Date: 2019-12-25 22:35:36 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 17467 rows and 159 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] 17467 159
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:skmeans | 3 | 1.000 | 0.969 | 0.988 | ** | 2 |
| CV:pam | 2 | 1.000 | 0.984 | 0.994 | ** | |
| ATC:kmeans | 2 | 1.000 | 0.982 | 0.993 | ** | |
| ATC:pam | 2 | 1.000 | 0.993 | 0.997 | ** | |
| ATC:mclust | 2 | 1.000 | 0.998 | 0.999 | ** | |
| ATC:NMF | 2 | 0.999 | 0.965 | 0.984 | ** | |
| MAD:skmeans | 2 | 0.986 | 0.952 | 0.981 | ** | |
| MAD:kmeans | 2 | 0.975 | 0.953 | 0.980 | ** | |
| MAD:NMF | 2 | 0.973 | 0.952 | 0.980 | ** | |
| CV:skmeans | 3 | 0.970 | 0.953 | 0.981 | ** | |
| CV:kmeans | 3 | 0.968 | 0.934 | 0.959 | ** | 2 |
| SD:NMF | 3 | 0.968 | 0.919 | 0.971 | ** | |
| CV:NMF | 3 | 0.959 | 0.951 | 0.980 | ** | 2 |
| ATC:hclust | 2 | 0.955 | 0.941 | 0.973 | ** | |
| MAD:mclust | 2 | 0.948 | 0.961 | 0.983 | * | |
| SD:kmeans | 2 | 0.936 | 0.927 | 0.944 | * | |
| ATC:skmeans | 4 | 0.909 | 0.889 | 0.953 | * | 2 |
| SD:mclust | 2 | 0.830 | 0.920 | 0.965 | ||
| SD:pam | 5 | 0.694 | 0.830 | 0.886 | ||
| CV:mclust | 2 | 0.634 | 0.896 | 0.946 | ||
| SD:hclust | 5 | 0.617 | 0.779 | 0.843 | ||
| MAD:hclust | 2 | 0.601 | 0.847 | 0.916 | ||
| CV:hclust | 3 | 0.594 | 0.811 | 0.891 | ||
| MAD:pam | 3 | 0.387 | 0.722 | 0.843 |
**: 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 0.717 0.878 0.936 0.401 0.621 0.621
#> CV:NMF 2 1.000 0.985 0.994 0.346 0.654 0.654
#> MAD:NMF 2 0.973 0.952 0.980 0.404 0.603 0.603
#> ATC:NMF 2 0.999 0.965 0.984 0.274 0.716 0.716
#> SD:skmeans 2 0.937 0.931 0.974 0.462 0.545 0.545
#> CV:skmeans 2 0.886 0.922 0.969 0.406 0.603 0.603
#> MAD:skmeans 2 0.986 0.952 0.981 0.479 0.524 0.524
#> ATC:skmeans 2 1.000 0.984 0.994 0.443 0.561 0.561
#> SD:mclust 2 0.830 0.920 0.965 0.501 0.498 0.498
#> CV:mclust 2 0.634 0.896 0.946 0.494 0.497 0.497
#> MAD:mclust 2 0.948 0.961 0.983 0.419 0.581 0.581
#> ATC:mclust 2 1.000 0.998 0.999 0.426 0.576 0.576
#> SD:kmeans 2 0.936 0.927 0.944 0.377 0.621 0.621
#> CV:kmeans 2 1.000 0.961 0.960 0.287 0.725 0.725
#> MAD:kmeans 2 0.975 0.953 0.980 0.407 0.592 0.592
#> ATC:kmeans 2 1.000 0.982 0.993 0.326 0.676 0.676
#> SD:pam 2 0.248 0.655 0.833 0.376 0.654 0.654
#> CV:pam 2 1.000 0.984 0.994 0.285 0.716 0.716
#> MAD:pam 2 0.257 0.685 0.834 0.461 0.511 0.511
#> ATC:pam 2 1.000 0.993 0.997 0.272 0.733 0.733
#> SD:hclust 2 0.488 0.844 0.906 0.299 0.716 0.716
#> CV:hclust 2 0.896 0.891 0.959 0.253 0.751 0.751
#> MAD:hclust 2 0.601 0.847 0.916 0.293 0.662 0.662
#> ATC:hclust 2 0.955 0.941 0.973 0.289 0.716 0.716
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.968 0.919 0.971 0.434 0.783 0.657
#> CV:NMF 3 0.959 0.951 0.980 0.728 0.699 0.556
#> MAD:NMF 3 0.406 0.605 0.770 0.433 0.899 0.836
#> ATC:NMF 3 0.499 0.717 0.864 1.113 0.623 0.490
#> SD:skmeans 3 1.000 0.969 0.988 0.347 0.792 0.633
#> CV:skmeans 3 0.970 0.953 0.981 0.525 0.734 0.575
#> MAD:skmeans 3 0.731 0.807 0.903 0.381 0.739 0.532
#> ATC:skmeans 3 0.651 0.668 0.842 0.409 0.811 0.665
#> SD:mclust 3 0.463 0.560 0.782 0.213 0.807 0.633
#> CV:mclust 3 0.691 0.800 0.885 0.279 0.819 0.653
#> MAD:mclust 3 0.818 0.892 0.951 0.592 0.720 0.530
#> ATC:mclust 3 0.607 0.645 0.821 0.492 0.755 0.574
#> SD:kmeans 3 0.645 0.872 0.903 0.458 0.809 0.694
#> CV:kmeans 3 0.968 0.934 0.959 0.905 0.727 0.623
#> MAD:kmeans 3 0.485 0.703 0.826 0.420 0.818 0.698
#> ATC:kmeans 3 0.652 0.770 0.903 0.747 0.710 0.584
#> SD:pam 3 0.551 0.725 0.879 0.596 0.671 0.525
#> CV:pam 3 0.451 0.678 0.837 0.868 0.754 0.658
#> MAD:pam 3 0.387 0.722 0.843 0.298 0.847 0.717
#> ATC:pam 3 0.531 0.695 0.867 1.180 0.651 0.524
#> SD:hclust 3 0.540 0.746 0.868 0.497 0.796 0.718
#> CV:hclust 3 0.594 0.811 0.891 0.445 0.898 0.865
#> MAD:hclust 3 0.658 0.783 0.900 0.274 0.955 0.932
#> ATC:hclust 3 0.756 0.844 0.889 0.445 0.811 0.738
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.600 0.534 0.749 0.1764 0.823 0.610
#> CV:NMF 4 0.651 0.732 0.861 0.1905 0.862 0.669
#> MAD:NMF 4 0.377 0.468 0.677 0.1667 0.811 0.659
#> ATC:NMF 4 0.468 0.759 0.824 0.0905 0.639 0.373
#> SD:skmeans 4 0.808 0.869 0.920 0.1945 0.855 0.628
#> CV:skmeans 4 0.642 0.614 0.792 0.1883 0.853 0.626
#> MAD:skmeans 4 0.630 0.636 0.783 0.1217 0.833 0.554
#> ATC:skmeans 4 0.909 0.889 0.953 0.1344 0.863 0.658
#> SD:mclust 4 0.704 0.783 0.886 0.1683 0.868 0.666
#> CV:mclust 4 0.635 0.697 0.816 0.1035 0.937 0.831
#> MAD:mclust 4 0.674 0.748 0.823 0.0813 0.966 0.903
#> ATC:mclust 4 0.474 0.532 0.739 0.1145 0.767 0.462
#> SD:kmeans 4 0.704 0.698 0.826 0.1921 0.918 0.816
#> CV:kmeans 4 0.643 0.675 0.829 0.1659 0.987 0.971
#> MAD:kmeans 4 0.458 0.552 0.728 0.1746 0.893 0.762
#> ATC:kmeans 4 0.719 0.754 0.875 0.1987 0.785 0.549
#> SD:pam 4 0.668 0.779 0.875 0.1653 0.751 0.473
#> CV:pam 4 0.521 0.625 0.800 0.2538 0.747 0.509
#> MAD:pam 4 0.413 0.484 0.689 0.1808 0.756 0.483
#> ATC:pam 4 0.548 0.461 0.742 0.1586 0.776 0.508
#> SD:hclust 4 0.586 0.662 0.819 0.0968 0.975 0.952
#> CV:hclust 4 0.558 0.394 0.726 0.2233 0.680 0.546
#> MAD:hclust 4 0.589 0.781 0.876 0.1875 0.994 0.991
#> ATC:hclust 4 0.510 0.718 0.841 0.2111 0.970 0.945
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.611 0.627 0.782 0.1181 0.764 0.399
#> CV:NMF 5 0.653 0.681 0.813 0.1100 0.824 0.484
#> MAD:NMF 5 0.555 0.597 0.744 0.1030 0.774 0.491
#> ATC:NMF 5 0.614 0.681 0.809 0.1676 0.809 0.542
#> SD:skmeans 5 0.799 0.812 0.872 0.0697 0.899 0.636
#> CV:skmeans 5 0.682 0.523 0.752 0.0780 0.928 0.733
#> MAD:skmeans 5 0.795 0.809 0.888 0.0675 0.912 0.679
#> ATC:skmeans 5 0.714 0.683 0.834 0.0525 0.960 0.867
#> SD:mclust 5 0.564 0.685 0.792 0.0326 0.968 0.893
#> CV:mclust 5 0.627 0.695 0.818 -0.0483 0.813 0.577
#> MAD:mclust 5 0.475 0.517 0.669 0.0131 0.858 0.600
#> ATC:mclust 5 0.476 0.534 0.698 0.0382 0.866 0.609
#> SD:kmeans 5 0.651 0.714 0.816 0.1101 0.880 0.690
#> CV:kmeans 5 0.530 0.597 0.737 0.1080 0.900 0.778
#> MAD:kmeans 5 0.534 0.490 0.657 0.0998 0.796 0.493
#> ATC:kmeans 5 0.798 0.778 0.881 0.0749 0.925 0.774
#> SD:pam 5 0.694 0.830 0.886 0.0704 0.937 0.791
#> CV:pam 5 0.566 0.591 0.787 0.1025 0.910 0.735
#> MAD:pam 5 0.640 0.689 0.828 0.0690 0.791 0.431
#> ATC:pam 5 0.664 0.615 0.832 0.0629 0.816 0.528
#> SD:hclust 5 0.617 0.779 0.843 0.0968 0.922 0.846
#> CV:hclust 5 0.532 0.676 0.803 0.1530 0.783 0.618
#> MAD:hclust 5 0.525 0.749 0.828 0.1564 0.993 0.989
#> ATC:hclust 5 0.482 0.691 0.829 0.0921 0.973 0.948
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.776 0.755 0.880 0.0468 0.880 0.580
#> CV:NMF 6 0.688 0.580 0.763 0.0432 0.935 0.709
#> MAD:NMF 6 0.642 0.655 0.820 0.0537 0.901 0.668
#> ATC:NMF 6 0.569 0.452 0.688 0.0622 0.880 0.586
#> SD:skmeans 6 0.809 0.713 0.857 0.0404 0.909 0.603
#> CV:skmeans 6 0.707 0.569 0.766 0.0406 0.904 0.600
#> MAD:skmeans 6 0.778 0.718 0.839 0.0428 0.937 0.715
#> ATC:skmeans 6 0.690 0.589 0.782 0.0499 0.965 0.877
#> SD:mclust 6 0.572 0.536 0.677 0.0233 0.942 0.796
#> CV:mclust 6 0.537 0.598 0.724 0.0860 0.928 0.822
#> MAD:mclust 6 0.446 0.460 0.610 0.0270 0.850 0.554
#> ATC:mclust 6 0.502 0.501 0.707 0.0395 0.925 0.725
#> SD:kmeans 6 0.652 0.610 0.770 0.0730 0.899 0.663
#> CV:kmeans 6 0.554 0.481 0.690 0.0758 0.895 0.715
#> MAD:kmeans 6 0.624 0.556 0.736 0.0648 0.893 0.601
#> ATC:kmeans 6 0.682 0.636 0.809 0.0625 0.933 0.767
#> SD:pam 6 0.698 0.523 0.735 0.0603 0.938 0.780
#> CV:pam 6 0.603 0.648 0.803 0.0297 0.950 0.833
#> MAD:pam 6 0.699 0.660 0.814 0.0583 0.895 0.613
#> ATC:pam 6 0.711 0.779 0.855 0.0736 0.879 0.625
#> SD:hclust 6 0.659 0.790 0.860 0.0908 0.960 0.911
#> CV:hclust 6 0.564 0.751 0.824 0.1815 0.920 0.835
#> MAD:hclust 6 0.433 0.460 0.743 0.1448 0.932 0.889
#> ATC:hclust 6 0.525 0.638 0.801 0.0756 0.938 0.876
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 17467 rows and 159 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 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 0.488 0.844 0.906 0.2992 0.716 0.716
#> 3 3 0.540 0.746 0.868 0.4967 0.796 0.718
#> 4 4 0.586 0.662 0.819 0.0968 0.975 0.952
#> 5 5 0.617 0.779 0.843 0.0968 0.922 0.846
#> 6 6 0.659 0.790 0.860 0.0908 0.960 0.911
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
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
#> SRR810713 2 0.0000 0.9133 0.000 1.000
#> SRR808862 2 0.7376 0.7487 0.208 0.792
#> SRR1500382 2 0.0376 0.9118 0.004 0.996
#> SRR1322683 2 0.0376 0.9121 0.004 0.996
#> SRR1329811 1 0.8207 0.9167 0.744 0.256
#> SRR1087297 2 0.0376 0.9118 0.004 0.996
#> SRR1072626 2 0.0000 0.9133 0.000 1.000
#> SRR1407428 1 0.6973 0.9173 0.812 0.188
#> SRR1321029 2 0.0000 0.9133 0.000 1.000
#> SRR1500282 1 0.7056 0.9181 0.808 0.192
#> SRR1100496 2 0.7376 0.7487 0.208 0.792
#> SRR1308778 2 0.0672 0.9097 0.008 0.992
#> SRR1445304 2 0.0000 0.9133 0.000 1.000
#> SRR1099378 2 0.2236 0.8869 0.036 0.964
#> SRR1347412 1 0.7219 0.7909 0.800 0.200
#> SRR1099694 2 0.0000 0.9133 0.000 1.000
#> SRR1088365 2 0.0000 0.9133 0.000 1.000
#> SRR1325752 2 0.0672 0.9097 0.008 0.992
#> SRR1416713 2 0.0000 0.9133 0.000 1.000
#> SRR1074474 1 0.6973 0.9173 0.812 0.188
#> SRR1469369 2 0.5408 0.8259 0.124 0.876
#> SRR1400507 2 0.0000 0.9133 0.000 1.000
#> SRR1378179 2 0.0000 0.9133 0.000 1.000
#> SRR1377905 2 0.0376 0.9122 0.004 0.996
#> SRR1089479 1 0.7056 0.9181 0.808 0.192
#> SRR1073365 2 0.0000 0.9133 0.000 1.000
#> SRR1500306 2 0.9608 0.0816 0.384 0.616
#> SRR1101566 2 0.0672 0.9114 0.008 0.992
#> SRR1350503 2 0.6623 0.7806 0.172 0.828
#> SRR1446007 2 0.6973 0.7642 0.188 0.812
#> SRR1102875 2 0.0000 0.9133 0.000 1.000
#> SRR1380293 2 0.0376 0.9118 0.004 0.996
#> SRR1331198 2 0.0000 0.9133 0.000 1.000
#> SRR1092686 2 0.6973 0.7642 0.188 0.812
#> SRR1069421 2 0.0000 0.9133 0.000 1.000
#> SRR1341650 2 0.0000 0.9133 0.000 1.000
#> SRR1357276 2 0.0376 0.9118 0.004 0.996
#> SRR1498374 2 0.0000 0.9133 0.000 1.000
#> SRR1093721 2 0.0000 0.9133 0.000 1.000
#> SRR1464660 1 0.8207 0.9167 0.744 0.256
#> SRR1402051 2 0.0000 0.9133 0.000 1.000
#> SRR1488734 2 0.0376 0.9118 0.004 0.996
#> SRR1082616 2 0.4161 0.8591 0.084 0.916
#> SRR1099427 2 0.0376 0.9121 0.004 0.996
#> SRR1453093 2 0.0672 0.9093 0.008 0.992
#> SRR1357064 1 0.8081 0.9205 0.752 0.248
#> SRR811237 2 0.0000 0.9133 0.000 1.000
#> SRR1100848 2 0.0000 0.9133 0.000 1.000
#> SRR1346755 2 0.0000 0.9133 0.000 1.000
#> SRR1472529 2 0.0000 0.9133 0.000 1.000
#> SRR1398905 2 0.9933 0.2591 0.452 0.548
#> SRR1082733 2 0.0000 0.9133 0.000 1.000
#> SRR1308035 2 0.6973 0.7642 0.188 0.812
#> SRR1466445 2 0.6887 0.7685 0.184 0.816
#> SRR1359080 2 0.0000 0.9133 0.000 1.000
#> SRR1455825 2 0.0000 0.9133 0.000 1.000
#> SRR1389300 2 0.0000 0.9133 0.000 1.000
#> SRR812246 2 0.6973 0.7642 0.188 0.812
#> SRR1076632 2 0.0000 0.9133 0.000 1.000
#> SRR1415567 1 0.6973 0.9173 0.812 0.188
#> SRR1331900 2 0.0000 0.9133 0.000 1.000
#> SRR1452099 2 0.0672 0.9094 0.008 0.992
#> SRR1352346 1 0.8016 0.9201 0.756 0.244
#> SRR1364034 2 0.0000 0.9133 0.000 1.000
#> SRR1086046 2 0.1633 0.8967 0.024 0.976
#> SRR1407226 1 0.8267 0.9147 0.740 0.260
#> SRR1319363 2 0.7056 0.6774 0.192 0.808
#> SRR1446961 2 0.5059 0.8363 0.112 0.888
#> SRR1486650 1 0.6973 0.9173 0.812 0.188
#> SRR1470152 1 0.8207 0.9167 0.744 0.256
#> SRR1454785 2 0.6973 0.7642 0.188 0.812
#> SRR1092329 2 0.0000 0.9133 0.000 1.000
#> SRR1091476 2 0.7056 0.7614 0.192 0.808
#> SRR1073775 2 0.0000 0.9133 0.000 1.000
#> SRR1366873 2 0.0000 0.9133 0.000 1.000
#> SRR1398114 2 0.0000 0.9133 0.000 1.000
#> SRR1089950 2 0.8955 0.3402 0.312 0.688
#> SRR1433272 2 0.1843 0.8942 0.028 0.972
#> SRR1075314 2 0.6712 0.7018 0.176 0.824
#> SRR1085590 2 0.5294 0.8293 0.120 0.880
#> SRR1100752 2 0.6973 0.7642 0.188 0.812
#> SRR1391494 2 0.0938 0.9082 0.012 0.988
#> SRR1333263 2 0.0376 0.9122 0.004 0.996
#> SRR1310231 2 0.0376 0.9118 0.004 0.996
#> SRR1094144 2 0.0000 0.9133 0.000 1.000
#> SRR1092160 2 0.0000 0.9133 0.000 1.000
#> SRR1320300 2 0.0000 0.9133 0.000 1.000
#> SRR1322747 2 0.3274 0.8772 0.060 0.940
#> SRR1432719 2 0.5519 0.8222 0.128 0.872
#> SRR1100728 2 0.0000 0.9133 0.000 1.000
#> SRR1087511 2 0.0376 0.9118 0.004 0.996
#> SRR1470336 2 0.9608 0.0816 0.384 0.616
#> SRR1322536 2 0.6712 0.7018 0.176 0.824
#> SRR1100824 1 0.8267 0.9147 0.740 0.260
#> SRR1085951 2 0.7376 0.7487 0.208 0.792
#> SRR1322046 2 0.0000 0.9133 0.000 1.000
#> SRR1316420 1 0.9248 0.8031 0.660 0.340
#> SRR1070913 2 0.0000 0.9133 0.000 1.000
#> SRR1345806 2 0.6887 0.7685 0.184 0.816
#> SRR1313872 2 0.0000 0.9133 0.000 1.000
#> SRR1337666 2 0.0376 0.9118 0.004 0.996
#> SRR1076823 2 0.7219 0.6623 0.200 0.800
#> SRR1093954 2 0.0000 0.9133 0.000 1.000
#> SRR1451921 2 0.2236 0.8862 0.036 0.964
#> SRR1491257 1 0.8267 0.9147 0.740 0.260
#> SRR1416979 2 0.0000 0.9133 0.000 1.000
#> SRR1419015 2 0.0672 0.9094 0.008 0.992
#> SRR817649 2 0.0376 0.9118 0.004 0.996
#> SRR1466376 2 0.0000 0.9133 0.000 1.000
#> SRR1392055 2 0.0376 0.9118 0.004 0.996
#> SRR1120913 2 0.0000 0.9133 0.000 1.000
#> SRR1120869 2 0.0000 0.9133 0.000 1.000
#> SRR1319419 2 0.6973 0.7642 0.188 0.812
#> SRR816495 2 0.6973 0.7642 0.188 0.812
#> SRR818694 2 0.0000 0.9133 0.000 1.000
#> SRR1465653 1 0.8207 0.9167 0.744 0.256
#> SRR1475952 1 0.6973 0.9173 0.812 0.188
#> SRR1465040 2 0.6973 0.7642 0.188 0.812
#> SRR1088461 2 0.0000 0.9133 0.000 1.000
#> SRR810129 2 0.0000 0.9133 0.000 1.000
#> SRR1400141 2 0.6973 0.7642 0.188 0.812
#> SRR1349585 1 0.8267 0.9147 0.740 0.260
#> SRR1437576 2 0.2603 0.8883 0.044 0.956
#> SRR814407 1 0.9393 0.7554 0.644 0.356
#> SRR1332403 2 0.0000 0.9133 0.000 1.000
#> SRR1099598 2 0.0000 0.9133 0.000 1.000
#> SRR1327723 2 0.0000 0.9133 0.000 1.000
#> SRR1392525 2 0.4161 0.8591 0.084 0.916
#> SRR1320536 1 0.6973 0.9173 0.812 0.188
#> SRR1083824 2 0.3733 0.8708 0.072 0.928
#> SRR1351390 2 0.8955 0.3402 0.312 0.688
#> SRR1309141 2 0.0376 0.9122 0.004 0.996
#> SRR1452803 2 0.0376 0.9118 0.004 0.996
#> SRR811631 2 0.1843 0.8988 0.028 0.972
#> SRR1485563 2 0.0672 0.9097 0.008 0.992
#> SRR1311531 2 0.6973 0.7642 0.188 0.812
#> SRR1353076 2 0.0000 0.9133 0.000 1.000
#> SRR1480831 2 0.0672 0.9093 0.008 0.992
#> SRR1083892 1 0.8081 0.9205 0.752 0.248
#> SRR809873 2 0.7056 0.6774 0.192 0.808
#> SRR1341854 2 0.0000 0.9133 0.000 1.000
#> SRR1399335 2 0.0000 0.9133 0.000 1.000
#> SRR1464209 1 0.8144 0.9191 0.748 0.252
#> SRR1389886 2 0.0000 0.9133 0.000 1.000
#> SRR1400730 1 0.9732 0.2639 0.596 0.404
#> SRR1448008 2 0.0672 0.9093 0.008 0.992
#> SRR1087606 2 0.8955 0.3402 0.312 0.688
#> SRR1445111 1 0.6973 0.9173 0.812 0.188
#> SRR816865 2 0.0000 0.9133 0.000 1.000
#> SRR1323360 2 0.6973 0.7642 0.188 0.812
#> SRR1417364 2 0.5059 0.8363 0.112 0.888
#> SRR1480329 2 0.0672 0.9096 0.008 0.992
#> SRR1403322 2 0.7219 0.6623 0.200 0.800
#> SRR1093625 1 0.6973 0.9173 0.812 0.188
#> SRR1479977 2 0.0000 0.9133 0.000 1.000
#> SRR1082035 2 0.9686 -0.0270 0.396 0.604
#> SRR1393046 2 0.1184 0.9060 0.016 0.984
#> SRR1466663 2 0.0938 0.9071 0.012 0.988
#> SRR1384456 1 0.6973 0.9173 0.812 0.188
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR808862 3 0.6095 0.8975 0.000 0.392 0.608
#> SRR1500382 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1322683 2 0.0237 0.8776 0.000 0.996 0.004
#> SRR1329811 1 0.7145 0.7159 0.692 0.236 0.072
#> SRR1087297 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1072626 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1321029 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1500282 1 0.0237 0.8045 0.996 0.000 0.004
#> SRR1100496 3 0.6095 0.8975 0.000 0.392 0.608
#> SRR1308778 2 0.0424 0.8752 0.008 0.992 0.000
#> SRR1445304 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1099378 2 0.1753 0.8344 0.048 0.952 0.000
#> SRR1347412 1 0.5397 0.6131 0.720 0.000 0.280
#> SRR1099694 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1325752 2 0.0424 0.8752 0.008 0.992 0.000
#> SRR1416713 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1469369 2 0.6154 -0.4301 0.000 0.592 0.408
#> SRR1400507 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1377905 2 0.0237 0.8774 0.000 0.996 0.004
#> SRR1089479 1 0.0237 0.8045 0.996 0.000 0.004
#> SRR1073365 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1500306 1 0.9509 0.3773 0.464 0.336 0.200
#> SRR1101566 2 0.0661 0.8736 0.004 0.988 0.008
#> SRR1350503 3 0.6215 0.8871 0.000 0.428 0.572
#> SRR1446007 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1102875 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1380293 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1331198 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1092686 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1069421 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1341650 2 0.0592 0.8721 0.012 0.988 0.000
#> SRR1357276 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1498374 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1093721 2 0.0237 0.8780 0.000 0.996 0.004
#> SRR1464660 1 0.7145 0.7159 0.692 0.236 0.072
#> SRR1402051 2 0.1289 0.8519 0.032 0.968 0.000
#> SRR1488734 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1082616 2 0.3500 0.7062 0.004 0.880 0.116
#> SRR1099427 2 0.0424 0.8745 0.000 0.992 0.008
#> SRR1453093 2 0.0661 0.8714 0.008 0.988 0.004
#> SRR1357064 1 0.5507 0.8047 0.808 0.136 0.056
#> SRR811237 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1100848 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1346755 2 0.0237 0.8775 0.000 0.996 0.004
#> SRR1472529 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1398905 3 0.0592 0.1605 0.000 0.012 0.988
#> SRR1082733 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1308035 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1466445 3 0.6180 0.9097 0.000 0.416 0.584
#> SRR1359080 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR812246 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1076632 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1415567 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1452099 2 0.2269 0.8226 0.016 0.944 0.040
#> SRR1352346 1 0.4931 0.7200 0.768 0.232 0.000
#> SRR1364034 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1086046 2 0.2301 0.8138 0.060 0.936 0.004
#> SRR1407226 1 0.5634 0.8016 0.800 0.144 0.056
#> SRR1319363 2 0.8763 0.1262 0.312 0.552 0.136
#> SRR1446961 2 0.6215 -0.5066 0.000 0.572 0.428
#> SRR1486650 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1470152 1 0.7145 0.7159 0.692 0.236 0.072
#> SRR1454785 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1092329 2 0.0237 0.8775 0.000 0.996 0.004
#> SRR1091476 3 0.6154 0.9119 0.000 0.408 0.592
#> SRR1073775 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1089950 2 0.9208 0.0493 0.264 0.532 0.204
#> SRR1433272 2 0.1163 0.8538 0.028 0.972 0.000
#> SRR1075314 2 0.8937 0.1117 0.308 0.540 0.152
#> SRR1085590 2 0.6026 -0.3012 0.000 0.624 0.376
#> SRR1100752 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1391494 2 0.0747 0.8665 0.000 0.984 0.016
#> SRR1333263 2 0.0237 0.8773 0.000 0.996 0.004
#> SRR1310231 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1094144 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1092160 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1322747 2 0.3192 0.7172 0.000 0.888 0.112
#> SRR1432719 2 0.6280 -0.6093 0.000 0.540 0.460
#> SRR1100728 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1087511 2 0.0475 0.8753 0.004 0.992 0.004
#> SRR1470336 1 0.9509 0.3773 0.464 0.336 0.200
#> SRR1322536 2 0.8937 0.1117 0.308 0.540 0.152
#> SRR1100824 1 0.5634 0.8016 0.800 0.144 0.056
#> SRR1085951 3 0.6095 0.8975 0.000 0.392 0.608
#> SRR1322046 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1316420 1 0.7278 0.7720 0.712 0.152 0.136
#> SRR1070913 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1345806 3 0.6180 0.9097 0.000 0.416 0.584
#> SRR1313872 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1337666 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1076823 2 0.9118 0.0177 0.352 0.496 0.152
#> SRR1093954 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1451921 2 0.4351 0.6477 0.168 0.828 0.004
#> SRR1491257 1 0.5696 0.7995 0.796 0.148 0.056
#> SRR1416979 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1419015 2 0.2878 0.7685 0.096 0.904 0.000
#> SRR817649 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1466376 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1392055 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR1120913 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1319419 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR816495 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR818694 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1465653 1 0.7145 0.7159 0.692 0.236 0.072
#> SRR1475952 1 0.0237 0.8046 0.996 0.000 0.004
#> SRR1465040 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1088461 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1400141 3 0.6192 0.9023 0.000 0.420 0.580
#> SRR1349585 1 0.5696 0.7995 0.796 0.148 0.056
#> SRR1437576 2 0.1860 0.8192 0.000 0.948 0.052
#> SRR814407 1 0.6783 0.6550 0.588 0.016 0.396
#> SRR1332403 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1099598 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1327723 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1392525 2 0.3500 0.7062 0.004 0.880 0.116
#> SRR1320536 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1083824 2 0.4521 0.5529 0.004 0.816 0.180
#> SRR1351390 2 0.9208 0.0493 0.264 0.532 0.204
#> SRR1309141 2 0.0237 0.8773 0.000 0.996 0.004
#> SRR1452803 2 0.0237 0.8781 0.004 0.996 0.000
#> SRR811631 2 0.1163 0.8521 0.000 0.972 0.028
#> SRR1485563 2 0.1411 0.8498 0.036 0.964 0.000
#> SRR1311531 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1353076 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1480831 2 0.0661 0.8714 0.008 0.988 0.004
#> SRR1083892 1 0.5507 0.8047 0.808 0.136 0.056
#> SRR809873 2 0.8763 0.1262 0.312 0.552 0.136
#> SRR1341854 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1464209 1 0.5571 0.8035 0.804 0.140 0.056
#> SRR1389886 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1400730 3 0.3816 0.0680 0.148 0.000 0.852
#> SRR1448008 2 0.0829 0.8682 0.012 0.984 0.004
#> SRR1087606 2 0.9208 0.0493 0.264 0.532 0.204
#> SRR1445111 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR816865 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1323360 3 0.6168 0.9147 0.000 0.412 0.588
#> SRR1417364 2 0.6215 -0.5066 0.000 0.572 0.428
#> SRR1480329 2 0.0661 0.8718 0.008 0.988 0.004
#> SRR1403322 2 0.9162 -0.0168 0.368 0.480 0.152
#> SRR1093625 1 0.0000 0.8056 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.8799 0.000 1.000 0.000
#> SRR1082035 2 0.7741 0.1003 0.376 0.568 0.056
#> SRR1393046 2 0.0892 0.8620 0.000 0.980 0.020
#> SRR1466663 2 0.1031 0.8621 0.024 0.976 0.000
#> SRR1384456 1 0.0000 0.8056 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR808862 3 0.6535 0.8653 0.036 0.392 0.548 0.024
#> SRR1500382 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1322683 2 0.0524 0.8535 0.000 0.988 0.008 0.004
#> SRR1329811 4 0.6927 0.5832 0.212 0.140 0.016 0.632
#> SRR1087297 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1072626 2 0.0336 0.8564 0.000 0.992 0.000 0.008
#> SRR1407428 1 0.4948 0.5072 0.560 0.000 0.000 0.440
#> SRR1321029 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1500282 1 0.4898 0.4977 0.584 0.000 0.000 0.416
#> SRR1100496 3 0.6535 0.8653 0.036 0.392 0.548 0.024
#> SRR1308778 2 0.0707 0.8497 0.000 0.980 0.000 0.020
#> SRR1445304 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1099378 2 0.2546 0.7879 0.028 0.912 0.000 0.060
#> SRR1347412 1 0.7687 0.2607 0.448 0.000 0.240 0.312
#> SRR1099694 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1088365 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1325752 2 0.0817 0.8473 0.000 0.976 0.000 0.024
#> SRR1416713 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1074474 1 0.4994 0.5077 0.520 0.000 0.000 0.480
#> SRR1469369 2 0.4888 -0.4401 0.000 0.588 0.412 0.000
#> SRR1400507 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1378179 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1377905 2 0.0188 0.8567 0.000 0.996 0.004 0.000
#> SRR1089479 1 0.4888 0.4963 0.588 0.000 0.000 0.412
#> SRR1073365 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1500306 1 0.9803 -0.0175 0.324 0.248 0.164 0.264
#> SRR1101566 2 0.0804 0.8509 0.000 0.980 0.012 0.008
#> SRR1350503 3 0.4916 0.8806 0.000 0.424 0.576 0.000
#> SRR1446007 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1102875 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1380293 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1331198 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1092686 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1069421 2 0.0707 0.8498 0.000 0.980 0.000 0.020
#> SRR1341650 2 0.1256 0.8402 0.008 0.964 0.000 0.028
#> SRR1357276 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1498374 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1093721 2 0.0524 0.8554 0.000 0.988 0.004 0.008
#> SRR1464660 4 0.6927 0.5832 0.212 0.140 0.016 0.632
#> SRR1402051 2 0.2385 0.7944 0.052 0.920 0.000 0.028
#> SRR1488734 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1082616 2 0.3719 0.6711 0.008 0.848 0.124 0.020
#> SRR1099427 2 0.0657 0.8508 0.000 0.984 0.012 0.004
#> SRR1453093 2 0.3398 0.7477 0.048 0.888 0.036 0.028
#> SRR1357064 4 0.1576 0.6978 0.004 0.048 0.000 0.948
#> SRR811237 2 0.0336 0.8564 0.000 0.992 0.000 0.008
#> SRR1100848 2 0.0336 0.8564 0.000 0.992 0.000 0.008
#> SRR1346755 2 0.0524 0.8551 0.000 0.988 0.004 0.008
#> SRR1472529 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1398905 3 0.3521 -0.0695 0.052 0.000 0.864 0.084
#> SRR1082733 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1308035 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1466445 3 0.4888 0.9014 0.000 0.412 0.588 0.000
#> SRR1359080 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1455825 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1389300 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR812246 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1076632 2 0.0592 0.8519 0.000 0.984 0.000 0.016
#> SRR1415567 1 0.4955 0.5064 0.556 0.000 0.000 0.444
#> SRR1331900 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1452099 2 0.2929 0.7807 0.024 0.908 0.040 0.028
#> SRR1352346 1 0.7220 -0.3634 0.440 0.140 0.000 0.420
#> SRR1364034 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1086046 2 0.4479 0.6738 0.092 0.832 0.036 0.040
#> SRR1407226 4 0.1807 0.6996 0.008 0.052 0.000 0.940
#> SRR1319363 2 0.9428 -0.2243 0.304 0.380 0.188 0.128
#> SRR1446961 2 0.4933 -0.5138 0.000 0.568 0.432 0.000
#> SRR1486650 1 0.4994 0.5077 0.520 0.000 0.000 0.480
#> SRR1470152 4 0.6927 0.5832 0.212 0.140 0.016 0.632
#> SRR1454785 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1092329 2 0.0524 0.8551 0.000 0.988 0.004 0.008
#> SRR1091476 3 0.4866 0.9028 0.000 0.404 0.596 0.000
#> SRR1073775 2 0.0524 0.8546 0.008 0.988 0.000 0.004
#> SRR1366873 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1398114 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1089950 2 0.8881 -0.1033 0.104 0.460 0.144 0.292
#> SRR1433272 2 0.1302 0.8289 0.000 0.956 0.000 0.044
#> SRR1075314 2 0.9038 -0.1968 0.328 0.392 0.204 0.076
#> SRR1085590 2 0.4790 -0.3101 0.000 0.620 0.380 0.000
#> SRR1100752 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1391494 2 0.0592 0.8483 0.000 0.984 0.016 0.000
#> SRR1333263 2 0.1004 0.8464 0.000 0.972 0.004 0.024
#> SRR1310231 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1094144 2 0.0707 0.8512 0.000 0.980 0.000 0.020
#> SRR1092160 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1320300 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1322747 2 0.2589 0.7019 0.000 0.884 0.116 0.000
#> SRR1432719 2 0.4981 -0.6151 0.000 0.536 0.464 0.000
#> SRR1100728 2 0.0707 0.8498 0.000 0.980 0.000 0.020
#> SRR1087511 2 0.0859 0.8507 0.008 0.980 0.004 0.008
#> SRR1470336 1 0.9803 -0.0175 0.324 0.248 0.164 0.264
#> SRR1322536 2 0.9038 -0.1968 0.328 0.392 0.204 0.076
#> SRR1100824 4 0.1807 0.6996 0.008 0.052 0.000 0.940
#> SRR1085951 3 0.6535 0.8653 0.036 0.392 0.548 0.024
#> SRR1322046 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1316420 4 0.3959 0.6078 0.016 0.052 0.076 0.856
#> SRR1070913 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1345806 3 0.4888 0.9014 0.000 0.412 0.588 0.000
#> SRR1313872 2 0.0336 0.8563 0.000 0.992 0.000 0.008
#> SRR1337666 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1076823 2 0.9449 -0.3259 0.340 0.340 0.200 0.120
#> SRR1093954 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1451921 2 0.5921 0.4950 0.180 0.728 0.036 0.056
#> SRR1491257 4 0.1557 0.7049 0.000 0.056 0.000 0.944
#> SRR1416979 2 0.0336 0.8564 0.000 0.992 0.000 0.008
#> SRR1419015 2 0.4083 0.6903 0.084 0.840 0.004 0.072
#> SRR817649 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1466376 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1392055 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR1120913 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1120869 2 0.0592 0.8519 0.000 0.984 0.000 0.016
#> SRR1319419 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR816495 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR818694 2 0.0524 0.8546 0.008 0.988 0.000 0.004
#> SRR1465653 4 0.6927 0.5832 0.212 0.140 0.016 0.632
#> SRR1475952 1 0.5203 0.5169 0.576 0.000 0.008 0.416
#> SRR1465040 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1088461 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR810129 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1400141 3 0.4898 0.8944 0.000 0.416 0.584 0.000
#> SRR1349585 4 0.1557 0.7049 0.000 0.056 0.000 0.944
#> SRR1437576 2 0.1557 0.8005 0.000 0.944 0.056 0.000
#> SRR814407 4 0.7905 -0.1577 0.304 0.000 0.332 0.364
#> SRR1332403 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1099598 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1327723 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1392525 2 0.3719 0.6711 0.008 0.848 0.124 0.020
#> SRR1320536 1 0.4994 0.5077 0.520 0.000 0.000 0.480
#> SRR1083824 2 0.3626 0.5400 0.000 0.812 0.184 0.004
#> SRR1351390 2 0.8881 -0.1033 0.104 0.460 0.144 0.292
#> SRR1309141 2 0.1004 0.8464 0.000 0.972 0.004 0.024
#> SRR1452803 2 0.0188 0.8575 0.000 0.996 0.000 0.004
#> SRR811631 2 0.0921 0.8357 0.000 0.972 0.028 0.000
#> SRR1485563 2 0.2466 0.7963 0.028 0.916 0.000 0.056
#> SRR1311531 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1353076 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1480831 2 0.3027 0.7639 0.040 0.904 0.032 0.024
#> SRR1083892 4 0.1576 0.6978 0.004 0.048 0.000 0.948
#> SRR809873 2 0.9428 -0.2243 0.304 0.380 0.188 0.128
#> SRR1341854 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1399335 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1464209 4 0.1661 0.7028 0.004 0.052 0.000 0.944
#> SRR1389886 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1400730 3 0.5008 -0.1070 0.040 0.000 0.732 0.228
#> SRR1448008 2 0.3296 0.7505 0.048 0.892 0.036 0.024
#> SRR1087606 2 0.8881 -0.1033 0.104 0.460 0.144 0.292
#> SRR1445111 1 0.4898 0.5247 0.584 0.000 0.000 0.416
#> SRR816865 2 0.0707 0.8498 0.000 0.980 0.000 0.020
#> SRR1323360 3 0.4877 0.9060 0.000 0.408 0.592 0.000
#> SRR1417364 2 0.4933 -0.5138 0.000 0.568 0.432 0.000
#> SRR1480329 2 0.0657 0.8527 0.000 0.984 0.004 0.012
#> SRR1403322 1 0.9432 0.0426 0.348 0.332 0.204 0.116
#> SRR1093625 1 0.4994 0.5077 0.520 0.000 0.000 0.480
#> SRR1479977 2 0.0000 0.8580 0.000 1.000 0.000 0.000
#> SRR1082035 2 0.6425 0.0123 0.068 0.508 0.000 0.424
#> SRR1393046 2 0.0707 0.8447 0.000 0.980 0.020 0.000
#> SRR1466663 2 0.1938 0.8145 0.012 0.936 0.000 0.052
#> SRR1384456 1 0.4994 0.5077 0.520 0.000 0.000 0.480
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR808862 3 0.5883 0.820 0.016 0.276 0.636 0.044 0.028
#> SRR1500382 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1322683 2 0.0566 0.911 0.000 0.984 0.012 0.004 0.000
#> SRR1329811 5 0.4239 0.650 0.012 0.032 0.028 0.116 0.812
#> SRR1087297 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1072626 2 0.0290 0.915 0.000 0.992 0.000 0.008 0.000
#> SRR1407428 1 0.3532 0.794 0.824 0.000 0.000 0.128 0.048
#> SRR1321029 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1500282 1 0.4981 0.736 0.704 0.000 0.000 0.188 0.108
#> SRR1100496 3 0.5883 0.820 0.016 0.276 0.636 0.044 0.028
#> SRR1308778 2 0.0671 0.909 0.000 0.980 0.000 0.004 0.016
#> SRR1445304 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1099378 2 0.2426 0.841 0.000 0.900 0.000 0.036 0.064
#> SRR1347412 1 0.6331 0.542 0.644 0.000 0.176 0.108 0.072
#> SRR1099694 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1088365 2 0.0290 0.915 0.000 0.992 0.000 0.000 0.008
#> SRR1325752 2 0.0865 0.905 0.000 0.972 0.000 0.004 0.024
#> SRR1416713 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1074474 1 0.1197 0.830 0.952 0.000 0.000 0.000 0.048
#> SRR1469369 2 0.4306 -0.514 0.000 0.508 0.492 0.000 0.000
#> SRR1400507 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1378179 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1377905 2 0.0162 0.916 0.000 0.996 0.004 0.000 0.000
#> SRR1089479 1 0.4967 0.735 0.704 0.000 0.000 0.192 0.104
#> SRR1073365 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1500306 4 0.7940 0.636 0.092 0.144 0.056 0.552 0.156
#> SRR1101566 2 0.0854 0.908 0.000 0.976 0.012 0.008 0.004
#> SRR1350503 3 0.3796 0.864 0.000 0.300 0.700 0.000 0.000
#> SRR1446007 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1102875 2 0.0290 0.915 0.000 0.992 0.000 0.000 0.008
#> SRR1380293 2 0.0290 0.916 0.000 0.992 0.000 0.000 0.008
#> SRR1331198 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1092686 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1069421 2 0.0865 0.905 0.000 0.972 0.000 0.004 0.024
#> SRR1341650 2 0.1329 0.895 0.008 0.956 0.000 0.004 0.032
#> SRR1357276 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1498374 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1093721 2 0.0404 0.914 0.000 0.988 0.000 0.012 0.000
#> SRR1464660 5 0.4239 0.650 0.012 0.032 0.028 0.116 0.812
#> SRR1402051 2 0.2144 0.851 0.000 0.912 0.000 0.068 0.020
#> SRR1488734 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1082616 2 0.3294 0.749 0.000 0.844 0.124 0.024 0.008
#> SRR1099427 2 0.0671 0.908 0.000 0.980 0.016 0.004 0.000
#> SRR1453093 2 0.2798 0.763 0.000 0.852 0.000 0.140 0.008
#> SRR1357064 5 0.4025 0.734 0.232 0.012 0.000 0.008 0.748
#> SRR811237 2 0.0290 0.915 0.000 0.992 0.000 0.008 0.000
#> SRR1100848 2 0.0290 0.915 0.000 0.992 0.000 0.008 0.000
#> SRR1346755 2 0.0451 0.914 0.000 0.988 0.004 0.008 0.000
#> SRR1472529 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1398905 3 0.4739 -0.059 0.020 0.000 0.712 0.240 0.028
#> SRR1082733 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1308035 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1466445 3 0.3730 0.877 0.000 0.288 0.712 0.000 0.000
#> SRR1359080 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1455825 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1389300 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR812246 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1076632 2 0.0671 0.909 0.000 0.980 0.000 0.004 0.016
#> SRR1415567 1 0.3485 0.795 0.828 0.000 0.000 0.124 0.048
#> SRR1331900 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1452099 2 0.3054 0.812 0.000 0.880 0.060 0.032 0.028
#> SRR1352346 5 0.6643 0.327 0.264 0.044 0.000 0.124 0.568
#> SRR1364034 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1086046 2 0.4347 0.520 0.012 0.712 0.000 0.264 0.012
#> SRR1407226 5 0.4380 0.731 0.240 0.020 0.000 0.012 0.728
#> SRR1319363 4 0.5636 0.761 0.072 0.208 0.000 0.680 0.040
#> SRR1446961 3 0.4294 0.609 0.000 0.468 0.532 0.000 0.000
#> SRR1486650 1 0.1197 0.830 0.952 0.000 0.000 0.000 0.048
#> SRR1470152 5 0.4239 0.650 0.012 0.032 0.028 0.116 0.812
#> SRR1454785 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1092329 2 0.0451 0.914 0.000 0.988 0.004 0.008 0.000
#> SRR1091476 3 0.3684 0.874 0.000 0.280 0.720 0.000 0.000
#> SRR1073775 2 0.0671 0.910 0.000 0.980 0.000 0.016 0.004
#> SRR1366873 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1398114 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1089950 2 0.8275 -0.377 0.040 0.436 0.056 0.236 0.232
#> SRR1433272 2 0.1430 0.882 0.000 0.944 0.000 0.004 0.052
#> SRR1075314 4 0.4619 0.767 0.056 0.212 0.000 0.728 0.004
#> SRR1085590 2 0.4210 -0.217 0.000 0.588 0.412 0.000 0.000
#> SRR1100752 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1391494 2 0.0510 0.909 0.000 0.984 0.016 0.000 0.000
#> SRR1333263 2 0.1116 0.901 0.000 0.964 0.004 0.004 0.028
#> SRR1310231 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1094144 2 0.0798 0.909 0.000 0.976 0.000 0.008 0.016
#> SRR1092160 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1320300 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1322747 2 0.2377 0.762 0.000 0.872 0.128 0.000 0.000
#> SRR1432719 3 0.4256 0.674 0.000 0.436 0.564 0.000 0.000
#> SRR1100728 2 0.0865 0.905 0.000 0.972 0.000 0.004 0.024
#> SRR1087511 2 0.0992 0.902 0.000 0.968 0.000 0.024 0.008
#> SRR1470336 4 0.7940 0.636 0.092 0.144 0.056 0.552 0.156
#> SRR1322536 4 0.4619 0.767 0.056 0.212 0.000 0.728 0.004
#> SRR1100824 5 0.4380 0.731 0.240 0.020 0.000 0.012 0.728
#> SRR1085951 3 0.5883 0.820 0.016 0.276 0.636 0.044 0.028
#> SRR1322046 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1316420 5 0.6720 0.614 0.224 0.020 0.044 0.100 0.612
#> SRR1070913 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1345806 3 0.3730 0.877 0.000 0.288 0.712 0.000 0.000
#> SRR1313872 2 0.0324 0.916 0.000 0.992 0.000 0.004 0.004
#> SRR1337666 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1076823 4 0.5176 0.766 0.104 0.172 0.000 0.712 0.012
#> SRR1093954 2 0.0290 0.915 0.000 0.992 0.000 0.000 0.008
#> SRR1451921 2 0.5526 0.229 0.080 0.608 0.000 0.308 0.004
#> SRR1491257 5 0.4324 0.736 0.232 0.020 0.000 0.012 0.736
#> SRR1416979 2 0.0290 0.915 0.000 0.992 0.000 0.008 0.000
#> SRR1419015 2 0.3877 0.754 0.044 0.832 0.000 0.088 0.036
#> SRR817649 2 0.0290 0.916 0.000 0.992 0.000 0.000 0.008
#> SRR1466376 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1392055 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR1120913 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1120869 2 0.0671 0.909 0.000 0.980 0.000 0.004 0.016
#> SRR1319419 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR816495 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR818694 2 0.0865 0.904 0.000 0.972 0.000 0.024 0.004
#> SRR1465653 5 0.4239 0.650 0.012 0.032 0.028 0.116 0.812
#> SRR1475952 1 0.2020 0.802 0.900 0.000 0.000 0.100 0.000
#> SRR1465040 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1088461 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR810129 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1400141 3 0.3752 0.872 0.000 0.292 0.708 0.000 0.000
#> SRR1349585 5 0.4324 0.736 0.232 0.020 0.000 0.012 0.736
#> SRR1437576 2 0.1410 0.864 0.000 0.940 0.060 0.000 0.000
#> SRR814407 4 0.8133 -0.230 0.296 0.000 0.264 0.340 0.100
#> SRR1332403 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1099598 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1327723 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1392525 2 0.3294 0.749 0.000 0.844 0.124 0.024 0.008
#> SRR1320536 1 0.1197 0.830 0.952 0.000 0.000 0.000 0.048
#> SRR1083824 2 0.3266 0.610 0.000 0.796 0.200 0.000 0.004
#> SRR1351390 2 0.8275 -0.377 0.040 0.436 0.056 0.236 0.232
#> SRR1309141 2 0.1116 0.901 0.000 0.964 0.004 0.004 0.028
#> SRR1452803 2 0.0162 0.916 0.000 0.996 0.000 0.000 0.004
#> SRR811631 2 0.0794 0.899 0.000 0.972 0.028 0.000 0.000
#> SRR1485563 2 0.2230 0.857 0.000 0.912 0.000 0.044 0.044
#> SRR1311531 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1353076 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1480831 2 0.2338 0.798 0.000 0.884 0.000 0.112 0.004
#> SRR1083892 5 0.4025 0.734 0.232 0.012 0.000 0.008 0.748
#> SRR809873 4 0.5636 0.761 0.072 0.208 0.000 0.680 0.040
#> SRR1341854 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1399335 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1464209 5 0.4124 0.737 0.232 0.016 0.000 0.008 0.744
#> SRR1389886 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 3 0.5516 -0.087 0.020 0.000 0.684 0.100 0.196
#> SRR1448008 2 0.2488 0.785 0.000 0.872 0.000 0.124 0.004
#> SRR1087606 2 0.8275 -0.377 0.040 0.436 0.056 0.236 0.232
#> SRR1445111 1 0.3226 0.803 0.852 0.000 0.000 0.088 0.060
#> SRR816865 2 0.0865 0.905 0.000 0.972 0.000 0.004 0.024
#> SRR1323360 3 0.3707 0.879 0.000 0.284 0.716 0.000 0.000
#> SRR1417364 3 0.4294 0.609 0.000 0.468 0.532 0.000 0.000
#> SRR1480329 2 0.0579 0.912 0.000 0.984 0.000 0.008 0.008
#> SRR1403322 4 0.5143 0.756 0.124 0.168 0.000 0.704 0.004
#> SRR1093625 1 0.1197 0.830 0.952 0.000 0.000 0.000 0.048
#> SRR1479977 2 0.0000 0.917 0.000 1.000 0.000 0.000 0.000
#> SRR1082035 2 0.6404 -0.153 0.052 0.492 0.000 0.056 0.400
#> SRR1393046 2 0.0609 0.906 0.000 0.980 0.020 0.000 0.000
#> SRR1466663 2 0.1800 0.873 0.000 0.932 0.000 0.020 0.048
#> SRR1384456 1 0.1197 0.830 0.952 0.000 0.000 0.000 0.048
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR808862 3 0.3994 0.7982 0.000 0.116 0.776 0.000 0.100 0.008
#> SRR1500382 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1322683 2 0.0508 0.9398 0.000 0.984 0.012 0.000 0.000 0.004
#> SRR1329811 4 0.0000 0.8921 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1087297 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1072626 2 0.0291 0.9430 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1407428 1 0.4125 0.7366 0.736 0.000 0.000 0.000 0.184 0.080
#> SRR1321029 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1500282 1 0.5646 0.6122 0.524 0.000 0.000 0.004 0.320 0.152
#> SRR1100496 3 0.3994 0.7982 0.000 0.116 0.776 0.000 0.100 0.008
#> SRR1308778 2 0.0603 0.9390 0.000 0.980 0.000 0.000 0.016 0.004
#> SRR1445304 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1099378 2 0.3125 0.8319 0.000 0.856 0.000 0.024 0.064 0.056
#> SRR1347412 1 0.6442 0.5237 0.548 0.000 0.144 0.004 0.236 0.068
#> SRR1099694 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1088365 2 0.0291 0.9429 0.000 0.992 0.000 0.004 0.004 0.000
#> SRR1325752 2 0.0951 0.9337 0.000 0.968 0.000 0.008 0.020 0.004
#> SRR1416713 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1074474 1 0.0146 0.7884 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1469369 3 0.3782 0.4659 0.000 0.412 0.588 0.000 0.000 0.000
#> SRR1400507 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1378179 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1377905 2 0.0146 0.9437 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1089479 1 0.5674 0.6093 0.520 0.000 0.000 0.004 0.320 0.156
#> SRR1073365 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1500306 6 0.5108 0.5702 0.008 0.004 0.012 0.036 0.356 0.584
#> SRR1101566 2 0.0881 0.9346 0.000 0.972 0.012 0.000 0.008 0.008
#> SRR1350503 3 0.2219 0.8518 0.000 0.136 0.864 0.000 0.000 0.000
#> SRR1446007 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1102875 2 0.0291 0.9429 0.000 0.992 0.000 0.004 0.004 0.000
#> SRR1380293 2 0.0405 0.9426 0.000 0.988 0.000 0.008 0.004 0.000
#> SRR1331198 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1092686 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1069421 2 0.0951 0.9330 0.000 0.968 0.000 0.008 0.020 0.004
#> SRR1341650 2 0.1282 0.9263 0.004 0.956 0.000 0.012 0.024 0.004
#> SRR1357276 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1498374 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1093721 2 0.0405 0.9422 0.000 0.988 0.000 0.000 0.008 0.004
#> SRR1464660 4 0.0000 0.8921 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1402051 2 0.2721 0.8413 0.000 0.868 0.000 0.004 0.040 0.088
#> SRR1488734 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1082616 2 0.3153 0.7922 0.000 0.832 0.128 0.000 0.008 0.032
#> SRR1099427 2 0.0717 0.9361 0.000 0.976 0.016 0.000 0.000 0.008
#> SRR1453093 2 0.3109 0.7070 0.000 0.772 0.000 0.000 0.004 0.224
#> SRR1357064 5 0.5738 0.3302 0.144 0.004 0.000 0.420 0.432 0.000
#> SRR811237 2 0.0291 0.9430 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1100848 2 0.0291 0.9430 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1346755 2 0.0551 0.9410 0.000 0.984 0.004 0.000 0.004 0.008
#> SRR1472529 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1398905 3 0.4603 0.0855 0.000 0.000 0.544 0.000 0.416 0.040
#> SRR1082733 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1308035 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1466445 3 0.2092 0.8622 0.000 0.124 0.876 0.000 0.000 0.000
#> SRR1359080 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1455825 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1389300 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR812246 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1076632 2 0.0767 0.9369 0.000 0.976 0.000 0.008 0.012 0.004
#> SRR1415567 1 0.3992 0.7404 0.748 0.000 0.000 0.000 0.180 0.072
#> SRR1331900 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1452099 2 0.3894 0.7792 0.000 0.816 0.080 0.008 0.044 0.052
#> SRR1352346 4 0.3740 0.5062 0.252 0.008 0.000 0.728 0.000 0.012
#> SRR1364034 2 0.0146 0.9438 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1086046 2 0.4234 0.3830 0.000 0.608 0.000 0.004 0.016 0.372
#> SRR1407226 5 0.6063 0.3552 0.148 0.012 0.000 0.400 0.436 0.004
#> SRR1319363 6 0.3634 0.7648 0.060 0.048 0.000 0.004 0.056 0.832
#> SRR1446961 3 0.3531 0.6097 0.000 0.328 0.672 0.000 0.000 0.000
#> SRR1486650 1 0.0146 0.7884 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1470152 4 0.0000 0.8921 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1454785 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1092329 2 0.0436 0.9423 0.000 0.988 0.004 0.000 0.004 0.004
#> SRR1091476 3 0.2003 0.8583 0.000 0.116 0.884 0.000 0.000 0.000
#> SRR1073775 2 0.0937 0.9271 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1366873 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1398114 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1089950 5 0.6941 0.1422 0.000 0.380 0.012 0.072 0.404 0.132
#> SRR1433272 2 0.1562 0.9134 0.000 0.940 0.000 0.024 0.032 0.004
#> SRR1075314 6 0.1149 0.7891 0.008 0.008 0.000 0.000 0.024 0.960
#> SRR1085590 2 0.3868 -0.2150 0.000 0.508 0.492 0.000 0.000 0.000
#> SRR1100752 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1391494 2 0.0458 0.9385 0.000 0.984 0.016 0.000 0.000 0.000
#> SRR1333263 2 0.1096 0.9315 0.000 0.964 0.004 0.008 0.020 0.004
#> SRR1310231 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1094144 2 0.0881 0.9362 0.000 0.972 0.000 0.008 0.012 0.008
#> SRR1092160 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1320300 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1322747 2 0.2178 0.8175 0.000 0.868 0.132 0.000 0.000 0.000
#> SRR1432719 3 0.3371 0.6602 0.000 0.292 0.708 0.000 0.000 0.000
#> SRR1100728 2 0.0951 0.9330 0.000 0.968 0.000 0.008 0.020 0.004
#> SRR1087511 2 0.1333 0.9159 0.000 0.944 0.000 0.000 0.008 0.048
#> SRR1470336 6 0.5108 0.5702 0.008 0.004 0.012 0.036 0.356 0.584
#> SRR1322536 6 0.1149 0.7891 0.008 0.008 0.000 0.000 0.024 0.960
#> SRR1100824 5 0.6063 0.3552 0.148 0.012 0.000 0.400 0.436 0.004
#> SRR1085951 3 0.3994 0.7982 0.000 0.116 0.776 0.000 0.100 0.008
#> SRR1322046 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1316420 5 0.6229 0.2780 0.140 0.012 0.008 0.296 0.532 0.012
#> SRR1070913 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1345806 3 0.2092 0.8622 0.000 0.124 0.876 0.000 0.000 0.000
#> SRR1313872 2 0.0260 0.9433 0.000 0.992 0.000 0.000 0.008 0.000
#> SRR1337666 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1076823 6 0.2577 0.7859 0.072 0.012 0.000 0.000 0.032 0.884
