0.970 0.996 0.004
#> SRR1947580 2 0.0000 0.994 0.000 1.000
#> SRR1947581 1 0.0376 0.970 0.996 0.004
#> SRR1947576 2 0.0376 0.993 0.004 0.996
#> SRR1947575 2 0.0376 0.993 0.004 0.996
#> SRR1947579 2 0.0376 0.993 0.004 0.996
#> SRR1947578 2 0.0000 0.994 0.000 1.000
#> SRR1947573 2 0.0376 0.993 0.004 0.996
#> SRR1947574 1 0.0376 0.970 0.996 0.004
#> SRR1947571 2 0.0000 0.994 0.000 1.000
#> SRR1947577 1 0.0376 0.970 0.996 0.004
#> SRR1947570 1 0.0000 0.969 1.000 0.000
#> SRR1947569 2 0.0376 0.993 0.004 0.996
#> SRR1947566 2 0.0000 0.994 0.000 1.000
#> SRR1947567 2 0.0000 0.994 0.000 1.000
#> SRR1947568 2 0.0000 0.994 0.000 1.000
#> SRR1947564 2 0.0000 0.994 0.000 1.000
#> SRR1947563 2 0.0376 0.993 0.004 0.996
#> SRR1947562 2 0.0000 0.994 0.000 1.000
#> SRR1947565 2 0.0376 0.993 0.004 0.996
#> SRR1947559 2 0.0000 0.994 0.000 1.000
#> SRR1947560 2 0.0376 0.993 0.004 0.996
#> SRR1947561 2 0.0000 0.994 0.000 1.000
#> SRR1947557 1 0.0376 0.970 0.996 0.004
#> SRR1947558 2 0.0376 0.993 0.004 0.996
#> SRR1947556 1 0.0376 0.970 0.996 0.004
#> SRR1947553 2 0.0000 0.994 0.000 1.000
#> SRR1947554 1 0.0376 0.970 0.996 0.004
#> SRR1947555 2 0.0000 0.994 0.000 1.000
#> SRR1947550 2 0.0000 0.994 0.000 1.000
#> SRR1947552 1 0.9209 0.530 0.664 0.336
#> SRR1947549 2 0.0376 0.993 0.004 0.996
#> SRR1947551 2 0.0376 0.993 0.004 0.996
#> SRR1947548 2 0.0000 0.994 0.000 1.000
#> SRR1947506 1 0.0000 0.969 1.000 0.000
#> SRR1947507 1 0.0376 0.970 0.996 0.004
#> SRR1947504 1 0.0376 0.970 0.996 0.004
#> SRR1947503 1 0.0376 0.970 0.996 0.004
#> SRR1947502 2 0.0000 0.994 0.000 1.000
#> SRR1947501 2 0.0000 0.994 0.000 1.000
#> SRR1947499 1 0.0000 0.969 1.000 0.000
#> SRR1947498 2 0.0376 0.993 0.004 0.996
#> SRR1947508 1 0.0000 0.969 1.000 0.000
#> SRR1947505 1 0.8608 0.633 0.716 0.284
#> SRR1947497 2 0.0000 0.994 0.000 1.000
#> SRR1947496 1 0.0376 0.970 0.996 0.004
#> SRR1947495 2 0.0000 0.994 0.000 1.000
#> SRR1947494 2 0.0000 0.994 0.000 1.000
#> SRR1947493 1 0.0000 0.969 1.000 0.000
#> SRR1947492 1 0.0376 0.970 0.996 0.004
#> SRR1947500 2 0.0000 0.994 0.000 1.000
#> SRR1947491 1 0.0376 0.970 0.996 0.004
#> SRR1947490 1 0.0376 0.970 0.996 0.004
#> SRR1947489 1 0.0000 0.969 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.0237 0.9955 0.996 0.000 0.004
#> SRR1947546 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947545 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947541 3 0.1163 0.8544 0.028 0.000 0.972
#> SRR1947540 3 0.4452 0.8411 0.000 0.192 0.808
#> SRR1947539 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947538 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947537 3 0.5948 0.3002 0.000 0.360 0.640
#> SRR1947536 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947535 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947534 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947533 3 0.6180 0.5159 0.000 0.416 0.584
#> SRR1947532 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947531 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947530 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947529 2 0.1289 0.9035 0.000 0.968 0.032
#> SRR1947528 3 0.4504 0.7752 0.196 0.000 0.804
#> SRR1947527 3 0.4555 0.8359 0.000 0.200 0.800
#> SRR1947526 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947525 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947524 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947523 3 0.4270 0.8670 0.024 0.116 0.860
#> SRR1947521 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947520 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947519 3 0.0000 0.8534 0.000 0.000 1.000
#> SRR1947518 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947517 3 0.2878 0.8254 0.096 0.000 0.904
#> SRR1947516 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947515 3 0.5465 0.7494 0.000 0.288 0.712
#> SRR1947514 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947513 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947511 3 0.4555 0.8359 0.000 0.200 0.800
#> SRR1947510 3 0.0592 0.8510 0.000 0.012 0.988
#> SRR1947572 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947611 3 0.5968 0.2837 0.000 0.364 0.636
#> SRR1947509 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947644 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947643 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947642 3 0.0000 0.8534 0.000 0.000 1.000
#> SRR1947640 3 0.4324 0.8667 0.028 0.112 0.860
#> SRR1947641 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947639 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947638 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947637 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947636 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947635 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947634 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947633 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947632 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.8534 0.000 0.000 1.000
#> SRR1947629 2 0.5058 0.7539 0.000 0.756 0.244
#> SRR1947630 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947627 1 0.0237 0.9955 0.996 0.000 0.004
#> SRR1947628 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947626 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947625 3 0.5948 0.2953 0.000 0.360 0.640
#> SRR1947624 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947623 3 0.4920 0.8443 0.108 0.052 0.840
#> SRR1947622 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947619 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947617 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947616 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947615 3 0.0000 0.8534 0.000 0.000 1.000
#> SRR1947614 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947613 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947610 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947612 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947609 3 0.3686 0.8252 0.140 0.000 0.860
#> SRR1947608 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947606 3 0.1031 0.8545 0.024 0.000 0.976
#> SRR1947607 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947604 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947605 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947602 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947600 3 0.5810 0.3623 0.000 0.336 0.664
#> SRR1947601 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947598 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947599 3 0.3686 0.8252 0.140 0.000 0.860
#> SRR1947597 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947596 3 0.4002 0.8580 0.000 0.160 0.840
#> SRR1947595 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947594 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947592 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947591 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947590 3 0.4931 0.8104 0.000 0.232 0.768
#> SRR1947588 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.8534 0.000 0.000 1.000
#> SRR1947586 3 0.4452 0.8411 0.000 0.192 0.808
#> SRR1947585 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947584 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947583 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947582 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947580 3 0.4555 0.8359 0.000 0.200 0.800
#> SRR1947581 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947576 2 0.4002 0.8285 0.000 0.840 0.160
#> SRR1947575 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947579 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947578 2 0.6111 0.0833 0.000 0.604 0.396
#> SRR1947573 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947574 3 0.4527 0.8523 0.088 0.052 0.860
#> SRR1947571 3 0.4452 0.8411 0.000 0.192 0.808
#> SRR1947577 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947570 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947569 2 0.5058 0.7539 0.000 0.756 0.244
#> SRR1947566 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947567 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947568 2 0.1289 0.9053 0.000 0.968 0.032
#> SRR1947564 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947563 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947562 2 0.0424 0.9233 0.000 0.992 0.008
#> SRR1947565 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947559 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947560 3 0.4452 0.6697 0.000 0.192 0.808
#> SRR1947561 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947558 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947556 3 0.4178 0.8032 0.172 0.000 0.828
#> SRR1947553 3 0.4555 0.8359 0.000 0.200 0.800
#> SRR1947554 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947550 3 0.4974 0.8065 0.000 0.236 0.764
#> SRR1947552 3 0.4270 0.8670 0.024 0.116 0.860
#> SRR1947549 2 0.3686 0.8432 0.000 0.860 0.140
#> SRR1947551 2 0.6126 0.4908 0.000 0.600 0.400
#> SRR1947548 2 0.3116 0.8206 0.000 0.892 0.108
#> SRR1947506 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947507 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947504 3 0.5138 0.8380 0.120 0.052 0.828
#> SRR1947503 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947502 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.9279 0.000 1.000 0.000
#> SRR1947499 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947498 3 0.0424 0.8523 0.000 0.008 0.992
#> SRR1947508 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947505 3 0.4015 0.8685 0.028 0.096 0.876
#> SRR1947497 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947496 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947495 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947494 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947493 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947500 3 0.3686 0.8659 0.000 0.140 0.860
#> SRR1947491 3 0.3686 0.8252 0.140 0.000 0.860
#> SRR1947490 1 0.0000 0.9997 1.000 0.000 0.000
#> SRR1947489 3 0.3686 0.8252 0.140 0.000 0.860
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.5203 0.49715 0.576 0.000 0.008 0.416
#> SRR1947546 2 0.4836 0.57501 0.000 0.672 0.320 0.008
#> SRR1947545 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.4406 0.67064 0.700 0.000 0.000 0.300
#> SRR1947542 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947541 4 0.4790 0.00861 0.000 0.000 0.380 0.620
#> SRR1947540 4 0.7024 0.54120 0.000 0.128 0.360 0.512
#> SRR1947539 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947538 4 0.6983 0.54386 0.000 0.124 0.360 0.516
#> SRR1947537 3 0.1118 0.82685 0.000 0.000 0.964 0.036
#> SRR1947536 1 0.0524 0.91931 0.988 0.000 0.008 0.004
#> SRR1947535 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947534 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947533 4 0.7478 0.47940 0.000 0.188 0.344 0.468
#> SRR1947532 4 0.3157 0.69035 0.000 0.004 0.144 0.852
#> SRR1947531 4 0.3161 0.69326 0.000 0.012 0.124 0.864
#> SRR1947530 1 0.0336 0.92082 0.992 0.000 0.008 0.000
#> SRR1947529 2 0.6039 0.46590 0.000 0.596 0.348 0.056
#> SRR1947528 4 0.7268 -0.17583 0.152 0.000 0.372 0.476
#> SRR1947527 4 0.5823 0.65887 0.000 0.120 0.176 0.704
#> SRR1947526 2 0.3257 0.76968 0.000 0.844 0.152 0.004
#> SRR1947525 2 0.5213 0.54897 0.000 0.652 0.328 0.020
#> SRR1947524 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947523 4 0.1004 0.65851 0.000 0.004 0.024 0.972
#> SRR1947521 3 0.4991 0.49651 0.000 0.004 0.608 0.388
#> SRR1947520 4 0.4375 0.68688 0.000 0.032 0.180 0.788
#> SRR1947519 4 0.4790 0.00861 0.000 0.000 0.380 0.620
#> SRR1947518 4 0.6867 0.57950 0.000 0.124 0.324 0.552
#> SRR1947517 3 0.6398 0.38434 0.056 0.004 0.524 0.416
#> SRR1947516 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947515 4 0.6083 0.57319 0.000 0.056 0.360 0.584
#> SRR1947514 2 0.2888 0.79072 0.000 0.872 0.124 0.004
#> SRR1947513 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947511 4 0.6852 0.57198 0.000 0.124 0.320 0.556
#> SRR1947510 3 0.1398 0.80478 0.000 0.004 0.956 0.040
#> SRR1947572 4 0.6937 0.56100 0.000 0.124 0.344 0.532
#> SRR1947611 3 0.1452 0.80564 0.000 0.008 0.956 0.036
#> SRR1947509 1 0.0524 0.91931 0.988 0.000 0.008 0.004
#> SRR1947644 3 0.1109 0.81489 0.000 0.004 0.968 0.028
#> SRR1947643 4 0.5411 0.62352 0.000 0.032 0.312 0.656
#> SRR1947642 4 0.4790 0.00861 0.000 0.000 0.380 0.620
#> SRR1947640 4 0.0712 0.65662 0.008 0.004 0.004 0.984
#> SRR1947641 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947639 2 0.5173 0.56075 0.000 0.660 0.320 0.020
#> SRR1947638 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947637 2 0.3400 0.73416 0.000 0.820 0.180 0.000
#> SRR1947636 3 0.1302 0.82757 0.000 0.000 0.956 0.044
#> SRR1947635 4 0.3208 0.69037 0.000 0.004 0.148 0.848
#> SRR1947634 4 0.4995 0.66345 0.000 0.032 0.248 0.720
#> SRR1947633 3 0.0817 0.82581 0.000 0.000 0.976 0.024
#> SRR1947632 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947631 3 0.4500 0.53301 0.000 0.000 0.684 0.316
#> SRR1947629 3 0.3280 0.73645 0.000 0.124 0.860 0.016
#> SRR1947630 4 0.4267 0.68411 0.000 0.024 0.188 0.788
#> SRR1947627 1 0.5099 0.55541 0.612 0.000 0.008 0.380
#> SRR1947628 2 0.4897 0.55796 0.000 0.660 0.332 0.008
#> SRR1947626 2 0.3448 0.75624 0.000 0.828 0.168 0.004
#> SRR1947625 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947624 2 0.4139 0.75111 0.000 0.800 0.176 0.024
#> SRR1947623 4 0.0779 0.65301 0.016 0.000 0.004 0.980
#> SRR1947622 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947621 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947620 1 0.0188 0.92187 0.996 0.000 0.004 0.000
#> SRR1947619 2 0.5229 0.45895 0.000 0.564 0.428 0.008
#> SRR1947617 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947618 1 0.0188 0.92187 0.996 0.000 0.004 0.000
#> SRR1947616 2 0.0524 0.84809 0.000 0.988 0.008 0.004
#> SRR1947615 4 0.1211 0.64667 0.000 0.000 0.040 0.960
#> SRR1947614 3 0.4991 0.49651 0.000 0.004 0.608 0.388
#> SRR1947613 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.6845 0.57885 0.000 0.128 0.308 0.564
#> SRR1947612 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947609 4 0.1406 0.65134 0.016 0.000 0.024 0.960
#> SRR1947608 2 0.3636 0.73348 0.000 0.820 0.172 0.008
#> SRR1947606 4 0.4790 0.00861 0.000 0.000 0.380 0.620
#> SRR1947607 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.3208 0.69037 0.000 0.004 0.148 0.848
#> SRR1947605 1 0.0188 0.92187 0.996 0.000 0.004 0.000
#> SRR1947603 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947602 1 0.0336 0.92082 0.992 0.000 0.008 0.000
#> SRR1947600 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947601 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947598 4 0.5024 0.59168 0.000 0.008 0.360 0.632
#> SRR1947599 4 0.1406 0.65134 0.016 0.000 0.024 0.960
#> SRR1947597 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947596 4 0.3257 0.69140 0.000 0.004 0.152 0.844
#> SRR1947595 4 0.3529 0.69130 0.000 0.012 0.152 0.836
#> SRR1947594 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947591 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947590 4 0.5253 0.58962 0.000 0.016 0.360 0.624
#> SRR1947588 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.4776 0.48134 0.000 0.000 0.624 0.376
#> SRR1947586 4 0.5226 0.67668 0.000 0.076 0.180 0.744
#> SRR1947585 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947584 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.2988 0.69328 0.000 0.012 0.112 0.876
#> SRR1947582 1 0.0188 0.92187 0.996 0.000 0.004 0.000
#> SRR1947580 4 0.6852 0.57198 0.000 0.124 0.320 0.556
#> SRR1947581 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947576 2 0.4155 0.65744 0.000 0.756 0.240 0.004
#> SRR1947575 2 0.3401 0.74985 0.000 0.840 0.152 0.008
#> SRR1947579 3 0.4188 0.62584 0.000 0.004 0.752 0.244
#> SRR1947578 4 0.7210 0.52052 0.000 0.148 0.360 0.492
#> SRR1947573 2 0.4123 0.67932 0.000 0.772 0.220 0.008
#> SRR1947574 4 0.1059 0.65192 0.012 0.000 0.016 0.972
#> SRR1947571 4 0.5253 0.58962 0.000 0.016 0.360 0.624
#> SRR1947577 1 0.0188 0.92187 0.996 0.000 0.004 0.000
#> SRR1947570 1 0.5138 0.53919 0.600 0.000 0.008 0.392
#> SRR1947569 3 0.3280 0.73645 0.000 0.124 0.860 0.016
#> SRR1947566 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947567 4 0.7024 0.54120 0.000 0.128 0.360 0.512
#> SRR1947568 4 0.7778 0.41480 0.000 0.256 0.324 0.420
#> SRR1947564 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947563 2 0.3636 0.73348 0.000 0.820 0.172 0.008
#> SRR1947562 2 0.4877 0.56436 0.000 0.664 0.328 0.008
#> SRR1947565 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947559 2 0.1576 0.83343 0.000 0.948 0.048 0.004
#> SRR1947560 3 0.1398 0.80478 0.000 0.004 0.956 0.040
#> SRR1947561 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947557 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.1211 0.83001 0.000 0.000 0.960 0.040
#> SRR1947556 4 0.1624 0.65233 0.020 0.000 0.028 0.952
#> SRR1947553 4 0.6808 0.57809 0.000 0.128 0.300 0.572
#> SRR1947554 1 0.4356 0.67613 0.708 0.000 0.000 0.292
#> SRR1947555 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947550 4 0.7024 0.54120 0.000 0.128 0.360 0.512
#> SRR1947552 4 0.1109 0.65797 0.000 0.004 0.028 0.968
#> SRR1947549 2 0.3636 0.73348 0.000 0.820 0.172 0.008
#> SRR1947551 3 0.3048 0.75021 0.000 0.108 0.876 0.016
#> SRR1947548 4 0.6983 0.53603 0.000 0.124 0.360 0.516
#> SRR1947506 1 0.2976 0.84215 0.872 0.000 0.008 0.120
#> SRR1947507 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947504 4 0.1510 0.65482 0.016 0.000 0.028 0.956
#> SRR1947503 1 0.4925 0.47535 0.572 0.000 0.000 0.428
#> SRR1947502 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947501 2 0.0188 0.85026 0.000 0.996 0.000 0.004
#> SRR1947499 1 0.0336 0.92082 0.992 0.000 0.008 0.000
#> SRR1947498 3 0.4761 0.51900 0.000 0.000 0.628 0.372
#> SRR1947508 1 0.2859 0.84821 0.880 0.000 0.008 0.112
#> SRR1947505 4 0.0921 0.65399 0.000 0.000 0.028 0.972
#> SRR1947497 4 0.4332 0.68760 0.000 0.032 0.176 0.792
#> SRR1947496 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947495 4 0.3047 0.68979 0.000 0.012 0.116 0.872
#> SRR1947494 4 0.3157 0.69035 0.000 0.004 0.144 0.852
#> SRR1947493 1 0.0336 0.92082 0.992 0.000 0.008 0.000
#> SRR1947492 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0657 0.65911 0.000 0.012 0.004 0.984
#> SRR1947491 4 0.0779 0.65045 0.016 0.000 0.004 0.980
#> SRR1947490 1 0.0000 0.92244 1.000 0.000 0.000 0.000
#> SRR1947489 4 0.3569 0.45829 0.000 0.000 0.196 0.804
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 5 0.3196 0.5991 0.192 0.000 0.004 0.000 0.804
#> SRR1947546 4 0.5903 0.5190 0.000 0.292 0.120 0.584 0.004
#> SRR1947545 1 0.0162 0.9298 0.996 0.000 0.000 0.000 0.004
#> SRR1947544 5 0.4015 0.3907 0.348 0.000 0.000 0.000 0.652
#> SRR1947542 2 0.0566 0.8597 0.000 0.984 0.000 0.012 0.004
#> SRR1947541 5 0.3980 0.6944 0.000 0.000 0.128 0.076 0.796
#> SRR1947540 4 0.3506 0.7278 0.000 0.024 0.124 0.836 0.016
#> SRR1947539 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947538 4 0.4342 0.7218 0.000 0.024 0.128 0.792 0.056
#> SRR1947537 3 0.1412 0.8541 0.000 0.004 0.952 0.008 0.036
#> SRR1947536 1 0.2672 0.8490 0.872 0.000 0.004 0.008 0.116
#> SRR1947535 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947534 1 0.1544 0.9069 0.932 0.000 0.000 0.000 0.068
#> SRR1947533 4 0.4169 0.6815 0.000 0.148 0.044 0.792 0.016
#> SRR1947532 4 0.4702 -0.0192 0.000 0.000 0.016 0.552 0.432
#> SRR1947531 4 0.3635 0.4598 0.000 0.000 0.004 0.748 0.248
#> SRR1947530 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947529 4 0.5623 0.6328 0.000 0.204 0.104 0.672 0.020
#> SRR1947528 5 0.3871 0.6636 0.040 0.000 0.112 0.024 0.824
#> SRR1947527 4 0.1743 0.7079 0.000 0.028 0.004 0.940 0.028
#> SRR1947526 2 0.5289 0.1142 0.000 0.528 0.040 0.428 0.004
#> SRR1947525 4 0.6287 0.5631 0.000 0.256 0.120 0.596 0.028
#> SRR1947524 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947523 5 0.4147 0.6344 0.000 0.000 0.008 0.316 0.676
#> SRR1947521 5 0.6070 -0.2153 0.000 0.000 0.440 0.120 0.440
#> SRR1947520 4 0.1991 0.6879 0.000 0.004 0.004 0.916 0.076
#> SRR1947519 5 0.4183 0.6943 0.000 0.000 0.136 0.084 0.780
#> SRR1947518 4 0.3644 0.7298 0.000 0.024 0.084 0.844 0.048
#> SRR1947517 5 0.4221 0.3867 0.000 0.000 0.236 0.032 0.732
#> SRR1947516 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.5425 0.6519 0.000 0.004 0.164 0.676 0.156
#> SRR1947514 2 0.4999 0.2691 0.000 0.604 0.032 0.360 0.004
#> SRR1947513 1 0.1544 0.9069 0.932 0.000 0.000 0.000 0.068
#> SRR1947512 1 0.1043 0.9205 0.960 0.000 0.000 0.000 0.040
#> SRR1947511 4 0.3170 0.7145 0.000 0.040 0.036 0.876 0.048
#> SRR1947510 3 0.3471 0.8030 0.000 0.000 0.836 0.072 0.092
#> SRR1947572 4 0.3714 0.7302 0.000 0.024 0.084 0.840 0.052
#> SRR1947611 3 0.2972 0.8260 0.000 0.004 0.872 0.040 0.084
#> SRR1947509 1 0.2672 0.8490 0.872 0.000 0.004 0.008 0.116
#> SRR1947644 3 0.3130 0.8129 0.000 0.000 0.856 0.048 0.096
#> SRR1947643 4 0.1928 0.6877 0.000 0.004 0.004 0.920 0.072
#> SRR1947642 5 0.4487 0.6923 0.000 0.000 0.140 0.104 0.756
#> SRR1947640 5 0.4331 0.5500 0.000 0.000 0.004 0.400 0.596
#> SRR1947641 3 0.0693 0.8620 0.000 0.000 0.980 0.008 0.012
#> SRR1947639 4 0.6188 0.5528 0.000 0.268 0.120 0.592 0.020
#> SRR1947638 1 0.1197 0.9177 0.952 0.000 0.000 0.000 0.048
#> SRR1947637 2 0.3944 0.6952 0.000 0.768 0.200 0.000 0.032
#> SRR1947636 3 0.1281 0.8473 0.000 0.000 0.956 0.032 0.012
#> SRR1947635 4 0.4494 0.2271 0.000 0.000 0.012 0.608 0.380
#> SRR1947634 4 0.1928 0.6877 0.000 0.004 0.004 0.920 0.072
#> SRR1947633 3 0.0451 0.8610 0.000 0.000 0.988 0.008 0.004
#> SRR1947632 2 0.0324 0.8610 0.000 0.992 0.000 0.004 0.004
#> SRR1947631 3 0.4481 0.6120 0.000 0.000 0.720 0.048 0.232
#> SRR1947629 3 0.1281 0.8531 0.000 0.012 0.956 0.000 0.032
#> SRR1947630 4 0.2445 0.6757 0.000 0.004 0.004 0.884 0.108
#> SRR1947627 5 0.3920 0.4653 0.268 0.000 0.004 0.004 0.724
#> SRR1947628 4 0.6765 0.4437 0.000 0.332 0.132 0.504 0.032
#> SRR1947626 4 0.5525 0.3583 0.000 0.392 0.060 0.544 0.004
#> SRR1947625 3 0.1202 0.8568 0.000 0.004 0.960 0.004 0.032
#> SRR1947624 2 0.6428 0.0708 0.000 0.456 0.048 0.436 0.060
#> SRR1947623 5 0.4166 0.5922 0.000 0.000 0.004 0.348 0.648
#> SRR1947622 2 0.0451 0.8599 0.000 0.988 0.000 0.008 0.004
#> SRR1947621 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947620 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947619 3 0.5615 0.2662 0.000 0.336 0.596 0.028 0.040
#> SRR1947617 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947618 1 0.1478 0.9094 0.936 0.000 0.000 0.000 0.064
#> SRR1947616 2 0.0898 0.8491 0.000 0.972 0.020 0.008 0.000
#> SRR1947615 5 0.3992 0.7065 0.000 0.000 0.080 0.124 0.796
#> SRR1947614 3 0.6070 0.1513 0.000 0.000 0.440 0.120 0.440
#> SRR1947613 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3224 0.7326 0.000 0.028 0.076 0.868 0.028
#> SRR1947612 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947609 5 0.3835 0.6769 0.000 0.000 0.008 0.260 0.732
#> SRR1947608 2 0.4323 0.6488 0.000 0.728 0.240 0.004 0.028
#> SRR1947606 5 0.4083 0.6927 0.000 0.000 0.132 0.080 0.788
#> SRR1947607 1 0.1121 0.9192 0.956 0.000 0.000 0.000 0.044
#> SRR1947604 4 0.4497 0.2809 0.000 0.000 0.016 0.632 0.352
#> SRR1947605 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947603 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947602 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947600 3 0.1202 0.8568 0.000 0.004 0.960 0.004 0.032
#> SRR1947601 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.5236 0.6530 0.000 0.000 0.164 0.684 0.152
#> SRR1947599 5 0.3835 0.6769 0.000 0.000 0.008 0.260 0.732
#> SRR1947597 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947596 4 0.4779 0.3050 0.000 0.000 0.032 0.628 0.340
#> SRR1947595 4 0.1831 0.6850 0.000 0.000 0.004 0.920 0.076
#> SRR1947594 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947591 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947590 4 0.5759 0.5701 0.000 0.000 0.160 0.616 0.224
#> SRR1947588 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.5289 0.0324 0.000 0.000 0.500 0.048 0.452
#> SRR1947586 4 0.1743 0.7079 0.000 0.028 0.004 0.940 0.028
#> SRR1947585 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947584 1 0.0162 0.9298 0.996 0.000 0.000 0.000 0.004
#> SRR1947583 4 0.3766 0.4396 0.000 0.000 0.004 0.728 0.268
#> SRR1947582 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947580 4 0.2351 0.7209 0.000 0.028 0.036 0.916 0.020
#> SRR1947581 1 0.0880 0.9227 0.968 0.000 0.000 0.000 0.032
#> SRR1947576 2 0.5973 0.4166 0.000 0.588 0.308 0.020 0.084
#> SRR1947575 2 0.3916 0.7080 0.000 0.780 0.188 0.004 0.028
#> SRR1947579 3 0.5435 0.6471 0.000 0.000 0.660 0.152 0.188
#> SRR1947578 4 0.4523 0.7174 0.000 0.036 0.148 0.776 0.040
#> SRR1947573 2 0.4485 0.5698 0.000 0.680 0.292 0.000 0.028
#> SRR1947574 5 0.4219 0.5367 0.000 0.000 0.000 0.416 0.584
#> SRR1947571 4 0.4805 0.6802 0.000 0.000 0.128 0.728 0.144
#> SRR1947577 1 0.1197 0.9177 0.952 0.000 0.000 0.000 0.048
#> SRR1947570 5 0.3300 0.5846 0.204 0.000 0.004 0.000 0.792
#> SRR1947569 3 0.1281 0.8531 0.000 0.012 0.956 0.000 0.032
#> SRR1947566 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 4 0.4015 0.7252 0.000 0.024 0.124 0.812 0.040
#> SRR1947568 4 0.6056 0.6486 0.000 0.196 0.120 0.648 0.036
#> SRR1947564 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947563 2 0.4019 0.6963 0.000 0.768 0.200 0.004 0.028