#> SRR1093954 2 0.0291 0.9429 0.000 0.992 0.000 0.004 0.004 0.000
#> SRR1451921 2 0.4846 0.0643 0.032 0.496 0.000 0.000 0.012 0.460
#> SRR1491257 5 0.6042 0.3538 0.144 0.012 0.000 0.408 0.432 0.004
#> SRR1416979 2 0.0291 0.9430 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1419015 2 0.3624 0.8004 0.036 0.828 0.000 0.004 0.044 0.088
#> SRR817649 2 0.0405 0.9426 0.000 0.988 0.000 0.008 0.004 0.000
#> SRR1466376 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1392055 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1120913 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1120869 2 0.0767 0.9369 0.000 0.976 0.000 0.008 0.012 0.004
#> SRR1319419 3 0.2092 0.8621 0.000 0.124 0.876 0.000 0.000 0.000
#> SRR816495 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR818694 2 0.1075 0.9211 0.000 0.952 0.000 0.000 0.000 0.048
#> SRR1465653 4 0.0000 0.8921 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1475952 1 0.2312 0.7422 0.876 0.000 0.000 0.000 0.012 0.112
#> SRR1465040 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1088461 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR810129 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1400141 3 0.2135 0.8590 0.000 0.128 0.872 0.000 0.000 0.000
#> SRR1349585 5 0.6042 0.3538 0.144 0.012 0.000 0.408 0.432 0.004
#> SRR1437576 2 0.1267 0.9028 0.000 0.940 0.060 0.000 0.000 0.000
#> SRR814407 5 0.6258 -0.2431 0.108 0.000 0.116 0.000 0.584 0.192
#> SRR1332403 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1099598 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1327723 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1392525 2 0.3153 0.7922 0.000 0.832 0.128 0.000 0.008 0.032
#> SRR1320536 1 0.0146 0.7884 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1083824 2 0.3189 0.6365 0.000 0.760 0.236 0.000 0.004 0.000
#> SRR1351390 5 0.6941 0.1422 0.000 0.380 0.012 0.072 0.404 0.132
#> SRR1309141 2 0.1096 0.9315 0.000 0.964 0.004 0.008 0.020 0.004
#> SRR1452803 2 0.0146 0.9439 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR811631 2 0.0713 0.9306 0.000 0.972 0.028 0.000 0.000 0.000
#> SRR1485563 2 0.2074 0.8920 0.000 0.912 0.000 0.004 0.048 0.036
#> SRR1311531 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1353076 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1480831 2 0.2703 0.7719 0.000 0.824 0.000 0.000 0.004 0.172
#> SRR1083892 5 0.5738 0.3302 0.144 0.004 0.000 0.420 0.432 0.000
#> SRR809873 6 0.3634 0.7648 0.060 0.048 0.000 0.004 0.056 0.832
#> SRR1341854 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1399335 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1464209 5 0.5833 0.3420 0.144 0.008 0.000 0.416 0.432 0.000
#> SRR1389886 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1400730 3 0.5956 0.0217 0.000 0.000 0.536 0.196 0.252 0.016
#> SRR1448008 2 0.2882 0.7571 0.000 0.812 0.000 0.000 0.008 0.180
#> SRR1087606 5 0.6941 0.1422 0.000 0.380 0.012 0.072 0.404 0.132
#> SRR1445111 1 0.4844 0.6991 0.672 0.000 0.000 0.004 0.204 0.120
#> SRR816865 2 0.0951 0.9330 0.000 0.968 0.000 0.008 0.020 0.004
#> SRR1323360 3 0.2048 0.8635 0.000 0.120 0.880 0.000 0.000 0.000
#> SRR1417364 3 0.3531 0.6097 0.000 0.328 0.672 0.000 0.000 0.000
#> SRR1480329 2 0.0622 0.9387 0.000 0.980 0.000 0.000 0.012 0.008
#> SRR1403322 6 0.2294 0.7787 0.076 0.008 0.000 0.000 0.020 0.896
#> SRR1093625 1 0.0146 0.7884 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1479977 2 0.0000 0.9442 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1082035 2 0.7202 -0.1043 0.048 0.492 0.000 0.220 0.192 0.048
#> SRR1393046 2 0.0547 0.9363 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1466663 2 0.1672 0.9070 0.000 0.932 0.000 0.004 0.048 0.016
#> SRR1384456 1 0.0146 0.7884 0.996 0.000 0.000 0.004 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", "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 17467 rows and 159 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.936 0.927 0.944 0.377 0.621 0.621
#> 3 3 0.645 0.872 0.903 0.458 0.809 0.694
#> 4 4 0.704 0.698 0.826 0.192 0.918 0.816
#> 5 5 0.651 0.714 0.816 0.110 0.880 0.690
#> 6 6 0.652 0.610 0.770 0.073 0.899 0.663
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
#> SRR810713 2 0.0000 0.959 0.000 1.000
#> SRR808862 2 0.9833 0.374 0.424 0.576
#> SRR1500382 2 0.0000 0.959 0.000 1.000
#> SRR1322683 2 0.0000 0.959 0.000 1.000
#> SRR1329811 1 0.4562 0.965 0.904 0.096
#> SRR1087297 2 0.0000 0.959 0.000 1.000
#> SRR1072626 2 0.0000 0.959 0.000 1.000
#> SRR1407428 1 0.4562 0.965 0.904 0.096
#> SRR1321029 2 0.0000 0.959 0.000 1.000
#> SRR1500282 1 0.4562 0.965 0.904 0.096
#> SRR1100496 2 0.4562 0.902 0.096 0.904
#> SRR1308778 2 0.0000 0.959 0.000 1.000
#> SRR1445304 2 0.0000 0.959 0.000 1.000
#> SRR1099378 2 0.6438 0.769 0.164 0.836
#> SRR1347412 1 0.3431 0.937 0.936 0.064
#> SRR1099694 2 0.0000 0.959 0.000 1.000
#> SRR1088365 2 0.0000 0.959 0.000 1.000
#> SRR1325752 2 0.2778 0.918 0.048 0.952
#> SRR1416713 2 0.0000 0.959 0.000 1.000
#> SRR1074474 1 0.4562 0.965 0.904 0.096
#> SRR1469369 2 0.4562 0.902 0.096 0.904
#> SRR1400507 2 0.0000 0.959 0.000 1.000
#> SRR1378179 2 0.0000 0.959 0.000 1.000
#> SRR1377905 2 0.0000 0.959 0.000 1.000
#> SRR1089479 1 0.4562 0.965 0.904 0.096
#> SRR1073365 2 0.0000 0.959 0.000 1.000
#> SRR1500306 1 0.4562 0.965 0.904 0.096
#> SRR1101566 2 0.0000 0.959 0.000 1.000
#> SRR1350503 2 0.4562 0.902 0.096 0.904
#> SRR1446007 2 0.4562 0.902 0.096 0.904
#> SRR1102875 2 0.0000 0.959 0.000 1.000
#> SRR1380293 2 0.0000 0.959 0.000 1.000
#> SRR1331198 2 0.0000 0.959 0.000 1.000
#> SRR1092686 2 0.4562 0.902 0.096 0.904
#> SRR1069421 2 0.0000 0.959 0.000 1.000
#> SRR1341650 2 0.3733 0.893 0.072 0.928
#> SRR1357276 2 0.0000 0.959 0.000 1.000
#> SRR1498374 2 0.0000 0.959 0.000 1.000
#> SRR1093721 2 0.0000 0.959 0.000 1.000
#> SRR1464660 1 0.4562 0.965 0.904 0.096
#> SRR1402051 2 0.2603 0.922 0.044 0.956
#> SRR1488734 2 0.0000 0.959 0.000 1.000
#> SRR1082616 2 0.4562 0.902 0.096 0.904
#> SRR1099427 2 0.0000 0.959 0.000 1.000
#> SRR1453093 2 0.0000 0.959 0.000 1.000
#> SRR1357064 1 0.4562 0.965 0.904 0.096
#> SRR811237 2 0.0000 0.959 0.000 1.000
#> SRR1100848 2 0.0000 0.959 0.000 1.000
#> SRR1346755 2 0.0000 0.959 0.000 1.000
#> SRR1472529 2 0.0000 0.959 0.000 1.000
#> SRR1398905 1 0.0000 0.878 1.000 0.000
#> SRR1082733 2 0.0000 0.959 0.000 1.000
#> SRR1308035 2 0.4562 0.902 0.096 0.904
#> SRR1466445 2 0.4562 0.902 0.096 0.904
#> SRR1359080 2 0.0000 0.959 0.000 1.000
#> SRR1455825 2 0.0000 0.959 0.000 1.000
#> SRR1389300 2 0.0000 0.959 0.000 1.000
#> SRR812246 2 0.4562 0.902 0.096 0.904
#> SRR1076632 2 0.0000 0.959 0.000 1.000
#> SRR1415567 1 0.4562 0.965 0.904 0.096
#> SRR1331900 2 0.0000 0.959 0.000 1.000
#> SRR1452099 2 0.2423 0.926 0.040 0.960
#> SRR1352346 1 0.7883 0.817 0.764 0.236
#> SRR1364034 2 0.0000 0.959 0.000 1.000
#> SRR1086046 2 0.0672 0.953 0.008 0.992
#> SRR1407226 1 0.4562 0.965 0.904 0.096
#> SRR1319363 1 0.7745 0.832 0.772 0.228
#> SRR1446961 2 0.4562 0.902 0.096 0.904
#> SRR1486650 1 0.4562 0.965 0.904 0.096
#> SRR1470152 1 0.4562 0.965 0.904 0.096
#> SRR1454785 2 0.4562 0.902 0.096 0.904
#> SRR1092329 2 0.0000 0.959 0.000 1.000
#> SRR1091476 2 0.4562 0.902 0.096 0.904
#> SRR1073775 2 0.0000 0.959 0.000 1.000
#> SRR1366873 2 0.0000 0.959 0.000 1.000
#> SRR1398114 2 0.0000 0.959 0.000 1.000
#> SRR1089950 1 0.4562 0.965 0.904 0.096
#> SRR1433272 2 0.0000 0.959 0.000 1.000
#> SRR1075314 1 0.8608 0.747 0.716 0.284
#> SRR1085590 2 0.4562 0.902 0.096 0.904
#> SRR1100752 2 0.4562 0.902 0.096 0.904
#> SRR1391494 2 0.0000 0.959 0.000 1.000
#> SRR1333263 2 0.2236 0.940 0.036 0.964
#> SRR1310231 2 0.0000 0.959 0.000 1.000
#> SRR1094144 2 0.0000 0.959 0.000 1.000
#> SRR1092160 2 0.0000 0.959 0.000 1.000
#> SRR1320300 2 0.0000 0.959 0.000 1.000
#> SRR1322747 2 0.4298 0.907 0.088 0.912
#> SRR1432719 2 0.4562 0.902 0.096 0.904
#> SRR1100728 2 0.0000 0.959 0.000 1.000
#> SRR1087511 2 0.0000 0.959 0.000 1.000
#> SRR1470336 1 0.4562 0.965 0.904 0.096
#> SRR1322536 1 0.7602 0.842 0.780 0.220
#> SRR1100824 1 0.4562 0.965 0.904 0.096
#> SRR1085951 2 0.9833 0.374 0.424 0.576
#> SRR1322046 2 0.0000 0.959 0.000 1.000
#> SRR1316420 1 0.4562 0.965 0.904 0.096
#> SRR1070913 2 0.0000 0.959 0.000 1.000
#> SRR1345806 2 0.4562 0.902 0.096 0.904
#> SRR1313872 2 0.0000 0.959 0.000 1.000
#> SRR1337666 2 0.0000 0.959 0.000 1.000
#> SRR1076823 1 0.7602 0.842 0.780 0.220
#> SRR1093954 2 0.0000 0.959 0.000 1.000
#> SRR1451921 2 0.8909 0.479 0.308 0.692
#> SRR1491257 1 0.4562 0.965 0.904 0.096
#> SRR1416979 2 0.0000 0.959 0.000 1.000
#> SRR1419015 2 0.9323 0.370 0.348 0.652
#> SRR817649 2 0.0000 0.959 0.000 1.000
#> SRR1466376 2 0.0000 0.959 0.000 1.000
#> SRR1392055 2 0.0000 0.959 0.000 1.000
#> SRR1120913 2 0.0000 0.959 0.000 1.000
#> SRR1120869 2 0.0000 0.959 0.000 1.000
#> SRR1319419 2 0.4562 0.902 0.096 0.904
#> SRR816495 2 0.4562 0.902 0.096 0.904
#> SRR818694 2 0.0000 0.959 0.000 1.000
#> SRR1465653 1 0.4562 0.965 0.904 0.096
#> SRR1475952 1 0.4562 0.965 0.904 0.096
#> SRR1465040 2 0.4562 0.902 0.096 0.904
#> SRR1088461 2 0.0000 0.959 0.000 1.000
#> SRR810129 2 0.0000 0.959 0.000 1.000
#> SRR1400141 2 0.4562 0.902 0.096 0.904
#> SRR1349585 1 0.4562 0.965 0.904 0.096
#> SRR1437576 2 0.0000 0.959 0.000 1.000
#> SRR814407 1 0.4562 0.965 0.904 0.096
#> SRR1332403 2 0.0000 0.959 0.000 1.000
#> SRR1099598 2 0.0000 0.959 0.000 1.000
#> SRR1327723 2 0.0000 0.959 0.000 1.000
#> SRR1392525 2 0.2423 0.937 0.040 0.960
#> SRR1320536 1 0.4562 0.965 0.904 0.096
#> SRR1083824 2 0.3274 0.925 0.060 0.940
#> SRR1351390 1 0.4562 0.965 0.904 0.096
#> SRR1309141 2 0.2236 0.940 0.036 0.964
#> SRR1452803 2 0.0000 0.959 0.000 1.000
#> SRR811631 2 0.2043 0.942 0.032 0.968
#> SRR1485563 2 0.0000 0.959 0.000 1.000
#> SRR1311531 2 0.4562 0.902 0.096 0.904
#> SRR1353076 2 0.0000 0.959 0.000 1.000
#> SRR1480831 2 0.0000 0.959 0.000 1.000
#> SRR1083892 1 0.4562 0.965 0.904 0.096
#> SRR809873 1 0.9323 0.624 0.652 0.348
#> SRR1341854 2 0.0000 0.959 0.000 1.000
#> SRR1399335 2 0.0000 0.959 0.000 1.000
#> SRR1464209 1 0.4562 0.965 0.904 0.096
#> SRR1389886 2 0.0000 0.959 0.000 1.000
#> SRR1400730 1 0.0000 0.878 1.000 0.000
#> SRR1448008 2 0.0000 0.959 0.000 1.000
#> SRR1087606 1 0.4562 0.965 0.904 0.096
#> SRR1445111 1 0.4562 0.965 0.904 0.096
#> SRR816865 2 0.0000 0.959 0.000 1.000
#> SRR1323360 2 0.4562 0.902 0.096 0.904
#> SRR1417364 2 0.4562 0.902 0.096 0.904
#> SRR1480329 2 0.0000 0.959 0.000 1.000
#> SRR1403322 1 0.4562 0.965 0.904 0.096
#> SRR1093625 1 0.4562 0.965 0.904 0.096
#> SRR1479977 2 0.0000 0.959 0.000 1.000
#> SRR1082035 1 0.4562 0.965 0.904 0.096
#> SRR1393046 2 0.0000 0.959 0.000 1.000
#> SRR1466663 2 0.0000 0.959 0.000 1.000
#> SRR1384456 1 0.4562 0.965 0.904 0.096
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.938 0.000 1.000 0.000
#> SRR808862 3 0.4146 0.745 0.044 0.080 0.876
#> SRR1500382 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1322683 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1329811 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1087297 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1072626 2 0.1643 0.914 0.000 0.956 0.044
#> SRR1407428 1 0.1411 0.888 0.964 0.000 0.036
#> SRR1321029 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1500282 1 0.2448 0.896 0.924 0.000 0.076
#> SRR1100496 3 0.3412 0.794 0.000 0.124 0.876
#> SRR1308778 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1099378 2 0.6443 0.633 0.040 0.720 0.240
#> SRR1347412 1 0.1289 0.892 0.968 0.000 0.032
#> SRR1099694 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1088365 2 0.1964 0.903 0.000 0.944 0.056
#> SRR1325752 2 0.3551 0.835 0.000 0.868 0.132
#> SRR1416713 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1074474 1 0.1031 0.890 0.976 0.000 0.024
#> SRR1469369 3 0.5327 0.923 0.000 0.272 0.728
#> SRR1400507 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1378179 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1377905 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1089479 1 0.0747 0.891 0.984 0.000 0.016
#> SRR1073365 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1500306 1 0.1411 0.885 0.964 0.000 0.036
#> SRR1101566 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1350503 3 0.5363 0.924 0.000 0.276 0.724
#> SRR1446007 3 0.5327 0.923 0.000 0.272 0.728
#> SRR1102875 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1092686 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1069421 2 0.3192 0.855 0.000 0.888 0.112
#> SRR1341650 2 0.4999 0.781 0.028 0.820 0.152
#> SRR1357276 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1498374 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1093721 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1464660 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1402051 2 0.3686 0.829 0.000 0.860 0.140
#> SRR1488734 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1082616 3 0.3551 0.806 0.000 0.132 0.868
#> SRR1099427 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1453093 2 0.2448 0.889 0.000 0.924 0.076
#> SRR1357064 1 0.3267 0.895 0.884 0.000 0.116
#> SRR811237 2 0.2878 0.871 0.000 0.904 0.096
#> SRR1100848 2 0.0747 0.932 0.000 0.984 0.016
#> SRR1346755 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1472529 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1398905 3 0.4887 0.549 0.228 0.000 0.772
#> SRR1082733 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1308035 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1466445 3 0.5291 0.924 0.000 0.268 0.732
#> SRR1359080 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1455825 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1389300 2 0.0237 0.937 0.000 0.996 0.004
#> SRR812246 3 0.5058 0.908 0.000 0.244 0.756
#> SRR1076632 2 0.2878 0.869 0.000 0.904 0.096
#> SRR1415567 1 0.1163 0.889 0.972 0.000 0.028
#> SRR1331900 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1452099 2 0.3879 0.812 0.000 0.848 0.152
#> SRR1352346 1 0.7585 0.679 0.688 0.180 0.132
#> SRR1364034 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1086046 2 0.3619 0.833 0.000 0.864 0.136
#> SRR1407226 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1319363 1 0.7923 0.642 0.664 0.156 0.180
#> SRR1446961 3 0.5363 0.924 0.000 0.276 0.724
#> SRR1486650 1 0.1163 0.890 0.972 0.000 0.028
#> SRR1470152 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1454785 3 0.5363 0.924 0.000 0.276 0.724
#> SRR1092329 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1091476 3 0.5816 0.888 0.024 0.224 0.752
#> SRR1073775 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1366873 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1398114 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1089950 1 0.3816 0.890 0.852 0.000 0.148
#> SRR1433272 2 0.3482 0.839 0.000 0.872 0.128
#> SRR1075314 1 0.7221 0.649 0.716 0.148 0.136
#> SRR1085590 2 0.6299 -0.378 0.000 0.524 0.476
#> SRR1100752 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1391494 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1333263 2 0.5465 0.603 0.000 0.712 0.288
#> SRR1310231 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1094144 2 0.3038 0.862 0.000 0.896 0.104
#> SRR1092160 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1320300 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1322747 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1432719 3 0.5363 0.924 0.000 0.276 0.724
#> SRR1100728 2 0.3192 0.855 0.000 0.888 0.112
#> SRR1087511 2 0.0747 0.932 0.000 0.984 0.016
#> SRR1470336 1 0.1411 0.888 0.964 0.000 0.036
#> SRR1322536 1 0.6653 0.704 0.752 0.112 0.136
#> SRR1100824 1 0.3619 0.892 0.864 0.000 0.136
#> SRR1085951 3 0.3590 0.734 0.028 0.076 0.896
#> SRR1322046 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1316420 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1070913 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1345806 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1313872 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1337666 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1076823 1 0.6590 0.708 0.756 0.112 0.132
#> SRR1093954 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1451921 2 0.8650 0.361 0.292 0.572 0.136
#> SRR1491257 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1416979 2 0.0747 0.932 0.000 0.984 0.016
#> SRR1419015 2 0.9256 0.131 0.344 0.488 0.168
#> SRR817649 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1466376 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1120869 2 0.1860 0.906 0.000 0.948 0.052
#> SRR1319419 3 0.5363 0.924 0.000 0.276 0.724
#> SRR816495 3 0.5363 0.924 0.000 0.276 0.724
#> SRR818694 2 0.0747 0.932 0.000 0.984 0.016
#> SRR1465653 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1475952 1 0.1411 0.888 0.964 0.000 0.036
#> SRR1465040 3 0.5327 0.923 0.000 0.272 0.728
#> SRR1088461 2 0.0000 0.938 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1400141 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1349585 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1437576 2 0.0000 0.938 0.000 1.000 0.000
#> SRR814407 1 0.1411 0.885 0.964 0.000 0.036
#> SRR1332403 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1099598 2 0.1643 0.914 0.000 0.956 0.044
#> SRR1327723 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1392525 2 0.5327 0.620 0.000 0.728 0.272
#> SRR1320536 1 0.1163 0.890 0.972 0.000 0.028
#> SRR1083824 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1351390 1 0.4002 0.886 0.840 0.000 0.160
#> SRR1309141 2 0.4235 0.704 0.000 0.824 0.176
#> SRR1452803 2 0.0000 0.938 0.000 1.000 0.000
#> SRR811631 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1485563 2 0.3116 0.861 0.000 0.892 0.108
#> SRR1311531 3 0.5327 0.923 0.000 0.272 0.728
#> SRR1353076 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1480831 2 0.2066 0.902 0.000 0.940 0.060
#> SRR1083892 1 0.3267 0.895 0.884 0.000 0.116
#> SRR809873 1 0.8637 0.496 0.596 0.236 0.168
#> SRR1341854 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1464209 1 0.3267 0.895 0.884 0.000 0.116
#> SRR1389886 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1400730 3 0.3941 0.530 0.156 0.000 0.844
#> SRR1448008 2 0.0747 0.932 0.000 0.984 0.016
#> SRR1087606 1 0.3412 0.895 0.876 0.000 0.124
#> SRR1445111 1 0.1031 0.890 0.976 0.000 0.024
#> SRR816865 2 0.3192 0.855 0.000 0.888 0.112
#> SRR1323360 3 0.5327 0.925 0.000 0.272 0.728
#> SRR1417364 3 0.5363 0.924 0.000 0.276 0.724
#> SRR1480329 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1403322 1 0.3941 0.825 0.844 0.000 0.156
#> SRR1093625 1 0.1031 0.890 0.976 0.000 0.024
#> SRR1479977 2 0.0237 0.937 0.000 0.996 0.004
#> SRR1082035 1 0.3619 0.893 0.864 0.000 0.136
#> SRR1393046 2 0.0000 0.938 0.000 1.000 0.000
#> SRR1466663 2 0.3482 0.839 0.000 0.872 0.128
#> SRR1384456 1 0.1031 0.890 0.976 0.000 0.024
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR808862 3 0.1743 0.9089 0.000 0.004 0.940 0.056
#> SRR1500382 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1322683 2 0.2647 0.8130 0.000 0.880 0.000 0.120
#> SRR1329811 1 0.5810 0.6772 0.580 0.004 0.028 0.388
#> SRR1087297 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1072626 2 0.4008 0.7086 0.000 0.756 0.000 0.244
#> SRR1407428 1 0.1022 0.6767 0.968 0.000 0.000 0.032
#> SRR1321029 2 0.1637 0.8419 0.000 0.940 0.000 0.060
#> SRR1500282 1 0.3852 0.6981 0.800 0.000 0.008 0.192
#> SRR1100496 3 0.1209 0.9167 0.000 0.004 0.964 0.032
#> SRR1308778 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR1445304 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1099378 4 0.3547 0.4054 0.000 0.144 0.016 0.840
#> SRR1347412 1 0.0779 0.6876 0.980 0.000 0.004 0.016
#> SRR1099694 2 0.0469 0.8573 0.000 0.988 0.000 0.012
#> SRR1088365 2 0.3444 0.7253 0.000 0.816 0.000 0.184
#> SRR1325752 2 0.4967 0.1458 0.000 0.548 0.000 0.452
#> SRR1416713 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1074474 1 0.0000 0.6905 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.2214 0.9289 0.000 0.044 0.928 0.028
#> SRR1400507 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1378179 2 0.1302 0.8471 0.000 0.956 0.000 0.044
#> SRR1377905 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1089479 1 0.1978 0.6848 0.928 0.000 0.004 0.068
#> SRR1073365 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1500306 1 0.5010 0.4771 0.700 0.000 0.024 0.276
#> SRR1101566 2 0.2868 0.7983 0.000 0.864 0.000 0.136
#> SRR1350503 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1446007 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1102875 2 0.0817 0.8551 0.000 0.976 0.000 0.024
#> SRR1380293 2 0.0469 0.8563 0.000 0.988 0.000 0.012
#> SRR1331198 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1092686 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1069421 2 0.4790 0.3478 0.000 0.620 0.000 0.380
#> SRR1341650 4 0.5583 0.1193 0.008 0.468 0.008 0.516
#> SRR1357276 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1498374 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1093721 2 0.2216 0.8331 0.000 0.908 0.000 0.092
#> SRR1464660 1 0.5810 0.6772 0.580 0.004 0.028 0.388
#> SRR1402051 4 0.5138 0.2540 0.000 0.392 0.008 0.600
#> SRR1488734 2 0.0336 0.8568 0.000 0.992 0.000 0.008
#> SRR1082616 3 0.5119 0.2980 0.000 0.004 0.556 0.440
#> SRR1099427 2 0.2868 0.8019 0.000 0.864 0.000 0.136
#> SRR1453093 2 0.4776 0.4831 0.000 0.624 0.000 0.376
#> SRR1357064 1 0.5465 0.6802 0.588 0.000 0.020 0.392
#> SRR811237 2 0.4855 0.4201 0.000 0.600 0.000 0.400
#> SRR1100848 2 0.3610 0.7577 0.000 0.800 0.000 0.200
#> SRR1346755 2 0.3569 0.7571 0.000 0.804 0.000 0.196
#> SRR1472529 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1398905 3 0.1929 0.9003 0.024 0.000 0.940 0.036
#> SRR1082733 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1308035 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1466445 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1359080 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1455825 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1389300 2 0.1716 0.8404 0.000 0.936 0.000 0.064
#> SRR812246 3 0.0817 0.9369 0.000 0.024 0.976 0.000
#> SRR1076632 2 0.4356 0.5482 0.000 0.708 0.000 0.292
#> SRR1415567 1 0.0592 0.6837 0.984 0.000 0.000 0.016
#> SRR1331900 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1452099 4 0.5244 0.2957 0.000 0.388 0.012 0.600
#> SRR1352346 1 0.7304 0.5115 0.516 0.096 0.020 0.368
#> SRR1364034 2 0.1302 0.8471 0.000 0.956 0.000 0.044
#> SRR1086046 4 0.5417 0.1487 0.000 0.412 0.016 0.572
#> SRR1407226 1 0.5498 0.6724 0.576 0.000 0.020 0.404
#> SRR1319363 4 0.5941 0.4271 0.128 0.128 0.016 0.728
#> SRR1446961 3 0.1389 0.9483 0.000 0.048 0.952 0.000
#> SRR1486650 1 0.0376 0.6916 0.992 0.000 0.004 0.004
#> SRR1470152 1 0.5548 0.6805 0.588 0.000 0.024 0.388
#> SRR1454785 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1092329 2 0.2281 0.8297 0.000 0.904 0.000 0.096
#> SRR1091476 3 0.1629 0.9313 0.000 0.024 0.952 0.024
#> SRR1073775 2 0.2647 0.8147 0.000 0.880 0.000 0.120
#> SRR1366873 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1398114 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR1089950 4 0.5889 -0.3968 0.340 0.012 0.028 0.620
#> SRR1433272 2 0.4855 0.2860 0.000 0.600 0.000 0.400
#> SRR1075314 4 0.6272 0.2849 0.396 0.032 0.016 0.556
#> SRR1085590 3 0.4375 0.6909 0.000 0.180 0.788 0.032
#> SRR1100752 3 0.1211 0.9496 0.000 0.040 0.960 0.000
#> SRR1391494 2 0.1118 0.8576 0.000 0.964 0.000 0.036
#> SRR1333263 2 0.6708 0.0989 0.000 0.528 0.096 0.376
#> SRR1310231 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1094144 2 0.4776 0.3833 0.000 0.624 0.000 0.376
#> SRR1092160 2 0.0592 0.8572 0.000 0.984 0.000 0.016
#> SRR1320300 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1322747 2 0.0779 0.8528 0.000 0.980 0.016 0.004
#> SRR1432719 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1100728 2 0.4746 0.3800 0.000 0.632 0.000 0.368
#> SRR1087511 2 0.4624 0.5408 0.000 0.660 0.000 0.340
#> SRR1470336 1 0.2704 0.6029 0.876 0.000 0.000 0.124
#> SRR1322536 4 0.6089 0.2749 0.392 0.024 0.016 0.568
#> SRR1100824 1 0.5657 0.6420 0.540 0.000 0.024 0.436
#> SRR1085951 3 0.1743 0.9089 0.000 0.004 0.940 0.056
#> SRR1322046 2 0.0592 0.8572 0.000 0.984 0.000 0.016
#> SRR1316420 1 0.5476 0.6786 0.584 0.000 0.020 0.396
#> SRR1070913 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1345806 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1313872 2 0.1022 0.8530 0.000 0.968 0.000 0.032
#> SRR1337666 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1076823 4 0.6182 0.2055 0.440 0.024 0.016 0.520
#> SRR1093954 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR1451921 4 0.7562 0.5046 0.220 0.204 0.016 0.560
#> SRR1491257 1 0.5476 0.6786 0.584 0.000 0.020 0.396
#> SRR1416979 2 0.3486 0.7701 0.000 0.812 0.000 0.188
#> SRR1419015 4 0.6591 0.5297 0.084 0.264 0.016 0.636
#> SRR817649 2 0.0469 0.8563 0.000 0.988 0.000 0.012
#> SRR1466376 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1392055 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1120913 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1120869 2 0.2530 0.7968 0.000 0.888 0.000 0.112
#> SRR1319419 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR816495 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR818694 2 0.4072 0.6924 0.000 0.748 0.000 0.252
#> SRR1465653 1 0.5721 0.6782 0.584 0.004 0.024 0.388
#> SRR1475952 1 0.1302 0.6709 0.956 0.000 0.000 0.044
#> SRR1465040 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1088461 2 0.0592 0.8561 0.000 0.984 0.000 0.016
#> SRR810129 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR1400141 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1349585 1 0.5465 0.6802 0.588 0.000 0.020 0.392
#> SRR1437576 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR814407 1 0.3658 0.6284 0.836 0.000 0.020 0.144
#> SRR1332403 2 0.0469 0.8563 0.000 0.988 0.000 0.012
#> SRR1099598 2 0.4134 0.6876 0.000 0.740 0.000 0.260
#> SRR1327723 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1392525 2 0.7684 -0.2227 0.000 0.392 0.216 0.392
#> SRR1320536 1 0.0188 0.6914 0.996 0.000 0.000 0.004
#> SRR1083824 2 0.0779 0.8528 0.000 0.980 0.016 0.004
#> SRR1351390 4 0.5558 -0.3553 0.324 0.000 0.036 0.640
#> SRR1309141 2 0.5050 0.6427 0.000 0.764 0.084 0.152
#> SRR1452803 2 0.0469 0.8563 0.000 0.988 0.000 0.012
#> SRR811631 2 0.1792 0.8387 0.000 0.932 0.000 0.068
#> SRR1485563 2 0.5147 0.2188 0.000 0.536 0.004 0.460
#> SRR1311531 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1353076 2 0.1118 0.8578 0.000 0.964 0.000 0.036
#> SRR1480831 2 0.3975 0.6952 0.000 0.760 0.000 0.240
#> SRR1083892 1 0.5465 0.6802 0.588 0.000 0.020 0.392
#> SRR809873 4 0.7124 0.5004 0.184 0.184 0.016 0.616
#> SRR1341854 2 0.0921 0.8540 0.000 0.972 0.000 0.028
#> SRR1399335 2 0.0707 0.8549 0.000 0.980 0.000 0.020
#> SRR1464209 1 0.5465 0.6802 0.588 0.000 0.020 0.392
#> SRR1389886 2 0.0000 0.8576 0.000 1.000 0.000 0.000
#> SRR1400730 3 0.1867 0.8851 0.000 0.000 0.928 0.072
#> SRR1448008 2 0.3975 0.7081 0.000 0.760 0.000 0.240
#> SRR1087606 1 0.5864 0.6013 0.492 0.004 0.024 0.480
#> SRR1445111 1 0.0376 0.6901 0.992 0.000 0.004 0.004
#> SRR816865 2 0.4776 0.3587 0.000 0.624 0.000 0.376
#> SRR1323360 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1417364 3 0.1302 0.9519 0.000 0.044 0.956 0.000
#> SRR1480329 2 0.2814 0.8016 0.000 0.868 0.000 0.132
#> SRR1403322 1 0.5483 -0.1254 0.536 0.000 0.016 0.448
#> SRR1093625 1 0.0000 0.6905 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.1389 0.8465 0.000 0.952 0.000 0.048
#> SRR1082035 4 0.5576 -0.5568 0.444 0.000 0.020 0.536
#> SRR1393046 2 0.0188 0.8573 0.000 0.996 0.000 0.004
#> SRR1466663 2 0.4866 0.2813 0.000 0.596 0.000 0.404
#> SRR1384456 1 0.0000 0.6905 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0290 0.8059 0.000 0.992 0.000 0.008 0.000
#> SRR808862 3 0.2922 0.8937 0.000 0.000 0.872 0.056 0.072
#> SRR1500382 2 0.0324 0.8073 0.000 0.992 0.000 0.004 0.004
#> SRR1322683 2 0.5332 0.6860 0.000 0.704 0.016 0.112 0.168
#> SRR1329811 5 0.4064 0.8556 0.272 0.000 0.008 0.004 0.716
#> SRR1087297 2 0.0404 0.8051 0.000 0.988 0.000 0.012 0.000
#> SRR1072626 2 0.6292 0.4533 0.000 0.548 0.012 0.308 0.132
#> SRR1407428 1 0.1082 0.8417 0.964 0.000 0.000 0.008 0.028
#> SRR1321029 2 0.3997 0.7589 0.000 0.812 0.012 0.064 0.112
#> SRR1500282 1 0.4251 0.1368 0.624 0.000 0.004 0.000 0.372
#> SRR1100496 3 0.1915 0.9245 0.000 0.000 0.928 0.040 0.032
#> SRR1308778 2 0.2020 0.7557 0.000 0.900 0.000 0.100 0.000
#> SRR1445304 2 0.0703 0.8015 0.000 0.976 0.000 0.024 0.000
#> SRR1099378 4 0.4484 0.3242 0.000 0.024 0.000 0.668 0.308
#> SRR1347412 1 0.1990 0.8381 0.920 0.000 0.004 0.008 0.068
#> SRR1099694 2 0.0955 0.8034 0.000 0.968 0.000 0.028 0.004
#> SRR1088365 2 0.4235 0.0482 0.000 0.576 0.000 0.424 0.000
#> SRR1325752 4 0.5008 0.6325 0.000 0.300 0.000 0.644 0.056
#> SRR1416713 2 0.0162 0.8064 0.000 0.996 0.000 0.004 0.000
#> SRR1074474 1 0.1410 0.8457 0.940 0.000 0.000 0.000 0.060
#> SRR1469369 3 0.1695 0.9241 0.000 0.008 0.940 0.008 0.044
#> SRR1400507 2 0.4169 0.7528 0.000 0.800 0.012 0.072 0.116
#> SRR1378179 2 0.2890 0.6980 0.000 0.836 0.000 0.160 0.004
#> SRR1377905 2 0.0510 0.8073 0.000 0.984 0.000 0.000 0.016
#> SRR1089479 1 0.2270 0.7998 0.904 0.000 0.000 0.020 0.076
#> SRR1073365 2 0.0290 0.8060 0.000 0.992 0.000 0.008 0.000
#> SRR1500306 1 0.6122 0.4183 0.560 0.000 0.004 0.292 0.144
#> SRR1101566 2 0.5464 0.6724 0.000 0.692 0.016 0.124 0.168
#> SRR1350503 3 0.1153 0.9502 0.000 0.024 0.964 0.004 0.008
#> SRR1446007 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1102875 2 0.1478 0.7868 0.000 0.936 0.000 0.064 0.000
#> SRR1380293 2 0.1571 0.7840 0.000 0.936 0.000 0.060 0.004
#> SRR1331198 2 0.1026 0.8061 0.000 0.968 0.004 0.004 0.024
#> SRR1092686 3 0.0865 0.9533 0.000 0.024 0.972 0.004 0.000
#> SRR1069421 4 0.4905 0.5968 0.000 0.336 0.000 0.624 0.040
#> SRR1341650 4 0.4832 0.6458 0.000 0.200 0.000 0.712 0.088
#> SRR1357276 2 0.0324 0.8073 0.000 0.992 0.000 0.004 0.004
#> SRR1498374 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR1093721 2 0.4381 0.7487 0.000 0.780 0.008 0.088 0.124
#> SRR1464660 5 0.4039 0.8541 0.268 0.000 0.008 0.004 0.720
#> SRR1402051 4 0.6326 0.4901 0.004 0.164 0.016 0.604 0.212
#> SRR1488734 2 0.0880 0.7991 0.000 0.968 0.000 0.032 0.000
#> SRR1082616 4 0.4167 0.4304 0.000 0.000 0.252 0.724 0.024
#> SRR1099427 2 0.5360 0.6846 0.000 0.704 0.016 0.128 0.152
#> SRR1453093 4 0.6836 0.0380 0.000 0.364 0.016 0.444 0.176
#> SRR1357064 5 0.3661 0.8536 0.276 0.000 0.000 0.000 0.724
#> SRR811237 4 0.4404 0.5644 0.000 0.292 0.000 0.684 0.024
#> SRR1100848 2 0.5925 0.5842 0.000 0.624 0.012 0.232 0.132
#> SRR1346755 2 0.6101 0.5894 0.000 0.616 0.016 0.216 0.152
#> SRR1472529 2 0.4169 0.7528 0.000 0.800 0.012 0.072 0.116
#> SRR1398905 3 0.3867 0.8597 0.012 0.000 0.824 0.076 0.088
#> SRR1082733 2 0.0404 0.8052 0.000 0.988 0.000 0.012 0.000
#> SRR1308035 3 0.0865 0.9533 0.000 0.024 0.972 0.004 0.000
#> SRR1466445 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1359080 2 0.1492 0.8028 0.000 0.948 0.004 0.008 0.040
#> SRR1455825 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR1389300 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR812246 3 0.0798 0.9416 0.000 0.008 0.976 0.016 0.000
#> SRR1076632 4 0.4397 0.4310 0.000 0.432 0.000 0.564 0.004
#> SRR1415567 1 0.1043 0.8483 0.960 0.000 0.000 0.000 0.040
#> SRR1331900 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR1452099 4 0.3620 0.6252 0.000 0.108 0.000 0.824 0.068
#> SRR1352346 5 0.6718 0.6417 0.284 0.052 0.004 0.096 0.564
#> SRR1364034 2 0.2930 0.6941 0.000 0.832 0.000 0.164 0.004
#> SRR1086046 4 0.3959 0.5440 0.052 0.040 0.004 0.836 0.068
#> SRR1407226 5 0.4132 0.8509 0.260 0.000 0.000 0.020 0.720
#> SRR1319363 4 0.3901 0.5190 0.052 0.016 0.000 0.820 0.112
#> SRR1446961 3 0.3063 0.8501 0.000 0.096 0.864 0.004 0.036
#> SRR1486650 1 0.1571 0.8452 0.936 0.000 0.004 0.000 0.060
#> SRR1470152 5 0.4064 0.8556 0.272 0.000 0.008 0.004 0.716
#> SRR1454785 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1092329 2 0.4632 0.7374 0.000 0.764 0.012 0.092 0.132
#> SRR1091476 3 0.2536 0.9166 0.000 0.012 0.904 0.032 0.052
#> SRR1073775 2 0.5213 0.6964 0.000 0.716 0.016 0.108 0.160
#> SRR1366873 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR1398114 2 0.2020 0.7557 0.000 0.900 0.000 0.100 0.000
#> SRR1089950 5 0.5775 0.5370 0.136 0.000 0.000 0.264 0.600
#> SRR1433272 4 0.5506 0.4851 0.000 0.404 0.000 0.528 0.068
#> SRR1075314 4 0.5418 0.2012 0.320 0.000 0.004 0.608 0.068
#> SRR1085590 3 0.3653 0.8318 0.000 0.088 0.840 0.016 0.056
#> SRR1100752 3 0.0865 0.9533 0.000 0.024 0.972 0.004 0.000
#> SRR1391494 2 0.3078 0.7964 0.000 0.872 0.008 0.056 0.064
#> SRR1333263 4 0.6263 0.5725 0.000 0.336 0.052 0.556 0.056
#> SRR1310231 2 0.0609 0.8029 0.000 0.980 0.000 0.020 0.000
#> SRR1094144 4 0.4029 0.6155 0.000 0.316 0.000 0.680 0.004
#> SRR1092160 2 0.1216 0.8087 0.000 0.960 0.000 0.020 0.020
#> SRR1320300 2 0.4059 0.7569 0.000 0.808 0.012 0.068 0.112
#> SRR1322747 2 0.0960 0.8032 0.000 0.972 0.016 0.004 0.008
#> SRR1432719 3 0.1153 0.9512 0.000 0.024 0.964 0.004 0.008
#> SRR1100728 4 0.4733 0.5813 0.000 0.348 0.000 0.624 0.028
#> SRR1087511 2 0.6836 0.1946 0.000 0.444 0.016 0.364 0.176
#> SRR1470336 1 0.3075 0.7259 0.860 0.000 0.000 0.092 0.048
#> SRR1322536 4 0.5368 0.2189 0.308 0.000 0.004 0.620 0.068
#> SRR1100824 5 0.4558 0.8184 0.216 0.000 0.000 0.060 0.724
#> SRR1085951 3 0.3110 0.8900 0.000 0.000 0.860 0.060 0.080
#> SRR1322046 2 0.0794 0.8037 0.000 0.972 0.000 0.028 0.000
#> SRR1316420 5 0.3790 0.8548 0.272 0.000 0.000 0.004 0.724
#> SRR1070913 2 0.4169 0.7528 0.000 0.800 0.012 0.072 0.116
#> SRR1345806 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1313872 2 0.2439 0.7367 0.000 0.876 0.000 0.120 0.004
#> SRR1337666 2 0.1026 0.8061 0.000 0.968 0.004 0.004 0.024
#> SRR1076823 4 0.5219 0.2163 0.328 0.000 0.004 0.616 0.052
#> SRR1093954 2 0.2179 0.7499 0.000 0.888 0.000 0.112 0.000
#> SRR1451921 4 0.4081 0.4873 0.120 0.004 0.004 0.804 0.068
#> SRR1491257 5 0.3766 0.8548 0.268 0.000 0.000 0.004 0.728
#> SRR1416979 2 0.5540 0.6460 0.000 0.664 0.008 0.208 0.120
#> SRR1419015 4 0.3830 0.5534 0.028 0.036 0.000 0.828 0.108
#> SRR817649 2 0.1502 0.7863 0.000 0.940 0.000 0.056 0.004
#> SRR1466376 2 0.0162 0.8074 0.000 0.996 0.000 0.000 0.004
#> SRR1392055 2 0.0162 0.8075 0.000 0.996 0.000 0.000 0.004
#> SRR1120913 2 0.0000 0.8070 0.000 1.000 0.000 0.000 0.000
#> SRR1120869 2 0.4182 0.2852 0.000 0.644 0.000 0.352 0.004
#> SRR1319419 3 0.0865 0.9531 0.000 0.024 0.972 0.000 0.004
#> SRR816495 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR818694 2 0.6666 0.3846 0.000 0.516 0.016 0.292 0.176
#> SRR1465653 5 0.4064 0.8556 0.272 0.000 0.008 0.004 0.716
#> SRR1475952 1 0.1331 0.7993 0.952 0.000 0.000 0.040 0.008
#> SRR1465040 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1088461 2 0.2020 0.7555 0.000 0.900 0.000 0.100 0.000
#> SRR810129 2 0.2074 0.7532 0.000 0.896 0.000 0.104 0.000
#> SRR1400141 3 0.1026 0.9530 0.000 0.024 0.968 0.004 0.004
#> SRR1349585 5 0.3661 0.8536 0.276 0.000 0.000 0.000 0.724
#> SRR1437576 2 0.2888 0.7874 0.000 0.880 0.004 0.056 0.060
#> SRR814407 1 0.4411 0.6795 0.772 0.000 0.004 0.128 0.096
#> SRR1332403 2 0.1270 0.7887 0.000 0.948 0.000 0.052 0.000
#> SRR1099598 2 0.6537 0.3889 0.000 0.508 0.012 0.324 0.156
#> SRR1327723 2 0.0162 0.8069 0.000 0.996 0.000 0.004 0.000
#> SRR1392525 4 0.5432 0.6328 0.000 0.164 0.116 0.700 0.020
#> SRR1320536 1 0.1410 0.8457 0.940 0.000 0.000 0.000 0.060
#> SRR1083824 2 0.1442 0.8037 0.000 0.952 0.012 0.004 0.032
#> SRR1351390 5 0.6122 0.3727 0.140 0.000 0.000 0.348 0.512
#> SRR1309141 2 0.6089 0.1371 0.000 0.580 0.052 0.320 0.048
#> SRR1452803 2 0.1197 0.7903 0.000 0.952 0.000 0.048 0.000
#> SRR811631 2 0.4322 0.7477 0.000 0.788 0.012 0.076 0.124
#> SRR1485563 4 0.3563 0.6597 0.000 0.208 0.000 0.780 0.012
#> SRR1311531 3 0.0703 0.9539 0.000 0.024 0.976 0.000 0.000
#> SRR1353076 2 0.3342 0.7679 0.000 0.836 0.008 0.136 0.020
#> SRR1480831 2 0.4994 0.3292 0.000 0.604 0.012 0.364 0.020
#> SRR1083892 5 0.3790 0.8563 0.272 0.000 0.000 0.004 0.724
#> SRR809873 4 0.3610 0.5421 0.088 0.020 0.000 0.844 0.048
#> SRR1341854 2 0.2286 0.7575 0.000 0.888 0.000 0.108 0.004
#> SRR1399335 2 0.2074 0.7529 0.000 0.896 0.000 0.104 0.000
#> SRR1464209 5 0.3661 0.8536 0.276 0.000 0.000 0.000 0.724
#> SRR1389886 2 0.0000 0.8070 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 3 0.3876 0.7884 0.000 0.000 0.776 0.032 0.192
#> SRR1448008 2 0.6489 0.4486 0.000 0.548 0.016 0.276 0.160
#> SRR1087606 5 0.4588 0.8034 0.208 0.000 0.004 0.056 0.732
#> SRR1445111 1 0.1121 0.8489 0.956 0.000 0.000 0.000 0.044
#> SRR816865 4 0.4851 0.5925 0.000 0.340 0.000 0.624 0.036
#> SRR1323360 3 0.0865 0.9533 0.000 0.024 0.972 0.004 0.000
#> SRR1417364 3 0.1267 0.9493 0.000 0.024 0.960 0.004 0.012
#> SRR1480329 2 0.5252 0.6843 0.000 0.708 0.012 0.120 0.160
#> SRR1403322 4 0.4833 0.0538 0.412 0.000 0.000 0.564 0.024
#> SRR1093625 1 0.1270 0.8482 0.948 0.000 0.000 0.000 0.052
#> SRR1479977 2 0.3997 0.7589 0.000 0.812 0.012 0.064 0.112
#> SRR1082035 5 0.5816 0.6407 0.164 0.000 0.000 0.228 0.608
#> SRR1393046 2 0.0865 0.8070 0.000 0.972 0.000 0.004 0.024
#> SRR1466663 4 0.5523 0.5683 0.000 0.348 0.000 0.572 0.080
#> SRR1384456 1 0.1410 0.8457 0.940 0.000 0.000 0.000 0.060
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.1082 0.7066 0.000 0.956 0.000 0.040 0.000 0.004
#> SRR808862 3 0.3813 0.8297 0.048 0.000 0.800 0.028 0.000 0.124
#> SRR1500382 2 0.0806 0.7010 0.000 0.972 0.000 0.008 0.000 0.020
#> SRR1322683 6 0.4314 0.4289 0.000 0.444 0.000 0.020 0.000 0.536
#> SRR1329811 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1087297 2 0.1010 0.7077 0.000 0.960 0.000 0.036 0.000 0.004
#> SRR1072626 6 0.5704 0.4929 0.000 0.300 0.000 0.192 0.000 0.508
#> SRR1407428 1 0.2408 0.8368 0.876 0.000 0.000 0.004 0.108 0.012
#> SRR1321029 2 0.3578 0.2194 0.000 0.660 0.000 0.000 0.000 0.340
#> SRR1500282 1 0.4821 0.2227 0.488 0.000 0.000 0.008 0.468 0.036
#> SRR1100496 3 0.2445 0.8905 0.008 0.000 0.892 0.040 0.000 0.060
#> SRR1308778 2 0.2994 0.6125 0.000 0.788 0.000 0.208 0.000 0.004
#> SRR1445304 2 0.1411 0.7055 0.000 0.936 0.000 0.060 0.000 0.004
#> SRR1099378 4 0.4520 0.3698 0.004 0.012 0.000 0.660 0.296 0.028
#> SRR1347412 1 0.3339 0.8180 0.824 0.000 0.000 0.008 0.120 0.048
#> SRR1099694 2 0.1700 0.7006 0.000 0.916 0.000 0.080 0.000 0.004
#> SRR1088365 4 0.3967 0.5494 0.000 0.356 0.000 0.632 0.000 0.012
#> SRR1325752 4 0.3830 0.7479 0.000 0.196 0.000 0.760 0.036 0.008
#> SRR1416713 2 0.0405 0.7046 0.000 0.988 0.000 0.008 0.000 0.004
#> SRR1074474 1 0.2278 0.8350 0.868 0.000 0.000 0.004 0.128 0.000
#> SRR1469369 3 0.2020 0.8665 0.000 0.000 0.896 0.008 0.000 0.096
#> SRR1400507 2 0.3717 0.0888 0.000 0.616 0.000 0.000 0.000 0.384
#> SRR1378179 2 0.3819 0.4161 0.000 0.672 0.000 0.316 0.000 0.012
#> SRR1377905 2 0.0865 0.6884 0.000 0.964 0.000 0.000 0.000 0.036
#> SRR1089479 1 0.3862 0.7816 0.788 0.000 0.000 0.008 0.100 0.104
#> SRR1073365 2 0.1219 0.7072 0.000 0.948 0.000 0.048 0.000 0.004
#> SRR1500306 6 0.6401 -0.3777 0.340 0.000 0.000 0.152 0.044 0.464
#> SRR1101566 6 0.3982 0.4008 0.000 0.460 0.000 0.004 0.000 0.536
#> SRR1350503 3 0.0291 0.9318 0.000 0.000 0.992 0.004 0.000 0.004
#> SRR1446007 3 0.0000 0.9334 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 2 0.2653 0.6683 0.000 0.844 0.000 0.144 0.000 0.012
#> SRR1380293 2 0.2320 0.6754 0.000 0.864 0.000 0.132 0.000 0.004
#> SRR1331198 2 0.0937 0.6854 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1092686 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1069421 4 0.3245 0.7494 0.000 0.184 0.000 0.796 0.016 0.004
#> SRR1341650 4 0.3608 0.7380 0.000 0.148 0.000 0.788 0.064 0.000
#> SRR1357276 2 0.0692 0.6996 0.000 0.976 0.000 0.004 0.000 0.020
#> SRR1498374 2 0.3578 0.2194 0.000 0.660 0.000 0.000 0.000 0.340
#> SRR1093721 2 0.4584 -0.2226 0.000 0.512 0.000 0.036 0.000 0.452
#> SRR1464660 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1402051 6 0.4955 0.4629 0.000 0.132 0.000 0.204 0.004 0.660
#> SRR1488734 2 0.1753 0.6990 0.000 0.912 0.000 0.084 0.000 0.004
#> SRR1082616 4 0.4678 0.4578 0.004 0.000 0.168 0.708 0.004 0.116
#> SRR1099427 6 0.4256 0.3908 0.000 0.464 0.000 0.016 0.000 0.520
#> SRR1453093 6 0.4680 0.5645 0.000 0.184 0.000 0.132 0.000 0.684
#> SRR1357064 5 0.0777 0.8571 0.024 0.000 0.000 0.004 0.972 0.000
#> SRR811237 4 0.4703 0.6241 0.000 0.164 0.000 0.684 0.000 0.152
#> SRR1100848 6 0.5319 0.4652 0.000 0.388 0.000 0.108 0.000 0.504
#> SRR1346755 6 0.4863 0.4626 0.000 0.412 0.000 0.060 0.000 0.528
#> SRR1472529 2 0.3717 0.0888 0.000 0.616 0.000 0.000 0.000 0.384
#> SRR1398905 3 0.5481 0.6797 0.088 0.000 0.644 0.052 0.000 0.216
#> SRR1082733 2 0.1757 0.7005 0.000 0.916 0.000 0.076 0.000 0.008
#> SRR1308035 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1466445 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1359080 2 0.1814 0.6266 0.000 0.900 0.000 0.000 0.000 0.100
#> SRR1455825 2 0.3592 0.2087 0.000 0.656 0.000 0.000 0.000 0.344
#> SRR1389300 2 0.3563 0.2301 0.000 0.664 0.000 0.000 0.000 0.336
#> SRR812246 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1076632 4 0.3420 0.7171 0.000 0.240 0.000 0.748 0.000 0.012
#> SRR1415567 1 0.2100 0.8374 0.884 0.000 0.000 0.004 0.112 0.000
#> SRR1331900 2 0.3563 0.2301 0.000 0.664 0.000 0.000 0.000 0.336
#> SRR1452099 4 0.3405 0.6768 0.004 0.060 0.000 0.844 0.028 0.064
#> SRR1352346 5 0.4859 0.6398 0.072 0.108 0.000 0.076 0.740 0.004
#> SRR1364034 2 0.3819 0.4161 0.000 0.672 0.000 0.316 0.000 0.012
#> SRR1086046 6 0.5214 -0.1260 0.064 0.012 0.000 0.400 0.000 0.524
#> SRR1407226 5 0.1625 0.8212 0.012 0.000 0.000 0.060 0.928 0.000
#> SRR1319363 4 0.3494 0.5649 0.020 0.000 0.000 0.828 0.072 0.080
#> SRR1446961 3 0.3183 0.7579 0.000 0.128 0.828 0.004 0.000 0.040
#> SRR1486650 1 0.2278 0.8350 0.868 0.000 0.000 0.004 0.128 0.000
#> SRR1470152 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1454785 3 0.0000 0.9334 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 2 0.4471 -0.3158 0.000 0.500 0.000 0.028 0.000 0.472
#> SRR1091476 3 0.2866 0.8714 0.020 0.000 0.864 0.024 0.000 0.092
#> SRR1073775 6 0.4377 0.4402 0.000 0.436 0.000 0.024 0.000 0.540
#> SRR1366873 2 0.3592 0.2087 0.000 0.656 0.000 0.000 0.000 0.344
#> SRR1398114 2 0.3245 0.5822 0.000 0.764 0.000 0.228 0.000 0.008
#> SRR1089950 5 0.5849 0.5370 0.044 0.000 0.000 0.184 0.608 0.164
#> SRR1433272 4 0.3971 0.6984 0.000 0.268 0.000 0.704 0.024 0.004
#> SRR1075314 6 0.5983 -0.2266 0.256 0.000 0.000 0.304 0.000 0.440
#> SRR1085590 3 0.3035 0.8242 0.000 0.040 0.860 0.024 0.000 0.076
#> SRR1100752 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1391494 2 0.4594 0.4075 0.000 0.676 0.000 0.092 0.000 0.232
#> SRR1333263 4 0.3888 0.7446 0.000 0.204 0.008 0.756 0.028 0.004
#> SRR1310231 2 0.1387 0.7034 0.000 0.932 0.000 0.068 0.000 0.000
#> SRR1094144 4 0.3269 0.7427 0.000 0.184 0.000 0.792 0.000 0.024
#> SRR1092160 2 0.2106 0.6998 0.000 0.904 0.000 0.064 0.000 0.032
#> SRR1320300 2 0.3563 0.2301 0.000 0.664 0.000 0.000 0.000 0.336
#> SRR1322747 2 0.0922 0.6935 0.000 0.968 0.004 0.004 0.000 0.024
#> SRR1432719 3 0.0291 0.9326 0.000 0.000 0.992 0.004 0.000 0.004
#> SRR1100728 4 0.3354 0.7486 0.000 0.184 0.000 0.792 0.016 0.008
#> SRR1087511 6 0.4454 0.5761 0.000 0.224 0.000 0.084 0.000 0.692
#> SRR1470336 1 0.4403 0.6418 0.676 0.000 0.000 0.020 0.024 0.280
#> SRR1322536 6 0.5983 -0.2266 0.256 0.000 0.000 0.304 0.000 0.440
#> SRR1100824 5 0.2234 0.7735 0.004 0.000 0.000 0.124 0.872 0.000
#> SRR1085951 3 0.3968 0.8230 0.048 0.000 0.788 0.032 0.000 0.132
#> SRR1322046 2 0.2257 0.6860 0.000 0.876 0.000 0.116 0.000 0.008
#> SRR1316420 5 0.0692 0.8561 0.020 0.000 0.000 0.004 0.976 0.000
#> SRR1070913 2 0.3747 0.0471 0.000 0.604 0.000 0.000 0.000 0.396
#> SRR1345806 3 0.0146 0.9330 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1313872 2 0.2738 0.6490 0.000 0.820 0.000 0.176 0.000 0.004
#> SRR1337666 2 0.0937 0.6854 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1076823 4 0.6559 -0.1600 0.260 0.000 0.000 0.360 0.024 0.356
#> SRR1093954 2 0.3349 0.5648 0.000 0.748 0.000 0.244 0.000 0.008
#> SRR1451921 4 0.5424 0.1399 0.100 0.004 0.000 0.452 0.000 0.444
#> SRR1491257 5 0.0405 0.8492 0.004 0.000 0.000 0.008 0.988 0.000
#> SRR1416979 6 0.5411 0.4081 0.000 0.412 0.000 0.116 0.000 0.472
#> SRR1419015 4 0.2995 0.5991 0.012 0.004 0.000 0.864 0.072 0.048
#> SRR817649 2 0.1908 0.6953 0.000 0.900 0.000 0.096 0.000 0.004
#> SRR1466376 2 0.0777 0.6979 0.000 0.972 0.000 0.004 0.000 0.024
#> SRR1392055 2 0.0547 0.6977 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1120913 2 0.0146 0.7032 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1120869 4 0.4047 0.4891 0.000 0.384 0.000 0.604 0.000 0.012
#> SRR1319419 3 0.0291 0.9326 0.000 0.000 0.992 0.004 0.000 0.004
#> SRR816495 3 0.0146 0.9330 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR818694 6 0.4550 0.5756 0.000 0.240 0.000 0.084 0.000 0.676
#> SRR1465653 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1475952 1 0.1844 0.8105 0.924 0.000 0.000 0.004 0.048 0.024
#> SRR1465040 3 0.0000 0.9334 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 2 0.3081 0.5975 0.000 0.776 0.000 0.220 0.000 0.004
#> SRR810129 2 0.3245 0.5822 0.000 0.764 0.000 0.228 0.000 0.008
#> SRR1400141 3 0.0405 0.9329 0.000 0.000 0.988 0.004 0.000 0.008
#> SRR1349585 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1437576 2 0.2562 0.5367 0.000 0.828 0.000 0.000 0.000 0.172
#> SRR814407 1 0.5202 0.6385 0.680 0.000 0.000 0.104 0.040 0.176
#> SRR1332403 2 0.2118 0.6897 0.000 0.888 0.000 0.104 0.000 0.008
#> SRR1099598 6 0.5607 0.4708 0.000 0.240 0.000 0.216 0.000 0.544
#> SRR1327723 2 0.0914 0.7061 0.000 0.968 0.000 0.016 0.000 0.016
#> SRR1392525 4 0.4009 0.7183 0.000 0.112 0.060 0.792 0.000 0.036
#> SRR1320536 1 0.2278 0.8350 0.868 0.000 0.000 0.004 0.128 0.000
#> SRR1083824 2 0.1340 0.6805 0.000 0.948 0.008 0.004 0.000 0.040
#> SRR1351390 5 0.7030 0.1868 0.072 0.000 0.000 0.224 0.352 0.352
#> SRR1309141 4 0.4450 0.5502 0.000 0.364 0.008 0.608 0.016 0.004
#> SRR1452803 2 0.1858 0.6961 0.000 0.904 0.000 0.092 0.000 0.004
#> SRR811631 2 0.3717 0.0888 0.000 0.616 0.000 0.000 0.000 0.384
#> SRR1485563 4 0.4015 0.7141 0.000 0.120 0.000 0.784 0.020 0.076
#> SRR1311531 3 0.0000 0.9334 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 2 0.4638 0.5331 0.000 0.672 0.000 0.232 0.000 0.096
#> SRR1480831 2 0.5249 0.1221 0.000 0.528 0.000 0.368 0.000 0.104
#> SRR1083892 5 0.0891 0.8571 0.024 0.000 0.000 0.008 0.968 0.000
#> SRR809873 4 0.3616 0.5590 0.040 0.000 0.000 0.824 0.048 0.088
#> SRR1341854 2 0.3014 0.6363 0.000 0.804 0.000 0.184 0.000 0.012
#> SRR1399335 2 0.3302 0.5689 0.000 0.760 0.000 0.232 0.004 0.004
#> SRR1464209 5 0.0858 0.8564 0.028 0.000 0.000 0.004 0.968 0.000
#> SRR1389886 2 0.0146 0.7032 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1400730 3 0.5820 0.7067 0.052 0.000 0.672 0.036 0.092 0.148
#> SRR1448008 6 0.4889 0.5542 0.000 0.312 0.000 0.084 0.000 0.604
#> SRR1087606 5 0.1605 0.8497 0.032 0.000 0.000 0.016 0.940 0.012
#> SRR1445111 1 0.2633 0.8361 0.864 0.000 0.000 0.004 0.112 0.020
#> SRR816865 4 0.3354 0.7486 0.000 0.184 0.000 0.792 0.016 0.008
#> SRR1323360 3 0.0146 0.9333 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1417364 3 0.0291 0.9326 0.000 0.000 0.992 0.004 0.000 0.004
#> SRR1480329 6 0.3854 0.3906 0.000 0.464 0.000 0.000 0.000 0.536
#> SRR1403322 1 0.6298 0.3094 0.436 0.000 0.000 0.324 0.016 0.224
#> SRR1093625 1 0.2191 0.8367 0.876 0.000 0.000 0.004 0.120 0.000
#> SRR1479977 2 0.3531 0.2476 0.000 0.672 0.000 0.000 0.000 0.328
#> SRR1082035 5 0.3697 0.6369 0.004 0.000 0.000 0.248 0.732 0.016
#> SRR1393046 2 0.0713 0.6936 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1466663 4 0.3924 0.7405 0.000 0.208 0.000 0.740 0.052 0.000
#> SRR1384456 1 0.2278 0.8350 0.868 0.000 0.000 0.004 0.128 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", "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 17467 rows and 159 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 0.937 0.931 0.974 0.4615 0.545 0.545
#> 3 3 1.000 0.969 0.988 0.3467 0.792 0.633
#> 4 4 0.808 0.869 0.920 0.1945 0.855 0.628
#> 5 5 0.799 0.812 0.872 0.0697 0.899 0.636
#> 6 6 0.809 0.713 0.857 0.0404 0.909 0.603
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
#> SRR810713 2 0.0000 0.970 0.000 1.000
#> SRR808862 1 0.0000 0.976 1.000 0.000
#> SRR1500382 2 0.0000 0.970 0.000 1.000
#> SRR1322683 2 0.0000 0.970 0.000 1.000
#> SRR1329811 1 0.0000 0.976 1.000 0.000
#> SRR1087297 2 0.0000 0.970 0.000 1.000
#> SRR1072626 2 0.0000 0.970 0.000 1.000
#> SRR1407428 1 0.0000 0.976 1.000 0.000
#> SRR1321029 2 0.0000 0.970 0.000 1.000
#> SRR1500282 1 0.0000 0.976 1.000 0.000
#> SRR1100496 1 0.1184 0.961 0.984 0.016
#> SRR1308778 2 0.0000 0.970 0.000 1.000
#> SRR1445304 2 0.0000 0.970 0.000 1.000
#> SRR1099378 1 0.0000 0.976 1.000 0.000
#> SRR1347412 1 0.0000 0.976 1.000 0.000
#> SRR1099694 2 0.0000 0.970 0.000 1.000
#> SRR1088365 2 0.0000 0.970 0.000 1.000
#> SRR1325752 1 0.0000 0.976 1.000 0.000
#> SRR1416713 2 0.0000 0.970 0.000 1.000
#> SRR1074474 1 0.0000 0.976 1.000 0.000
#> SRR1469369 2 0.0000 0.970 0.000 1.000
#> SRR1400507 2 0.0000 0.970 0.000 1.000
#> SRR1378179 2 0.0000 0.970 0.000 1.000
#> SRR1377905 2 0.0000 0.970 0.000 1.000
#> SRR1089479 1 0.0000 0.976 1.000 0.000
#> SRR1073365 2 0.0000 0.970 0.000 1.000
#> SRR1500306 1 0.0000 0.976 1.000 0.000
#> SRR1101566 2 0.0000 0.970 0.000 1.000
#> SRR1350503 2 0.0000 0.970 0.000 1.000
#> SRR1446007 2 0.0000 0.970 0.000 1.000
#> SRR1102875 2 0.0000 0.970 0.000 1.000
#> SRR1380293 2 0.0000 0.970 0.000 1.000
#> SRR1331198 2 0.0000 0.970 0.000 1.000
#> SRR1092686 2 0.0000 0.970 0.000 1.000
#> SRR1069421 2 0.9686 0.360 0.396 0.604
#> SRR1341650 1 0.0000 0.976 1.000 0.000
#> SRR1357276 2 0.0000 0.970 0.000 1.000
#> SRR1498374 2 0.0000 0.970 0.000 1.000
#> SRR1093721 2 0.0000 0.970 0.000 1.000
#> SRR1464660 1 0.0000 0.976 1.000 0.000
#> SRR1402051 1 0.9710 0.298 0.600 0.400
#> SRR1488734 2 0.0000 0.970 0.000 1.000
#> SRR1082616 1 0.0000 0.976 1.000 0.000
#> SRR1099427 2 0.0000 0.970 0.000 1.000
#> SRR1453093 2 0.0000 0.970 0.000 1.000
#> SRR1357064 1 0.0000 0.976 1.000 0.000
#> SRR811237 2 0.0000 0.970 0.000 1.000
#> SRR1100848 2 0.0000 0.970 0.000 1.000
#> SRR1346755 2 0.0000 0.970 0.000 1.000
#> SRR1472529 2 0.0000 0.970 0.000 1.000
#> SRR1398905 1 0.0000 0.976 1.000 0.000
#> SRR1082733 2 0.0000 0.970 0.000 1.000
#> SRR1308035 2 0.0000 0.970 0.000 1.000
#> SRR1466445 2 0.0000 0.970 0.000 1.000
#> SRR1359080 2 0.0000 0.970 0.000 1.000
#> SRR1455825 2 0.0000 0.970 0.000 1.000
#> SRR1389300 2 0.0000 0.970 0.000 1.000
#> SRR812246 1 0.9850 0.248 0.572 0.428
#> SRR1076632 2 0.0376 0.967 0.004 0.996
#> SRR1415567 1 0.0000 0.976 1.000 0.000
#> SRR1331900 2 0.0000 0.970 0.000 1.000
#> SRR1452099 1 0.0000 0.976 1.000 0.000
#> SRR1352346 1 0.0000 0.976 1.000 0.000
#> SRR1364034 2 0.0000 0.970 0.000 1.000
#> SRR1086046 1 0.0000 0.976 1.000 0.000
#> SRR1407226 1 0.0000 0.976 1.000 0.000
#> SRR1319363 1 0.0000 0.976 1.000 0.000
#> SRR1446961 2 0.0000 0.970 0.000 1.000
#> SRR1486650 1 0.0000 0.976 1.000 0.000
#> SRR1470152 1 0.0000 0.976 1.000 0.000
#> SRR1454785 2 0.0000 0.970 0.000 1.000
#> SRR1092329 2 0.0000 0.970 0.000 1.000
#> SRR1091476 1 0.9635 0.358 0.612 0.388
#> SRR1073775 2 0.0000 0.970 0.000 1.000
#> SRR1366873 2 0.0000 0.970 0.000 1.000
#> SRR1398114 2 0.0000 0.970 0.000 1.000
#> SRR1089950 1 0.0000 0.976 1.000 0.000
#> SRR1433272 2 0.9775 0.317 0.412 0.588
#> SRR1075314 1 0.0000 0.976 1.000 0.000
#> SRR1085590 2 0.0000 0.970 0.000 1.000
#> SRR1100752 2 0.0000 0.970 0.000 1.000
#> SRR1391494 2 0.0000 0.970 0.000 1.000
#> SRR1333263 2 0.9580 0.399 0.380 0.620
#> SRR1310231 2 0.0000 0.970 0.000 1.000
#> SRR1094144 2 0.9686 0.360 0.396 0.604
#> SRR1092160 2 0.0000 0.970 0.000 1.000
#> SRR1320300 2 0.0000 0.970 0.000 1.000
#> SRR1322747 2 0.0000 0.970 0.000 1.000
#> SRR1432719 2 0.0000 0.970 0.000 1.000
#> SRR1100728 2 0.9686 0.360 0.396 0.604
#> SRR1087511 2 0.0000 0.970 0.000 1.000
#> SRR1470336 1 0.0000 0.976 1.000 0.000
#> SRR1322536 1 0.0000 0.976 1.000 0.000
#> SRR1100824 1 0.0000 0.976 1.000 0.000
#> SRR1085951 1 0.0000 0.976 1.000 0.000
#> SRR1322046 2 0.0000 0.970 0.000 1.000
#> SRR1316420 1 0.0000 0.976 1.000 0.000
#> SRR1070913 2 0.0000 0.970 0.000 1.000
#> SRR1345806 2 0.0000 0.970 0.000 1.000
#> SRR1313872 2 0.0000 0.970 0.000 1.000
#> SRR1337666 2 0.0000 0.970 0.000 1.000
#> SRR1076823 1 0.0000 0.976 1.000 0.000
#> SRR1093954 2 0.0000 0.970 0.000 1.000
#> SRR1451921 1 0.0000 0.976 1.000 0.000
#> SRR1491257 1 0.0000 0.976 1.000 0.000
#> SRR1416979 2 0.0000 0.970 0.000 1.000
#> SRR1419015 1 0.0000 0.976 1.000 0.000
#> SRR817649 2 0.0376 0.967 0.004 0.996
#> SRR1466376 2 0.0000 0.970 0.000 1.000
#> SRR1392055 2 0.0000 0.970 0.000 1.000
#> SRR1120913 2 0.0000 0.970 0.000 1.000
#> SRR1120869 2 0.0000 0.970 0.000 1.000
#> SRR1319419 2 0.0000 0.970 0.000 1.000
#> SRR816495 2 0.0000 0.970 0.000 1.000
#> SRR818694 2 0.0000 0.970 0.000 1.000
#> SRR1465653 1 0.0000 0.976 1.000 0.000
#> SRR1475952 1 0.0000 0.976 1.000 0.000
#> SRR1465040 2 0.0000 0.970 0.000 1.000
#> SRR1088461 2 0.0000 0.970 0.000 1.000
#> SRR810129 2 0.0000 0.970 0.000 1.000
#> SRR1400141 2 0.0000 0.970 0.000 1.000
#> SRR1349585 1 0.0000 0.976 1.000 0.000
#> SRR1437576 2 0.0000 0.970 0.000 1.000
#> SRR814407 1 0.0000 0.976 1.000 0.000
#> SRR1332403 2 0.0000 0.970 0.000 1.000
#> SRR1099598 2 0.0000 0.970 0.000 1.000
#> SRR1327723 2 0.0000 0.970 0.000 1.000
#> SRR1392525 2 0.0000 0.970 0.000 1.000
#> SRR1320536 1 0.0000 0.976 1.000 0.000
#> SRR1083824 2 0.0000 0.970 0.000 1.000
#> SRR1351390 1 0.0000 0.976 1.000 0.000
#> SRR1309141 2 0.2236 0.936 0.036 0.964
#> SRR1452803 2 0.0000 0.970 0.000 1.000
#> SRR811631 2 0.0000 0.970 0.000 1.000
#> SRR1485563 2 0.9963 0.159 0.464 0.536
#> SRR1311531 2 0.0000 0.970 0.000 1.000
#> SRR1353076 2 0.0000 0.970 0.000 1.000
#> SRR1480831 2 0.0000 0.970 0.000 1.000
#> SRR1083892 1 0.0000 0.976 1.000 0.000
#> SRR809873 1 0.0000 0.976 1.000 0.000
#> SRR1341854 2 0.0000 0.970 0.000 1.000
#> SRR1399335 2 0.0000 0.970 0.000 1.000
#> SRR1464209 1 0.0000 0.976 1.000 0.000
#> SRR1389886 2 0.0000 0.970 0.000 1.000
#> SRR1400730 1 0.0000 0.976 1.000 0.000
#> SRR1448008 2 0.0000 0.970 0.000 1.000
#> SRR1087606 1 0.0000 0.976 1.000 0.000
#> SRR1445111 1 0.0000 0.976 1.000 0.000
#> SRR816865 2 0.9686 0.360 0.396 0.604
#> SRR1323360 2 0.0000 0.970 0.000 1.000
#> SRR1417364 2 0.0000 0.970 0.000 1.000
#> SRR1480329 2 0.0938 0.959 0.012 0.988
#> SRR1403322 1 0.0000 0.976 1.000 0.000
#> SRR1093625 1 0.0000 0.976 1.000 0.000
#> SRR1479977 2 0.0000 0.970 0.000 1.000
#> SRR1082035 1 0.0000 0.976 1.000 0.000
#> SRR1393046 2 0.0000 0.970 0.000 1.000
#> SRR1466663 1 0.0376 0.972 0.996 0.004
#> SRR1384456 1 0.0000 0.976 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.983 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1322683 2 0.1031 0.962 0.000 0.976 0.024
#> SRR1329811 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1087297 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1072626 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1321029 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1500282 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1100496 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1308778 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1099378 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1347412 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1099694 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1325752 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1416713 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1469369 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1400507 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1377905 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1089479 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1073365 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1500306 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1101566 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1350503 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1102875 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1092686 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1069421 2 0.1031 0.962 0.024 0.976 0.000
#> SRR1341650 1 0.0592 0.985 0.988 0.000 0.012
#> SRR1357276 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1498374 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1093721 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1464660 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1402051 2 0.6286 0.153 0.464 0.536 0.000
#> SRR1488734 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1082616 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1099427 3 0.5650 0.547 0.000 0.312 0.688
#> SRR1453093 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1357064 1 0.0000 0.996 1.000 0.000 0.000
#> SRR811237 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1100848 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1346755 2 0.0747 0.970 0.000 0.984 0.016
#> SRR1472529 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1398905 3 0.0592 0.966 0.012 0.000 0.988
#> SRR1082733 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1308035 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1359080 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.983 0.000 1.000 0.000
#> SRR812246 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1076632 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1415567 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1452099 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1352346 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1364034 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1086046 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1407226 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1319363 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1446961 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1486650 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1454785 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1092329 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1091476 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1073775 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1089950 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1433272 2 0.1031 0.962 0.024 0.976 0.000
#> SRR1075314 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1085590 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1100752 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1391494 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1333263 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1310231 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1094144 2 0.1031 0.962 0.024 0.976 0.000
#> SRR1092160 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1322747 2 0.5291 0.632 0.000 0.732 0.268
#> SRR1432719 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1100728 2 0.1031 0.962 0.024 0.976 0.000
#> SRR1087511 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1470336 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1322536 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1100824 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1085951 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1316420 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1070913 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1345806 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1313872 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1337666 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1076823 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1093954 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1451921 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1491257 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1416979 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1419015 1 0.0000 0.996 1.000 0.000 0.000
#> SRR817649 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1466376 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1319419 3 0.0000 0.977 0.000 0.000 1.000
#> SRR816495 3 0.0000 0.977 0.000 0.000 1.000
#> SRR818694 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1465653 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1465040 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1088461 2 0.0000 0.983 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1400141 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1349585 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1437576 2 0.0000 0.983 0.000 1.000 0.000
#> SRR814407 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1332403 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1099598 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1327723 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1392525 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1320536 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1083824 3 0.5363 0.618 0.000 0.276 0.724
#> SRR1351390 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1309141 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1452803 2 0.0000 0.983 0.000 1.000 0.000
#> SRR811631 2 0.4555 0.747 0.000 0.800 0.200
#> SRR1485563 2 0.4002 0.807 0.160 0.840 0.000
#> SRR1311531 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1353076 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1480831 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1083892 1 0.0000 0.996 1.000 0.000 0.000
#> SRR809873 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1341854 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1464209 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1389886 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1400730 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1448008 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1087606 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.996 1.000 0.000 0.000
#> SRR816865 2 0.1031 0.962 0.024 0.976 0.000
#> SRR1323360 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1417364 3 0.0000 0.977 0.000 0.000 1.000
#> SRR1480329 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1403322 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1082035 1 0.0000 0.996 1.000 0.000 0.000
#> SRR1393046 2 0.0000 0.983 0.000 1.000 0.000
#> SRR1466663 1 0.3340 0.835 0.880 0.120 0.000
#> SRR1384456 1 0.0000 0.996 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0469 0.907 0.000 0.988 0.000 0.012
#> SRR808862 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.0707 0.904 0.000 0.980 0.000 0.020
#> SRR1322683 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1329811 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1087297 2 0.0336 0.908 0.000 0.992 0.000 0.008
#> SRR1072626 4 0.0188 0.787 0.000 0.004 0.000 0.996
#> SRR1407428 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1321029 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1500282 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1100496 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1308778 2 0.0592 0.905 0.000 0.984 0.000 0.016
#> SRR1445304 2 0.0188 0.909 0.000 0.996 0.000 0.004
#> SRR1099378 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1347412 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1099694 2 0.0188 0.909 0.000 0.996 0.000 0.004
#> SRR1088365 2 0.3764 0.743 0.000 0.784 0.000 0.216
#> SRR1325752 1 0.1406 0.920 0.960 0.016 0.000 0.024
#> SRR1416713 2 0.0469 0.907 0.000 0.988 0.000 0.012
#> SRR1074474 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1400507 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1378179 2 0.1022 0.898 0.000 0.968 0.000 0.032
#> SRR1377905 2 0.1118 0.893 0.000 0.964 0.000 0.036
#> SRR1089479 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1073365 2 0.0336 0.908 0.000 0.992 0.000 0.008
#> SRR1500306 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1101566 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1350503 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1446007 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.0707 0.903 0.000 0.980 0.000 0.020
#> SRR1380293 2 0.0000 0.909 0.000 1.000 0.000 0.000
#> SRR1331198 2 0.1118 0.893 0.000 0.964 0.000 0.036
#> SRR1092686 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.3764 0.743 0.000 0.784 0.000 0.216
#> SRR1341650 1 0.6679 0.656 0.652 0.116 0.016 0.216
#> SRR1357276 2 0.0921 0.899 0.000 0.972 0.000 0.028
#> SRR1498374 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1093721 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1464660 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1402051 4 0.1059 0.793 0.012 0.016 0.000 0.972
#> SRR1488734 2 0.0188 0.909 0.000 0.996 0.000 0.004
#> SRR1082616 3 0.3569 0.774 0.000 0.000 0.804 0.196
#> SRR1099427 4 0.3881 0.854 0.000 0.172 0.016 0.812
#> SRR1453093 4 0.0188 0.787 0.000 0.004 0.000 0.996
#> SRR1357064 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR811237 4 0.1211 0.770 0.000 0.040 0.000 0.960
#> SRR1100848 4 0.1302 0.811 0.000 0.044 0.000 0.956
#> SRR1346755 4 0.2081 0.828 0.000 0.084 0.000 0.916
#> SRR1472529 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1398905 3 0.0188 0.967 0.004 0.000 0.996 0.000
#> SRR1082733 2 0.0336 0.908 0.000 0.992 0.000 0.008
#> SRR1308035 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1359080 2 0.2760 0.784 0.000 0.872 0.000 0.128
#> SRR1455825 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1389300 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR812246 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.3764 0.743 0.000 0.784 0.000 0.216
#> SRR1415567 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1331900 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1452099 1 0.4804 0.567 0.616 0.000 0.000 0.384
#> SRR1352346 1 0.2408 0.845 0.896 0.104 0.000 0.000
#> SRR1364034 2 0.2281 0.852 0.000 0.904 0.000 0.096
#> SRR1086046 4 0.4961 -0.166 0.448 0.000 0.000 0.552
#> SRR1407226 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1319363 1 0.3528 0.818 0.808 0.000 0.000 0.192
#> SRR1446961 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1486650 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1454785 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1092329 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1091476 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1073775 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1366873 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1398114 2 0.0592 0.905 0.000 0.984 0.000 0.016
#> SRR1089950 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1433272 2 0.3610 0.759 0.000 0.800 0.000 0.200
#> SRR1075314 1 0.3610 0.811 0.800 0.000 0.000 0.200
#> SRR1085590 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1100752 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1391494 4 0.3873 0.853 0.000 0.228 0.000 0.772
#> SRR1333263 3 0.0469 0.961 0.000 0.000 0.988 0.012
#> SRR1310231 2 0.0188 0.909 0.000 0.996 0.000 0.004
#> SRR1094144 2 0.3801 0.739 0.000 0.780 0.000 0.220
#> SRR1092160 2 0.1118 0.892 0.000 0.964 0.000 0.036
#> SRR1320300 4 0.3801 0.862 0.000 0.220 0.000 0.780
#> SRR1322747 2 0.4983 0.569 0.000 0.704 0.272 0.024
#> SRR1432719 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1100728 2 0.3764 0.743 0.000 0.784 0.000 0.216
#> SRR1087511 4 0.0592 0.797 0.000 0.016 0.000 0.984
#> SRR1470336 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1322536 1 0.3569 0.814 0.804 0.000 0.000 0.196
#> SRR1100824 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1085951 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1322046 2 0.0336 0.908 0.000 0.992 0.000 0.008
#> SRR1316420 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1070913 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1345806 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1313872 2 0.0000 0.909 0.000 1.000 0.000 0.000
#> SRR1337666 2 0.1211 0.889 0.000 0.960 0.000 0.040
#> SRR1076823 1 0.3486 0.820 0.812 0.000 0.000 0.188
#> SRR1093954 2 0.0921 0.900 0.000 0.972 0.000 0.028
#> SRR1451921 1 0.4454 0.691 0.692 0.000 0.000 0.308
#> SRR1491257 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1416979 4 0.1302 0.811 0.000 0.044 0.000 0.956
#> SRR1419015 1 0.3688 0.805 0.792 0.000 0.000 0.208
#> SRR817649 2 0.0469 0.906 0.012 0.988 0.000 0.000
#> SRR1466376 2 0.0707 0.904 0.000 0.980 0.000 0.020
#> SRR1392055 2 0.0921 0.899 0.000 0.972 0.000 0.028
#> SRR1120913 2 0.0469 0.907 0.000 0.988 0.000 0.012
#> SRR1120869 2 0.2704 0.829 0.000 0.876 0.000 0.124
#> SRR1319419 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR816495 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR818694 4 0.1022 0.808 0.000 0.032 0.000 0.968
#> SRR1465653 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1475952 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1465040 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1088461 2 0.0592 0.907 0.000 0.984 0.000 0.016
#> SRR810129 2 0.0592 0.905 0.000 0.984 0.000 0.016
#> SRR1400141 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1437576 4 0.4643 0.696 0.000 0.344 0.000 0.656
#> SRR814407 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1332403 2 0.0000 0.909 0.000 1.000 0.000 0.000
#> SRR1099598 4 0.0188 0.787 0.000 0.004 0.000 0.996
#> SRR1327723 2 0.0469 0.907 0.000 0.988 0.000 0.012
#> SRR1392525 3 0.3764 0.754 0.000 0.000 0.784 0.216
#> SRR1320536 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1083824 3 0.5368 0.434 0.000 0.340 0.636 0.024
#> SRR1351390 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1309141 3 0.1489 0.925 0.000 0.044 0.952 0.004
#> SRR1452803 2 0.0000 0.909 0.000 1.000 0.000 0.000
#> SRR811631 4 0.3764 0.863 0.000 0.216 0.000 0.784
#> SRR1485563 4 0.1211 0.770 0.000 0.040 0.000 0.960
#> SRR1311531 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1353076 4 0.4925 0.487 0.000 0.428 0.000 0.572
#> SRR1480831 2 0.4697 0.575 0.000 0.644 0.000 0.356
#> SRR1083892 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR809873 1 0.3726 0.801 0.788 0.000 0.000 0.212
#> SRR1341854 2 0.0921 0.900 0.000 0.972 0.000 0.028
#> SRR1399335 2 0.0188 0.908 0.000 0.996 0.000 0.004
#> SRR1464209 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1389886 2 0.0469 0.907 0.000 0.988 0.000 0.012
#> SRR1400730 3 0.0188 0.967 0.004 0.000 0.996 0.000
#> SRR1448008 4 0.1022 0.808 0.000 0.032 0.000 0.968
#> SRR1087606 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1445111 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR816865 2 0.3764 0.743 0.000 0.784 0.000 0.216
#> SRR1323360 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.970 0.000 0.000 1.000 0.000
#> SRR1480329 4 0.4011 0.861 0.008 0.208 0.000 0.784
#> SRR1403322 1 0.3486 0.820 0.812 0.000 0.000 0.188
#> SRR1093625 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1479977 4 0.3837 0.858 0.000 0.224 0.000 0.776
#> SRR1082035 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> SRR1393046 2 0.1022 0.896 0.000 0.968 0.000 0.032
#> SRR1466663 2 0.7309 0.376 0.272 0.528 0.000 0.200
#> SRR1384456 1 0.0000 0.942 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0162 0.9054 0.000 0.996 0.000 0.000 0.004
#> SRR808862 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1500382 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1322683 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1329811 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1087297 2 0.0290 0.9048 0.000 0.992 0.000 0.000 0.008
#> SRR1072626 5 0.0771 0.8528 0.000 0.004 0.000 0.020 0.976
#> SRR1407428 1 0.2516 0.8950 0.860 0.000 0.000 0.140 0.000
#> SRR1321029 5 0.3561 0.7444 0.000 0.260 0.000 0.000 0.740
#> SRR1500282 1 0.1410 0.9099 0.940 0.000 0.000 0.060 0.000
#> SRR1100496 3 0.0510 0.9715 0.000 0.000 0.984 0.016 0.000
#> SRR1308778 2 0.2377 0.8473 0.000 0.872 0.000 0.128 0.000
#> SRR1445304 2 0.0290 0.9062 0.000 0.992 0.000 0.008 0.000
#> SRR1099378 1 0.3305 0.6557 0.776 0.000 0.000 0.224 0.000
#> SRR1347412 1 0.2127 0.9053 0.892 0.000 0.000 0.108 0.000
#> SRR1099694 2 0.1484 0.9011 0.000 0.944 0.000 0.048 0.008
#> SRR1088365 4 0.3707 0.5013 0.000 0.284 0.000 0.716 0.000
#> SRR1325752 4 0.2921 0.6544 0.124 0.020 0.000 0.856 0.000
#> SRR1416713 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1074474 1 0.2424 0.8986 0.868 0.000 0.000 0.132 0.000
#> SRR1469369 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1400507 5 0.1965 0.8443 0.000 0.096 0.000 0.000 0.904
#> SRR1378179 2 0.3109 0.7741 0.000 0.800 0.000 0.200 0.000
#> SRR1377905 2 0.0880 0.8931 0.000 0.968 0.000 0.000 0.032
#> SRR1089479 1 0.2516 0.8950 0.860 0.000 0.000 0.140 0.000
#> SRR1073365 2 0.0992 0.9065 0.000 0.968 0.000 0.024 0.008
#> SRR1500306 1 0.4036 0.8331 0.788 0.000 0.000 0.144 0.068
#> SRR1101566 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1350503 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1446007 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.2471 0.8455 0.000 0.864 0.000 0.136 0.000
#> SRR1380293 2 0.0794 0.9042 0.000 0.972 0.000 0.028 0.000
#> SRR1331198 2 0.0703 0.8978 0.000 0.976 0.000 0.000 0.024
#> SRR1092686 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 4 0.2806 0.6626 0.004 0.152 0.000 0.844 0.000
#> SRR1341650 4 0.3455 0.6588 0.208 0.008 0.000 0.784 0.000
#> SRR1357276 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1498374 5 0.3452 0.7585 0.000 0.244 0.000 0.000 0.756
#> SRR1093721 5 0.0771 0.8633 0.000 0.020 0.000 0.004 0.976
#> SRR1464660 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1402051 5 0.0771 0.8523 0.004 0.000 0.000 0.020 0.976
#> SRR1488734 2 0.0703 0.9052 0.000 0.976 0.000 0.024 0.000
#> SRR1082616 4 0.4748 0.0844 0.000 0.000 0.492 0.492 0.016
#> SRR1099427 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1453093 5 0.0794 0.8479 0.000 0.000 0.000 0.028 0.972
#> SRR1357064 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR811237 4 0.4046 0.5200 0.000 0.008 0.000 0.696 0.296
#> SRR1100848 5 0.0290 0.8624 0.000 0.000 0.000 0.008 0.992
#> SRR1346755 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1472529 5 0.2424 0.8268 0.000 0.132 0.000 0.000 0.868
#> SRR1398905 3 0.0693 0.9673 0.008 0.000 0.980 0.012 0.000
#> SRR1082733 2 0.0451 0.9064 0.000 0.988 0.000 0.008 0.004
#> SRR1308035 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.1732 0.8507 0.000 0.920 0.000 0.000 0.080
#> SRR1455825 5 0.3366 0.7678 0.000 0.232 0.000 0.000 0.768
#> SRR1389300 5 0.3612 0.7357 0.000 0.268 0.000 0.000 0.732
#> SRR812246 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 4 0.3003 0.6334 0.000 0.188 0.000 0.812 0.000
#> SRR1415567 1 0.2516 0.8950 0.860 0.000 0.000 0.140 0.000
#> SRR1331900 5 0.3586 0.7400 0.000 0.264 0.000 0.000 0.736
#> SRR1452099 4 0.3146 0.6742 0.052 0.000 0.000 0.856 0.092
#> SRR1352346 1 0.1981 0.8653 0.924 0.028 0.000 0.048 0.000
#> SRR1364034 2 0.3242 0.7537 0.000 0.784 0.000 0.216 0.000
#> SRR1086046 4 0.5947 0.4652 0.132 0.000 0.000 0.556 0.312
#> SRR1407226 1 0.0290 0.9061 0.992 0.000 0.000 0.008 0.000
#> SRR1319363 4 0.2424 0.6493 0.132 0.000 0.000 0.868 0.000
#> SRR1446961 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1486650 1 0.2127 0.9053 0.892 0.000 0.000 0.108 0.000
#> SRR1470152 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1454785 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1092329 5 0.0162 0.8644 0.000 0.004 0.000 0.000 0.996
#> SRR1091476 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1366873 5 0.3366 0.7679 0.000 0.232 0.000 0.000 0.768
#> SRR1398114 2 0.2471 0.8408 0.000 0.864 0.000 0.136 0.000
#> SRR1089950 1 0.1671 0.9093 0.924 0.000 0.000 0.076 0.000
#> SRR1433272 4 0.4401 0.3883 0.016 0.328 0.000 0.656 0.000
#> SRR1075314 4 0.6022 0.3923 0.280 0.000 0.000 0.564 0.156
#> SRR1085590 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1100752 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 5 0.1836 0.8518 0.000 0.036 0.000 0.032 0.932
#> SRR1333263 4 0.4555 0.1150 0.000 0.008 0.472 0.520 0.000
#> SRR1310231 2 0.0000 0.9058 0.000 1.000 0.000 0.000 0.000
#> SRR1094144 4 0.2732 0.6579 0.000 0.160 0.000 0.840 0.000
#> SRR1092160 2 0.1836 0.8955 0.000 0.932 0.000 0.036 0.032
#> SRR1320300 5 0.3508 0.7517 0.000 0.252 0.000 0.000 0.748
#> SRR1322747 2 0.3013 0.7451 0.000 0.832 0.160 0.000 0.008
#> SRR1432719 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 4 0.2773 0.6550 0.000 0.164 0.000 0.836 0.000
#> SRR1087511 5 0.0290 0.8599 0.000 0.000 0.000 0.008 0.992
#> SRR1470336 1 0.3327 0.8741 0.828 0.000 0.000 0.144 0.028
#> SRR1322536 4 0.6085 0.3860 0.280 0.000 0.000 0.556 0.164
#> SRR1100824 1 0.0404 0.9050 0.988 0.000 0.000 0.012 0.000
#> SRR1085951 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1322046 2 0.1251 0.9049 0.000 0.956 0.000 0.036 0.008
#> SRR1316420 1 0.0290 0.9057 0.992 0.000 0.000 0.008 0.000
#> SRR1070913 5 0.1732 0.8502 0.000 0.080 0.000 0.000 0.920
#> SRR1345806 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.1671 0.8877 0.000 0.924 0.000 0.076 0.000
#> SRR1337666 2 0.0794 0.8954 0.000 0.972 0.000 0.000 0.028
#> SRR1076823 4 0.4825 0.1678 0.408 0.000 0.000 0.568 0.024
#> SRR1093954 2 0.2648 0.8274 0.000 0.848 0.000 0.152 0.000
#> SRR1451921 4 0.4509 0.6338 0.096 0.000 0.000 0.752 0.152
#> SRR1491257 1 0.0404 0.9048 0.988 0.000 0.000 0.012 0.000
#> SRR1416979 5 0.0290 0.8630 0.000 0.000 0.000 0.008 0.992
#> SRR1419015 4 0.2561 0.6527 0.144 0.000 0.000 0.856 0.000
#> SRR817649 2 0.1597 0.8987 0.012 0.940 0.000 0.048 0.000
#> SRR1466376 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1392055 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1120913 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1120869 2 0.4262 0.3059 0.000 0.560 0.000 0.440 0.000
#> SRR1319419 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR818694 5 0.0162 0.8619 0.000 0.000 0.000 0.004 0.996
#> SRR1465653 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1475952 1 0.2561 0.8926 0.856 0.000 0.000 0.144 0.000
#> SRR1465040 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 2 0.1908 0.8704 0.000 0.908 0.000 0.092 0.000
#> SRR810129 2 0.2471 0.8408 0.000 0.864 0.000 0.136 0.000
#> SRR1400141 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 1 0.0290 0.9057 0.992 0.000 0.000 0.008 0.000
#> SRR1437576 2 0.3816 0.4435 0.000 0.696 0.000 0.000 0.304
#> SRR814407 1 0.2561 0.8926 0.856 0.000 0.000 0.144 0.000
#> SRR1332403 2 0.1270 0.8973 0.000 0.948 0.000 0.052 0.000
#> SRR1099598 5 0.0771 0.8522 0.000 0.004 0.000 0.020 0.976
#> SRR1327723 2 0.0579 0.9061 0.000 0.984 0.000 0.008 0.008
#> SRR1392525 4 0.4632 0.2070 0.000 0.000 0.448 0.540 0.012
#> SRR1320536 1 0.2280 0.9023 0.880 0.000 0.000 0.120 0.000
#> SRR1083824 2 0.4588 0.3714 0.000 0.604 0.380 0.000 0.016
#> SRR1351390 1 0.2377 0.9004 0.872 0.000 0.000 0.128 0.000
#> SRR1309141 3 0.4704 0.6351 0.000 0.112 0.736 0.152 0.000
#> SRR1452803 2 0.0963 0.9020 0.000 0.964 0.000 0.036 0.000
#> SRR811631 5 0.2189 0.8455 0.000 0.084 0.012 0.000 0.904
#> SRR1485563 4 0.3489 0.6121 0.004 0.004 0.000 0.784 0.208
#> SRR1311531 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 5 0.6102 0.0348 0.000 0.436 0.000 0.124 0.440
#> SRR1480831 4 0.5618 0.4928 0.000 0.280 0.000 0.608 0.112
#> SRR1083892 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR809873 4 0.2230 0.6617 0.116 0.000 0.000 0.884 0.000
#> SRR1341854 2 0.2424 0.8496 0.000 0.868 0.000 0.132 0.000
#> SRR1399335 2 0.1410 0.8916 0.000 0.940 0.000 0.060 0.000
#> SRR1464209 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1389886 2 0.0162 0.9054 0.000 0.996 0.000 0.000 0.004
#> SRR1400730 3 0.0609 0.9668 0.020 0.000 0.980 0.000 0.000
#> SRR1448008 5 0.0324 0.8636 0.000 0.004 0.000 0.004 0.992
#> SRR1087606 1 0.0609 0.9024 0.980 0.000 0.000 0.020 0.000
#> SRR1445111 1 0.2471 0.8970 0.864 0.000 0.000 0.136 0.000
#> SRR816865 4 0.2732 0.6577 0.000 0.160 0.000 0.840 0.000
#> SRR1323360 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.0000 0.9865 0.000 0.000 1.000 0.000 0.000
#> SRR1480329 5 0.0000 0.8639 0.000 0.000 0.000 0.000 1.000
#> SRR1403322 4 0.4173 0.4414 0.300 0.000 0.000 0.688 0.012
#> SRR1093625 1 0.2471 0.8970 0.864 0.000 0.000 0.136 0.000
#> SRR1479977 5 0.4015 0.6127 0.000 0.348 0.000 0.000 0.652
#> SRR1082035 1 0.0290 0.9061 0.992 0.000 0.000 0.008 0.000
#> SRR1393046 2 0.0404 0.9037 0.000 0.988 0.000 0.000 0.012
#> SRR1466663 4 0.3844 0.6754 0.164 0.044 0.000 0.792 0.000
#> SRR1384456 1 0.2424 0.8986 0.868 0.000 0.000 0.132 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0458 0.88608 0.000 0.984 0.000 0.016 0.000 0.000
#> SRR808862 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1500382 2 0.0363 0.88624 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1322683 6 0.0000 0.84198 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1329811 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1087297 2 0.0260 0.88639 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1072626 6 0.1245 0.82704 0.032 0.000 0.000 0.016 0.000 0.952
#> SRR1407428 1 0.3499 0.62091 0.680 0.000 0.000 0.000 0.320 0.000
#> SRR1321029 6 0.4141 0.40950 0.012 0.432 0.000 0.000 0.000 0.556
#> SRR1500282 5 0.2178 0.76385 0.132 0.000 0.000 0.000 0.868 0.000
#> SRR1100496 3 0.0972 0.91032 0.008 0.000 0.964 0.028 0.000 0.000
#> SRR1308778 2 0.3706 0.25481 0.000 0.620 0.000 0.380 0.000 0.000
#> SRR1445304 2 0.0547 0.88567 0.000 0.980 0.000 0.020 0.000 0.000
#> SRR1099378 5 0.3686 0.65731 0.088 0.000 0.000 0.124 0.788 0.000
#> SRR1347412 1 0.3857 0.42780 0.532 0.000 0.000 0.000 0.468 0.000
#> SRR1099694 2 0.2593 0.80024 0.008 0.844 0.000 0.148 0.000 0.000
#> SRR1088365 4 0.0458 0.67807 0.000 0.016 0.000 0.984 0.000 0.000
#> SRR1325752 4 0.1951 0.62026 0.076 0.000 0.000 0.908 0.016 0.000
#> SRR1416713 2 0.0405 0.88627 0.004 0.988 0.000 0.008 0.000 0.000
#> SRR1074474 1 0.3797 0.52015 0.580 0.000 0.000 0.000 0.420 0.000
#> SRR1469369 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1400507 6 0.1563 0.82667 0.012 0.056 0.000 0.000 0.000 0.932
#> SRR1378179 4 0.3695 0.39974 0.000 0.376 0.000 0.624 0.000 0.000
#> SRR1377905 2 0.1078 0.87847 0.012 0.964 0.000 0.008 0.000 0.016
#> SRR1089479 1 0.3515 0.61995 0.676 0.000 0.000 0.000 0.324 0.000
#> SRR1073365 2 0.1610 0.85816 0.000 0.916 0.000 0.084 0.000 0.000
#> SRR1500306 1 0.3770 0.63679 0.728 0.000 0.000 0.000 0.244 0.028
#> SRR1101566 6 0.0000 0.84198 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1350503 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1446007 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 4 0.3810 0.29028 0.000 0.428 0.000 0.572 0.000 0.000
#> SRR1380293 2 0.1657 0.86845 0.000 0.928 0.000 0.056 0.016 0.000
#> SRR1331198 2 0.0363 0.88283 0.012 0.988 0.000 0.000 0.000 0.000
#> SRR1092686 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.0363 0.67340 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1341650 4 0.5253 0.37069 0.200 0.000 0.000 0.608 0.192 0.000
#> SRR1357276 2 0.0146 0.88618 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1498374 6 0.4066 0.48889 0.012 0.392 0.000 0.000 0.000 0.596
#> SRR1093721 6 0.0436 0.84269 0.004 0.004 0.000 0.004 0.000 0.988
#> SRR1464660 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1402051 6 0.1010 0.83303 0.036 0.000 0.000 0.000 0.004 0.960
#> SRR1488734 2 0.1501 0.86393 0.000 0.924 0.000 0.076 0.000 0.000
#> SRR1082616 3 0.5318 0.48748 0.252 0.000 0.588 0.160 0.000 0.000
#> SRR1099427 6 0.0291 0.84231 0.000 0.004 0.004 0.000 0.000 0.992
#> SRR1453093 6 0.1958 0.78548 0.100 0.000 0.000 0.004 0.000 0.896
#> SRR1357064 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR811237 4 0.4205 0.54258 0.084 0.000 0.000 0.728 0.000 0.188
#> SRR1100848 6 0.1542 0.82087 0.052 0.004 0.000 0.008 0.000 0.936
#> SRR1346755 6 0.0000 0.84198 0.000 0.000 0.000 0.000 0.000 1.000
#> SRR1472529 6 0.2121 0.80324 0.012 0.096 0.000 0.000 0.000 0.892
#> SRR1398905 3 0.3287 0.68980 0.220 0.000 0.768 0.000 0.012 0.000
#> SRR1082733 2 0.1075 0.87712 0.000 0.952 0.000 0.048 0.000 0.000
#> SRR1308035 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.1367 0.85597 0.012 0.944 0.000 0.000 0.000 0.044
#> SRR1455825 6 0.4093 0.47007 0.012 0.404 0.000 0.000 0.000 0.584
#> SRR1389300 6 0.4172 0.33801 0.012 0.460 0.000 0.000 0.000 0.528
#> SRR812246 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.0146 0.67502 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1415567 1 0.3515 0.61995 0.676 0.000 0.000 0.000 0.324 0.000
#> SRR1331900 6 0.4165 0.35824 0.012 0.452 0.000 0.000 0.000 0.536
#> SRR1452099 1 0.4484 0.02114 0.516 0.000 0.000 0.460 0.008 0.016
#> SRR1352346 5 0.2052 0.83912 0.028 0.004 0.000 0.056 0.912 0.000
#> SRR1364034 4 0.3409 0.51024 0.000 0.300 0.000 0.700 0.000 0.000
#> SRR1086046 1 0.2020 0.59679 0.896 0.000 0.000 0.000 0.008 0.096
#> SRR1407226 5 0.0937 0.88977 0.040 0.000 0.000 0.000 0.960 0.000
#> SRR1319363 1 0.3841 0.27820 0.616 0.000 0.000 0.380 0.004 0.000
#> SRR1446961 3 0.0260 0.93131 0.008 0.000 0.992 0.000 0.000 0.000
#> SRR1486650 1 0.3867 0.38374 0.512 0.000 0.000 0.000 0.488 0.000
#> SRR1470152 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1454785 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 6 0.0520 0.84184 0.008 0.008 0.000 0.000 0.000 0.984
#> SRR1091476 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 6 0.0146 0.84244 0.000 0.004 0.000 0.000 0.000 0.996
#> SRR1366873 6 0.4015 0.52186 0.012 0.372 0.000 0.000 0.000 0.616
#> SRR1398114 4 0.3867 0.12507 0.000 0.488 0.000 0.512 0.000 0.000
#> SRR1089950 5 0.3101 0.58440 0.244 0.000 0.000 0.000 0.756 0.000
#> SRR1433272 4 0.1296 0.66457 0.012 0.004 0.000 0.952 0.032 0.000
#> SRR1075314 1 0.1219 0.62097 0.948 0.000 0.000 0.000 0.004 0.048
#> SRR1085590 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100752 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 6 0.1230 0.83537 0.008 0.008 0.000 0.028 0.000 0.956
#> SRR1333263 4 0.4629 -0.04172 0.040 0.000 0.436 0.524 0.000 0.000
#> SRR1310231 2 0.0363 0.88625 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1094144 4 0.0363 0.67340 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1092160 2 0.2264 0.84826 0.012 0.888 0.000 0.096 0.000 0.004
#> SRR1320300 6 0.3797 0.44924 0.000 0.420 0.000 0.000 0.000 0.580
#> SRR1322747 2 0.2062 0.82044 0.008 0.900 0.088 0.004 0.000 0.000
#> SRR1432719 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100728 4 0.0363 0.67340 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1087511 6 0.0260 0.84110 0.008 0.000 0.000 0.000 0.000 0.992
#> SRR1470336 1 0.3758 0.63351 0.700 0.000 0.000 0.000 0.284 0.016
#> SRR1322536 1 0.1219 0.62097 0.948 0.000 0.000 0.000 0.004 0.048
#> SRR1100824 5 0.0632 0.90197 0.024 0.000 0.000 0.000 0.976 0.000
#> SRR1085951 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1322046 2 0.2100 0.83833 0.004 0.884 0.000 0.112 0.000 0.000
#> SRR1316420 5 0.0363 0.90552 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1070913 6 0.1151 0.83564 0.012 0.032 0.000 0.000 0.000 0.956
#> SRR1345806 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.2982 0.78479 0.008 0.828 0.000 0.152 0.012 0.000
#> SRR1337666 2 0.0363 0.88283 0.012 0.988 0.000 0.000 0.000 0.000
#> SRR1076823 1 0.0653 0.62483 0.980 0.000 0.000 0.004 0.012 0.004
#> SRR1093954 4 0.3765 0.34192 0.000 0.404 0.000 0.596 0.000 0.000
#> SRR1451921 1 0.1370 0.62116 0.948 0.000 0.000 0.012 0.004 0.036
#> SRR1491257 5 0.0363 0.90552 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1416979 6 0.0870 0.83941 0.012 0.004 0.000 0.012 0.000 0.972
#> SRR1419015 1 0.4756 0.23572 0.564 0.000 0.000 0.380 0.056 0.000
#> SRR817649 2 0.3062 0.74972 0.000 0.824 0.000 0.032 0.144 0.000
#> SRR1466376 2 0.0508 0.88328 0.012 0.984 0.000 0.004 0.000 0.000
#> SRR1392055 2 0.0260 0.88595 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1120913 2 0.0405 0.88627 0.004 0.988 0.000 0.008 0.000 0.000
#> SRR1120869 4 0.0713 0.67842 0.000 0.028 0.000 0.972 0.000 0.000
#> SRR1319419 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR816495 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR818694 6 0.0146 0.84145 0.004 0.000 0.000 0.000 0.000 0.996
#> SRR1465653 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1475952 1 0.3371 0.63166 0.708 0.000 0.000 0.000 0.292 0.000
#> SRR1465040 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 2 0.3531 0.42263 0.000 0.672 0.000 0.328 0.000 0.000
#> SRR810129 4 0.3868 0.11007 0.000 0.496 0.000 0.504 0.000 0.000
#> SRR1400141 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 5 0.0363 0.90552 0.012 0.000 0.000 0.000 0.988 0.000
#> SRR1437576 2 0.2566 0.78276 0.012 0.868 0.000 0.008 0.000 0.112
#> SRR814407 1 0.3288 0.63931 0.724 0.000 0.000 0.000 0.276 0.000
#> SRR1332403 2 0.2597 0.75893 0.000 0.824 0.000 0.176 0.000 0.000
#> SRR1099598 6 0.1245 0.82492 0.016 0.000 0.000 0.032 0.000 0.952
#> SRR1327723 2 0.0632 0.88527 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1392525 3 0.5711 0.32504 0.208 0.000 0.516 0.276 0.000 0.000
#> SRR1320536 1 0.3847 0.45728 0.544 0.000 0.000 0.000 0.456 0.000
#> SRR1083824 2 0.3314 0.62784 0.012 0.764 0.224 0.000 0.000 0.000
#> SRR1351390 5 0.3823 -0.00969 0.436 0.000 0.000 0.000 0.564 0.000
#> SRR1309141 3 0.5044 0.37710 0.024 0.040 0.576 0.360 0.000 0.000
#> SRR1452803 2 0.0937 0.88080 0.000 0.960 0.000 0.040 0.000 0.000
#> SRR811631 6 0.1332 0.83547 0.012 0.028 0.008 0.000 0.000 0.952
#> SRR1485563 4 0.4828 0.47115 0.176 0.000 0.000 0.668 0.000 0.156
#> SRR1311531 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.5831 0.40641 0.000 0.244 0.000 0.492 0.000 0.264
#> SRR1480831 4 0.4944 0.63104 0.080 0.136 0.000 0.720 0.000 0.064
#> SRR1083892 5 0.0000 0.90609 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR809873 1 0.3841 0.27820 0.616 0.000 0.000 0.380 0.004 0.000
#> SRR1341854 4 0.3860 0.17612 0.000 0.472 0.000 0.528 0.000 0.000
#> SRR1399335 2 0.2378 0.77895 0.000 0.848 0.000 0.152 0.000 0.000
#> SRR1464209 5 0.0260 0.90597 0.008 0.000 0.000 0.000 0.992 0.000
#> SRR1389886 2 0.0146 0.88616 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1400730 3 0.2454 0.78935 0.000 0.000 0.840 0.000 0.160 0.000
#> SRR1448008 6 0.1908 0.82233 0.056 0.028 0.000 0.000 0.000 0.916
#> SRR1087606 5 0.0260 0.90162 0.008 0.000 0.000 0.000 0.992 0.000
#> SRR1445111 1 0.3647 0.58973 0.640 0.000 0.000 0.000 0.360 0.000
#> SRR816865 4 0.0363 0.67340 0.012 0.000 0.000 0.988 0.000 0.000
#> SRR1323360 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.0000 0.93737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1480329 6 0.0260 0.84109 0.008 0.000 0.000 0.000 0.000 0.992
#> SRR1403322 1 0.0603 0.62236 0.980 0.000 0.000 0.016 0.004 0.000
#> SRR1093625 1 0.3706 0.57035 0.620 0.000 0.000 0.000 0.380 0.000
#> SRR1479977 2 0.3784 0.39009 0.012 0.680 0.000 0.000 0.000 0.308
#> SRR1082035 5 0.1075 0.88955 0.048 0.000 0.000 0.000 0.952 0.000
#> SRR1393046 2 0.0520 0.88471 0.008 0.984 0.000 0.008 0.000 0.000
#> SRR1466663 4 0.4431 0.48524 0.084 0.004 0.000 0.712 0.200 0.000
#> SRR1384456 1 0.3797 0.52015 0.580 0.000 0.000 0.000 0.420 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "pam"]
# you can also extract it by
# res = res_list["SD:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 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 0.248 0.655 0.833 0.3764 0.654 0.654
#> 3 3 0.551 0.725 0.879 0.5958 0.671 0.525
#> 4 4 0.668 0.779 0.875 0.1653 0.751 0.473
#> 5 5 0.694 0.830 0.886 0.0704 0.937 0.791
#> 6 6 0.698 0.523 0.735 0.0603 0.938 0.780
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
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
#> SRR810713 2 0.0000 0.8016 0.000 1.000
#> SRR808862 1 0.8909 0.2975 0.692 0.308
#> SRR1500382 2 0.0000 0.8016 0.000 1.000
#> SRR1322683 2 0.0376 0.8012 0.004 0.996
#> SRR1329811 1 0.9977 0.4294 0.528 0.472
#> SRR1087297 2 0.0000 0.8016 0.000 1.000
#> SRR1072626 2 0.0000 0.8016 0.000 1.000
#> SRR1407428 1 0.7815 0.8101 0.768 0.232
#> SRR1321029 2 0.0376 0.8012 0.004 0.996
#> SRR1500282 1 0.7299 0.8047 0.796 0.204
#> SRR1100496 2 0.9323 0.5539 0.348 0.652
#> SRR1308778 2 0.0000 0.8016 0.000 1.000
#> SRR1445304 2 0.0000 0.8016 0.000 1.000
#> SRR1099378 1 1.0000 0.2600 0.504 0.496
#> SRR1347412 1 0.7602 0.8078 0.780 0.220
#> SRR1099694 2 0.0000 0.8016 0.000 1.000
#> SRR1088365 2 0.5629 0.7292 0.132 0.868
#> SRR1325752 2 0.8909 0.4374 0.308 0.692
#> SRR1416713 2 0.0000 0.8016 0.000 1.000
#> SRR1074474 1 0.7376 0.8056 0.792 0.208
#> SRR1469369 2 0.7528 0.6355 0.216 0.784
#> SRR1400507 2 0.0376 0.8012 0.004 0.996
#> SRR1378179 2 0.0000 0.8016 0.000 1.000
#> SRR1377905 2 0.0376 0.8012 0.004 0.996
#> SRR1089479 1 0.7376 0.8056 0.792 0.208
#> SRR1073365 2 0.0000 0.8016 0.000 1.000
#> SRR1500306 2 0.9661 -0.0962 0.392 0.608
#> SRR1101566 2 0.1633 0.7904 0.024 0.976
#> SRR1350503 2 0.7376 0.6395 0.208 0.792
#> SRR1446007 2 0.7815 0.6298 0.232 0.768
#> SRR1102875 2 0.0000 0.8016 0.000 1.000
#> SRR1380293 2 0.0000 0.8016 0.000 1.000
#> SRR1331198 2 0.0376 0.8012 0.004 0.996
#> SRR1092686 2 0.9248 0.5620 0.340 0.660
#> SRR1069421 2 0.5737 0.7270 0.136 0.864
#> SRR1341650 2 0.8713 0.5177 0.292 0.708
#> SRR1357276 2 0.0000 0.8016 0.000 1.000
#> SRR1498374 2 0.0376 0.8012 0.004 0.996
#> SRR1093721 2 0.0000 0.8016 0.000 1.000
#> SRR1464660 1 0.9754 0.5824 0.592 0.408
#> SRR1402051 2 0.9044 0.2796 0.320 0.680
#> SRR1488734 2 0.0000 0.8016 0.000 1.000
#> SRR1082616 2 0.9393 0.5459 0.356 0.644
#> SRR1099427 2 0.0376 0.8012 0.004 0.996
#> SRR1453093 2 0.5946 0.6401 0.144 0.856
#> SRR1357064 1 0.7815 0.8101 0.768 0.232
#> SRR811237 2 0.1633 0.7944 0.024 0.976
#> SRR1100848 2 0.0000 0.8016 0.000 1.000
#> SRR1346755 2 0.0000 0.8016 0.000 1.000
#> SRR1472529 2 0.0000 0.8016 0.000 1.000
#> SRR1398905 1 0.0000 0.6224 1.000 0.000
#> SRR1082733 2 0.0000 0.8016 0.000 1.000
#> SRR1308035 2 0.9248 0.5620 0.340 0.660
#> SRR1466445 2 0.9248 0.5620 0.340 0.660
#> SRR1359080 2 0.0376 0.8012 0.004 0.996
#> SRR1455825 2 0.0376 0.8012 0.004 0.996
#> SRR1389300 2 0.0376 0.8012 0.004 0.996
#> SRR812246 2 0.9661 0.4870 0.392 0.608
#> SRR1076632 2 0.4939 0.7412 0.108 0.892
#> SRR1415567 1 0.7376 0.8056 0.792 0.208
#> SRR1331900 2 0.0000 0.8016 0.000 1.000
#> SRR1452099 2 0.8909 0.4704 0.308 0.692
#> SRR1352346 1 0.9661 0.6868 0.608 0.392
#> SRR1364034 2 0.0672 0.8006 0.008 0.992
#> SRR1086046 2 0.7602 0.4946 0.220 0.780
#> SRR1407226 1 0.7376 0.8056 0.792 0.208
#> SRR1319363 1 0.9998 0.2682 0.508 0.492
#> SRR1446961 2 0.7219 0.6478 0.200 0.800
#> SRR1486650 1 0.7883 0.8090 0.764 0.236
#> SRR1470152 1 0.8813 0.7709 0.700 0.300
#> SRR1454785 2 0.9248 0.5620 0.340 0.660
#> SRR1092329 2 0.1843 0.7944 0.028 0.972
#> SRR1091476 2 0.9977 0.3264 0.472 0.528
#> SRR1073775 2 0.0376 0.8012 0.004 0.996
#> SRR1366873 2 0.0376 0.8012 0.004 0.996
#> SRR1398114 2 0.4939 0.7412 0.108 0.892
#> SRR1089950 2 0.9552 -0.0455 0.376 0.624
#> SRR1433272 2 0.5629 0.7292 0.132 0.868
#> SRR1075314 2 0.9460 0.0159 0.364 0.636
#> SRR1085590 2 0.9209 0.5637 0.336 0.664
#> SRR1100752 2 0.9248 0.5620 0.340 0.660
#> SRR1391494 2 0.1633 0.7944 0.024 0.976
#> SRR1333263 2 0.9129 0.5723 0.328 0.672
#> SRR1310231 2 0.0000 0.8016 0.000 1.000
#> SRR1094144 2 0.5737 0.7276 0.136 0.864
#> SRR1092160 2 0.0000 0.8016 0.000 1.000
#> SRR1320300 2 0.0000 0.8016 0.000 1.000
#> SRR1322747 2 0.0376 0.8012 0.004 0.996
#> SRR1432719 2 0.9248 0.5620 0.340 0.660
#> SRR1100728 2 0.5629 0.7292 0.132 0.868
#> SRR1087511 2 0.8386 0.3701 0.268 0.732
#> SRR1470336 1 0.9909 0.5998 0.556 0.444
#> SRR1322536 2 0.9427 0.0489 0.360 0.640
#> SRR1100824 1 0.7376 0.8056 0.792 0.208