#> SRR1947562 4 0.6697 0.4486 0.000 0.332 0.124 0.512 0.032
#> SRR1947565 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947559 2 0.1990 0.8177 0.000 0.928 0.028 0.040 0.004
#> SRR1947560 3 0.3471 0.8030 0.000 0.000 0.836 0.072 0.092
#> SRR1947561 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0566 0.8624 0.000 0.000 0.984 0.004 0.012
#> SRR1947556 5 0.4108 0.6452 0.000 0.000 0.008 0.308 0.684
#> SRR1947553 4 0.2949 0.7323 0.000 0.028 0.076 0.880 0.016
#> SRR1947554 1 0.4268 0.2398 0.556 0.000 0.000 0.000 0.444
#> SRR1947555 2 0.0000 0.8628 0.000 1.000 0.000 0.000 0.000
#> SRR1947550 4 0.4015 0.7252 0.000 0.024 0.124 0.812 0.040
#> SRR1947552 5 0.3980 0.6632 0.000 0.000 0.008 0.284 0.708
#> SRR1947549 2 0.4052 0.6920 0.000 0.764 0.204 0.004 0.028
#> SRR1947551 3 0.3294 0.8198 0.000 0.008 0.852 0.036 0.104
#> SRR1947548 4 0.5909 0.6732 0.000 0.052 0.156 0.680 0.112
#> SRR1947506 1 0.4695 0.2943 0.524 0.000 0.004 0.008 0.464
#> SRR1947507 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947504 5 0.4166 0.6043 0.000 0.000 0.004 0.348 0.648
#> SRR1947503 5 0.4522 0.6404 0.196 0.000 0.000 0.068 0.736
#> SRR1947502 2 0.0162 0.8631 0.000 0.996 0.000 0.000 0.004
#> SRR1947501 2 0.0324 0.8610 0.000 0.992 0.000 0.004 0.004
#> SRR1947499 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947498 3 0.4788 0.5858 0.000 0.000 0.696 0.064 0.240
#> SRR1947508 1 0.4651 0.3929 0.560 0.000 0.004 0.008 0.428
#> SRR1947505 5 0.3957 0.6668 0.000 0.000 0.008 0.280 0.712
#> SRR1947497 4 0.1798 0.6921 0.000 0.004 0.004 0.928 0.064
#> SRR1947496 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.2930 0.5901 0.000 0.000 0.004 0.832 0.164
#> SRR1947494 4 0.4713 -0.0409 0.000 0.000 0.016 0.544 0.440
#> SRR1947493 1 0.0162 0.9299 0.996 0.000 0.000 0.004 0.000
#> SRR1947492 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 5 0.4446 0.3655 0.000 0.000 0.004 0.476 0.520
#> SRR1947491 5 0.3838 0.6734 0.000 0.000 0.004 0.280 0.716
#> SRR1947490 1 0.0000 0.9301 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 5 0.3639 0.7066 0.000 0.000 0.100 0.076 0.824
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.3714 0.586574 0.044 0.000 0.000 0.000 0.196 0.760
#> SRR1947546 4 0.7018 -0.074818 0.000 0.192 0.084 0.396 0.328 0.000
#> SRR1947545 1 0.1333 0.906032 0.944 0.000 0.000 0.000 0.048 0.008
#> SRR1947544 6 0.5420 0.417157 0.256 0.000 0.000 0.000 0.172 0.572
#> SRR1947542 2 0.3120 0.716449 0.000 0.832 0.008 0.028 0.132 0.000
#> SRR1947541 6 0.1367 0.647152 0.000 0.000 0.044 0.000 0.012 0.944
#> SRR1947540 4 0.5227 0.229712 0.000 0.004 0.088 0.608 0.292 0.008
#> SRR1947539 3 0.1078 0.803714 0.000 0.000 0.964 0.008 0.012 0.016
#> SRR1947538 4 0.6163 0.032392 0.000 0.004 0.092 0.492 0.364 0.048
#> SRR1947537 3 0.1340 0.794766 0.000 0.000 0.948 0.008 0.040 0.004
#> SRR1947536 1 0.3707 0.825715 0.784 0.000 0.000 0.000 0.136 0.080
#> SRR1947535 3 0.0862 0.804857 0.000 0.000 0.972 0.008 0.004 0.016
#> SRR1947534 1 0.3088 0.847862 0.808 0.000 0.000 0.000 0.172 0.020
#> SRR1947533 4 0.1788 0.471609 0.000 0.040 0.004 0.928 0.028 0.000
#> SRR1947532 6 0.6198 0.141674 0.000 0.000 0.016 0.248 0.252 0.484
#> SRR1947531 4 0.3163 0.400412 0.000 0.000 0.004 0.764 0.000 0.232
#> SRR1947530 1 0.1462 0.899042 0.936 0.000 0.000 0.000 0.056 0.008
#> SRR1947529 4 0.4528 0.382240 0.000 0.052 0.064 0.752 0.132 0.000
#> SRR1947528 6 0.3351 0.602638 0.000 0.000 0.040 0.000 0.160 0.800
#> SRR1947527 4 0.1340 0.497649 0.000 0.004 0.000 0.948 0.008 0.040
#> SRR1947526 4 0.5165 0.182935 0.000 0.372 0.008 0.548 0.072 0.000
#> SRR1947525 4 0.6983 -0.084699 0.000 0.152 0.084 0.396 0.364 0.004
#> SRR1947524 3 0.0767 0.805665 0.000 0.000 0.976 0.008 0.004 0.012
#> SRR1947523 6 0.3101 0.623765 0.000 0.000 0.000 0.148 0.032 0.820
#> SRR1947521 5 0.7290 -0.237855 0.000 0.000 0.268 0.096 0.328 0.308
#> SRR1947520 4 0.1411 0.492643 0.000 0.000 0.000 0.936 0.004 0.060
#> SRR1947519 6 0.1858 0.645836 0.000 0.000 0.052 0.012 0.012 0.924
#> SRR1947518 4 0.5611 0.140861 0.000 0.004 0.064 0.548 0.352 0.032
#> SRR1947517 6 0.4751 0.354344 0.000 0.000 0.040 0.004 0.428 0.528
#> SRR1947516 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 5 0.7401 0.348081 0.000 0.000 0.208 0.296 0.360 0.136
#> SRR1947514 2 0.5627 0.225795 0.000 0.572 0.012 0.268 0.148 0.000
#> SRR1947513 1 0.3333 0.845832 0.784 0.000 0.000 0.000 0.192 0.024
#> SRR1947512 1 0.2558 0.865670 0.840 0.000 0.000 0.000 0.156 0.004
#> SRR1947511 4 0.0870 0.489350 0.000 0.012 0.000 0.972 0.012 0.004
#> SRR1947510 3 0.5132 0.599910 0.000 0.000 0.604 0.056 0.316 0.024
#> SRR1947572 4 0.5765 0.118223 0.000 0.004 0.072 0.536 0.352 0.036
#> SRR1947611 3 0.4257 0.671780 0.000 0.000 0.712 0.028 0.240 0.020
#> SRR1947509 1 0.3707 0.825715 0.784 0.000 0.000 0.000 0.136 0.080
#> SRR1947644 3 0.5186 0.604976 0.000 0.000 0.608 0.052 0.308 0.032
#> SRR1947643 4 0.1204 0.495046 0.000 0.000 0.000 0.944 0.000 0.056
#> SRR1947642 6 0.2164 0.644210 0.000 0.000 0.060 0.020 0.012 0.908
#> SRR1947640 6 0.4333 0.194382 0.000 0.000 0.000 0.468 0.020 0.512
#> SRR1947641 3 0.1078 0.803714 0.000 0.000 0.964 0.008 0.012 0.016
#> SRR1947639 4 0.6967 -0.075181 0.000 0.156 0.080 0.400 0.360 0.004
#> SRR1947638 1 0.3046 0.855641 0.800 0.000 0.000 0.000 0.188 0.012
#> SRR1947637 2 0.4427 0.577888 0.000 0.660 0.284 0.000 0.056 0.000
#> SRR1947636 3 0.1585 0.792678 0.000 0.000 0.940 0.012 0.012 0.036
#> SRR1947635 4 0.5214 0.070602 0.000 0.000 0.012 0.524 0.064 0.400
#> SRR1947634 4 0.1471 0.493033 0.000 0.000 0.000 0.932 0.004 0.064
#> SRR1947633 3 0.1151 0.802335 0.000 0.000 0.956 0.012 0.032 0.000
#> SRR1947632 2 0.0260 0.830982 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1947631 3 0.4303 0.339626 0.000 0.000 0.588 0.008 0.012 0.392
#> SRR1947629 3 0.1387 0.778600 0.000 0.000 0.932 0.000 0.068 0.000
#> SRR1947630 4 0.3092 0.428069 0.000 0.000 0.000 0.836 0.104 0.060
#> SRR1947627 6 0.4650 0.537264 0.104 0.000 0.000 0.000 0.220 0.676
#> SRR1947628 5 0.7647 0.204735 0.000 0.168 0.180 0.276 0.368 0.008
#> SRR1947626 4 0.6617 0.004181 0.000 0.332 0.028 0.376 0.264 0.000
#> SRR1947625 3 0.0858 0.798937 0.000 0.000 0.968 0.004 0.028 0.000
#> SRR1947624 4 0.5676 0.234613 0.000 0.224 0.012 0.612 0.140 0.012
#> SRR1947623 6 0.4718 0.455199 0.000 0.000 0.000 0.292 0.076 0.632
#> SRR1947622 2 0.2203 0.776020 0.000 0.896 0.004 0.016 0.084 0.000
#> SRR1947621 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 1 0.1082 0.906968 0.956 0.000 0.000 0.000 0.040 0.004
#> SRR1947619 3 0.5388 0.274672 0.000 0.084 0.612 0.020 0.280 0.004
#> SRR1947617 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 1 0.3394 0.846346 0.776 0.000 0.000 0.000 0.200 0.024
#> SRR1947616 2 0.2663 0.762332 0.000 0.876 0.012 0.028 0.084 0.000
#> SRR1947615 6 0.2100 0.652447 0.000 0.000 0.036 0.032 0.016 0.916
#> SRR1947614 5 0.7288 -0.232726 0.000 0.000 0.268 0.096 0.332 0.304
#> SRR1947613 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.4738 0.253987 0.000 0.004 0.040 0.624 0.324 0.008
#> SRR1947612 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 6 0.2724 0.649532 0.000 0.000 0.000 0.084 0.052 0.864
#> SRR1947608 2 0.4916 0.339013 0.000 0.520 0.416 0.000 0.064 0.000
#> SRR1947606 6 0.1511 0.647563 0.000 0.000 0.044 0.004 0.012 0.940
#> SRR1947607 1 0.2814 0.855752 0.820 0.000 0.000 0.000 0.172 0.008
#> SRR1947604 6 0.6329 -0.038539 0.000 0.000 0.012 0.284 0.288 0.416
#> SRR1947605 1 0.0790 0.905095 0.968 0.000 0.000 0.000 0.032 0.000
#> SRR1947603 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947602 1 0.1462 0.899042 0.936 0.000 0.000 0.000 0.056 0.008
#> SRR1947600 3 0.0858 0.798937 0.000 0.000 0.968 0.004 0.028 0.000
#> SRR1947601 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 5 0.7393 0.344210 0.000 0.000 0.204 0.300 0.360 0.136
#> SRR1947599 6 0.2724 0.649532 0.000 0.000 0.000 0.084 0.052 0.864
#> SRR1947597 2 0.0146 0.832074 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1947596 6 0.6467 -0.114691 0.000 0.000 0.020 0.260 0.316 0.404
#> SRR1947595 4 0.1814 0.482429 0.000 0.000 0.000 0.900 0.000 0.100
#> SRR1947594 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0881 0.804256 0.000 0.000 0.972 0.008 0.008 0.012
#> SRR1947591 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 5 0.7553 0.329382 0.000 0.000 0.200 0.244 0.360 0.196
#> SRR1947588 1 0.0260 0.905898 0.992 0.000 0.000 0.000 0.008 0.000
#> SRR1947587 6 0.4491 -0.068542 0.000 0.000 0.476 0.008 0.016 0.500
#> SRR1947586 4 0.1442 0.497375 0.000 0.004 0.000 0.944 0.012 0.040
#> SRR1947585 3 0.0767 0.805665 0.000 0.000 0.976 0.008 0.004 0.012
#> SRR1947584 1 0.1285 0.900498 0.944 0.000 0.000 0.000 0.052 0.004
#> SRR1947583 4 0.3767 0.373073 0.000 0.000 0.004 0.720 0.016 0.260
#> SRR1947582 1 0.1152 0.903116 0.952 0.000 0.000 0.000 0.044 0.004
#> SRR1947580 4 0.1080 0.485222 0.000 0.004 0.000 0.960 0.032 0.004
#> SRR1947581 1 0.2146 0.880878 0.880 0.000 0.000 0.000 0.116 0.004
#> SRR1947576 2 0.6116 0.336266 0.000 0.504 0.288 0.004 0.192 0.012
#> SRR1947575 2 0.4408 0.585707 0.000 0.664 0.280 0.000 0.056 0.000
#> SRR1947579 3 0.6963 0.381800 0.000 0.000 0.420 0.132 0.332 0.116
#> SRR1947578 4 0.5994 -0.011106 0.000 0.008 0.144 0.488 0.352 0.008
#> SRR1947573 2 0.4936 0.281768 0.000 0.500 0.436 0.000 0.064 0.000
#> SRR1947574 4 0.4183 -0.170946 0.000 0.000 0.000 0.508 0.012 0.480
#> SRR1947571 4 0.6847 -0.177220 0.000 0.000 0.104 0.416 0.356 0.124
#> SRR1947577 1 0.3141 0.854671 0.788 0.000 0.000 0.000 0.200 0.012
#> SRR1947570 6 0.3651 0.591367 0.048 0.000 0.000 0.000 0.180 0.772
#> SRR1947569 3 0.1387 0.778600 0.000 0.000 0.932 0.000 0.068 0.000
#> SRR1947566 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 4 0.5403 0.153013 0.000 0.004 0.088 0.556 0.344 0.008
#> SRR1947568 4 0.6694 -0.015516 0.000 0.124 0.072 0.440 0.360 0.004
#> SRR1947564 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947563 2 0.4548 0.543972 0.000 0.632 0.312 0.000 0.056 0.000
#> SRR1947562 5 0.7418 0.075598 0.000 0.176 0.116 0.344 0.356 0.008
#> SRR1947565 3 0.0881 0.804256 0.000 0.000 0.972 0.008 0.008 0.012
#> SRR1947559 2 0.3955 0.638557 0.000 0.776 0.012 0.064 0.148 0.000
#> SRR1947560 3 0.5184 0.595935 0.000 0.000 0.600 0.060 0.316 0.024
#> SRR1947561 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0951 0.804641 0.000 0.000 0.968 0.008 0.004 0.020
#> SRR1947556 6 0.3971 0.574048 0.000 0.000 0.000 0.068 0.184 0.748
#> SRR1947553 4 0.4738 0.253987 0.000 0.004 0.040 0.624 0.324 0.008
#> SRR1947554 1 0.5624 0.347040 0.524 0.000 0.000 0.000 0.180 0.296
#> SRR1947555 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947550 4 0.5403 0.153013 0.000 0.004 0.088 0.556 0.344 0.008
#> SRR1947552 6 0.2875 0.640315 0.000 0.000 0.000 0.096 0.052 0.852
#> SRR1947549 2 0.4548 0.543972 0.000 0.632 0.312 0.000 0.056 0.000
#> SRR1947551 3 0.4265 0.652672 0.000 0.000 0.680 0.016 0.284 0.020
#> SRR1947548 5 0.7555 0.323081 0.000 0.012 0.196 0.312 0.364 0.116
#> SRR1947506 6 0.5520 0.310678 0.240 0.000 0.000 0.000 0.200 0.560
#> SRR1947507 1 0.0260 0.905708 0.992 0.000 0.000 0.000 0.008 0.000
#> SRR1947504 6 0.4924 0.480307 0.000 0.000 0.000 0.144 0.204 0.652
#> SRR1947503 6 0.4351 0.601721 0.064 0.000 0.000 0.012 0.196 0.728
#> SRR1947502 2 0.0000 0.832954 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 2 0.0260 0.830982 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1947499 1 0.1462 0.899042 0.936 0.000 0.000 0.000 0.056 0.008
#> SRR1947498 3 0.5184 0.554682 0.000 0.000 0.636 0.008 0.132 0.224
#> SRR1947508 6 0.5910 -0.000304 0.332 0.000 0.000 0.000 0.220 0.448
#> SRR1947505 6 0.2706 0.642992 0.000 0.000 0.000 0.104 0.036 0.860
#> SRR1947497 4 0.1444 0.494330 0.000 0.000 0.000 0.928 0.000 0.072
#> SRR1947496 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.2260 0.457290 0.000 0.000 0.000 0.860 0.000 0.140
#> SRR1947494 6 0.5951 0.237570 0.000 0.000 0.012 0.232 0.228 0.528
#> SRR1947493 1 0.1524 0.898466 0.932 0.000 0.000 0.000 0.060 0.008
#> SRR1947492 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.4246 -0.087559 0.000 0.000 0.000 0.532 0.016 0.452
#> SRR1947491 6 0.2912 0.646374 0.000 0.000 0.000 0.116 0.040 0.844
#> SRR1947490 1 0.0000 0.906532 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 6 0.1074 0.652627 0.000 0.000 0.028 0.000 0.012 0.960
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 15148 rows and 152 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 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 0.976 0.989 0.4995 0.501 0.501
#> 3 3 0.839 0.935 0.952 0.2960 0.776 0.581
#> 4 4 0.927 0.880 0.945 0.1018 0.887 0.696
#> 5 5 0.919 0.883 0.947 0.0687 0.921 0.738
#> 6 6 0.882 0.870 0.931 0.0591 0.896 0.602
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 4
There is also optional best \(k\) = 2 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
#> SRR1947547 1 0.0000 0.988 1.000 0.000
#> SRR1947546 2 0.0000 0.990 0.000 1.000
#> SRR1947545 1 0.0000 0.988 1.000 0.000
#> SRR1947544 1 0.0000 0.988 1.000 0.000
#> SRR1947542 2 0.0000 0.990 0.000 1.000
#> SRR1947541 1 0.0000 0.988 1.000 0.000
#> SRR1947540 2 0.0000 0.990 0.000 1.000
#> SRR1947539 2 0.0000 0.990 0.000 1.000
#> SRR1947538 2 0.0000 0.990 0.000 1.000
#> SRR1947537 2 0.0000 0.990 0.000 1.000
#> SRR1947536 1 0.0000 0.988 1.000 0.000
#> SRR1947535 2 0.0000 0.990 0.000 1.000
#> SRR1947534 1 0.0000 0.988 1.000 0.000
#> SRR1947533 2 0.0000 0.990 0.000 1.000
#> SRR1947532 1 0.0000 0.988 1.000 0.000
#> SRR1947531 1 0.0000 0.988 1.000 0.000
#> SRR1947530 1 0.0000 0.988 1.000 0.000
#> SRR1947529 2 0.0000 0.990 0.000 1.000
#> SRR1947528 1 0.0000 0.988 1.000 0.000
#> SRR1947527 2 0.0000 0.990 0.000 1.000
#> SRR1947526 2 0.0000 0.990 0.000 1.000
#> SRR1947525 2 0.0000 0.990 0.000 1.000
#> SRR1947524 2 0.0000 0.990 0.000 1.000
#> SRR1947523 1 0.0000 0.988 1.000 0.000
#> SRR1947521 1 0.0000 0.988 1.000 0.000
#> SRR1947520 2 0.0000 0.990 0.000 1.000
#> SRR1947519 1 0.0000 0.988 1.000 0.000
#> SRR1947518 2 0.0000 0.990 0.000 1.000
#> SRR1947517 1 0.0000 0.988 1.000 0.000
#> SRR1947516 2 0.0000 0.990 0.000 1.000
#> SRR1947515 2 0.0000 0.990 0.000 1.000
#> SRR1947514 2 0.0000 0.990 0.000 1.000
#> SRR1947513 1 0.0000 0.988 1.000 0.000
#> SRR1947512 1 0.0000 0.988 1.000 0.000
#> SRR1947511 2 0.0000 0.990 0.000 1.000
#> SRR1947510 2 0.0000 0.990 0.000 1.000
#> SRR1947572 2 0.0000 0.990 0.000 1.000
#> SRR1947611 2 0.0000 0.990 0.000 1.000
#> SRR1947509 1 0.0000 0.988 1.000 0.000
#> SRR1947644 2 0.0000 0.990 0.000 1.000
#> SRR1947643 2 0.0000 0.990 0.000 1.000
#> SRR1947642 1 0.0000 0.988 1.000 0.000
#> SRR1947640 1 0.0000 0.988 1.000 0.000
#> SRR1947641 2 0.0000 0.990 0.000 1.000
#> SRR1947639 2 0.0000 0.990 0.000 1.000
#> SRR1947638 1 0.0000 0.988 1.000 0.000
#> SRR1947637 2 0.0000 0.990 0.000 1.000
#> SRR1947636 2 0.0000 0.990 0.000 1.000
#> SRR1947635 1 0.8016 0.682 0.756 0.244
#> SRR1947634 2 0.0000 0.990 0.000 1.000
#> SRR1947633 2 0.0000 0.990 0.000 1.000
#> SRR1947632 2 0.0000 0.990 0.000 1.000
#> SRR1947631 2 0.3114 0.934 0.056 0.944
#> SRR1947629 2 0.0000 0.990 0.000 1.000
#> SRR1947630 2 0.8661 0.597 0.288 0.712
#> SRR1947627 1 0.0000 0.988 1.000 0.000
#> SRR1947628 2 0.0000 0.990 0.000 1.000
#> SRR1947626 2 0.0000 0.990 0.000 1.000
#> SRR1947625 2 0.0000 0.990 0.000 1.000
#> SRR1947624 2 0.0000 0.990 0.000 1.000
#> SRR1947623 1 0.0000 0.988 1.000 0.000
#> SRR1947622 2 0.0000 0.990 0.000 1.000
#> SRR1947621 2 0.0000 0.990 0.000 1.000
#> SRR1947620 1 0.0000 0.988 1.000 0.000
#> SRR1947619 2 0.0000 0.990 0.000 1.000
#> SRR1947617 2 0.0000 0.990 0.000 1.000
#> SRR1947618 1 0.0000 0.988 1.000 0.000
#> SRR1947616 2 0.0000 0.990 0.000 1.000
#> SRR1947615 1 0.0000 0.988 1.000 0.000
#> SRR1947614 1 0.0000 0.988 1.000 0.000
#> SRR1947613 1 0.0000 0.988 1.000 0.000
#> SRR1947610 2 0.0000 0.990 0.000 1.000
#> SRR1947612 2 0.0000 0.990 0.000 1.000
#> SRR1947609 1 0.0000 0.988 1.000 0.000
#> SRR1947608 2 0.0000 0.990 0.000 1.000
#> SRR1947606 1 0.0000 0.988 1.000 0.000
#> SRR1947607 1 0.0000 0.988 1.000 0.000
#> SRR1947604 1 0.5059 0.873 0.888 0.112
#> SRR1947605 1 0.0000 0.988 1.000 0.000
#> SRR1947603 2 0.0000 0.990 0.000 1.000
#> SRR1947602 1 0.0000 0.988 1.000 0.000
#> SRR1947600 2 0.0000 0.990 0.000 1.000
#> SRR1947601 2 0.0000 0.990 0.000 1.000
#> SRR1947598 2 0.0000 0.990 0.000 1.000
#> SRR1947599 1 0.0000 0.988 1.000 0.000
#> SRR1947597 2 0.0000 0.990 0.000 1.000
#> SRR1947596 2 0.6712 0.785 0.176 0.824
#> SRR1947595 1 0.2948 0.939 0.948 0.052
#> SRR1947594 1 0.0000 0.988 1.000 0.000
#> SRR1947592 2 0.0000 0.990 0.000 1.000
#> SRR1947591 2 0.0000 0.990 0.000 1.000
#> SRR1947590 2 0.0000 0.990 0.000 1.000
#> SRR1947588 1 0.0000 0.988 1.000 0.000
#> SRR1947587 1 0.8443 0.629 0.728 0.272
#> SRR1947586 1 0.4815 0.882 0.896 0.104
#> SRR1947585 2 0.0000 0.990 0.000 1.000
#> SRR1947584 1 0.0000 0.988 1.000 0.000
#> SRR1947583 1 0.0000 0.988 1.000 0.000
#> SRR1947582 1 0.0000 0.988 1.000 0.000
#> SRR1947580 2 0.0000 0.990 0.000 1.000
#> SRR1947581 1 0.0000 0.988 1.000 0.000
#> SRR1947576 2 0.0000 0.990 0.000 1.000
#> SRR1947575 2 0.0000 0.990 0.000 1.000
#> SRR1947579 1 0.0938 0.977 0.988 0.012
#> SRR1947578 2 0.0000 0.990 0.000 1.000
#> SRR1947573 2 0.0000 0.990 0.000 1.000
#> SRR1947574 1 0.0000 0.988 1.000 0.000
#> SRR1947571 2 0.0000 0.990 0.000 1.000
#> SRR1947577 1 0.0000 0.988 1.000 0.000
#> SRR1947570 1 0.0000 0.988 1.000 0.000
#> SRR1947569 2 0.0000 0.990 0.000 1.000
#> SRR1947566 2 0.0000 0.990 0.000 1.000
#> SRR1947567 2 0.0000 0.990 0.000 1.000
#> SRR1947568 2 0.0000 0.990 0.000 1.000
#> SRR1947564 2 0.0000 0.990 0.000 1.000
#> SRR1947563 2 0.0000 0.990 0.000 1.000
#> SRR1947562 2 0.0000 0.990 0.000 1.000
#> SRR1947565 2 0.0000 0.990 0.000 1.000
#> SRR1947559 2 0.0000 0.990 0.000 1.000
#> SRR1947560 2 0.0000 0.990 0.000 1.000
#> SRR1947561 2 0.0000 0.990 0.000 1.000
#> SRR1947557 1 0.0000 0.988 1.000 0.000
#> SRR1947558 2 0.0000 0.990 0.000 1.000
#> SRR1947556 1 0.0000 0.988 1.000 0.000
#> SRR1947553 2 0.0000 0.990 0.000 1.000
#> SRR1947554 1 0.0000 0.988 1.000 0.000
#> SRR1947555 2 0.0000 0.990 0.000 1.000
#> SRR1947550 2 0.0000 0.990 0.000 1.000
#> SRR1947552 1 0.0000 0.988 1.000 0.000
#> SRR1947549 2 0.0000 0.990 0.000 1.000
#> SRR1947551 2 0.0000 0.990 0.000 1.000
#> SRR1947548 2 0.0000 0.990 0.000 1.000
#> SRR1947506 1 0.0000 0.988 1.000 0.000
#> SRR1947507 1 0.0000 0.988 1.000 0.000
#> SRR1947504 1 0.0000 0.988 1.000 0.000
#> SRR1947503 1 0.0000 0.988 1.000 0.000
#> SRR1947502 2 0.0000 0.990 0.000 1.000
#> SRR1947501 2 0.0000 0.990 0.000 1.000
#> SRR1947499 1 0.0000 0.988 1.000 0.000
#> SRR1947498 1 0.0000 0.988 1.000 0.000
#> SRR1947508 1 0.0000 0.988 1.000 0.000
#> SRR1947505 1 0.0000 0.988 1.000 0.000
#> SRR1947497 2 0.8713 0.587 0.292 0.708
#> SRR1947496 1 0.0000 0.988 1.000 0.000
#> SRR1947495 1 0.0000 0.988 1.000 0.000
#> SRR1947494 1 0.0000 0.988 1.000 0.000
#> SRR1947493 1 0.0000 0.988 1.000 0.000
#> SRR1947492 1 0.0000 0.988 1.000 0.000
#> SRR1947500 1 0.0000 0.988 1.000 0.000
#> SRR1947491 1 0.0000 0.988 1.000 0.000
#> SRR1947490 1 0.0000 0.988 1.000 0.000
#> SRR1947489 1 0.0000 0.988 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947546 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947545 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947542 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947541 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947540 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947539 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947538 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947537 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947536 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947535 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947534 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947533 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947532 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947531 1 0.5465 0.653 0.712 0.288 0.000
#> SRR1947530 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947529 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947528 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947527 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947526 2 0.2878 0.966 0.000 0.904 0.096
#> SRR1947525 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947524 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947523 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947521 3 0.6140 0.347 0.404 0.000 0.596
#> SRR1947520 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947519 1 0.4555 0.731 0.800 0.000 0.200
#> SRR1947518 2 0.2878 0.966 0.000 0.904 0.096
#> SRR1947517 1 0.1289 0.946 0.968 0.000 0.032
#> SRR1947516 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947515 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947514 2 0.2878 0.966 0.000 0.904 0.096
#> SRR1947513 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947511 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947572 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947611 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947509 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947644 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947643 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947642 3 0.6215 0.280 0.428 0.000 0.572
#> SRR1947640 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947641 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947639 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947638 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947637 3 0.0592 0.941 0.000 0.012 0.988
#> SRR1947636 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947635 2 0.4887 0.628 0.228 0.772 0.000
#> SRR1947634 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947632 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947631 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947630 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947627 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947628 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947626 2 0.2878 0.966 0.000 0.904 0.096
#> SRR1947625 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947624 2 0.2711 0.962 0.000 0.912 0.088
#> SRR1947623 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947622 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947621 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947620 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947619 3 0.0424 0.944 0.000 0.008 0.992
#> SRR1947617 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947618 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947616 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947615 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947614 3 0.6140 0.347 0.404 0.000 0.596
#> SRR1947613 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947610 2 0.1289 0.930 0.000 0.968 0.032
#> SRR1947612 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947609 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947608 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947606 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947607 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947604 2 0.3112 0.874 0.096 0.900 0.004
#> SRR1947605 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947603 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947602 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947600 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947601 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947598 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947599 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947597 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947596 2 0.3213 0.962 0.008 0.900 0.092
#> SRR1947595 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947594 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947591 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947590 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947588 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947587 3 0.0592 0.939 0.012 0.000 0.988
#> SRR1947586 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947583 1 0.5905 0.544 0.648 0.352 0.000
#> SRR1947582 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947576 3 0.0424 0.944 0.000 0.008 0.992
#> SRR1947575 3 0.0592 0.941 0.000 0.012 0.988
#> SRR1947579 3 0.3112 0.864 0.004 0.096 0.900
#> SRR1947578 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947573 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947574 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947571 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947577 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947570 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947569 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947566 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947567 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947568 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947564 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947563 3 0.0424 0.944 0.000 0.008 0.992