#> SRR1085951 1 0.9993 -0.2354 0.516 0.484
#> SRR1322046 2 0.4939 0.7412 0.108 0.892
#> SRR1316420 1 0.9248 0.7316 0.660 0.340
#> SRR1070913 2 0.0376 0.8012 0.004 0.996
#> SRR1345806 2 0.9248 0.5620 0.340 0.660
#> SRR1313872 2 0.2603 0.7879 0.044 0.956
#> SRR1337666 2 0.0376 0.8012 0.004 0.996
#> SRR1076823 1 0.9993 0.2962 0.516 0.484
#> SRR1093954 2 0.0000 0.8016 0.000 1.000
#> SRR1451921 2 0.9000 0.4476 0.316 0.684
#> SRR1491257 1 0.7950 0.7924 0.760 0.240
#> SRR1416979 2 0.1633 0.7944 0.024 0.976
#> SRR1419015 2 0.9248 0.3866 0.340 0.660
#> SRR817649 2 0.0000 0.8016 0.000 1.000
#> SRR1466376 2 0.0000 0.8016 0.000 1.000
#> SRR1392055 2 0.0000 0.8016 0.000 1.000
#> SRR1120913 2 0.0000 0.8016 0.000 1.000
#> SRR1120869 2 0.5842 0.7253 0.140 0.860
#> SRR1319419 2 0.9000 0.5784 0.316 0.684
#> SRR816495 2 0.8955 0.5817 0.312 0.688
#> SRR818694 2 0.6531 0.6074 0.168 0.832
#> SRR1465653 1 0.9522 0.7077 0.628 0.372
#> SRR1475952 1 0.9248 0.7316 0.660 0.340
#> SRR1465040 2 0.8081 0.6234 0.248 0.752
#> SRR1088461 2 0.4939 0.7412 0.108 0.892
#> SRR810129 2 0.1633 0.7944 0.024 0.976
#> SRR1400141 2 0.9248 0.5620 0.340 0.660
#> SRR1349585 1 0.7815 0.8101 0.768 0.232
#> SRR1437576 2 0.1843 0.7944 0.028 0.972
#> SRR814407 1 0.0672 0.6300 0.992 0.008
#> SRR1332403 2 0.0000 0.8016 0.000 1.000
#> SRR1099598 2 0.6343 0.6146 0.160 0.840
#> SRR1327723 2 0.0000 0.8016 0.000 1.000
#> SRR1392525 2 0.9209 0.5637 0.336 0.664
#> SRR1320536 1 0.7815 0.8101 0.768 0.232
#> SRR1083824 2 0.0376 0.8012 0.004 0.996
#> SRR1351390 2 0.9608 -0.0626 0.384 0.616
#> SRR1309141 2 0.6048 0.7232 0.148 0.852
#> SRR1452803 2 0.0000 0.8016 0.000 1.000
#> SRR811631 2 0.0672 0.8002 0.008 0.992
#> SRR1485563 2 0.7815 0.5272 0.232 0.768
#> SRR1311531 2 0.7376 0.6395 0.208 0.792
#> SRR1353076 2 0.0000 0.8016 0.000 1.000
#> SRR1480831 2 0.5294 0.6770 0.120 0.880
#> SRR1083892 1 0.7815 0.8101 0.768 0.232
#> SRR809873 2 1.0000 -0.2470 0.496 0.504
#> SRR1341854 2 0.3431 0.7779 0.064 0.936
#> SRR1399335 2 0.5629 0.7292 0.132 0.868
#> SRR1464209 1 0.7453 0.8072 0.788 0.212
#> SRR1389886 2 0.0000 0.8016 0.000 1.000
#> SRR1400730 1 0.4815 0.5809 0.896 0.104
#> SRR1448008 2 0.0376 0.8012 0.004 0.996
#> SRR1087606 1 0.9358 0.7227 0.648 0.352
#> SRR1445111 1 0.8909 0.7602 0.692 0.308
#> SRR816865 2 0.5737 0.7276 0.136 0.864
#> SRR1323360 2 0.9248 0.5620 0.340 0.660
#> SRR1417364 2 0.9000 0.5784 0.316 0.684
#> SRR1480329 2 0.7815 0.4560 0.232 0.768
#> SRR1403322 2 1.0000 -0.2470 0.496 0.504
#> SRR1093625 1 0.7602 0.8092 0.780 0.220
#> SRR1479977 2 0.0376 0.8012 0.004 0.996
#> SRR1082035 2 0.9661 -0.0976 0.392 0.608
#> SRR1393046 2 0.0000 0.8016 0.000 1.000
#> SRR1466663 2 0.5842 0.7243 0.140 0.860
#> SRR1384456 1 0.7815 0.8101 0.768 0.232
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1500382 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1322683 2 0.2096 0.8334 0.052 0.944 0.004
#> SRR1329811 2 0.8714 0.0698 0.408 0.484 0.108
#> SRR1087297 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1072626 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1321029 2 0.3038 0.7886 0.000 0.896 0.104
#> SRR1500282 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1100496 3 0.0237 0.8433 0.000 0.004 0.996
#> SRR1308778 2 0.0424 0.8681 0.008 0.992 0.000
#> SRR1445304 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1099378 1 0.8063 0.5878 0.644 0.132 0.224
#> SRR1347412 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1099694 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1088365 2 0.4842 0.6939 0.000 0.776 0.224
#> SRR1325752 2 0.9561 0.1352 0.316 0.468 0.216
#> SRR1416713 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1074474 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1469369 3 0.4931 0.6574 0.000 0.232 0.768
#> SRR1400507 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1378179 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1377905 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1089479 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1073365 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1500306 1 0.5803 0.6724 0.736 0.248 0.016
#> SRR1101566 2 0.9715 -0.2241 0.220 0.400 0.380
#> SRR1350503 3 0.4842 0.6651 0.000 0.224 0.776
#> SRR1446007 3 0.4750 0.6731 0.000 0.216 0.784
#> SRR1102875 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1380293 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1331198 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1092686 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1069421 2 0.6715 0.6388 0.056 0.716 0.228
#> SRR1341650 2 0.9641 0.1029 0.316 0.456 0.228
#> SRR1357276 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1498374 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1093721 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1464660 1 0.7588 0.6127 0.684 0.196 0.120
#> SRR1402051 1 0.6664 0.2954 0.528 0.464 0.008
#> SRR1488734 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1082616 3 0.0237 0.8433 0.000 0.004 0.996
#> SRR1099427 2 0.8790 0.1582 0.132 0.540 0.328
#> SRR1453093 2 0.3619 0.7401 0.136 0.864 0.000
#> SRR1357064 1 0.0424 0.7955 0.992 0.008 0.000
#> SRR811237 2 0.0661 0.8672 0.004 0.988 0.008
#> SRR1100848 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1346755 2 0.5618 0.6775 0.156 0.796 0.048
#> SRR1472529 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1398905 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1082733 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1308035 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1359080 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1455825 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1389300 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR812246 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1076632 2 0.5860 0.6742 0.024 0.748 0.228
#> SRR1415567 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1331900 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1452099 3 0.9263 0.2528 0.220 0.252 0.528
#> SRR1352346 1 0.5138 0.6811 0.748 0.252 0.000
#> SRR1364034 2 0.2261 0.8323 0.000 0.932 0.068
#> SRR1086046 2 0.8521 -0.2202 0.440 0.468 0.092
#> SRR1407226 1 0.3267 0.7443 0.884 0.000 0.116
#> SRR1319363 1 0.8063 0.5866 0.644 0.132 0.224
#> SRR1446961 3 0.6225 0.3331 0.000 0.432 0.568
#> SRR1486650 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1470152 1 0.3267 0.7401 0.884 0.116 0.000
#> SRR1454785 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1092329 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1091476 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1073775 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1366873 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1398114 2 0.4750 0.7014 0.000 0.784 0.216
#> SRR1089950 1 0.5178 0.6734 0.744 0.256 0.000
#> SRR1433272 2 0.4842 0.6939 0.000 0.776 0.224
#> SRR1075314 1 0.6434 0.5078 0.612 0.380 0.008
#> SRR1085590 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1100752 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1391494 2 0.0592 0.8654 0.012 0.988 0.000
#> SRR1333263 2 0.5650 0.5812 0.000 0.688 0.312
#> SRR1310231 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1094144 2 0.4750 0.7014 0.000 0.784 0.216
#> SRR1092160 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1320300 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1322747 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1432719 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1100728 2 0.4887 0.6897 0.000 0.772 0.228
#> SRR1087511 3 0.9929 0.0630 0.296 0.312 0.392
#> SRR1470336 1 0.1031 0.7931 0.976 0.024 0.000
#> SRR1322536 1 0.8255 0.5696 0.620 0.252 0.128
#> SRR1100824 1 0.5406 0.6642 0.764 0.012 0.224
#> SRR1085951 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1322046 2 0.4750 0.7014 0.000 0.784 0.216
#> SRR1316420 1 0.3965 0.7583 0.860 0.132 0.008
#> SRR1070913 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1345806 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1313872 2 0.1964 0.8438 0.000 0.944 0.056
#> SRR1337666 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1076823 1 0.5687 0.6598 0.756 0.020 0.224
#> SRR1093954 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1451921 2 0.9734 -0.1029 0.376 0.400 0.224
#> SRR1491257 1 0.5449 0.7349 0.816 0.068 0.116
#> SRR1416979 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1419015 3 0.7379 0.1427 0.376 0.040 0.584
#> SRR817649 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1466376 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1392055 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1120913 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1120869 2 0.4842 0.6939 0.000 0.776 0.224
#> SRR1319419 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR816495 3 0.3879 0.7383 0.000 0.152 0.848
#> SRR818694 2 0.9050 0.1653 0.168 0.536 0.296
#> SRR1465653 1 0.6235 0.3079 0.564 0.436 0.000
#> SRR1475952 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1465040 3 0.4750 0.6731 0.000 0.216 0.784
#> SRR1088461 2 0.4750 0.7014 0.000 0.784 0.216
#> SRR810129 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1400141 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1349585 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1437576 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR814407 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1332403 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1099598 2 0.5431 0.4843 0.284 0.716 0.000
#> SRR1327723 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1392525 3 0.0424 0.8416 0.000 0.008 0.992
#> SRR1320536 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1083824 2 0.0424 0.8707 0.000 0.992 0.008
#> SRR1351390 1 0.7259 0.6319 0.680 0.248 0.072
#> SRR1309141 2 0.4974 0.6857 0.000 0.764 0.236
#> SRR1452803 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR811631 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1485563 2 0.6713 0.0922 0.416 0.572 0.012
#> SRR1311531 3 0.4750 0.6731 0.000 0.216 0.784
#> SRR1353076 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1480831 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1083892 1 0.0592 0.7955 0.988 0.012 0.000
#> SRR809873 1 0.6677 0.5392 0.652 0.024 0.324
#> SRR1341854 2 0.3686 0.7745 0.000 0.860 0.140
#> SRR1399335 2 0.4931 0.6894 0.000 0.768 0.232
#> SRR1464209 1 0.0424 0.7955 0.992 0.008 0.000
#> SRR1389886 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1400730 3 0.2261 0.7960 0.068 0.000 0.932
#> SRR1448008 2 0.0000 0.8719 0.000 1.000 0.000
#> SRR1087606 1 0.3686 0.7558 0.860 0.140 0.000
#> SRR1445111 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR816865 2 0.4842 0.6939 0.000 0.776 0.224
#> SRR1323360 3 0.0000 0.8465 0.000 0.000 1.000
#> SRR1417364 3 0.2959 0.7812 0.000 0.100 0.900
#> SRR1480329 1 0.6489 0.3252 0.540 0.456 0.004
#> SRR1403322 1 0.5595 0.6568 0.756 0.016 0.228
#> SRR1093625 1 0.0000 0.7946 1.000 0.000 0.000
#> SRR1479977 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1082035 1 0.5502 0.6776 0.744 0.248 0.008
#> SRR1393046 2 0.0237 0.8723 0.000 0.996 0.004
#> SRR1466663 2 0.7106 0.6258 0.076 0.700 0.224
#> SRR1384456 1 0.0000 0.7946 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0336 0.8634 0.000 0.992 0.000 0.008
#> SRR808862 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.0188 0.8626 0.000 0.996 0.000 0.004
#> SRR1322683 2 0.1792 0.8244 0.000 0.932 0.000 0.068
#> SRR1329811 2 0.6477 0.1024 0.420 0.508 0.000 0.072
#> SRR1087297 2 0.0336 0.8634 0.000 0.992 0.000 0.008
#> SRR1072626 4 0.4454 0.7766 0.000 0.308 0.000 0.692
#> SRR1407428 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1321029 2 0.2737 0.7806 0.000 0.888 0.104 0.008
#> SRR1500282 1 0.0592 0.8961 0.984 0.000 0.000 0.016
#> SRR1100496 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1308778 2 0.0469 0.8604 0.000 0.988 0.000 0.012
#> SRR1445304 2 0.0188 0.8626 0.000 0.996 0.000 0.004
#> SRR1099378 4 0.4122 0.7911 0.000 0.236 0.004 0.760
#> SRR1347412 1 0.0188 0.8972 0.996 0.000 0.000 0.004
#> SRR1099694 2 0.2281 0.8110 0.000 0.904 0.000 0.096
#> SRR1088365 4 0.2125 0.7393 0.000 0.076 0.004 0.920
#> SRR1325752 4 0.2466 0.7085 0.000 0.096 0.004 0.900
#> SRR1416713 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1074474 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.3870 0.6557 0.000 0.208 0.788 0.004
#> SRR1400507 2 0.1118 0.8422 0.000 0.964 0.000 0.036
#> SRR1378179 2 0.3942 0.6754 0.000 0.764 0.000 0.236
#> SRR1377905 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1089479 1 0.0592 0.8961 0.984 0.000 0.000 0.016
#> SRR1073365 2 0.1022 0.8553 0.000 0.968 0.000 0.032
#> SRR1500306 4 0.4262 0.7879 0.008 0.236 0.000 0.756
#> SRR1101566 4 0.6528 0.7252 0.000 0.300 0.104 0.596
#> SRR1350503 3 0.0188 0.9691 0.000 0.004 0.996 0.000
#> SRR1446007 3 0.0188 0.9691 0.000 0.004 0.996 0.000
#> SRR1102875 2 0.0921 0.8552 0.000 0.972 0.000 0.028
#> SRR1380293 2 0.0336 0.8636 0.000 0.992 0.000 0.008
#> SRR1331198 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1092686 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1069421 4 0.1902 0.7380 0.000 0.064 0.004 0.932
#> SRR1341650 4 0.1902 0.7378 0.000 0.064 0.004 0.932
#> SRR1357276 2 0.0188 0.8634 0.000 0.996 0.000 0.004
#> SRR1498374 2 0.0817 0.8525 0.000 0.976 0.000 0.024
#> SRR1093721 2 0.1474 0.8396 0.000 0.948 0.000 0.052
#> SRR1464660 2 0.6773 0.0831 0.420 0.500 0.008 0.072
#> SRR1402051 4 0.4072 0.7905 0.000 0.252 0.000 0.748
#> SRR1488734 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1082616 4 0.4522 0.4044 0.000 0.000 0.320 0.680
#> SRR1099427 4 0.4673 0.7865 0.000 0.292 0.008 0.700
#> SRR1453093 4 0.4431 0.7814 0.000 0.304 0.000 0.696
#> SRR1357064 1 0.2053 0.8748 0.924 0.004 0.000 0.072
#> SRR811237 4 0.4356 0.7872 0.000 0.292 0.000 0.708
#> SRR1100848 4 0.4431 0.7773 0.000 0.304 0.000 0.696
#> SRR1346755 4 0.4343 0.7898 0.000 0.264 0.004 0.732
#> SRR1472529 2 0.0336 0.8625 0.000 0.992 0.000 0.008
#> SRR1398905 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1082733 2 0.3975 0.6756 0.000 0.760 0.000 0.240
#> SRR1308035 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1359080 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1455825 2 0.0336 0.8625 0.000 0.992 0.000 0.008
#> SRR1389300 2 0.0336 0.8635 0.000 0.992 0.000 0.008
#> SRR812246 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1076632 4 0.2334 0.7383 0.000 0.088 0.004 0.908
#> SRR1415567 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1331900 2 0.0000 0.8635 0.000 1.000 0.000 0.000
#> SRR1452099 4 0.0779 0.7082 0.000 0.004 0.016 0.980
#> SRR1352346 2 0.5693 0.5428 0.240 0.688 0.000 0.072
#> SRR1364034 2 0.4304 0.6367 0.000 0.716 0.000 0.284
#> SRR1086046 4 0.3024 0.7846 0.000 0.148 0.000 0.852
#> SRR1407226 1 0.4855 0.5397 0.644 0.000 0.004 0.352
#> SRR1319363 4 0.0657 0.7103 0.000 0.012 0.004 0.984
#> SRR1446961 3 0.4228 0.6285 0.000 0.232 0.760 0.008
#> SRR1486650 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.4740 0.7741 0.788 0.132 0.000 0.080
#> SRR1454785 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1092329 4 0.4454 0.7766 0.000 0.308 0.000 0.692
#> SRR1091476 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1073775 4 0.4585 0.7545 0.000 0.332 0.000 0.668
#> SRR1366873 2 0.0188 0.8626 0.000 0.996 0.000 0.004
#> SRR1398114 2 0.4313 0.6532 0.000 0.736 0.004 0.260
#> SRR1089950 4 0.7299 0.5263 0.224 0.240 0.000 0.536
#> SRR1433272 2 0.4343 0.6527 0.000 0.732 0.004 0.264
#> SRR1075314 4 0.4040 0.7899 0.000 0.248 0.000 0.752
#> SRR1085590 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1100752 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.3873 0.5547 0.000 0.772 0.000 0.228
#> SRR1333263 4 0.5658 0.3754 0.000 0.328 0.040 0.632
#> SRR1310231 2 0.0188 0.8634 0.000 0.996 0.000 0.004
#> SRR1094144 4 0.2125 0.7393 0.000 0.076 0.004 0.920
#> SRR1092160 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1320300 2 0.0921 0.8516 0.000 0.972 0.000 0.028
#> SRR1322747 2 0.0188 0.8634 0.000 0.996 0.000 0.004
#> SRR1432719 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1100728 4 0.2266 0.7376 0.000 0.084 0.004 0.912
#> SRR1087511 4 0.5791 0.7674 0.000 0.284 0.060 0.656
#> SRR1470336 1 0.3970 0.8096 0.840 0.084 0.000 0.076
#> SRR1322536 4 0.4188 0.7899 0.000 0.244 0.004 0.752
#> SRR1100824 1 0.6934 0.6088 0.588 0.020 0.084 0.308
#> SRR1085951 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1322046 2 0.4155 0.6714 0.000 0.756 0.004 0.240
#> SRR1316420 1 0.5815 0.6921 0.708 0.152 0.000 0.140
#> SRR1070913 2 0.0592 0.8601 0.000 0.984 0.000 0.016
#> SRR1345806 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1313872 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR1337666 2 0.0336 0.8636 0.000 0.992 0.000 0.008
#> SRR1076823 4 0.4980 0.7796 0.044 0.196 0.004 0.756
#> SRR1093954 2 0.2647 0.7964 0.000 0.880 0.000 0.120
#> SRR1451921 4 0.0779 0.7146 0.000 0.016 0.004 0.980
#> SRR1491257 1 0.6695 0.1725 0.504 0.416 0.004 0.076
#> SRR1416979 4 0.4431 0.7773 0.000 0.304 0.000 0.696
#> SRR1419015 4 0.1174 0.7117 0.000 0.020 0.012 0.968
#> SRR817649 2 0.0469 0.8631 0.000 0.988 0.000 0.012
#> SRR1466376 2 0.0336 0.8635 0.000 0.992 0.000 0.008
#> SRR1392055 2 0.0188 0.8626 0.000 0.996 0.000 0.004
#> SRR1120913 2 0.0336 0.8636 0.000 0.992 0.000 0.008
#> SRR1120869 2 0.4855 0.5323 0.000 0.644 0.004 0.352
#> SRR1319419 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR816495 3 0.0188 0.9691 0.000 0.004 0.996 0.000
#> SRR818694 4 0.4673 0.7850 0.000 0.292 0.008 0.700
#> SRR1465653 2 0.6532 0.0905 0.420 0.504 0.000 0.076
#> SRR1475952 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1465040 3 0.0188 0.9691 0.000 0.004 0.996 0.000
#> SRR1088461 4 0.2197 0.7423 0.000 0.080 0.004 0.916
#> SRR810129 2 0.0336 0.8620 0.000 0.992 0.000 0.008
#> SRR1400141 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.1792 0.8775 0.932 0.000 0.000 0.068
#> SRR1437576 2 0.0469 0.8632 0.000 0.988 0.000 0.012
#> SRR814407 1 0.0592 0.8961 0.984 0.000 0.000 0.016
#> SRR1332403 2 0.3907 0.6799 0.000 0.768 0.000 0.232
#> SRR1099598 4 0.4431 0.7822 0.000 0.304 0.000 0.696
#> SRR1327723 2 0.0336 0.8634 0.000 0.992 0.000 0.008
#> SRR1392525 4 0.4950 0.2281 0.000 0.004 0.376 0.620
#> SRR1320536 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.0657 0.8631 0.000 0.984 0.004 0.012
#> SRR1351390 4 0.4088 0.7890 0.004 0.232 0.000 0.764
#> SRR1309141 2 0.2623 0.8209 0.000 0.908 0.028 0.064
#> SRR1452803 2 0.0336 0.8634 0.000 0.992 0.000 0.008
#> SRR811631 2 0.0336 0.8625 0.000 0.992 0.000 0.008
#> SRR1485563 4 0.4103 0.7906 0.000 0.256 0.000 0.744
#> SRR1311531 3 0.0188 0.9691 0.000 0.004 0.996 0.000
#> SRR1353076 4 0.4746 0.7106 0.000 0.368 0.000 0.632
#> SRR1480831 4 0.4522 0.7714 0.000 0.320 0.000 0.680
#> SRR1083892 1 0.3616 0.8486 0.852 0.036 0.000 0.112
#> SRR809873 4 0.0844 0.7068 0.004 0.012 0.004 0.980
#> SRR1341854 2 0.3942 0.6773 0.000 0.764 0.000 0.236
#> SRR1399335 2 0.4122 0.6713 0.000 0.760 0.004 0.236
#> SRR1464209 1 0.1022 0.8921 0.968 0.000 0.000 0.032
#> SRR1389886 2 0.0188 0.8634 0.000 0.996 0.000 0.004
#> SRR1400730 3 0.0188 0.9691 0.000 0.000 0.996 0.004
#> SRR1448008 4 0.4500 0.7727 0.000 0.316 0.000 0.684
#> SRR1087606 2 0.6586 0.0789 0.420 0.500 0.000 0.080
#> SRR1445111 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR816865 4 0.2401 0.7354 0.000 0.092 0.004 0.904
#> SRR1323360 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.9724 0.000 0.000 1.000 0.000
#> SRR1480329 2 0.4933 -0.0642 0.000 0.568 0.000 0.432
#> SRR1403322 4 0.3831 0.5449 0.204 0.000 0.004 0.792
#> SRR1093625 1 0.0000 0.8972 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.0336 0.8625 0.000 0.992 0.000 0.008
#> SRR1082035 2 0.7314 -0.0371 0.168 0.496 0.000 0.336
#> SRR1393046 2 0.0336 0.8636 0.000 0.992 0.000 0.008
#> SRR1466663 2 0.3157 0.7488 0.000 0.852 0.004 0.144
#> SRR1384456 1 0.0000 0.8972 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1270 0.905 0.000 0.948 0.000 0.052 0.000
#> SRR808862 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1500382 2 0.0510 0.906 0.000 0.984 0.000 0.016 0.000
#> SRR1322683 2 0.3019 0.867 0.000 0.864 0.000 0.088 0.048
#> SRR1329811 5 0.5478 0.515 0.044 0.288 0.000 0.028 0.640
#> SRR1087297 2 0.1341 0.904 0.000 0.944 0.000 0.056 0.000
#> SRR1072626 4 0.3237 0.816 0.000 0.104 0.000 0.848 0.048
#> SRR1407428 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.3909 0.761 0.000 0.800 0.148 0.004 0.048
#> SRR1500282 5 0.3452 0.618 0.244 0.000 0.000 0.000 0.756
#> SRR1100496 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1308778 2 0.0290 0.909 0.000 0.992 0.000 0.008 0.000
#> SRR1445304 2 0.0510 0.910 0.000 0.984 0.000 0.016 0.000
#> SRR1099378 5 0.4588 0.118 0.000 0.016 0.000 0.380 0.604
#> SRR1347412 1 0.0703 0.939 0.976 0.000 0.000 0.000 0.024
#> SRR1099694 2 0.2233 0.900 0.000 0.892 0.000 0.104 0.004
#> SRR1088365 4 0.0880 0.802 0.000 0.032 0.000 0.968 0.000
#> SRR1325752 4 0.5102 0.686 0.000 0.128 0.000 0.696 0.176
#> SRR1416713 2 0.0955 0.903 0.000 0.968 0.000 0.028 0.004
#> SRR1074474 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.2664 0.828 0.000 0.064 0.892 0.004 0.040
#> SRR1400507 2 0.2708 0.887 0.000 0.884 0.000 0.072 0.044
#> SRR1378179 2 0.2605 0.841 0.000 0.852 0.000 0.148 0.000
#> SRR1377905 2 0.0955 0.903 0.000 0.968 0.000 0.028 0.004
#> SRR1089479 1 0.3913 0.441 0.676 0.000 0.000 0.000 0.324
#> SRR1073365 2 0.2629 0.870 0.000 0.860 0.000 0.136 0.004
#> SRR1500306 5 0.1195 0.760 0.000 0.012 0.000 0.028 0.960
#> SRR1101566 4 0.6033 0.719 0.000 0.152 0.140 0.664 0.044
#> SRR1350503 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1446007 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.2732 0.849 0.000 0.840 0.000 0.160 0.000
#> SRR1380293 2 0.0794 0.903 0.000 0.972 0.000 0.028 0.000
#> SRR1331198 2 0.1041 0.904 0.000 0.964 0.000 0.032 0.004
#> SRR1092686 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 4 0.2079 0.795 0.000 0.064 0.000 0.916 0.020
#> SRR1341650 4 0.2522 0.778 0.000 0.012 0.000 0.880 0.108
#> SRR1357276 2 0.1270 0.905 0.000 0.948 0.000 0.052 0.000
#> SRR1498374 2 0.2645 0.894 0.000 0.888 0.000 0.068 0.044
#> SRR1093721 2 0.3456 0.849 0.000 0.800 0.000 0.184 0.016
#> SRR1464660 5 0.4478 0.679 0.044 0.152 0.000 0.028 0.776
#> SRR1402051 4 0.4933 0.766 0.000 0.076 0.000 0.688 0.236
#> SRR1488734 2 0.1831 0.908 0.000 0.920 0.000 0.076 0.004
#> SRR1082616 4 0.3707 0.613 0.000 0.000 0.284 0.716 0.000
#> SRR1099427 4 0.3888 0.815 0.000 0.148 0.000 0.796 0.056
#> SRR1453093 4 0.3164 0.816 0.000 0.104 0.000 0.852 0.044
#> SRR1357064 5 0.1502 0.769 0.056 0.004 0.000 0.000 0.940
#> SRR811237 4 0.3649 0.819 0.000 0.152 0.000 0.808 0.040
#> SRR1100848 4 0.3622 0.810 0.000 0.136 0.000 0.816 0.048
#> SRR1346755 4 0.3551 0.810 0.000 0.136 0.000 0.820 0.044
#> SRR1472529 2 0.2520 0.886 0.000 0.896 0.000 0.056 0.048
#> SRR1398905 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1082733 2 0.2583 0.867 0.000 0.864 0.000 0.132 0.004
#> SRR1308035 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.2209 0.907 0.000 0.912 0.000 0.056 0.032
#> SRR1455825 2 0.2450 0.901 0.000 0.900 0.000 0.052 0.048
#> SRR1389300 2 0.2450 0.898 0.000 0.900 0.000 0.052 0.048
#> SRR812246 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 4 0.2144 0.801 0.000 0.068 0.000 0.912 0.020
#> SRR1415567 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.2376 0.898 0.000 0.904 0.000 0.052 0.044
#> SRR1452099 4 0.1571 0.795 0.000 0.004 0.000 0.936 0.060
#> SRR1352346 5 0.5118 0.278 0.040 0.412 0.000 0.000 0.548
#> SRR1364034 2 0.3480 0.808 0.000 0.752 0.000 0.248 0.000
#> SRR1086046 4 0.4152 0.783 0.000 0.060 0.000 0.772 0.168
#> SRR1407226 5 0.3569 0.723 0.068 0.000 0.000 0.104 0.828
#> SRR1319363 4 0.3160 0.732 0.000 0.004 0.000 0.808 0.188
#> SRR1446961 3 0.4338 0.519 0.000 0.280 0.696 0.024 0.000
#> SRR1486650 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.3110 0.760 0.044 0.060 0.000 0.020 0.876
#> SRR1454785 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1092329 4 0.3551 0.810 0.000 0.136 0.000 0.820 0.044
#> SRR1091476 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 4 0.3413 0.810 0.000 0.124 0.000 0.832 0.044
#> SRR1366873 2 0.2446 0.897 0.000 0.900 0.000 0.056 0.044
#> SRR1398114 2 0.2074 0.870 0.000 0.896 0.000 0.104 0.000
#> SRR1089950 5 0.0798 0.765 0.000 0.016 0.000 0.008 0.976
#> SRR1433272 2 0.2648 0.838 0.000 0.848 0.000 0.152 0.000
#> SRR1075314 4 0.4822 0.774 0.000 0.076 0.000 0.704 0.220
#> SRR1085590 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1100752 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 2 0.3578 0.813 0.000 0.820 0.000 0.132 0.048
#> SRR1333263 4 0.4768 0.554 0.000 0.288 0.036 0.672 0.004
#> SRR1310231 2 0.1410 0.904 0.000 0.940 0.000 0.060 0.000
#> SRR1094144 4 0.1121 0.806 0.000 0.044 0.000 0.956 0.000
#> SRR1092160 2 0.0955 0.903 0.000 0.968 0.000 0.028 0.004
#> SRR1320300 2 0.3804 0.821 0.000 0.796 0.000 0.160 0.044
#> SRR1322747 2 0.0162 0.908 0.000 0.996 0.000 0.004 0.000
#> SRR1432719 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 4 0.1638 0.792 0.000 0.064 0.000 0.932 0.004
#> SRR1087511 4 0.4822 0.799 0.000 0.088 0.064 0.776 0.072
#> SRR1470336 5 0.1956 0.766 0.076 0.000 0.000 0.008 0.916
#> SRR1322536 4 0.4822 0.774 0.000 0.076 0.000 0.704 0.220
#> SRR1100824 5 0.2439 0.723 0.004 0.000 0.000 0.120 0.876
#> SRR1085951 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1322046 2 0.2719 0.868 0.000 0.852 0.000 0.144 0.004
#> SRR1316420 5 0.1282 0.770 0.044 0.004 0.000 0.000 0.952
#> SRR1070913 2 0.2446 0.886 0.000 0.900 0.000 0.056 0.044
#> SRR1345806 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.0955 0.903 0.000 0.968 0.000 0.028 0.004
#> SRR1337666 2 0.0794 0.903 0.000 0.972 0.000 0.028 0.000
#> SRR1076823 4 0.5409 0.645 0.004 0.064 0.000 0.600 0.332
#> SRR1093954 2 0.2966 0.840 0.000 0.816 0.000 0.184 0.000
#> SRR1451921 4 0.1671 0.793 0.000 0.000 0.000 0.924 0.076
#> SRR1491257 5 0.4741 0.564 0.044 0.240 0.000 0.008 0.708
#> SRR1416979 4 0.3622 0.810 0.000 0.136 0.000 0.816 0.048
#> SRR1419015 4 0.3246 0.734 0.000 0.008 0.000 0.808 0.184
#> SRR817649 2 0.1774 0.906 0.000 0.932 0.000 0.052 0.016
#> SRR1466376 2 0.1430 0.905 0.000 0.944 0.000 0.052 0.004
#> SRR1392055 2 0.1270 0.905 0.000 0.948 0.000 0.052 0.000
#> SRR1120913 2 0.0324 0.909 0.000 0.992 0.000 0.004 0.004
#> SRR1120869 2 0.3969 0.714 0.000 0.692 0.000 0.304 0.004
#> SRR1319419 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR818694 4 0.3307 0.816 0.000 0.104 0.000 0.844 0.052
#> SRR1465653 5 0.3981 0.719 0.044 0.108 0.000 0.028 0.820
#> SRR1475952 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 4 0.1965 0.809 0.000 0.096 0.000 0.904 0.000
#> SRR810129 2 0.0404 0.910 0.000 0.988 0.000 0.012 0.000
#> SRR1400141 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 5 0.2516 0.737 0.140 0.000 0.000 0.000 0.860
#> SRR1437576 2 0.0290 0.908 0.000 0.992 0.000 0.008 0.000
#> SRR814407 5 0.3586 0.595 0.264 0.000 0.000 0.000 0.736
#> SRR1332403 2 0.2424 0.866 0.000 0.868 0.000 0.132 0.000
#> SRR1099598 4 0.3164 0.816 0.000 0.104 0.000 0.852 0.044
#> SRR1327723 2 0.1341 0.904 0.000 0.944 0.000 0.056 0.000
#> SRR1392525 4 0.4030 0.465 0.000 0.000 0.352 0.648 0.000
#> SRR1320536 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.0955 0.903 0.000 0.968 0.000 0.028 0.004
#> SRR1351390 5 0.0290 0.767 0.000 0.000 0.000 0.008 0.992
#> SRR1309141 2 0.1857 0.895 0.000 0.928 0.008 0.060 0.004
#> SRR1452803 2 0.0703 0.911 0.000 0.976 0.000 0.024 0.000
#> SRR811631 2 0.1522 0.898 0.000 0.944 0.000 0.012 0.044
#> SRR1485563 4 0.3992 0.813 0.000 0.080 0.000 0.796 0.124
#> SRR1311531 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 4 0.3659 0.738 0.000 0.220 0.000 0.768 0.012
#> SRR1480831 4 0.3267 0.815 0.000 0.112 0.000 0.844 0.044
#> SRR1083892 5 0.1282 0.770 0.044 0.004 0.000 0.000 0.952
#> SRR809873 4 0.3280 0.732 0.004 0.004 0.000 0.808 0.184
#> SRR1341854 2 0.2536 0.865 0.000 0.868 0.000 0.128 0.004
#> SRR1399335 2 0.2471 0.865 0.000 0.864 0.000 0.136 0.000
#> SRR1464209 5 0.2813 0.702 0.168 0.000 0.000 0.000 0.832
#> SRR1389886 2 0.1270 0.905 0.000 0.948 0.000 0.052 0.000
#> SRR1400730 3 0.0404 0.966 0.000 0.000 0.988 0.000 0.012
#> SRR1448008 4 0.3532 0.813 0.000 0.128 0.000 0.824 0.048
#> SRR1087606 5 0.1818 0.776 0.044 0.024 0.000 0.000 0.932
#> SRR1445111 1 0.0290 0.953 0.992 0.000 0.000 0.000 0.008
#> SRR816865 4 0.2389 0.763 0.000 0.116 0.000 0.880 0.004
#> SRR1323360 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.0000 0.976 0.000 0.000 1.000 0.000 0.000
#> SRR1480329 2 0.6035 0.180 0.000 0.528 0.000 0.340 0.132
#> SRR1403322 4 0.3650 0.705 0.176 0.000 0.000 0.796 0.028
#> SRR1093625 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.2304 0.900 0.000 0.908 0.000 0.044 0.048
#> SRR1082035 5 0.3506 0.650 0.000 0.132 0.000 0.044 0.824
#> SRR1393046 2 0.0794 0.903 0.000 0.972 0.000 0.028 0.000
#> SRR1466663 2 0.3752 0.808 0.000 0.812 0.000 0.124 0.064
#> SRR1384456 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.3464 0.52760 0.000 0.688 0.000 0.000 0.000 0.312
#> SRR808862 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1500382 2 0.3854 0.55485 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1322683 2 0.4329 0.26192 0.000 0.728 0.000 0.088 0.004 0.180
#> SRR1329811 5 0.1010 0.77046 0.000 0.004 0.000 0.000 0.960 0.036
#> SRR1087297 2 0.4002 0.55414 0.000 0.588 0.000 0.008 0.000 0.404
#> SRR1072626 4 0.5127 0.47578 0.000 0.384 0.000 0.528 0.000 0.088
#> SRR1407428 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.3667 0.28455 0.000 0.788 0.080 0.000 0.000 0.132
#> SRR1500282 5 0.2744 0.70556 0.144 0.000 0.000 0.000 0.840 0.016
#> SRR1100496 3 0.1814 0.85784 0.000 0.000 0.900 0.000 0.000 0.100
#> SRR1308778 2 0.3989 0.55354 0.000 0.528 0.000 0.004 0.000 0.468
#> SRR1445304 2 0.3838 0.55990 0.000 0.552 0.000 0.000 0.000 0.448
#> SRR1099378 5 0.6263 0.54315 0.000 0.040 0.000 0.192 0.532 0.236
#> SRR1347412 1 0.1007 0.92848 0.956 0.000 0.000 0.000 0.044 0.000
#> SRR1099694 2 0.3619 0.52536 0.000 0.680 0.000 0.004 0.000 0.316
#> SRR1088365 4 0.2859 0.44722 0.000 0.156 0.000 0.828 0.000 0.016
#> SRR1325752 4 0.3436 0.44200 0.000 0.028 0.000 0.816 0.020 0.136
#> SRR1416713 2 0.3854 0.55423 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1074474 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.4108 0.53216 0.000 0.260 0.704 0.008 0.000 0.028
#> SRR1400507 2 0.2971 0.28144 0.000 0.844 0.000 0.052 0.000 0.104
#> SRR1378179 2 0.5789 0.32197 0.000 0.496 0.000 0.216 0.000 0.288
#> SRR1377905 2 0.3847 0.55564 0.000 0.544 0.000 0.000 0.000 0.456
#> SRR1089479 1 0.4565 0.49463 0.684 0.000 0.000 0.000 0.220 0.096
#> SRR1073365 2 0.4844 0.47201 0.000 0.608 0.000 0.080 0.000 0.312
#> SRR1500306 5 0.5222 0.75233 0.000 0.032 0.000 0.088 0.656 0.224
#> SRR1101566 4 0.6455 0.44307 0.000 0.344 0.036 0.440 0.000 0.180
#> SRR1350503 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1446007 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 2 0.5341 0.41218 0.000 0.556 0.000 0.132 0.000 0.312
#> SRR1380293 2 0.3857 0.55428 0.000 0.532 0.000 0.000 0.000 0.468
#> SRR1331198 2 0.3847 0.55683 0.000 0.544 0.000 0.000 0.000 0.456
#> SRR1092686 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.2979 0.44398 0.000 0.004 0.000 0.804 0.004 0.188
#> SRR1341650 4 0.5091 0.36796 0.000 0.136 0.000 0.640 0.004 0.220
#> SRR1357276 2 0.3765 0.55746 0.000 0.596 0.000 0.000 0.000 0.404
#> SRR1498374 2 0.1391 0.36295 0.000 0.944 0.000 0.016 0.000 0.040
#> SRR1093721 2 0.5186 0.18645 0.000 0.612 0.000 0.156 0.000 0.232
#> SRR1464660 5 0.0909 0.77784 0.000 0.012 0.000 0.000 0.968 0.020
#> SRR1402051 4 0.6422 0.45111 0.000 0.308 0.000 0.452 0.028 0.212
#> SRR1488734 2 0.3872 0.55367 0.000 0.604 0.000 0.004 0.000 0.392
#> SRR1082616 4 0.5767 0.16835 0.000 0.000 0.376 0.448 0.000 0.176
#> SRR1099427 4 0.5736 0.46222 0.000 0.320 0.000 0.492 0.000 0.188
#> SRR1453093 4 0.5361 0.47153 0.000 0.372 0.000 0.512 0.000 0.116
#> SRR1357064 5 0.1910 0.79646 0.000 0.000 0.000 0.000 0.892 0.108
#> SRR811237 4 0.5351 0.49017 0.000 0.288 0.000 0.568 0.000 0.144
#> SRR1100848 4 0.5609 0.46077 0.000 0.348 0.000 0.496 0.000 0.156
#> SRR1346755 4 0.5736 0.46222 0.000 0.320 0.000 0.492 0.000 0.188
#> SRR1472529 2 0.3139 0.35477 0.000 0.816 0.000 0.032 0.000 0.152
#> SRR1398905 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1082733 2 0.4170 0.49972 0.000 0.660 0.000 0.032 0.000 0.308
#> SRR1308035 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.2854 0.49466 0.000 0.792 0.000 0.000 0.000 0.208
#> SRR1455825 2 0.0547 0.36953 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1389300 2 0.0260 0.36881 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR812246 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.4573 0.37032 0.000 0.208 0.000 0.688 0.000 0.104
#> SRR1415567 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0260 0.36623 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1452099 4 0.3001 0.44324 0.000 0.008 0.000 0.840 0.024 0.128
#> SRR1352346 5 0.5937 0.45939 0.000 0.172 0.000 0.052 0.604 0.172
#> SRR1364034 4 0.5385 -0.17284 0.000 0.420 0.000 0.468 0.000 0.112
#> SRR1086046 4 0.6289 0.45534 0.000 0.180 0.000 0.584 0.124 0.112
#> SRR1407226 4 0.5767 -0.01189 0.012 0.000 0.000 0.472 0.124 0.392
#> SRR1319363 4 0.2907 0.43061 0.000 0.000 0.000 0.828 0.020 0.152
#> SRR1446961 3 0.4907 0.49197 0.000 0.156 0.688 0.012 0.000 0.144
#> SRR1486650 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0458 0.78120 0.000 0.000 0.000 0.000 0.984 0.016
#> SRR1454785 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 4 0.5665 0.46335 0.000 0.328 0.000 0.500 0.000 0.172
#> SRR1091476 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 2 0.5472 -0.51563 0.000 0.464 0.000 0.412 0.000 0.124
#> SRR1366873 2 0.1196 0.32907 0.000 0.952 0.000 0.008 0.000 0.040
#> SRR1398114 2 0.4598 0.50677 0.000 0.592 0.000 0.048 0.000 0.360
#> SRR1089950 5 0.5099 0.75866 0.000 0.032 0.000 0.068 0.656 0.244
#> SRR1433272 4 0.6067 -0.17886 0.000 0.332 0.000 0.396 0.000 0.272
#> SRR1075314 4 0.6924 0.42460 0.000 0.304 0.000 0.444 0.104 0.148
#> SRR1085590 3 0.0146 0.94473 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1100752 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 2 0.4247 0.25012 0.000 0.740 0.000 0.092 0.004 0.164
#> SRR1333263 4 0.5866 0.19525 0.000 0.196 0.024 0.576 0.000 0.204
#> SRR1310231 2 0.3619 0.52439 0.000 0.680 0.000 0.004 0.000 0.316
#> SRR1094144 4 0.1909 0.47940 0.000 0.024 0.000 0.920 0.004 0.052
#> SRR1092160 2 0.3854 0.55423 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1320300 2 0.3680 0.12684 0.000 0.784 0.000 0.144 0.000 0.072
#> SRR1322747 2 0.3854 0.55572 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1432719 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100728 4 0.4486 0.37863 0.000 0.184 0.000 0.704 0.000 0.112
#> SRR1087511 4 0.5874 0.46263 0.000 0.368 0.016 0.484 0.000 0.132
#> SRR1470336 5 0.5377 0.77269 0.052 0.004 0.000 0.064 0.656 0.224
#> SRR1322536 4 0.6604 0.43656 0.000 0.308 0.000 0.464 0.056 0.172
#> SRR1100824 4 0.5761 -0.07698 0.000 0.000 0.000 0.432 0.172 0.396
#> SRR1085951 3 0.1814 0.85784 0.000 0.000 0.900 0.000 0.000 0.100
#> SRR1322046 2 0.3975 0.55294 0.000 0.600 0.000 0.008 0.000 0.392
#> SRR1316420 5 0.3835 0.79194 0.000 0.000 0.000 0.048 0.748 0.204
#> SRR1070913 2 0.3481 0.33603 0.000 0.792 0.000 0.048 0.000 0.160
#> SRR1345806 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.3851 0.55445 0.000 0.540 0.000 0.000 0.000 0.460
#> SRR1337666 2 0.3854 0.55485 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1076823 4 0.6729 0.37952 0.000 0.272 0.000 0.376 0.036 0.316
#> SRR1093954 2 0.5796 0.24057 0.000 0.432 0.000 0.180 0.000 0.388
#> SRR1451921 4 0.2113 0.48987 0.000 0.004 0.000 0.896 0.008 0.092
#> SRR1491257 6 0.5299 -0.03022 0.000 0.076 0.000 0.012 0.372 0.540
#> SRR1416979 4 0.5650 0.46670 0.000 0.332 0.000 0.500 0.000 0.168
#> SRR1419015 4 0.3460 0.39188 0.000 0.000 0.000 0.760 0.020 0.220
#> SRR817649 2 0.5157 0.49589 0.000 0.484 0.000 0.004 0.072 0.440
#> SRR1466376 2 0.3446 0.52742 0.000 0.692 0.000 0.000 0.000 0.308
#> SRR1392055 2 0.3756 0.55857 0.000 0.600 0.000 0.000 0.000 0.400
#> SRR1120913 2 0.3851 0.55605 0.000 0.540 0.000 0.000 0.000 0.460
#> SRR1120869 4 0.5383 -0.00818 0.000 0.416 0.000 0.472 0.000 0.112
#> SRR1319419 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR816495 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR818694 2 0.5533 -0.52593 0.000 0.448 0.000 0.420 0.000 0.132
#> SRR1465653 5 0.0547 0.77949 0.000 0.000 0.000 0.000 0.980 0.020
#> SRR1475952 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 4 0.5597 0.09322 0.000 0.148 0.000 0.480 0.000 0.372
#> SRR810129 2 0.4086 0.55285 0.000 0.528 0.000 0.008 0.000 0.464
#> SRR1400141 3 0.0146 0.94473 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1349585 5 0.5971 0.70266 0.172 0.000 0.000 0.040 0.584 0.204
#> SRR1437576 2 0.4045 0.55788 0.000 0.564 0.000 0.008 0.000 0.428
#> SRR814407 5 0.5112 0.73339 0.096 0.000 0.000 0.036 0.684 0.184
#> SRR1332403 2 0.3725 0.52216 0.000 0.676 0.000 0.008 0.000 0.316
#> SRR1099598 4 0.5257 0.44459 0.000 0.432 0.000 0.472 0.000 0.096
#> SRR1327723 2 0.3725 0.52216 0.000 0.676 0.000 0.008 0.000 0.316
#> SRR1392525 4 0.5166 0.17217 0.000 0.000 0.348 0.552 0.000 0.100
#> SRR1320536 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.3854 0.55538 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1351390 5 0.4545 0.77568 0.000 0.008 0.000 0.064 0.688 0.240
#> SRR1309141 6 0.4644 -0.53515 0.000 0.456 0.000 0.040 0.000 0.504
#> SRR1452803 2 0.3971 0.55817 0.000 0.548 0.000 0.004 0.000 0.448
#> SRR811631 2 0.2980 0.34407 0.000 0.808 0.000 0.012 0.000 0.180
#> SRR1485563 4 0.5224 0.48333 0.000 0.304 0.000 0.592 0.008 0.096
#> SRR1311531 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.5971 0.12124 0.000 0.288 0.000 0.448 0.000 0.264
#> SRR1480831 4 0.5261 0.43739 0.000 0.444 0.000 0.460 0.000 0.096
#> SRR1083892 5 0.2362 0.80363 0.000 0.000 0.000 0.004 0.860 0.136
#> SRR809873 4 0.2907 0.43061 0.000 0.000 0.000 0.828 0.020 0.152
#> SRR1341854 2 0.4129 0.55538 0.000 0.564 0.000 0.012 0.000 0.424
#> SRR1399335 2 0.4537 0.33462 0.000 0.552 0.000 0.036 0.000 0.412
#> SRR1464209 5 0.2726 0.79221 0.032 0.000 0.000 0.000 0.856 0.112
#> SRR1389886 2 0.3464 0.52760 0.000 0.688 0.000 0.000 0.000 0.312
#> SRR1400730 3 0.3409 0.61463 0.000 0.000 0.700 0.000 0.300 0.000
#> SRR1448008 2 0.5335 -0.51342 0.000 0.492 0.000 0.400 0.000 0.108
#> SRR1087606 5 0.2978 0.79952 0.000 0.008 0.000 0.052 0.856 0.084
#> SRR1445111 1 0.0458 0.94683 0.984 0.000 0.000 0.000 0.016 0.000
#> SRR816865 4 0.4461 0.36185 0.000 0.192 0.000 0.704 0.000 0.104
#> SRR1323360 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.0000 0.94737 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1480329 2 0.6198 -0.41424 0.000 0.424 0.000 0.328 0.008 0.240
#> SRR1403322 4 0.3968 0.42335 0.124 0.000 0.000 0.772 0.004 0.100
#> SRR1093625 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.1075 0.38179 0.000 0.952 0.000 0.000 0.000 0.048
#> SRR1082035 6 0.7031 -0.26309 0.000 0.312 0.000 0.116 0.148 0.424
#> SRR1393046 2 0.3854 0.55485 0.000 0.536 0.000 0.000 0.000 0.464
#> SRR1466663 2 0.4766 0.14487 0.000 0.552 0.000 0.044 0.004 0.400
#> SRR1384456 1 0.0000 0.95883 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["SD", "mclust"]
# you can also extract it by
# res = res_list["SD:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.830 0.920 0.965 0.5006 0.498 0.498
#> 3 3 0.463 0.560 0.782 0.2132 0.807 0.633
#> 4 4 0.704 0.783 0.886 0.1683 0.868 0.666
#> 5 5 0.564 0.685 0.792 0.0326 0.968 0.893
#> 6 6 0.572 0.536 0.677 0.0233 0.942 0.796
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
#> SRR810713 2 0.0000 0.964 0.000 1.000
#> SRR808862 1 0.0000 0.960 1.000 0.000
#> SRR1500382 2 0.0000 0.964 0.000 1.000
#> SRR1322683 2 0.7376 0.756 0.208 0.792
#> SRR1329811 1 0.0000 0.960 1.000 0.000
#> SRR1087297 2 0.0000 0.964 0.000 1.000
#> SRR1072626 2 0.0000 0.964 0.000 1.000
#> SRR1407428 1 0.0000 0.960 1.000 0.000
#> SRR1321029 2 0.0000 0.964 0.000 1.000
#> SRR1500282 1 0.0000 0.960 1.000 0.000
#> SRR1100496 1 0.0000 0.960 1.000 0.000
#> SRR1308778 2 0.0000 0.964 0.000 1.000
#> SRR1445304 2 0.0000 0.964 0.000 1.000
#> SRR1099378 1 0.6247 0.806 0.844 0.156
#> SRR1347412 1 0.0000 0.960 1.000 0.000
#> SRR1099694 2 0.0000 0.964 0.000 1.000
#> SRR1088365 2 0.0000 0.964 0.000 1.000
#> SRR1325752 1 0.6048 0.816 0.852 0.148
#> SRR1416713 2 0.0000 0.964 0.000 1.000
#> SRR1074474 1 0.0000 0.960 1.000 0.000
#> SRR1469369 1 0.0000 0.960 1.000 0.000
#> SRR1400507 2 0.0000 0.964 0.000 1.000
#> SRR1378179 2 0.0000 0.964 0.000 1.000
#> SRR1377905 2 0.7219 0.767 0.200 0.800
#> SRR1089479 1 0.0000 0.960 1.000 0.000
#> SRR1073365 2 0.0000 0.964 0.000 1.000
#> SRR1500306 1 0.0000 0.960 1.000 0.000
#> SRR1101566 2 0.7376 0.756 0.208 0.792
#> SRR1350503 1 0.0000 0.960 1.000 0.000
#> SRR1446007 1 0.0000 0.960 1.000 0.000
#> SRR1102875 2 0.0000 0.964 0.000 1.000
#> SRR1380293 2 0.0000 0.964 0.000 1.000
#> SRR1331198 2 0.0000 0.964 0.000 1.000
#> SRR1092686 1 0.0000 0.960 1.000 0.000
#> SRR1069421 2 0.2043 0.940 0.032 0.968
#> SRR1341650 1 0.9129 0.501 0.672 0.328
#> SRR1357276 2 0.0000 0.964 0.000 1.000
#> SRR1498374 2 0.0000 0.964 0.000 1.000
#> SRR1093721 2 0.0000 0.964 0.000 1.000
#> SRR1464660 1 0.0000 0.960 1.000 0.000
#> SRR1402051 2 0.2778 0.926 0.048 0.952
#> SRR1488734 2 0.0000 0.964 0.000 1.000
#> SRR1082616 1 0.0000 0.960 1.000 0.000
#> SRR1099427 2 0.7815 0.721 0.232 0.768
#> SRR1453093 2 0.2043 0.940 0.032 0.968
#> SRR1357064 1 0.0000 0.960 1.000 0.000
#> SRR811237 2 0.0000 0.964 0.000 1.000
#> SRR1100848 2 0.0000 0.964 0.000 1.000
#> SRR1346755 2 0.7376 0.756 0.208 0.792
#> SRR1472529 2 0.0000 0.964 0.000 1.000
#> SRR1398905 1 0.0000 0.960 1.000 0.000
#> SRR1082733 2 0.0000 0.964 0.000 1.000
#> SRR1308035 1 0.0000 0.960 1.000 0.000
#> SRR1466445 1 0.0000 0.960 1.000 0.000
#> SRR1359080 2 0.0000 0.964 0.000 1.000
#> SRR1455825 2 0.0000 0.964 0.000 1.000
#> SRR1389300 2 0.0000 0.964 0.000 1.000
#> SRR812246 1 0.0000 0.960 1.000 0.000
#> SRR1076632 2 0.0000 0.964 0.000 1.000
#> SRR1415567 1 0.0000 0.960 1.000 0.000
#> SRR1331900 2 0.0000 0.964 0.000 1.000
#> SRR1452099 1 0.7299 0.731 0.796 0.204
#> SRR1352346 1 0.0000 0.960 1.000 0.000
#> SRR1364034 2 0.0000 0.964 0.000 1.000
#> SRR1086046 1 0.6343 0.801 0.840 0.160
#> SRR1407226 1 0.0000 0.960 1.000 0.000
#> SRR1319363 1 0.0000 0.960 1.000 0.000
#> SRR1446961 1 0.0000 0.960 1.000 0.000
#> SRR1486650 1 0.0000 0.960 1.000 0.000
#> SRR1470152 1 0.0000 0.960 1.000 0.000
#> SRR1454785 1 0.0000 0.960 1.000 0.000
#> SRR1092329 2 0.7219 0.767 0.200 0.800
#> SRR1091476 1 0.0000 0.960 1.000 0.000
#> SRR1073775 2 0.0000 0.964 0.000 1.000
#> SRR1366873 2 0.0000 0.964 0.000 1.000
#> SRR1398114 2 0.0000 0.964 0.000 1.000
#> SRR1089950 1 0.5946 0.821 0.856 0.144
#> SRR1433272 2 0.0000 0.964 0.000 1.000
#> SRR1075314 1 0.0000 0.960 1.000 0.000
#> SRR1085590 1 0.0376 0.957 0.996 0.004
#> SRR1100752 1 0.0000 0.960 1.000 0.000
#> SRR1391494 2 0.7219 0.767 0.200 0.800
#> SRR1333263 1 0.9710 0.317 0.600 0.400
#> SRR1310231 2 0.0000 0.964 0.000 1.000
#> SRR1094144 2 0.0000 0.964 0.000 1.000
#> SRR1092160 2 0.0000 0.964 0.000 1.000
#> SRR1320300 2 0.0000 0.964 0.000 1.000
#> SRR1322747 2 0.9710 0.366 0.400 0.600
#> SRR1432719 1 0.0000 0.960 1.000 0.000
#> SRR1100728 2 0.0000 0.964 0.000 1.000
#> SRR1087511 2 0.2423 0.933 0.040 0.960
#> SRR1470336 1 0.0000 0.960 1.000 0.000
#> SRR1322536 1 0.0000 0.960 1.000 0.000
#> SRR1100824 1 0.0000 0.960 1.000 0.000
#> SRR1085951 1 0.0000 0.960 1.000 0.000
#> SRR1322046 2 0.0000 0.964 0.000 1.000
#> SRR1316420 1 0.0000 0.960 1.000 0.000
#> SRR1070913 2 0.0000 0.964 0.000 1.000
#> SRR1345806 1 0.0000 0.960 1.000 0.000
#> SRR1313872 2 0.0000 0.964 0.000 1.000
#> SRR1337666 2 0.0000 0.964 0.000 1.000
#> SRR1076823 1 0.0000 0.960 1.000 0.000
#> SRR1093954 2 0.0000 0.964 0.000 1.000
#> SRR1451921 1 0.0000 0.960 1.000 0.000
#> SRR1491257 1 0.0000 0.960 1.000 0.000
#> SRR1416979 2 0.0000 0.964 0.000 1.000
#> SRR1419015 1 0.0000 0.960 1.000 0.000
#> SRR817649 2 0.0000 0.964 0.000 1.000
#> SRR1466376 2 0.0000 0.964 0.000 1.000
#> SRR1392055 2 0.0000 0.964 0.000 1.000
#> SRR1120913 2 0.0000 0.964 0.000 1.000
#> SRR1120869 2 0.0000 0.964 0.000 1.000
#> SRR1319419 1 0.0000 0.960 1.000 0.000
#> SRR816495 1 0.0000 0.960 1.000 0.000
#> SRR818694 2 0.0000 0.964 0.000 1.000
#> SRR1465653 1 0.0376 0.957 0.996 0.004
#> SRR1475952 1 0.0000 0.960 1.000 0.000
#> SRR1465040 1 0.0000 0.960 1.000 0.000
#> SRR1088461 2 0.0000 0.964 0.000 1.000
#> SRR810129 2 0.0000 0.964 0.000 1.000
#> SRR1400141 1 0.0000 0.960 1.000 0.000
#> SRR1349585 1 0.0000 0.960 1.000 0.000
#> SRR1437576 2 0.7219 0.767 0.200 0.800
#> SRR814407 1 0.0000 0.960 1.000 0.000
#> SRR1332403 2 0.0000 0.964 0.000 1.000
#> SRR1099598 2 0.0000 0.964 0.000 1.000
#> SRR1327723 2 0.0000 0.964 0.000 1.000
#> SRR1392525 1 0.7602 0.706 0.780 0.220
#> SRR1320536 1 0.0000 0.960 1.000 0.000
#> SRR1083824 1 0.9710 0.317 0.600 0.400
#> SRR1351390 1 0.0000 0.960 1.000 0.000
#> SRR1309141 1 0.9754 0.293 0.592 0.408
#> SRR1452803 2 0.0000 0.964 0.000 1.000
#> SRR811631 2 0.9358 0.490 0.352 0.648
#> SRR1485563 2 0.0000 0.964 0.000 1.000
#> SRR1311531 1 0.0000 0.960 1.000 0.000
#> SRR1353076 2 0.0000 0.964 0.000 1.000
#> SRR1480831 2 0.0000 0.964 0.000 1.000
#> SRR1083892 1 0.0000 0.960 1.000 0.000
#> SRR809873 1 0.0000 0.960 1.000 0.000
#> SRR1341854 2 0.0000 0.964 0.000 1.000
#> SRR1399335 2 0.0000 0.964 0.000 1.000
#> SRR1464209 1 0.0000 0.960 1.000 0.000
#> SRR1389886 2 0.0000 0.964 0.000 1.000
#> SRR1400730 1 0.0000 0.960 1.000 0.000
#> SRR1448008 2 0.0000 0.964 0.000 1.000
#> SRR1087606 1 0.5737 0.830 0.864 0.136
#> SRR1445111 1 0.0000 0.960 1.000 0.000
#> SRR816865 2 0.0000 0.964 0.000 1.000
#> SRR1323360 1 0.0000 0.960 1.000 0.000
#> SRR1417364 1 0.0000 0.960 1.000 0.000
#> SRR1480329 2 0.0000 0.964 0.000 1.000
#> SRR1403322 1 0.0000 0.960 1.000 0.000
#> SRR1093625 1 0.0000 0.960 1.000 0.000
#> SRR1479977 2 0.0000 0.964 0.000 1.000
#> SRR1082035 1 0.2423 0.927 0.960 0.040
#> SRR1393046 2 0.7219 0.767 0.200 0.800
#> SRR1466663 2 0.1414 0.949 0.020 0.980
#> SRR1384456 1 0.0000 0.960 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR808862 1 0.5835 0.28433 0.660 0.000 0.340
#> SRR1500382 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1322683 3 0.9083 0.06287 0.180 0.280 0.540
#> SRR1329811 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1087297 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1072626 2 0.6267 0.44666 0.000 0.548 0.452
#> SRR1407428 1 0.0829 0.69117 0.984 0.004 0.012
#> SRR1321029 2 0.1753 0.85232 0.000 0.952 0.048
#> SRR1500282 1 0.3686 0.55091 0.860 0.000 0.140
#> SRR1100496 1 0.6045 0.18601 0.620 0.000 0.380
#> SRR1308778 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1445304 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1099378 1 0.5521 0.60893 0.788 0.180 0.032
#> SRR1347412 1 0.4399 0.48348 0.812 0.000 0.188
#> SRR1099694 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1088365 2 0.3267 0.81517 0.000 0.884 0.116
#> SRR1325752 1 0.6056 0.53385 0.744 0.224 0.032
#> SRR1416713 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1074474 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1469369 1 0.6724 0.03309 0.568 0.012 0.420
#> SRR1400507 2 0.4346 0.75728 0.000 0.816 0.184
#> SRR1378179 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1377905 2 0.5659 0.69541 0.152 0.796 0.052
#> SRR1089479 1 0.0475 0.69423 0.992 0.004 0.004
#> SRR1073365 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1500306 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1101566 3 0.9161 0.06297 0.188 0.280 0.532
#> SRR1350503 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1446007 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1102875 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1380293 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1331198 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1092686 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1069421 2 0.4995 0.73289 0.144 0.824 0.032
#> SRR1341650 1 0.9648 0.03170 0.464 0.244 0.292
#> SRR1357276 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1498374 2 0.1411 0.86217 0.000 0.964 0.036
#> SRR1093721 2 0.1031 0.86733 0.000 0.976 0.024
#> SRR1464660 1 0.0000 0.69158 1.000 0.000 0.000
#> SRR1402051 3 0.9284 0.04036 0.192 0.296 0.512
#> SRR1488734 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1082616 1 0.6189 0.22357 0.632 0.004 0.364
#> SRR1099427 3 0.7421 0.15183 0.084 0.240 0.676
#> SRR1453093 1 0.8795 0.27498 0.576 0.256 0.168
#> SRR1357064 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR811237 2 0.6267 0.44666 0.000 0.548 0.452
#> SRR1100848 2 0.6204 0.48548 0.000 0.576 0.424
#> SRR1346755 3 0.9161 0.06297 0.188 0.280 0.532
#> SRR1472529 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1398905 1 0.5560 0.34472 0.700 0.000 0.300
#> SRR1082733 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1308035 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1466445 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1359080 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1455825 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1389300 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR812246 3 0.6309 0.17916 0.496 0.000 0.504
#> SRR1076632 2 0.3619 0.79943 0.000 0.864 0.136
#> SRR1415567 1 0.0829 0.69117 0.984 0.004 0.012
#> SRR1331900 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1452099 1 0.9787 -0.00739 0.424 0.248 0.328
#> SRR1352346 1 0.5723 0.52569 0.744 0.240 0.016
#> SRR1364034 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1086046 1 0.6245 0.59085 0.760 0.180 0.060
#> SRR1407226 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1319363 1 0.4865 0.65722 0.832 0.136 0.032
#> SRR1446961 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1486650 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1470152 1 0.0000 0.69158 1.000 0.000 0.000
#> SRR1454785 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1092329 3 0.9046 -0.00987 0.160 0.312 0.528
#> SRR1091476 1 0.6154 0.10493 0.592 0.000 0.408
#> SRR1073775 2 0.7075 0.35789 0.020 0.496 0.484
#> SRR1366873 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1398114 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1089950 1 0.5008 0.61521 0.804 0.180 0.016
#> SRR1433272 2 0.1753 0.84527 0.048 0.952 0.000
#> SRR1075314 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1085590 3 0.7903 0.18140 0.356 0.068 0.576
#> SRR1100752 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1391494 2 0.6679 0.66396 0.152 0.748 0.100
#> SRR1333263 1 0.9843 -0.10931 0.376 0.248 0.376
#> SRR1310231 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1094144 2 0.7248 0.41454 0.028 0.536 0.436
#> SRR1092160 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1320300 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1322747 2 0.7580 0.29225 0.056 0.604 0.340
#> SRR1432719 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1100728 2 0.5285 0.69450 0.004 0.752 0.244
#> SRR1087511 3 0.9440 0.04110 0.204 0.308 0.488
#> SRR1470336 1 0.4551 0.66032 0.844 0.132 0.024
#> SRR1322536 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1100824 1 0.3686 0.55091 0.860 0.000 0.140
#> SRR1085951 1 0.5948 0.23771 0.640 0.000 0.360
#> SRR1322046 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1316420 1 0.2356 0.68711 0.928 0.072 0.000
#> SRR1070913 2 0.0892 0.86836 0.000 0.980 0.020
#> SRR1345806 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1313872 2 0.0661 0.86971 0.004 0.988 0.008
#> SRR1337666 2 0.4099 0.72543 0.140 0.852 0.008
#> SRR1076823 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1093954 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1451921 1 0.5267 0.65195 0.816 0.140 0.044
#> SRR1491257 1 0.0000 0.69158 1.000 0.000 0.000
#> SRR1416979 2 0.6267 0.44666 0.000 0.548 0.452
#> SRR1419015 1 0.7535 0.52725 0.692 0.132 0.176
#> SRR817649 2 0.3755 0.75370 0.120 0.872 0.008
#> SRR1466376 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1120869 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1319419 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR816495 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR818694 3 0.9243 -0.09524 0.160 0.368 0.472
#> SRR1465653 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1475952 1 0.4551 0.66032 0.844 0.132 0.024
#> SRR1465040 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1088461 2 0.0592 0.87048 0.000 0.988 0.012
#> SRR810129 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1400141 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1349585 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1437576 2 0.6530 0.67242 0.120 0.760 0.120
#> SRR814407 1 0.4346 0.48566 0.816 0.000 0.184
#> SRR1332403 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1099598 2 0.6274 0.44070 0.000 0.544 0.456
#> SRR1327723 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1392525 3 0.8109 0.21284 0.256 0.116 0.628
#> SRR1320536 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1083824 3 0.9827 0.17198 0.244 0.372 0.384
#> SRR1351390 1 0.4744 0.65875 0.836 0.136 0.028
#> SRR1309141 2 0.9955 -0.34226 0.304 0.380 0.316
#> SRR1452803 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR811631 3 0.7328 0.12110 0.044 0.344 0.612
#> SRR1485563 3 0.8579 -0.28272 0.096 0.440 0.464
#> SRR1311531 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1353076 2 0.6168 0.50247 0.000 0.588 0.412
#> SRR1480831 2 0.6267 0.44666 0.000 0.548 0.452
#> SRR1083892 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR809873 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1341854 2 0.0237 0.87173 0.000 0.996 0.004
#> SRR1399335 2 0.0424 0.87055 0.000 0.992 0.008
#> SRR1464209 1 0.0237 0.69496 0.996 0.004 0.000
#> SRR1389886 2 0.0000 0.87274 0.000 1.000 0.000
#> SRR1400730 1 0.5560 0.34472 0.700 0.000 0.300
#> SRR1448008 3 0.8387 -0.25444 0.084 0.428 0.488
#> SRR1087606 1 0.4235 0.62704 0.824 0.176 0.000
#> SRR1445111 1 0.0475 0.69423 0.992 0.004 0.004
#> SRR816865 2 0.3482 0.80205 0.000 0.872 0.128
#> SRR1323360 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1417364 3 0.6305 0.21346 0.484 0.000 0.516
#> SRR1480329 2 0.5098 0.69499 0.000 0.752 0.248
#> SRR1403322 1 0.5202 0.65549 0.820 0.136 0.044
#> SRR1093625 1 0.0661 0.69287 0.988 0.004 0.008
#> SRR1479977 2 0.0747 0.86945 0.000 0.984 0.016
#> SRR1082035 1 0.4861 0.61673 0.808 0.180 0.012
#> SRR1393046 2 0.5998 0.68847 0.128 0.788 0.084
#> SRR1466663 2 0.4228 0.73825 0.148 0.844 0.008
#> SRR1384456 1 0.0237 0.69496 0.996 0.004 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR808862 1 0.6016 0.5181 0.632 0.000 0.300 0.068
#> SRR1500382 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1322683 4 0.2944 0.7508 0.044 0.004 0.052 0.900
#> SRR1329811 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1087297 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1072626 4 0.3266 0.7573 0.000 0.168 0.000 0.832
#> SRR1407428 1 0.0524 0.9053 0.988 0.004 0.000 0.008
#> SRR1321029 2 0.4253 0.7550 0.000 0.776 0.016 0.208
#> SRR1500282 1 0.3542 0.8243 0.864 0.000 0.076 0.060
#> SRR1100496 3 0.6750 0.4263 0.288 0.000 0.584 0.128
#> SRR1308778 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1445304 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1099378 1 0.1913 0.8801 0.940 0.020 0.000 0.040
#> SRR1347412 1 0.5327 0.6509 0.720 0.000 0.220 0.060
#> SRR1099694 2 0.1022 0.8627 0.000 0.968 0.000 0.032
#> SRR1088365 2 0.3074 0.7734 0.000 0.848 0.000 0.152
#> SRR1325752 1 0.3128 0.8268 0.884 0.076 0.000 0.040
#> SRR1416713 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1074474 1 0.0188 0.9053 0.996 0.004 0.000 0.000
#> SRR1469369 3 0.6688 0.2877 0.096 0.000 0.536 0.368
#> SRR1400507 2 0.4304 0.6358 0.000 0.716 0.000 0.284
#> SRR1378179 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1377905 2 0.5922 0.7190 0.052 0.748 0.068 0.132
#> SRR1089479 1 0.0921 0.8946 0.972 0.000 0.000 0.028
#> SRR1073365 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1500306 1 0.1042 0.9034 0.972 0.008 0.000 0.020
#> SRR1101566 4 0.2650 0.7605 0.040 0.008 0.036 0.916
#> SRR1350503 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1446007 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1380293 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1331198 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1092686 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.3907 0.7576 0.120 0.836 0.000 0.044
#> SRR1341650 4 0.6554 0.1621 0.468 0.048 0.012 0.472
#> SRR1357276 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1498374 2 0.3356 0.7729 0.000 0.824 0.000 0.176
#> SRR1093721 2 0.3764 0.7504 0.000 0.784 0.000 0.216
#> SRR1464660 1 0.1022 0.8929 0.968 0.000 0.000 0.032
#> SRR1402051 4 0.3757 0.7399 0.152 0.020 0.000 0.828
#> SRR1488734 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1082616 1 0.7859 0.0464 0.376 0.000 0.272 0.352
#> SRR1099427 4 0.3583 0.7191 0.040 0.004 0.092 0.864
#> SRR1453093 4 0.2342 0.7654 0.080 0.008 0.000 0.912
#> SRR1357064 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR811237 4 0.3486 0.7495 0.000 0.188 0.000 0.812
#> SRR1100848 4 0.4933 0.2330 0.000 0.432 0.000 0.568
#> SRR1346755 4 0.2685 0.7567 0.044 0.004 0.040 0.912
#> SRR1472529 2 0.3311 0.7762 0.000 0.828 0.000 0.172
#> SRR1398905 1 0.6016 0.5181 0.632 0.000 0.300 0.068
#> SRR1082733 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1308035 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1359080 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1455825 2 0.3266 0.7793 0.000 0.832 0.000 0.168
#> SRR1389300 2 0.2530 0.8203 0.000 0.888 0.000 0.112
#> SRR812246 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.2216 0.8278 0.000 0.908 0.000 0.092
#> SRR1415567 1 0.0524 0.9053 0.988 0.004 0.000 0.008
#> SRR1331900 2 0.3123 0.7890 0.000 0.844 0.000 0.156
#> SRR1452099 4 0.5040 0.4655 0.364 0.008 0.000 0.628
#> SRR1352346 1 0.4004 0.8000 0.844 0.088 0.004 0.064
#> SRR1364034 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1086046 4 0.5130 0.5207 0.332 0.016 0.000 0.652
#> SRR1407226 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1319363 1 0.0804 0.9045 0.980 0.008 0.000 0.012
#> SRR1446961 3 0.0336 0.9051 0.008 0.000 0.992 0.000
#> SRR1486650 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1470152 1 0.1022 0.8929 0.968 0.000 0.000 0.032
#> SRR1454785 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1092329 4 0.5188 0.7173 0.036 0.136 0.044 0.784
#> SRR1091476 3 0.5155 0.0053 0.468 0.000 0.528 0.004
#> SRR1073775 4 0.2198 0.7792 0.008 0.072 0.000 0.920
#> SRR1366873 2 0.3610 0.7511 0.000 0.800 0.000 0.200
#> SRR1398114 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1089950 1 0.1888 0.8818 0.940 0.016 0.000 0.044
#> SRR1433272 2 0.3399 0.8011 0.092 0.868 0.000 0.040
#> SRR1075314 1 0.1151 0.9024 0.968 0.008 0.000 0.024
#> SRR1085590 3 0.4019 0.6811 0.012 0.000 0.792 0.196
#> SRR1100752 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.6577 0.5708 0.036 0.624 0.044 0.296
#> SRR1333263 2 0.7972 0.4510 0.108 0.576 0.232 0.084
#> SRR1310231 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1094144 4 0.4889 0.5476 0.004 0.360 0.000 0.636
#> SRR1092160 2 0.1118 0.8614 0.000 0.964 0.000 0.036
#> SRR1320300 2 0.3528 0.7591 0.000 0.808 0.000 0.192
#> SRR1322747 2 0.6182 0.5074 0.076 0.616 0.308 0.000
#> SRR1432719 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1100728 2 0.4713 0.3140 0.000 0.640 0.000 0.360
#> SRR1087511 4 0.2271 0.7655 0.076 0.008 0.000 0.916
#> SRR1470336 1 0.1042 0.9034 0.972 0.008 0.000 0.020
#> SRR1322536 1 0.1151 0.9024 0.968 0.008 0.000 0.024
#> SRR1100824 1 0.3088 0.8436 0.888 0.000 0.052 0.060
#> SRR1085951 1 0.6058 0.5032 0.624 0.000 0.308 0.068
#> SRR1322046 2 0.1398 0.8590 0.000 0.956 0.004 0.040
#> SRR1316420 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1070913 2 0.3486 0.7629 0.000 0.812 0.000 0.188
#> SRR1345806 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1313872 2 0.1211 0.8595 0.000 0.960 0.000 0.040
#> SRR1337666 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1076823 1 0.1109 0.9009 0.968 0.004 0.000 0.028
#> SRR1093954 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1451921 1 0.1256 0.9012 0.964 0.008 0.000 0.028
#> SRR1491257 1 0.1022 0.8929 0.968 0.000 0.000 0.032
#> SRR1416979 4 0.3569 0.7398 0.000 0.196 0.000 0.804
#> SRR1419015 1 0.5710 0.6754 0.708 0.000 0.100 0.192
#> SRR817649 2 0.0921 0.8645 0.000 0.972 0.000 0.028
#> SRR1466376 2 0.0707 0.8691 0.000 0.980 0.000 0.020
#> SRR1392055 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1120913 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1120869 2 0.1118 0.8612 0.000 0.964 0.000 0.036
#> SRR1319419 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR816495 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR818694 4 0.2376 0.7707 0.068 0.016 0.000 0.916
#> SRR1465653 1 0.0657 0.9048 0.984 0.004 0.000 0.012
#> SRR1475952 1 0.0927 0.9042 0.976 0.008 0.000 0.016
#> SRR1465040 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1088461 2 0.0336 0.8717 0.000 0.992 0.000 0.008
#> SRR810129 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1400141 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1437576 2 0.7144 0.5741 0.024 0.620 0.136 0.220
#> SRR814407 1 0.5257 0.6616 0.728 0.000 0.212 0.060
#> SRR1332403 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1099598 4 0.2589 0.7719 0.000 0.116 0.000 0.884
#> SRR1327723 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1392525 4 0.6323 0.3761 0.100 0.000 0.272 0.628
#> SRR1320536 1 0.0188 0.9053 0.996 0.004 0.000 0.000
#> SRR1083824 2 0.6182 0.5074 0.076 0.616 0.308 0.000
#> SRR1351390 1 0.0927 0.9034 0.976 0.008 0.000 0.016
#> SRR1309141 2 0.7501 0.4868 0.104 0.600 0.244 0.052
#> SRR1452803 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR811631 2 0.6957 0.5132 0.016 0.600 0.280 0.104
#> SRR1485563 4 0.4127 0.7773 0.052 0.124 0.000 0.824
#> SRR1311531 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1353076 4 0.4564 0.5456 0.000 0.328 0.000 0.672
#> SRR1480831 4 0.3569 0.7450 0.000 0.196 0.000 0.804
#> SRR1083892 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR809873 1 0.1042 0.9028 0.972 0.008 0.000 0.020
#> SRR1341854 2 0.0707 0.8674 0.000 0.980 0.000 0.020
#> SRR1399335 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1464209 1 0.0376 0.9056 0.992 0.004 0.000 0.004
#> SRR1389886 2 0.0000 0.8733 0.000 1.000 0.000 0.000
#> SRR1400730 1 0.6016 0.5181 0.632 0.000 0.300 0.068
#> SRR1448008 4 0.2450 0.7818 0.016 0.072 0.000 0.912
#> SRR1087606 1 0.1798 0.8828 0.944 0.016 0.000 0.040
#> SRR1445111 1 0.0188 0.9053 0.996 0.004 0.000 0.000
#> SRR816865 2 0.3311 0.7359 0.000 0.828 0.000 0.172
#> SRR1323360 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.9139 0.000 0.000 1.000 0.000
#> SRR1480329 2 0.4356 0.6379 0.000 0.708 0.000 0.292
#> SRR1403322 1 0.0672 0.9050 0.984 0.008 0.000 0.008
#> SRR1093625 1 0.0188 0.9053 0.996 0.004 0.000 0.000
#> SRR1479977 2 0.1867 0.8445 0.000 0.928 0.000 0.072
#> SRR1082035 1 0.1913 0.8805 0.940 0.020 0.000 0.040
#> SRR1393046 2 0.6842 0.6253 0.028 0.656 0.116 0.200
#> SRR1466663 2 0.3764 0.7652 0.116 0.844 0.000 0.040
#> SRR1384456 1 0.0188 0.9053 0.996 0.004 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1671 0.8134 0.000 0.924 0.000 0.000 0.076
#> SRR808862 1 0.6073 0.4093 0.624 0.000 0.188 0.172 0.016
#> SRR1500382 2 0.1952 0.8059 0.000 0.912 0.000 0.004 0.084
#> SRR1322683 4 0.4700 0.7747 0.064 0.096 0.048 0.788 0.004
#> SRR1329811 5 0.4491 0.9463 0.364 0.004 0.000 0.008 0.624
#> SRR1087297 2 0.2193 0.8048 0.000 0.900 0.000 0.008 0.092
#> SRR1072626 4 0.4227 0.7404 0.000 0.292 0.000 0.692 0.016
#> SRR1407428 1 0.0162 0.6218 0.996 0.000 0.000 0.000 0.004
#> SRR1321029 2 0.3880 0.7827 0.004 0.824 0.008 0.104 0.060
#> SRR1500282 1 0.5000 0.4585 0.752 0.000 0.052 0.056 0.140
#> SRR1100496 3 0.5656 0.6191 0.136 0.000 0.672 0.176 0.016
#> SRR1308778 2 0.2470 0.8015 0.000 0.884 0.000 0.012 0.104
#> SRR1445304 2 0.1121 0.8221 0.000 0.956 0.000 0.000 0.044
#> SRR1099378 1 0.5057 0.4619 0.748 0.128 0.000 0.088 0.036
#> SRR1347412 1 0.5692 0.4511 0.704 0.000 0.108 0.056 0.132
#> SRR1099694 2 0.3130 0.7894 0.000 0.856 0.000 0.048 0.096
#> SRR1088365 2 0.3318 0.7089 0.000 0.808 0.000 0.180 0.012
#> SRR1325752 1 0.5304 0.4079 0.712 0.172 0.000 0.092 0.024
#> SRR1416713 2 0.1357 0.8148 0.000 0.948 0.000 0.004 0.048
#> SRR1074474 1 0.0451 0.6202 0.988 0.000 0.000 0.004 0.008
#> SRR1469369 3 0.4801 0.3850 0.008 0.000 0.584 0.396 0.012
#> SRR1400507 2 0.4277 0.6976 0.000 0.768 0.000 0.156 0.076
#> SRR1378179 2 0.1894 0.8143 0.000 0.920 0.000 0.008 0.072
#> SRR1377905 2 0.5110 0.7260 0.040 0.776 0.028 0.088 0.068
#> SRR1089479 1 0.2722 0.5468 0.872 0.000 0.000 0.020 0.108
#> SRR1073365 2 0.1831 0.8129 0.000 0.920 0.000 0.004 0.076
#> SRR1500306 1 0.2793 0.6154 0.876 0.000 0.000 0.036 0.088
#> SRR1101566 4 0.4216 0.7986 0.072 0.116 0.004 0.800 0.008
#> SRR1350503 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1446007 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.1831 0.8129 0.000 0.920 0.000 0.004 0.076
#> SRR1380293 2 0.2193 0.8041 0.000 0.900 0.000 0.008 0.092
#> SRR1331198 2 0.1956 0.8079 0.000 0.916 0.000 0.008 0.076
#> SRR1092686 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 2 0.5589 0.6724 0.076 0.712 0.000 0.144 0.068
#> SRR1341650 4 0.7541 0.6631 0.176 0.204 0.056 0.540 0.024
#> SRR1357276 2 0.1952 0.8059 0.000 0.912 0.000 0.004 0.084
#> SRR1498374 2 0.2144 0.8056 0.000 0.912 0.000 0.068 0.020
#> SRR1093721 2 0.3304 0.7506 0.000 0.816 0.000 0.168 0.016
#> SRR1464660 5 0.4088 0.9490 0.368 0.000 0.000 0.000 0.632
#> SRR1402051 4 0.4748 0.7885 0.112 0.120 0.000 0.756 0.012
#> SRR1488734 2 0.1197 0.8149 0.000 0.952 0.000 0.000 0.048
#> SRR1082616 4 0.7114 0.0333 0.236 0.000 0.312 0.432 0.020
#> SRR1099427 4 0.5281 0.7334 0.056 0.088 0.104 0.748 0.004
#> SRR1453093 4 0.4490 0.7973 0.088 0.124 0.000 0.776 0.012
#> SRR1357064 5 0.4161 0.9468 0.392 0.000 0.000 0.000 0.608
#> SRR811237 4 0.4249 0.7364 0.000 0.296 0.000 0.688 0.016
#> SRR1100848 4 0.4922 0.3918 0.004 0.424 0.000 0.552 0.020
#> SRR1346755 4 0.4154 0.7975 0.064 0.112 0.012 0.808 0.004
#> SRR1472529 2 0.3176 0.7883 0.000 0.856 0.000 0.064 0.080
#> SRR1398905 1 0.6073 0.4093 0.624 0.000 0.188 0.172 0.016
#> SRR1082733 2 0.1831 0.8129 0.000 0.920 0.000 0.004 0.076
#> SRR1308035 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.0671 0.8193 0.000 0.980 0.000 0.004 0.016
#> SRR1455825 2 0.3176 0.7883 0.000 0.856 0.000 0.064 0.080
#> SRR1389300 2 0.2974 0.7950 0.000 0.868 0.000 0.052 0.080
#> SRR812246 3 0.0613 0.9200 0.004 0.000 0.984 0.008 0.004
#> SRR1076632 2 0.4167 0.6245 0.000 0.724 0.000 0.252 0.024
#> SRR1415567 1 0.0451 0.6202 0.988 0.000 0.000 0.004 0.008
#> SRR1331900 2 0.3176 0.7883 0.000 0.856 0.000 0.064 0.080
#> SRR1452099 4 0.5159 0.7348 0.180 0.116 0.000 0.700 0.004
#> SRR1352346 1 0.7577 -0.1560 0.440 0.180 0.008 0.048 0.324
#> SRR1364034 2 0.2068 0.8152 0.000 0.904 0.000 0.004 0.092
#> SRR1086046 4 0.4871 0.7665 0.144 0.120 0.000 0.732 0.004
#> SRR1407226 1 0.2930 0.4822 0.832 0.000 0.000 0.004 0.164
#> SRR1319363 1 0.2689 0.6021 0.900 0.040 0.000 0.036 0.024
#> SRR1446961 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1486650 1 0.1012 0.6162 0.968 0.000 0.000 0.012 0.020
#> SRR1470152 5 0.4088 0.9490 0.368 0.000 0.000 0.000 0.632
#> SRR1454785 3 0.0162 0.9281 0.004 0.000 0.996 0.000 0.000
#> SRR1092329 4 0.5099 0.7502 0.060 0.232 0.008 0.696 0.004
#> SRR1091476 3 0.5541 0.3655 0.300 0.000 0.612 0.084 0.004
#> SRR1073775 4 0.3724 0.8097 0.028 0.184 0.000 0.788 0.000
#> SRR1366873 2 0.3421 0.7790 0.000 0.840 0.000 0.080 0.080
#> SRR1398114 2 0.1851 0.8141 0.000 0.912 0.000 0.000 0.088
#> SRR1089950 1 0.4835 0.4803 0.760 0.116 0.000 0.100 0.024
#> SRR1433272 2 0.4308 0.7628 0.040 0.804 0.000 0.052 0.104
#> SRR1075314 1 0.3531 0.5838 0.816 0.000 0.000 0.036 0.148
#> SRR1085590 3 0.3333 0.7083 0.004 0.000 0.788 0.208 0.000
#> SRR1100752 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 2 0.6101 0.6208 0.052 0.668 0.020 0.208 0.052
#> SRR1333263 2 0.8010 0.2096 0.044 0.448 0.256 0.220 0.032
#> SRR1310231 2 0.1571 0.8115 0.000 0.936 0.000 0.004 0.060
#> SRR1094144 4 0.4815 0.7124 0.008 0.304 0.000 0.660 0.028
#> SRR1092160 2 0.3339 0.7819 0.000 0.840 0.000 0.048 0.112
#> SRR1320300 2 0.3421 0.7790 0.000 0.840 0.000 0.080 0.080
#> SRR1322747 2 0.6289 0.4117 0.024 0.576 0.328 0.036 0.036
#> SRR1432719 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 2 0.5182 0.0282 0.000 0.544 0.000 0.412 0.044
#> SRR1087511 4 0.4444 0.7967 0.088 0.120 0.000 0.780 0.012
#> SRR1470336 1 0.2426 0.6221 0.900 0.000 0.000 0.036 0.064
#> SRR1322536 1 0.3452 0.5848 0.820 0.000 0.000 0.032 0.148
#> SRR1100824 1 0.5544 0.1278 0.636 0.000 0.028 0.048 0.288
#> SRR1085951 1 0.6726 0.2561 0.492 0.000 0.320 0.172 0.016
#> SRR1322046 2 0.3164 0.8035 0.000 0.852 0.000 0.044 0.104
#> SRR1316420 1 0.4779 -0.6148 0.536 0.004 0.000 0.012 0.448
#> SRR1070913 2 0.3362 0.7817 0.000 0.844 0.000 0.076 0.080
#> SRR1345806 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.3159 0.7895 0.000 0.856 0.000 0.056 0.088
#> SRR1337666 2 0.2077 0.8055 0.000 0.908 0.000 0.008 0.084
#> SRR1076823 1 0.3012 0.5963 0.852 0.000 0.000 0.024 0.124
#> SRR1093954 2 0.1831 0.8129 0.000 0.920 0.000 0.004 0.076
#> SRR1451921 1 0.3764 0.5843 0.808 0.004 0.000 0.040 0.148
#> SRR1491257 5 0.4101 0.9498 0.372 0.000 0.000 0.000 0.628
#> SRR1416979 4 0.4029 0.7097 0.000 0.316 0.000 0.680 0.004
#> SRR1419015 1 0.8341 0.1745 0.428 0.092 0.116 0.316 0.048
#> SRR817649 2 0.3115 0.7887 0.000 0.852 0.000 0.036 0.112
#> SRR1466376 2 0.2012 0.8218 0.000 0.920 0.000 0.020 0.060
#> SRR1392055 2 0.0609 0.8204 0.000 0.980 0.000 0.000 0.020
#> SRR1120913 2 0.1671 0.8134 0.000 0.924 0.000 0.000 0.076
#> SRR1120869 2 0.3102 0.7927 0.000 0.860 0.000 0.056 0.084
#> SRR1319419 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR818694 4 0.4347 0.8052 0.076 0.136 0.000 0.780 0.008
#> SRR1465653 5 0.4723 0.9314 0.368 0.012 0.000 0.008 0.612
#> SRR1475952 1 0.1830 0.6266 0.932 0.000 0.000 0.028 0.040
#> SRR1465040 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 2 0.1831 0.8129 0.000 0.920 0.000 0.004 0.076
#> SRR810129 2 0.1732 0.8155 0.000 0.920 0.000 0.000 0.080
#> SRR1400141 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 5 0.4302 0.7784 0.480 0.000 0.000 0.000 0.520
#> SRR1437576 2 0.6834 0.5961 0.016 0.632 0.148 0.124 0.080
#> SRR814407 1 0.5505 0.4627 0.720 0.000 0.096 0.056 0.128
#> SRR1332403 2 0.1671 0.8134 0.000 0.924 0.000 0.000 0.076
#> SRR1099598 4 0.4090 0.7588 0.000 0.268 0.000 0.716 0.016
#> SRR1327723 2 0.1671 0.8134 0.000 0.924 0.000 0.000 0.076
#> SRR1392525 4 0.5041 0.3913 0.048 0.000 0.260 0.680 0.012
#> SRR1320536 1 0.0566 0.6186 0.984 0.000 0.000 0.004 0.012
#> SRR1083824 2 0.6725 0.3997 0.024 0.548 0.328 0.040 0.060
#> SRR1351390 1 0.3823 0.5210 0.820 0.112 0.000 0.060 0.008
#> SRR1309141 2 0.7564 0.3929 0.036 0.540 0.256 0.084 0.084
#> SRR1452803 2 0.2077 0.8055 0.000 0.908 0.000 0.008 0.084
#> SRR811631 2 0.6576 0.2620 0.004 0.480 0.320 0.196 0.000
#> SRR1485563 4 0.4930 0.7999 0.056 0.188 0.000 0.732 0.024
#> SRR1311531 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 4 0.4610 0.5826 0.000 0.388 0.000 0.596 0.016
#> SRR1480831 4 0.4290 0.7281 0.000 0.304 0.000 0.680 0.016
#> SRR1083892 5 0.4150 0.9501 0.388 0.000 0.000 0.000 0.612
#> SRR809873 1 0.2754 0.6118 0.884 0.004 0.000 0.032 0.080
#> SRR1341854 2 0.3012 0.8069 0.000 0.860 0.000 0.036 0.104
#> SRR1399335 2 0.2304 0.8027 0.000 0.892 0.000 0.008 0.100
#> SRR1464209 5 0.4138 0.9522 0.384 0.000 0.000 0.000 0.616
#> SRR1389886 2 0.1671 0.8134 0.000 0.924 0.000 0.000 0.076
#> SRR1400730 1 0.6073 0.4093 0.624 0.000 0.188 0.172 0.016
#> SRR1448008 4 0.3844 0.8134 0.044 0.164 0.000 0.792 0.000
#> SRR1087606 1 0.7109 -0.3693 0.416 0.112 0.000 0.060 0.412
#> SRR1445111 1 0.1952 0.5686 0.912 0.000 0.000 0.004 0.084
#> SRR816865 2 0.4481 0.6209 0.000 0.720 0.000 0.232 0.048
#> SRR1323360 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.0000 0.9310 0.000 0.000 1.000 0.000 0.000
#> SRR1480329 2 0.4229 0.5553 0.000 0.704 0.000 0.276 0.020
#> SRR1403322 1 0.3152 0.5909 0.840 0.000 0.000 0.024 0.136
#> SRR1093625 1 0.0451 0.6202 0.988 0.000 0.000 0.004 0.008
#> SRR1479977 2 0.1549 0.8167 0.000 0.944 0.000 0.040 0.016
#> SRR1082035 1 0.6533 0.2701 0.628 0.120 0.000 0.080 0.172
#> SRR1393046 2 0.6180 0.6626 0.008 0.684 0.124 0.104 0.080
#> SRR1466663 2 0.5063 0.7099 0.072 0.756 0.000 0.060 0.112
#> SRR1384456 1 0.0404 0.6189 0.988 0.000 0.000 0.000 0.012
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0405 0.66178 0.000 0.988 0.000 0.000 0.004 0.008
#> SRR808862 1 0.6184 0.43160 0.480 0.000 0.076 0.052 0.008 0.384
#> SRR1500382 2 0.3769 0.52529 0.000 0.640 0.000 0.000 0.004 0.356
#> SRR1322683 4 0.5179 0.66414 0.052 0.252 0.048 0.648 0.000 0.000
#> SRR1329811 5 0.2048 0.84016 0.120 0.000 0.000 0.000 0.880 0.000
#> SRR1087297 2 0.3756 0.49233 0.000 0.600 0.000 0.000 0.000 0.400
#> SRR1072626 4 0.4405 0.54972 0.000 0.472 0.000 0.504 0.000 0.024
#> SRR1407428 1 0.1268 0.63046 0.952 0.000 0.000 0.036 0.008 0.004
#> SRR1321029 2 0.4637 0.57500 0.008 0.668 0.016 0.028 0.000 0.280
#> SRR1500282 1 0.3509 0.55190 0.832 0.000 0.008 0.064 0.084 0.012
#> SRR1100496 3 0.5477 0.59807 0.104 0.000 0.672 0.172 0.008 0.044
#> SRR1308778 2 0.4083 0.41277 0.000 0.532 0.000 0.008 0.000 0.460
#> SRR1445304 2 0.2092 0.67452 0.000 0.876 0.000 0.000 0.000 0.124
#> SRR1099378 1 0.7061 0.04174 0.440 0.344 0.000 0.080 0.024 0.112
#> SRR1347412 1 0.3971 0.55566 0.816 0.000 0.032 0.076 0.056 0.020
#> SRR1099694 2 0.4184 0.36456 0.000 0.504 0.000 0.012 0.000 0.484
#> SRR1088365 2 0.3741 0.08304 0.000 0.672 0.000 0.320 0.000 0.008
#> SRR1325752 1 0.7051 -0.12705 0.404 0.348 0.000 0.148 0.004 0.096
#> SRR1416713 2 0.3221 0.60828 0.000 0.736 0.000 0.000 0.000 0.264
#> SRR1074474 1 0.0692 0.62295 0.976 0.000 0.000 0.000 0.020 0.004
#> SRR1469369 3 0.4469 0.48119 0.008 0.000 0.608 0.364 0.008 0.012
#> SRR1400507 2 0.2378 0.52540 0.000 0.848 0.000 0.152 0.000 0.000
#> SRR1378179 2 0.3782 0.54677 0.000 0.636 0.000 0.004 0.000 0.360
#> SRR1377905 2 0.5856 0.49566 0.016 0.620 0.056 0.068 0.000 0.240
#> SRR1089479 1 0.0862 0.62506 0.972 0.000 0.000 0.016 0.008 0.004
#> SRR1073365 2 0.0146 0.65928 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1500306 1 0.5613 0.58174 0.584 0.012 0.000 0.316 0.048 0.040
#> SRR1101566 4 0.4204 0.66743 0.052 0.252 0.000 0.696 0.000 0.000
#> SRR1350503 3 0.0665 0.85839 0.004 0.000 0.980 0.008 0.000 0.008
#> SRR1446007 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 2 0.0146 0.65844 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1380293 2 0.3823 0.45330 0.000 0.564 0.000 0.000 0.000 0.436
#> SRR1331198 2 0.3717 0.50332 0.000 0.616 0.000 0.000 0.000 0.384
#> SRR1092686 3 0.0146 0.86217 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1069421 2 0.5847 0.15592 0.000 0.484 0.000 0.232 0.000 0.284
#> SRR1341650 4 0.7322 0.60405 0.104 0.288 0.028 0.492 0.028 0.060
#> SRR1357276 2 0.3852 0.49876 0.000 0.612 0.000 0.000 0.004 0.384
#> SRR1498374 2 0.3134 0.65436 0.000 0.808 0.000 0.024 0.000 0.168
#> SRR1093721 2 0.5215 0.31578 0.000 0.600 0.000 0.256 0.000 0.144
#> SRR1464660 5 0.2191 0.83956 0.120 0.000 0.000 0.004 0.876 0.000
#> SRR1402051 4 0.5048 0.66444 0.068 0.316 0.000 0.604 0.000 0.012
#> SRR1488734 2 0.3360 0.60247 0.000 0.732 0.000 0.000 0.004 0.264
#> SRR1082616 3 0.5784 0.28434 0.096 0.000 0.472 0.412 0.008 0.012
#> SRR1099427 4 0.5565 0.65758 0.048 0.268 0.076 0.608 0.000 0.000
#> SRR1453093 4 0.3493 0.54514 0.056 0.148 0.000 0.796 0.000 0.000
#> SRR1357064 5 0.2191 0.83964 0.120 0.000 0.000 0.004 0.876 0.000
#> SRR811237 4 0.4403 0.55152 0.000 0.468 0.000 0.508 0.000 0.024
#> SRR1100848 4 0.5018 0.47754 0.012 0.464 0.000 0.480 0.000 0.044
#> SRR1346755 4 0.5241 0.66777 0.056 0.292 0.036 0.616 0.000 0.000
#> SRR1472529 2 0.0713 0.64619 0.000 0.972 0.000 0.028 0.000 0.000
#> SRR1398905 1 0.6019 0.43726 0.488 0.000 0.060 0.052 0.008 0.392
#> SRR1082733 2 0.0146 0.65928 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1308035 3 0.0260 0.86030 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1466445 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.2632 0.65392 0.000 0.832 0.000 0.000 0.004 0.164
#> SRR1455825 2 0.0692 0.65172 0.000 0.976 0.000 0.020 0.000 0.004
#> SRR1389300 2 0.0146 0.65705 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR812246 3 0.0551 0.85415 0.000 0.000 0.984 0.008 0.004 0.004
#> SRR1076632 2 0.5508 -0.32487 0.000 0.480 0.000 0.388 0.000 0.132
#> SRR1415567 1 0.0692 0.62297 0.976 0.000 0.000 0.000 0.020 0.004
#> SRR1331900 2 0.0692 0.65172 0.000 0.976 0.000 0.020 0.000 0.004
#> SRR1452099 4 0.6133 0.61914 0.116 0.364 0.000 0.480 0.000 0.040
#> SRR1352346 5 0.6235 0.67292 0.148 0.064 0.000 0.044 0.640 0.104
#> SRR1364034 2 0.0937 0.66155 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1086046 4 0.3940 0.49818 0.096 0.140 0.000 0.764 0.000 0.000
#> SRR1407226 1 0.4141 0.09021 0.556 0.000 0.000 0.012 0.432 0.000
#> SRR1319363 1 0.6981 0.35599 0.540 0.096 0.000 0.108 0.220 0.036
#> SRR1446961 3 0.0665 0.85839 0.004 0.000 0.980 0.008 0.000 0.008
#> SRR1486650 1 0.1788 0.59605 0.916 0.000 0.000 0.004 0.076 0.004
#> SRR1470152 5 0.2191 0.83956 0.120 0.000 0.000 0.004 0.876 0.000
#> SRR1454785 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 4 0.5368 0.63781 0.052 0.344 0.036 0.568 0.000 0.000
#> SRR1091476 3 0.6088 0.08749 0.228 0.000 0.420 0.000 0.004 0.348
#> SRR1073775 4 0.4524 0.64912 0.040 0.376 0.000 0.584 0.000 0.000
#> SRR1366873 2 0.1411 0.62686 0.000 0.936 0.000 0.060 0.000 0.004
#> SRR1398114 2 0.1082 0.66409 0.000 0.956 0.000 0.004 0.000 0.040
#> SRR1089950 1 0.7336 0.31482 0.512 0.156 0.000 0.100 0.188 0.044
#> SRR1433272 2 0.5253 0.35015 0.028 0.492 0.000 0.016 0.016 0.448
#> SRR1075314 1 0.6242 0.56149 0.528 0.012 0.000 0.316 0.104 0.040
#> SRR1085590 3 0.3023 0.66171 0.004 0.000 0.784 0.212 0.000 0.000
#> SRR1100752 3 0.0260 0.86030 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1391494 2 0.5334 0.31969 0.048 0.672 0.048 0.216 0.000 0.016
#> SRR1333263 4 0.7624 0.28266 0.028 0.228 0.220 0.440 0.008 0.076
#> SRR1310231 2 0.3684 0.54774 0.000 0.664 0.000 0.000 0.004 0.332
#> SRR1094144 4 0.5492 0.54706 0.012 0.424 0.000 0.476 0.000 0.088
#> SRR1092160 2 0.4264 0.35990 0.000 0.500 0.000 0.016 0.000 0.484
#> SRR1320300 2 0.1327 0.62005 0.000 0.936 0.000 0.064 0.000 0.000
#> SRR1322747 2 0.6908 -0.08329 0.008 0.412 0.332 0.048 0.000 0.200
#> SRR1432719 3 0.0405 0.86062 0.004 0.000 0.988 0.000 0.000 0.008
#> SRR1100728 2 0.5794 -0.39489 0.000 0.436 0.000 0.384 0.000 0.180
#> SRR1087511 4 0.3530 0.55084 0.056 0.152 0.000 0.792 0.000 0.000
#> SRR1470336 1 0.4815 0.59229 0.632 0.012 0.000 0.316 0.024 0.016
#> SRR1322536 1 0.6242 0.56149 0.528 0.012 0.000 0.316 0.104 0.040
#> SRR1100824 5 0.5120 0.20653 0.408 0.000 0.004 0.052 0.528 0.008
#> SRR1085951 6 0.7031 -0.50142 0.324 0.000 0.224 0.052 0.008 0.392
#> SRR1322046 2 0.2147 0.63447 0.000 0.896 0.000 0.020 0.000 0.084
#> SRR1316420 5 0.4424 0.72220 0.232 0.036 0.000 0.024 0.708 0.000
#> SRR1070913 2 0.1204 0.62769 0.000 0.944 0.000 0.056 0.000 0.000
#> SRR1345806 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.4179 0.38623 0.000 0.516 0.000 0.012 0.000 0.472
#> SRR1337666 2 0.3727 0.50074 0.000 0.612 0.000 0.000 0.000 0.388
#> SRR1076823 1 0.5965 0.56818 0.548 0.004 0.000 0.312 0.096 0.040
#> SRR1093954 2 0.0146 0.65928 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1451921 1 0.7029 0.53341 0.472 0.076 0.000 0.320 0.096 0.036
#> SRR1491257 5 0.2234 0.83894 0.124 0.000 0.000 0.004 0.872 0.000
#> SRR1416979 4 0.3997 0.51486 0.000 0.488 0.000 0.508 0.000 0.004
#> SRR1419015 4 0.5683 0.00823 0.116 0.000 0.032 0.680 0.132 0.040
#> SRR817649 2 0.4093 0.39037 0.000 0.516 0.000 0.008 0.000 0.476
#> SRR1466376 2 0.2362 0.67215 0.000 0.860 0.000 0.004 0.000 0.136
#> SRR1392055 2 0.2191 0.66888 0.000 0.876 0.000 0.000 0.004 0.120
#> SRR1120913 2 0.0405 0.66178 0.000 0.988 0.000 0.000 0.004 0.008
#> SRR1120869 2 0.4682 0.46145 0.000 0.556 0.000 0.048 0.000 0.396
#> SRR1319419 3 0.0291 0.86129 0.004 0.000 0.992 0.000 0.000 0.004
#> SRR816495 3 0.0260 0.86183 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR818694 4 0.3835 0.61173 0.048 0.204 0.000 0.748 0.000 0.000
#> SRR1465653 5 0.2048 0.84016 0.120 0.000 0.000 0.000 0.880 0.000
#> SRR1475952 1 0.3442 0.61533 0.756 0.004 0.000 0.232 0.004 0.004
#> SRR1465040 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 2 0.0260 0.65801 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR810129 2 0.1806 0.67378 0.000 0.908 0.000 0.004 0.000 0.088
#> SRR1400141 3 0.0146 0.86217 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1349585 5 0.2994 0.77902 0.208 0.000 0.000 0.004 0.788 0.000
#> SRR1437576 2 0.3749 0.48111 0.004 0.796 0.128 0.068 0.000 0.004
#> SRR814407 1 0.2935 0.57816 0.872 0.000 0.020 0.076 0.016 0.016
#> SRR1332403 2 0.0363 0.66240 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1099598 4 0.4389 0.57640 0.000 0.448 0.000 0.528 0.000 0.024
#> SRR1327723 2 0.0291 0.66050 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1392525 4 0.6218 0.37571 0.012 0.148 0.276 0.544 0.008 0.012
#> SRR1320536 1 0.1471 0.60415 0.932 0.000 0.000 0.000 0.064 0.004
#> SRR1083824 3 0.7133 -0.37963 0.008 0.268 0.344 0.052 0.000 0.328
#> SRR1351390 1 0.7054 0.44387 0.536 0.084 0.004 0.192 0.160 0.024
#> SRR1309141 6 0.8072 0.00113 0.020 0.248 0.228 0.144 0.008 0.352
#> SRR1452803 2 0.3717 0.50332 0.000 0.616 0.000 0.000 0.000 0.384
#> SRR811631 4 0.6313 0.33572 0.004 0.304 0.288 0.400 0.000 0.004
#> SRR1485563 4 0.5449 0.63133 0.056 0.384 0.000 0.528 0.000 0.032
#> SRR1311531 3 0.0000 0.86236 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.4408 0.52176 0.000 0.488 0.000 0.488 0.000 0.024
#> SRR1480831 4 0.4407 0.53538 0.000 0.480 0.000 0.496 0.000 0.024
#> SRR1083892 5 0.2191 0.83964 0.120 0.000 0.000 0.004 0.876 0.000
#> SRR809873 1 0.6810 0.53982 0.488 0.080 0.000 0.320 0.088 0.024
#> SRR1341854 2 0.1918 0.65262 0.000 0.904 0.000 0.008 0.000 0.088
#> SRR1399335 2 0.3828 0.44864 0.000 0.560 0.000 0.000 0.000 0.440
#> SRR1464209 5 0.2048 0.84016 0.120 0.000 0.000 0.000 0.880 0.000
#> SRR1389886 2 0.0405 0.66178 0.000 0.988 0.000 0.000 0.004 0.008
#> SRR1400730 1 0.6019 0.43726 0.488 0.000 0.060 0.052 0.008 0.392
#> SRR1448008 4 0.4782 0.64181 0.048 0.380 0.000 0.568 0.000 0.004
#> SRR1087606 5 0.5880 0.66707 0.168 0.084 0.000 0.032 0.660 0.056
#> SRR1445111 1 0.0696 0.62565 0.980 0.004 0.000 0.004 0.008 0.004
#> SRR816865 2 0.5788 -0.19271 0.000 0.484 0.000 0.316 0.000 0.200
#> SRR1323360 3 0.0260 0.86030 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1417364 3 0.0551 0.85999 0.004 0.000 0.984 0.004 0.000 0.008
#> SRR1480329 2 0.5182 -0.13591 0.000 0.532 0.000 0.372 0.000 0.096
#> SRR1403322 1 0.6066 0.56639 0.544 0.008 0.000 0.312 0.096 0.040
#> SRR1093625 1 0.0692 0.62297 0.976 0.000 0.000 0.000 0.020 0.004
#> SRR1479977 2 0.1814 0.67375 0.000 0.900 0.000 0.000 0.000 0.100
#> SRR1082035 5 0.7747 0.33620 0.248 0.148 0.000 0.060 0.444 0.100
#> SRR1393046 2 0.3705 0.48903 0.008 0.804 0.124 0.060 0.000 0.004
#> SRR1466663 6 0.4472 -0.55042 0.000 0.476 0.000 0.028 0.000 0.496
#> SRR1384456 1 0.1152 0.61397 0.952 0.000 0.000 0.000 0.044 0.004
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 17467 rows and 159 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 0.717 0.878 0.936 0.4012 0.621 0.621
#> 3 3 0.968 0.919 0.971 0.4340 0.783 0.657
#> 4 4 0.600 0.534 0.749 0.1764 0.823 0.610
#> 5 5 0.611 0.627 0.782 0.1181 0.764 0.399
#> 6 6 0.776 0.755 0.880 0.0468 0.880 0.580
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
#> SRR810713 2 0.0000 0.937 0.000 1.000
#> SRR808862 2 0.9988 0.191 0.480 0.520
#> SRR1500382 2 0.0000 0.937 0.000 1.000
#> SRR1322683 2 0.0000 0.937 0.000 1.000
#> SRR1329811 1 0.5059 0.891 0.888 0.112
#> SRR1087297 2 0.0000 0.937 0.000 1.000
#> SRR1072626 2 0.0000 0.937 0.000 1.000
#> SRR1407428 1 0.2236 0.946 0.964 0.036
#> SRR1321029 2 0.0000 0.937 0.000 1.000
#> SRR1500282 1 0.2236 0.946 0.964 0.036
#> SRR1100496 2 0.9732 0.414 0.404 0.596
#> SRR1308778 2 0.0000 0.937 0.000 1.000
#> SRR1445304 2 0.0000 0.937 0.000 1.000
#> SRR1099378 2 0.9087 0.473 0.324 0.676
#> SRR1347412 1 0.0000 0.916 1.000 0.000
#> SRR1099694 2 0.0000 0.937 0.000 1.000
#> SRR1088365 2 0.0000 0.937 0.000 1.000
#> SRR1325752 2 0.4562 0.857 0.096 0.904
#> SRR1416713 2 0.0000 0.937 0.000 1.000
#> SRR1074474 1 0.2236 0.946 0.964 0.036
#> SRR1469369 2 0.6801 0.804 0.180 0.820
#> SRR1400507 2 0.0000 0.937 0.000 1.000
#> SRR1378179 2 0.0000 0.937 0.000 1.000
#> SRR1377905 2 0.0000 0.937 0.000 1.000
#> SRR1089479 1 0.2236 0.946 0.964 0.036
#> SRR1073365 2 0.0000 0.937 0.000 1.000
#> SRR1500306 1 0.2236 0.946 0.964 0.036
#> SRR1101566 2 0.0000 0.937 0.000 1.000
#> SRR1350503 2 0.2236 0.916 0.036 0.964
#> SRR1446007 2 0.5059 0.870 0.112 0.888
#> SRR1102875 2 0.0000 0.937 0.000 1.000
#> SRR1380293 2 0.0000 0.937 0.000 1.000
#> SRR1331198 2 0.0000 0.937 0.000 1.000
#> SRR1092686 2 0.7528 0.760 0.216 0.784
#> SRR1069421 2 0.0000 0.937 0.000 1.000
#> SRR1341650 2 0.5519 0.847 0.128 0.872
#> SRR1357276 2 0.0000 0.937 0.000 1.000
#> SRR1498374 2 0.0000 0.937 0.000 1.000
#> SRR1093721 2 0.0000 0.937 0.000 1.000
#> SRR1464660 1 0.3114 0.935 0.944 0.056
#> SRR1402051 2 0.4431 0.861 0.092 0.908
#> SRR1488734 2 0.0000 0.937 0.000 1.000
#> SRR1082616 2 0.8955 0.612 0.312 0.688
#> SRR1099427 2 0.2236 0.916 0.036 0.964
#> SRR1453093 2 0.0000 0.937 0.000 1.000
#> SRR1357064 1 0.2236 0.946 0.964 0.036
#> SRR811237 2 0.0000 0.937 0.000 1.000
#> SRR1100848 2 0.0000 0.937 0.000 1.000
#> SRR1346755 2 0.0000 0.937 0.000 1.000
#> SRR1472529 2 0.0000 0.937 0.000 1.000
#> SRR1398905 1 0.0000 0.916 1.000 0.000
#> SRR1082733 2 0.0000 0.937 0.000 1.000
#> SRR1308035 2 0.8861 0.626 0.304 0.696
#> SRR1466445 2 0.8608 0.660 0.284 0.716
#> SRR1359080 2 0.0000 0.937 0.000 1.000
#> SRR1455825 2 0.0000 0.937 0.000 1.000
#> SRR1389300 2 0.0000 0.937 0.000 1.000
#> SRR812246 2 0.9795 0.383 0.416 0.584
#> SRR1076632 2 0.0000 0.937 0.000 1.000
#> SRR1415567 1 0.2236 0.946 0.964 0.036
#> SRR1331900 2 0.0000 0.937 0.000 1.000
#> SRR1452099 2 0.4939 0.844 0.108 0.892
#> SRR1352346 2 0.8763 0.528 0.296 0.704
#> SRR1364034 2 0.0000 0.937 0.000 1.000
#> SRR1086046 2 0.3114 0.895 0.056 0.944
#> SRR1407226 1 0.2236 0.946 0.964 0.036
#> SRR1319363 1 0.6712 0.826 0.824 0.176
#> SRR1446961 2 0.2236 0.916 0.036 0.964
#> SRR1486650 1 0.2236 0.946 0.964 0.036
#> SRR1470152 1 0.2236 0.946 0.964 0.036
#> SRR1454785 2 0.4939 0.873 0.108 0.892
#> SRR1092329 2 0.0000 0.937 0.000 1.000
#> SRR1091476 2 0.9922 0.294 0.448 0.552
#> SRR1073775 2 0.0000 0.937 0.000 1.000
#> SRR1366873 2 0.0000 0.937 0.000 1.000
#> SRR1398114 2 0.0000 0.937 0.000 1.000
#> SRR1089950 1 0.7674 0.762 0.776 0.224
#> SRR1433272 2 0.0000 0.937 0.000 1.000
#> SRR1075314 1 0.3114 0.934 0.944 0.056
#> SRR1085590 2 0.3114 0.908 0.056 0.944
#> SRR1100752 2 0.8861 0.626 0.304 0.696
#> SRR1391494 2 0.0000 0.937 0.000 1.000
#> SRR1333263 2 0.4939 0.873 0.108 0.892
#> SRR1310231 2 0.0000 0.937 0.000 1.000
#> SRR1094144 2 0.0000 0.937 0.000 1.000
#> SRR1092160 2 0.0000 0.937 0.000 1.000
#> SRR1320300 2 0.0000 0.937 0.000 1.000
#> SRR1322747 2 0.2236 0.916 0.036 0.964
#> SRR1432719 2 0.5059 0.870 0.112 0.888
#> SRR1100728 2 0.0000 0.937 0.000 1.000
#> SRR1087511 2 0.0000 0.937 0.000 1.000
#> SRR1470336 1 0.2236 0.946 0.964 0.036
#> SRR1322536 1 0.2236 0.946 0.964 0.036
#> SRR1100824 1 0.2236 0.946 0.964 0.036
#> SRR1085951 1 0.9795 0.187 0.584 0.416
#> SRR1322046 2 0.0000 0.937 0.000 1.000
#> SRR1316420 1 0.2236 0.946 0.964 0.036
#> SRR1070913 2 0.0000 0.937 0.000 1.000
#> SRR1345806 2 0.5059 0.870 0.112 0.888
#> SRR1313872 2 0.0000 0.937 0.000 1.000
#> SRR1337666 2 0.0000 0.937 0.000 1.000
#> SRR1076823 1 0.2236 0.946 0.964 0.036
#> SRR1093954 2 0.0000 0.937 0.000 1.000
#> SRR1451921 2 0.7745 0.673 0.228 0.772
#> SRR1491257 1 0.2236 0.946 0.964 0.036
#> SRR1416979 2 0.0000 0.937 0.000 1.000
#> SRR1419015 2 0.9963 0.163 0.464 0.536
#> SRR817649 2 0.0000 0.937 0.000 1.000
#> SRR1466376 2 0.0000 0.937 0.000 1.000
#> SRR1392055 2 0.0000 0.937 0.000 1.000
#> SRR1120913 2 0.0000 0.937 0.000 1.000
#> SRR1120869 2 0.0000 0.937 0.000 1.000
#> SRR1319419 2 0.4562 0.882 0.096 0.904
#> SRR816495 2 0.4562 0.882 0.096 0.904
#> SRR818694 2 0.0000 0.937 0.000 1.000
#> SRR1465653 1 0.6623 0.831 0.828 0.172
#> SRR1475952 1 0.2236 0.946 0.964 0.036
#> SRR1465040 2 0.4939 0.873 0.108 0.892
#> SRR1088461 2 0.0000 0.937 0.000 1.000
#> SRR810129 2 0.0000 0.937 0.000 1.000
#> SRR1400141 2 0.6247 0.830 0.156 0.844
#> SRR1349585 1 0.2236 0.946 0.964 0.036
#> SRR1437576 2 0.0000 0.937 0.000 1.000
#> SRR814407 1 0.1843 0.940 0.972 0.028
#> SRR1332403 2 0.0000 0.937 0.000 1.000
#> SRR1099598 2 0.0000 0.937 0.000 1.000
#> SRR1327723 2 0.0000 0.937 0.000 1.000
#> SRR1392525 2 0.4298 0.888 0.088 0.912
#> SRR1320536 1 0.2236 0.946 0.964 0.036
#> SRR1083824 2 0.2236 0.916 0.036 0.964
#> SRR1351390 1 0.4815 0.897 0.896 0.104
#> SRR1309141 2 0.4562 0.883 0.096 0.904
#> SRR1452803 2 0.0000 0.937 0.000 1.000
#> SRR811631 2 0.2236 0.916 0.036 0.964
#> SRR1485563 2 0.0000 0.937 0.000 1.000
#> SRR1311531 2 0.6623 0.813 0.172 0.828
#> SRR1353076 2 0.0000 0.937 0.000 1.000
#> SRR1480831 2 0.0000 0.937 0.000 1.000
#> SRR1083892 1 0.2423 0.944 0.960 0.040
#> SRR809873 1 0.6623 0.818 0.828 0.172
#> SRR1341854 2 0.0000 0.937 0.000 1.000
#> SRR1399335 2 0.0000 0.937 0.000 1.000
#> SRR1464209 1 0.2236 0.946 0.964 0.036
#> SRR1389886 2 0.0000 0.937 0.000 1.000
#> SRR1400730 1 0.3584 0.882 0.932 0.068
#> SRR1448008 2 0.0000 0.937 0.000 1.000
#> SRR1087606 1 0.5519 0.877 0.872 0.128
#> SRR1445111 1 0.2236 0.946 0.964 0.036
#> SRR816865 2 0.0000 0.937 0.000 1.000
#> SRR1323360 2 0.7299 0.775 0.204 0.796
#> SRR1417364 2 0.3114 0.908 0.056 0.944
#> SRR1480329 2 0.0000 0.937 0.000 1.000
#> SRR1403322 1 0.2236 0.946 0.964 0.036
#> SRR1093625 1 0.2236 0.946 0.964 0.036
#> SRR1479977 2 0.0000 0.937 0.000 1.000
#> SRR1082035 1 0.9922 0.288 0.552 0.448
#> SRR1393046 2 0.0938 0.930 0.012 0.988
#> SRR1466663 2 0.2043 0.915 0.032 0.968
#> SRR1384456 1 0.2236 0.946 0.964 0.036
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1322683 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1329811 1 0.0237 0.95498 0.996 0.004 0.000
#> SRR1087297 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1072626 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1407428 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1321029 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1500282 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1100496 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1308778 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1445304 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1099378 2 0.6305 0.04198 0.484 0.516 0.000
#> SRR1347412 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1099694 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1325752 2 0.2625 0.88717 0.084 0.916 0.000
#> SRR1416713 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1074474 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1469369 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1400507 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1377905 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1089479 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1073365 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1500306 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1101566 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1350503 3 0.0424 0.95170 0.000 0.008 0.992
#> SRR1446007 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1102875 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1380293 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1331198 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1092686 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1069421 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1341650 2 0.4654 0.73138 0.208 0.792 0.000
#> SRR1357276 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1498374 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1093721 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1464660 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1402051 2 0.2066 0.91206 0.060 0.940 0.000
#> SRR1488734 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1082616 3 0.1529 0.91511 0.000 0.040 0.960
#> SRR1099427 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1453093 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1357064 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR811237 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1100848 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1346755 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1472529 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1398905 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1082733 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1308035 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1466445 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1359080 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR812246 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1076632 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1415567 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1331900 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1452099 2 0.4796 0.71269 0.220 0.780 0.000
#> SRR1352346 2 0.6140 0.29757 0.404 0.596 0.000
#> SRR1364034 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1086046 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1407226 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1319363 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1446961 3 0.5926 0.45045 0.000 0.356 0.644
#> SRR1486650 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1470152 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1454785 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1092329 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1091476 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1073775 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1089950 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1433272 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1075314 1 0.0592 0.95369 0.988 0.000 0.012
#> SRR1085590 2 0.6302 0.05197 0.000 0.520 0.480
#> SRR1100752 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1391494 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1333263 2 0.5785 0.49042 0.000 0.668 0.332
#> SRR1310231 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1094144 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1092160 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1320300 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1322747 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1432719 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1100728 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1087511 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1470336 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1322536 1 0.0592 0.95369 0.988 0.000 0.012