#> SRR1947562 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947565 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947559 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947560 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947561 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947557 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947556 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947553 2 0.1289 0.930 0.000 0.968 0.032
#> SRR1947554 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947555 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947550 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947552 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947549 3 0.0424 0.944 0.000 0.008 0.992
#> SRR1947551 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947548 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947506 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947507 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947504 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947503 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947502 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947501 2 0.2959 0.967 0.000 0.900 0.100
#> SRR1947499 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947498 3 0.2959 0.844 0.100 0.000 0.900
#> SRR1947508 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947505 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947497 2 0.0000 0.910 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947495 1 0.6045 0.483 0.620 0.380 0.000
#> SRR1947494 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947493 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947500 1 0.0237 0.973 0.996 0.004 0.000
#> SRR1947491 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947490 1 0.0000 0.977 1.000 0.000 0.000
#> SRR1947489 1 0.0000 0.977 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947546 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947545 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947542 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947541 1 0.0188 0.974 0.996 0.000 0.004 0.000
#> SRR1947540 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947539 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947538 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947537 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947536 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947535 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947534 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947533 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947532 1 0.6432 0.258 0.536 0.060 0.004 0.400
#> SRR1947531 2 0.1888 0.905 0.044 0.940 0.000 0.016
#> SRR1947530 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947529 4 0.5204 0.347 0.000 0.376 0.012 0.612
#> SRR1947528 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947527 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947526 4 0.5290 0.270 0.000 0.404 0.012 0.584
#> SRR1947525 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947524 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947523 1 0.0188 0.974 0.996 0.000 0.004 0.000
#> SRR1947521 3 0.3801 0.676 0.220 0.000 0.780 0.000
#> SRR1947520 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947519 1 0.3649 0.721 0.796 0.000 0.204 0.000
#> SRR1947518 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947517 1 0.0188 0.973 0.996 0.000 0.004 0.000
#> SRR1947516 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947515 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947514 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947513 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947511 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947510 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947572 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947611 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947509 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947644 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947643 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947642 3 0.4697 0.471 0.356 0.000 0.644 0.000
#> SRR1947640 1 0.1211 0.940 0.960 0.040 0.000 0.000
#> SRR1947641 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947639 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947638 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947637 4 0.4989 0.190 0.000 0.000 0.472 0.528
#> SRR1947636 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947635 2 0.0376 0.895 0.004 0.992 0.004 0.000
#> SRR1947634 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947633 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947632 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947631 3 0.0000 0.928 0.000 0.000 1.000 0.000
#> SRR1947629 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947630 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947627 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947628 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947626 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947625 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947624 2 0.4744 0.615 0.000 0.704 0.012 0.284
#> SRR1947623 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947622 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947621 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947620 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947619 4 0.4040 0.673 0.000 0.000 0.248 0.752
#> SRR1947617 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947618 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947616 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947615 1 0.0188 0.974 0.996 0.000 0.004 0.000
#> SRR1947614 3 0.4382 0.574 0.296 0.000 0.704 0.000
#> SRR1947613 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.0592 0.897 0.000 0.016 0.000 0.984
#> SRR1947612 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947609 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947608 4 0.4989 0.193 0.000 0.000 0.472 0.528
#> SRR1947606 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947607 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.2010 0.872 0.004 0.060 0.004 0.932
#> SRR1947605 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947603 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947602 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947600 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947601 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947598 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947599 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947597 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947596 4 0.1824 0.875 0.000 0.060 0.004 0.936
#> SRR1947595 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947594 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947591 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947590 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947588 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0336 0.921 0.000 0.000 0.992 0.008
#> SRR1947586 2 0.1557 0.940 0.000 0.944 0.000 0.056
#> SRR1947585 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947584 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947583 2 0.1913 0.910 0.040 0.940 0.000 0.020
#> SRR1947582 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947580 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947581 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947576 3 0.3688 0.692 0.000 0.000 0.792 0.208
#> SRR1947575 4 0.4948 0.286 0.000 0.000 0.440 0.560
#> SRR1947579 3 0.0592 0.916 0.000 0.016 0.984 0.000
#> SRR1947578 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947573 3 0.4356 0.530 0.000 0.000 0.708 0.292
#> SRR1947574 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947571 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947577 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947570 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947569 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947566 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947567 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947568 4 0.0000 0.902 0.000 0.000 0.000 1.000
#> SRR1947564 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947563 4 0.4955 0.277 0.000 0.000 0.444 0.556
#> SRR1947562 4 0.1059 0.902 0.000 0.016 0.012 0.972
#> SRR1947565 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947559 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947560 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947561 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947557 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947556 1 0.1211 0.943 0.960 0.040 0.000 0.000
#> SRR1947553 4 0.0592 0.897 0.000 0.016 0.000 0.984
#> SRR1947554 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947555 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947550 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947552 1 0.1398 0.941 0.956 0.040 0.004 0.000
#> SRR1947549 4 0.4955 0.277 0.000 0.000 0.444 0.556
#> SRR1947551 3 0.0188 0.931 0.000 0.000 0.996 0.004
#> SRR1947548 4 0.1637 0.878 0.000 0.060 0.000 0.940
#> SRR1947506 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947507 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947504 1 0.1211 0.943 0.960 0.040 0.000 0.000
#> SRR1947503 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947502 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947501 4 0.0469 0.908 0.000 0.000 0.012 0.988
#> SRR1947499 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947498 3 0.0469 0.915 0.012 0.000 0.988 0.000
#> SRR1947508 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947505 1 0.0188 0.974 0.996 0.000 0.004 0.000
#> SRR1947497 2 0.1637 0.942 0.000 0.940 0.000 0.060
#> SRR1947496 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947495 2 0.1929 0.925 0.024 0.940 0.000 0.036
#> SRR1947494 1 0.5667 0.588 0.696 0.060 0.004 0.240
#> SRR1947493 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947500 2 0.4431 0.562 0.304 0.696 0.000 0.000
#> SRR1947491 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947490 1 0.0000 0.976 1.000 0.000 0.000 0.000
#> SRR1947489 1 0.0188 0.974 0.996 0.000 0.004 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 1 0.0703 0.958 0.976 0.000 0.000 0.024 0.000
#> SRR1947546 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947545 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947542 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947541 1 0.1732 0.920 0.920 0.000 0.000 0.080 0.000
#> SRR1947540 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947539 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947538 4 0.1908 0.845 0.000 0.092 0.000 0.908 0.000
#> SRR1947537 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 1 0.0510 0.961 0.984 0.000 0.000 0.016 0.000
#> SRR1947535 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947533 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947532 4 0.0671 0.821 0.004 0.016 0.000 0.980 0.000
#> SRR1947531 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947530 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947529 2 0.0510 0.894 0.000 0.984 0.000 0.000 0.016
#> SRR1947528 1 0.0609 0.959 0.980 0.000 0.000 0.020 0.000
#> SRR1947527 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947526 2 0.0794 0.885 0.000 0.972 0.000 0.000 0.028
#> SRR1947525 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947524 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 1 0.1608 0.920 0.928 0.000 0.000 0.072 0.000
#> SRR1947521 3 0.3877 0.675 0.212 0.000 0.764 0.024 0.000
#> SRR1947520 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947519 1 0.4449 0.706 0.752 0.000 0.168 0.080 0.000
#> SRR1947518 4 0.1908 0.845 0.000 0.092 0.000 0.908 0.000
#> SRR1947517 1 0.0703 0.957 0.976 0.000 0.000 0.024 0.000
#> SRR1947516 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.1608 0.848 0.000 0.072 0.000 0.928 0.000
#> SRR1947514 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947513 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947511 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947510 3 0.0162 0.955 0.000 0.000 0.996 0.004 0.000
#> SRR1947572 4 0.1908 0.845 0.000 0.092 0.000 0.908 0.000
#> SRR1947611 3 0.0162 0.955 0.000 0.000 0.996 0.004 0.000
#> SRR1947509 1 0.0510 0.961 0.984 0.000 0.000 0.016 0.000
#> SRR1947644 3 0.0162 0.955 0.000 0.000 0.996 0.004 0.000
#> SRR1947643 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947642 3 0.4555 0.648 0.200 0.000 0.732 0.068 0.000
#> SRR1947640 1 0.3983 0.490 0.660 0.000 0.000 0.000 0.340
#> SRR1947641 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947638 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947637 2 0.3586 0.674 0.000 0.736 0.264 0.000 0.000
#> SRR1947636 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 5 0.1732 0.902 0.000 0.000 0.000 0.080 0.920
#> SRR1947634 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947633 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947632 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947631 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947629 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947627 1 0.0609 0.959 0.980 0.000 0.000 0.020 0.000
#> SRR1947628 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947626 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947625 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.3612 0.636 0.000 0.732 0.000 0.000 0.268
#> SRR1947623 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947622 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947621 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947619 2 0.3480 0.693 0.000 0.752 0.248 0.000 0.000
#> SRR1947617 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947615 1 0.2179 0.899 0.896 0.000 0.004 0.100 0.000
#> SRR1947614 3 0.4193 0.606 0.256 0.000 0.720 0.024 0.000
#> SRR1947613 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3707 0.662 0.000 0.284 0.000 0.716 0.000
#> SRR1947612 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947608 2 0.4219 0.391 0.000 0.584 0.416 0.000 0.000
#> SRR1947606 1 0.0609 0.959 0.980 0.000 0.000 0.020 0.000
#> SRR1947607 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.0703 0.827 0.000 0.024 0.000 0.976 0.000
#> SRR1947605 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947602 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947600 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.1608 0.848 0.000 0.072 0.000 0.928 0.000
#> SRR1947599 1 0.1197 0.938 0.952 0.000 0.000 0.048 0.000
#> SRR1947597 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947596 4 0.0703 0.827 0.000 0.024 0.000 0.976 0.000
#> SRR1947595 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947594 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.1341 0.843 0.000 0.056 0.000 0.944 0.000
#> SRR1947588 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.1478 0.908 0.000 0.000 0.936 0.064 0.000
#> SRR1947586 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947585 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947582 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947580 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947581 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 2 0.4390 0.353 0.000 0.568 0.428 0.004 0.000
#> SRR1947575 2 0.3508 0.690 0.000 0.748 0.252 0.000 0.000
#> SRR1947579 3 0.0290 0.953 0.000 0.000 0.992 0.008 0.000
#> SRR1947578 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947573 2 0.4249 0.352 0.000 0.568 0.432 0.000 0.000
#> SRR1947574 1 0.1851 0.890 0.912 0.000 0.000 0.000 0.088
#> SRR1947571 4 0.1792 0.848 0.000 0.084 0.000 0.916 0.000
#> SRR1947577 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947570 1 0.1197 0.944 0.952 0.000 0.000 0.048 0.000
#> SRR1947569 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947568 2 0.3816 0.460 0.000 0.696 0.000 0.304 0.000
#> SRR1947564 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 2 0.3508 0.690 0.000 0.748 0.252 0.000 0.000
#> SRR1947562 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947565 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947560 3 0.0162 0.955 0.000 0.000 0.996 0.004 0.000
#> SRR1947561 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.957 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 4 0.4150 0.314 0.388 0.000 0.000 0.612 0.000
#> SRR1947553 4 0.3861 0.660 0.000 0.284 0.000 0.712 0.004
#> SRR1947554 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947550 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947552 1 0.3636 0.652 0.728 0.000 0.000 0.272 0.000
#> SRR1947549 2 0.3508 0.690 0.000 0.748 0.252 0.000 0.000
#> SRR1947551 3 0.0162 0.955 0.000 0.000 0.996 0.004 0.000
#> SRR1947548 4 0.1792 0.848 0.000 0.084 0.000 0.916 0.000
#> SRR1947506 1 0.0510 0.961 0.984 0.000 0.000 0.016 0.000
#> SRR1947507 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.4283 0.182 0.456 0.000 0.000 0.544 0.000
#> SRR1947503 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947502 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 2 0.0000 0.905 0.000 1.000 0.000 0.000 0.000
#> SRR1947499 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947498 3 0.0703 0.941 0.000 0.000 0.976 0.024 0.000
#> SRR1947508 1 0.0609 0.959 0.980 0.000 0.000 0.020 0.000
#> SRR1947505 1 0.1410 0.929 0.940 0.000 0.000 0.060 0.000
#> SRR1947497 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947496 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 5 0.0000 0.973 0.000 0.000 0.000 0.000 1.000
#> SRR1947494 4 0.0671 0.821 0.004 0.016 0.000 0.980 0.000
#> SRR1947493 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 5 0.3210 0.647 0.212 0.000 0.000 0.000 0.788
#> SRR1947491 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947490 1 0.0000 0.967 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 1 0.1851 0.913 0.912 0.000 0.000 0.088 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.2883 0.8524 0.212 0.000 0.000 0.000 0.000 0.788
#> SRR1947546 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947545 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947542 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947541 6 0.2613 0.8494 0.140 0.000 0.000 0.012 0.000 0.848
#> SRR1947540 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947539 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947538 4 0.0363 0.8790 0.000 0.012 0.000 0.988 0.000 0.000
#> SRR1947537 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947536 6 0.3428 0.7705 0.304 0.000 0.000 0.000 0.000 0.696
#> SRR1947535 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947533 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947532 4 0.0363 0.8707 0.000 0.000 0.000 0.988 0.000 0.012
#> SRR1947531 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947530 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947529 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947528 6 0.2823 0.8546 0.204 0.000 0.000 0.000 0.000 0.796
#> SRR1947527 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947526 2 0.1007 0.9400 0.000 0.956 0.000 0.000 0.044 0.000
#> SRR1947525 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947524 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 1 0.3104 0.7103 0.800 0.000 0.000 0.016 0.000 0.184
#> SRR1947521 6 0.1528 0.7800 0.048 0.000 0.016 0.000 0.000 0.936
#> SRR1947520 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947519 6 0.2666 0.8380 0.112 0.000 0.012 0.012 0.000 0.864
#> SRR1947518 4 0.0508 0.8783 0.000 0.012 0.000 0.984 0.000 0.004
#> SRR1947517 6 0.1387 0.7948 0.068 0.000 0.000 0.000 0.000 0.932
#> SRR1947516 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 4 0.0260 0.8791 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947514 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947513 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947511 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947510 3 0.2048 0.8025 0.000 0.000 0.880 0.000 0.000 0.120
#> SRR1947572 4 0.0458 0.8766 0.000 0.016 0.000 0.984 0.000 0.000
#> SRR1947611 3 0.0790 0.8455 0.000 0.000 0.968 0.000 0.000 0.032
#> SRR1947509 6 0.3428 0.7705 0.304 0.000 0.000 0.000 0.000 0.696
#> SRR1947644 3 0.2048 0.8025 0.000 0.000 0.880 0.000 0.000 0.120
#> SRR1947643 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947642 6 0.2586 0.8173 0.080 0.000 0.032 0.008 0.000 0.880
#> SRR1947640 1 0.0260 0.9589 0.992 0.000 0.000 0.000 0.000 0.008
#> SRR1947641 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947638 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947637 3 0.3747 0.4933 0.000 0.396 0.604 0.000 0.000 0.000
#> SRR1947636 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947635 5 0.2889 0.8287 0.000 0.000 0.000 0.108 0.848 0.044
#> SRR1947634 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947633 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947632 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947631 3 0.1267 0.8278 0.000 0.000 0.940 0.000 0.000 0.060
#> SRR1947629 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947627 6 0.2996 0.8460 0.228 0.000 0.000 0.000 0.000 0.772
#> SRR1947628 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947626 2 0.0146 0.9811 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1947625 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 2 0.3765 0.3310 0.000 0.596 0.000 0.000 0.404 0.000
#> SRR1947623 1 0.0146 0.9620 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947622 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947621 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947619 3 0.3515 0.6170 0.000 0.324 0.676 0.000 0.000 0.000
#> SRR1947617 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947615 6 0.2709 0.8462 0.132 0.000 0.000 0.020 0.000 0.848
#> SRR1947614 6 0.1657 0.7854 0.056 0.000 0.016 0.000 0.000 0.928
#> SRR1947613 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3742 0.4864 0.000 0.348 0.000 0.648 0.000 0.004
#> SRR1947612 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 1 0.0260 0.9589 0.992 0.000 0.000 0.000 0.000 0.008
#> SRR1947608 3 0.3390 0.6536 0.000 0.296 0.704 0.000 0.000 0.000
#> SRR1947606 6 0.2762 0.8554 0.196 0.000 0.000 0.000 0.000 0.804
#> SRR1947607 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.8753 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947605 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947602 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947600 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 4 0.0260 0.8791 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947599 1 0.0520 0.9520 0.984 0.000 0.000 0.008 0.000 0.008
#> SRR1947597 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947596 4 0.0000 0.8753 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947595 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947594 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947591 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 4 0.0146 0.8777 0.000 0.004 0.000 0.996 0.000 0.000
#> SRR1947588 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 6 0.4002 0.3171 0.000 0.000 0.404 0.008 0.000 0.588
#> SRR1947586 5 0.0146 0.9636 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947585 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 5 0.0260 0.9603 0.000 0.000 0.000 0.000 0.992 0.008
#> SRR1947582 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947580 5 0.0146 0.9636 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1947581 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 3 0.4193 0.5670 0.000 0.352 0.624 0.000 0.000 0.024
#> SRR1947575 3 0.3747 0.4933 0.000 0.396 0.604 0.000 0.000 0.000
#> SRR1947579 3 0.3409 0.6011 0.000 0.000 0.700 0.000 0.000 0.300
#> SRR1947578 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947573 3 0.3309 0.6720 0.000 0.280 0.720 0.000 0.000 0.000
#> SRR1947574 1 0.0146 0.9620 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947571 4 0.0363 0.8790 0.000 0.012 0.000 0.988 0.000 0.000
#> SRR1947577 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947570 6 0.3109 0.8470 0.224 0.000 0.000 0.004 0.000 0.772
#> SRR1947569 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947568 2 0.0363 0.9726 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1947564 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947563 3 0.3563 0.5991 0.000 0.336 0.664 0.000 0.000 0.000
#> SRR1947562 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947565 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947559 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947560 3 0.1863 0.8102 0.000 0.000 0.896 0.000 0.000 0.104
#> SRR1947561 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.8562 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 4 0.3862 -0.0259 0.476 0.000 0.000 0.524 0.000 0.000
#> SRR1947553 4 0.3756 0.4784 0.000 0.352 0.000 0.644 0.000 0.004
#> SRR1947554 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947555 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947550 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947552 1 0.4480 0.4246 0.616 0.000 0.000 0.340 0.000 0.044
#> SRR1947549 3 0.3531 0.6118 0.000 0.328 0.672 0.000 0.000 0.000
#> SRR1947551 3 0.0790 0.8455 0.000 0.000 0.968 0.000 0.000 0.032
#> SRR1947548 4 0.0363 0.8790 0.000 0.012 0.000 0.988 0.000 0.000
#> SRR1947506 6 0.3737 0.6138 0.392 0.000 0.000 0.000 0.000 0.608
#> SRR1947507 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 1 0.3782 0.3043 0.588 0.000 0.000 0.412 0.000 0.000
#> SRR1947503 1 0.0146 0.9620 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1947502 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 2 0.0000 0.9846 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947499 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947498 6 0.1204 0.7278 0.000 0.000 0.056 0.000 0.000 0.944
#> SRR1947508 6 0.2996 0.8460 0.228 0.000 0.000 0.000 0.000 0.772
#> SRR1947505 1 0.1745 0.8889 0.920 0.000 0.000 0.012 0.000 0.068
#> SRR1947497 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 5 0.0000 0.9654 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947494 4 0.0547 0.8663 0.000 0.000 0.000 0.980 0.000 0.020
#> SRR1947493 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 5 0.3421 0.5831 0.256 0.000 0.000 0.000 0.736 0.008
#> SRR1947491 1 0.0260 0.9589 0.992 0.000 0.000 0.000 0.000 0.008
#> SRR1947490 1 0.0000 0.9646 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 6 0.2613 0.8491 0.140 0.000 0.000 0.012 0.000 0.848
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 15148 rows and 152 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 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 1.000 0.982 0.993 0.4303 0.575 0.575
#> 3 3 0.958 0.942 0.968 0.4589 0.665 0.481
#> 4 4 0.873 0.881 0.947 0.1904 0.851 0.618
#> 5 5 0.768 0.672 0.838 0.0444 0.979 0.917
#> 6 6 0.797 0.748 0.863 0.0374 0.930 0.726
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
#> SRR1947547 1 0.000 0.998 1.000 0.000
#> SRR1947546 2 0.000 0.990 0.000 1.000
#> SRR1947545 1 0.000 0.998 1.000 0.000
#> SRR1947544 1 0.000 0.998 1.000 0.000
#> SRR1947542 2 0.000 0.990 0.000 1.000
#> SRR1947541 1 0.000 0.998 1.000 0.000
#> SRR1947540 2 0.000 0.990 0.000 1.000
#> SRR1947539 2 0.000 0.990 0.000 1.000
#> SRR1947538 2 0.000 0.990 0.000 1.000
#> SRR1947537 2 0.000 0.990 0.000 1.000
#> SRR1947536 1 0.000 0.998 1.000 0.000
#> SRR1947535 2 0.000 0.990 0.000 1.000
#> SRR1947534 1 0.000 0.998 1.000 0.000
#> SRR1947533 2 0.000 0.990 0.000 1.000
#> SRR1947532 2 0.000 0.990 0.000 1.000
#> SRR1947531 2 0.000 0.990 0.000 1.000
#> SRR1947530 1 0.000 0.998 1.000 0.000
#> SRR1947529 2 0.000 0.990 0.000 1.000
#> SRR1947528 1 0.000 0.998 1.000 0.000
#> SRR1947527 2 0.000 0.990 0.000 1.000
#> SRR1947526 2 0.000 0.990 0.000 1.000
#> SRR1947525 2 0.000 0.990 0.000 1.000
#> SRR1947524 2 0.000 0.990 0.000 1.000
#> SRR1947523 2 0.000 0.990 0.000 1.000
#> SRR1947521 1 0.430 0.902 0.912 0.088
#> SRR1947520 2 0.000 0.990 0.000 1.000
#> SRR1947519 2 0.000 0.990 0.000 1.000
#> SRR1947518 2 0.000 0.990 0.000 1.000
#> SRR1947517 1 0.000 0.998 1.000 0.000
#> SRR1947516 2 0.000 0.990 0.000 1.000
#> SRR1947515 2 0.000 0.990 0.000 1.000
#> SRR1947514 2 0.000 0.990 0.000 1.000
#> SRR1947513 1 0.000 0.998 1.000 0.000
#> SRR1947512 1 0.000 0.998 1.000 0.000
#> SRR1947511 2 0.000 0.990 0.000 1.000
#> SRR1947510 2 0.000 0.990 0.000 1.000
#> SRR1947572 2 0.000 0.990 0.000 1.000
#> SRR1947611 2 0.000 0.990 0.000 1.000
#> SRR1947509 1 0.000 0.998 1.000 0.000
#> SRR1947644 2 0.000 0.990 0.000 1.000
#> SRR1947643 2 0.000 0.990 0.000 1.000
#> SRR1947642 2 0.000 0.990 0.000 1.000
#> SRR1947640 2 0.000 0.990 0.000 1.000
#> SRR1947641 2 0.000 0.990 0.000 1.000
#> SRR1947639 2 0.000 0.990 0.000 1.000
#> SRR1947638 1 0.000 0.998 1.000 0.000
#> SRR1947637 2 0.000 0.990 0.000 1.000
#> SRR1947636 2 0.000 0.990 0.000 1.000
#> SRR1947635 2 0.000 0.990 0.000 1.000
#> SRR1947634 2 0.000 0.990 0.000 1.000
#> SRR1947633 2 0.000 0.990 0.000 1.000
#> SRR1947632 2 0.000 0.990 0.000 1.000
#> SRR1947631 2 0.000 0.990 0.000 1.000
#> SRR1947629 2 0.000 0.990 0.000 1.000
#> SRR1947630 2 0.000 0.990 0.000 1.000
#> SRR1947627 1 0.000 0.998 1.000 0.000
#> SRR1947628 2 0.000 0.990 0.000 1.000
#> SRR1947626 2 0.000 0.990 0.000 1.000
#> SRR1947625 2 0.000 0.990 0.000 1.000
#> SRR1947624 2 0.000 0.990 0.000 1.000
#> SRR1947623 2 0.881 0.575 0.300 0.700
#> SRR1947622 2 0.000 0.990 0.000 1.000
#> SRR1947621 2 0.000 0.990 0.000 1.000
#> SRR1947620 1 0.000 0.998 1.000 0.000
#> SRR1947619 2 0.000 0.990 0.000 1.000
#> SRR1947617 2 0.000 0.990 0.000 1.000
#> SRR1947618 1 0.000 0.998 1.000 0.000
#> SRR1947616 2 0.000 0.990 0.000 1.000
#> SRR1947615 2 0.000 0.990 0.000 1.000
#> SRR1947614 1 0.000 0.998 1.000 0.000
#> SRR1947613 1 0.000 0.998 1.000 0.000
#> SRR1947610 2 0.000 0.990 0.000 1.000
#> SRR1947612 2 0.000 0.990 0.000 1.000
#> SRR1947609 1 0.000 0.998 1.000 0.000
#> SRR1947608 2 0.000 0.990 0.000 1.000
#> SRR1947606 1 0.000 0.998 1.000 0.000
#> SRR1947607 1 0.000 0.998 1.000 0.000
#> SRR1947604 2 0.000 0.990 0.000 1.000
#> SRR1947605 1 0.000 0.998 1.000 0.000
#> SRR1947603 2 0.000 0.990 0.000 1.000
#> SRR1947602 1 0.000 0.998 1.000 0.000
#> SRR1947600 2 0.000 0.990 0.000 1.000
#> SRR1947601 2 0.000 0.990 0.000 1.000
#> SRR1947598 2 0.000 0.990 0.000 1.000
#> SRR1947599 1 0.000 0.998 1.000 0.000
#> SRR1947597 2 0.000 0.990 0.000 1.000
#> SRR1947596 2 0.000 0.990 0.000 1.000
#> SRR1947595 2 0.000 0.990 0.000 1.000
#> SRR1947594 1 0.000 0.998 1.000 0.000
#> SRR1947592 2 0.000 0.990 0.000 1.000
#> SRR1947591 2 0.000 0.990 0.000 1.000
#> SRR1947590 2 0.000 0.990 0.000 1.000
#> SRR1947588 1 0.000 0.998 1.000 0.000
#> SRR1947587 2 0.000 0.990 0.000 1.000
#> SRR1947586 2 0.000 0.990 0.000 1.000
#> SRR1947585 2 0.000 0.990 0.000 1.000
#> SRR1947584 1 0.000 0.998 1.000 0.000
#> SRR1947583 2 0.000 0.990 0.000 1.000
#> SRR1947582 1 0.000 0.998 1.000 0.000
#> SRR1947580 2 0.000 0.990 0.000 1.000
#> SRR1947581 1 0.000 0.998 1.000 0.000
#> SRR1947576 2 0.000 0.990 0.000 1.000
#> SRR1947575 2 0.000 0.990 0.000 1.000
#> SRR1947579 2 0.900 0.539 0.316 0.684
#> SRR1947578 2 0.000 0.990 0.000 1.000
#> SRR1947573 2 0.000 0.990 0.000 1.000
#> SRR1947574 1 0.000 0.998 1.000 0.000
#> SRR1947571 2 0.000 0.990 0.000 1.000
#> SRR1947577 1 0.000 0.998 1.000 0.000
#> SRR1947570 1 0.000 0.998 1.000 0.000
#> SRR1947569 2 0.000 0.990 0.000 1.000
#> SRR1947566 2 0.000 0.990 0.000 1.000
#> SRR1947567 2 0.000 0.990 0.000 1.000
#> SRR1947568 2 0.000 0.990 0.000 1.000
#> SRR1947564 2 0.000 0.990 0.000 1.000
#> SRR1947563 2 0.000 0.990 0.000 1.000
#> SRR1947562 2 0.000 0.990 0.000 1.000
#> SRR1947565 2 0.000 0.990 0.000 1.000
#> SRR1947559 2 0.000 0.990 0.000 1.000
#> SRR1947560 2 0.000 0.990 0.000 1.000
#> SRR1947561 2 0.000 0.990 0.000 1.000
#> SRR1947557 1 0.000 0.998 1.000 0.000
#> SRR1947558 2 0.000 0.990 0.000 1.000
#> SRR1947556 2 0.980 0.296 0.416 0.584
#> SRR1947553 2 0.000 0.990 0.000 1.000
#> SRR1947554 1 0.000 0.998 1.000 0.000
#> SRR1947555 2 0.000 0.990 0.000 1.000
#> SRR1947550 2 0.000 0.990 0.000 1.000
#> SRR1947552 2 0.000 0.990 0.000 1.000
#> SRR1947549 2 0.000 0.990 0.000 1.000
#> SRR1947551 2 0.000 0.990 0.000 1.000
#> SRR1947548 2 0.000 0.990 0.000 1.000
#> SRR1947506 1 0.000 0.998 1.000 0.000
#> SRR1947507 1 0.000 0.998 1.000 0.000
#> SRR1947504 2 0.000 0.990 0.000 1.000
#> SRR1947503 1 0.000 0.998 1.000 0.000
#> SRR1947502 2 0.000 0.990 0.000 1.000
#> SRR1947501 2 0.000 0.990 0.000 1.000
#> SRR1947499 1 0.000 0.998 1.000 0.000
#> SRR1947498 2 0.000 0.990 0.000 1.000
#> SRR1947508 1 0.000 0.998 1.000 0.000
#> SRR1947505 2 0.000 0.990 0.000 1.000
#> SRR1947497 2 0.000 0.990 0.000 1.000
#> SRR1947496 1 0.000 0.998 1.000 0.000
#> SRR1947495 2 0.000 0.990 0.000 1.000
#> SRR1947494 2 0.000 0.990 0.000 1.000
#> SRR1947493 1 0.000 0.998 1.000 0.000
#> SRR1947492 1 0.000 0.998 1.000 0.000
#> SRR1947500 2 0.000 0.990 0.000 1.000
#> SRR1947491 1 0.000 0.998 1.000 0.000
#> SRR1947490 1 0.000 0.998 1.000 0.000
#> SRR1947489 1 0.000 0.998 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947546 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947545 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947542 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947541 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947540 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947539 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947538 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947537 3 0.6140 0.287 0.000 0.404 0.596
#> SRR1947536 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947535 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947534 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947533 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947532 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947531 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947530 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947529 3 0.5216 0.692 0.000 0.260 0.740
#> SRR1947528 3 0.4974 0.675 0.236 0.000 0.764
#> SRR1947527 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947526 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947525 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947524 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947523 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947521 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947520 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947519 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947518 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947517 3 0.6095 0.339 0.392 0.000 0.608
#> SRR1947516 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947515 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947514 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947512 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947511 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947510 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947572 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947611 3 0.4605 0.729 0.000 0.204 0.796
#> SRR1947509 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947644 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947643 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947642 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947640 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947641 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947639 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947638 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947637 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947636 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947635 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947634 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947633 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947632 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947631 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947629 2 0.4062 0.827 0.000 0.836 0.164
#> SRR1947630 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947627 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947628 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947626 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947625 3 0.0747 0.943 0.000 0.016 0.984
#> SRR1947624 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947623 3 0.1585 0.945 0.028 0.008 0.964
#> SRR1947622 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947621 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947620 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947619 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947617 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947618 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947616 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947615 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947614 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947610 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947612 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947609 3 0.1411 0.940 0.036 0.000 0.964
#> SRR1947608 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947606 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947607 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947604 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947605 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947603 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947602 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947600 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947598 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947599 3 0.1411 0.940 0.036 0.000 0.964
#> SRR1947597 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947596 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947595 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947594 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947590 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947588 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947586 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947585 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947583 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947582 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947580 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947581 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947576 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947575 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947579 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947578 3 0.4291 0.812 0.000 0.180 0.820
#> SRR1947573 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947574 3 0.1411 0.940 0.036 0.000 0.964
#> SRR1947571 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947577 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947570 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947569 2 0.4504 0.788 0.000 0.804 0.196
#> SRR1947566 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947567 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947568 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947564 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947563 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947562 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947565 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947559 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947560 3 0.1643 0.922 0.000 0.044 0.956
#> SRR1947561 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947557 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947556 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947553 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947554 1 0.3816 0.805 0.852 0.000 0.148
#> SRR1947555 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947550 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947552 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947549 2 0.1411 0.951 0.000 0.964 0.036
#> SRR1947551 2 0.4702 0.767 0.000 0.788 0.212
#> SRR1947548 3 0.3879 0.847 0.000 0.152 0.848
#> SRR1947506 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947507 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947504 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947503 3 0.6215 0.283 0.428 0.000 0.572
#> SRR1947502 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947501 2 0.0000 0.975 0.000 1.000 0.000
#> SRR1947499 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.949 0.000 0.000 1.000
#> SRR1947508 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947505 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947497 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947496 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947495 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947494 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947493 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947500 3 0.1411 0.954 0.000 0.036 0.964
#> SRR1947491 3 0.1411 0.940 0.036 0.000 0.964
#> SRR1947490 1 0.0000 0.994 1.000 0.000 0.000
#> SRR1947489 3 0.0000 0.949 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.0336 0.980 0.992 0.000 0.000 0.008
#> SRR1947546 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947545 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947544 1 0.1474 0.937 0.948 0.000 0.000 0.052
#> SRR1947542 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947541 3 0.4830 0.434 0.000 0.000 0.608 0.392
#> SRR1947540 4 0.2345 0.855 0.000 0.000 0.100 0.900
#> SRR1947539 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947538 4 0.2345 0.855 0.000 0.000 0.100 0.900
#> SRR1947537 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947536 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947535 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947534 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947533 4 0.2011 0.857 0.000 0.080 0.000 0.920
#> SRR1947532 4 0.0188 0.910 0.000 0.000 0.004 0.996
#> SRR1947531 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947530 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947529 4 0.3907 0.689 0.000 0.232 0.000 0.768
#> SRR1947528 4 0.6025 0.515 0.096 0.000 0.236 0.668
#> SRR1947527 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947526 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947525 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947524 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947523 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947521 3 0.4585 0.552 0.000 0.000 0.668 0.332
#> SRR1947520 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947519 3 0.4304 0.634 0.000 0.000 0.716 0.284
#> SRR1947518 4 0.2149 0.864 0.000 0.000 0.088 0.912
#> SRR1947517 3 0.7494 0.287 0.188 0.000 0.460 0.352
#> SRR1947516 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947515 4 0.4585 0.541 0.000 0.000 0.332 0.668
#> SRR1947514 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947513 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947511 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947510 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.0188 0.910 0.000 0.000 0.004 0.996
#> SRR1947611 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947509 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947644 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947643 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947642 3 0.3528 0.752 0.000 0.000 0.808 0.192
#> SRR1947640 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947641 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947639 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947638 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947637 2 0.1557 0.919 0.000 0.944 0.056 0.000
#> SRR1947636 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947635 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947634 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947633 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947632 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947631 3 0.2814 0.801 0.000 0.000 0.868 0.132
#> SRR1947629 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947630 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947627 1 0.2081 0.902 0.916 0.000 0.000 0.084
#> SRR1947628 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947626 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947625 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947623 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947622 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947621 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947620 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947619 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947617 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947618 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947616 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947615 3 0.2814 0.801 0.000 0.000 0.868 0.132
#> SRR1947614 3 0.4624 0.537 0.000 0.000 0.660 0.340
#> SRR1947613 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947610 4 0.1474 0.887 0.000 0.000 0.052 0.948
#> SRR1947612 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947609 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947608 3 0.4277 0.568 0.000 0.280 0.720 0.000
#> SRR1947606 4 0.4855 0.242 0.000 0.000 0.400 0.600
#> SRR1947607 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947604 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947605 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947602 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947600 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947598 4 0.3219 0.793 0.000 0.000 0.164 0.836
#> SRR1947599 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947597 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947596 4 0.1211 0.894 0.000 0.000 0.040 0.960
#> SRR1947595 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947594 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947590 4 0.4585 0.541 0.000 0.000 0.332 0.668
#> SRR1947588 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947586 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947585 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947583 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947582 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947580 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947581 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947576 2 0.4761 0.409 0.000 0.628 0.372 0.000
#> SRR1947575 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947579 3 0.2530 0.831 0.000 0.000 0.888 0.112
#> SRR1947578 4 0.4440 0.775 0.000 0.060 0.136 0.804
#> SRR1947573 2 0.4830 0.357 0.000 0.608 0.392 0.000
#> SRR1947574 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947571 4 0.2345 0.855 0.000 0.000 0.100 0.900
#> SRR1947577 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947570 1 0.0188 0.983 0.996 0.000 0.000 0.004
#> SRR1947569 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947566 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947567 4 0.2345 0.855 0.000 0.000 0.100 0.900
#> SRR1947568 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947564 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947563 2 0.2973 0.811 0.000 0.856 0.144 0.000
#> SRR1947562 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947565 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947559 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947560 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947557 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947556 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947553 4 0.1211 0.894 0.000 0.000 0.040 0.960
#> SRR1947554 1 0.4134 0.651 0.740 0.000 0.000 0.260
#> SRR1947555 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947550 4 0.1474 0.887 0.000 0.000 0.052 0.948
#> SRR1947552 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947549 2 0.1557 0.919 0.000 0.944 0.056 0.000
#> SRR1947551 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.5110 0.485 0.000 0.012 0.352 0.636
#> SRR1947506 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947507 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947504 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947503 4 0.4898 0.271 0.416 0.000 0.000 0.584
#> SRR1947502 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947501 2 0.0000 0.968 0.000 1.000 0.000 0.000
#> SRR1947499 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947498 3 0.0000 0.909 0.000 0.000 1.000 0.000
#> SRR1947508 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947505 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947497 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947496 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947495 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947494 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947493 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947492 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947491 4 0.0000 0.911 0.000 0.000 0.000 1.000
#> SRR1947490 1 0.0000 0.986 1.000 0.000 0.000 0.000
#> SRR1947489 4 0.4500 0.464 0.000 0.000 0.316 0.684
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947546 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947545 1 0.2516 0.7792 0.860 0.000 0.000 0.000 0.140
#> SRR1947544 1 0.6296 0.5919 0.528 0.000 0.000 0.272 0.200
#> SRR1947542 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947541 3 0.4171 0.1878 0.000 0.000 0.604 0.396 0.000
#> SRR1947540 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947539 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947538 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947537 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 1 0.3508 0.7588 0.748 0.000 0.000 0.000 0.252
#> SRR1947535 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 1 0.6053 0.6313 0.576 0.000 0.000 0.228 0.196
#> SRR1947533 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947532 4 0.0703 0.6788 0.000 0.000 0.000 0.976 0.024
#> SRR1947531 4 0.2230 0.7268 0.000 0.000 0.000 0.884 0.116
#> SRR1947530 1 0.1341 0.7767 0.944 0.000 0.000 0.000 0.056
#> SRR1947529 4 0.4016 0.7759 0.000 0.012 0.000 0.716 0.272
#> SRR1947528 4 0.7347 -0.1795 0.080 0.000 0.164 0.516 0.240
#> SRR1947527 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947526 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947525 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947524 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947521 5 0.6575 0.4386 0.000 0.000 0.236 0.300 0.464