#> SRR1100824 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1085951 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1316420 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1070913 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1345806 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1313872 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1337666 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1076823 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1093954 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1451921 1 0.6521 0.00103 0.504 0.492 0.004
#> SRR1491257 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1416979 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1419015 1 0.6513 0.30816 0.592 0.400 0.008
#> SRR817649 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1466376 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1319419 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR816495 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR818694 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1465653 1 0.2261 0.87746 0.932 0.068 0.000
#> SRR1475952 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1465040 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1088461 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1400141 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1349585 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1437576 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR814407 1 0.0424 0.95621 0.992 0.000 0.008
#> SRR1332403 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1099598 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1327723 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1392525 3 0.6225 0.23044 0.000 0.432 0.568
#> SRR1320536 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1083824 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1351390 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1309141 2 0.5431 0.59034 0.000 0.716 0.284
#> SRR1452803 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR811631 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1485563 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1311531 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1353076 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1480831 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1083892 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR809873 1 0.0661 0.95205 0.988 0.008 0.004
#> SRR1341854 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1399335 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1464209 1 0.0000 0.95771 1.000 0.000 0.000
#> SRR1389886 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1400730 3 0.0000 0.95252 0.000 0.000 1.000
#> SRR1448008 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1087606 1 0.0892 0.93774 0.980 0.020 0.000
#> SRR1445111 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR816865 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1323360 3 0.0237 0.95515 0.000 0.004 0.996
#> SRR1417364 3 0.0424 0.95170 0.000 0.008 0.992
#> SRR1480329 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1403322 1 0.0592 0.95369 0.988 0.000 0.012
#> SRR1093625 1 0.0237 0.95828 0.996 0.000 0.004
#> SRR1479977 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1082035 1 0.2066 0.88800 0.940 0.060 0.000
#> SRR1393046 2 0.0000 0.96969 0.000 1.000 0.000
#> SRR1466663 2 0.0237 0.96677 0.004 0.996 0.000
#> SRR1384456 1 0.0237 0.95828 0.996 0.000 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.4843 0.64215 0.000 0.604 0.000 0.396
#> SRR808862 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1500382 4 0.4998 -0.40427 0.000 0.488 0.000 0.512
#> SRR1322683 2 0.0817 0.56007 0.000 0.976 0.000 0.024
#> SRR1329811 4 0.4277 -0.00845 0.280 0.000 0.000 0.720
#> SRR1087297 4 0.4888 -0.17537 0.000 0.412 0.000 0.588
#> SRR1072626 2 0.0188 0.53780 0.000 0.996 0.000 0.004
#> SRR1407428 1 0.0000 0.81929 1.000 0.000 0.000 0.000
#> SRR1321029 2 0.4998 0.44530 0.000 0.512 0.000 0.488
#> SRR1500282 1 0.3219 0.77396 0.836 0.000 0.000 0.164
#> SRR1100496 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1308778 4 0.4830 -0.12594 0.000 0.392 0.000 0.608
#> SRR1445304 4 0.5000 -0.45577 0.000 0.500 0.000 0.500
#> SRR1099378 4 0.4313 0.04155 0.260 0.004 0.000 0.736
#> SRR1347412 1 0.2216 0.80764 0.908 0.000 0.000 0.092
#> SRR1099694 4 0.4830 -0.12656 0.000 0.392 0.000 0.608
#> SRR1088365 2 0.4356 0.68591 0.000 0.708 0.000 0.292
#> SRR1325752 2 0.7072 0.48264 0.172 0.560 0.000 0.268
#> SRR1416713 4 0.4972 -0.31771 0.000 0.456 0.000 0.544
#> SRR1074474 1 0.1118 0.81918 0.964 0.000 0.000 0.036
#> SRR1469369 3 0.1022 0.91318 0.000 0.032 0.968 0.000
#> SRR1400507 2 0.3311 0.65030 0.000 0.828 0.000 0.172
#> SRR1378179 2 0.4898 0.62200 0.000 0.584 0.000 0.416
#> SRR1377905 4 0.4977 -0.32577 0.000 0.460 0.000 0.540
#> SRR1089479 1 0.0469 0.82047 0.988 0.000 0.000 0.012
#> SRR1073365 2 0.4761 0.66410 0.000 0.628 0.000 0.372
#> SRR1500306 1 0.5113 0.66182 0.684 0.292 0.000 0.024
#> SRR1101566 2 0.0707 0.54356 0.000 0.980 0.000 0.020
#> SRR1350503 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1446007 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.4605 0.68516 0.000 0.664 0.000 0.336
#> SRR1380293 4 0.2647 0.36957 0.000 0.120 0.000 0.880
#> SRR1331198 4 0.4250 0.18908 0.000 0.276 0.000 0.724
#> SRR1092686 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.4967 0.56633 0.000 0.548 0.000 0.452
#> SRR1341650 2 0.7034 0.39805 0.220 0.576 0.000 0.204
#> SRR1357276 4 0.4356 0.16308 0.000 0.292 0.000 0.708
#> SRR1498374 2 0.4843 0.63446 0.000 0.604 0.000 0.396
#> SRR1093721 2 0.4250 0.68070 0.000 0.724 0.000 0.276
#> SRR1464660 4 0.4643 -0.15150 0.344 0.000 0.000 0.656
#> SRR1402051 2 0.2021 0.47576 0.040 0.936 0.000 0.024
#> SRR1488734 2 0.4877 0.62733 0.000 0.592 0.000 0.408
#> SRR1082616 3 0.6685 0.26009 0.060 0.404 0.524 0.012
#> SRR1099427 2 0.0336 0.53409 0.000 0.992 0.000 0.008
#> SRR1453093 2 0.1733 0.48765 0.028 0.948 0.000 0.024
#> SRR1357064 4 0.4855 -0.25923 0.400 0.000 0.000 0.600
#> SRR811237 2 0.1302 0.56225 0.000 0.956 0.000 0.044
#> SRR1100848 2 0.4585 0.68495 0.000 0.668 0.000 0.332
#> SRR1346755 2 0.0921 0.56364 0.000 0.972 0.000 0.028
#> SRR1472529 2 0.4543 0.68645 0.000 0.676 0.000 0.324
#> SRR1398905 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1082733 2 0.4643 0.68130 0.000 0.656 0.000 0.344
#> SRR1308035 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1359080 4 0.4977 -0.32187 0.000 0.460 0.000 0.540
#> SRR1455825 2 0.4605 0.68203 0.000 0.664 0.000 0.336
#> SRR1389300 2 0.4697 0.67531 0.000 0.644 0.000 0.356
#> SRR812246 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.4605 0.68408 0.000 0.664 0.000 0.336
#> SRR1415567 1 0.0469 0.81984 0.988 0.000 0.000 0.012
#> SRR1331900 2 0.4564 0.68382 0.000 0.672 0.000 0.328
#> SRR1452099 2 0.5835 0.22472 0.372 0.588 0.000 0.040
#> SRR1352346 4 0.1724 0.40473 0.020 0.032 0.000 0.948
#> SRR1364034 2 0.4713 0.67629 0.000 0.640 0.000 0.360
#> SRR1086046 2 0.3552 0.35511 0.128 0.848 0.000 0.024
#> SRR1407226 1 0.2704 0.79635 0.876 0.000 0.000 0.124
#> SRR1319363 1 0.1109 0.81712 0.968 0.004 0.000 0.028
#> SRR1446961 3 0.6973 0.19162 0.000 0.220 0.584 0.196
#> SRR1486650 1 0.2589 0.79924 0.884 0.000 0.000 0.116
#> SRR1470152 4 0.4855 -0.26039 0.400 0.000 0.000 0.600
#> SRR1454785 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1092329 2 0.3311 0.65111 0.000 0.828 0.000 0.172
#> SRR1091476 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1073775 2 0.0817 0.54740 0.000 0.976 0.000 0.024
#> SRR1366873 2 0.4008 0.67146 0.000 0.756 0.000 0.244
#> SRR1398114 2 0.4804 0.65723 0.000 0.616 0.000 0.384
#> SRR1089950 1 0.5184 0.75809 0.736 0.060 0.000 0.204
#> SRR1433272 4 0.2216 0.38276 0.000 0.092 0.000 0.908
#> SRR1075314 1 0.5548 0.57758 0.588 0.388 0.000 0.024
#> SRR1085590 2 0.5592 0.28657 0.000 0.572 0.404 0.024
#> SRR1100752 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.4522 0.68751 0.000 0.680 0.000 0.320
#> SRR1333263 2 0.7109 0.50483 0.000 0.520 0.144 0.336
#> SRR1310231 2 0.4972 0.53401 0.000 0.544 0.000 0.456
#> SRR1094144 2 0.4193 0.67829 0.000 0.732 0.000 0.268
#> SRR1092160 4 0.3764 0.27551 0.000 0.216 0.000 0.784
#> SRR1320300 2 0.3942 0.67640 0.000 0.764 0.000 0.236
#> SRR1322747 2 0.5060 0.62059 0.000 0.584 0.004 0.412
#> SRR1432719 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1100728 2 0.4697 0.66047 0.000 0.644 0.000 0.356
#> SRR1087511 2 0.1929 0.47793 0.036 0.940 0.000 0.024
#> SRR1470336 1 0.4898 0.68806 0.716 0.260 0.000 0.024
#> SRR1322536 1 0.5482 0.59613 0.608 0.368 0.000 0.024
#> SRR1100824 1 0.4605 0.63742 0.664 0.000 0.000 0.336
#> SRR1085951 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1322046 2 0.4713 0.67356 0.000 0.640 0.000 0.360
#> SRR1316420 1 0.4907 0.53846 0.580 0.000 0.000 0.420
#> SRR1070913 2 0.4164 0.67729 0.000 0.736 0.000 0.264
#> SRR1345806 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1313872 4 0.4916 -0.24326 0.000 0.424 0.000 0.576
#> SRR1337666 4 0.3074 0.34758 0.000 0.152 0.000 0.848
#> SRR1076823 1 0.3160 0.78517 0.872 0.108 0.000 0.020
#> SRR1093954 2 0.4624 0.68369 0.000 0.660 0.000 0.340
#> SRR1451921 2 0.5613 -0.27062 0.380 0.592 0.000 0.028
#> SRR1491257 4 0.4925 -0.31350 0.428 0.000 0.000 0.572
#> SRR1416979 2 0.4193 0.68413 0.000 0.732 0.000 0.268
#> SRR1419015 1 0.4993 0.57569 0.712 0.260 0.000 0.028
#> SRR817649 4 0.2408 0.37994 0.000 0.104 0.000 0.896
#> SRR1466376 2 0.5000 0.43671 0.000 0.504 0.000 0.496
#> SRR1392055 2 0.4907 0.60495 0.000 0.580 0.000 0.420
#> SRR1120913 2 0.4907 0.60928 0.000 0.580 0.000 0.420
#> SRR1120869 2 0.4877 0.63717 0.000 0.592 0.000 0.408
#> SRR1319419 3 0.0188 0.94567 0.000 0.004 0.996 0.000
#> SRR816495 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR818694 2 0.1284 0.50550 0.012 0.964 0.000 0.024
#> SRR1465653 4 0.4134 0.03939 0.260 0.000 0.000 0.740
#> SRR1475952 1 0.3441 0.77787 0.856 0.120 0.000 0.024
#> SRR1465040 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1088461 2 0.4730 0.67305 0.000 0.636 0.000 0.364
#> SRR810129 2 0.4907 0.61601 0.000 0.580 0.000 0.420
#> SRR1400141 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.4679 0.62036 0.648 0.000 0.000 0.352
#> SRR1437576 2 0.4643 0.68142 0.000 0.656 0.000 0.344
#> SRR814407 1 0.0188 0.81894 0.996 0.000 0.000 0.004
#> SRR1332403 2 0.4866 0.63726 0.000 0.596 0.000 0.404
#> SRR1099598 2 0.0895 0.51837 0.004 0.976 0.000 0.020
#> SRR1327723 2 0.4730 0.67015 0.000 0.636 0.000 0.364
#> SRR1392525 2 0.5284 0.29124 0.000 0.616 0.368 0.016
#> SRR1320536 1 0.1940 0.81220 0.924 0.000 0.000 0.076
#> SRR1083824 4 0.4955 -0.27482 0.000 0.444 0.000 0.556
#> SRR1351390 1 0.3907 0.78849 0.836 0.120 0.000 0.044
#> SRR1309141 2 0.6716 0.53893 0.000 0.504 0.092 0.404
#> SRR1452803 4 0.4406 0.13843 0.000 0.300 0.000 0.700
#> SRR811631 2 0.3837 0.67269 0.000 0.776 0.000 0.224
#> SRR1485563 2 0.0927 0.52863 0.008 0.976 0.000 0.016
#> SRR1311531 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1353076 2 0.3024 0.63856 0.000 0.852 0.000 0.148
#> SRR1480831 2 0.1474 0.58052 0.000 0.948 0.000 0.052
#> SRR1083892 4 0.4776 -0.21763 0.376 0.000 0.000 0.624
#> SRR809873 1 0.3427 0.77807 0.860 0.112 0.000 0.028
#> SRR1341854 2 0.4776 0.66297 0.000 0.624 0.000 0.376
#> SRR1399335 4 0.4477 0.11031 0.000 0.312 0.000 0.688
#> SRR1464209 4 0.4916 -0.30524 0.424 0.000 0.000 0.576
#> SRR1389886 2 0.4817 0.65137 0.000 0.612 0.000 0.388
#> SRR1400730 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1448008 2 0.2149 0.60278 0.000 0.912 0.000 0.088
#> SRR1087606 4 0.4925 -0.31368 0.428 0.000 0.000 0.572
#> SRR1445111 1 0.1118 0.81930 0.964 0.000 0.000 0.036
#> SRR816865 2 0.4843 0.63266 0.000 0.604 0.000 0.396
#> SRR1323360 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.95047 0.000 0.000 1.000 0.000
#> SRR1480329 2 0.2408 0.57376 0.000 0.896 0.000 0.104
#> SRR1403322 1 0.4741 0.71519 0.744 0.228 0.000 0.028
#> SRR1093625 1 0.0817 0.81996 0.976 0.000 0.000 0.024
#> SRR1479977 2 0.4804 0.65378 0.000 0.616 0.000 0.384
#> SRR1082035 1 0.4996 0.42797 0.516 0.000 0.000 0.484
#> SRR1393046 2 0.4761 0.66410 0.000 0.628 0.000 0.372
#> SRR1466663 4 0.5119 -0.31692 0.004 0.440 0.000 0.556
#> SRR1384456 1 0.1867 0.81305 0.928 0.000 0.000 0.072
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.2677 0.6979 0.000 0.872 0.000 0.112 0.016
#> SRR808862 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1500382 2 0.1668 0.7336 0.000 0.940 0.000 0.032 0.028
#> SRR1322683 2 0.3752 0.5958 0.292 0.708 0.000 0.000 0.000
#> SRR1329811 5 0.0609 0.6601 0.000 0.020 0.000 0.000 0.980
#> SRR1087297 2 0.3164 0.7043 0.000 0.852 0.000 0.044 0.104
#> SRR1072626 2 0.4317 0.6565 0.160 0.764 0.000 0.076 0.000
#> SRR1407428 1 0.5339 0.6799 0.672 0.000 0.000 0.176 0.152
#> SRR1321029 2 0.1484 0.7384 0.000 0.944 0.000 0.008 0.048
#> SRR1500282 5 0.6040 -0.2338 0.372 0.000 0.000 0.124 0.504
#> SRR1100496 3 0.3857 0.5414 0.000 0.000 0.688 0.312 0.000
#> SRR1308778 2 0.5983 0.3250 0.000 0.588 0.000 0.212 0.200
#> SRR1445304 2 0.4384 0.5317 0.000 0.728 0.000 0.228 0.044
#> SRR1099378 5 0.6018 0.2448 0.008 0.112 0.000 0.312 0.568
#> SRR1347412 1 0.6160 0.4669 0.508 0.000 0.016 0.088 0.388
#> SRR1099694 2 0.6211 0.2562 0.000 0.544 0.000 0.192 0.264
#> SRR1088365 4 0.3177 0.8164 0.000 0.208 0.000 0.792 0.000
#> SRR1325752 4 0.2230 0.7817 0.000 0.116 0.000 0.884 0.000
#> SRR1416713 2 0.3639 0.6796 0.000 0.824 0.000 0.100 0.076
#> SRR1074474 1 0.5973 0.6241 0.580 0.000 0.000 0.164 0.256
#> SRR1469369 2 0.6121 0.2988 0.148 0.528 0.324 0.000 0.000
#> SRR1400507 2 0.2488 0.7126 0.124 0.872 0.000 0.004 0.000
#> SRR1378179 4 0.4161 0.7651 0.000 0.280 0.000 0.704 0.016
#> SRR1377905 2 0.4657 0.5935 0.000 0.740 0.000 0.152 0.108
#> SRR1089479 1 0.5608 0.6692 0.640 0.000 0.000 0.172 0.188
#> SRR1073365 2 0.3318 0.6355 0.000 0.808 0.000 0.180 0.012
#> SRR1500306 1 0.1205 0.6035 0.956 0.040 0.000 0.000 0.004
#> SRR1101566 2 0.3837 0.5788 0.308 0.692 0.000 0.000 0.000
#> SRR1350503 3 0.4294 -0.0158 0.000 0.468 0.532 0.000 0.000
#> SRR1446007 3 0.0290 0.9225 0.000 0.008 0.992 0.000 0.000
#> SRR1102875 2 0.4430 -0.1370 0.000 0.540 0.000 0.456 0.004
#> SRR1380293 5 0.4551 0.2897 0.000 0.368 0.000 0.016 0.616
#> SRR1331198 2 0.3690 0.6463 0.000 0.764 0.000 0.012 0.224
#> SRR1092686 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 4 0.2852 0.8172 0.000 0.172 0.000 0.828 0.000
#> SRR1341650 4 0.1908 0.7606 0.000 0.092 0.000 0.908 0.000
#> SRR1357276 2 0.3462 0.6715 0.000 0.792 0.000 0.012 0.196
#> SRR1498374 2 0.0771 0.7393 0.020 0.976 0.000 0.000 0.004
#> SRR1093721 2 0.1270 0.7351 0.052 0.948 0.000 0.000 0.000
#> SRR1464660 5 0.0404 0.6626 0.000 0.012 0.000 0.000 0.988
#> SRR1402051 2 0.4278 0.3657 0.452 0.548 0.000 0.000 0.000
#> SRR1488734 2 0.3438 0.6439 0.000 0.808 0.000 0.172 0.020
#> SRR1082616 4 0.4419 0.3100 0.004 0.008 0.344 0.644 0.000
#> SRR1099427 2 0.3661 0.6156 0.276 0.724 0.000 0.000 0.000
#> SRR1453093 2 0.4182 0.4572 0.400 0.600 0.000 0.000 0.000
#> SRR1357064 5 0.0451 0.6621 0.008 0.004 0.000 0.000 0.988
#> SRR811237 4 0.3074 0.8178 0.000 0.196 0.000 0.804 0.000
#> SRR1100848 2 0.1041 0.7351 0.000 0.964 0.000 0.032 0.004
#> SRR1346755 2 0.2843 0.7012 0.144 0.848 0.000 0.008 0.000
#> SRR1472529 2 0.1341 0.7342 0.056 0.944 0.000 0.000 0.000
#> SRR1398905 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1082733 2 0.2929 0.6694 0.000 0.840 0.000 0.152 0.008
#> SRR1308035 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.2473 0.7233 0.000 0.896 0.000 0.032 0.072
#> SRR1455825 2 0.1908 0.7235 0.092 0.908 0.000 0.000 0.000
#> SRR1389300 2 0.0566 0.7381 0.004 0.984 0.000 0.012 0.000
#> SRR812246 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 4 0.3177 0.8164 0.000 0.208 0.000 0.792 0.000
#> SRR1415567 1 0.5756 0.6599 0.620 0.000 0.000 0.176 0.204
#> SRR1331900 2 0.0955 0.7381 0.028 0.968 0.000 0.004 0.000
#> SRR1452099 4 0.2233 0.7337 0.016 0.080 0.000 0.904 0.000
#> SRR1352346 5 0.3177 0.5289 0.000 0.208 0.000 0.000 0.792
#> SRR1364034 4 0.3521 0.8062 0.000 0.232 0.000 0.764 0.004
#> SRR1086046 1 0.3395 0.3951 0.764 0.236 0.000 0.000 0.000
#> SRR1407226 5 0.6588 -0.1129 0.208 0.000 0.000 0.396 0.396
#> SRR1319363 4 0.2660 0.4119 0.128 0.000 0.000 0.864 0.008
#> SRR1446961 2 0.4109 0.5587 0.000 0.700 0.288 0.000 0.012
#> SRR1486650 5 0.5933 -0.3949 0.448 0.000 0.000 0.104 0.448
#> SRR1470152 5 0.0579 0.6626 0.008 0.008 0.000 0.000 0.984
#> SRR1454785 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1092329 2 0.1568 0.7378 0.036 0.944 0.000 0.020 0.000
#> SRR1091476 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 2 0.3837 0.5788 0.308 0.692 0.000 0.000 0.000
#> SRR1366873 2 0.3003 0.6789 0.188 0.812 0.000 0.000 0.000
#> SRR1398114 4 0.3741 0.7866 0.000 0.264 0.000 0.732 0.004
#> SRR1089950 1 0.4574 0.3205 0.576 0.012 0.000 0.000 0.412
#> SRR1433272 4 0.4793 0.7811 0.000 0.232 0.000 0.700 0.068
#> SRR1075314 1 0.1704 0.5791 0.928 0.068 0.000 0.004 0.000
#> SRR1085590 3 0.5680 0.3325 0.000 0.148 0.624 0.228 0.000
#> SRR1100752 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 2 0.3461 0.5856 0.000 0.772 0.000 0.224 0.004
#> SRR1333263 4 0.3093 0.8167 0.000 0.168 0.008 0.824 0.000
#> SRR1310231 2 0.2795 0.7010 0.000 0.872 0.000 0.100 0.028
#> SRR1094144 4 0.2813 0.8164 0.000 0.168 0.000 0.832 0.000
#> SRR1092160 5 0.5605 0.0995 0.000 0.404 0.000 0.076 0.520
#> SRR1320300 2 0.1522 0.7361 0.044 0.944 0.000 0.012 0.000
#> SRR1322747 2 0.3257 0.6968 0.000 0.856 0.016 0.104 0.024
#> SRR1432719 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 4 0.2813 0.8164 0.000 0.168 0.000 0.832 0.000
#> SRR1087511 2 0.4182 0.4587 0.400 0.600 0.000 0.000 0.000
#> SRR1470336 1 0.1106 0.6172 0.964 0.024 0.000 0.000 0.012
#> SRR1322536 1 0.1732 0.5693 0.920 0.080 0.000 0.000 0.000
#> SRR1100824 5 0.5361 0.3423 0.144 0.000 0.000 0.188 0.668
#> SRR1085951 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1322046 2 0.3700 0.5498 0.000 0.752 0.000 0.240 0.008
#> SRR1316420 5 0.2179 0.5928 0.100 0.000 0.000 0.004 0.896
#> SRR1070913 2 0.2891 0.6853 0.176 0.824 0.000 0.000 0.000
#> SRR1345806 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.6517 -0.3092 0.000 0.416 0.000 0.392 0.192
#> SRR1337666 2 0.4118 0.5036 0.000 0.660 0.000 0.004 0.336
#> SRR1076823 1 0.4832 0.6811 0.712 0.000 0.000 0.200 0.088
#> SRR1093954 4 0.4088 0.6560 0.000 0.368 0.000 0.632 0.000
#> SRR1451921 1 0.4455 0.5244 0.704 0.036 0.000 0.260 0.000
#> SRR1491257 5 0.1300 0.6471 0.028 0.000 0.000 0.016 0.956
#> SRR1416979 4 0.4302 0.3148 0.000 0.480 0.000 0.520 0.000
#> SRR1419015 4 0.1831 0.5317 0.076 0.004 0.000 0.920 0.000
#> SRR817649 5 0.3861 0.4648 0.000 0.284 0.000 0.004 0.712
#> SRR1466376 2 0.2830 0.7090 0.000 0.876 0.000 0.080 0.044
#> SRR1392055 2 0.1281 0.7342 0.000 0.956 0.000 0.032 0.012
#> SRR1120913 2 0.3236 0.6628 0.000 0.828 0.000 0.152 0.020
#> SRR1120869 4 0.3242 0.8140 0.000 0.216 0.000 0.784 0.000
#> SRR1319419 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR818694 2 0.3999 0.5369 0.344 0.656 0.000 0.000 0.000
#> SRR1465653 5 0.0510 0.6617 0.000 0.016 0.000 0.000 0.984
#> SRR1475952 1 0.3543 0.6805 0.828 0.000 0.000 0.112 0.060
#> SRR1465040 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 4 0.4354 0.6324 0.000 0.368 0.000 0.624 0.008
#> SRR810129 4 0.4380 0.7348 0.000 0.304 0.000 0.676 0.020
#> SRR1400141 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 5 0.3825 0.4980 0.136 0.000 0.000 0.060 0.804
#> SRR1437576 2 0.1478 0.7271 0.000 0.936 0.000 0.064 0.000
#> SRR814407 1 0.5296 0.6816 0.676 0.000 0.000 0.180 0.144
#> SRR1332403 2 0.4632 -0.1305 0.000 0.540 0.000 0.448 0.012
#> SRR1099598 2 0.4135 0.5409 0.340 0.656 0.000 0.004 0.000
#> SRR1327723 2 0.1282 0.7321 0.000 0.952 0.000 0.044 0.004
#> SRR1392525 4 0.4022 0.7392 0.004 0.092 0.100 0.804 0.000
#> SRR1320536 1 0.6175 0.5203 0.508 0.000 0.000 0.148 0.344
#> SRR1083824 2 0.3375 0.6980 0.000 0.840 0.000 0.056 0.104
#> SRR1351390 1 0.3093 0.6209 0.824 0.008 0.000 0.000 0.168
#> SRR1309141 4 0.4358 0.7996 0.000 0.236 0.016 0.732 0.016
#> SRR1452803 2 0.5888 0.2402 0.000 0.580 0.000 0.280 0.140
#> SRR811631 2 0.2017 0.7278 0.080 0.912 0.000 0.008 0.000
#> SRR1485563 4 0.4676 0.7461 0.072 0.208 0.000 0.720 0.000
#> SRR1311531 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 2 0.2616 0.7263 0.036 0.888 0.000 0.076 0.000
#> SRR1480831 2 0.3953 0.6292 0.048 0.784 0.000 0.168 0.000
#> SRR1083892 5 0.0162 0.6633 0.000 0.000 0.000 0.004 0.996
#> SRR809873 4 0.2763 0.3896 0.148 0.000 0.000 0.848 0.004
#> SRR1341854 4 0.4252 0.6910 0.000 0.340 0.000 0.652 0.008
#> SRR1399335 4 0.6470 0.4705 0.000 0.348 0.000 0.460 0.192
#> SRR1464209 5 0.0865 0.6536 0.024 0.000 0.000 0.004 0.972
#> SRR1389886 2 0.3141 0.6645 0.000 0.832 0.000 0.152 0.016
#> SRR1400730 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1448008 2 0.2929 0.6892 0.180 0.820 0.000 0.000 0.000
#> SRR1087606 5 0.0992 0.6580 0.024 0.008 0.000 0.000 0.968
#> SRR1445111 1 0.5329 0.5727 0.596 0.000 0.000 0.068 0.336
#> SRR816865 4 0.2852 0.8172 0.000 0.172 0.000 0.828 0.000
#> SRR1323360 3 0.0000 0.9311 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.1043 0.8881 0.000 0.040 0.960 0.000 0.000
#> SRR1480329 2 0.3774 0.5893 0.296 0.704 0.000 0.000 0.000
#> SRR1403322 1 0.4040 0.6333 0.712 0.000 0.000 0.276 0.012
#> SRR1093625 1 0.5856 0.6487 0.604 0.000 0.000 0.172 0.224
#> SRR1479977 2 0.0404 0.7380 0.000 0.988 0.000 0.012 0.000
#> SRR1082035 5 0.4535 0.5063 0.124 0.016 0.000 0.084 0.776
#> SRR1393046 2 0.1638 0.7262 0.000 0.932 0.000 0.064 0.004
#> SRR1466663 4 0.4276 0.7919 0.000 0.244 0.000 0.724 0.032
#> SRR1384456 1 0.6163 0.5761 0.536 0.000 0.000 0.164 0.300
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0798 0.8828 0.004 0.976 0.000 0.012 0.004 0.004
#> SRR808862 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1500382 2 0.0653 0.8818 0.004 0.980 0.000 0.000 0.012 0.004
#> SRR1322683 2 0.1957 0.8308 0.000 0.888 0.000 0.000 0.000 0.112
#> SRR1329811 5 0.0622 0.8250 0.012 0.000 0.000 0.000 0.980 0.008
#> SRR1087297 2 0.0146 0.8833 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1072626 4 0.5860 0.3222 0.000 0.268 0.000 0.484 0.000 0.248
#> SRR1407428 1 0.0632 0.8894 0.976 0.000 0.000 0.000 0.000 0.024
#> SRR1321029 2 0.0964 0.8796 0.004 0.968 0.000 0.000 0.016 0.012
#> SRR1500282 1 0.1588 0.8770 0.924 0.000 0.000 0.000 0.072 0.004
#> SRR1100496 3 0.3862 0.0958 0.000 0.000 0.524 0.476 0.000 0.000
#> SRR1308778 2 0.2272 0.8460 0.004 0.900 0.000 0.040 0.056 0.000
#> SRR1445304 2 0.1706 0.8704 0.004 0.936 0.000 0.032 0.024 0.004
#> SRR1099378 5 0.3464 0.4996 0.000 0.000 0.000 0.312 0.688 0.000
#> SRR1347412 1 0.0405 0.8963 0.988 0.000 0.000 0.000 0.008 0.004
#> SRR1099694 5 0.5990 0.2266 0.000 0.308 0.000 0.220 0.468 0.004
#> SRR1088365 4 0.0937 0.8007 0.000 0.040 0.000 0.960 0.000 0.000
#> SRR1325752 4 0.3058 0.7427 0.124 0.024 0.000 0.840 0.012 0.000
#> SRR1416713 2 0.0820 0.8816 0.000 0.972 0.000 0.012 0.016 0.000
#> SRR1074474 1 0.0363 0.8932 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1469369 3 0.4887 0.3912 0.000 0.280 0.624 0.000 0.000 0.096
#> SRR1400507 2 0.0937 0.8765 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1378179 4 0.2831 0.7520 0.000 0.136 0.000 0.840 0.024 0.000
#> SRR1377905 2 0.1864 0.8624 0.004 0.924 0.000 0.032 0.040 0.000
#> SRR1089479 1 0.0790 0.8861 0.968 0.000 0.000 0.000 0.000 0.032
#> SRR1073365 2 0.1471 0.8614 0.000 0.932 0.000 0.064 0.000 0.004
#> SRR1500306 6 0.1219 0.7802 0.048 0.000 0.000 0.004 0.000 0.948
#> SRR1101566 2 0.3864 0.5018 0.004 0.648 0.000 0.000 0.004 0.344
#> SRR1350503 2 0.2969 0.7029 0.000 0.776 0.224 0.000 0.000 0.000
#> SRR1446007 3 0.0547 0.9266 0.000 0.020 0.980 0.000 0.000 0.000
#> SRR1102875 4 0.3841 0.4608 0.000 0.380 0.000 0.616 0.000 0.004
#> SRR1380293 5 0.0748 0.8147 0.004 0.016 0.000 0.004 0.976 0.000
#> SRR1331198 2 0.2263 0.8328 0.000 0.884 0.000 0.000 0.100 0.016
#> SRR1092686 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.0405 0.7988 0.000 0.008 0.000 0.988 0.004 0.000
#> SRR1341650 4 0.0508 0.8005 0.004 0.012 0.000 0.984 0.000 0.000
#> SRR1357276 2 0.0922 0.8794 0.004 0.968 0.000 0.000 0.024 0.004
#> SRR1498374 2 0.0951 0.8799 0.004 0.968 0.000 0.000 0.008 0.020
#> SRR1093721 2 0.3607 0.5009 0.000 0.652 0.000 0.000 0.000 0.348
#> SRR1464660 5 0.0622 0.8250 0.012 0.000 0.000 0.000 0.980 0.008
#> SRR1402051 6 0.2039 0.7716 0.016 0.072 0.000 0.004 0.000 0.908
#> SRR1488734 2 0.0547 0.8813 0.000 0.980 0.000 0.020 0.000 0.000
#> SRR1082616 4 0.2308 0.7499 0.000 0.000 0.040 0.892 0.000 0.068
#> SRR1099427 2 0.1327 0.8653 0.000 0.936 0.000 0.000 0.000 0.064
#> SRR1453093 6 0.1951 0.7615 0.000 0.076 0.000 0.016 0.000 0.908
#> SRR1357064 5 0.2378 0.6917 0.152 0.000 0.000 0.000 0.848 0.000
#> SRR811237 4 0.0458 0.8014 0.000 0.016 0.000 0.984 0.000 0.000
#> SRR1100848 5 0.7387 0.0717 0.000 0.284 0.000 0.120 0.352 0.244
#> SRR1346755 2 0.2340 0.8014 0.000 0.852 0.000 0.000 0.000 0.148
#> SRR1472529 2 0.0713 0.8803 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1398905 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1082733 2 0.1082 0.8748 0.000 0.956 0.000 0.040 0.000 0.004
#> SRR1308035 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.0291 0.8838 0.004 0.992 0.000 0.004 0.000 0.000
#> SRR1455825 2 0.0547 0.8819 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1389300 2 0.0458 0.8822 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR812246 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.0260 0.7993 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1415567 1 0.0458 0.8922 0.984 0.000 0.000 0.000 0.000 0.016
#> SRR1331900 2 0.0260 0.8832 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1452099 4 0.0870 0.7960 0.004 0.012 0.000 0.972 0.000 0.012
#> SRR1352346 5 0.0767 0.8186 0.004 0.008 0.000 0.000 0.976 0.012
#> SRR1364034 4 0.1285 0.7983 0.000 0.052 0.000 0.944 0.004 0.000
#> SRR1086046 6 0.1565 0.7789 0.028 0.004 0.000 0.028 0.000 0.940
#> SRR1407226 1 0.2560 0.8278 0.872 0.000 0.000 0.092 0.036 0.000
#> SRR1319363 4 0.1643 0.7670 0.068 0.000 0.000 0.924 0.000 0.008
#> SRR1446961 2 0.1075 0.8704 0.000 0.952 0.048 0.000 0.000 0.000
#> SRR1486650 1 0.0713 0.8938 0.972 0.000 0.000 0.000 0.028 0.000
#> SRR1470152 5 0.1296 0.8153 0.012 0.000 0.000 0.004 0.952 0.032
#> SRR1454785 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 2 0.1141 0.8716 0.000 0.948 0.000 0.000 0.000 0.052
#> SRR1091476 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 2 0.3198 0.6572 0.000 0.740 0.000 0.000 0.000 0.260
#> SRR1366873 2 0.0547 0.8811 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1398114 4 0.3245 0.6911 0.000 0.228 0.000 0.764 0.008 0.000
#> SRR1089950 6 0.4844 0.1482 0.056 0.000 0.000 0.000 0.440 0.504
#> SRR1433272 4 0.2669 0.7136 0.000 0.008 0.000 0.836 0.156 0.000
#> SRR1075314 6 0.1682 0.7802 0.052 0.000 0.000 0.020 0.000 0.928
#> SRR1085590 4 0.6054 0.3169 0.000 0.232 0.316 0.448 0.000 0.004
#> SRR1100752 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 4 0.3830 0.4664 0.000 0.376 0.000 0.620 0.000 0.004
#> SRR1333263 4 0.0458 0.8011 0.000 0.016 0.000 0.984 0.000 0.000
#> SRR1310231 2 0.0363 0.8827 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1094144 4 0.0260 0.7993 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1092160 5 0.3058 0.6900 0.000 0.124 0.000 0.024 0.840 0.012
#> SRR1320300 2 0.0363 0.8828 0.000 0.988 0.000 0.000 0.000 0.012
#> SRR1322747 2 0.0363 0.8827 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1432719 3 0.0146 0.9441 0.000 0.000 0.996 0.004 0.000 0.000
#> SRR1100728 4 0.0260 0.7993 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1087511 6 0.1219 0.7733 0.000 0.048 0.000 0.004 0.000 0.948
#> SRR1470336 6 0.1327 0.7775 0.064 0.000 0.000 0.000 0.000 0.936
#> SRR1322536 6 0.1500 0.7803 0.052 0.000 0.000 0.012 0.000 0.936
#> SRR1100824 1 0.5573 0.4052 0.536 0.000 0.000 0.176 0.288 0.000
#> SRR1085951 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1322046 2 0.3499 0.6105 0.000 0.728 0.000 0.264 0.004 0.004
#> SRR1316420 1 0.3620 0.5410 0.648 0.000 0.000 0.000 0.352 0.000
#> SRR1070913 2 0.1387 0.8633 0.000 0.932 0.000 0.000 0.000 0.068
#> SRR1345806 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.4631 0.6354 0.000 0.692 0.000 0.140 0.168 0.000
#> SRR1337666 2 0.1765 0.8409 0.000 0.904 0.000 0.000 0.096 0.000
#> SRR1076823 1 0.1265 0.8782 0.948 0.000 0.000 0.008 0.000 0.044
#> SRR1093954 4 0.3714 0.5590 0.000 0.340 0.000 0.656 0.004 0.000
#> SRR1451921 6 0.3283 0.7023 0.036 0.000 0.000 0.160 0.000 0.804
#> SRR1491257 1 0.1444 0.8776 0.928 0.000 0.000 0.000 0.072 0.000
#> SRR1416979 4 0.3012 0.6989 0.000 0.196 0.000 0.796 0.000 0.008
#> SRR1419015 4 0.3349 0.5662 0.244 0.000 0.000 0.748 0.000 0.008
#> SRR817649 5 0.0260 0.8248 0.008 0.000 0.000 0.000 0.992 0.000
#> SRR1466376 2 0.0363 0.8827 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1392055 2 0.0551 0.8826 0.004 0.984 0.000 0.000 0.008 0.004
#> SRR1120913 2 0.0508 0.8828 0.000 0.984 0.000 0.012 0.000 0.004
#> SRR1120869 4 0.1010 0.8008 0.000 0.036 0.000 0.960 0.004 0.000
#> SRR1319419 3 0.0260 0.9400 0.000 0.008 0.992 0.000 0.000 0.000
#> SRR816495 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR818694 6 0.2595 0.6815 0.000 0.160 0.000 0.004 0.000 0.836
#> SRR1465653 5 0.0520 0.8252 0.008 0.000 0.000 0.000 0.984 0.008
#> SRR1475952 6 0.3789 0.3268 0.416 0.000 0.000 0.000 0.000 0.584
#> SRR1465040 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 2 0.4356 0.0856 0.004 0.548 0.000 0.432 0.016 0.000
#> SRR810129 4 0.3835 0.6071 0.000 0.300 0.000 0.684 0.016 0.000
#> SRR1400141 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 1 0.1267 0.8830 0.940 0.000 0.000 0.000 0.060 0.000
#> SRR1437576 2 0.0260 0.8832 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR814407 6 0.3867 0.0781 0.488 0.000 0.000 0.000 0.000 0.512
#> SRR1332403 2 0.3371 0.5601 0.000 0.708 0.000 0.292 0.000 0.000
#> SRR1099598 6 0.2121 0.7461 0.000 0.096 0.000 0.012 0.000 0.892
#> SRR1327723 2 0.0717 0.8834 0.000 0.976 0.000 0.008 0.000 0.016
#> SRR1392525 4 0.1078 0.7949 0.000 0.012 0.008 0.964 0.000 0.016
#> SRR1320536 1 0.0508 0.8967 0.984 0.000 0.000 0.000 0.012 0.004
#> SRR1083824 2 0.0508 0.8828 0.000 0.984 0.000 0.012 0.004 0.000
#> SRR1351390 6 0.3206 0.7190 0.068 0.000 0.000 0.000 0.104 0.828
#> SRR1309141 2 0.5966 -0.1063 0.000 0.452 0.120 0.404 0.024 0.000
#> SRR1452803 2 0.2886 0.8139 0.004 0.860 0.000 0.072 0.064 0.000
#> SRR811631 2 0.0547 0.8819 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1485563 4 0.2230 0.7798 0.000 0.084 0.000 0.892 0.000 0.024
#> SRR1311531 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 2 0.1807 0.8630 0.000 0.920 0.000 0.060 0.000 0.020
#> SRR1480831 2 0.4648 0.3760 0.000 0.604 0.000 0.340 0.000 0.056
#> SRR1083892 5 0.0508 0.8245 0.012 0.004 0.000 0.000 0.984 0.000
#> SRR809873 4 0.0891 0.7852 0.024 0.000 0.000 0.968 0.000 0.008
#> SRR1341854 4 0.4058 0.4464 0.000 0.372 0.000 0.616 0.008 0.004
#> SRR1399335 2 0.5996 -0.1175 0.004 0.432 0.000 0.364 0.200 0.000
#> SRR1464209 5 0.1075 0.8105 0.048 0.000 0.000 0.000 0.952 0.000
#> SRR1389886 2 0.0363 0.8827 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1400730 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1448008 2 0.2941 0.7113 0.000 0.780 0.000 0.000 0.000 0.220
#> SRR1087606 5 0.0520 0.8252 0.008 0.000 0.000 0.000 0.984 0.008
#> SRR1445111 1 0.2611 0.8404 0.864 0.000 0.000 0.008 0.012 0.116
#> SRR816865 4 0.0260 0.7993 0.000 0.008 0.000 0.992 0.000 0.000
#> SRR1323360 3 0.0000 0.9479 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.0865 0.9063 0.000 0.036 0.964 0.000 0.000 0.000
#> SRR1480329 6 0.4227 0.3930 0.004 0.344 0.000 0.000 0.020 0.632
#> SRR1403322 6 0.5172 0.4917 0.268 0.000 0.000 0.132 0.000 0.600
#> SRR1093625 1 0.0363 0.8932 0.988 0.000 0.000 0.000 0.000 0.012
#> SRR1479977 2 0.0260 0.8829 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1082035 1 0.3560 0.7498 0.772 0.012 0.000 0.004 0.204 0.008
#> SRR1393046 2 0.0405 0.8833 0.000 0.988 0.000 0.008 0.000 0.004
#> SRR1466663 4 0.5634 0.6006 0.176 0.124 0.000 0.644 0.056 0.000
#> SRR1384456 1 0.0363 0.8963 0.988 0.000 0.000 0.000 0.012 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "hclust"]
# you can also extract it by
# res = res_list["CV:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 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 0.896 0.891 0.959 0.253 0.751 0.751
#> 3 3 0.594 0.811 0.891 0.445 0.898 0.865
#> 4 4 0.558 0.394 0.726 0.223 0.680 0.546
#> 5 5 0.532 0.676 0.803 0.153 0.783 0.618
#> 6 6 0.564 0.751 0.824 0.182 0.920 0.835
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
#> SRR810713 2 0.0000 0.9681 0.000 1.000
#> SRR808862 1 0.0000 0.8637 1.000 0.000
#> SRR1500382 2 0.0000 0.9681 0.000 1.000
#> SRR1322683 2 0.0000 0.9681 0.000 1.000
#> SRR1329811 2 0.0000 0.9681 0.000 1.000
#> SRR1087297 2 0.0000 0.9681 0.000 1.000
#> SRR1072626 2 0.0000 0.9681 0.000 1.000
#> SRR1407428 2 0.0000 0.9681 0.000 1.000
#> SRR1321029 2 0.0000 0.9681 0.000 1.000
#> SRR1500282 2 0.0000 0.9681 0.000 1.000
#> SRR1100496 1 0.4939 0.8408 0.892 0.108
#> SRR1308778 2 0.0000 0.9681 0.000 1.000
#> SRR1445304 2 0.0000 0.9681 0.000 1.000
#> SRR1099378 2 0.0000 0.9681 0.000 1.000
#> SRR1347412 2 0.2043 0.9343 0.032 0.968
#> SRR1099694 2 0.0000 0.9681 0.000 1.000
#> SRR1088365 2 0.0000 0.9681 0.000 1.000
#> SRR1325752 2 0.0000 0.9681 0.000 1.000
#> SRR1416713 2 0.0000 0.9681 0.000 1.000
#> SRR1074474 2 0.0000 0.9681 0.000 1.000
#> SRR1469369 2 0.9996 -0.1595 0.488 0.512
#> SRR1400507 2 0.0000 0.9681 0.000 1.000
#> SRR1378179 2 0.0000 0.9681 0.000 1.000
#> SRR1377905 2 0.0000 0.9681 0.000 1.000
#> SRR1089479 2 0.0000 0.9681 0.000 1.000
#> SRR1073365 2 0.0000 0.9681 0.000 1.000
#> SRR1500306 2 0.0000 0.9681 0.000 1.000
#> SRR1101566 2 0.0000 0.9681 0.000 1.000
#> SRR1350503 2 0.9909 0.0218 0.444 0.556
#> SRR1446007 1 0.4022 0.8551 0.920 0.080
#> SRR1102875 2 0.0000 0.9681 0.000 1.000
#> SRR1380293 2 0.0000 0.9681 0.000 1.000
#> SRR1331198 2 0.0000 0.9681 0.000 1.000
#> SRR1092686 1 0.5178 0.8347 0.884 0.116
#> SRR1069421 2 0.0000 0.9681 0.000 1.000
#> SRR1341650 2 0.0000 0.9681 0.000 1.000
#> SRR1357276 2 0.0000 0.9681 0.000 1.000
#> SRR1498374 2 0.0000 0.9681 0.000 1.000
#> SRR1093721 2 0.0000 0.9681 0.000 1.000
#> SRR1464660 2 0.0000 0.9681 0.000 1.000
#> SRR1402051 2 0.0000 0.9681 0.000 1.000
#> SRR1488734 2 0.0000 0.9681 0.000 1.000
#> SRR1082616 2 0.9977 -0.0971 0.472 0.528
#> SRR1099427 2 0.0376 0.9641 0.004 0.996
#> SRR1453093 2 0.0000 0.9681 0.000 1.000
#> SRR1357064 2 0.0000 0.9681 0.000 1.000
#> SRR811237 2 0.0000 0.9681 0.000 1.000
#> SRR1100848 2 0.0000 0.9681 0.000 1.000
#> SRR1346755 2 0.0000 0.9681 0.000 1.000
#> SRR1472529 2 0.0000 0.9681 0.000 1.000
#> SRR1398905 1 0.0000 0.8637 1.000 0.000
#> SRR1082733 2 0.0000 0.9681 0.000 1.000
#> SRR1308035 1 0.0000 0.8637 1.000 0.000
#> SRR1466445 1 0.4562 0.8484 0.904 0.096
#> SRR1359080 2 0.0000 0.9681 0.000 1.000
#> SRR1455825 2 0.0000 0.9681 0.000 1.000
#> SRR1389300 2 0.0000 0.9681 0.000 1.000
#> SRR812246 1 0.0000 0.8637 1.000 0.000
#> SRR1076632 2 0.0000 0.9681 0.000 1.000
#> SRR1415567 2 0.0000 0.9681 0.000 1.000
#> SRR1331900 2 0.0000 0.9681 0.000 1.000
#> SRR1452099 2 0.0000 0.9681 0.000 1.000
#> SRR1352346 2 0.0000 0.9681 0.000 1.000
#> SRR1364034 2 0.0000 0.9681 0.000 1.000
#> SRR1086046 2 0.0000 0.9681 0.000 1.000
#> SRR1407226 2 0.0000 0.9681 0.000 1.000
#> SRR1319363 2 0.0000 0.9681 0.000 1.000
#> SRR1446961 1 1.0000 0.1782 0.504 0.496
#> SRR1486650 2 0.0000 0.9681 0.000 1.000
#> SRR1470152 2 0.0000 0.9681 0.000 1.000
#> SRR1454785 1 0.0000 0.8637 1.000 0.000
#> SRR1092329 2 0.0000 0.9681 0.000 1.000
#> SRR1091476 1 0.0000 0.8637 1.000 0.000
#> SRR1073775 2 0.0000 0.9681 0.000 1.000
#> SRR1366873 2 0.0000 0.9681 0.000 1.000
#> SRR1398114 2 0.0000 0.9681 0.000 1.000
#> SRR1089950 2 0.0000 0.9681 0.000 1.000
#> SRR1433272 2 0.0000 0.9681 0.000 1.000
#> SRR1075314 2 0.0000 0.9681 0.000 1.000
#> SRR1085590 2 0.9795 0.1351 0.416 0.584
#> SRR1100752 1 0.0000 0.8637 1.000 0.000
#> SRR1391494 2 0.0000 0.9681 0.000 1.000
#> SRR1333263 2 0.9087 0.4248 0.324 0.676
#> SRR1310231 2 0.0000 0.9681 0.000 1.000
#> SRR1094144 2 0.0000 0.9681 0.000 1.000
#> SRR1092160 2 0.0000 0.9681 0.000 1.000
#> SRR1320300 2 0.0000 0.9681 0.000 1.000
#> SRR1322747 2 0.9754 0.1649 0.408 0.592
#> SRR1432719 1 0.9608 0.4824 0.616 0.384
#> SRR1100728 2 0.0000 0.9681 0.000 1.000
#> SRR1087511 2 0.0000 0.9681 0.000 1.000
#> SRR1470336 2 0.0000 0.9681 0.000 1.000
#> SRR1322536 2 0.0000 0.9681 0.000 1.000
#> SRR1100824 2 0.0000 0.9681 0.000 1.000
#> SRR1085951 1 0.0000 0.8637 1.000 0.000
#> SRR1322046 2 0.0000 0.9681 0.000 1.000
#> SRR1316420 2 0.0000 0.9681 0.000 1.000
#> SRR1070913 2 0.0000 0.9681 0.000 1.000
#> SRR1345806 1 0.4562 0.8484 0.904 0.096
#> SRR1313872 2 0.0000 0.9681 0.000 1.000
#> SRR1337666 2 0.0000 0.9681 0.000 1.000
#> SRR1076823 2 0.0000 0.9681 0.000 1.000
#> SRR1093954 2 0.0000 0.9681 0.000 1.000
#> SRR1451921 2 0.0000 0.9681 0.000 1.000
#> SRR1491257 2 0.0000 0.9681 0.000 1.000
#> SRR1416979 2 0.0000 0.9681 0.000 1.000
#> SRR1419015 2 0.0000 0.9681 0.000 1.000
#> SRR817649 2 0.0000 0.9681 0.000 1.000
#> SRR1466376 2 0.0000 0.9681 0.000 1.000
#> SRR1392055 2 0.0000 0.9681 0.000 1.000
#> SRR1120913 2 0.0000 0.9681 0.000 1.000
#> SRR1120869 2 0.0000 0.9681 0.000 1.000
#> SRR1319419 1 0.9896 0.3499 0.560 0.440
#> SRR816495 1 0.4022 0.8551 0.920 0.080
#> SRR818694 2 0.0000 0.9681 0.000 1.000
#> SRR1465653 2 0.0000 0.9681 0.000 1.000
#> SRR1475952 2 0.0000 0.9681 0.000 1.000
#> SRR1465040 1 0.0000 0.8637 1.000 0.000
#> SRR1088461 2 0.0000 0.9681 0.000 1.000
#> SRR810129 2 0.0000 0.9681 0.000 1.000
#> SRR1400141 1 0.9286 0.5582 0.656 0.344
#> SRR1349585 2 0.0000 0.9681 0.000 1.000
#> SRR1437576 2 0.0000 0.9681 0.000 1.000
#> SRR814407 2 0.2043 0.9343 0.032 0.968
#> SRR1332403 2 0.0000 0.9681 0.000 1.000
#> SRR1099598 2 0.0000 0.9681 0.000 1.000
#> SRR1327723 2 0.0000 0.9681 0.000 1.000
#> SRR1392525 2 0.9393 0.3357 0.356 0.644
#> SRR1320536 2 0.0000 0.9681 0.000 1.000
#> SRR1083824 2 0.8267 0.5776 0.260 0.740
#> SRR1351390 2 0.0000 0.9681 0.000 1.000
#> SRR1309141 2 0.9522 0.2874 0.372 0.628
#> SRR1452803 2 0.0000 0.9681 0.000 1.000
#> SRR811631 2 0.2236 0.9298 0.036 0.964
#> SRR1485563 2 0.0000 0.9681 0.000 1.000
#> SRR1311531 1 0.4022 0.8551 0.920 0.080
#> SRR1353076 2 0.0000 0.9681 0.000 1.000
#> SRR1480831 2 0.0000 0.9681 0.000 1.000
#> SRR1083892 2 0.0000 0.9681 0.000 1.000
#> SRR809873 2 0.0000 0.9681 0.000 1.000
#> SRR1341854 2 0.0000 0.9681 0.000 1.000
#> SRR1399335 2 0.0000 0.9681 0.000 1.000
#> SRR1464209 2 0.0000 0.9681 0.000 1.000
#> SRR1389886 2 0.0000 0.9681 0.000 1.000
#> SRR1400730 1 0.0000 0.8637 1.000 0.000
#> SRR1448008 2 0.0000 0.9681 0.000 1.000
#> SRR1087606 2 0.0000 0.9681 0.000 1.000
#> SRR1445111 2 0.0000 0.9681 0.000 1.000
#> SRR816865 2 0.0000 0.9681 0.000 1.000
#> SRR1323360 1 0.0000 0.8637 1.000 0.000
#> SRR1417364 1 1.0000 0.1782 0.504 0.496
#> SRR1480329 2 0.0000 0.9681 0.000 1.000
#> SRR1403322 2 0.0000 0.9681 0.000 1.000
#> SRR1093625 2 0.0000 0.9681 0.000 1.000
#> SRR1479977 2 0.0000 0.9681 0.000 1.000
#> SRR1082035 2 0.0000 0.9681 0.000 1.000
#> SRR1393046 2 0.0000 0.9681 0.000 1.000
#> SRR1466663 2 0.0000 0.9681 0.000 1.000
#> SRR1384456 2 0.0000 0.9681 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.916 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1322683 2 0.0747 0.909 0.016 0.984 0.000
#> SRR1329811 2 0.3340 0.813 0.120 0.880 0.000
#> SRR1087297 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1072626 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1407428 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1321029 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1500282 2 0.5291 0.575 0.268 0.732 0.000
#> SRR1100496 3 0.7557 0.615 0.264 0.080 0.656
#> SRR1308778 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1445304 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1099378 2 0.2066 0.878 0.060 0.940 0.000
#> SRR1347412 1 0.6302 0.203 0.520 0.480 0.000
#> SRR1099694 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1088365 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1325752 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1416713 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1074474 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1469369 1 0.9061 0.742 0.548 0.264 0.188
#> SRR1400507 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1377905 2 0.1964 0.873 0.056 0.944 0.000
#> SRR1089479 2 0.5138 0.616 0.252 0.748 0.000
#> SRR1073365 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1500306 2 0.4750 0.676 0.216 0.784 0.000
#> SRR1101566 2 0.0424 0.913 0.008 0.992 0.000
#> SRR1350503 1 0.8702 0.763 0.568 0.292 0.140
#> SRR1446007 3 0.7246 0.661 0.276 0.060 0.664
#> SRR1102875 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1092686 3 0.8054 0.524 0.340 0.080 0.580
#> SRR1069421 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1341650 2 0.1529 0.899 0.040 0.960 0.000
#> SRR1357276 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1498374 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1093721 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1464660 2 0.3340 0.813 0.120 0.880 0.000
#> SRR1402051 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1488734 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1082616 1 0.8950 0.753 0.556 0.272 0.172
#> SRR1099427 2 0.1964 0.874 0.056 0.944 0.000
#> SRR1453093 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1357064 2 0.3267 0.828 0.116 0.884 0.000
#> SRR811237 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1100848 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1346755 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1472529 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1398905 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1082733 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1308035 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1466445 3 0.7622 0.600 0.332 0.060 0.608
#> SRR1359080 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.916 0.000 1.000 0.000
#> SRR812246 3 0.5178 0.727 0.256 0.000 0.744
#> SRR1076632 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1415567 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1331900 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1452099 2 0.2356 0.867 0.072 0.928 0.000
#> SRR1352346 2 0.0892 0.907 0.020 0.980 0.000
#> SRR1364034 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1086046 2 0.0747 0.910 0.016 0.984 0.000
#> SRR1407226 2 0.1411 0.899 0.036 0.964 0.000
#> SRR1319363 2 0.1411 0.899 0.036 0.964 0.000
#> SRR1446961 1 0.8873 0.686 0.576 0.224 0.200
#> SRR1486650 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1470152 2 0.3340 0.813 0.120 0.880 0.000
#> SRR1454785 3 0.0237 0.816 0.004 0.000 0.996
#> SRR1092329 2 0.0747 0.909 0.016 0.984 0.000
#> SRR1091476 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1073775 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1089950 2 0.2165 0.877 0.064 0.936 0.000
#> SRR1433272 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1075314 2 0.4750 0.676 0.216 0.784 0.000
#> SRR1085590 1 0.8784 0.764 0.548 0.316 0.136
#> SRR1100752 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1391494 2 0.0592 0.911 0.012 0.988 0.000
#> SRR1333263 1 0.8561 0.672 0.484 0.420 0.096
#> SRR1310231 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1094144 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1092160 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1322747 1 0.8719 0.762 0.548 0.324 0.128
#> SRR1432719 1 0.9323 0.496 0.500 0.188 0.312
#> SRR1100728 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1087511 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1470336 2 0.4750 0.676 0.216 0.784 0.000
#> SRR1322536 2 0.4750 0.676 0.216 0.784 0.000
#> SRR1100824 2 0.5098 0.618 0.248 0.752 0.000
#> SRR1085951 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1316420 2 0.2959 0.844 0.100 0.900 0.000
#> SRR1070913 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1345806 3 0.7600 0.605 0.328 0.060 0.612
#> SRR1313872 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1337666 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1076823 2 0.1411 0.899 0.036 0.964 0.000
#> SRR1093954 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1451921 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1491257 2 0.3267 0.828 0.116 0.884 0.000
#> SRR1416979 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1419015 2 0.1860 0.885 0.052 0.948 0.000
#> SRR817649 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1466376 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1319419 1 0.9243 0.610 0.528 0.208 0.264
#> SRR816495 3 0.7213 0.664 0.272 0.060 0.668
#> SRR818694 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1465653 2 0.3267 0.818 0.116 0.884 0.000
#> SRR1475952 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1465040 3 0.0592 0.815 0.012 0.000 0.988
#> SRR1088461 2 0.0000 0.916 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1400141 1 0.9606 0.483 0.440 0.208 0.352
#> SRR1349585 2 0.3192 0.836 0.112 0.888 0.000
#> SRR1437576 2 0.2066 0.868 0.060 0.940 0.000
#> SRR814407 2 0.6309 -0.247 0.500 0.500 0.000
#> SRR1332403 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1099598 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1327723 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1392525 1 0.8526 0.724 0.524 0.376 0.100
#> SRR1320536 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1083824 2 0.6309 -0.515 0.496 0.504 0.000
#> SRR1351390 2 0.5098 0.620 0.248 0.752 0.000
#> SRR1309141 1 0.8410 0.738 0.544 0.360 0.096
#> SRR1452803 2 0.0000 0.916 0.000 1.000 0.000
#> SRR811631 2 0.4291 0.672 0.180 0.820 0.000
#> SRR1485563 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1311531 3 0.7112 0.672 0.260 0.060 0.680
#> SRR1353076 2 0.0237 0.915 0.004 0.996 0.000
#> SRR1480831 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1083892 2 0.3267 0.828 0.116 0.884 0.000
#> SRR809873 2 0.1289 0.902 0.032 0.968 0.000
#> SRR1341854 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1464209 2 0.3192 0.832 0.112 0.888 0.000
#> SRR1389886 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1400730 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1448008 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1087606 2 0.4346 0.729 0.184 0.816 0.000
#> SRR1445111 2 0.5138 0.616 0.252 0.748 0.000
#> SRR816865 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1323360 3 0.0000 0.816 0.000 0.000 1.000
#> SRR1417364 1 0.8873 0.686 0.576 0.224 0.200
#> SRR1480329 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1403322 2 0.1411 0.899 0.036 0.964 0.000
#> SRR1093625 2 0.5363 0.562 0.276 0.724 0.000
#> SRR1479977 2 0.0000 0.916 0.000 1.000 0.000
#> SRR1082035 2 0.1411 0.899 0.036 0.964 0.000
#> SRR1393046 2 0.1860 0.876 0.052 0.948 0.000
#> SRR1466663 2 0.0424 0.914 0.008 0.992 0.000
#> SRR1384456 2 0.5363 0.562 0.276 0.724 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR808862 3 0.0000 0.79555 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1322683 2 0.4972 0.67782 0.456 0.544 0.000 0.000
#> SRR1329811 2 0.7069 -0.05650 0.324 0.532 0.000 0.144
#> SRR1087297 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1072626 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1407428 1 0.0817 0.42764 0.976 0.024 0.000 0.000
#> SRR1321029 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1500282 4 0.7778 -0.08860 0.332 0.252 0.000 0.416
#> SRR1100496 3 0.6340 0.34118 0.000 0.064 0.528 0.408
#> SRR1308778 2 0.4994 0.69260 0.480 0.520 0.000 0.000
#> SRR1445304 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1099378 1 0.6969 -0.35773 0.448 0.440 0.000 0.112
#> SRR1347412 2 0.7558 -0.57098 0.360 0.444 0.000 0.196