#> SRR1947520 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947519 3 0.3242 0.5355 0.000 0.000 0.784 0.216 0.000
#> SRR1947518 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947517 5 0.4114 0.3589 0.000 0.000 0.016 0.272 0.712
#> SRR1947516 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947515 4 0.5446 0.6931 0.000 0.000 0.100 0.628 0.272
#> SRR1947514 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947513 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947512 1 0.2127 0.7775 0.892 0.000 0.000 0.000 0.108
#> SRR1947511 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947510 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947572 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947611 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947509 1 0.3508 0.7588 0.748 0.000 0.000 0.000 0.252
#> SRR1947644 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947643 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947642 3 0.0510 0.8183 0.000 0.000 0.984 0.016 0.000
#> SRR1947640 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947641 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947638 1 0.5887 0.6819 0.592 0.000 0.000 0.156 0.252
#> SRR1947637 2 0.2674 0.6569 0.000 0.856 0.004 0.000 0.140
#> SRR1947636 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947634 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947633 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947632 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947631 3 0.0510 0.8183 0.000 0.000 0.984 0.016 0.000
#> SRR1947629 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947627 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947628 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947626 2 0.3707 0.6689 0.000 0.716 0.000 0.000 0.284
#> SRR1947625 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 5 0.3612 0.1364 0.000 0.268 0.000 0.000 0.732
#> SRR1947623 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947622 2 0.2561 0.7473 0.000 0.856 0.000 0.000 0.144
#> SRR1947621 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947620 1 0.3508 0.7588 0.748 0.000 0.000 0.000 0.252
#> SRR1947619 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947617 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947618 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947616 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947615 3 0.0609 0.8155 0.000 0.000 0.980 0.020 0.000
#> SRR1947614 5 0.6554 0.4512 0.000 0.000 0.224 0.312 0.464
#> SRR1947613 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947612 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947609 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947608 3 0.3366 0.5328 0.000 0.232 0.768 0.000 0.000
#> SRR1947606 4 0.4182 -0.0811 0.000 0.000 0.400 0.600 0.000
#> SRR1947607 1 0.2813 0.7707 0.832 0.000 0.000 0.000 0.168
#> SRR1947604 4 0.3143 0.7661 0.000 0.000 0.000 0.796 0.204
#> SRR1947605 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947602 1 0.1732 0.7786 0.920 0.000 0.000 0.000 0.080
#> SRR1947600 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947598 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947599 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947597 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947596 4 0.3452 0.7792 0.000 0.000 0.000 0.756 0.244
#> SRR1947595 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947594 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947590 4 0.5446 0.6932 0.000 0.000 0.100 0.628 0.272
#> SRR1947588 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947586 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947585 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.2732 0.7486 0.000 0.000 0.000 0.840 0.160
#> SRR1947582 1 0.3336 0.7655 0.772 0.000 0.000 0.000 0.228
#> SRR1947580 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947581 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.5694 0.1886 0.000 0.456 0.080 0.000 0.464
#> SRR1947575 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947578 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947573 2 0.4150 0.1778 0.000 0.612 0.388 0.000 0.000
#> SRR1947574 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947571 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947577 1 0.5240 0.7209 0.656 0.000 0.000 0.092 0.252
#> SRR1947570 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947569 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947567 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947568 2 0.3707 0.6689 0.000 0.716 0.000 0.000 0.284
#> SRR1947564 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947563 2 0.3074 0.5540 0.000 0.804 0.196 0.000 0.000
#> SRR1947562 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947565 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 2 0.3636 0.6793 0.000 0.728 0.000 0.000 0.272
#> SRR1947560 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947561 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947553 4 0.3707 0.7791 0.000 0.000 0.000 0.716 0.284
#> SRR1947554 4 0.6726 -0.5442 0.360 0.000 0.000 0.388 0.252
#> SRR1947555 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947550 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947552 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947549 2 0.0162 0.8066 0.000 0.996 0.004 0.000 0.000
#> SRR1947551 3 0.4291 0.2360 0.000 0.000 0.536 0.000 0.464
#> SRR1947548 4 0.5620 0.6730 0.000 0.000 0.116 0.612 0.272
#> SRR1947506 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947507 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.0290 0.6585 0.008 0.000 0.000 0.992 0.000
#> SRR1947503 4 0.6673 -0.4580 0.316 0.000 0.000 0.432 0.252
#> SRR1947502 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947501 2 0.0000 0.8102 0.000 1.000 0.000 0.000 0.000
#> SRR1947499 1 0.1341 0.7767 0.944 0.000 0.000 0.000 0.056
#> SRR1947498 3 0.0000 0.8331 0.000 0.000 1.000 0.000 0.000
#> SRR1947508 1 0.6554 0.5883 0.476 0.000 0.000 0.272 0.252
#> SRR1947505 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947497 4 0.3636 0.7839 0.000 0.000 0.000 0.728 0.272
#> SRR1947496 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.3336 0.7749 0.000 0.000 0.000 0.772 0.228
#> SRR1947494 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947493 1 0.2179 0.7795 0.888 0.000 0.000 0.000 0.112
#> SRR1947492 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947491 4 0.0000 0.6650 0.000 0.000 0.000 1.000 0.000
#> SRR1947490 1 0.0000 0.7724 1.000 0.000 0.000 0.000 0.000
#> SRR1947489 4 0.4171 -0.0715 0.000 0.000 0.396 0.604 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 6 0.0713 0.8498 0.000 0.000 0.028 0.000 0.000 0.972
#> SRR1947546 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947545 6 0.3810 0.1068 0.428 0.000 0.000 0.000 0.000 0.572
#> SRR1947544 6 0.3377 0.6942 0.188 0.000 0.028 0.000 0.000 0.784
#> SRR1947542 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947541 3 0.3328 0.3488 0.000 0.000 0.816 0.120 0.064 0.000
#> SRR1947540 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947539 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947538 4 0.2135 0.7339 0.000 0.000 0.128 0.872 0.000 0.000
#> SRR1947537 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947536 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947535 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947534 6 0.2793 0.6857 0.200 0.000 0.000 0.000 0.000 0.800
#> SRR1947533 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947532 4 0.0865 0.8140 0.000 0.000 0.036 0.964 0.000 0.000
#> SRR1947531 4 0.3175 0.7979 0.000 0.000 0.256 0.744 0.000 0.000
#> SRR1947530 1 0.2793 0.7142 0.800 0.000 0.000 0.000 0.000 0.200
#> SRR1947529 4 0.0458 0.8025 0.000 0.016 0.000 0.984 0.000 0.000
#> SRR1947528 6 0.3584 0.5492 0.000 0.000 0.308 0.000 0.004 0.688
#> SRR1947527 4 0.3151 0.8011 0.000 0.000 0.252 0.748 0.000 0.000
#> SRR1947526 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947525 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947524 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947523 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947521 5 0.4855 0.5242 0.000 0.000 0.256 0.104 0.640 0.000
#> SRR1947520 4 0.3101 0.8020 0.000 0.000 0.244 0.756 0.000 0.000
#> SRR1947519 3 0.3830 0.8472 0.000 0.000 0.620 0.004 0.376 0.000
#> SRR1947518 4 0.2135 0.7339 0.000 0.000 0.128 0.872 0.000 0.000
#> SRR1947517 6 0.4319 0.3426 0.000 0.000 0.024 0.000 0.400 0.576
#> SRR1947516 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947515 4 0.1910 0.7240 0.000 0.000 0.000 0.892 0.108 0.000
#> SRR1947514 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947513 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947512 1 0.3684 0.3126 0.628 0.000 0.000 0.000 0.000 0.372
#> SRR1947511 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947510 5 0.0000 0.6157 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 4 0.0146 0.8106 0.000 0.000 0.004 0.996 0.000 0.000
#> SRR1947611 5 0.0000 0.6157 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947509 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947644 5 0.0000 0.6157 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947643 4 0.0146 0.8128 0.000 0.000 0.004 0.996 0.000 0.000
#> SRR1947642 3 0.3890 0.8745 0.000 0.000 0.596 0.004 0.400 0.000
#> SRR1947640 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947641 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947639 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947638 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947637 2 0.2762 0.6266 0.000 0.804 0.000 0.000 0.196 0.000
#> SRR1947636 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947635 4 0.1327 0.8197 0.000 0.000 0.064 0.936 0.000 0.000
#> SRR1947634 4 0.0260 0.8137 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947633 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947632 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947631 3 0.3890 0.8745 0.000 0.000 0.596 0.004 0.400 0.000
#> SRR1947629 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947630 4 0.3101 0.8020 0.000 0.000 0.244 0.756 0.000 0.000
#> SRR1947627 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947628 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947626 2 0.5173 0.6001 0.000 0.596 0.128 0.276 0.000 0.000
#> SRR1947625 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947624 5 0.5240 0.3602 0.000 0.136 0.000 0.276 0.588 0.000
#> SRR1947623 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947622 2 0.2340 0.7742 0.000 0.852 0.000 0.148 0.000 0.000
#> SRR1947621 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947620 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947619 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947617 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947618 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947616 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947615 3 0.3890 0.8745 0.000 0.000 0.596 0.004 0.400 0.000
#> SRR1947614 5 0.4954 0.5117 0.000 0.000 0.260 0.112 0.628 0.000
#> SRR1947613 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947610 4 0.2135 0.7339 0.000 0.000 0.128 0.872 0.000 0.000
#> SRR1947612 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947609 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947608 3 0.5309 0.5273 0.000 0.228 0.596 0.000 0.176 0.000
#> SRR1947606 3 0.3652 -0.0756 0.000 0.000 0.672 0.324 0.004 0.000
#> SRR1947607 6 0.3756 0.3278 0.400 0.000 0.000 0.000 0.000 0.600
#> SRR1947604 4 0.0865 0.8167 0.000 0.000 0.036 0.964 0.000 0.000
#> SRR1947605 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947603 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947602 1 0.3563 0.5100 0.664 0.000 0.000 0.000 0.000 0.336
#> SRR1947600 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947601 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947599 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947597 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947596 4 0.0260 0.8125 0.000 0.000 0.008 0.992 0.000 0.000
#> SRR1947595 4 0.3101 0.8020 0.000 0.000 0.244 0.756 0.000 0.000
#> SRR1947594 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947591 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947590 4 0.1910 0.7242 0.000 0.000 0.000 0.892 0.108 0.000
#> SRR1947588 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947586 4 0.3684 0.7389 0.000 0.000 0.372 0.628 0.000 0.000
#> SRR1947585 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947584 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947583 4 0.3151 0.7994 0.000 0.000 0.252 0.748 0.000 0.000
#> SRR1947582 6 0.3151 0.5702 0.252 0.000 0.000 0.000 0.000 0.748
#> SRR1947580 4 0.2135 0.7339 0.000 0.000 0.128 0.872 0.000 0.000
#> SRR1947581 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.3756 0.2921 0.000 0.400 0.000 0.000 0.600 0.000
#> SRR1947575 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947579 5 0.2664 0.6122 0.000 0.000 0.184 0.000 0.816 0.000
#> SRR1947578 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947573 2 0.3852 0.2608 0.000 0.612 0.384 0.000 0.004 0.000
#> SRR1947574 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947571 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947577 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947570 6 0.0713 0.8498 0.000 0.000 0.028 0.000 0.000 0.972
#> SRR1947569 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947566 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947567 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947568 2 0.5173 0.6001 0.000 0.596 0.128 0.276 0.000 0.000
#> SRR1947564 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947563 2 0.2762 0.6092 0.000 0.804 0.196 0.000 0.000 0.000
#> SRR1947562 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947565 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947559 2 0.3288 0.7144 0.000 0.724 0.000 0.276 0.000 0.000
#> SRR1947560 5 0.0000 0.6157 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947558 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947556 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947553 4 0.2135 0.7339 0.000 0.000 0.128 0.872 0.000 0.000
#> SRR1947554 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947555 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947550 4 0.0000 0.8116 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1947552 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947549 2 0.0146 0.8247 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1947551 5 0.0000 0.6157 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.2092 0.7040 0.000 0.000 0.000 0.876 0.124 0.000
#> SRR1947506 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947507 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.3819 0.7757 0.020 0.000 0.280 0.700 0.000 0.000
#> SRR1947503 6 0.0790 0.8475 0.000 0.000 0.032 0.000 0.000 0.968
#> SRR1947502 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947501 2 0.0000 0.8278 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947499 1 0.2793 0.7142 0.800 0.000 0.000 0.000 0.000 0.200
#> SRR1947498 3 0.3765 0.8787 0.000 0.000 0.596 0.000 0.404 0.000
#> SRR1947508 6 0.0000 0.8620 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1947505 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947497 4 0.3101 0.8020 0.000 0.000 0.244 0.756 0.000 0.000
#> SRR1947496 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947495 4 0.3101 0.8020 0.000 0.000 0.244 0.756 0.000 0.000
#> SRR1947494 4 0.2178 0.8155 0.000 0.000 0.132 0.868 0.000 0.000
#> SRR1947493 1 0.3864 0.1379 0.520 0.000 0.000 0.000 0.000 0.480
#> SRR1947492 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947500 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947491 4 0.3288 0.7899 0.000 0.000 0.276 0.724 0.000 0.000
#> SRR1947490 1 0.0000 0.8752 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.3531 -0.0864 0.000 0.000 0.672 0.328 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 15148 rows and 152 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 0.969 0.987 0.4477 0.556 0.556
#> 3 3 0.634 0.748 0.861 0.3896 0.809 0.657
#> 4 4 0.583 0.720 0.796 0.0485 0.921 0.801
#> 5 5 0.721 0.803 0.843 0.1635 0.859 0.605
#> 6 6 0.847 0.853 0.908 0.0706 0.909 0.637
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
#> SRR1947547 2 0.0376 0.990 0.004 0.996
#> SRR1947546 1 0.0000 0.986 1.000 0.000
#> SRR1947545 1 0.0376 0.984 0.996 0.004
#> SRR1947544 1 0.0376 0.984 0.996 0.004
#> SRR1947542 1 0.0000 0.986 1.000 0.000
#> SRR1947541 2 0.0376 0.990 0.004 0.996
#> SRR1947540 1 0.0000 0.986 1.000 0.000
#> SRR1947539 2 0.0376 0.990 0.004 0.996
#> SRR1947538 1 0.0000 0.986 1.000 0.000
#> SRR1947537 2 0.0376 0.990 0.004 0.996
#> SRR1947536 2 0.0000 0.986 0.000 1.000
#> SRR1947535 2 0.0376 0.990 0.004 0.996
#> SRR1947534 1 0.0376 0.984 0.996 0.004
#> SRR1947533 1 0.0000 0.986 1.000 0.000
#> SRR1947532 1 0.0000 0.986 1.000 0.000
#> SRR1947531 1 0.0000 0.986 1.000 0.000
#> SRR1947530 1 0.9732 0.324 0.596 0.404
#> SRR1947529 1 0.0000 0.986 1.000 0.000
#> SRR1947528 2 0.0376 0.990 0.004 0.996
#> SRR1947527 1 0.0000 0.986 1.000 0.000
#> SRR1947526 1 0.0000 0.986 1.000 0.000
#> SRR1947525 1 0.0000 0.986 1.000 0.000
#> SRR1947524 2 0.0376 0.990 0.004 0.996
#> SRR1947523 1 0.0000 0.986 1.000 0.000
#> SRR1947521 2 0.0376 0.990 0.004 0.996
#> SRR1947520 1 0.0000 0.986 1.000 0.000
#> SRR1947519 2 0.0376 0.990 0.004 0.996
#> SRR1947518 1 0.0000 0.986 1.000 0.000
#> SRR1947517 2 0.0376 0.990 0.004 0.996
#> SRR1947516 1 0.0000 0.986 1.000 0.000
#> SRR1947515 1 0.0000 0.986 1.000 0.000
#> SRR1947514 1 0.0000 0.986 1.000 0.000
#> SRR1947513 1 0.0376 0.984 0.996 0.004
#> SRR1947512 1 0.0376 0.984 0.996 0.004
#> SRR1947511 1 0.0000 0.986 1.000 0.000
#> SRR1947510 2 0.0376 0.990 0.004 0.996
#> SRR1947572 1 0.0000 0.986 1.000 0.000
#> SRR1947611 2 0.0376 0.990 0.004 0.996
#> SRR1947509 2 0.0000 0.986 0.000 1.000
#> SRR1947644 2 0.0376 0.990 0.004 0.996
#> SRR1947643 1 0.0000 0.986 1.000 0.000
#> SRR1947642 2 0.0376 0.990 0.004 0.996
#> SRR1947640 1 0.0000 0.986 1.000 0.000
#> SRR1947641 2 0.0376 0.990 0.004 0.996
#> SRR1947639 1 0.0000 0.986 1.000 0.000
#> SRR1947638 1 0.0376 0.984 0.996 0.004
#> SRR1947637 2 0.0376 0.990 0.004 0.996
#> SRR1947636 2 0.0376 0.990 0.004 0.996
#> SRR1947635 1 0.0000 0.986 1.000 0.000
#> SRR1947634 1 0.0000 0.986 1.000 0.000
#> SRR1947633 2 0.0376 0.990 0.004 0.996
#> SRR1947632 1 0.0000 0.986 1.000 0.000
#> SRR1947631 2 0.0376 0.990 0.004 0.996
#> SRR1947629 2 0.0376 0.990 0.004 0.996
#> SRR1947630 1 0.0000 0.986 1.000 0.000
#> SRR1947627 2 0.0376 0.990 0.004 0.996
#> SRR1947628 1 0.0000 0.986 1.000 0.000
#> SRR1947626 1 0.0000 0.986 1.000 0.000
#> SRR1947625 2 0.0376 0.990 0.004 0.996
#> SRR1947624 1 0.0000 0.986 1.000 0.000
#> SRR1947623 1 0.0000 0.986 1.000 0.000
#> SRR1947622 1 0.0000 0.986 1.000 0.000
#> SRR1947621 1 0.0000 0.986 1.000 0.000
#> SRR1947620 1 0.0376 0.984 0.996 0.004
#> SRR1947619 2 0.2603 0.951 0.044 0.956
#> SRR1947617 1 0.0000 0.986 1.000 0.000
#> SRR1947618 1 0.0376 0.984 0.996 0.004
#> SRR1947616 1 0.0000 0.986 1.000 0.000
#> SRR1947615 2 0.8813 0.573 0.300 0.700
#> SRR1947614 2 0.0376 0.990 0.004 0.996
#> SRR1947613 1 0.0376 0.984 0.996 0.004
#> SRR1947610 1 0.0000 0.986 1.000 0.000
#> SRR1947612 1 0.0000 0.986 1.000 0.000
#> SRR1947609 1 0.0000 0.986 1.000 0.000
#> SRR1947608 2 0.0376 0.990 0.004 0.996
#> SRR1947606 2 0.0376 0.990 0.004 0.996
#> SRR1947607 1 0.0376 0.984 0.996 0.004
#> SRR1947604 1 0.0000 0.986 1.000 0.000
#> SRR1947605 1 0.0376 0.984 0.996 0.004
#> SRR1947603 1 0.0000 0.986 1.000 0.000
#> SRR1947602 1 0.9850 0.256 0.572 0.428
#> SRR1947600 2 0.0376 0.990 0.004 0.996
#> SRR1947601 1 0.0000 0.986 1.000 0.000
#> SRR1947598 1 0.0000 0.986 1.000 0.000
#> SRR1947599 1 0.0000 0.986 1.000 0.000
#> SRR1947597 1 0.0000 0.986 1.000 0.000
#> SRR1947596 1 0.0000 0.986 1.000 0.000
#> SRR1947595 1 0.0000 0.986 1.000 0.000
#> SRR1947594 1 0.0376 0.984 0.996 0.004
#> SRR1947592 2 0.0376 0.990 0.004 0.996
#> SRR1947591 1 0.0000 0.986 1.000 0.000
#> SRR1947590 1 0.0000 0.986 1.000 0.000
#> SRR1947588 1 0.0376 0.984 0.996 0.004
#> SRR1947587 2 0.0376 0.990 0.004 0.996
#> SRR1947586 1 0.0000 0.986 1.000 0.000
#> SRR1947585 2 0.0376 0.990 0.004 0.996
#> SRR1947584 1 0.0376 0.984 0.996 0.004
#> SRR1947583 1 0.0000 0.986 1.000 0.000
#> SRR1947582 1 0.0376 0.984 0.996 0.004
#> SRR1947580 1 0.0000 0.986 1.000 0.000
#> SRR1947581 1 0.0376 0.984 0.996 0.004
#> SRR1947576 2 0.0376 0.990 0.004 0.996
#> SRR1947575 2 0.0376 0.990 0.004 0.996
#> SRR1947579 2 0.0376 0.990 0.004 0.996
#> SRR1947578 1 0.0000 0.986 1.000 0.000
#> SRR1947573 2 0.0376 0.990 0.004 0.996
#> SRR1947574 1 0.0000 0.986 1.000 0.000
#> SRR1947571 1 0.0000 0.986 1.000 0.000
#> SRR1947577 1 0.0376 0.984 0.996 0.004
#> SRR1947570 2 0.0376 0.990 0.004 0.996
#> SRR1947569 2 0.0376 0.990 0.004 0.996
#> SRR1947566 1 0.0000 0.986 1.000 0.000
#> SRR1947567 1 0.0000 0.986 1.000 0.000
#> SRR1947568 1 0.0000 0.986 1.000 0.000
#> SRR1947564 1 0.0000 0.986 1.000 0.000
#> SRR1947563 2 0.0376 0.990 0.004 0.996
#> SRR1947562 1 0.0000 0.986 1.000 0.000
#> SRR1947565 2 0.0376 0.990 0.004 0.996
#> SRR1947559 1 0.0000 0.986 1.000 0.000
#> SRR1947560 2 0.0376 0.990 0.004 0.996
#> SRR1947561 1 0.0000 0.986 1.000 0.000
#> SRR1947557 1 0.0376 0.984 0.996 0.004
#> SRR1947558 2 0.0376 0.990 0.004 0.996
#> SRR1947556 1 0.0000 0.986 1.000 0.000
#> SRR1947553 1 0.0000 0.986 1.000 0.000
#> SRR1947554 1 0.0000 0.986 1.000 0.000
#> SRR1947555 1 0.0000 0.986 1.000 0.000
#> SRR1947550 1 0.0000 0.986 1.000 0.000
#> SRR1947552 1 0.0000 0.986 1.000 0.000
#> SRR1947549 2 0.0376 0.990 0.004 0.996
#> SRR1947551 2 0.0376 0.990 0.004 0.996
#> SRR1947548 1 0.0000 0.986 1.000 0.000
#> SRR1947506 2 0.0000 0.986 0.000 1.000
#> SRR1947507 1 0.0376 0.984 0.996 0.004
#> SRR1947504 1 0.0000 0.986 1.000 0.000
#> SRR1947503 1 0.0000 0.986 1.000 0.000
#> SRR1947502 1 0.0000 0.986 1.000 0.000
#> SRR1947501 1 0.0000 0.986 1.000 0.000
#> SRR1947499 1 0.9850 0.256 0.572 0.428
#> SRR1947498 2 0.0376 0.990 0.004 0.996
#> SRR1947508 2 0.0000 0.986 0.000 1.000
#> SRR1947505 1 0.0000 0.986 1.000 0.000
#> SRR1947497 1 0.0000 0.986 1.000 0.000
#> SRR1947496 1 0.0376 0.984 0.996 0.004
#> SRR1947495 1 0.0000 0.986 1.000 0.000
#> SRR1947494 1 0.0000 0.986 1.000 0.000
#> SRR1947493 2 0.6048 0.823 0.148 0.852
#> SRR1947492 1 0.0376 0.984 0.996 0.004
#> SRR1947500 1 0.0000 0.986 1.000 0.000
#> SRR1947491 1 0.0000 0.986 1.000 0.000
#> SRR1947490 1 0.0376 0.984 0.996 0.004
#> SRR1947489 2 0.0376 0.990 0.004 0.996
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947546 2 0.1989 0.8062 0.048 0.948 0.004
#> SRR1947545 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947544 1 0.4291 0.8734 0.820 0.180 0.000
#> SRR1947542 2 0.2860 0.7912 0.084 0.912 0.004
#> SRR1947541 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947540 2 0.3918 0.7535 0.140 0.856 0.004
#> SRR1947539 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947538 2 0.6421 0.1985 0.424 0.572 0.004
#> SRR1947537 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947536 3 0.4291 0.8780 0.180 0.000 0.820
#> SRR1947535 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947534 2 0.5948 0.1726 0.360 0.640 0.000
#> SRR1947533 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947532 2 0.6495 0.0656 0.460 0.536 0.004
#> SRR1947531 2 0.3983 0.7503 0.144 0.852 0.004
#> SRR1947530 1 0.5746 0.6926 0.780 0.040 0.180
#> SRR1947529 2 0.1765 0.8074 0.040 0.956 0.004
#> SRR1947528 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947527 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947526 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947525 2 0.2496 0.7990 0.068 0.928 0.004
#> SRR1947524 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947523 2 0.6505 0.0288 0.468 0.528 0.004
#> SRR1947521 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947520 2 0.1647 0.8075 0.036 0.960 0.004
#> SRR1947519 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947518 2 0.0661 0.8092 0.008 0.988 0.004
#> SRR1947517 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947516 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947515 2 0.6451 0.1624 0.436 0.560 0.004
#> SRR1947514 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947513 1 0.4504 0.8656 0.804 0.196 0.000
#> SRR1947512 1 0.4399 0.8695 0.812 0.188 0.000
#> SRR1947511 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947510 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947572 2 0.0661 0.8091 0.008 0.988 0.004
#> SRR1947611 3 0.4062 0.8851 0.164 0.000 0.836
#> SRR1947509 3 0.4291 0.8780 0.180 0.000 0.820
#> SRR1947644 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947643 2 0.2096 0.8048 0.052 0.944 0.004
#> SRR1947642 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947640 2 0.3851 0.7571 0.136 0.860 0.004
#> SRR1947641 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947639 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947638 1 0.4291 0.8734 0.820 0.180 0.000
#> SRR1947637 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947636 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947635 2 0.6442 0.1759 0.432 0.564 0.004
#> SRR1947634 2 0.1989 0.8060 0.048 0.948 0.004
#> SRR1947633 3 0.3879 0.8898 0.152 0.000 0.848
#> SRR1947632 2 0.3851 0.7570 0.136 0.860 0.004
#> SRR1947631 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947630 2 0.1647 0.8075 0.036 0.960 0.004
#> SRR1947627 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947628 2 0.5845 0.5005 0.308 0.688 0.004
#> SRR1947626 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947625 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947624 2 0.1647 0.8075 0.036 0.960 0.004
#> SRR1947623 2 0.0661 0.8093 0.008 0.988 0.004
#> SRR1947622 2 0.1878 0.8069 0.044 0.952 0.004
#> SRR1947621 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947620 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947619 3 0.6317 0.6788 0.124 0.104 0.772
#> SRR1947617 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947618 1 0.4291 0.8734 0.820 0.180 0.000
#> SRR1947616 2 0.2945 0.7891 0.088 0.908 0.004
#> SRR1947615 3 0.7610 0.1412 0.388 0.048 0.564
#> SRR1947614 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947613 1 0.4842 0.8341 0.776 0.224 0.000
#> SRR1947610 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947612 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947609 1 0.6209 0.5505 0.628 0.368 0.004
#> SRR1947608 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947606 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947607 2 0.5968 0.1570 0.364 0.636 0.000
#> SRR1947604 2 0.6451 0.1624 0.436 0.560 0.004
#> SRR1947605 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947603 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947602 1 0.5689 0.6886 0.780 0.036 0.184
#> SRR1947600 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947601 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947598 2 0.6897 0.1397 0.436 0.548 0.016
#> SRR1947599 1 0.5956 0.6517 0.672 0.324 0.004
#> SRR1947597 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947596 2 0.6451 0.1624 0.436 0.560 0.004
#> SRR1947595 2 0.2200 0.8036 0.056 0.940 0.004
#> SRR1947594 1 0.4291 0.8734 0.820 0.180 0.000
#> SRR1947592 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947591 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947590 2 0.6483 0.0997 0.452 0.544 0.004
#> SRR1947588 1 0.4555 0.8594 0.800 0.200 0.000
#> SRR1947587 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947586 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947585 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947584 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947583 2 0.3715 0.7632 0.128 0.868 0.004
#> SRR1947582 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947580 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947581 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947576 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947575 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947579 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947578 2 0.3983 0.7498 0.144 0.852 0.004
#> SRR1947573 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947574 2 0.2096 0.8050 0.052 0.944 0.004
#> SRR1947571 2 0.6451 0.1624 0.436 0.560 0.004
#> SRR1947577 1 0.4291 0.8734 0.820 0.180 0.000
#> SRR1947570 3 0.1182 0.9280 0.012 0.012 0.976
#> SRR1947569 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947566 2 0.1860 0.8055 0.052 0.948 0.000
#> SRR1947567 2 0.3425 0.7745 0.112 0.884 0.004
#> SRR1947568 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947564 2 0.0237 0.8080 0.004 0.996 0.000
#> SRR1947563 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947562 2 0.5517 0.5742 0.268 0.728 0.004
#> SRR1947565 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947559 2 0.0661 0.8092 0.008 0.988 0.004
#> SRR1947560 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947561 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947557 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947558 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947556 1 0.6520 0.1214 0.508 0.488 0.004
#> SRR1947553 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947554 2 0.6180 0.0755 0.416 0.584 0.000
#> SRR1947555 2 0.1647 0.8075 0.036 0.960 0.004
#> SRR1947550 2 0.3272 0.7796 0.104 0.892 0.004
#> SRR1947552 2 0.6520 -0.0692 0.488 0.508 0.004
#> SRR1947549 3 0.0000 0.9433 0.000 0.000 1.000
#> SRR1947551 3 0.4235 0.8801 0.176 0.000 0.824
#> SRR1947548 2 0.6451 0.1624 0.436 0.560 0.004
#> SRR1947506 3 0.0237 0.9404 0.004 0.000 0.996
#> SRR1947507 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947504 2 0.6228 0.2630 0.372 0.624 0.004
#> SRR1947503 1 0.4629 0.8637 0.808 0.188 0.004
#> SRR1947502 2 0.0000 0.8068 0.000 1.000 0.000
#> SRR1947501 2 0.3983 0.7497 0.144 0.852 0.004
#> SRR1947499 1 0.5689 0.6886 0.780 0.036 0.184
#> SRR1947498 3 0.3412 0.9006 0.124 0.000 0.876
#> SRR1947508 3 0.0237 0.9404 0.004 0.000 0.996
#> SRR1947505 1 0.7490 0.4759 0.576 0.380 0.044
#> SRR1947497 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947496 1 0.4399 0.8693 0.812 0.188 0.000
#> SRR1947495 2 0.0237 0.8082 0.000 0.996 0.004
#> SRR1947494 2 0.6500 0.0476 0.464 0.532 0.004
#> SRR1947493 1 0.5953 0.5390 0.708 0.012 0.280
#> SRR1947492 1 0.4235 0.8745 0.824 0.176 0.000
#> SRR1947500 2 0.4172 0.7376 0.156 0.840 0.004
#> SRR1947491 1 0.6298 0.4956 0.608 0.388 0.004
#> SRR1947490 1 0.4702 0.8474 0.788 0.212 0.000
#> SRR1947489 3 0.0000 0.9433 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 3 0.3933 0.7437 0.196 0.004 0.796 0.004
#> SRR1947546 2 0.1389 0.7596 0.000 0.952 0.000 0.048
#> SRR1947545 1 0.4222 0.8404 0.728 0.272 0.000 0.000
#> SRR1947544 1 0.6113 0.7486 0.636 0.284 0.000 0.080
#> SRR1947542 2 0.5376 0.6867 0.088 0.736 0.000 0.176
#> SRR1947541 3 0.0188 0.8745 0.000 0.000 0.996 0.004
#> SRR1947540 2 0.5811 0.6625 0.116 0.704 0.000 0.180
#> SRR1947539 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947538 2 0.5811 0.6625 0.116 0.704 0.000 0.180
#> SRR1947537 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947536 4 0.4643 0.8012 0.000 0.000 0.344 0.656
#> SRR1947535 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947534 2 0.5693 -0.5042 0.472 0.504 0.000 0.024
#> SRR1947533 2 0.1474 0.7429 0.000 0.948 0.000 0.052
#> SRR1947532 2 0.6536 0.6334 0.164 0.652 0.004 0.180
#> SRR1947531 2 0.3441 0.7413 0.024 0.856 0.000 0.120
#> SRR1947530 1 0.4203 0.4905 0.824 0.068 0.108 0.000
#> SRR1947529 2 0.1716 0.7586 0.000 0.936 0.000 0.064
#> SRR1947528 3 0.3052 0.7923 0.136 0.000 0.860 0.004
#> SRR1947527 2 0.1661 0.7409 0.004 0.944 0.000 0.052
#> SRR1947526 2 0.1118 0.7483 0.000 0.964 0.000 0.036
#> SRR1947525 2 0.2216 0.7551 0.000 0.908 0.000 0.092
#> SRR1947524 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947523 2 0.6476 0.6212 0.176 0.644 0.000 0.180
#> SRR1947521 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947520 2 0.0469 0.7483 0.000 0.988 0.000 0.012
#> SRR1947519 3 0.0188 0.8745 0.000 0.000 0.996 0.004
#> SRR1947518 2 0.3354 0.7405 0.044 0.872 0.000 0.084
#> SRR1947517 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947516 2 0.1913 0.7367 0.020 0.940 0.000 0.040
#> SRR1947515 2 0.7064 0.6172 0.160 0.636 0.024 0.180
#> SRR1947514 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947513 1 0.4500 0.8350 0.684 0.316 0.000 0.000
#> SRR1947512 1 0.4454 0.8414 0.692 0.308 0.000 0.000
#> SRR1947511 2 0.1474 0.7429 0.000 0.948 0.000 0.052
#> SRR1947510 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947572 2 0.2125 0.7554 0.004 0.920 0.000 0.076
#> SRR1947611 3 0.4916 -0.0545 0.000 0.000 0.576 0.424
#> SRR1947509 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947644 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947643 2 0.1867 0.7579 0.000 0.928 0.000 0.072
#> SRR1947642 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947640 2 0.5512 0.6808 0.100 0.728 0.000 0.172
#> SRR1947641 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947639 2 0.1398 0.7454 0.004 0.956 0.000 0.040
#> SRR1947638 1 0.4193 0.8417 0.732 0.268 0.000 0.000
#> SRR1947637 3 0.2011 0.7891 0.000 0.000 0.920 0.080
#> SRR1947636 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947635 2 0.6279 0.6454 0.156 0.664 0.000 0.180
#> SRR1947634 2 0.1557 0.7589 0.000 0.944 0.000 0.056
#> SRR1947633 3 0.3688 0.6532 0.000 0.000 0.792 0.208
#> SRR1947632 2 0.6236 0.6498 0.152 0.668 0.000 0.180
#> SRR1947631 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947629 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947630 2 0.0707 0.7512 0.000 0.980 0.000 0.020
#> SRR1947627 3 0.3933 0.7437 0.196 0.004 0.796 0.004
#> SRR1947628 2 0.6236 0.6498 0.152 0.668 0.000 0.180
#> SRR1947626 2 0.2908 0.7007 0.064 0.896 0.000 0.040
#> SRR1947625 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947624 2 0.0469 0.7483 0.000 0.988 0.000 0.012
#> SRR1947623 2 0.1474 0.7599 0.000 0.948 0.000 0.052
#> SRR1947622 2 0.1211 0.7585 0.000 0.960 0.000 0.040
#> SRR1947621 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947620 1 0.4193 0.8417 0.732 0.268 0.000 0.000
#> SRR1947619 3 0.6369 0.2988 0.004 0.260 0.640 0.096
#> SRR1947617 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947618 1 0.4222 0.8404 0.728 0.272 0.000 0.000
#> SRR1947616 2 0.2466 0.7531 0.004 0.900 0.000 0.096
#> SRR1947615 3 0.8185 0.3419 0.184 0.140 0.576 0.100
#> SRR1947614 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947613 1 0.4855 0.7216 0.600 0.400 0.000 0.000
#> SRR1947610 2 0.1398 0.7454 0.004 0.956 0.000 0.040
#> SRR1947612 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947609 2 0.7463 0.0703 0.364 0.456 0.000 0.180
#> SRR1947608 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947606 3 0.3933 0.7437 0.196 0.004 0.796 0.004
#> SRR1947607 1 0.5856 0.5484 0.504 0.464 0.000 0.032
#> SRR1947604 2 0.6279 0.6454 0.156 0.664 0.000 0.180
#> SRR1947605 1 0.4193 0.8417 0.732 0.268 0.000 0.000
#> SRR1947603 2 0.0188 0.7520 0.000 0.996 0.000 0.004
#> SRR1947602 1 0.4203 0.4905 0.824 0.068 0.108 0.000
#> SRR1947600 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947601 2 0.1118 0.7482 0.000 0.964 0.000 0.036
#> SRR1947598 2 0.7156 0.6121 0.160 0.632 0.028 0.180
#> SRR1947599 1 0.7285 0.5380 0.520 0.300 0.000 0.180
#> SRR1947597 2 0.0000 0.7506 0.000 1.000 0.000 0.000
#> SRR1947596 2 0.6496 0.6384 0.160 0.656 0.004 0.180
#> SRR1947595 2 0.1940 0.7574 0.000 0.924 0.000 0.076
#> SRR1947594 1 0.4454 0.8414 0.692 0.308 0.000 0.000
#> SRR1947592 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947591 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947590 2 0.6966 0.6219 0.160 0.640 0.020 0.180
#> SRR1947588 1 0.4477 0.8385 0.688 0.312 0.000 0.000
#> SRR1947587 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947586 2 0.1661 0.7409 0.004 0.944 0.000 0.052
#> SRR1947585 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947584 1 0.4250 0.8402 0.724 0.276 0.000 0.000
#> SRR1947583 2 0.3910 0.7286 0.024 0.820 0.000 0.156
#> SRR1947582 1 0.4193 0.8417 0.732 0.268 0.000 0.000
#> SRR1947580 2 0.1474 0.7429 0.000 0.948 0.000 0.052
#> SRR1947581 1 0.4454 0.8414 0.692 0.308 0.000 0.000
#> SRR1947576 4 0.4008 0.9675 0.000 0.000 0.244 0.756
#> SRR1947575 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947579 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947578 2 0.6236 0.6498 0.152 0.668 0.000 0.180
#> SRR1947573 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947574 2 0.1302 0.7595 0.000 0.956 0.000 0.044
#> SRR1947571 2 0.6279 0.6454 0.156 0.664 0.000 0.180
#> SRR1947577 1 0.4193 0.8417 0.732 0.268 0.000 0.000
#> SRR1947570 3 0.4666 0.7078 0.200 0.028 0.768 0.004
#> SRR1947569 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947566 2 0.1637 0.7593 0.000 0.940 0.000 0.060
#> SRR1947567 2 0.5811 0.6625 0.116 0.704 0.000 0.180
#> SRR1947568 2 0.1398 0.7454 0.004 0.956 0.000 0.040
#> SRR1947564 2 0.1118 0.7482 0.000 0.964 0.000 0.036
#> SRR1947563 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947562 2 0.5811 0.6625 0.116 0.704 0.000 0.180
#> SRR1947565 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947559 2 0.0000 0.7506 0.000 1.000 0.000 0.000
#> SRR1947560 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947561 2 0.1211 0.7466 0.000 0.960 0.000 0.040
#> SRR1947557 1 0.4382 0.8435 0.704 0.296 0.000 0.000
#> SRR1947558 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947556 2 0.7174 0.4820 0.244 0.572 0.004 0.180
#> SRR1947553 2 0.1398 0.7454 0.004 0.956 0.000 0.040
#> SRR1947554 2 0.4985 -0.4966 0.468 0.532 0.000 0.000
#> SRR1947555 2 0.1211 0.7581 0.000 0.960 0.000 0.040
#> SRR1947550 2 0.5705 0.6696 0.108 0.712 0.000 0.180
#> SRR1947552 2 0.7014 0.5371 0.220 0.596 0.004 0.180
#> SRR1947549 3 0.0000 0.8767 0.000 0.000 1.000 0.000
#> SRR1947551 4 0.3907 0.9811 0.000 0.000 0.232 0.768
#> SRR1947548 2 0.6496 0.6384 0.160 0.656 0.004 0.180
#> SRR1947506 3 0.3933 0.7437 0.196 0.004 0.796 0.004
#> SRR1947507 1 0.4431 0.8422 0.696 0.304 0.000 0.000
#> SRR1947504 2 0.5604 0.6744 0.116 0.724 0.000 0.160
#> SRR1947503 1 0.6444 0.7117 0.612 0.284 0.000 0.104
#> SRR1947502 2 0.2983 0.6970 0.068 0.892 0.000 0.040
#> SRR1947501 2 0.6236 0.6498 0.152 0.668 0.000 0.180
#> SRR1947499 1 0.4203 0.4905 0.824 0.068 0.108 0.000
#> SRR1947498 3 0.3764 0.6387 0.000 0.000 0.784 0.216
#> SRR1947508 3 0.3933 0.7437 0.196 0.004 0.796 0.004
#> SRR1947505 2 0.9726 -0.0451 0.236 0.368 0.216 0.180
#> SRR1947497 2 0.0592 0.7471 0.000 0.984 0.000 0.016
#> SRR1947496 1 0.4454 0.8414 0.692 0.308 0.000 0.000
#> SRR1947495 2 0.0921 0.7469 0.000 0.972 0.000 0.028
#> SRR1947494 2 0.6752 0.6307 0.160 0.648 0.012 0.180
#> SRR1947493 1 0.5459 0.3456 0.732 0.072 0.192 0.004
#> SRR1947492 1 0.4454 0.8414 0.692 0.308 0.000 0.000
#> SRR1947500 2 0.5823 0.6618 0.120 0.704 0.000 0.176
#> SRR1947491 2 0.7441 0.1190 0.352 0.468 0.000 0.180
#> SRR1947490 1 0.4730 0.7777 0.636 0.364 0.000 0.000
#> SRR1947489 3 0.3973 0.7396 0.200 0.004 0.792 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947546 2 0.4832 0.8001 0.104 0.720 0.000 0.176 0.000
#> SRR1947545 1 0.4668 0.6572 0.684 0.044 0.000 0.272 0.000
#> SRR1947544 4 0.5142 0.1431 0.392 0.044 0.000 0.564 0.000
#> SRR1947542 4 0.3691 0.7544 0.104 0.076 0.000 0.820 0.000
#> SRR1947541 3 0.1205 0.9605 0.000 0.000 0.956 0.040 0.004
#> SRR1947540 2 0.5785 0.5967 0.108 0.560 0.000 0.332 0.000
#> SRR1947539 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947538 4 0.3307 0.7685 0.104 0.052 0.000 0.844 0.000
#> SRR1947537 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947536 5 0.3003 0.8055 0.000 0.000 0.188 0.000 0.812
#> SRR1947535 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947534 2 0.4451 -0.3775 0.492 0.504 0.000 0.000 0.004
#> SRR1947533 2 0.0960 0.7731 0.016 0.972 0.000 0.008 0.004
#> SRR1947532 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947531 2 0.4981 0.7965 0.108 0.704 0.000 0.188 0.000
#> SRR1947530 1 0.3911 0.6942 0.796 0.000 0.144 0.060 0.000
#> SRR1947529 2 0.4648 0.8140 0.104 0.740 0.000 0.156 0.000
#> SRR1947528 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947527 2 0.1074 0.7753 0.016 0.968 0.000 0.012 0.004
#> SRR1947526 2 0.0912 0.7767 0.016 0.972 0.000 0.012 0.000
#> SRR1947525 2 0.5825 0.5331 0.104 0.536 0.000 0.360 0.000
#> SRR1947524 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947523 4 0.1522 0.8409 0.012 0.044 0.000 0.944 0.000
#> SRR1947521 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947520 2 0.2783 0.7894 0.116 0.868 0.000 0.012 0.004
#> SRR1947519 3 0.0162 0.9743 0.000 0.000 0.996 0.000 0.004
#> SRR1947518 4 0.5532 0.3562 0.104 0.280 0.000 0.616 0.000
#> SRR1947517 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947516 2 0.3339 0.8183 0.000 0.836 0.000 0.124 0.040
#> SRR1947515 4 0.1569 0.8421 0.004 0.044 0.008 0.944 0.000
#> SRR1947514 2 0.2563 0.8206 0.000 0.872 0.000 0.120 0.008
#> SRR1947513 1 0.2408 0.7935 0.892 0.092 0.000 0.016 0.000
#> SRR1947512 1 0.2408 0.7935 0.892 0.092 0.000 0.016 0.000
#> SRR1947511 2 0.0960 0.7731 0.016 0.972 0.000 0.008 0.004
#> SRR1947510 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947572 4 0.5861 -0.0374 0.104 0.376 0.000 0.520 0.000
#> SRR1947611 5 0.1732 0.9488 0.000 0.000 0.080 0.000 0.920
#> SRR1947509 5 0.1121 0.9749 0.000 0.000 0.044 0.000 0.956
#> SRR1947644 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947643 2 0.3670 0.8164 0.112 0.820 0.000 0.068 0.000
#> SRR1947642 3 0.0162 0.9743 0.000 0.000 0.996 0.000 0.004
#> SRR1947640 2 0.5010 0.8039 0.144 0.708 0.000 0.148 0.000
#> SRR1947641 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947639 2 0.4785 0.8193 0.104 0.752 0.000 0.132 0.012
#> SRR1947638 1 0.4521 0.7621 0.748 0.088 0.000 0.164 0.000
#> SRR1947637 3 0.2561 0.8108 0.000 0.000 0.856 0.000 0.144
#> SRR1947636 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947635 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947634 2 0.2574 0.7939 0.112 0.876 0.000 0.012 0.000
#> SRR1947633 3 0.1270 0.9458 0.000 0.000 0.948 0.000 0.052
#> SRR1947632 4 0.1410 0.8376 0.000 0.060 0.000 0.940 0.000
#> SRR1947631 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947629 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947630 2 0.2833 0.7887 0.120 0.864 0.000 0.012 0.004
#> SRR1947627 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947628 4 0.1341 0.8396 0.000 0.056 0.000 0.944 0.000
#> SRR1947626 2 0.2439 0.8208 0.000 0.876 0.000 0.120 0.004
#> SRR1947625 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947624 2 0.2575 0.7906 0.100 0.884 0.000 0.012 0.004
#> SRR1947623 2 0.4365 0.8232 0.116 0.768 0.000 0.116 0.000
#> SRR1947622 2 0.5049 0.8125 0.104 0.732 0.000 0.148 0.016
#> SRR1947621 2 0.3291 0.8177 0.000 0.840 0.000 0.120 0.040
#> SRR1947620 1 0.4168 0.7427 0.756 0.044 0.000 0.200 0.000
#> SRR1947619 3 0.1443 0.9192 0.000 0.044 0.948 0.004 0.004
#> SRR1947617 2 0.3291 0.8177 0.000 0.840 0.000 0.120 0.040
#> SRR1947618 1 0.4168 0.7427 0.756 0.044 0.000 0.200 0.000
#> SRR1947616 2 0.5120 0.7701 0.104 0.684 0.000 0.212 0.000
#> SRR1947615 3 0.2681 0.8712 0.000 0.012 0.876 0.108 0.004
#> SRR1947614 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947613 1 0.1341 0.7956 0.944 0.056 0.000 0.000 0.000
#> SRR1947610 2 0.2516 0.8197 0.000 0.860 0.000 0.140 0.000
#> SRR1947612 2 0.3291 0.8177 0.000 0.840 0.000 0.120 0.040
#> SRR1947609 4 0.3317 0.7153 0.116 0.044 0.000 0.840 0.000
#> SRR1947608 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947606 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947607 1 0.4443 0.4361 0.524 0.472 0.000 0.000 0.004
#> SRR1947604 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947605 1 0.4168 0.7427 0.756 0.044 0.000 0.200 0.000
#> SRR1947603 2 0.5290 0.8170 0.104 0.732 0.000 0.124 0.040
#> SRR1947602 1 0.3911 0.6942 0.796 0.000 0.144 0.060 0.000
#> SRR1947600 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947601 2 0.3339 0.8183 0.000 0.836 0.000 0.124 0.040
#> SRR1947598 4 0.1569 0.8414 0.004 0.044 0.008 0.944 0.000
#> SRR1947599 4 0.3365 0.7108 0.120 0.044 0.000 0.836 0.000
#> SRR1947597 2 0.5290 0.8170 0.104 0.732 0.000 0.124 0.040
#> SRR1947596 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947595 2 0.3543 0.8149 0.112 0.828 0.000 0.060 0.000
#> SRR1947594 1 0.1701 0.8074 0.936 0.048 0.000 0.016 0.000
#> SRR1947592 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947591 2 0.3291 0.8177 0.000 0.840 0.000 0.120 0.040
#> SRR1947590 4 0.1569 0.8421 0.004 0.044 0.008 0.944 0.000
#> SRR1947588 1 0.1701 0.8074 0.936 0.048 0.000 0.016 0.000
#> SRR1947587 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947586 2 0.0960 0.7731 0.016 0.972 0.000 0.008 0.004
#> SRR1947585 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947584 1 0.4325 0.7248 0.736 0.044 0.000 0.220 0.000
#> SRR1947583 2 0.4879 0.8023 0.108 0.716 0.000 0.176 0.000
#> SRR1947582 1 0.4168 0.7427 0.756 0.044 0.000 0.200 0.000
#> SRR1947580 2 0.0960 0.7731 0.016 0.972 0.000 0.008 0.004
#> SRR1947581 1 0.2408 0.7935 0.892 0.092 0.000 0.016 0.000
#> SRR1947576 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947575 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947579 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947578 4 0.4367 0.0746 0.004 0.416 0.000 0.580 0.000
#> SRR1947573 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947574 2 0.2833 0.7887 0.120 0.864 0.000 0.012 0.004
#> SRR1947571 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947577 1 0.4168 0.7427 0.756 0.044 0.000 0.200 0.000
#> SRR1947570 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947569 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947566 2 0.5148 0.8147 0.104 0.732 0.000 0.140 0.024
#> SRR1947567 2 0.5933 0.3297 0.104 0.452 0.000 0.444 0.000
#> SRR1947568 2 0.3612 0.6942 0.000 0.732 0.000 0.268 0.000
#> SRR1947564 2 0.6268 0.7084 0.104 0.612 0.000 0.244 0.040
#> SRR1947563 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947562 4 0.3442 0.7675 0.104 0.060 0.000 0.836 0.000
#> SRR1947565 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947559 2 0.5376 0.8157 0.104 0.724 0.000 0.132 0.040
#> SRR1947560 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947561 2 0.3339 0.8183 0.000 0.836 0.000 0.124 0.040
#> SRR1947557 1 0.1549 0.8074 0.944 0.040 0.000 0.016 0.000
#> SRR1947558 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947556 4 0.1522 0.8414 0.012 0.044 0.000 0.944 0.000
#> SRR1947553 2 0.2471 0.8204 0.000 0.864 0.000 0.136 0.000
#> SRR1947554 1 0.4135 0.5431 0.656 0.340 0.000 0.000 0.004
#> SRR1947555 2 0.3911 0.8234 0.104 0.816 0.000 0.072 0.008
#> SRR1947550 2 0.5919 0.4119 0.104 0.480 0.000 0.416 0.000
#> SRR1947552 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947549 3 0.0000 0.9757 0.000 0.000 1.000 0.000 0.000
#> SRR1947551 5 0.1197 0.9787 0.000 0.000 0.048 0.000 0.952
#> SRR1947548 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947506 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947507 1 0.1549 0.8074 0.944 0.040 0.000 0.016 0.000
#> SRR1947504 4 0.4469 0.6787 0.148 0.096 0.000 0.756 0.000
#> SRR1947503 4 0.4597 0.4967 0.260 0.044 0.000 0.696 0.000
#> SRR1947502 2 0.3291 0.8177 0.000 0.840 0.000 0.120 0.040
#> SRR1947501 4 0.1410 0.8376 0.000 0.060 0.000 0.940 0.000
#> SRR1947499 1 0.3911 0.6942 0.796 0.000 0.144 0.060 0.000
#> SRR1947498 3 0.1121 0.9525 0.000 0.000 0.956 0.000 0.044
#> SRR1947508 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
#> SRR1947505 4 0.5492 0.4502 0.024 0.044 0.308 0.624 0.000
#> SRR1947497 2 0.1059 0.7748 0.020 0.968 0.000 0.008 0.004
#> SRR1947496 1 0.1701 0.8074 0.936 0.048 0.000 0.016 0.000
#> SRR1947495 2 0.0960 0.7731 0.016 0.972 0.000 0.008 0.004
#> SRR1947494 4 0.1282 0.8451 0.004 0.044 0.000 0.952 0.000
#> SRR1947493 1 0.5078 0.5265 0.648 0.000 0.296 0.052 0.004
#> SRR1947492 1 0.1549 0.8074 0.944 0.040 0.000 0.016 0.000
#> SRR1947500 2 0.5324 0.7738 0.128 0.668 0.000 0.204 0.000
#> SRR1947491 1 0.4466 0.6837 0.748 0.076 0.000 0.176 0.000
#> SRR1947490 1 0.1270 0.7971 0.948 0.052 0.000 0.000 0.000
#> SRR1947489 3 0.1282 0.9589 0.000 0.000 0.952 0.044 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.1970 0.9199 0.000 0.000 0.900 0.008 0.000 0.092
#> SRR1947546 2 0.1124 0.8538 0.008 0.956 0.000 0.000 0.000 0.036
#> SRR1947545 4 0.3617 0.6381 0.244 0.000 0.000 0.736 0.000 0.020
#> SRR1947544 4 0.3221 0.6257 0.264 0.000 0.000 0.736 0.000 0.000
#> SRR1947542 2 0.4552 0.5709 0.012 0.636 0.000 0.320 0.000 0.032
#> SRR1947541 3 0.0806 0.9664 0.000 0.000 0.972 0.008 0.000 0.020
#> SRR1947540 2 0.4264 0.7104 0.032 0.744 0.000 0.188 0.000 0.036
#> SRR1947539 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947538 4 0.1251 0.8952 0.012 0.008 0.000 0.956 0.000 0.024
#> SRR1947537 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947536 5 0.1007 0.9389 0.000 0.000 0.044 0.000 0.956 0.000
#> SRR1947535 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947534 6 0.5120 0.3376 0.380 0.088 0.000 0.000 0.000 0.532
#> SRR1947533 6 0.2969 0.8724 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1947532 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947531 2 0.4326 0.6064 0.032 0.724 0.000 0.028 0.000 0.216
#> SRR1947530 1 0.3587 0.7852 0.792 0.000 0.068 0.000 0.000 0.140
#> SRR1947529 2 0.3869 -0.2992 0.000 0.500 0.000 0.000 0.000 0.500
#> SRR1947528 3 0.0806 0.9664 0.000 0.000 0.972 0.008 0.000 0.020
#> SRR1947527 2 0.2969 0.5594 0.000 0.776 0.000 0.000 0.000 0.224
#> SRR1947526 6 0.2941 0.8724 0.000 0.220 0.000 0.000 0.000 0.780
#> SRR1947525 2 0.2739 0.8224 0.012 0.872 0.000 0.084 0.000 0.032
#> SRR1947524 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947523 4 0.1265 0.8939 0.044 0.008 0.000 0.948 0.000 0.000
#> SRR1947521 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947520 6 0.2562 0.8643 0.000 0.172 0.000 0.000 0.000 0.828
#> SRR1947519 3 0.0603 0.9699 0.000 0.000 0.980 0.004 0.000 0.016
#> SRR1947518 2 0.3229 0.7568 0.044 0.816 0.000 0.140 0.000 0.000
#> SRR1947517 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947516 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947515 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947514 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947513 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947512 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947511 6 0.2969 0.8724 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1947510 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947572 2 0.3148 0.7881 0.020 0.840 0.000 0.116 0.000 0.024