#> SRR1099694 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1088365 2 0.4992 0.69952 0.476 0.524 0.000 0.000
#> SRR1325752 2 0.4994 0.69260 0.480 0.520 0.000 0.000
#> SRR1416713 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1074474 1 0.0707 0.42882 0.980 0.020 0.000 0.000
#> SRR1469369 4 0.7060 0.52952 0.000 0.376 0.128 0.496
#> SRR1400507 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1378179 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1377905 2 0.5028 0.52387 0.400 0.596 0.000 0.004
#> SRR1089479 1 0.4688 0.35023 0.792 0.128 0.000 0.080
#> SRR1073365 2 0.4992 0.69952 0.476 0.524 0.000 0.000
#> SRR1500306 1 0.7332 0.35757 0.480 0.164 0.000 0.356
#> SRR1101566 2 0.4981 0.69344 0.464 0.536 0.000 0.000
#> SRR1350503 4 0.6924 0.50736 0.000 0.428 0.108 0.464
#> SRR1446007 3 0.6120 0.37565 0.000 0.048 0.520 0.432
#> SRR1102875 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1380293 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1331198 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1092686 4 0.6380 -0.26536 0.000 0.064 0.436 0.500
#> SRR1069421 2 0.4999 0.66411 0.492 0.508 0.000 0.000
#> SRR1341650 1 0.5168 -0.53777 0.504 0.492 0.000 0.004
#> SRR1357276 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1498374 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1093721 2 0.4985 0.70089 0.468 0.532 0.000 0.000
#> SRR1464660 2 0.7069 -0.05650 0.324 0.532 0.000 0.144
#> SRR1402051 2 0.5161 0.67891 0.476 0.520 0.000 0.004
#> SRR1488734 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1082616 4 0.7049 0.52676 0.000 0.392 0.124 0.484
#> SRR1099427 2 0.5172 0.52498 0.404 0.588 0.000 0.008
#> SRR1453093 1 0.4998 -0.61343 0.512 0.488 0.000 0.000
#> SRR1357064 2 0.5989 0.12301 0.400 0.556 0.000 0.044
#> SRR811237 1 0.5000 -0.65676 0.500 0.500 0.000 0.000
#> SRR1100848 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1346755 2 0.4985 0.70095 0.468 0.532 0.000 0.000
#> SRR1472529 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1398905 3 0.0000 0.79555 0.000 0.000 1.000 0.000
#> SRR1082733 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1308035 3 0.0707 0.79758 0.000 0.000 0.980 0.020
#> SRR1466445 4 0.6147 -0.34984 0.000 0.048 0.464 0.488
#> SRR1359080 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1455825 2 0.4992 0.69994 0.476 0.524 0.000 0.000
#> SRR1389300 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR812246 3 0.4855 0.53467 0.000 0.000 0.600 0.400
#> SRR1076632 2 0.4992 0.69954 0.476 0.524 0.000 0.000
#> SRR1415567 1 0.0817 0.42764 0.976 0.024 0.000 0.000
#> SRR1331900 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1452099 2 0.6031 0.34264 0.388 0.564 0.000 0.048
#> SRR1352346 2 0.5000 0.63983 0.500 0.500 0.000 0.000
#> SRR1364034 2 0.4998 0.67171 0.488 0.512 0.000 0.000
#> SRR1086046 1 0.4992 -0.57970 0.524 0.476 0.000 0.000
#> SRR1407226 1 0.4989 -0.53844 0.528 0.472 0.000 0.000
#> SRR1319363 1 0.4996 -0.57383 0.516 0.484 0.000 0.000
#> SRR1446961 4 0.7408 0.52050 0.000 0.364 0.172 0.464
#> SRR1486650 1 0.0707 0.42882 0.980 0.020 0.000 0.000
#> SRR1470152 2 0.7069 -0.05650 0.324 0.532 0.000 0.144
#> SRR1454785 3 0.0921 0.79635 0.000 0.000 0.972 0.028
#> SRR1092329 2 0.5143 0.67077 0.456 0.540 0.000 0.004
#> SRR1091476 3 0.0000 0.79555 0.000 0.000 1.000 0.000
#> SRR1073775 2 0.4994 0.69152 0.480 0.520 0.000 0.000
#> SRR1366873 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1398114 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1089950 1 0.7236 -0.24537 0.460 0.396 0.000 0.144
#> SRR1433272 2 0.4989 0.69501 0.472 0.528 0.000 0.000
#> SRR1075314 1 0.7392 0.35492 0.472 0.172 0.000 0.356
#> SRR1085590 2 0.6994 -0.70236 0.000 0.472 0.116 0.412
#> SRR1100752 3 0.0000 0.79555 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.4977 0.68543 0.460 0.540 0.000 0.000
#> SRR1333263 2 0.7699 -0.51749 0.052 0.524 0.084 0.340
#> SRR1310231 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1094144 2 0.4998 0.67171 0.488 0.512 0.000 0.000
#> SRR1092160 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1320300 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1322747 2 0.7204 -0.68138 0.008 0.472 0.108 0.412
#> SRR1432719 4 0.7371 0.45355 0.000 0.268 0.212 0.520
#> SRR1100728 2 0.4998 0.67171 0.488 0.512 0.000 0.000
#> SRR1087511 2 0.5512 0.63164 0.488 0.496 0.000 0.016
#> SRR1470336 1 0.7332 0.35757 0.480 0.164 0.000 0.356
#> SRR1322536 1 0.7392 0.35492 0.472 0.172 0.000 0.356
#> SRR1100824 4 0.7768 -0.19222 0.360 0.240 0.000 0.400
#> SRR1085951 3 0.1022 0.79329 0.000 0.000 0.968 0.032
#> SRR1322046 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1316420 2 0.5816 0.16017 0.392 0.572 0.000 0.036
#> SRR1070913 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1345806 4 0.6148 -0.35718 0.000 0.048 0.468 0.484
#> SRR1313872 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1337666 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1076823 1 0.5088 -0.42178 0.572 0.424 0.000 0.004
#> SRR1093954 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1451921 1 0.4994 -0.59256 0.520 0.480 0.000 0.000
#> SRR1491257 2 0.5989 0.12301 0.400 0.556 0.000 0.044
#> SRR1416979 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1419015 2 0.5378 0.41940 0.448 0.540 0.000 0.012
#> SRR817649 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1466376 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1392055 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1120913 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1120869 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1319419 4 0.7481 0.49435 0.000 0.316 0.200 0.484
#> SRR816495 3 0.6108 0.38875 0.000 0.048 0.528 0.424
#> SRR818694 2 0.5512 0.63164 0.488 0.496 0.000 0.016
#> SRR1465653 2 0.7072 -0.04432 0.336 0.524 0.000 0.140
#> SRR1475952 1 0.0592 0.42753 0.984 0.016 0.000 0.000
#> SRR1465040 3 0.2345 0.77304 0.000 0.000 0.900 0.100
#> SRR1088461 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR810129 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1400141 4 0.7274 0.44344 0.000 0.240 0.220 0.540
#> SRR1349585 1 0.5935 -0.12871 0.496 0.468 0.000 0.036
#> SRR1437576 2 0.5016 0.51373 0.396 0.600 0.000 0.004
#> SRR814407 4 0.6477 -0.00624 0.072 0.420 0.000 0.508
#> SRR1332403 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1099598 2 0.4992 0.69952 0.476 0.524 0.000 0.000
#> SRR1327723 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1392525 2 0.7232 -0.59889 0.020 0.512 0.088 0.380
#> SRR1320536 1 0.0707 0.42882 0.980 0.020 0.000 0.000
#> SRR1083824 2 0.5658 -0.28380 0.040 0.632 0.000 0.328
#> SRR1351390 1 0.7043 0.18930 0.456 0.120 0.000 0.424
#> SRR1309141 2 0.6898 -0.61880 0.008 0.512 0.084 0.396
#> SRR1452803 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR811631 2 0.5649 0.21337 0.284 0.664 0.000 0.052
#> SRR1485563 2 0.4985 0.68748 0.468 0.532 0.000 0.000
#> SRR1311531 3 0.6070 0.41620 0.000 0.048 0.548 0.404
#> SRR1353076 2 0.4992 0.69952 0.476 0.524 0.000 0.000
#> SRR1480831 1 0.4999 -0.62586 0.508 0.492 0.000 0.000
#> SRR1083892 2 0.5989 0.12301 0.400 0.556 0.000 0.044
#> SRR809873 1 0.5126 -0.48662 0.552 0.444 0.000 0.004
#> SRR1341854 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1399335 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1464209 2 0.5980 0.13203 0.396 0.560 0.000 0.044
#> SRR1389886 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1400730 3 0.0000 0.79555 0.000 0.000 1.000 0.000
#> SRR1448008 1 0.4999 -0.63229 0.508 0.492 0.000 0.000
#> SRR1087606 1 0.7869 0.31451 0.368 0.276 0.000 0.356
#> SRR1445111 1 0.4740 0.35711 0.788 0.132 0.000 0.080
#> SRR816865 2 0.4998 0.67171 0.488 0.512 0.000 0.000
#> SRR1323360 3 0.0707 0.79758 0.000 0.000 0.980 0.020
#> SRR1417364 4 0.7408 0.52050 0.000 0.364 0.172 0.464
#> SRR1480329 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1403322 1 0.5097 -0.43442 0.568 0.428 0.000 0.004
#> SRR1093625 1 0.0707 0.42882 0.980 0.020 0.000 0.000
#> SRR1479977 2 0.4989 0.70701 0.472 0.528 0.000 0.000
#> SRR1082035 1 0.4992 -0.54936 0.524 0.476 0.000 0.000
#> SRR1393046 2 0.4855 0.53128 0.400 0.600 0.000 0.000
#> SRR1466663 2 0.4989 0.67920 0.472 0.528 0.000 0.000
#> SRR1384456 1 0.0707 0.42882 0.980 0.020 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR808862 5 0.0290 0.8562 0.008 0.000 0.000 0.000 0.992
#> SRR1500382 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1322683 2 0.0566 0.8684 0.000 0.984 0.012 0.004 0.000
#> SRR1329811 2 0.8088 -0.3558 0.172 0.404 0.284 0.140 0.000
#> SRR1087297 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1072626 2 0.0162 0.8743 0.004 0.996 0.000 0.000 0.000
#> SRR1407428 1 0.3774 0.9066 0.704 0.296 0.000 0.000 0.000
#> SRR1321029 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1500282 4 0.6624 0.3494 0.120 0.268 0.044 0.568 0.000
#> SRR1100496 3 0.7390 0.1135 0.112 0.040 0.456 0.024 0.368
#> SRR1308778 2 0.0807 0.8684 0.012 0.976 0.012 0.000 0.000
#> SRR1445304 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1099378 2 0.3543 0.6993 0.004 0.828 0.040 0.128 0.000
#> SRR1347412 4 0.6582 0.0132 0.308 0.024 0.136 0.532 0.000
#> SRR1099694 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1088365 2 0.0451 0.8721 0.004 0.988 0.008 0.000 0.000
#> SRR1325752 2 0.0807 0.8684 0.012 0.976 0.012 0.000 0.000
#> SRR1416713 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1074474 1 0.3752 0.9141 0.708 0.292 0.000 0.000 0.000
#> SRR1469369 3 0.5009 0.6499 0.008 0.196 0.732 0.028 0.036
#> SRR1400507 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1378179 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1377905 2 0.1992 0.8112 0.000 0.924 0.032 0.044 0.000
#> SRR1089479 1 0.6650 0.6858 0.576 0.264 0.064 0.096 0.000
#> SRR1073365 2 0.0162 0.8738 0.004 0.996 0.000 0.000 0.000
#> SRR1500306 4 0.6702 0.3293 0.168 0.364 0.012 0.456 0.000
#> SRR1101566 2 0.0290 0.8721 0.000 0.992 0.008 0.000 0.000
#> SRR1350503 3 0.4747 0.6292 0.000 0.232 0.716 0.036 0.016
#> SRR1446007 3 0.7272 0.1128 0.124 0.028 0.472 0.024 0.352
#> SRR1102875 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1380293 2 0.0510 0.8714 0.000 0.984 0.016 0.000 0.000
#> SRR1331198 2 0.0290 0.8741 0.000 0.992 0.008 0.000 0.000
#> SRR1092686 3 0.7007 0.2638 0.092 0.040 0.548 0.024 0.296
#> SRR1069421 2 0.1492 0.8538 0.040 0.948 0.008 0.004 0.000
#> SRR1341650 2 0.3010 0.7619 0.116 0.860 0.008 0.016 0.000
#> SRR1357276 2 0.0404 0.8728 0.000 0.988 0.012 0.000 0.000
#> SRR1498374 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1093721 2 0.0162 0.8750 0.000 0.996 0.000 0.004 0.000
#> SRR1464660 2 0.8088 -0.3558 0.172 0.404 0.284 0.140 0.000
#> SRR1402051 2 0.1095 0.8655 0.012 0.968 0.012 0.008 0.000
#> SRR1488734 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1082616 3 0.4957 0.6501 0.004 0.204 0.728 0.032 0.032
#> SRR1099427 2 0.2153 0.8046 0.000 0.916 0.044 0.040 0.000
#> SRR1453093 2 0.2302 0.7973 0.080 0.904 0.008 0.008 0.000
#> SRR1357064 2 0.7234 -0.1234 0.232 0.492 0.232 0.044 0.000
#> SRR811237 2 0.1041 0.8591 0.032 0.964 0.000 0.004 0.000
#> SRR1100848 2 0.0324 0.8745 0.004 0.992 0.004 0.000 0.000
#> SRR1346755 2 0.0290 0.8742 0.000 0.992 0.008 0.000 0.000
#> SRR1472529 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1398905 5 0.0290 0.8562 0.008 0.000 0.000 0.000 0.992
#> SRR1082733 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1308035 5 0.2179 0.8313 0.000 0.000 0.112 0.000 0.888
#> SRR1466445 3 0.6865 0.1991 0.088 0.028 0.532 0.024 0.328
#> SRR1359080 2 0.0290 0.8741 0.000 0.992 0.008 0.000 0.000
#> SRR1455825 2 0.0324 0.8744 0.004 0.992 0.004 0.000 0.000
#> SRR1389300 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR812246 5 0.6681 0.0857 0.124 0.000 0.420 0.024 0.432
#> SRR1076632 2 0.0579 0.8729 0.008 0.984 0.008 0.000 0.000
#> SRR1415567 1 0.3774 0.9066 0.704 0.296 0.000 0.000 0.000
#> SRR1331900 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1452099 2 0.5003 0.5981 0.080 0.764 0.084 0.072 0.000
#> SRR1352346 2 0.1281 0.8545 0.032 0.956 0.012 0.000 0.000
#> SRR1364034 2 0.1492 0.8522 0.040 0.948 0.008 0.004 0.000
#> SRR1086046 2 0.2588 0.7741 0.100 0.884 0.008 0.008 0.000
#> SRR1407226 2 0.2865 0.7555 0.132 0.856 0.004 0.008 0.000
#> SRR1319363 2 0.2741 0.7624 0.132 0.860 0.004 0.004 0.000
#> SRR1446961 3 0.5417 0.6347 0.000 0.160 0.716 0.044 0.080
#> SRR1486650 1 0.3752 0.9141 0.708 0.292 0.000 0.000 0.000
#> SRR1470152 2 0.8088 -0.3558 0.172 0.404 0.284 0.140 0.000
#> SRR1454785 5 0.2536 0.8211 0.004 0.000 0.128 0.000 0.868
#> SRR1092329 2 0.0693 0.8674 0.000 0.980 0.012 0.008 0.000
#> SRR1091476 5 0.0000 0.8572 0.000 0.000 0.000 0.000 1.000
#> SRR1073775 2 0.0451 0.8720 0.008 0.988 0.004 0.000 0.000
#> SRR1366873 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1398114 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1089950 2 0.4043 0.6343 0.012 0.792 0.036 0.160 0.000
#> SRR1433272 2 0.1012 0.8642 0.012 0.968 0.020 0.000 0.000
#> SRR1075314 4 0.6702 0.3948 0.176 0.336 0.012 0.476 0.000
#> SRR1085590 3 0.5685 0.6145 0.000 0.236 0.656 0.084 0.024
#> SRR1100752 5 0.0000 0.8572 0.000 0.000 0.000 0.000 1.000
#> SRR1391494 2 0.0579 0.8706 0.000 0.984 0.008 0.008 0.000
#> SRR1333263 3 0.5895 0.4217 0.004 0.336 0.572 0.080 0.008
#> SRR1310231 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1094144 2 0.1492 0.8522 0.040 0.948 0.008 0.004 0.000
#> SRR1092160 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1320300 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1322747 3 0.5480 0.6023 0.000 0.248 0.660 0.076 0.016
#> SRR1432719 3 0.5548 0.5978 0.032 0.132 0.720 0.008 0.108
#> SRR1100728 2 0.1569 0.8494 0.044 0.944 0.008 0.004 0.000
#> SRR1087511 2 0.1306 0.8596 0.016 0.960 0.008 0.016 0.000
#> SRR1470336 4 0.6710 0.3831 0.176 0.340 0.012 0.472 0.000
#> SRR1322536 4 0.6702 0.3948 0.176 0.336 0.012 0.476 0.000
#> SRR1100824 4 0.6770 0.3327 0.120 0.304 0.044 0.532 0.000
#> SRR1085951 5 0.2006 0.8364 0.072 0.000 0.000 0.012 0.916
#> SRR1322046 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1316420 2 0.7008 -0.0420 0.224 0.520 0.220 0.036 0.000
#> SRR1070913 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1345806 3 0.6877 0.1925 0.088 0.028 0.528 0.024 0.332
#> SRR1313872 2 0.0324 0.8746 0.004 0.992 0.004 0.000 0.000
#> SRR1337666 2 0.0404 0.8732 0.000 0.988 0.012 0.000 0.000
#> SRR1076823 2 0.3967 0.5795 0.200 0.772 0.008 0.020 0.000
#> SRR1093954 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1451921 2 0.2420 0.7891 0.088 0.896 0.008 0.008 0.000
#> SRR1491257 2 0.7234 -0.1234 0.232 0.492 0.232 0.044 0.000
#> SRR1416979 2 0.0324 0.8745 0.004 0.992 0.004 0.000 0.000
#> SRR1419015 2 0.4103 0.6969 0.100 0.812 0.020 0.068 0.000
#> SRR817649 2 0.0510 0.8714 0.000 0.984 0.016 0.000 0.000
#> SRR1466376 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1392055 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1120913 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1120869 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1319419 3 0.5086 0.6185 0.012 0.144 0.740 0.008 0.096
#> SRR816495 3 0.7252 0.0966 0.120 0.028 0.468 0.024 0.360
#> SRR818694 2 0.1306 0.8596 0.016 0.960 0.008 0.016 0.000
#> SRR1465653 2 0.8026 -0.3419 0.176 0.412 0.284 0.128 0.000
#> SRR1475952 1 0.4243 0.8359 0.712 0.264 0.000 0.024 0.000
#> SRR1465040 5 0.5026 0.7297 0.088 0.000 0.148 0.024 0.740
#> SRR1088461 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR810129 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1400141 3 0.6449 0.5936 0.068 0.144 0.672 0.024 0.092
#> SRR1349585 2 0.7135 -0.2362 0.292 0.480 0.192 0.036 0.000
#> SRR1437576 2 0.2067 0.8064 0.000 0.920 0.032 0.048 0.000
#> SRR814407 4 0.1671 0.0783 0.000 0.000 0.076 0.924 0.000
#> SRR1332403 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1099598 2 0.0451 0.8721 0.004 0.988 0.008 0.000 0.000
#> SRR1327723 2 0.0290 0.8741 0.000 0.992 0.008 0.000 0.000
#> SRR1392525 3 0.5772 0.5254 0.004 0.292 0.616 0.076 0.012
#> SRR1320536 1 0.3752 0.9141 0.708 0.292 0.000 0.000 0.000
#> SRR1083824 3 0.5736 0.1784 0.000 0.448 0.468 0.084 0.000
#> SRR1351390 4 0.6694 0.3855 0.132 0.308 0.032 0.528 0.000
#> SRR1309141 3 0.5500 0.5352 0.000 0.288 0.628 0.076 0.008
#> SRR1452803 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR811631 2 0.3934 0.6160 0.000 0.800 0.124 0.076 0.000
#> SRR1485563 2 0.1116 0.8605 0.004 0.964 0.028 0.004 0.000
#> SRR1311531 3 0.7215 0.0449 0.112 0.028 0.452 0.024 0.384
#> SRR1353076 2 0.0451 0.8721 0.004 0.988 0.008 0.000 0.000
#> SRR1480831 2 0.1764 0.8225 0.064 0.928 0.008 0.000 0.000
#> SRR1083892 2 0.7234 -0.1234 0.232 0.492 0.232 0.044 0.000
#> SRR809873 2 0.3234 0.7041 0.144 0.836 0.008 0.012 0.000
#> SRR1341854 2 0.0162 0.8746 0.000 0.996 0.004 0.000 0.000
#> SRR1399335 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1464209 2 0.7215 -0.1136 0.228 0.496 0.232 0.044 0.000
#> SRR1389886 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 5 0.0290 0.8562 0.008 0.000 0.000 0.000 0.992
#> SRR1448008 2 0.1857 0.8258 0.060 0.928 0.004 0.008 0.000
#> SRR1087606 2 0.7158 -0.5336 0.084 0.420 0.088 0.408 0.000
#> SRR1445111 1 0.6605 0.6864 0.580 0.264 0.064 0.092 0.000
#> SRR816865 2 0.1492 0.8522 0.040 0.948 0.008 0.004 0.000
#> SRR1323360 5 0.2179 0.8313 0.000 0.000 0.112 0.000 0.888
#> SRR1417364 3 0.5417 0.6347 0.000 0.160 0.716 0.044 0.080
#> SRR1480329 2 0.0290 0.8739 0.000 0.992 0.008 0.000 0.000
#> SRR1403322 2 0.3597 0.6352 0.180 0.800 0.008 0.012 0.000
#> SRR1093625 1 0.3752 0.9141 0.708 0.292 0.000 0.000 0.000
#> SRR1479977 2 0.0000 0.8745 0.000 1.000 0.000 0.000 0.000
#> SRR1082035 2 0.2694 0.7654 0.128 0.864 0.004 0.004 0.000
#> SRR1393046 2 0.1907 0.8144 0.000 0.928 0.028 0.044 0.000
#> SRR1466663 2 0.1356 0.8560 0.012 0.956 0.028 0.004 0.000
#> SRR1384456 1 0.3752 0.9141 0.708 0.292 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0458 0.89546 0.000 0.984 0.016 0.000 0.000 0.000
#> SRR808862 4 0.0405 0.88152 0.000 0.000 0.000 0.988 0.008 0.004
#> SRR1500382 2 0.0547 0.89523 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1322683 2 0.1484 0.88616 0.008 0.944 0.040 0.000 0.004 0.004
#> SRR1329811 5 0.3336 0.73022 0.056 0.100 0.012 0.000 0.832 0.000
#> SRR1087297 2 0.0692 0.89655 0.000 0.976 0.020 0.000 0.004 0.000
#> SRR1072626 2 0.0520 0.89615 0.008 0.984 0.008 0.000 0.000 0.000
#> SRR1407428 1 0.1788 0.89280 0.916 0.076 0.004 0.000 0.004 0.000
#> SRR1321029 2 0.0865 0.89016 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1500282 6 0.6876 0.31082 0.108 0.128 0.008 0.000 0.248 0.508
#> SRR1100496 3 0.5971 0.32954 0.016 0.000 0.548 0.308 0.112 0.016
#> SRR1308778 2 0.1078 0.89334 0.012 0.964 0.016 0.000 0.008 0.000
#> SRR1445304 2 0.0547 0.89534 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1099378 2 0.4297 0.72282 0.016 0.772 0.008 0.000 0.096 0.108
#> SRR1347412 6 0.6568 -0.00674 0.308 0.000 0.068 0.000 0.144 0.480
#> SRR1099694 2 0.1194 0.89578 0.004 0.956 0.032 0.000 0.008 0.000
#> SRR1088365 2 0.1982 0.87581 0.016 0.912 0.068 0.000 0.000 0.004
#> SRR1325752 2 0.1173 0.89380 0.016 0.960 0.016 0.000 0.008 0.000
#> SRR1416713 2 0.0603 0.89521 0.000 0.980 0.016 0.000 0.004 0.000
#> SRR1074474 1 0.1812 0.90136 0.912 0.080 0.000 0.000 0.008 0.000
#> SRR1469369 3 0.2157 0.65447 0.004 0.076 0.904 0.000 0.008 0.008
#> SRR1400507 2 0.1010 0.89048 0.004 0.960 0.036 0.000 0.000 0.000
#> SRR1378179 2 0.1003 0.89402 0.004 0.964 0.028 0.000 0.004 0.000
#> SRR1377905 2 0.2481 0.84829 0.008 0.896 0.060 0.000 0.008 0.028
#> SRR1089479 1 0.5329 0.64111 0.672 0.092 0.008 0.000 0.196 0.032
#> SRR1073365 2 0.1168 0.89778 0.016 0.956 0.028 0.000 0.000 0.000
#> SRR1500306 6 0.5613 0.51435 0.356 0.096 0.008 0.000 0.008 0.532
#> SRR1101566 2 0.1196 0.88862 0.008 0.952 0.040 0.000 0.000 0.000
#> SRR1350503 3 0.2758 0.64227 0.000 0.112 0.860 0.000 0.016 0.012
#> SRR1446007 3 0.6396 0.34403 0.024 0.000 0.528 0.288 0.136 0.024
#> SRR1102875 2 0.1542 0.88600 0.008 0.936 0.052 0.000 0.000 0.004
#> SRR1380293 2 0.1003 0.89530 0.000 0.964 0.020 0.000 0.016 0.000
#> SRR1331198 2 0.1049 0.89647 0.000 0.960 0.032 0.000 0.008 0.000
#> SRR1092686 3 0.5739 0.43885 0.016 0.000 0.620 0.236 0.104 0.024
#> SRR1069421 2 0.2895 0.85628 0.020 0.880 0.044 0.000 0.044 0.012
#> SRR1341650 2 0.5380 0.60680 0.116 0.696 0.060 0.000 0.120 0.008
#> SRR1357276 2 0.1074 0.89239 0.000 0.960 0.028 0.000 0.012 0.000
#> SRR1498374 2 0.1010 0.89048 0.004 0.960 0.036 0.000 0.000 0.000
#> SRR1093721 2 0.0862 0.89763 0.008 0.972 0.016 0.000 0.004 0.000
#> SRR1464660 5 0.3336 0.73022 0.056 0.100 0.012 0.000 0.832 0.000
#> SRR1402051 2 0.2316 0.88133 0.020 0.908 0.044 0.000 0.024 0.004
#> SRR1488734 2 0.0547 0.89523 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1082616 3 0.2253 0.65295 0.004 0.084 0.896 0.000 0.012 0.004
#> SRR1099427 2 0.3065 0.82777 0.008 0.852 0.104 0.000 0.008 0.028
#> SRR1453093 2 0.4014 0.75875 0.132 0.776 0.080 0.000 0.000 0.012
#> SRR1357064 5 0.5200 0.80773 0.112 0.192 0.028 0.000 0.668 0.000
#> SRR811237 2 0.2265 0.85628 0.084 0.896 0.008 0.000 0.008 0.004
#> SRR1100848 2 0.1442 0.89366 0.004 0.944 0.040 0.000 0.012 0.000
#> SRR1346755 2 0.1080 0.89088 0.004 0.960 0.032 0.000 0.004 0.000
#> SRR1472529 2 0.0935 0.89690 0.004 0.964 0.032 0.000 0.000 0.000
#> SRR1398905 4 0.0405 0.88152 0.000 0.000 0.000 0.988 0.008 0.004
#> SRR1082733 2 0.0865 0.89609 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1308035 4 0.2340 0.82881 0.000 0.000 0.148 0.852 0.000 0.000
#> SRR1466445 3 0.5856 0.40927 0.016 0.000 0.592 0.268 0.100 0.024
#> SRR1359080 2 0.1296 0.89216 0.004 0.952 0.032 0.000 0.012 0.000
#> SRR1455825 2 0.1442 0.89548 0.012 0.944 0.040 0.000 0.004 0.000
#> SRR1389300 2 0.0790 0.89106 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR812246 3 0.6582 0.13213 0.024 0.000 0.440 0.376 0.136 0.024
#> SRR1076632 2 0.2095 0.87834 0.004 0.916 0.052 0.000 0.016 0.012
#> SRR1415567 1 0.1644 0.89373 0.920 0.076 0.000 0.000 0.004 0.000
#> SRR1331900 2 0.0692 0.89377 0.004 0.976 0.020 0.000 0.000 0.000
#> SRR1452099 2 0.4848 0.46733 0.032 0.652 0.028 0.000 0.284 0.004
#> SRR1352346 2 0.1930 0.87708 0.028 0.924 0.036 0.000 0.012 0.000
#> SRR1364034 2 0.3373 0.83014 0.020 0.848 0.076 0.000 0.044 0.012
#> SRR1086046 2 0.4926 0.65898 0.188 0.704 0.080 0.000 0.012 0.016
#> SRR1407226 2 0.5416 0.60859 0.136 0.688 0.072 0.000 0.100 0.004
#> SRR1319363 2 0.5285 0.63943 0.136 0.700 0.076 0.000 0.084 0.004
#> SRR1446961 3 0.2379 0.64704 0.000 0.052 0.904 0.024 0.008 0.012
#> SRR1486650 1 0.1812 0.90136 0.912 0.080 0.000 0.000 0.008 0.000
#> SRR1470152 5 0.3336 0.73022 0.056 0.100 0.012 0.000 0.832 0.000
#> SRR1454785 4 0.2841 0.81391 0.004 0.000 0.156 0.832 0.004 0.004
#> SRR1092329 2 0.1863 0.89210 0.008 0.924 0.056 0.000 0.004 0.008
#> SRR1091476 4 0.0000 0.88341 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 2 0.2039 0.88011 0.016 0.908 0.072 0.000 0.000 0.004
#> SRR1366873 2 0.0935 0.89135 0.004 0.964 0.032 0.000 0.000 0.000
#> SRR1398114 2 0.0363 0.89467 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1089950 2 0.5060 0.66944 0.028 0.728 0.028 0.000 0.084 0.132
#> SRR1433272 2 0.1434 0.89381 0.008 0.948 0.020 0.000 0.024 0.000
#> SRR1075314 6 0.5440 0.53553 0.336 0.084 0.008 0.000 0.008 0.564
#> SRR1085590 3 0.3515 0.62509 0.004 0.120 0.820 0.000 0.012 0.044
#> SRR1100752 4 0.0000 0.88341 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 2 0.1261 0.89043 0.004 0.956 0.028 0.000 0.004 0.008
#> SRR1333263 3 0.4959 0.42996 0.008 0.264 0.660 0.000 0.020 0.048
#> SRR1310231 2 0.0363 0.89335 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1094144 2 0.3373 0.83014 0.020 0.848 0.076 0.000 0.044 0.012
#> SRR1092160 2 0.1194 0.89578 0.004 0.956 0.032 0.000 0.008 0.000
#> SRR1320300 2 0.0692 0.89377 0.004 0.976 0.020 0.000 0.000 0.000
#> SRR1322747 3 0.3574 0.61905 0.008 0.128 0.816 0.000 0.012 0.036
#> SRR1432719 3 0.3494 0.62881 0.004 0.032 0.852 0.052 0.044 0.016
#> SRR1100728 2 0.3352 0.82973 0.016 0.848 0.076 0.000 0.048 0.012
#> SRR1087511 2 0.2872 0.85357 0.024 0.868 0.080 0.000 0.000 0.028
#> SRR1470336 6 0.5394 0.51849 0.332 0.104 0.008 0.000 0.000 0.556
#> SRR1322536 6 0.5440 0.53553 0.336 0.084 0.008 0.000 0.008 0.564
#> SRR1100824 6 0.7095 0.25017 0.112 0.148 0.008 0.000 0.260 0.472
#> SRR1085951 4 0.2044 0.85615 0.004 0.000 0.008 0.908 0.076 0.004
#> SRR1322046 2 0.0858 0.89402 0.000 0.968 0.028 0.000 0.004 0.000
#> SRR1316420 5 0.5436 0.69178 0.104 0.244 0.028 0.000 0.624 0.000
#> SRR1070913 2 0.1010 0.89048 0.004 0.960 0.036 0.000 0.000 0.000
#> SRR1345806 3 0.5873 0.40447 0.016 0.000 0.588 0.272 0.100 0.024
#> SRR1313872 2 0.1194 0.89667 0.004 0.956 0.032 0.000 0.008 0.000
#> SRR1337666 2 0.1151 0.89081 0.000 0.956 0.032 0.000 0.012 0.000
#> SRR1076823 2 0.5913 0.30413 0.336 0.540 0.080 0.000 0.008 0.036
#> SRR1093954 2 0.1542 0.88600 0.008 0.936 0.052 0.000 0.000 0.004
#> SRR1451921 2 0.4587 0.70177 0.168 0.732 0.080 0.000 0.008 0.012
#> SRR1491257 5 0.5200 0.80773 0.112 0.192 0.028 0.000 0.668 0.000
#> SRR1416979 2 0.1442 0.89366 0.004 0.944 0.040 0.000 0.012 0.000
#> SRR1419015 2 0.6078 0.52141 0.132 0.660 0.052 0.000 0.096 0.060
#> SRR817649 2 0.1245 0.88976 0.000 0.952 0.032 0.000 0.016 0.000
#> SRR1466376 2 0.0363 0.89335 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1392055 2 0.0717 0.89477 0.008 0.976 0.016 0.000 0.000 0.000
#> SRR1120913 2 0.0692 0.89655 0.000 0.976 0.020 0.000 0.004 0.000
#> SRR1120869 2 0.1226 0.89020 0.004 0.952 0.040 0.000 0.000 0.004
#> SRR1319419 3 0.2856 0.63822 0.008 0.036 0.888 0.040 0.016 0.012
#> SRR816495 3 0.6422 0.33265 0.024 0.000 0.520 0.296 0.136 0.024
#> SRR818694 2 0.2872 0.85357 0.024 0.868 0.080 0.000 0.000 0.028
#> SRR1465653 5 0.3488 0.74100 0.060 0.108 0.012 0.000 0.820 0.000
#> SRR1475952 1 0.2052 0.80262 0.912 0.056 0.004 0.000 0.000 0.028
#> SRR1465040 4 0.5192 0.68544 0.016 0.000 0.160 0.696 0.108 0.020
#> SRR1088461 2 0.0909 0.89619 0.012 0.968 0.020 0.000 0.000 0.000
#> SRR810129 2 0.0363 0.89467 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1400141 3 0.4223 0.62319 0.016 0.036 0.812 0.032 0.080 0.024
#> SRR1349585 5 0.5909 0.70321 0.244 0.160 0.028 0.000 0.568 0.000
#> SRR1437576 2 0.2786 0.84265 0.008 0.876 0.076 0.000 0.008 0.032
#> SRR814407 6 0.2837 0.39567 0.000 0.000 0.056 0.000 0.088 0.856
#> SRR1332403 2 0.0692 0.89678 0.000 0.976 0.020 0.000 0.004 0.000
#> SRR1099598 2 0.1982 0.87581 0.016 0.912 0.068 0.000 0.000 0.004
#> SRR1327723 2 0.0891 0.89441 0.000 0.968 0.024 0.000 0.008 0.000
#> SRR1392525 3 0.4139 0.54316 0.008 0.180 0.760 0.000 0.016 0.036
#> SRR1320536 1 0.1812 0.90136 0.912 0.080 0.000 0.000 0.008 0.000
#> SRR1083824 3 0.5235 0.20977 0.008 0.380 0.552 0.000 0.016 0.044
#> SRR1351390 6 0.6688 0.49281 0.236 0.156 0.000 0.000 0.096 0.512
#> SRR1309141 3 0.4005 0.54006 0.004 0.188 0.760 0.000 0.012 0.036
#> SRR1452803 2 0.0458 0.89450 0.000 0.984 0.016 0.000 0.000 0.000
#> SRR811631 2 0.4085 0.68401 0.008 0.764 0.176 0.000 0.012 0.040
#> SRR1485563 2 0.1296 0.89250 0.004 0.952 0.012 0.000 0.032 0.000
#> SRR1311531 3 0.6430 0.29621 0.024 0.000 0.504 0.320 0.128 0.024
#> SRR1353076 2 0.1863 0.88009 0.016 0.920 0.060 0.000 0.000 0.004
#> SRR1480831 2 0.3265 0.81568 0.088 0.836 0.068 0.000 0.000 0.008
#> SRR1083892 5 0.5200 0.80773 0.112 0.192 0.028 0.000 0.668 0.000
#> SRR809873 2 0.5467 0.50033 0.268 0.620 0.080 0.000 0.008 0.024
#> SRR1341854 2 0.0858 0.89402 0.000 0.968 0.028 0.000 0.004 0.000
#> SRR1399335 2 0.0909 0.89619 0.012 0.968 0.020 0.000 0.000 0.000
#> SRR1464209 5 0.5159 0.80692 0.108 0.192 0.028 0.000 0.672 0.000
#> SRR1389886 2 0.0363 0.89335 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1400730 4 0.0405 0.88152 0.000 0.000 0.000 0.988 0.008 0.004
#> SRR1448008 2 0.3830 0.78980 0.120 0.796 0.072 0.000 0.004 0.008
#> SRR1087606 2 0.6912 -0.53072 0.048 0.320 0.000 0.000 0.312 0.320
#> SRR1445111 1 0.5356 0.64140 0.668 0.092 0.008 0.000 0.200 0.032
#> SRR816865 2 0.3373 0.83014 0.020 0.848 0.076 0.000 0.044 0.012
#> SRR1323360 4 0.2340 0.82881 0.000 0.000 0.148 0.852 0.000 0.000
#> SRR1417364 3 0.2379 0.64704 0.000 0.052 0.904 0.024 0.008 0.012
#> SRR1480329 2 0.0767 0.89599 0.004 0.976 0.012 0.000 0.008 0.000
#> SRR1403322 2 0.5696 0.35526 0.328 0.560 0.080 0.000 0.008 0.024
#> SRR1093625 1 0.1812 0.90136 0.912 0.080 0.000 0.000 0.008 0.000
#> SRR1479977 2 0.1124 0.89071 0.008 0.956 0.036 0.000 0.000 0.000
#> SRR1082035 2 0.5253 0.63953 0.128 0.704 0.072 0.000 0.092 0.004
#> SRR1393046 2 0.2321 0.85315 0.008 0.904 0.052 0.000 0.004 0.032
#> SRR1466663 2 0.1737 0.88645 0.008 0.932 0.020 0.000 0.040 0.000
#> SRR1384456 1 0.1812 0.90136 0.912 0.080 0.000 0.000 0.008 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "kmeans"]
# you can also extract it by
# res = res_list["CV:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 1.000 0.961 0.960 0.2867 0.725 0.725
#> 3 3 0.968 0.934 0.959 0.9050 0.727 0.623
#> 4 4 0.643 0.675 0.829 0.1659 0.987 0.971
#> 5 5 0.530 0.597 0.737 0.1080 0.900 0.778
#> 6 6 0.554 0.481 0.690 0.0758 0.895 0.715
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
#> SRR810713 2 0.0000 0.969 0.000 1.000
#> SRR808862 1 0.4298 0.991 0.912 0.088
#> SRR1500382 2 0.0000 0.969 0.000 1.000
#> SRR1322683 2 0.0000 0.969 0.000 1.000
#> SRR1329811 2 0.4562 0.924 0.096 0.904
#> SRR1087297 2 0.0000 0.969 0.000 1.000
#> SRR1072626 2 0.0000 0.969 0.000 1.000
#> SRR1407428 2 0.4562 0.924 0.096 0.904
#> SRR1321029 2 0.0000 0.969 0.000 1.000
#> SRR1500282 2 0.4562 0.924 0.096 0.904
#> SRR1100496 1 0.4562 0.997 0.904 0.096
#> SRR1308778 2 0.0000 0.969 0.000 1.000
#> SRR1445304 2 0.0000 0.969 0.000 1.000
#> SRR1099378 2 0.4562 0.924 0.096 0.904
#> SRR1347412 2 0.7674 0.790 0.224 0.776
#> SRR1099694 2 0.0000 0.969 0.000 1.000
#> SRR1088365 2 0.0000 0.969 0.000 1.000
#> SRR1325752 2 0.3733 0.935 0.072 0.928
#> SRR1416713 2 0.0000 0.969 0.000 1.000
#> SRR1074474 2 0.4562 0.924 0.096 0.904
#> SRR1469369 1 0.4562 0.997 0.904 0.096
#> SRR1400507 2 0.0000 0.969 0.000 1.000
#> SRR1378179 2 0.0000 0.969 0.000 1.000
#> SRR1377905 2 0.0000 0.969 0.000 1.000
#> SRR1089479 2 0.4562 0.924 0.096 0.904
#> SRR1073365 2 0.0000 0.969 0.000 1.000
#> SRR1500306 2 0.4562 0.924 0.096 0.904
#> SRR1101566 2 0.0000 0.969 0.000 1.000
#> SRR1350503 1 0.4562 0.997 0.904 0.096
#> SRR1446007 1 0.4562 0.997 0.904 0.096
#> SRR1102875 2 0.0000 0.969 0.000 1.000
#> SRR1380293 2 0.0000 0.969 0.000 1.000
#> SRR1331198 2 0.0000 0.969 0.000 1.000
#> SRR1092686 1 0.4562 0.997 0.904 0.096
#> SRR1069421 2 0.0000 0.969 0.000 1.000
#> SRR1341650 2 0.0000 0.969 0.000 1.000
#> SRR1357276 2 0.0000 0.969 0.000 1.000
#> SRR1498374 2 0.0000 0.969 0.000 1.000
#> SRR1093721 2 0.0000 0.969 0.000 1.000
#> SRR1464660 2 0.4562 0.924 0.096 0.904
#> SRR1402051 2 0.0000 0.969 0.000 1.000
#> SRR1488734 2 0.0000 0.969 0.000 1.000
#> SRR1082616 1 0.4562 0.997 0.904 0.096
#> SRR1099427 2 0.0000 0.969 0.000 1.000
#> SRR1453093 2 0.0000 0.969 0.000 1.000
#> SRR1357064 2 0.4562 0.924 0.096 0.904
#> SRR811237 2 0.0000 0.969 0.000 1.000
#> SRR1100848 2 0.0000 0.969 0.000 1.000
#> SRR1346755 2 0.0000 0.969 0.000 1.000
#> SRR1472529 2 0.0000 0.969 0.000 1.000
#> SRR1398905 1 0.3733 0.976 0.928 0.072
#> SRR1082733 2 0.0000 0.969 0.000 1.000
#> SRR1308035 1 0.4562 0.997 0.904 0.096
#> SRR1466445 1 0.4562 0.997 0.904 0.096
#> SRR1359080 2 0.0000 0.969 0.000 1.000
#> SRR1455825 2 0.0000 0.969 0.000 1.000
#> SRR1389300 2 0.0000 0.969 0.000 1.000
#> SRR812246 1 0.4562 0.997 0.904 0.096
#> SRR1076632 2 0.0000 0.969 0.000 1.000
#> SRR1415567 2 0.4562 0.924 0.096 0.904
#> SRR1331900 2 0.0000 0.969 0.000 1.000
#> SRR1452099 2 0.0376 0.967 0.004 0.996
#> SRR1352346 2 0.4022 0.932 0.080 0.920
#> SRR1364034 2 0.0000 0.969 0.000 1.000
#> SRR1086046 2 0.0376 0.967 0.004 0.996
#> SRR1407226 2 0.4562 0.924 0.096 0.904
#> SRR1319363 2 0.4022 0.932 0.080 0.920
#> SRR1446961 1 0.4562 0.997 0.904 0.096
#> SRR1486650 2 0.4562 0.924 0.096 0.904
#> SRR1470152 2 0.4562 0.924 0.096 0.904
#> SRR1454785 1 0.4562 0.997 0.904 0.096
#> SRR1092329 2 0.0000 0.969 0.000 1.000
#> SRR1091476 1 0.4298 0.991 0.912 0.088
#> SRR1073775 2 0.0000 0.969 0.000 1.000
#> SRR1366873 2 0.0000 0.969 0.000 1.000
#> SRR1398114 2 0.0000 0.969 0.000 1.000
#> SRR1089950 2 0.4562 0.924 0.096 0.904
#> SRR1433272 2 0.0000 0.969 0.000 1.000
#> SRR1075314 2 0.4562 0.924 0.096 0.904
#> SRR1085590 2 0.0000 0.969 0.000 1.000
#> SRR1100752 1 0.4562 0.997 0.904 0.096
#> SRR1391494 2 0.0000 0.969 0.000 1.000
#> SRR1333263 2 0.0000 0.969 0.000 1.000
#> SRR1310231 2 0.0000 0.969 0.000 1.000
#> SRR1094144 2 0.0000 0.969 0.000 1.000
#> SRR1092160 2 0.0000 0.969 0.000 1.000
#> SRR1320300 2 0.0000 0.969 0.000 1.000
#> SRR1322747 2 0.0000 0.969 0.000 1.000
#> SRR1432719 1 0.4562 0.997 0.904 0.096
#> SRR1100728 2 0.0000 0.969 0.000 1.000
#> SRR1087511 2 0.0000 0.969 0.000 1.000
#> SRR1470336 2 0.4562 0.924 0.096 0.904
#> SRR1322536 2 0.4562 0.924 0.096 0.904
#> SRR1100824 2 0.4562 0.924 0.096 0.904
#> SRR1085951 1 0.4298 0.991 0.912 0.088
#> SRR1322046 2 0.0000 0.969 0.000 1.000
#> SRR1316420 2 0.4562 0.924 0.096 0.904
#> SRR1070913 2 0.0000 0.969 0.000 1.000
#> SRR1345806 1 0.4562 0.997 0.904 0.096
#> SRR1313872 2 0.0000 0.969 0.000 1.000
#> SRR1337666 2 0.0000 0.969 0.000 1.000
#> SRR1076823 2 0.4562 0.924 0.096 0.904
#> SRR1093954 2 0.0000 0.969 0.000 1.000
#> SRR1451921 2 0.0376 0.967 0.004 0.996
#> SRR1491257 2 0.4562 0.924 0.096 0.904
#> SRR1416979 2 0.0000 0.969 0.000 1.000
#> SRR1419015 2 0.0000 0.969 0.000 1.000
#> SRR817649 2 0.0000 0.969 0.000 1.000
#> SRR1466376 2 0.0000 0.969 0.000 1.000
#> SRR1392055 2 0.0000 0.969 0.000 1.000
#> SRR1120913 2 0.0000 0.969 0.000 1.000
#> SRR1120869 2 0.0000 0.969 0.000 1.000
#> SRR1319419 1 0.4562 0.997 0.904 0.096
#> SRR816495 1 0.4562 0.997 0.904 0.096
#> SRR818694 2 0.0000 0.969 0.000 1.000
#> SRR1465653 2 0.4562 0.924 0.096 0.904
#> SRR1475952 2 0.4562 0.924 0.096 0.904
#> SRR1465040 1 0.4562 0.997 0.904 0.096
#> SRR1088461 2 0.0000 0.969 0.000 1.000
#> SRR810129 2 0.0000 0.969 0.000 1.000
#> SRR1400141 1 0.4562 0.997 0.904 0.096
#> SRR1349585 2 0.4562 0.924 0.096 0.904
#> SRR1437576 2 0.0000 0.969 0.000 1.000
#> SRR814407 2 0.4562 0.924 0.096 0.904
#> SRR1332403 2 0.0000 0.969 0.000 1.000
#> SRR1099598 2 0.0000 0.969 0.000 1.000
#> SRR1327723 2 0.0000 0.969 0.000 1.000
#> SRR1392525 2 0.0000 0.969 0.000 1.000
#> SRR1320536 2 0.4562 0.924 0.096 0.904
#> SRR1083824 2 0.0000 0.969 0.000 1.000
#> SRR1351390 2 0.4562 0.924 0.096 0.904
#> SRR1309141 2 0.0000 0.969 0.000 1.000
#> SRR1452803 2 0.0000 0.969 0.000 1.000
#> SRR811631 2 0.0000 0.969 0.000 1.000
#> SRR1485563 2 0.0000 0.969 0.000 1.000
#> SRR1311531 1 0.4562 0.997 0.904 0.096
#> SRR1353076 2 0.0000 0.969 0.000 1.000
#> SRR1480831 2 0.0000 0.969 0.000 1.000
#> SRR1083892 2 0.4562 0.924 0.096 0.904
#> SRR809873 2 0.3879 0.933 0.076 0.924
#> SRR1341854 2 0.0000 0.969 0.000 1.000
#> SRR1399335 2 0.0000 0.969 0.000 1.000
#> SRR1464209 2 0.4562 0.924 0.096 0.904
#> SRR1389886 2 0.0000 0.969 0.000 1.000
#> SRR1400730 1 0.3733 0.976 0.928 0.072
#> SRR1448008 2 0.0000 0.969 0.000 1.000
#> SRR1087606 2 0.4562 0.924 0.096 0.904
#> SRR1445111 2 0.4562 0.924 0.096 0.904
#> SRR816865 2 0.0000 0.969 0.000 1.000
#> SRR1323360 1 0.4562 0.997 0.904 0.096
#> SRR1417364 1 0.4562 0.997 0.904 0.096
#> SRR1480329 2 0.0000 0.969 0.000 1.000
#> SRR1403322 2 0.4431 0.926 0.092 0.908
#> SRR1093625 2 0.4562 0.924 0.096 0.904
#> SRR1479977 2 0.0000 0.969 0.000 1.000
#> SRR1082035 2 0.3114 0.943 0.056 0.944
#> SRR1393046 2 0.0000 0.969 0.000 1.000
#> SRR1466663 2 0.0000 0.969 0.000 1.000
#> SRR1384456 2 0.4562 0.924 0.096 0.904
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0424 0.965 0.008 0.992 0.000
#> SRR808862 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1500382 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1322683 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1329811 1 0.1964 0.953 0.944 0.056 0.000
#> SRR1087297 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1072626 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1407428 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1321029 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1500282 1 0.1860 0.952 0.948 0.052 0.000
#> SRR1100496 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1308778 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1445304 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1099378 1 0.4702 0.787 0.788 0.212 0.000
#> SRR1347412 1 0.0424 0.877 0.992 0.000 0.008
#> SRR1099694 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1088365 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1325752 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1416713 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1074474 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1469369 3 0.1964 0.966 0.056 0.000 0.944
#> SRR1400507 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1378179 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1377905 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1089479 1 0.2066 0.958 0.940 0.060 0.000
#> SRR1073365 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1500306 1 0.2711 0.944 0.912 0.088 0.000
#> SRR1101566 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1350503 3 0.1964 0.966 0.056 0.000 0.944
#> SRR1446007 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1102875 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1380293 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1331198 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1092686 3 0.0000 0.985 0.000 0.000 1.000
#> SRR1069421 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1341650 2 0.0424 0.965 0.008 0.992 0.000
#> SRR1357276 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1498374 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1093721 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1464660 1 0.1964 0.953 0.944 0.056 0.000
#> SRR1402051 2 0.3551 0.829 0.132 0.868 0.000
#> SRR1488734 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1082616 3 0.2066 0.964 0.060 0.000 0.940
#> SRR1099427 2 0.1753 0.929 0.048 0.952 0.000
#> SRR1453093 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1357064 1 0.2261 0.960 0.932 0.068 0.000
#> SRR811237 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1100848 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1346755 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1472529 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1398905 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1082733 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1308035 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1466445 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1359080 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1455825 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1389300 2 0.0237 0.965 0.004 0.996 0.000
#> SRR812246 3 0.0000 0.985 0.000 0.000 1.000
#> SRR1076632 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1415567 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1331900 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1452099 2 0.5810 0.448 0.336 0.664 0.000
#> SRR1352346 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1364034 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1086046 2 0.5733 0.480 0.324 0.676 0.000
#> SRR1407226 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1319363 2 0.6252 0.139 0.444 0.556 0.000
#> SRR1446961 3 0.2066 0.964 0.060 0.000 0.940
#> SRR1486650 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1470152 1 0.1964 0.953 0.944 0.056 0.000
#> SRR1454785 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1092329 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1091476 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1073775 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1366873 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1398114 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1089950 1 0.4178 0.842 0.828 0.172 0.000
#> SRR1433272 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1075314 1 0.3038 0.928 0.896 0.104 0.000
#> SRR1085590 2 0.2301 0.912 0.060 0.936 0.004
#> SRR1100752 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1391494 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1333263 2 0.2301 0.912 0.060 0.936 0.004
#> SRR1310231 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1094144 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1092160 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1320300 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1322747 2 0.2301 0.912 0.060 0.936 0.004
#> SRR1432719 3 0.2066 0.964 0.060 0.000 0.940
#> SRR1100728 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1087511 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1470336 1 0.2261 0.957 0.932 0.068 0.000
#> SRR1322536 1 0.3038 0.928 0.896 0.104 0.000
#> SRR1100824 1 0.2066 0.956 0.940 0.060 0.000
#> SRR1085951 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1322046 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1316420 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1070913 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1345806 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1313872 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1337666 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1076823 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1093954 2 0.0000 0.965 0.000 1.000 0.000
#> SRR1451921 2 0.2796 0.879 0.092 0.908 0.000
#> SRR1491257 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1416979 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1419015 2 0.6252 0.175 0.444 0.556 0.000
#> SRR817649 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1466376 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1392055 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1120913 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1120869 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1319419 3 0.2066 0.964 0.060 0.000 0.940
#> SRR816495 3 0.0237 0.985 0.004 0.000 0.996
#> SRR818694 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1465653 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1475952 1 0.2261 0.957 0.932 0.068 0.000
#> SRR1465040 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1088461 2 0.0424 0.965 0.008 0.992 0.000
#> SRR810129 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1400141 3 0.0424 0.984 0.008 0.000 0.992
#> SRR1349585 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1437576 2 0.1289 0.943 0.032 0.968 0.000
#> SRR814407 1 0.0475 0.880 0.992 0.004 0.004
#> SRR1332403 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1099598 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1327723 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1392525 2 0.2400 0.911 0.064 0.932 0.004
#> SRR1320536 1 0.2261 0.960 0.932 0.068 0.000
#> SRR1083824 2 0.2301 0.912 0.060 0.936 0.004
#> SRR1351390 1 0.2537 0.950 0.920 0.080 0.000
#> SRR1309141 2 0.2400 0.911 0.064 0.932 0.004
#> SRR1452803 2 0.0237 0.965 0.004 0.996 0.000
#> SRR811631 2 0.2400 0.911 0.064 0.932 0.004
#> SRR1485563 2 0.0424 0.965 0.008 0.992 0.000
#> SRR1311531 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1353076 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1480831 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1083892 1 0.2448 0.955 0.924 0.076 0.000
#> SRR809873 2 0.6225 0.178 0.432 0.568 0.000
#> SRR1341854 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1399335 2 0.0424 0.965 0.008 0.992 0.000
#> SRR1464209 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1389886 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1400730 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1448008 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1087606 1 0.2537 0.951 0.920 0.080 0.000
#> SRR1445111 1 0.2066 0.958 0.940 0.060 0.000
#> SRR816865 2 0.0237 0.965 0.004 0.996 0.000
#> SRR1323360 3 0.0237 0.985 0.004 0.000 0.996
#> SRR1417364 3 0.2066 0.964 0.060 0.000 0.940
#> SRR1480329 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1403322 1 0.5968 0.506 0.636 0.364 0.000
#> SRR1093625 1 0.2165 0.959 0.936 0.064 0.000
#> SRR1479977 2 0.0237 0.964 0.004 0.996 0.000
#> SRR1082035 2 0.0424 0.965 0.008 0.992 0.000
#> SRR1393046 2 0.1411 0.940 0.036 0.964 0.000
#> SRR1466663 2 0.1529 0.935 0.040 0.960 0.000
#> SRR1384456 1 0.2261 0.960 0.932 0.068 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.1389 0.8348 0.000 0.952 0.000 0.048
#> SRR808862 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1500382 2 0.1557 0.8379 0.000 0.944 0.000 0.056
#> SRR1322683 2 0.2281 0.8226 0.000 0.904 0.000 0.096
#> SRR1329811 1 0.5326 0.3287 0.604 0.016 0.000 0.380
#> SRR1087297 2 0.0188 0.8355 0.000 0.996 0.000 0.004
#> SRR1072626 2 0.2868 0.8215 0.000 0.864 0.000 0.136
#> SRR1407428 1 0.1743 0.5649 0.940 0.004 0.000 0.056
#> SRR1321029 2 0.2011 0.8253 0.000 0.920 0.000 0.080
#> SRR1500282 1 0.4188 0.4985 0.752 0.004 0.000 0.244
#> SRR1100496 3 0.0336 0.9119 0.000 0.000 0.992 0.008
#> SRR1308778 2 0.2149 0.8324 0.000 0.912 0.000 0.088
#> SRR1445304 2 0.1637 0.8376 0.000 0.940 0.000 0.060
#> SRR1099378 4 0.7640 0.0000 0.316 0.228 0.000 0.456
#> SRR1347412 1 0.4697 0.3335 0.644 0.000 0.000 0.356
#> SRR1099694 2 0.2011 0.8310 0.000 0.920 0.000 0.080
#> SRR1088365 2 0.3569 0.7986 0.000 0.804 0.000 0.196
#> SRR1325752 2 0.2944 0.8155 0.004 0.868 0.000 0.128
#> SRR1416713 2 0.0469 0.8365 0.000 0.988 0.000 0.012
#> SRR1074474 1 0.0188 0.5787 0.996 0.004 0.000 0.000
#> SRR1469369 3 0.4072 0.7909 0.000 0.000 0.748 0.252
#> SRR1400507 2 0.1792 0.8317 0.000 0.932 0.000 0.068
#> SRR1378179 2 0.2216 0.8307 0.000 0.908 0.000 0.092
#> SRR1377905 2 0.1716 0.8294 0.000 0.936 0.000 0.064
#> SRR1089479 1 0.1824 0.5728 0.936 0.004 0.000 0.060
#> SRR1073365 2 0.2281 0.8353 0.000 0.904 0.000 0.096
#> SRR1500306 1 0.3907 0.4779 0.828 0.032 0.000 0.140
#> SRR1101566 2 0.2345 0.8236 0.000 0.900 0.000 0.100
#> SRR1350503 3 0.4072 0.7909 0.000 0.000 0.748 0.252
#> SRR1446007 3 0.0188 0.9127 0.000 0.000 0.996 0.004
#> SRR1102875 2 0.3311 0.7977 0.000 0.828 0.000 0.172
#> SRR1380293 2 0.2814 0.7750 0.000 0.868 0.000 0.132
#> SRR1331198 2 0.2408 0.7811 0.000 0.896 0.000 0.104
#> SRR1092686 3 0.0000 0.9128 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.3219 0.7998 0.000 0.836 0.000 0.164
#> SRR1341650 2 0.3569 0.7969 0.000 0.804 0.000 0.196
#> SRR1357276 2 0.0817 0.8338 0.000 0.976 0.000 0.024
#> SRR1498374 2 0.2011 0.8289 0.000 0.920 0.000 0.080
#> SRR1093721 2 0.1792 0.8372 0.000 0.932 0.000 0.068
#> SRR1464660 1 0.5326 0.3287 0.604 0.016 0.000 0.380
#> SRR1402051 2 0.5766 0.5902 0.104 0.704 0.000 0.192
#> SRR1488734 2 0.1302 0.8388 0.000 0.956 0.000 0.044
#> SRR1082616 3 0.4564 0.7217 0.000 0.000 0.672 0.328
#> SRR1099427 2 0.3837 0.6870 0.000 0.776 0.000 0.224
#> SRR1453093 2 0.4040 0.7353 0.000 0.752 0.000 0.248
#> SRR1357064 1 0.4855 0.3867 0.644 0.004 0.000 0.352
#> SRR811237 2 0.3486 0.7968 0.000 0.812 0.000 0.188
#> SRR1100848 2 0.3172 0.7658 0.000 0.840 0.000 0.160
#> SRR1346755 2 0.2011 0.8260 0.000 0.920 0.000 0.080
#> SRR1472529 2 0.1867 0.8314 0.000 0.928 0.000 0.072
#> SRR1398905 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1082733 2 0.2647 0.8233 0.000 0.880 0.000 0.120
#> SRR1308035 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1466445 3 0.0188 0.9127 0.000 0.000 0.996 0.004
#> SRR1359080 2 0.1637 0.8297 0.000 0.940 0.000 0.060
#> SRR1455825 2 0.1022 0.8370 0.000 0.968 0.000 0.032
#> SRR1389300 2 0.0921 0.8333 0.000 0.972 0.000 0.028
#> SRR812246 3 0.0000 0.9128 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.3172 0.7969 0.000 0.840 0.000 0.160
#> SRR1415567 1 0.1004 0.5749 0.972 0.004 0.000 0.024
#> SRR1331900 2 0.1474 0.8346 0.000 0.948 0.000 0.052
#> SRR1452099 2 0.7475 -0.4158 0.180 0.448 0.000 0.372
#> SRR1352346 2 0.3048 0.8277 0.016 0.876 0.000 0.108
#> SRR1364034 2 0.3219 0.7969 0.000 0.836 0.000 0.164