#> SRR1947611 5 0.0458 0.9784 0.000 0.000 0.016 0.000 0.984 0.000
#> SRR1947509 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947644 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947643 6 0.3653 0.7559 0.008 0.300 0.000 0.000 0.000 0.692
#> SRR1947642 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947640 1 0.4625 0.1588 0.540 0.424 0.000 0.004 0.000 0.032
#> SRR1947641 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947639 2 0.0405 0.8594 0.008 0.988 0.000 0.000 0.000 0.004
#> SRR1947638 1 0.1462 0.8726 0.936 0.008 0.000 0.056 0.000 0.000
#> SRR1947637 3 0.1075 0.9396 0.000 0.000 0.952 0.000 0.048 0.000
#> SRR1947636 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947635 4 0.1866 0.8514 0.008 0.084 0.000 0.908 0.000 0.000
#> SRR1947634 6 0.3126 0.8221 0.000 0.248 0.000 0.000 0.000 0.752
#> SRR1947633 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947632 4 0.0547 0.9109 0.000 0.020 0.000 0.980 0.000 0.000
#> SRR1947631 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947629 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947630 6 0.2562 0.8643 0.000 0.172 0.000 0.000 0.000 0.828
#> SRR1947627 3 0.2212 0.9043 0.000 0.000 0.880 0.008 0.000 0.112
#> SRR1947628 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947626 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947625 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947624 6 0.2562 0.8643 0.000 0.172 0.000 0.000 0.000 0.828
#> SRR1947623 2 0.1657 0.8446 0.056 0.928 0.000 0.000 0.000 0.016
#> SRR1947622 2 0.1124 0.8538 0.008 0.956 0.000 0.000 0.000 0.036
#> SRR1947621 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947620 1 0.2384 0.8641 0.888 0.000 0.000 0.064 0.000 0.048
#> SRR1947619 3 0.1910 0.8739 0.000 0.000 0.892 0.108 0.000 0.000
#> SRR1947617 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947618 1 0.2282 0.8563 0.888 0.000 0.000 0.088 0.000 0.024
#> SRR1947616 2 0.2412 0.8206 0.000 0.880 0.000 0.028 0.000 0.092
#> SRR1947615 4 0.4328 0.0981 0.000 0.000 0.460 0.520 0.000 0.020
#> SRR1947614 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947613 1 0.1257 0.8695 0.952 0.020 0.000 0.000 0.000 0.028
#> SRR1947610 2 0.0000 0.8583 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947612 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947609 4 0.0260 0.9121 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1947608 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947606 3 0.0806 0.9664 0.000 0.000 0.972 0.008 0.000 0.020
#> SRR1947607 6 0.3786 0.7106 0.168 0.064 0.000 0.000 0.000 0.768
#> SRR1947604 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947605 1 0.2384 0.8641 0.888 0.000 0.000 0.064 0.000 0.048
#> SRR1947603 2 0.1007 0.8537 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947602 1 0.3587 0.7852 0.792 0.000 0.068 0.000 0.000 0.140
#> SRR1947600 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947601 2 0.0000 0.8583 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947598 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947599 4 0.0260 0.9121 0.008 0.000 0.000 0.992 0.000 0.000
#> SRR1947597 2 0.1124 0.8538 0.008 0.956 0.000 0.000 0.000 0.036
#> SRR1947596 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947595 6 0.3555 0.7836 0.008 0.280 0.000 0.000 0.000 0.712
#> SRR1947594 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947591 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947590 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947588 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947586 6 0.3221 0.8476 0.000 0.264 0.000 0.000 0.000 0.736
#> SRR1947585 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947584 4 0.3547 0.5292 0.332 0.000 0.000 0.668 0.000 0.000
#> SRR1947583 2 0.2777 0.8267 0.036 0.880 0.000 0.048 0.000 0.036
#> SRR1947582 1 0.2384 0.8641 0.888 0.000 0.000 0.064 0.000 0.048
#> SRR1947580 6 0.2969 0.8724 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1947581 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947576 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947575 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947579 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947578 2 0.3756 0.4237 0.000 0.600 0.000 0.400 0.000 0.000
#> SRR1947573 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947574 6 0.4536 0.8093 0.120 0.180 0.000 0.000 0.000 0.700
#> SRR1947571 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947577 1 0.2309 0.8579 0.888 0.000 0.000 0.084 0.000 0.028
#> SRR1947570 3 0.2070 0.9178 0.000 0.000 0.896 0.012 0.000 0.092
#> SRR1947569 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947566 2 0.1387 0.8441 0.000 0.932 0.000 0.000 0.000 0.068
#> SRR1947567 2 0.4205 0.6650 0.012 0.708 0.000 0.248 0.000 0.032
#> SRR1947568 2 0.1141 0.8406 0.000 0.948 0.000 0.052 0.000 0.000
#> SRR1947564 2 0.0260 0.8592 0.008 0.992 0.000 0.000 0.000 0.000
#> SRR1947563 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947562 4 0.1251 0.8958 0.008 0.012 0.000 0.956 0.000 0.024
#> SRR1947565 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947559 2 0.1151 0.8537 0.012 0.956 0.000 0.000 0.000 0.032
#> SRR1947560 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947561 2 0.0000 0.8583 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947557 1 0.0603 0.8848 0.980 0.016 0.000 0.004 0.000 0.000
#> SRR1947558 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947556 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947553 2 0.0000 0.8583 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1947554 6 0.3122 0.7087 0.176 0.020 0.000 0.000 0.000 0.804
#> SRR1947555 6 0.3684 0.6309 0.000 0.372 0.000 0.000 0.000 0.628
#> SRR1947550 2 0.3732 0.7404 0.012 0.776 0.000 0.180 0.000 0.032
#> SRR1947552 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947549 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947551 5 0.0000 0.9927 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1947548 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947506 3 0.2212 0.9043 0.000 0.000 0.880 0.008 0.000 0.112
#> SRR1947507 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947504 4 0.2826 0.8206 0.092 0.052 0.000 0.856 0.000 0.000
#> SRR1947503 4 0.0713 0.9015 0.028 0.000 0.000 0.972 0.000 0.000
#> SRR1947502 2 0.0363 0.8585 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1947501 4 0.0547 0.9109 0.000 0.020 0.000 0.980 0.000 0.000
#> SRR1947499 1 0.3587 0.7852 0.792 0.000 0.068 0.000 0.000 0.140
#> SRR1947498 3 0.0000 0.9778 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1947508 3 0.2212 0.9043 0.000 0.000 0.880 0.008 0.000 0.112
#> SRR1947505 4 0.2118 0.8139 0.000 0.000 0.104 0.888 0.000 0.008
#> SRR1947497 6 0.2969 0.8724 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1947496 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947495 6 0.2969 0.8724 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1947494 4 0.0260 0.9164 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1947493 1 0.5789 0.4108 0.516 0.000 0.316 0.008 0.000 0.160
#> SRR1947492 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947500 2 0.3880 0.7709 0.056 0.800 0.000 0.112 0.000 0.032
#> SRR1947491 1 0.2489 0.8253 0.860 0.012 0.000 0.128 0.000 0.000
#> SRR1947490 1 0.0547 0.8854 0.980 0.020 0.000 0.000 0.000 0.000
#> SRR1947489 3 0.0806 0.9664 0.000 0.000 0.972 0.008 0.000 0.020
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 15148 rows and 152 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 1.000 0.979 0.991 0.431 0.570 0.570
#> 3 3 0.914 0.908 0.951 0.502 0.686 0.491
#> 4 4 0.655 0.690 0.831 0.126 0.862 0.631
#> 5 5 0.629 0.605 0.756 0.074 0.831 0.473
#> 6 6 0.642 0.507 0.704 0.047 0.898 0.585
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
#> SRR1947547 1 0.0000 0.987 1.000 0.000
#> SRR1947546 2 0.0000 0.992 0.000 1.000
#> SRR1947545 1 0.0000 0.987 1.000 0.000
#> SRR1947544 1 0.0000 0.987 1.000 0.000
#> SRR1947542 2 0.0000 0.992 0.000 1.000
#> SRR1947541 1 0.0376 0.984 0.996 0.004
#> SRR1947540 2 0.0000 0.992 0.000 1.000
#> SRR1947539 2 0.0000 0.992 0.000 1.000
#> SRR1947538 2 0.0000 0.992 0.000 1.000
#> SRR1947537 2 0.0000 0.992 0.000 1.000
#> SRR1947536 1 0.0000 0.987 1.000 0.000
#> SRR1947535 2 0.0000 0.992 0.000 1.000
#> SRR1947534 1 0.0000 0.987 1.000 0.000
#> SRR1947533 2 0.0000 0.992 0.000 1.000
#> SRR1947532 2 0.0000 0.992 0.000 1.000
#> SRR1947531 2 0.0000 0.992 0.000 1.000
#> SRR1947530 1 0.0000 0.987 1.000 0.000
#> SRR1947529 2 0.0000 0.992 0.000 1.000
#> SRR1947528 1 0.0000 0.987 1.000 0.000
#> SRR1947527 2 0.0000 0.992 0.000 1.000
#> SRR1947526 2 0.0000 0.992 0.000 1.000
#> SRR1947525 2 0.0000 0.992 0.000 1.000
#> SRR1947524 2 0.0000 0.992 0.000 1.000
#> SRR1947523 2 0.4298 0.902 0.088 0.912
#> SRR1947521 2 0.0000 0.992 0.000 1.000
#> SRR1947520 2 0.0000 0.992 0.000 1.000
#> SRR1947519 2 0.8713 0.590 0.292 0.708
#> SRR1947518 2 0.0000 0.992 0.000 1.000
#> SRR1947517 1 0.0000 0.987 1.000 0.000
#> SRR1947516 2 0.0000 0.992 0.000 1.000
#> SRR1947515 2 0.0000 0.992 0.000 1.000
#> SRR1947514 2 0.0000 0.992 0.000 1.000
#> SRR1947513 1 0.0000 0.987 1.000 0.000
#> SRR1947512 1 0.0000 0.987 1.000 0.000
#> SRR1947511 2 0.0000 0.992 0.000 1.000
#> SRR1947510 2 0.0000 0.992 0.000 1.000
#> SRR1947572 2 0.0000 0.992 0.000 1.000
#> SRR1947611 2 0.0000 0.992 0.000 1.000
#> SRR1947509 1 0.0000 0.987 1.000 0.000
#> SRR1947644 2 0.0000 0.992 0.000 1.000
#> SRR1947643 2 0.0000 0.992 0.000 1.000
#> SRR1947642 2 0.0000 0.992 0.000 1.000
#> SRR1947640 2 0.7139 0.759 0.196 0.804
#> SRR1947641 2 0.0000 0.992 0.000 1.000
#> SRR1947639 2 0.0000 0.992 0.000 1.000
#> SRR1947638 1 0.0000 0.987 1.000 0.000
#> SRR1947637 2 0.0000 0.992 0.000 1.000
#> SRR1947636 2 0.0000 0.992 0.000 1.000
#> SRR1947635 2 0.0000 0.992 0.000 1.000
#> SRR1947634 2 0.0000 0.992 0.000 1.000
#> SRR1947633 2 0.0000 0.992 0.000 1.000
#> SRR1947632 2 0.0000 0.992 0.000 1.000
#> SRR1947631 2 0.0000 0.992 0.000 1.000
#> SRR1947629 2 0.0000 0.992 0.000 1.000
#> SRR1947630 2 0.0000 0.992 0.000 1.000
#> SRR1947627 1 0.0000 0.987 1.000 0.000
#> SRR1947628 2 0.0000 0.992 0.000 1.000
#> SRR1947626 2 0.0000 0.992 0.000 1.000
#> SRR1947625 2 0.0000 0.992 0.000 1.000
#> SRR1947624 2 0.0000 0.992 0.000 1.000
#> SRR1947623 1 0.5946 0.831 0.856 0.144
#> SRR1947622 2 0.0000 0.992 0.000 1.000
#> SRR1947621 2 0.0000 0.992 0.000 1.000
#> SRR1947620 1 0.0000 0.987 1.000 0.000
#> SRR1947619 2 0.0000 0.992 0.000 1.000
#> SRR1947617 2 0.0000 0.992 0.000 1.000
#> SRR1947618 1 0.0000 0.987 1.000 0.000
#> SRR1947616 2 0.0000 0.992 0.000 1.000
#> SRR1947615 2 0.5946 0.833 0.144 0.856
#> SRR1947614 2 0.0376 0.988 0.004 0.996
#> SRR1947613 1 0.0000 0.987 1.000 0.000
#> SRR1947610 2 0.0000 0.992 0.000 1.000
#> SRR1947612 2 0.0000 0.992 0.000 1.000
#> SRR1947609 1 0.0000 0.987 1.000 0.000
#> SRR1947608 2 0.0000 0.992 0.000 1.000
#> SRR1947606 1 0.4022 0.909 0.920 0.080
#> SRR1947607 1 0.0000 0.987 1.000 0.000
#> SRR1947604 2 0.0000 0.992 0.000 1.000
#> SRR1947605 1 0.0000 0.987 1.000 0.000
#> SRR1947603 2 0.0000 0.992 0.000 1.000
#> SRR1947602 1 0.0000 0.987 1.000 0.000
#> SRR1947600 2 0.0000 0.992 0.000 1.000
#> SRR1947601 2 0.0000 0.992 0.000 1.000
#> SRR1947598 2 0.0000 0.992 0.000 1.000
#> SRR1947599 1 0.0000 0.987 1.000 0.000
#> SRR1947597 2 0.0000 0.992 0.000 1.000
#> SRR1947596 2 0.0000 0.992 0.000 1.000
#> SRR1947595 2 0.0000 0.992 0.000 1.000
#> SRR1947594 1 0.0000 0.987 1.000 0.000
#> SRR1947592 2 0.0000 0.992 0.000 1.000
#> SRR1947591 2 0.0000 0.992 0.000 1.000
#> SRR1947590 2 0.0000 0.992 0.000 1.000
#> SRR1947588 1 0.0000 0.987 1.000 0.000
#> SRR1947587 2 0.0000 0.992 0.000 1.000
#> SRR1947586 2 0.0000 0.992 0.000 1.000
#> SRR1947585 2 0.0000 0.992 0.000 1.000
#> SRR1947584 1 0.0000 0.987 1.000 0.000
#> SRR1947583 2 0.0000 0.992 0.000 1.000
#> SRR1947582 1 0.0000 0.987 1.000 0.000
#> SRR1947580 2 0.0000 0.992 0.000 1.000
#> SRR1947581 1 0.0000 0.987 1.000 0.000
#> SRR1947576 2 0.0000 0.992 0.000 1.000
#> SRR1947575 2 0.0000 0.992 0.000 1.000
#> SRR1947579 2 0.0000 0.992 0.000 1.000
#> SRR1947578 2 0.0000 0.992 0.000 1.000
#> SRR1947573 2 0.0000 0.992 0.000 1.000
#> SRR1947574 1 0.9129 0.512 0.672 0.328
#> SRR1947571 2 0.0000 0.992 0.000 1.000
#> SRR1947577 1 0.0000 0.987 1.000 0.000
#> SRR1947570 1 0.0000 0.987 1.000 0.000
#> SRR1947569 2 0.0000 0.992 0.000 1.000
#> SRR1947566 2 0.0000 0.992 0.000 1.000
#> SRR1947567 2 0.0000 0.992 0.000 1.000
#> SRR1947568 2 0.0000 0.992 0.000 1.000
#> SRR1947564 2 0.0000 0.992 0.000 1.000
#> SRR1947563 2 0.0000 0.992 0.000 1.000
#> SRR1947562 2 0.0000 0.992 0.000 1.000
#> SRR1947565 2 0.0000 0.992 0.000 1.000
#> SRR1947559 2 0.0000 0.992 0.000 1.000
#> SRR1947560 2 0.0000 0.992 0.000 1.000
#> SRR1947561 2 0.0000 0.992 0.000 1.000
#> SRR1947557 1 0.0000 0.987 1.000 0.000
#> SRR1947558 2 0.0000 0.992 0.000 1.000
#> SRR1947556 1 0.0000 0.987 1.000 0.000
#> SRR1947553 2 0.0000 0.992 0.000 1.000
#> SRR1947554 1 0.0000 0.987 1.000 0.000
#> SRR1947555 2 0.0000 0.992 0.000 1.000
#> SRR1947550 2 0.0000 0.992 0.000 1.000
#> SRR1947552 2 0.3274 0.933 0.060 0.940
#> SRR1947549 2 0.0000 0.992 0.000 1.000
#> SRR1947551 2 0.0000 0.992 0.000 1.000
#> SRR1947548 2 0.0000 0.992 0.000 1.000
#> SRR1947506 1 0.0000 0.987 1.000 0.000
#> SRR1947507 1 0.0000 0.987 1.000 0.000
#> SRR1947504 1 0.2236 0.954 0.964 0.036
#> SRR1947503 1 0.0000 0.987 1.000 0.000
#> SRR1947502 2 0.0000 0.992 0.000 1.000
#> SRR1947501 2 0.0000 0.992 0.000 1.000
#> SRR1947499 1 0.0000 0.987 1.000 0.000
#> SRR1947498 2 0.0000 0.992 0.000 1.000
#> SRR1947508 1 0.0000 0.987 1.000 0.000
#> SRR1947505 2 0.3431 0.929 0.064 0.936
#> SRR1947497 2 0.0000 0.992 0.000 1.000
#> SRR1947496 1 0.0000 0.987 1.000 0.000
#> SRR1947495 2 0.0000 0.992 0.000 1.000
#> SRR1947494 2 0.0000 0.992 0.000 1.000
#> SRR1947493 1 0.0000 0.987 1.000 0.000
#> SRR1947492 1 0.0000 0.987 1.000 0.000
#> SRR1947500 2 0.0000 0.992 0.000 1.000
#> SRR1947491 1 0.0000 0.987 1.000 0.000
#> SRR1947490 1 0.0000 0.987 1.000 0.000
#> SRR1947489 1 0.0000 0.987 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR1947547 1 0.6295 0.0922 0.528 0.000 0.472
#> SRR1947546 2 0.1529 0.9536 0.000 0.960 0.040
#> SRR1947545 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947544 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947542 2 0.2066 0.9482 0.000 0.940 0.060
#> SRR1947541 3 0.2261 0.8870 0.068 0.000 0.932
#> SRR1947540 2 0.2356 0.9433 0.000 0.928 0.072
#> SRR1947539 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947538 2 0.0747 0.9510 0.000 0.984 0.016
#> SRR1947537 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947536 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947535 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947534 1 0.1529 0.9212 0.960 0.040 0.000
#> SRR1947533 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947532 2 0.2486 0.9476 0.008 0.932 0.060
#> SRR1947531 2 0.1289 0.9536 0.000 0.968 0.032
#> SRR1947530 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947529 2 0.2261 0.9451 0.000 0.932 0.068
#> SRR1947528 3 0.2796 0.8639 0.092 0.000 0.908
#> SRR1947527 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947526 2 0.1163 0.9533 0.000 0.972 0.028
#> SRR1947525 2 0.1411 0.9538 0.000 0.964 0.036
#> SRR1947524 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947523 1 0.6264 0.3494 0.616 0.380 0.004
#> SRR1947521 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947520 2 0.1031 0.9528 0.000 0.976 0.024
#> SRR1947519 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947518 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947517 3 0.2711 0.8682 0.088 0.000 0.912
#> SRR1947516 2 0.1753 0.9521 0.000 0.952 0.048
#> SRR1947515 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947514 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947513 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947512 1 0.0237 0.9469 0.996 0.004 0.000
#> SRR1947511 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947510 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947572 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947611 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947509 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947644 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947643 2 0.1753 0.9521 0.000 0.952 0.048
#> SRR1947642 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947640 2 0.2625 0.8812 0.084 0.916 0.000
#> SRR1947641 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947639 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947638 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947637 3 0.5810 0.4791 0.000 0.336 0.664
#> SRR1947636 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947635 2 0.2356 0.9433 0.000 0.928 0.072
#> SRR1947634 2 0.1643 0.9529 0.000 0.956 0.044
#> SRR1947633 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947632 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947631 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947629 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947630 2 0.1529 0.9538 0.000 0.960 0.040
#> SRR1947627 3 0.3752 0.8086 0.144 0.000 0.856
#> SRR1947628 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947626 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947625 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947624 2 0.2448 0.9411 0.000 0.924 0.076
#> SRR1947623 2 0.3941 0.7880 0.156 0.844 0.000
#> SRR1947622 2 0.2066 0.9482 0.000 0.940 0.060
#> SRR1947621 2 0.0892 0.9520 0.000 0.980 0.020
#> SRR1947620 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947619 3 0.5016 0.6728 0.000 0.240 0.760
#> SRR1947617 2 0.1163 0.9533 0.000 0.972 0.028
#> SRR1947618 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947616 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947615 3 0.3742 0.8736 0.072 0.036 0.892
#> SRR1947614 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947613 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947610 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947612 2 0.0747 0.9510 0.000 0.984 0.016
#> SRR1947609 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947608 3 0.0424 0.9421 0.000 0.008 0.992
#> SRR1947606 3 0.1753 0.9071 0.048 0.000 0.952
#> SRR1947607 1 0.0747 0.9387 0.984 0.016 0.000
#> SRR1947604 2 0.0747 0.9510 0.000 0.984 0.016
#> SRR1947605 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947603 2 0.2711 0.9337 0.000 0.912 0.088
#> SRR1947602 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947600 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947601 2 0.2356 0.9433 0.000 0.928 0.072
#> SRR1947598 2 0.4842 0.7688 0.000 0.776 0.224
#> SRR1947599 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947597 2 0.1529 0.9536 0.000 0.960 0.040
#> SRR1947596 2 0.0237 0.9469 0.000 0.996 0.004
#> SRR1947595 2 0.1411 0.9538 0.000 0.964 0.036
#> SRR1947594 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947592 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947591 2 0.1289 0.9536 0.000 0.968 0.032
#> SRR1947590 2 0.2537 0.9387 0.000 0.920 0.080
#> SRR1947588 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947587 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947586 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947585 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947584 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947583 2 0.0892 0.9521 0.000 0.980 0.020
#> SRR1947582 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947580 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947581 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947576 3 0.5650 0.5347 0.000 0.312 0.688
#> SRR1947575 3 0.5291 0.6236 0.000 0.268 0.732
#> SRR1947579 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947578 2 0.2878 0.9277 0.000 0.904 0.096
#> SRR1947573 3 0.0424 0.9421 0.000 0.008 0.992
#> SRR1947574 2 0.6045 0.3483 0.380 0.620 0.000
#> SRR1947571 2 0.1643 0.9529 0.000 0.956 0.044
#> SRR1947577 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947570 1 0.4121 0.7797 0.832 0.000 0.168
#> SRR1947569 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947566 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947567 2 0.1411 0.9538 0.000 0.964 0.036
#> SRR1947568 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947564 2 0.1529 0.9536 0.000 0.960 0.040
#> SRR1947563 3 0.0747 0.9361 0.000 0.016 0.984
#> SRR1947562 2 0.1753 0.9521 0.000 0.952 0.048
#> SRR1947565 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947559 2 0.1411 0.9538 0.000 0.964 0.036
#> SRR1947560 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947561 2 0.2261 0.9451 0.000 0.932 0.068
#> SRR1947557 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947558 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947556 1 0.2066 0.9063 0.940 0.060 0.000
#> SRR1947553 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947554 1 0.0747 0.9387 0.984 0.016 0.000
#> SRR1947555 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947550 2 0.1529 0.9536 0.000 0.960 0.040
#> SRR1947552 1 0.5092 0.7386 0.804 0.176 0.020
#> SRR1947549 3 0.1031 0.9296 0.000 0.024 0.976
#> SRR1947551 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947548 2 0.2625 0.9363 0.000 0.916 0.084
#> SRR1947506 1 0.3752 0.8144 0.856 0.000 0.144
#> SRR1947507 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947504 2 0.5363 0.5895 0.276 0.724 0.000
#> SRR1947503 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947502 2 0.1031 0.9527 0.000 0.976 0.024
#> SRR1947501 2 0.2796 0.9310 0.000 0.908 0.092
#> SRR1947499 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947498 3 0.0000 0.9471 0.000 0.000 1.000
#> SRR1947508 1 0.1643 0.9163 0.956 0.000 0.044
#> SRR1947505 1 0.5873 0.5472 0.684 0.004 0.312
#> SRR1947497 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947496 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947495 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947494 2 0.4887 0.8856 0.060 0.844 0.096
#> SRR1947493 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947492 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947500 2 0.0000 0.9455 0.000 1.000 0.000
#> SRR1947491 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947490 1 0.0000 0.9494 1.000 0.000 0.000
#> SRR1947489 3 0.3192 0.8461 0.112 0.000 0.888
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR1947547 1 0.5102 0.6253 0.748 0.000 0.188 0.064
#> SRR1947546 2 0.2921 0.8248 0.000 0.860 0.000 0.140
#> SRR1947545 1 0.0469 0.8989 0.988 0.000 0.000 0.012
#> SRR1947544 1 0.3942 0.6922 0.764 0.000 0.000 0.236
#> SRR1947542 2 0.4933 0.4442 0.000 0.568 0.000 0.432
#> SRR1947541 3 0.5964 0.5591 0.108 0.000 0.684 0.208
#> SRR1947540 2 0.3400 0.8043 0.000 0.820 0.000 0.180
#> SRR1947539 3 0.0000 0.8089 0.000 0.000 1.000 0.000
#> SRR1947538 4 0.4989 -0.2265 0.000 0.472 0.000 0.528
#> SRR1947537 4 0.5376 0.3118 0.000 0.016 0.396 0.588
#> SRR1947536 1 0.1004 0.8872 0.972 0.000 0.024 0.004
#> SRR1947535 3 0.3450 0.7387 0.000 0.008 0.836 0.156
#> SRR1947534 1 0.4035 0.7457 0.804 0.176 0.000 0.020
#> SRR1947533 2 0.0336 0.8146 0.000 0.992 0.000 0.008
#> SRR1947532 4 0.4199 0.6328 0.008 0.060 0.096 0.836
#> SRR1947531 2 0.0336 0.8186 0.000 0.992 0.000 0.008
#> SRR1947530 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947529 2 0.2011 0.8356 0.000 0.920 0.000 0.080
#> SRR1947528 3 0.2197 0.7759 0.080 0.000 0.916 0.004
#> SRR1947527 2 0.0657 0.8130 0.004 0.984 0.000 0.012
#> SRR1947526 2 0.0469 0.8194 0.000 0.988 0.000 0.012
#> SRR1947525 2 0.3837 0.7763 0.000 0.776 0.000 0.224
#> SRR1947524 3 0.0469 0.8097 0.000 0.000 0.988 0.012
#> SRR1947523 1 0.5113 0.7197 0.760 0.088 0.000 0.152
#> SRR1947521 3 0.2345 0.7749 0.000 0.000 0.900 0.100
#> SRR1947520 2 0.2266 0.7608 0.000 0.912 0.004 0.084
#> SRR1947519 3 0.3969 0.7146 0.016 0.000 0.804 0.180
#> SRR1947518 2 0.3837 0.7271 0.000 0.776 0.000 0.224
#> SRR1947517 3 0.3617 0.7463 0.064 0.000 0.860 0.076
#> SRR1947516 2 0.2704 0.8286 0.000 0.876 0.000 0.124
#> SRR1947515 4 0.3840 0.6310 0.000 0.052 0.104 0.844
#> SRR1947514 2 0.0336 0.8208 0.000 0.992 0.000 0.008
#> SRR1947513 1 0.0000 0.8989 1.000 0.000 0.000 0.000
#> SRR1947512 1 0.1256 0.8919 0.964 0.008 0.000 0.028
#> SRR1947511 2 0.0336 0.8146 0.000 0.992 0.000 0.008
#> SRR1947510 3 0.2976 0.7621 0.000 0.008 0.872 0.120
#> SRR1947572 2 0.5000 0.2992 0.000 0.504 0.000 0.496
#> SRR1947611 3 0.3935 0.7338 0.000 0.060 0.840 0.100
#> SRR1947509 1 0.0895 0.8905 0.976 0.000 0.020 0.004
#> SRR1947644 3 0.1940 0.7853 0.000 0.000 0.924 0.076
#> SRR1947643 2 0.0336 0.8146 0.000 0.992 0.000 0.008
#> SRR1947642 3 0.2611 0.7863 0.008 0.000 0.896 0.096
#> SRR1947640 1 0.5295 0.1007 0.504 0.488 0.000 0.008
#> SRR1947641 3 0.0336 0.8097 0.000 0.000 0.992 0.008
#> SRR1947639 2 0.3569 0.8017 0.000 0.804 0.000 0.196
#> SRR1947638 1 0.0000 0.8989 1.000 0.000 0.000 0.000
#> SRR1947637 4 0.7733 0.1327 0.000 0.304 0.256 0.440
#> SRR1947636 3 0.2530 0.7762 0.000 0.000 0.888 0.112
#> SRR1947635 2 0.4262 0.7593 0.008 0.756 0.000 0.236
#> SRR1947634 2 0.1489 0.8134 0.004 0.952 0.000 0.044
#> SRR1947633 3 0.0000 0.8089 0.000 0.000 1.000 0.000
#> SRR1947632 2 0.4855 0.4923 0.000 0.600 0.000 0.400
#> SRR1947631 3 0.3400 0.7214 0.000 0.000 0.820 0.180
#> SRR1947629 3 0.1716 0.7991 0.000 0.000 0.936 0.064
#> SRR1947630 2 0.3994 0.6790 0.004 0.828 0.028 0.140
#> SRR1947627 3 0.5158 0.0908 0.472 0.000 0.524 0.004
#> SRR1947628 4 0.5630 0.1957 0.000 0.360 0.032 0.608
#> SRR1947626 2 0.0921 0.8258 0.000 0.972 0.000 0.028
#> SRR1947625 3 0.1637 0.8002 0.000 0.000 0.940 0.060
#> SRR1947624 2 0.3852 0.7343 0.000 0.800 0.008 0.192
#> SRR1947623 1 0.6352 0.4580 0.632 0.260 0.000 0.108
#> SRR1947622 2 0.4008 0.7513 0.000 0.756 0.000 0.244
#> SRR1947621 2 0.1792 0.8337 0.000 0.932 0.000 0.068
#> SRR1947620 1 0.0469 0.8989 0.988 0.000 0.000 0.012
#> SRR1947619 4 0.5334 0.4958 0.000 0.036 0.284 0.680
#> SRR1947617 2 0.2081 0.8344 0.000 0.916 0.000 0.084
#> SRR1947618 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947616 2 0.3306 0.8219 0.000 0.840 0.004 0.156
#> SRR1947615 4 0.6486 0.4641 0.088 0.012 0.256 0.644
#> SRR1947614 3 0.2814 0.7587 0.000 0.000 0.868 0.132
#> SRR1947613 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947610 2 0.1940 0.8024 0.000 0.924 0.000 0.076
#> SRR1947612 2 0.2216 0.8335 0.000 0.908 0.000 0.092
#> SRR1947609 1 0.5075 0.5090 0.644 0.012 0.000 0.344
#> SRR1947608 4 0.5649 0.4021 0.000 0.036 0.344 0.620
#> SRR1947606 3 0.1042 0.8092 0.008 0.000 0.972 0.020
#> SRR1947607 1 0.2706 0.8415 0.900 0.080 0.000 0.020
#> SRR1947604 4 0.3494 0.5682 0.000 0.172 0.004 0.824
#> SRR1947605 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947603 2 0.4134 0.7374 0.000 0.740 0.000 0.260
#> SRR1947602 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947600 3 0.0707 0.8091 0.000 0.000 0.980 0.020
#> SRR1947601 2 0.2921 0.8240 0.000 0.860 0.000 0.140
#> SRR1947598 4 0.3812 0.6118 0.000 0.028 0.140 0.832
#> SRR1947599 4 0.5464 -0.1848 0.492 0.004 0.008 0.496
#> SRR1947597 2 0.3569 0.7930 0.000 0.804 0.000 0.196
#> SRR1947596 4 0.3947 0.6273 0.004 0.116 0.040 0.840
#> SRR1947595 2 0.1302 0.8303 0.000 0.956 0.000 0.044
#> SRR1947594 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947592 3 0.4059 0.6641 0.000 0.012 0.788 0.200
#> SRR1947591 2 0.1867 0.8343 0.000 0.928 0.000 0.072
#> SRR1947590 4 0.3899 0.6294 0.000 0.052 0.108 0.840
#> SRR1947588 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947587 3 0.4040 0.6454 0.000 0.000 0.752 0.248
#> SRR1947586 2 0.1209 0.8056 0.004 0.964 0.000 0.032
#> SRR1947585 3 0.0469 0.8097 0.000 0.000 0.988 0.012
#> SRR1947584 1 0.0592 0.8975 0.984 0.000 0.000 0.016
#> SRR1947583 2 0.2401 0.8353 0.004 0.904 0.000 0.092
#> SRR1947582 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947580 2 0.0336 0.8141 0.000 0.992 0.000 0.008
#> SRR1947581 1 0.1118 0.8910 0.964 0.000 0.000 0.036
#> SRR1947576 3 0.7640 0.0861 0.000 0.280 0.468 0.252
#> SRR1947575 4 0.7825 0.3036 0.000 0.304 0.284 0.412
#> SRR1947579 3 0.2814 0.7587 0.000 0.000 0.868 0.132
#> SRR1947578 2 0.4792 0.6561 0.000 0.680 0.008 0.312
#> SRR1947573 3 0.5200 0.5211 0.000 0.072 0.744 0.184
#> SRR1947574 2 0.5099 0.2302 0.380 0.612 0.000 0.008
#> SRR1947571 4 0.4008 0.4575 0.000 0.244 0.000 0.756
#> SRR1947577 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947570 1 0.6245 0.4826 0.668 0.000 0.164 0.168
#> SRR1947569 3 0.3583 0.7170 0.000 0.004 0.816 0.180
#> SRR1947566 2 0.4155 0.7697 0.000 0.756 0.004 0.240
#> SRR1947567 2 0.3444 0.8009 0.000 0.816 0.000 0.184
#> SRR1947568 2 0.2011 0.8349 0.000 0.920 0.000 0.080
#> SRR1947564 2 0.3801 0.7737 0.000 0.780 0.000 0.220
#> SRR1947563 4 0.6788 0.4963 0.000 0.144 0.264 0.592
#> SRR1947562 4 0.4985 -0.2121 0.000 0.468 0.000 0.532
#> SRR1947565 3 0.5070 0.1975 0.000 0.004 0.580 0.416
#> SRR1947559 2 0.3801 0.7740 0.000 0.780 0.000 0.220
#> SRR1947560 3 0.4388 0.7089 0.000 0.060 0.808 0.132
#> SRR1947561 2 0.3123 0.8177 0.000 0.844 0.000 0.156
#> SRR1947557 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947558 3 0.2466 0.7843 0.000 0.004 0.900 0.096
#> SRR1947556 4 0.6232 -0.1249 0.472 0.036 0.008 0.484
#> SRR1947553 2 0.1637 0.8148 0.000 0.940 0.000 0.060
#> SRR1947554 1 0.4507 0.6824 0.756 0.224 0.000 0.020
#> SRR1947555 2 0.4722 0.7129 0.000 0.692 0.008 0.300
#> SRR1947550 2 0.4500 0.6664 0.000 0.684 0.000 0.316
#> SRR1947552 4 0.4931 0.5879 0.056 0.016 0.136 0.792
#> SRR1947549 4 0.7125 0.2927 0.000 0.132 0.392 0.476
#> SRR1947551 3 0.3384 0.7565 0.000 0.024 0.860 0.116
#> SRR1947548 4 0.4030 0.6361 0.000 0.092 0.072 0.836
#> SRR1947506 1 0.0376 0.8982 0.992 0.000 0.004 0.004
#> SRR1947507 1 0.0188 0.8991 0.996 0.000 0.000 0.004
#> SRR1947504 1 0.6240 0.5472 0.668 0.156 0.000 0.176
#> SRR1947503 1 0.1004 0.8958 0.972 0.004 0.000 0.024
#> SRR1947502 2 0.2149 0.8344 0.000 0.912 0.000 0.088
#> SRR1947501 2 0.4643 0.6091 0.000 0.656 0.000 0.344
#> SRR1947499 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947498 3 0.0336 0.8097 0.000 0.000 0.992 0.008
#> SRR1947508 1 0.1489 0.8722 0.952 0.000 0.044 0.004
#> SRR1947505 4 0.8237 0.2178 0.316 0.012 0.284 0.388
#> SRR1947497 2 0.0336 0.8141 0.000 0.992 0.000 0.008
#> SRR1947496 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947495 2 0.0376 0.8135 0.004 0.992 0.000 0.004
#> SRR1947494 4 0.4819 0.6265 0.028 0.048 0.116 0.808
#> SRR1947493 1 0.0188 0.8987 0.996 0.000 0.000 0.004
#> SRR1947492 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947500 2 0.2402 0.7690 0.076 0.912 0.000 0.012
#> SRR1947491 1 0.0707 0.8924 0.980 0.020 0.000 0.000
#> SRR1947490 1 0.0592 0.8984 0.984 0.000 0.000 0.016
#> SRR1947489 4 0.7899 0.1621 0.324 0.000 0.304 0.372
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR1947547 3 0.5588 0.212221 0.436 0.000 0.500 0.004 0.060
#> SRR1947546 2 0.4562 -0.440204 0.000 0.500 0.008 0.492 0.000
#> SRR1947545 1 0.1608 0.856218 0.928 0.000 0.000 0.072 0.000
#> SRR1947544 1 0.6122 0.337568 0.512 0.000 0.348 0.140 0.000
#> SRR1947542 2 0.3663 0.595117 0.000 0.776 0.208 0.016 0.000
#> SRR1947541 3 0.4686 0.553301 0.104 0.000 0.736 0.000 0.160
#> SRR1947540 2 0.3611 0.575882 0.000 0.780 0.008 0.208 0.004
#> SRR1947539 5 0.1430 0.831409 0.000 0.000 0.052 0.004 0.944
#> SRR1947538 3 0.4914 0.576231 0.000 0.204 0.704 0.092 0.000
#> SRR1947537 3 0.5655 0.319915 0.000 0.392 0.544 0.016 0.048
#> SRR1947536 1 0.3455 0.748475 0.844 0.000 0.068 0.004 0.084
#> SRR1947535 3 0.3949 0.424672 0.000 0.004 0.696 0.000 0.300
#> SRR1947534 4 0.4299 -0.197462 0.388 0.000 0.004 0.608 0.000
#> SRR1947533 4 0.4482 0.667863 0.000 0.376 0.000 0.612 0.012
#> SRR1947532 3 0.2032 0.670208 0.004 0.052 0.924 0.020 0.000
#> SRR1947531 4 0.4220 0.725720 0.008 0.300 0.004 0.688 0.000
#> SRR1947530 1 0.0566 0.848805 0.984 0.000 0.012 0.004 0.000
#> SRR1947529 2 0.2522 0.657030 0.000 0.880 0.000 0.108 0.012
#> SRR1947528 1 0.5330 0.421294 0.620 0.000 0.064 0.004 0.312
#> SRR1947527 4 0.3395 0.720379 0.000 0.236 0.000 0.764 0.000
#> SRR1947526 2 0.3236 0.601605 0.000 0.828 0.000 0.152 0.020
#> SRR1947525 2 0.1668 0.683280 0.000 0.940 0.032 0.028 0.000
#> SRR1947524 5 0.2230 0.811765 0.000 0.000 0.116 0.000 0.884
#> SRR1947523 3 0.7210 0.451470 0.184 0.060 0.568 0.176 0.012
#> SRR1947521 5 0.1041 0.830632 0.000 0.000 0.032 0.004 0.964
#> SRR1947520 4 0.5047 0.717225 0.000 0.284 0.000 0.652 0.064
#> SRR1947519 3 0.5848 0.402119 0.168 0.000 0.604 0.000 0.228
#> SRR1947518 4 0.4094 0.551259 0.000 0.128 0.084 0.788 0.000
#> SRR1947517 5 0.1701 0.824655 0.016 0.000 0.028 0.012 0.944
#> SRR1947516 2 0.1965 0.656034 0.000 0.904 0.000 0.096 0.000
#> SRR1947515 3 0.2179 0.672195 0.000 0.100 0.896 0.000 0.004
#> SRR1947514 2 0.3983 0.167138 0.000 0.660 0.000 0.340 0.000
#> SRR1947513 1 0.0693 0.851925 0.980 0.000 0.008 0.012 0.000
#> SRR1947512 1 0.3333 0.821437 0.788 0.000 0.004 0.208 0.000
#> SRR1947511 4 0.4161 0.722886 0.000 0.280 0.000 0.704 0.016
#> SRR1947510 5 0.1195 0.803886 0.000 0.028 0.000 0.012 0.960
#> SRR1947572 2 0.6225 0.255149 0.004 0.472 0.124 0.400 0.000
#> SRR1947611 5 0.1557 0.789645 0.000 0.052 0.000 0.008 0.940
#> SRR1947509 1 0.2597 0.796586 0.896 0.000 0.040 0.004 0.060
#> SRR1947644 5 0.1205 0.831644 0.000 0.000 0.040 0.004 0.956
#> SRR1947643 4 0.4613 0.685497 0.000 0.360 0.000 0.620 0.020
#> SRR1947642 3 0.6356 0.096728 0.168 0.000 0.468 0.000 0.364
#> SRR1947640 4 0.6464 0.432282 0.304 0.168 0.008 0.520 0.000
#> SRR1947641 5 0.1908 0.821519 0.000 0.000 0.092 0.000 0.908
#> SRR1947639 2 0.3151 0.627477 0.000 0.836 0.020 0.144 0.000
#> SRR1947638 1 0.0693 0.853146 0.980 0.000 0.008 0.012 0.000
#> SRR1947637 2 0.4160 0.575027 0.000 0.772 0.008 0.036 0.184
#> SRR1947636 5 0.5046 -0.000475 0.000 0.032 0.468 0.000 0.500
#> SRR1947635 2 0.7296 0.145880 0.048 0.448 0.356 0.144 0.004
#> SRR1947634 2 0.4724 0.524544 0.000 0.732 0.000 0.164 0.104
#> SRR1947633 5 0.1282 0.831802 0.000 0.000 0.044 0.004 0.952
#> SRR1947632 2 0.2685 0.656707 0.000 0.880 0.092 0.028 0.000
#> SRR1947631 3 0.4240 0.447285 0.012 0.004 0.700 0.000 0.284
#> SRR1947629 5 0.5182 0.170710 0.000 0.044 0.412 0.000 0.544
#> SRR1947630 4 0.6724 0.467473 0.000 0.284 0.000 0.420 0.296
#> SRR1947627 5 0.5810 0.391239 0.364 0.000 0.088 0.004 0.544
#> SRR1947628 2 0.4829 -0.048808 0.000 0.500 0.480 0.020 0.000
#> SRR1947626 4 0.4390 0.579857 0.000 0.428 0.004 0.568 0.000
#> SRR1947625 5 0.4546 0.149572 0.000 0.008 0.460 0.000 0.532
#> SRR1947624 2 0.3590 0.625590 0.000 0.828 0.000 0.080 0.092
#> SRR1947623 1 0.5012 0.665341 0.600 0.016 0.016 0.368 0.000
#> SRR1947622 2 0.1310 0.683676 0.000 0.956 0.024 0.020 0.000
#> SRR1947621 2 0.2329 0.631444 0.000 0.876 0.000 0.124 0.000
#> SRR1947620 1 0.0290 0.851131 0.992 0.000 0.008 0.000 0.000
#> SRR1947619 3 0.4905 0.092537 0.000 0.476 0.500 0.000 0.024
#> SRR1947617 2 0.2966 0.569159 0.000 0.816 0.000 0.184 0.000
#> SRR1947618 1 0.0290 0.851131 0.992 0.000 0.008 0.000 0.000
#> SRR1947616 2 0.2522 0.645456 0.000 0.880 0.000 0.108 0.012
#> SRR1947615 3 0.2459 0.642197 0.052 0.004 0.908 0.004 0.032
#> SRR1947614 5 0.0798 0.825612 0.000 0.000 0.016 0.008 0.976
#> SRR1947613 1 0.2471 0.848732 0.864 0.000 0.000 0.136 0.000
#> SRR1947610 4 0.4703 0.681630 0.000 0.340 0.028 0.632 0.000
#> SRR1947612 2 0.2891 0.582457 0.000 0.824 0.000 0.176 0.000
#> SRR1947609 3 0.4986 0.157760 0.444 0.012 0.532 0.012 0.000
#> SRR1947608 3 0.5581 0.225038 0.000 0.428 0.508 0.004 0.060
#> SRR1947606 5 0.2773 0.772456 0.000 0.000 0.164 0.000 0.836
#> SRR1947607 1 0.3684 0.778337 0.720 0.000 0.000 0.280 0.000
#> SRR1947604 3 0.2812 0.671907 0.004 0.096 0.876 0.024 0.000
#> SRR1947605 1 0.0609 0.855034 0.980 0.000 0.000 0.020 0.000
#> SRR1947603 2 0.0727 0.687464 0.000 0.980 0.004 0.012 0.004
#> SRR1947602 1 0.0566 0.848805 0.984 0.000 0.012 0.004 0.000
#> SRR1947600 5 0.2471 0.798209 0.000 0.000 0.136 0.000 0.864
#> SRR1947601 2 0.1740 0.674792 0.000 0.932 0.000 0.056 0.012
#> SRR1947598 3 0.2068 0.672315 0.000 0.092 0.904 0.000 0.004
#> SRR1947599 3 0.3700 0.606790 0.240 0.008 0.752 0.000 0.000
#> SRR1947597 2 0.0703 0.686040 0.000 0.976 0.000 0.024 0.000
#> SRR1947596 3 0.2972 0.670224 0.004 0.108 0.864 0.024 0.000
#> SRR1947595 4 0.4499 0.546227 0.000 0.408 0.004 0.584 0.004
#> SRR1947594 1 0.2773 0.841199 0.836 0.000 0.000 0.164 0.000
#> SRR1947592 3 0.5675 0.303925 0.000 0.092 0.556 0.000 0.352
#> SRR1947591 2 0.2732 0.597910 0.000 0.840 0.000 0.160 0.000
#> SRR1947590 3 0.2230 0.670610 0.000 0.116 0.884 0.000 0.000
#> SRR1947588 1 0.3086 0.833655 0.816 0.000 0.004 0.180 0.000
#> SRR1947587 3 0.2833 0.610218 0.012 0.004 0.864 0.000 0.120
#> SRR1947586 4 0.3807 0.720002 0.000 0.240 0.012 0.748 0.000
#> SRR1947585 5 0.2074 0.818340 0.000 0.000 0.104 0.000 0.896
#> SRR1947584 1 0.2891 0.837015 0.824 0.000 0.000 0.176 0.000
#> SRR1947583 2 0.5543 0.323706 0.064 0.624 0.008 0.300 0.004
#> SRR1947582 1 0.0451 0.850207 0.988 0.000 0.008 0.004 0.000
#> SRR1947580 4 0.4238 0.668599 0.000 0.368 0.004 0.628 0.000
#> SRR1947581 1 0.3333 0.821721 0.788 0.000 0.004 0.208 0.000
#> SRR1947576 2 0.4874 0.432324 0.000 0.632 0.000 0.040 0.328
#> SRR1947575 2 0.3985 0.611632 0.000 0.812 0.128 0.036 0.024
#> SRR1947579 5 0.0807 0.822353 0.000 0.000 0.012 0.012 0.976
#> SRR1947578 2 0.4180 0.568559 0.000 0.768 0.192 0.028 0.012
#> SRR1947573 2 0.4727 0.491308 0.000 0.692 0.012 0.028 0.268
#> SRR1947574 4 0.3520 0.595775 0.080 0.076 0.004 0.840 0.000
#> SRR1947571 3 0.4025 0.510827 0.000 0.292 0.700 0.008 0.000
#> SRR1947577 1 0.0290 0.851131 0.992 0.000 0.008 0.000 0.000
#> SRR1947570 3 0.4218 0.508149 0.332 0.000 0.660 0.000 0.008
#> SRR1947569 3 0.5219 0.427650 0.000 0.060 0.636 0.004 0.300
#> SRR1947566 2 0.1018 0.686059 0.000 0.968 0.000 0.016 0.016
#> SRR1947567 2 0.4400 0.289862 0.000 0.672 0.020 0.308 0.000
#> SRR1947568 4 0.4434 0.259069 0.000 0.460 0.004 0.536 0.000
#> SRR1947564 2 0.1041 0.685942 0.000 0.964 0.004 0.032 0.000
#> SRR1947563 2 0.4805 0.456397 0.000 0.688 0.268 0.032 0.012
#> SRR1947562 2 0.5039 0.003111 0.000 0.512 0.456 0.032 0.000
#> SRR1947565 3 0.6177 0.488347 0.000 0.212 0.556 0.000 0.232
#> SRR1947559 2 0.1894 0.674499 0.000 0.920 0.008 0.072 0.000
#> SRR1947560 5 0.1626 0.791994 0.000 0.044 0.000 0.016 0.940
#> SRR1947561 2 0.1502 0.675358 0.000 0.940 0.000 0.056 0.004
#> SRR1947557 1 0.2377 0.850011 0.872 0.000 0.000 0.128 0.000
#> SRR1947558 3 0.4030 0.327412 0.000 0.000 0.648 0.000 0.352
#> SRR1947556 3 0.5907 0.366540 0.284 0.004 0.588 0.124 0.000
#> SRR1947553 4 0.4846 0.632679 0.000 0.384 0.028 0.588 0.000
#> SRR1947554 1 0.4299 0.659002 0.608 0.000 0.004 0.388 0.000
#> SRR1947555 2 0.1195 0.684593 0.000 0.960 0.000 0.012 0.028
#> SRR1947550 2 0.5155 0.535795 0.000 0.704 0.160 0.132 0.004
#> SRR1947552 3 0.4211 0.666508 0.080 0.116 0.796 0.004 0.004
#> SRR1947549 2 0.4734 0.515628 0.000 0.720 0.228 0.032 0.020
#> SRR1947551 5 0.2349 0.761501 0.000 0.084 0.004 0.012 0.900
#> SRR1947548 3 0.2824 0.670504 0.000 0.116 0.864 0.020 0.000
#> SRR1947506 1 0.0566 0.848805 0.984 0.000 0.012 0.004 0.000
#> SRR1947507 1 0.1908 0.854972 0.908 0.000 0.000 0.092 0.000
#> SRR1947504 1 0.4623 0.713495 0.640 0.008 0.012 0.340 0.000
#> SRR1947503 1 0.3828 0.777764 0.808 0.000 0.120 0.072 0.000
#> SRR1947502 2 0.2773 0.595704 0.000 0.836 0.000 0.164 0.000
#> SRR1947501 2 0.2362 0.666546 0.000 0.900 0.076 0.024 0.000
#> SRR1947499 1 0.0566 0.848805 0.984 0.000 0.012 0.004 0.000
#> SRR1947498 5 0.1965 0.820404 0.000 0.000 0.096 0.000 0.904
#> SRR1947508 1 0.4314 0.666930 0.780 0.000 0.092 0.004 0.124
#> SRR1947505 3 0.4965 0.535189 0.320 0.032 0.640 0.000 0.008
#> SRR1947497 4 0.3816 0.724246 0.000 0.304 0.000 0.696 0.000
#> SRR1947496 1 0.2970 0.838576 0.828 0.000 0.004 0.168 0.000
#> SRR1947495 4 0.3752 0.725365 0.000 0.292 0.000 0.708 0.000
#> SRR1947494 3 0.1990 0.671692 0.000 0.068 0.920 0.004 0.008
#> SRR1947493 1 0.0290 0.851131 0.992 0.000 0.008 0.000 0.000
#> SRR1947492 1 0.2424 0.849417 0.868 0.000 0.000 0.132 0.000
#> SRR1947500 4 0.5982 0.632655 0.144 0.240 0.008 0.608 0.000
#> SRR1947491 1 0.3584 0.772167 0.820 0.012 0.020 0.148 0.000
#> SRR1947490 1 0.2230 0.852158 0.884 0.000 0.000 0.116 0.000
#> SRR1947489 3 0.2505 0.644346 0.092 0.000 0.888 0.000 0.020
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR1947547 3 0.3221 0.453115 0.188 0.000 0.792 0.000 0.020 0.000
#> SRR1947546 2 0.3705 0.530391 0.000 0.776 0.008 0.180 0.000 0.036
#> SRR1947545 1 0.2941 0.756087 0.856 0.000 0.004 0.064 0.000 0.076
#> SRR1947544 1 0.6779 0.270426 0.416 0.000 0.068 0.168 0.000 0.348
#> SRR1947542 2 0.2390 0.702801 0.000 0.896 0.052 0.008 0.000 0.044
#> SRR1947541 3 0.6822 0.343377 0.212 0.000 0.508 0.000 0.128 0.152
#> SRR1947540 4 0.5821 0.374719 0.000 0.388 0.012 0.468 0.000 0.132
#> SRR1947539 5 0.2325 0.755598 0.000 0.008 0.100 0.000 0.884 0.008
#> SRR1947538 2 0.7411 -0.124214 0.000 0.348 0.312 0.140 0.000 0.200
#> SRR1947537 6 0.7302 0.170963 0.000 0.216 0.264 0.000 0.124 0.396
#> SRR1947536 1 0.1594 0.737517 0.932 0.000 0.052 0.000 0.016 0.000
#> SRR1947535 3 0.2373 0.545566 0.000 0.000 0.880 0.008 0.104 0.008
#> SRR1947534 4 0.5155 -0.067999 0.344 0.000 0.000 0.556 0.000 0.100
#> SRR1947533 4 0.4117 0.643132 0.000 0.256 0.000 0.708 0.016 0.020
#> SRR1947532 3 0.2846 0.558492 0.000 0.004 0.840 0.016 0.000 0.140
#> SRR1947531 4 0.3636 0.663125 0.000 0.208 0.016 0.764 0.000 0.012
#> SRR1947530 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947529 2 0.6415 -0.242906 0.000 0.460 0.000 0.356 0.056 0.128
#> SRR1947528 1 0.5519 0.299624 0.564 0.000 0.048 0.000 0.336 0.052
#> SRR1947527 4 0.3806 0.652580 0.000 0.164 0.000 0.768 0.000 0.068
#> SRR1947526 2 0.4810 0.165843 0.000 0.604 0.000 0.340 0.012 0.044
#> SRR1947525 2 0.3563 0.538942 0.000 0.664 0.000 0.000 0.000 0.336
#> SRR1947524 5 0.4118 0.544040 0.000 0.004 0.396 0.000 0.592 0.008
#> SRR1947523 3 0.4615 0.423219 0.064 0.008 0.732 0.176 0.000 0.020
#> SRR1947521 5 0.0508 0.754424 0.000 0.000 0.012 0.000 0.984 0.004
#> SRR1947520 4 0.5129 0.642654 0.000 0.216 0.000 0.656 0.112 0.016
#> SRR1947519 3 0.3282 0.554950 0.092 0.000 0.840 0.004 0.056 0.008
#> SRR1947518 4 0.7019 0.187080 0.000 0.156 0.168 0.484 0.000 0.192
#> SRR1947517 5 0.0405 0.751406 0.008 0.000 0.000 0.000 0.988 0.004
#> SRR1947516 2 0.0865 0.691916 0.000 0.964 0.000 0.036 0.000 0.000
#> SRR1947515 3 0.3767 0.479027 0.000 0.012 0.708 0.004 0.000 0.276
#> SRR1947514 2 0.3543 0.404501 0.000 0.720 0.000 0.272 0.004 0.004
#> SRR1947513 1 0.1410 0.749119 0.944 0.000 0.008 0.044 0.000 0.004
#> SRR1947512 1 0.5202 0.612749 0.616 0.000 0.000 0.196 0.000 0.188
#> SRR1947511 4 0.3984 0.660681 0.000 0.224 0.000 0.736 0.028 0.012
#> SRR1947510 5 0.0547 0.745100 0.000 0.000 0.000 0.000 0.980 0.020
#> SRR1947572 6 0.5207 0.352243 0.000 0.108 0.016 0.236 0.000 0.640
#> SRR1947611 5 0.1838 0.744503 0.000 0.040 0.012 0.000 0.928 0.020
#> SRR1947509 1 0.0622 0.762634 0.980 0.000 0.008 0.000 0.012 0.000
#> SRR1947644 5 0.1267 0.758743 0.000 0.000 0.060 0.000 0.940 0.000
#> SRR1947643 4 0.4367 0.657271 0.000 0.228 0.000 0.712 0.044 0.016
#> SRR1947642 3 0.2494 0.558060 0.020 0.000 0.892 0.008 0.072 0.008
#> SRR1947640 4 0.6076 0.516260 0.120 0.100 0.016 0.644 0.000 0.120
#> SRR1947641 5 0.3189 0.709603 0.000 0.004 0.236 0.000 0.760 0.000
#> SRR1947639 2 0.3423 0.668296 0.000 0.812 0.000 0.100 0.000 0.088
#> SRR1947638 1 0.0260 0.766984 0.992 0.000 0.000 0.008 0.000 0.000
#> SRR1947637 2 0.4425 0.587770 0.000 0.724 0.004 0.000 0.164 0.108
#> SRR1947636 5 0.4648 0.556922 0.000 0.008 0.320 0.000 0.628 0.044
#> SRR1947635 4 0.7772 0.238752 0.064 0.160 0.068 0.428 0.004 0.276
#> SRR1947634 4 0.7507 0.360221 0.000 0.248 0.000 0.320 0.292 0.140
#> SRR1947633 5 0.1867 0.758339 0.000 0.000 0.064 0.000 0.916 0.020
#> SRR1947632 2 0.3490 0.589621 0.000 0.724 0.008 0.000 0.000 0.268
#> SRR1947631 3 0.6935 0.306458 0.056 0.008 0.456 0.004 0.308 0.168
#> SRR1947629 5 0.6385 0.302085 0.000 0.200 0.316 0.000 0.456 0.028
#> SRR1947630 5 0.6663 -0.391356 0.000 0.188 0.000 0.360 0.404 0.048
#> SRR1947627 1 0.4990 0.327423 0.616 0.000 0.108 0.000 0.276 0.000
#> SRR1947628 6 0.6165 0.275398 0.000 0.332 0.260 0.004 0.000 0.404
#> SRR1947626 2 0.4912 0.000676 0.000 0.568 0.004 0.368 0.000 0.060
#> SRR1947625 5 0.4840 0.474952 0.000 0.020 0.384 0.000 0.568 0.028
#> SRR1947624 2 0.5680 0.501717 0.000 0.656 0.000 0.132 0.092 0.120
#> SRR1947623 6 0.5806 0.131553 0.192 0.000 0.000 0.344 0.000 0.464
#> SRR1947622 2 0.3076 0.635265 0.000 0.760 0.000 0.000 0.000 0.240
#> SRR1947621 2 0.2145 0.706244 0.000 0.900 0.000 0.028 0.000 0.072
#> SRR1947620 1 0.0291 0.766873 0.992 0.000 0.004 0.004 0.000 0.000
#> SRR1947619 2 0.4736 0.400746 0.000 0.624 0.312 0.004 0.000 0.060
#> SRR1947617 2 0.1757 0.667262 0.000 0.916 0.000 0.076 0.000 0.008
#> SRR1947618 1 0.0551 0.764578 0.984 0.000 0.004 0.008 0.000 0.004
#> SRR1947616 2 0.1923 0.672654 0.000 0.916 0.000 0.064 0.004 0.016
#> SRR1947615 3 0.1854 0.554131 0.020 0.000 0.932 0.016 0.004 0.028
#> SRR1947614 5 0.0291 0.752150 0.000 0.000 0.004 0.000 0.992 0.004
#> SRR1947613 1 0.3703 0.733277 0.788 0.000 0.000 0.108 0.000 0.104
#> SRR1947610 4 0.6072 0.423330 0.000 0.276 0.048 0.552 0.000 0.124
#> SRR1947612 2 0.1285 0.687420 0.000 0.944 0.000 0.052 0.000 0.004
#> SRR1947609 6 0.7327 0.056912 0.244 0.004 0.276 0.080 0.004 0.392
#> SRR1947608 2 0.5025 0.156629 0.000 0.492 0.444 0.000 0.004 0.060
#> SRR1947606 5 0.3748 0.705812 0.012 0.000 0.224 0.000 0.748 0.016
#> SRR1947607 1 0.5186 0.614225 0.616 0.000 0.000 0.216 0.000 0.168
#> SRR1947604 3 0.4268 0.457011 0.000 0.004 0.684 0.040 0.000 0.272
#> SRR1947605 1 0.0806 0.769024 0.972 0.000 0.000 0.008 0.000 0.020
#> SRR1947603 2 0.0790 0.710586 0.000 0.968 0.000 0.000 0.000 0.032
#> SRR1947602 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947600 5 0.4235 0.655065 0.000 0.012 0.296 0.000 0.672 0.020
#> SRR1947601 2 0.0508 0.702017 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1947598 3 0.3411 0.516365 0.000 0.004 0.756 0.008 0.000 0.232
#> SRR1947599 3 0.6620 0.171802 0.236 0.000 0.448 0.024 0.008 0.284
#> SRR1947597 2 0.2340 0.691890 0.000 0.852 0.000 0.000 0.000 0.148
#> SRR1947596 3 0.4777 0.400581 0.000 0.024 0.628 0.032 0.000 0.316
#> SRR1947595 4 0.5366 0.632225 0.000 0.212 0.000 0.652 0.040 0.096
#> SRR1947594 1 0.4204 0.708250 0.740 0.000 0.000 0.128 0.000 0.132
#> SRR1947592 3 0.5470 0.219910 0.000 0.144 0.588 0.000 0.260 0.008
#> SRR1947591 2 0.1812 0.664130 0.000 0.912 0.000 0.080 0.000 0.008
#> SRR1947590 3 0.4660 0.403987 0.000 0.048 0.636 0.008 0.000 0.308
#> SRR1947588 1 0.4500 0.686465 0.708 0.000 0.000 0.144 0.000 0.148
#> SRR1947587 3 0.3500 0.571413 0.012 0.000 0.820 0.000 0.064 0.104
#> SRR1947586 4 0.5435 0.494368 0.000 0.304 0.020 0.584 0.000 0.092
#> SRR1947585 5 0.3371 0.723721 0.000 0.004 0.200 0.000 0.780 0.016
#> SRR1947584 1 0.4232 0.708317 0.736 0.000 0.000 0.116 0.000 0.148
#> SRR1947583 4 0.7034 0.304769 0.016 0.184 0.004 0.444 0.044 0.308
#> SRR1947582 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947580 4 0.5375 0.399424 0.000 0.404 0.020 0.512 0.000 0.064
#> SRR1947581 1 0.5123 0.622742 0.628 0.000 0.000 0.188 0.000 0.184
#> SRR1947576 2 0.5035 0.361464 0.000 0.556 0.000 0.000 0.360 0.084
#> SRR1947575 2 0.4035 0.610146 0.000 0.744 0.032 0.000 0.016 0.208
#> SRR1947579 5 0.0547 0.746526 0.000 0.000 0.000 0.000 0.980 0.020
#> SRR1947578 6 0.6156 0.389684 0.000 0.200 0.092 0.084 0.012 0.612
#> SRR1947573 2 0.6238 0.344785 0.000 0.508 0.028 0.000 0.264 0.200
#> SRR1947574 4 0.2113 0.568641 0.008 0.048 0.000 0.912 0.000 0.032
#> SRR1947571 6 0.5562 0.027330 0.000 0.088 0.412 0.016 0.000 0.484
#> SRR1947577 1 0.0551 0.764578 0.984 0.000 0.004 0.008 0.000 0.004
#> SRR1947570 1 0.4649 0.168046 0.572 0.000 0.380 0.000 0.000 0.048
#> SRR1947569 3 0.6451 -0.109615 0.000 0.188 0.424 0.000 0.356 0.032
#> SRR1947566 2 0.1007 0.709459 0.000 0.956 0.000 0.000 0.000 0.044
#> SRR1947567 4 0.5642 0.579977 0.000 0.288 0.024 0.576 0.000 0.112
#> SRR1947568 2 0.5603 0.159904 0.000 0.476 0.000 0.376 0.000 0.148
#> SRR1947564 2 0.0937 0.710083 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1947563 2 0.4990 0.509164 0.000 0.644 0.152 0.000 0.000 0.204
#> SRR1947562 6 0.5620 0.354046 0.000 0.272 0.172 0.004 0.000 0.552
#> SRR1947565 5 0.7030 0.159658 0.000 0.088 0.292 0.000 0.420 0.200
#> SRR1947559 2 0.1657 0.706149 0.000 0.928 0.000 0.016 0.000 0.056
#> SRR1947560 5 0.0891 0.742979 0.000 0.008 0.000 0.000 0.968 0.024
#> SRR1947561 2 0.0458 0.699946 0.000 0.984 0.000 0.016 0.000 0.000
#> SRR1947557 1 0.3701 0.733448 0.788 0.000 0.000 0.100 0.000 0.112
#> SRR1947558 3 0.2814 0.505798 0.000 0.000 0.820 0.000 0.172 0.008
#> SRR1947556 6 0.7338 0.202922 0.204 0.004 0.164 0.184 0.000 0.444
#> SRR1947553 4 0.5946 0.340833 0.000 0.356 0.040 0.508 0.000 0.096
#> SRR1947554 4 0.5742 -0.211476 0.356 0.000 0.000 0.468 0.000 0.176
#> SRR1947555 2 0.0777 0.708871 0.000 0.972 0.000 0.000 0.004 0.024
#> SRR1947550 6 0.6388 0.251240 0.000 0.148 0.048 0.276 0.004 0.524
#> SRR1947552 6 0.6428 -0.112395 0.036 0.060 0.432 0.028 0.008 0.436
#> SRR1947549 2 0.5366 0.483940 0.000 0.608 0.052 0.000 0.048 0.292
#> SRR1947551 5 0.2811 0.715600 0.000 0.084 0.012 0.000 0.868 0.036
#> SRR1947548 3 0.4354 0.470406 0.000 0.080 0.720 0.004 0.000 0.196
#> SRR1947506 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947507 1 0.2451 0.760083 0.884 0.000 0.000 0.060 0.000 0.056
#> SRR1947504 1 0.6053 0.327604 0.408 0.000 0.000 0.272 0.000 0.320
#> SRR1947503 1 0.5081 0.407834 0.640 0.000 0.088 0.008 0.004 0.260
#> SRR1947502 2 0.1757 0.666727 0.000 0.916 0.000 0.076 0.000 0.008
#> SRR1947501 2 0.2772 0.656966 0.000 0.816 0.004 0.000 0.000 0.180
#> SRR1947499 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947498 5 0.3756 0.613019 0.000 0.000 0.352 0.000 0.644 0.004
#> SRR1947508 1 0.2653 0.687304 0.868 0.000 0.100 0.000 0.028 0.004
#> SRR1947505 3 0.7442 0.095732 0.248 0.000 0.364 0.044 0.036 0.308
#> SRR1947497 4 0.2912 0.663150 0.000 0.216 0.000 0.784 0.000 0.000
#> SRR1947496 1 0.4086 0.715378 0.752 0.000 0.000 0.124 0.000 0.124
#> SRR1947495 4 0.3133 0.664467 0.000 0.212 0.000 0.780 0.000 0.008
#> SRR1947494 3 0.3878 0.503113 0.000 0.004 0.736 0.032 0.000 0.228
#> SRR1947493 1 0.0146 0.768171 0.996 0.000 0.004 0.000 0.000 0.000
#> SRR1947492 1 0.3375 0.743306 0.816 0.000 0.000 0.096 0.000 0.088
#> SRR1947500 4 0.5754 0.598001 0.052 0.160 0.012 0.656 0.000 0.120
#> SRR1947491 1 0.7171 -0.207613 0.356 0.008 0.012 0.336 0.032 0.256
#> SRR1947490 1 0.3068 0.750664 0.840 0.000 0.000 0.088 0.000 0.072
#> SRR1947489 3 0.4117 0.542551 0.084 0.000 0.752 0.000 0.004 0.160
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