#> SRR1086046 2 0.7860 -0.2482 0.292 0.396 0.000 0.312
#> SRR1407226 1 0.3831 0.4868 0.792 0.004 0.000 0.204
#> SRR1319363 2 0.7506 0.1127 0.288 0.492 0.000 0.220
#> SRR1446961 3 0.6464 0.5912 0.000 0.096 0.596 0.308
#> SRR1486650 1 0.0524 0.5788 0.988 0.004 0.000 0.008
#> SRR1470152 1 0.5326 0.3287 0.604 0.016 0.000 0.380
#> SRR1454785 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1092329 2 0.2081 0.8283 0.000 0.916 0.000 0.084
#> SRR1091476 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1073775 2 0.2647 0.8255 0.000 0.880 0.000 0.120
#> SRR1366873 2 0.1867 0.8306 0.000 0.928 0.000 0.072
#> SRR1398114 2 0.2345 0.8331 0.000 0.900 0.000 0.100
#> SRR1089950 1 0.7082 -0.2663 0.540 0.152 0.000 0.308
#> SRR1433272 2 0.3266 0.7482 0.000 0.832 0.000 0.168
#> SRR1075314 1 0.5592 0.2443 0.656 0.044 0.000 0.300
#> SRR1085590 2 0.5746 0.3934 0.004 0.600 0.028 0.368
#> SRR1100752 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1391494 2 0.1940 0.8282 0.000 0.924 0.000 0.076
#> SRR1333263 2 0.5349 0.4053 0.004 0.616 0.012 0.368
#> SRR1310231 2 0.0707 0.8379 0.000 0.980 0.000 0.020
#> SRR1094144 2 0.3400 0.7913 0.000 0.820 0.000 0.180
#> SRR1092160 2 0.3024 0.7326 0.000 0.852 0.000 0.148
#> SRR1320300 2 0.2345 0.8370 0.000 0.900 0.000 0.100
#> SRR1322747 2 0.4277 0.5480 0.000 0.720 0.000 0.280
#> SRR1432719 3 0.4072 0.7909 0.000 0.000 0.748 0.252
#> SRR1100728 2 0.3219 0.7969 0.000 0.836 0.000 0.164
#> SRR1087511 2 0.4431 0.7104 0.000 0.696 0.000 0.304
#> SRR1470336 1 0.2976 0.5283 0.872 0.008 0.000 0.120
#> SRR1322536 1 0.5432 0.2448 0.652 0.032 0.000 0.316
#> SRR1100824 1 0.5004 0.3603 0.604 0.004 0.000 0.392
#> SRR1085951 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1322046 2 0.0188 0.8349 0.000 0.996 0.000 0.004
#> SRR1316420 1 0.4819 0.3976 0.652 0.004 0.000 0.344
#> SRR1070913 2 0.1792 0.8327 0.000 0.932 0.000 0.068
#> SRR1345806 3 0.0188 0.9127 0.000 0.000 0.996 0.004
#> SRR1313872 2 0.0921 0.8369 0.000 0.972 0.000 0.028
#> SRR1337666 2 0.2647 0.7753 0.000 0.880 0.000 0.120
#> SRR1076823 1 0.4576 0.3654 0.728 0.012 0.000 0.260
#> SRR1093954 2 0.3266 0.8007 0.000 0.832 0.000 0.168
#> SRR1451921 2 0.7802 -0.0998 0.276 0.420 0.000 0.304
#> SRR1491257 1 0.4872 0.3846 0.640 0.004 0.000 0.356
#> SRR1416979 2 0.1474 0.8365 0.000 0.948 0.000 0.052
#> SRR1419015 2 0.7740 -0.1217 0.328 0.428 0.000 0.244
#> SRR817649 2 0.2647 0.7639 0.000 0.880 0.000 0.120
#> SRR1466376 2 0.0188 0.8349 0.000 0.996 0.000 0.004
#> SRR1392055 2 0.1557 0.8340 0.000 0.944 0.000 0.056
#> SRR1120913 2 0.0469 0.8345 0.000 0.988 0.000 0.012
#> SRR1120869 2 0.2973 0.8087 0.000 0.856 0.000 0.144
#> SRR1319419 3 0.4072 0.7909 0.000 0.000 0.748 0.252
#> SRR816495 3 0.0188 0.9127 0.000 0.000 0.996 0.004
#> SRR818694 2 0.3975 0.7459 0.000 0.760 0.000 0.240
#> SRR1465653 1 0.5400 0.3248 0.608 0.020 0.000 0.372
#> SRR1475952 1 0.2466 0.5452 0.900 0.004 0.000 0.096
#> SRR1465040 3 0.0921 0.9113 0.000 0.000 0.972 0.028
#> SRR1088461 2 0.2149 0.8387 0.000 0.912 0.000 0.088
#> SRR810129 2 0.2081 0.8364 0.000 0.916 0.000 0.084
#> SRR1400141 3 0.1557 0.8948 0.000 0.000 0.944 0.056
#> SRR1349585 1 0.3668 0.5173 0.808 0.004 0.000 0.188
#> SRR1437576 2 0.1792 0.8288 0.000 0.932 0.000 0.068
#> SRR814407 1 0.4967 0.3509 0.548 0.000 0.000 0.452
#> SRR1332403 2 0.1557 0.8377 0.000 0.944 0.000 0.056
#> SRR1099598 2 0.3649 0.7957 0.000 0.796 0.000 0.204
#> SRR1327723 2 0.0921 0.8391 0.000 0.972 0.000 0.028
#> SRR1392525 2 0.5509 0.3921 0.004 0.560 0.012 0.424
#> SRR1320536 1 0.0524 0.5788 0.988 0.004 0.000 0.008
#> SRR1083824 2 0.5130 0.4444 0.000 0.652 0.016 0.332
#> SRR1351390 1 0.5712 0.3451 0.584 0.032 0.000 0.384
#> SRR1309141 2 0.5232 0.4564 0.004 0.644 0.012 0.340
#> SRR1452803 2 0.0707 0.8379 0.000 0.980 0.000 0.020
#> SRR811631 2 0.4605 0.5006 0.000 0.664 0.000 0.336
#> SRR1485563 2 0.3400 0.8067 0.000 0.820 0.000 0.180
#> SRR1311531 3 0.0000 0.9128 0.000 0.000 1.000 0.000
#> SRR1353076 2 0.3726 0.7957 0.000 0.788 0.000 0.212
#> SRR1480831 2 0.3024 0.8081 0.000 0.852 0.000 0.148
#> SRR1083892 1 0.5698 0.2957 0.608 0.036 0.000 0.356
#> SRR809873 1 0.7758 -0.2680 0.432 0.260 0.000 0.308
#> SRR1341854 2 0.2149 0.8319 0.000 0.912 0.000 0.088
#> SRR1399335 2 0.1474 0.8356 0.000 0.948 0.000 0.052
#> SRR1464209 1 0.4889 0.3829 0.636 0.004 0.000 0.360
#> SRR1389886 2 0.1022 0.8382 0.000 0.968 0.000 0.032
#> SRR1400730 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1448008 2 0.2760 0.8151 0.000 0.872 0.000 0.128
#> SRR1087606 1 0.5856 0.1592 0.504 0.032 0.000 0.464
#> SRR1445111 1 0.1004 0.5795 0.972 0.004 0.000 0.024
#> SRR816865 2 0.3356 0.7924 0.000 0.824 0.000 0.176
#> SRR1323360 3 0.1109 0.9115 0.004 0.000 0.968 0.028
#> SRR1417364 3 0.4072 0.7909 0.000 0.000 0.748 0.252
#> SRR1480329 2 0.1211 0.8401 0.000 0.960 0.000 0.040
#> SRR1403322 1 0.6336 0.1081 0.608 0.088 0.000 0.304
#> SRR1093625 1 0.0188 0.5787 0.996 0.004 0.000 0.000
#> SRR1479977 2 0.2081 0.8293 0.000 0.916 0.000 0.084
#> SRR1082035 2 0.3172 0.8197 0.000 0.840 0.000 0.160
#> SRR1393046 2 0.1940 0.8253 0.000 0.924 0.000 0.076
#> SRR1466663 2 0.3764 0.7913 0.072 0.852 0.000 0.076
#> SRR1384456 1 0.0524 0.5788 0.988 0.004 0.000 0.008
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.3422 0.7154 0.004 0.792 0.000 0.200 0.004
#> SRR808862 3 0.0963 0.8294 0.036 0.000 0.964 0.000 0.000
#> SRR1500382 2 0.2170 0.7378 0.004 0.904 0.000 0.088 0.004
#> SRR1322683 2 0.5379 0.6192 0.064 0.608 0.000 0.324 0.004
#> SRR1329811 5 0.1522 0.6945 0.000 0.012 0.000 0.044 0.944
#> SRR1087297 2 0.2677 0.7218 0.000 0.872 0.000 0.112 0.016
#> SRR1072626 2 0.3081 0.7244 0.072 0.868 0.000 0.056 0.004
#> SRR1407428 1 0.3612 0.5058 0.732 0.000 0.000 0.000 0.268
#> SRR1321029 2 0.4512 0.6625 0.020 0.676 0.000 0.300 0.004
#> SRR1500282 5 0.3013 0.5356 0.160 0.000 0.000 0.008 0.832
#> SRR1100496 3 0.2690 0.8184 0.000 0.000 0.844 0.156 0.000
#> SRR1308778 2 0.1306 0.7278 0.008 0.960 0.000 0.016 0.016
#> SRR1445304 2 0.2445 0.7379 0.004 0.884 0.000 0.108 0.004
#> SRR1099378 5 0.6407 0.3398 0.040 0.208 0.000 0.140 0.612
#> SRR1347412 5 0.6733 0.0889 0.296 0.000 0.000 0.288 0.416
#> SRR1099694 2 0.3495 0.6999 0.000 0.816 0.000 0.152 0.032
#> SRR1088365 2 0.5083 0.6485 0.136 0.712 0.000 0.148 0.004
#> SRR1325752 2 0.2522 0.7111 0.012 0.904 0.000 0.056 0.028
#> SRR1416713 2 0.2046 0.7337 0.000 0.916 0.000 0.068 0.016
#> SRR1074474 1 0.4287 0.3772 0.540 0.000 0.000 0.000 0.460
#> SRR1469369 3 0.4452 0.4110 0.004 0.000 0.500 0.496 0.000
#> SRR1400507 2 0.4907 0.6729 0.052 0.680 0.000 0.264 0.004
#> SRR1378179 2 0.1405 0.7261 0.008 0.956 0.000 0.020 0.016
#> SRR1377905 2 0.4268 0.6694 0.004 0.708 0.000 0.272 0.016
#> SRR1089479 1 0.4108 0.4806 0.684 0.000 0.000 0.008 0.308
#> SRR1073365 2 0.2313 0.7359 0.040 0.912 0.000 0.044 0.004
#> SRR1500306 1 0.4878 0.4687 0.720 0.012 0.000 0.060 0.208
#> SRR1101566 2 0.5312 0.6334 0.064 0.624 0.000 0.308 0.004
#> SRR1350503 3 0.4451 0.4162 0.004 0.000 0.504 0.492 0.000
#> SRR1446007 3 0.2605 0.8226 0.000 0.000 0.852 0.148 0.000
#> SRR1102875 2 0.4425 0.6619 0.112 0.772 0.000 0.112 0.004
#> SRR1380293 2 0.5211 0.6226 0.004 0.664 0.000 0.256 0.076
#> SRR1331198 2 0.4252 0.6605 0.000 0.764 0.000 0.172 0.064
#> SRR1092686 3 0.2329 0.8283 0.000 0.000 0.876 0.124 0.000
#> SRR1069421 2 0.4191 0.6612 0.084 0.804 0.000 0.096 0.016
#> SRR1341650 2 0.4816 0.6552 0.096 0.732 0.000 0.168 0.004
#> SRR1357276 2 0.3333 0.7060 0.004 0.788 0.000 0.208 0.000
#> SRR1498374 2 0.5200 0.6461 0.060 0.640 0.000 0.296 0.004
#> SRR1093721 2 0.4060 0.7151 0.052 0.788 0.000 0.156 0.004
#> SRR1464660 5 0.1522 0.6945 0.000 0.012 0.000 0.044 0.944
#> SRR1402051 2 0.7247 0.3669 0.180 0.436 0.000 0.344 0.040
#> SRR1488734 2 0.0566 0.7349 0.000 0.984 0.000 0.012 0.004
#> SRR1082616 4 0.4705 -0.3127 0.012 0.000 0.404 0.580 0.004
#> SRR1099427 2 0.4815 0.3423 0.020 0.524 0.000 0.456 0.000
#> SRR1453093 2 0.5879 0.4720 0.236 0.612 0.000 0.148 0.004
#> SRR1357064 5 0.0854 0.6816 0.012 0.008 0.000 0.004 0.976
#> SRR811237 2 0.4557 0.6651 0.132 0.760 0.000 0.104 0.004
#> SRR1100848 2 0.4355 0.6490 0.000 0.760 0.000 0.164 0.076
#> SRR1346755 2 0.4419 0.6498 0.020 0.668 0.000 0.312 0.000
#> SRR1472529 2 0.5119 0.6641 0.060 0.656 0.000 0.280 0.004
#> SRR1398905 3 0.1043 0.8296 0.040 0.000 0.960 0.000 0.000
#> SRR1082733 2 0.2353 0.7330 0.028 0.908 0.000 0.060 0.004
#> SRR1308035 3 0.0963 0.8294 0.036 0.000 0.964 0.000 0.000
#> SRR1466445 3 0.2605 0.8226 0.000 0.000 0.852 0.148 0.000
#> SRR1359080 2 0.4194 0.6809 0.004 0.720 0.000 0.260 0.016
#> SRR1455825 2 0.4139 0.7137 0.052 0.780 0.000 0.164 0.004
#> SRR1389300 2 0.3734 0.6935 0.004 0.752 0.000 0.240 0.004
#> SRR812246 3 0.2280 0.8289 0.000 0.000 0.880 0.120 0.000
#> SRR1076632 2 0.3702 0.6707 0.084 0.820 0.000 0.096 0.000
#> SRR1415567 1 0.4150 0.4439 0.612 0.000 0.000 0.000 0.388
#> SRR1331900 2 0.4922 0.6744 0.056 0.684 0.000 0.256 0.004
#> SRR1452099 2 0.7898 -0.1018 0.100 0.376 0.000 0.176 0.348
#> SRR1352346 2 0.3163 0.7283 0.028 0.872 0.000 0.072 0.028
#> SRR1364034 2 0.3532 0.6726 0.076 0.832 0.000 0.092 0.000
#> SRR1086046 1 0.6898 0.1375 0.512 0.232 0.000 0.232 0.024
#> SRR1407226 5 0.7551 -0.0832 0.308 0.152 0.000 0.084 0.456
#> SRR1319363 2 0.7203 0.3797 0.188 0.560 0.000 0.140 0.112
#> SRR1446961 4 0.3970 0.2742 0.004 0.012 0.220 0.760 0.004
#> SRR1486650 1 0.4291 0.3709 0.536 0.000 0.000 0.000 0.464
#> SRR1470152 5 0.1522 0.6945 0.000 0.012 0.000 0.044 0.944
#> SRR1454785 3 0.0992 0.8315 0.024 0.000 0.968 0.008 0.000
#> SRR1092329 2 0.5255 0.6376 0.060 0.628 0.000 0.308 0.004
#> SRR1091476 3 0.1043 0.8296 0.040 0.000 0.960 0.000 0.000
#> SRR1073775 2 0.5166 0.6587 0.100 0.692 0.000 0.204 0.004
#> SRR1366873 2 0.5053 0.6660 0.060 0.668 0.000 0.268 0.004
#> SRR1398114 2 0.2448 0.7383 0.020 0.892 0.000 0.088 0.000
#> SRR1089950 5 0.6298 0.3731 0.148 0.192 0.000 0.036 0.624
#> SRR1433272 2 0.4082 0.6115 0.008 0.796 0.000 0.056 0.140
#> SRR1075314 1 0.4481 0.4852 0.788 0.032 0.000 0.120 0.060
#> SRR1085590 4 0.4296 0.6266 0.008 0.292 0.000 0.692 0.008
#> SRR1100752 3 0.1043 0.8296 0.040 0.000 0.960 0.000 0.000
#> SRR1391494 2 0.4290 0.6559 0.016 0.680 0.000 0.304 0.000
#> SRR1333263 4 0.3883 0.6240 0.004 0.244 0.000 0.744 0.008
#> SRR1310231 2 0.0510 0.7363 0.000 0.984 0.000 0.016 0.000
#> SRR1094144 2 0.4169 0.6556 0.100 0.784 0.000 0.116 0.000
#> SRR1092160 2 0.4772 0.6093 0.000 0.728 0.000 0.164 0.108
#> SRR1320300 2 0.3148 0.7339 0.060 0.864 0.000 0.072 0.004
#> SRR1322747 4 0.4242 0.4155 0.000 0.428 0.000 0.572 0.000
#> SRR1432719 3 0.4452 0.4110 0.004 0.000 0.500 0.496 0.000
#> SRR1100728 2 0.3697 0.6672 0.080 0.820 0.000 0.100 0.000
#> SRR1087511 2 0.6896 0.3085 0.288 0.400 0.000 0.308 0.004
#> SRR1470336 1 0.4009 0.5138 0.792 0.008 0.000 0.040 0.160
#> SRR1322536 1 0.4356 0.4856 0.784 0.016 0.000 0.140 0.060
#> SRR1100824 5 0.2054 0.6852 0.028 0.000 0.000 0.052 0.920
#> SRR1085951 3 0.1043 0.8296 0.040 0.000 0.960 0.000 0.000
#> SRR1322046 2 0.2873 0.7161 0.000 0.856 0.000 0.128 0.016
#> SRR1316420 5 0.0963 0.6618 0.036 0.000 0.000 0.000 0.964
#> SRR1070913 2 0.5037 0.6683 0.056 0.664 0.000 0.276 0.004
#> SRR1345806 3 0.2605 0.8226 0.000 0.000 0.852 0.148 0.000
#> SRR1313872 2 0.2171 0.7320 0.000 0.912 0.000 0.064 0.024
#> SRR1337666 2 0.4923 0.6214 0.000 0.680 0.000 0.252 0.068
#> SRR1076823 1 0.3970 0.5119 0.800 0.000 0.000 0.096 0.104
#> SRR1093954 2 0.4425 0.6630 0.112 0.772 0.000 0.112 0.004
#> SRR1451921 1 0.5832 0.3081 0.624 0.240 0.000 0.128 0.008
#> SRR1491257 5 0.1195 0.6738 0.028 0.000 0.000 0.012 0.960
#> SRR1416979 2 0.2753 0.7181 0.000 0.856 0.000 0.136 0.008
#> SRR1419015 2 0.8089 0.0741 0.256 0.416 0.000 0.192 0.136
#> SRR817649 2 0.4412 0.6439 0.000 0.756 0.000 0.164 0.080
#> SRR1466376 2 0.2522 0.7265 0.000 0.880 0.000 0.108 0.012
#> SRR1392055 2 0.4793 0.6893 0.056 0.704 0.000 0.236 0.004
#> SRR1120913 2 0.2966 0.7211 0.000 0.848 0.000 0.136 0.016
#> SRR1120869 2 0.2710 0.7064 0.036 0.892 0.000 0.064 0.008
#> SRR1319419 3 0.4451 0.4162 0.004 0.000 0.504 0.492 0.000
#> SRR816495 3 0.2605 0.8226 0.000 0.000 0.852 0.148 0.000
#> SRR818694 2 0.6366 0.4787 0.212 0.544 0.000 0.240 0.004
#> SRR1465653 5 0.1444 0.6942 0.000 0.012 0.000 0.040 0.948
#> SRR1475952 1 0.3196 0.5207 0.804 0.000 0.000 0.004 0.192
#> SRR1465040 3 0.0898 0.8315 0.020 0.000 0.972 0.008 0.000
#> SRR1088461 2 0.3293 0.7247 0.008 0.824 0.000 0.160 0.008
#> SRR810129 2 0.2466 0.7388 0.012 0.900 0.000 0.076 0.012
#> SRR1400141 3 0.3480 0.7474 0.000 0.000 0.752 0.248 0.000
#> SRR1349585 5 0.3366 0.4088 0.232 0.000 0.000 0.000 0.768
#> SRR1437576 2 0.4442 0.6453 0.016 0.676 0.000 0.304 0.004
#> SRR814407 5 0.6296 0.0574 0.408 0.000 0.000 0.152 0.440
#> SRR1332403 2 0.0740 0.7316 0.008 0.980 0.000 0.008 0.004
#> SRR1099598 2 0.5084 0.6423 0.140 0.712 0.000 0.144 0.004
#> SRR1327723 2 0.2074 0.7331 0.004 0.920 0.000 0.060 0.016
#> SRR1392525 4 0.4608 0.5820 0.036 0.260 0.000 0.700 0.004
#> SRR1320536 1 0.4291 0.3709 0.536 0.000 0.000 0.000 0.464
#> SRR1083824 4 0.3728 0.6390 0.000 0.244 0.000 0.748 0.008
#> SRR1351390 5 0.5753 0.0352 0.456 0.012 0.000 0.056 0.476
#> SRR1309141 4 0.3992 0.5944 0.004 0.280 0.000 0.712 0.004
#> SRR1452803 2 0.1386 0.7326 0.000 0.952 0.000 0.032 0.016
#> SRR811631 4 0.3876 0.4784 0.000 0.316 0.000 0.684 0.000
#> SRR1485563 2 0.4425 0.6903 0.112 0.772 0.000 0.112 0.004
#> SRR1311531 3 0.1851 0.8316 0.000 0.000 0.912 0.088 0.000
#> SRR1353076 2 0.5497 0.6344 0.136 0.664 0.000 0.196 0.004
#> SRR1480831 2 0.2308 0.7131 0.036 0.912 0.000 0.048 0.004
#> SRR1083892 5 0.1913 0.6736 0.008 0.044 0.000 0.016 0.932
#> SRR809873 1 0.6859 0.2781 0.552 0.252 0.000 0.148 0.048
#> SRR1341854 2 0.1405 0.7275 0.008 0.956 0.000 0.020 0.016
#> SRR1399335 2 0.3006 0.7240 0.004 0.836 0.000 0.156 0.004
#> SRR1464209 5 0.1116 0.6899 0.004 0.004 0.000 0.028 0.964
#> SRR1389886 2 0.1041 0.7393 0.000 0.964 0.000 0.032 0.004
#> SRR1400730 3 0.1043 0.8296 0.040 0.000 0.960 0.000 0.000
#> SRR1448008 2 0.5630 0.5590 0.164 0.652 0.000 0.180 0.004
#> SRR1087606 5 0.4638 0.5606 0.160 0.032 0.000 0.044 0.764
#> SRR1445111 1 0.4533 0.3663 0.544 0.000 0.000 0.008 0.448
#> SRR816865 2 0.3810 0.6610 0.088 0.812 0.000 0.100 0.000
#> SRR1323360 3 0.0880 0.8298 0.032 0.000 0.968 0.000 0.000
#> SRR1417364 4 0.4451 -0.4798 0.004 0.000 0.492 0.504 0.000
#> SRR1480329 2 0.4139 0.7177 0.052 0.780 0.000 0.164 0.004
#> SRR1403322 1 0.4218 0.4970 0.804 0.024 0.000 0.112 0.060
#> SRR1093625 1 0.4278 0.3868 0.548 0.000 0.000 0.000 0.452
#> SRR1479977 2 0.4996 0.6656 0.052 0.664 0.000 0.280 0.004
#> SRR1082035 2 0.5003 0.6653 0.072 0.692 0.000 0.232 0.004
#> SRR1393046 2 0.4579 0.6274 0.008 0.668 0.000 0.308 0.016
#> SRR1466663 2 0.3926 0.7148 0.008 0.808 0.000 0.132 0.052
#> SRR1384456 1 0.4291 0.3709 0.536 0.000 0.000 0.000 0.464
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.4543 0.60606 0.024 0.740 0.000 0.100 0.000 0.136
#> SRR808862 3 0.1225 0.83169 0.012 0.000 0.952 0.000 0.000 0.036
#> SRR1500382 2 0.4010 0.60879 0.020 0.764 0.000 0.040 0.000 0.176
#> SRR1322683 2 0.6054 0.48231 0.032 0.568 0.000 0.128 0.008 0.264
#> SRR1329811 5 0.0520 0.73547 0.000 0.008 0.000 0.008 0.984 0.000
#> SRR1087297 2 0.0551 0.63113 0.000 0.984 0.000 0.004 0.008 0.004
#> SRR1072626 2 0.3867 0.49127 0.000 0.660 0.000 0.012 0.000 0.328
#> SRR1407428 1 0.2162 0.67082 0.896 0.000 0.000 0.012 0.088 0.004
#> SRR1321029 2 0.5578 0.54434 0.032 0.628 0.000 0.140 0.000 0.200
#> SRR1500282 5 0.3428 0.61048 0.152 0.000 0.000 0.016 0.808 0.024
#> SRR1100496 3 0.3881 0.74050 0.004 0.000 0.720 0.252 0.000 0.024
#> SRR1308778 2 0.3037 0.56441 0.000 0.820 0.000 0.016 0.004 0.160
#> SRR1445304 2 0.4737 0.57395 0.024 0.688 0.000 0.044 0.004 0.240
#> SRR1099378 5 0.4955 0.49585 0.024 0.184 0.000 0.044 0.716 0.032
#> SRR1347412 4 0.6383 -0.34777 0.356 0.000 0.000 0.356 0.276 0.012
#> SRR1099694 2 0.2750 0.60989 0.008 0.888 0.000 0.028 0.036 0.040
#> SRR1088365 6 0.3942 0.11630 0.000 0.368 0.000 0.004 0.004 0.624
#> SRR1325752 2 0.3579 0.52843 0.004 0.784 0.000 0.020 0.008 0.184
#> SRR1416713 2 0.0858 0.62960 0.000 0.968 0.000 0.000 0.004 0.028
#> SRR1074474 1 0.3608 0.64000 0.716 0.000 0.000 0.012 0.272 0.000
#> SRR1469369 4 0.3840 0.37043 0.000 0.000 0.284 0.696 0.000 0.020
#> SRR1400507 2 0.5560 0.53100 0.032 0.616 0.000 0.112 0.000 0.240
#> SRR1378179 2 0.2462 0.58157 0.000 0.860 0.000 0.004 0.004 0.132
#> SRR1377905 2 0.4124 0.61131 0.028 0.796 0.000 0.104 0.012 0.060
#> SRR1089479 1 0.3931 0.63476 0.768 0.000 0.000 0.048 0.172 0.012
#> SRR1073365 2 0.3822 0.51333 0.004 0.688 0.000 0.004 0.004 0.300
#> SRR1500306 1 0.6995 0.32059 0.464 0.000 0.000 0.108 0.188 0.240
#> SRR1101566 2 0.6023 0.46354 0.032 0.536 0.000 0.140 0.000 0.292
#> SRR1350503 4 0.3879 0.35901 0.000 0.000 0.292 0.688 0.000 0.020
#> SRR1446007 3 0.3650 0.78183 0.004 0.000 0.756 0.216 0.000 0.024
#> SRR1102875 6 0.3975 0.02062 0.000 0.452 0.000 0.000 0.004 0.544
#> SRR1380293 2 0.4794 0.56888 0.016 0.752 0.000 0.068 0.116 0.048
#> SRR1331198 2 0.2635 0.59500 0.008 0.884 0.000 0.036 0.068 0.004
#> SRR1092686 3 0.3343 0.80435 0.004 0.000 0.796 0.176 0.000 0.024
#> SRR1069421 2 0.4650 0.00468 0.000 0.512 0.000 0.016 0.016 0.456
#> SRR1341650 6 0.4947 0.05572 0.004 0.424 0.000 0.032 0.012 0.528
#> SRR1357276 2 0.2340 0.64158 0.004 0.896 0.000 0.044 0.000 0.056
#> SRR1498374 2 0.5812 0.51140 0.032 0.584 0.000 0.136 0.000 0.248
#> SRR1093721 2 0.3613 0.57118 0.008 0.772 0.000 0.024 0.000 0.196
#> SRR1464660 5 0.0520 0.73547 0.000 0.008 0.000 0.008 0.984 0.000
#> SRR1402051 6 0.6739 -0.13519 0.052 0.380 0.000 0.104 0.024 0.440
#> SRR1488734 2 0.2692 0.59575 0.000 0.840 0.000 0.012 0.000 0.148
#> SRR1082616 4 0.3808 0.43130 0.000 0.000 0.228 0.736 0.000 0.036
#> SRR1099427 2 0.6141 0.36943 0.032 0.508 0.000 0.312 0.000 0.148
#> SRR1453093 6 0.5270 0.41421 0.056 0.248 0.000 0.052 0.000 0.644
#> SRR1357064 5 0.2290 0.70346 0.084 0.000 0.000 0.020 0.892 0.004
#> SRR811237 2 0.4096 0.09159 0.000 0.508 0.000 0.008 0.000 0.484
#> SRR1100848 2 0.3753 0.53979 0.008 0.812 0.000 0.028 0.120 0.032
#> SRR1346755 2 0.5578 0.56240 0.032 0.668 0.000 0.132 0.016 0.152
#> SRR1472529 2 0.5524 0.52415 0.032 0.612 0.000 0.100 0.000 0.256
#> SRR1398905 3 0.1245 0.83190 0.016 0.000 0.952 0.000 0.000 0.032
#> SRR1082733 2 0.3782 0.41971 0.000 0.636 0.000 0.000 0.004 0.360
#> SRR1308035 3 0.1225 0.83169 0.012 0.000 0.952 0.000 0.000 0.036
#> SRR1466445 3 0.3650 0.78183 0.004 0.000 0.756 0.216 0.000 0.024
#> SRR1359080 2 0.4007 0.61250 0.024 0.796 0.000 0.104 0.004 0.072
#> SRR1455825 2 0.3820 0.57155 0.008 0.756 0.000 0.032 0.000 0.204
#> SRR1389300 2 0.4680 0.60893 0.028 0.736 0.000 0.084 0.004 0.148
#> SRR812246 3 0.3343 0.80435 0.004 0.000 0.796 0.176 0.000 0.024
#> SRR1076632 2 0.4498 -0.00551 0.000 0.504 0.000 0.012 0.012 0.472
#> SRR1415567 1 0.2631 0.67796 0.840 0.000 0.000 0.008 0.152 0.000
#> SRR1331900 2 0.5303 0.54307 0.024 0.636 0.000 0.100 0.000 0.240
#> SRR1452099 2 0.6978 -0.09072 0.024 0.436 0.000 0.048 0.340 0.152
#> SRR1352346 2 0.4722 0.54405 0.032 0.712 0.000 0.040 0.008 0.208
#> SRR1364034 2 0.4284 0.05501 0.000 0.544 0.000 0.012 0.004 0.440
#> SRR1086046 6 0.6959 0.19266 0.256 0.156 0.000 0.092 0.008 0.488
#> SRR1407226 6 0.7750 -0.14401 0.256 0.064 0.000 0.048 0.260 0.372
#> SRR1319363 6 0.6317 0.24119 0.068 0.348 0.000 0.040 0.032 0.512
#> SRR1446961 4 0.3525 0.53505 0.000 0.068 0.120 0.808 0.000 0.004
#> SRR1486650 1 0.3650 0.63160 0.708 0.000 0.000 0.012 0.280 0.000
#> SRR1470152 5 0.0520 0.73547 0.000 0.008 0.000 0.008 0.984 0.000
#> SRR1454785 3 0.0692 0.83485 0.000 0.000 0.976 0.020 0.000 0.004
#> SRR1092329 2 0.5749 0.49849 0.032 0.588 0.000 0.124 0.000 0.256
#> SRR1091476 3 0.1245 0.83190 0.016 0.000 0.952 0.000 0.000 0.032
#> SRR1073775 2 0.5086 0.37180 0.032 0.584 0.000 0.036 0.000 0.348
#> SRR1366873 2 0.5730 0.50408 0.032 0.580 0.000 0.112 0.000 0.276
#> SRR1398114 2 0.5024 0.46548 0.024 0.620 0.000 0.040 0.004 0.312
#> SRR1089950 5 0.6692 0.40752 0.032 0.176 0.000 0.076 0.580 0.136
#> SRR1433272 2 0.4495 0.51705 0.000 0.748 0.000 0.028 0.096 0.128
#> SRR1075314 6 0.5886 -0.20463 0.412 0.008 0.000 0.108 0.012 0.460
#> SRR1085590 4 0.3329 0.58383 0.004 0.220 0.000 0.768 0.000 0.008
#> SRR1100752 3 0.1245 0.83190 0.016 0.000 0.952 0.000 0.000 0.032
#> SRR1391494 2 0.5289 0.57629 0.032 0.700 0.000 0.132 0.016 0.120
#> SRR1333263 4 0.4583 0.53406 0.012 0.256 0.000 0.684 0.004 0.044
#> SRR1310231 2 0.1910 0.60604 0.000 0.892 0.000 0.000 0.000 0.108
#> SRR1094144 2 0.4499 -0.02527 0.000 0.500 0.000 0.012 0.012 0.476
#> SRR1092160 2 0.3589 0.54922 0.008 0.824 0.000 0.032 0.112 0.024
#> SRR1320300 2 0.4864 0.51483 0.020 0.600 0.000 0.036 0.000 0.344
#> SRR1322747 4 0.4070 0.40562 0.000 0.424 0.000 0.568 0.004 0.004
#> SRR1432719 4 0.3840 0.37043 0.000 0.000 0.284 0.696 0.000 0.020
#> SRR1100728 2 0.4491 0.00609 0.000 0.516 0.000 0.012 0.012 0.460
#> SRR1087511 6 0.4727 0.41257 0.064 0.124 0.000 0.072 0.000 0.740
#> SRR1470336 1 0.5565 0.50078 0.648 0.000 0.000 0.100 0.060 0.192
#> SRR1322536 6 0.6005 -0.24583 0.416 0.000 0.000 0.108 0.032 0.444
#> SRR1100824 5 0.2860 0.70643 0.068 0.000 0.000 0.032 0.872 0.028
#> SRR1085951 3 0.1245 0.83190 0.016 0.000 0.952 0.000 0.000 0.032
#> SRR1322046 2 0.0881 0.62788 0.008 0.972 0.000 0.012 0.008 0.000
#> SRR1316420 5 0.2443 0.69537 0.096 0.000 0.000 0.020 0.880 0.004
#> SRR1070913 2 0.5615 0.51232 0.032 0.592 0.000 0.100 0.000 0.276
#> SRR1345806 3 0.3650 0.78183 0.004 0.000 0.756 0.216 0.000 0.024
#> SRR1313872 2 0.1780 0.62438 0.000 0.932 0.000 0.012 0.028 0.028
#> SRR1337666 2 0.3601 0.59239 0.004 0.824 0.000 0.084 0.072 0.016
#> SRR1076823 1 0.5308 0.23690 0.516 0.004 0.000 0.068 0.008 0.404
#> SRR1093954 6 0.3991 -0.02552 0.000 0.472 0.000 0.000 0.004 0.524
#> SRR1451921 6 0.6411 0.14642 0.296 0.092 0.000 0.084 0.004 0.524
#> SRR1491257 5 0.2237 0.70667 0.080 0.000 0.000 0.020 0.896 0.004
#> SRR1416979 2 0.2226 0.61990 0.008 0.912 0.000 0.028 0.008 0.044
#> SRR1419015 6 0.7073 0.40022 0.124 0.216 0.000 0.072 0.052 0.536
#> SRR817649 2 0.3564 0.54545 0.008 0.820 0.000 0.028 0.124 0.020
#> SRR1466376 2 0.0653 0.63138 0.000 0.980 0.000 0.004 0.004 0.012
#> SRR1392055 2 0.5081 0.55598 0.024 0.664 0.000 0.088 0.000 0.224
#> SRR1120913 2 0.1223 0.63337 0.004 0.960 0.000 0.016 0.008 0.012
#> SRR1120869 2 0.3163 0.51047 0.000 0.780 0.000 0.004 0.004 0.212
#> SRR1319419 4 0.3840 0.37043 0.000 0.000 0.284 0.696 0.000 0.020
#> SRR816495 3 0.3650 0.78183 0.004 0.000 0.756 0.216 0.000 0.024
#> SRR818694 6 0.4857 0.42152 0.036 0.228 0.000 0.052 0.000 0.684
#> SRR1465653 5 0.0520 0.73560 0.000 0.008 0.000 0.008 0.984 0.000
#> SRR1475952 1 0.2732 0.64362 0.880 0.000 0.000 0.020 0.056 0.044
#> SRR1465040 3 0.0951 0.83435 0.004 0.000 0.968 0.020 0.000 0.008
#> SRR1088461 2 0.5329 0.56274 0.024 0.636 0.000 0.084 0.004 0.252
#> SRR810129 2 0.4359 0.57667 0.024 0.724 0.000 0.040 0.000 0.212
#> SRR1400141 3 0.4407 0.51031 0.004 0.000 0.592 0.380 0.000 0.024
#> SRR1349585 5 0.4381 -0.04167 0.440 0.000 0.000 0.024 0.536 0.000
#> SRR1437576 2 0.5190 0.56277 0.028 0.676 0.000 0.156 0.000 0.140
#> SRR814407 5 0.7268 0.00508 0.308 0.000 0.000 0.160 0.388 0.144
#> SRR1332403 2 0.2402 0.58133 0.000 0.856 0.000 0.000 0.004 0.140
#> SRR1099598 6 0.3515 0.17102 0.000 0.324 0.000 0.000 0.000 0.676
#> SRR1327723 2 0.1194 0.62392 0.000 0.956 0.000 0.008 0.004 0.032
#> SRR1392525 4 0.5155 0.48171 0.004 0.188 0.000 0.652 0.004 0.152
#> SRR1320536 1 0.3650 0.63160 0.708 0.000 0.000 0.012 0.280 0.000
#> SRR1083824 4 0.4338 0.53077 0.008 0.304 0.000 0.664 0.008 0.016
#> SRR1351390 5 0.7116 -0.00448 0.284 0.000 0.000 0.088 0.400 0.228
#> SRR1309141 4 0.4491 0.51333 0.008 0.268 0.000 0.680 0.004 0.040
#> SRR1452803 2 0.1806 0.61015 0.000 0.908 0.000 0.000 0.004 0.088
#> SRR811631 4 0.5083 0.44254 0.016 0.308 0.000 0.616 0.004 0.056
#> SRR1485563 2 0.4938 0.28312 0.020 0.488 0.000 0.028 0.000 0.464
#> SRR1311531 3 0.3129 0.81173 0.004 0.000 0.820 0.152 0.000 0.024
#> SRR1353076 6 0.4146 0.17168 0.000 0.288 0.000 0.028 0.004 0.680
#> SRR1480831 2 0.2871 0.52724 0.000 0.804 0.000 0.004 0.000 0.192
#> SRR1083892 5 0.2247 0.71887 0.040 0.024 0.000 0.020 0.912 0.004
#> SRR809873 6 0.5311 0.23616 0.252 0.056 0.000 0.044 0.004 0.644
#> SRR1341854 2 0.2716 0.58290 0.004 0.852 0.000 0.008 0.004 0.132
#> SRR1399335 2 0.5412 0.56870 0.024 0.640 0.000 0.104 0.004 0.228
#> SRR1464209 5 0.0405 0.73230 0.008 0.000 0.000 0.004 0.988 0.000
#> SRR1389886 2 0.2968 0.60125 0.000 0.816 0.000 0.016 0.000 0.168
#> SRR1400730 3 0.1245 0.83190 0.016 0.000 0.952 0.000 0.000 0.032
#> SRR1448008 2 0.5747 0.17212 0.112 0.604 0.000 0.044 0.000 0.240
#> SRR1087606 5 0.3119 0.67414 0.048 0.020 0.000 0.016 0.868 0.048
#> SRR1445111 1 0.4513 0.58846 0.628 0.000 0.000 0.040 0.328 0.004
#> SRR816865 2 0.4498 -0.02852 0.000 0.504 0.000 0.012 0.012 0.472
#> SRR1323360 3 0.1049 0.83268 0.008 0.000 0.960 0.000 0.000 0.032
#> SRR1417364 4 0.3840 0.37043 0.000 0.000 0.284 0.696 0.000 0.020
#> SRR1480329 2 0.3340 0.58809 0.004 0.784 0.000 0.016 0.000 0.196
#> SRR1403322 6 0.5346 -0.20125 0.460 0.008 0.000 0.068 0.004 0.460
#> SRR1093625 1 0.3445 0.64852 0.732 0.000 0.000 0.008 0.260 0.000
#> SRR1479977 2 0.5472 0.53989 0.032 0.632 0.000 0.112 0.000 0.224
#> SRR1082035 6 0.5883 -0.12912 0.024 0.388 0.000 0.096 0.004 0.488
#> SRR1393046 2 0.4714 0.58316 0.024 0.736 0.000 0.148 0.008 0.084
#> SRR1466663 2 0.5775 0.56004 0.024 0.660 0.000 0.092 0.048 0.176
#> SRR1384456 1 0.3555 0.63343 0.712 0.000 0.000 0.008 0.280 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "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 17467 rows and 159 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 0.886 0.922 0.969 0.4056 0.603 0.603
#> 3 3 0.970 0.953 0.981 0.5251 0.734 0.575
#> 4 4 0.642 0.614 0.792 0.1883 0.853 0.626
#> 5 5 0.682 0.523 0.752 0.0780 0.928 0.733
#> 6 6 0.707 0.569 0.766 0.0406 0.904 0.600
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
#> SRR810713 2 0.000 0.96977 0.000 1.000
#> SRR808862 1 0.000 0.95609 1.000 0.000
#> SRR1500382 2 0.000 0.96977 0.000 1.000
#> SRR1322683 2 0.184 0.94382 0.028 0.972
#> SRR1329811 1 0.946 0.42645 0.636 0.364
#> SRR1087297 2 0.000 0.96977 0.000 1.000
#> SRR1072626 2 0.000 0.96977 0.000 1.000
#> SRR1407428 2 0.000 0.96977 0.000 1.000
#> SRR1321029 2 0.000 0.96977 0.000 1.000
#> SRR1500282 1 0.000 0.95609 1.000 0.000
#> SRR1100496 1 0.000 0.95609 1.000 0.000
#> SRR1308778 2 0.000 0.96977 0.000 1.000
#> SRR1445304 2 0.000 0.96977 0.000 1.000
#> SRR1099378 2 0.000 0.96977 0.000 1.000
#> SRR1347412 1 0.000 0.95609 1.000 0.000
#> SRR1099694 2 0.000 0.96977 0.000 1.000
#> SRR1088365 2 0.000 0.96977 0.000 1.000
#> SRR1325752 2 0.000 0.96977 0.000 1.000
#> SRR1416713 2 0.000 0.96977 0.000 1.000
#> SRR1074474 2 0.000 0.96977 0.000 1.000
#> SRR1469369 1 0.000 0.95609 1.000 0.000
#> SRR1400507 2 0.000 0.96977 0.000 1.000
#> SRR1378179 2 0.000 0.96977 0.000 1.000
#> SRR1377905 2 0.000 0.96977 0.000 1.000
#> SRR1089479 2 0.969 0.34353 0.396 0.604
#> SRR1073365 2 0.000 0.96977 0.000 1.000
#> SRR1500306 2 0.738 0.72880 0.208 0.792
#> SRR1101566 2 0.000 0.96977 0.000 1.000
#> SRR1350503 1 0.000 0.95609 1.000 0.000
#> SRR1446007 1 0.000 0.95609 1.000 0.000
#> SRR1102875 2 0.000 0.96977 0.000 1.000
#> SRR1380293 2 0.000 0.96977 0.000 1.000
#> SRR1331198 2 0.000 0.96977 0.000 1.000
#> SRR1092686 1 0.000 0.95609 1.000 0.000
#> SRR1069421 2 0.000 0.96977 0.000 1.000
#> SRR1341650 2 0.000 0.96977 0.000 1.000
#> SRR1357276 2 0.000 0.96977 0.000 1.000
#> SRR1498374 2 0.000 0.96977 0.000 1.000
#> SRR1093721 2 0.000 0.96977 0.000 1.000
#> SRR1464660 1 0.722 0.74045 0.800 0.200
#> SRR1402051 2 0.000 0.96977 0.000 1.000
#> SRR1488734 2 0.000 0.96977 0.000 1.000
#> SRR1082616 1 0.000 0.95609 1.000 0.000
#> SRR1099427 1 0.876 0.58667 0.704 0.296
#> SRR1453093 2 0.000 0.96977 0.000 1.000
#> SRR1357064 2 0.000 0.96977 0.000 1.000
#> SRR811237 2 0.000 0.96977 0.000 1.000
#> SRR1100848 2 0.000 0.96977 0.000 1.000
#> SRR1346755 2 0.000 0.96977 0.000 1.000
#> SRR1472529 2 0.000 0.96977 0.000 1.000
#> SRR1398905 1 0.000 0.95609 1.000 0.000
#> SRR1082733 2 0.000 0.96977 0.000 1.000
#> SRR1308035 1 0.000 0.95609 1.000 0.000
#> SRR1466445 1 0.000 0.95609 1.000 0.000
#> SRR1359080 2 0.000 0.96977 0.000 1.000
#> SRR1455825 2 0.000 0.96977 0.000 1.000
#> SRR1389300 2 0.000 0.96977 0.000 1.000
#> SRR812246 1 0.000 0.95609 1.000 0.000
#> SRR1076632 2 0.000 0.96977 0.000 1.000
#> SRR1415567 2 0.000 0.96977 0.000 1.000
#> SRR1331900 2 0.000 0.96977 0.000 1.000
#> SRR1452099 2 0.595 0.81573 0.144 0.856
#> SRR1352346 2 0.000 0.96977 0.000 1.000
#> SRR1364034 2 0.000 0.96977 0.000 1.000
#> SRR1086046 2 0.000 0.96977 0.000 1.000
#> SRR1407226 2 0.000 0.96977 0.000 1.000
#> SRR1319363 2 0.000 0.96977 0.000 1.000
#> SRR1446961 1 0.000 0.95609 1.000 0.000
#> SRR1486650 2 0.000 0.96977 0.000 1.000
#> SRR1470152 1 0.722 0.74045 0.800 0.200
#> SRR1454785 1 0.000 0.95609 1.000 0.000
#> SRR1092329 2 0.000 0.96977 0.000 1.000
#> SRR1091476 1 0.000 0.95609 1.000 0.000
#> SRR1073775 2 0.000 0.96977 0.000 1.000
#> SRR1366873 2 0.000 0.96977 0.000 1.000
#> SRR1398114 2 0.000 0.96977 0.000 1.000
#> SRR1089950 2 0.000 0.96977 0.000 1.000
#> SRR1433272 2 0.000 0.96977 0.000 1.000
#> SRR1075314 2 0.000 0.96977 0.000 1.000
#> SRR1085590 1 0.000 0.95609 1.000 0.000
#> SRR1100752 1 0.000 0.95609 1.000 0.000
#> SRR1391494 2 0.000 0.96977 0.000 1.000
#> SRR1333263 1 0.000 0.95609 1.000 0.000
#> SRR1310231 2 0.000 0.96977 0.000 1.000
#> SRR1094144 2 0.000 0.96977 0.000 1.000
#> SRR1092160 2 0.000 0.96977 0.000 1.000
#> SRR1320300 2 0.000 0.96977 0.000 1.000
#> SRR1322747 1 0.000 0.95609 1.000 0.000
#> SRR1432719 1 0.000 0.95609 1.000 0.000
#> SRR1100728 2 0.000 0.96977 0.000 1.000
#> SRR1087511 2 0.000 0.96977 0.000 1.000
#> SRR1470336 2 0.000 0.96977 0.000 1.000
#> SRR1322536 2 0.745 0.72307 0.212 0.788
#> SRR1100824 1 0.000 0.95609 1.000 0.000
#> SRR1085951 1 0.000 0.95609 1.000 0.000
#> SRR1322046 2 0.000 0.96977 0.000 1.000
#> SRR1316420 2 0.000 0.96977 0.000 1.000
#> SRR1070913 2 0.000 0.96977 0.000 1.000
#> SRR1345806 1 0.000 0.95609 1.000 0.000
#> SRR1313872 2 0.000 0.96977 0.000 1.000
#> SRR1337666 2 0.000 0.96977 0.000 1.000
#> SRR1076823 2 0.000 0.96977 0.000 1.000
#> SRR1093954 2 0.000 0.96977 0.000 1.000
#> SRR1451921 2 0.000 0.96977 0.000 1.000
#> SRR1491257 2 0.753 0.71726 0.216 0.784
#> SRR1416979 2 0.000 0.96977 0.000 1.000
#> SRR1419015 1 0.827 0.65053 0.740 0.260
#> SRR817649 2 0.000 0.96977 0.000 1.000
#> SRR1466376 2 0.000 0.96977 0.000 1.000
#> SRR1392055 2 0.000 0.96977 0.000 1.000
#> SRR1120913 2 0.000 0.96977 0.000 1.000
#> SRR1120869 2 0.000 0.96977 0.000 1.000
#> SRR1319419 1 0.000 0.95609 1.000 0.000
#> SRR816495 1 0.000 0.95609 1.000 0.000
#> SRR818694 2 0.000 0.96977 0.000 1.000
#> SRR1465653 2 0.827 0.64431 0.260 0.740
#> SRR1475952 2 0.000 0.96977 0.000 1.000
#> SRR1465040 1 0.000 0.95609 1.000 0.000
#> SRR1088461 2 0.000 0.96977 0.000 1.000
#> SRR810129 2 0.000 0.96977 0.000 1.000
#> SRR1400141 1 0.000 0.95609 1.000 0.000
#> SRR1349585 2 0.000 0.96977 0.000 1.000
#> SRR1437576 2 0.973 0.28761 0.404 0.596
#> SRR814407 1 0.000 0.95609 1.000 0.000
#> SRR1332403 2 0.000 0.96977 0.000 1.000
#> SRR1099598 2 0.000 0.96977 0.000 1.000
#> SRR1327723 2 0.000 0.96977 0.000 1.000
#> SRR1392525 1 0.000 0.95609 1.000 0.000
#> SRR1320536 2 0.000 0.96977 0.000 1.000
#> SRR1083824 1 0.000 0.95609 1.000 0.000
#> SRR1351390 1 0.978 0.29603 0.588 0.412
#> SRR1309141 1 0.000 0.95609 1.000 0.000
#> SRR1452803 2 0.000 0.96977 0.000 1.000
#> SRR811631 1 0.000 0.95609 1.000 0.000
#> SRR1485563 2 0.000 0.96977 0.000 1.000
#> SRR1311531 1 0.000 0.95609 1.000 0.000
#> SRR1353076 2 0.000 0.96977 0.000 1.000
#> SRR1480831 2 0.000 0.96977 0.000 1.000
#> SRR1083892 2 0.000 0.96977 0.000 1.000
#> SRR809873 2 0.000 0.96977 0.000 1.000
#> SRR1341854 2 0.000 0.96977 0.000 1.000
#> SRR1399335 2 0.000 0.96977 0.000 1.000
#> SRR1464209 2 0.760 0.71063 0.220 0.780
#> SRR1389886 2 0.000 0.96977 0.000 1.000
#> SRR1400730 1 0.000 0.95609 1.000 0.000
#> SRR1448008 2 0.000 0.96977 0.000 1.000
#> SRR1087606 2 0.971 0.33252 0.400 0.600
#> SRR1445111 2 0.833 0.63718 0.264 0.736
#> SRR816865 2 0.000 0.96977 0.000 1.000
#> SRR1323360 1 0.000 0.95609 1.000 0.000
#> SRR1417364 1 0.000 0.95609 1.000 0.000
#> SRR1480329 2 0.000 0.96977 0.000 1.000
#> SRR1403322 2 0.000 0.96977 0.000 1.000
#> SRR1093625 2 0.000 0.96977 0.000 1.000
#> SRR1479977 2 0.000 0.96977 0.000 1.000
#> SRR1082035 2 0.000 0.96977 0.000 1.000
#> SRR1393046 2 1.000 -0.00325 0.488 0.512
#> SRR1466663 2 0.000 0.96977 0.000 1.000
#> SRR1384456 2 0.000 0.96977 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1322683 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1329811 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1087297 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1072626 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1321029 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1500282 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1100496 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1308778 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1099378 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1347412 1 0.6309 0.0254 0.504 0.000 0.496
#> SRR1099694 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1325752 2 0.2537 0.9033 0.080 0.920 0.000
#> SRR1416713 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1469369 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1400507 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1377905 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1089479 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1073365 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1500306 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1101566 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1350503 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1102875 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1092686 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1069421 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1341650 2 0.5968 0.4398 0.364 0.636 0.000
#> SRR1357276 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1498374 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1093721 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1464660 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1402051 1 0.3752 0.7944 0.856 0.144 0.000
#> SRR1488734 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1082616 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1099427 3 0.6154 0.2994 0.000 0.408 0.592
#> SRR1453093 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1357064 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR811237 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1100848 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1346755 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1472529 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1398905 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1082733 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1308035 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1359080 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR812246 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1076632 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1415567 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1452099 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1352346 2 0.4399 0.7686 0.188 0.812 0.000
#> SRR1364034 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1086046 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1407226 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1319363 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1446961 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1486650 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1454785 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1092329 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1091476 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1073775 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1089950 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1433272 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1075314 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1085590 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1100752 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1391494 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1333263 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1310231 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1094144 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1092160 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1322747 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1432719 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1100728 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1087511 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1470336 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1322536 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1100824 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1085951 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1316420 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1070913 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1345806 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1313872 2 0.0237 0.9782 0.004 0.996 0.000
#> SRR1337666 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1076823 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1093954 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1451921 1 0.5058 0.6564 0.756 0.244 0.000
#> SRR1491257 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1416979 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1419015 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR817649 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1466376 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1319419 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR816495 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR818694 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1465653 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1465040 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1088461 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1400141 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1349585 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1437576 2 0.3412 0.8504 0.000 0.876 0.124
#> SRR814407 1 0.4605 0.7299 0.796 0.000 0.204
#> SRR1332403 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1099598 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1327723 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1392525 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1320536 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1083824 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1351390 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1309141 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1452803 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR811631 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1485563 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1311531 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1353076 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1480831 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1083892 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR809873 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1341854 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1464209 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1389886 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1400730 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1448008 2 0.0424 0.9746 0.008 0.992 0.000
#> SRR1087606 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR816865 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1323360 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1417364 3 0.0000 0.9842 0.000 0.000 1.000
#> SRR1480329 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1403322 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.9704 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.9816 0.000 1.000 0.000
#> SRR1082035 2 0.4399 0.7684 0.188 0.812 0.000
#> SRR1393046 2 0.5465 0.5922 0.000 0.712 0.288
#> SRR1466663 2 0.4605 0.7465 0.204 0.796 0.000
#> SRR1384456 1 0.0000 0.9704 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 4 0.4955 0.27789 0.000 0.444 0.000 0.556
#> SRR808862 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.4925 -0.00712 0.000 0.572 0.000 0.428
#> SRR1322683 4 0.2973 0.50543 0.000 0.144 0.000 0.856
#> SRR1329811 1 0.2814 0.83377 0.868 0.132 0.000 0.000
#> SRR1087297 2 0.3569 0.58709 0.000 0.804 0.000 0.196
#> SRR1072626 2 0.4713 0.36154 0.000 0.640 0.000 0.360
#> SRR1407428 1 0.0707 0.86028 0.980 0.000 0.000 0.020
#> SRR1321029 4 0.4790 0.42183 0.000 0.380 0.000 0.620
#> SRR1500282 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1100496 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1308778 2 0.2973 0.62137 0.000 0.856 0.000 0.144
#> SRR1445304 2 0.4989 -0.13771 0.000 0.528 0.000 0.472
#> SRR1099378 1 0.3142 0.83436 0.860 0.132 0.000 0.008
#> SRR1347412 1 0.4967 0.24893 0.548 0.000 0.452 0.000
#> SRR1099694 2 0.1211 0.57000 0.000 0.960 0.000 0.040
#> SRR1088365 4 0.4277 0.34008 0.000 0.280 0.000 0.720
#> SRR1325752 2 0.3249 0.61390 0.008 0.852 0.000 0.140
#> SRR1416713 2 0.3219 0.60871 0.000 0.836 0.000 0.164
#> SRR1074474 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1400507 4 0.4454 0.50272 0.000 0.308 0.000 0.692
#> SRR1378179 2 0.2589 0.62267 0.000 0.884 0.000 0.116
#> SRR1377905 2 0.4981 -0.10337 0.000 0.536 0.000 0.464
#> SRR1089479 1 0.0707 0.86029 0.980 0.000 0.000 0.020
#> SRR1073365 2 0.4134 0.51216 0.000 0.740 0.000 0.260
#> SRR1500306 1 0.3801 0.77647 0.780 0.000 0.000 0.220
#> SRR1101566 4 0.3074 0.50434 0.000 0.152 0.000 0.848
#> SRR1350503 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1446007 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.4985 0.26923 0.000 0.532 0.000 0.468
#> SRR1380293 2 0.4730 -0.04079 0.000 0.636 0.000 0.364
#> SRR1331198 2 0.2081 0.55124 0.000 0.916 0.000 0.084
#> SRR1092686 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.3942 0.48646 0.000 0.764 0.000 0.236
#> SRR1341650 4 0.7457 0.14258 0.220 0.276 0.000 0.504
#> SRR1357276 2 0.4996 -0.10117 0.000 0.516 0.000 0.484
#> SRR1498374 4 0.4406 0.50714 0.000 0.300 0.000 0.700
#> SRR1093721 2 0.4804 0.32405 0.000 0.616 0.000 0.384
#> SRR1464660 1 0.2814 0.83377 0.868 0.132 0.000 0.000
#> SRR1402051 4 0.4874 0.34383 0.180 0.056 0.000 0.764
#> SRR1488734 2 0.2973 0.61298 0.000 0.856 0.000 0.144
#> SRR1082616 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1099427 4 0.6130 0.27658 0.000 0.052 0.400 0.548
#> SRR1453093 4 0.5161 -0.08213 0.008 0.400 0.000 0.592
#> SRR1357064 1 0.2814 0.83377 0.868 0.132 0.000 0.000
#> SRR811237 2 0.4981 0.29002 0.000 0.536 0.000 0.464
#> SRR1100848 2 0.1807 0.55849 0.008 0.940 0.000 0.052
#> SRR1346755 4 0.4679 0.43275 0.000 0.352 0.000 0.648
#> SRR1472529 4 0.3907 0.52898 0.000 0.232 0.000 0.768
#> SRR1398905 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1082733 2 0.4406 0.50424 0.000 0.700 0.000 0.300
#> SRR1308035 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1359080 2 0.4877 -0.14497 0.000 0.592 0.000 0.408
#> SRR1455825 2 0.4855 0.29963 0.000 0.600 0.000 0.400
#> SRR1389300 4 0.4961 0.26160 0.000 0.448 0.000 0.552
#> SRR812246 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.4564 0.47913 0.000 0.672 0.000 0.328
#> SRR1415567 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1331900 4 0.4406 0.50714 0.000 0.300 0.000 0.700
#> SRR1452099 1 0.4791 0.82753 0.784 0.136 0.000 0.080
#> SRR1352346 2 0.6655 0.34372 0.184 0.624 0.000 0.192
#> SRR1364034 2 0.4522 0.48635 0.000 0.680 0.000 0.320
#> SRR1086046 1 0.6071 0.64003 0.612 0.064 0.000 0.324
#> SRR1407226 1 0.3554 0.80168 0.844 0.020 0.000 0.136
#> SRR1319363 1 0.4544 0.75633 0.788 0.048 0.000 0.164
#> SRR1446961 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1486650 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.2814 0.83377 0.868 0.132 0.000 0.000
#> SRR1454785 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1092329 4 0.3942 0.52789 0.000 0.236 0.000 0.764
#> SRR1091476 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1073775 4 0.4790 0.17621 0.000 0.380 0.000 0.620
#> SRR1366873 4 0.4040 0.52879 0.000 0.248 0.000 0.752
#> SRR1398114 4 0.5000 0.02859 0.000 0.500 0.000 0.500
#> SRR1089950 1 0.2335 0.84992 0.920 0.020 0.000 0.060
#> SRR1433272 2 0.2256 0.55775 0.020 0.924 0.000 0.056
#> SRR1075314 1 0.5112 0.64542 0.608 0.008 0.000 0.384
#> SRR1085590 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1100752 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1391494 4 0.4356 0.43241 0.000 0.292 0.000 0.708
#> SRR1333263 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1310231 2 0.3266 0.60661 0.000 0.832 0.000 0.168
#> SRR1094144 2 0.4624 0.46771 0.000 0.660 0.000 0.340
#> SRR1092160 2 0.2048 0.55514 0.008 0.928 0.000 0.064
#> SRR1320300 4 0.4985 0.26665 0.000 0.468 0.000 0.532
#> SRR1322747 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1432719 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1100728 2 0.4431 0.49639 0.000 0.696 0.000 0.304
#> SRR1087511 4 0.1807 0.41366 0.008 0.052 0.000 0.940
#> SRR1470336 1 0.3801 0.77647 0.780 0.000 0.000 0.220
#> SRR1322536 1 0.4522 0.71207 0.680 0.000 0.000 0.320
#> SRR1100824 1 0.1716 0.85413 0.936 0.064 0.000 0.000
#> SRR1085951 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1322046 2 0.3266 0.59783 0.000 0.832 0.000 0.168
#> SRR1316420 1 0.0707 0.86039 0.980 0.020 0.000 0.000
#> SRR1070913 4 0.4222 0.51997 0.000 0.272 0.000 0.728
#> SRR1345806 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1313872 2 0.2466 0.60945 0.004 0.900 0.000 0.096
#> SRR1337666 2 0.3801 0.35436 0.000 0.780 0.000 0.220
#> SRR1076823 1 0.3710 0.80649 0.804 0.004 0.000 0.192
#> SRR1093954 2 0.4955 0.31226 0.000 0.556 0.000 0.444
#> SRR1451921 4 0.7683 -0.03469 0.216 0.384 0.000 0.400
#> SRR1491257 1 0.2530 0.84116 0.888 0.112 0.000 0.000
#> SRR1416979 2 0.2921 0.61240 0.000 0.860 0.000 0.140
#> SRR1419015 1 0.4095 0.77644 0.804 0.024 0.000 0.172
#> SRR817649 2 0.1902 0.55963 0.004 0.932 0.000 0.064
#> SRR1466376 2 0.3400 0.60298 0.000 0.820 0.000 0.180
#> SRR1392055 4 0.4477 0.49875 0.000 0.312 0.000 0.688
#> SRR1120913 2 0.4134 0.50462 0.000 0.740 0.000 0.260
#> SRR1120869 2 0.3486 0.59571 0.000 0.812 0.000 0.188
#> SRR1319419 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR816495 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR818694 4 0.4781 0.00908 0.004 0.336 0.000 0.660
#> SRR1465653 1 0.2868 0.83159 0.864 0.136 0.000 0.000
#> SRR1475952 1 0.2647 0.83421 0.880 0.000 0.000 0.120
#> SRR1465040 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1088461 4 0.4981 0.28134 0.000 0.464 0.000 0.536
#> SRR810129 2 0.4916 0.05715 0.000 0.576 0.000 0.424
#> SRR1400141 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.0469 0.86083 0.988 0.012 0.000 0.000
#> SRR1437576 4 0.6517 0.44126 0.000 0.288 0.108 0.604
#> SRR814407 1 0.4482 0.64122 0.728 0.000 0.264 0.008
#> SRR1332403 2 0.2814 0.61458 0.000 0.868 0.000 0.132
#> SRR1099598 4 0.3764 0.32265 0.000 0.216 0.000 0.784
#> SRR1327723 2 0.2973 0.61606 0.000 0.856 0.000 0.144
#> SRR1392525 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1320536 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1083824 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1351390 1 0.3945 0.77991 0.780 0.004 0.000 0.216
#> SRR1309141 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1452803 2 0.2973 0.61461 0.000 0.856 0.000 0.144
#> SRR811631 3 0.0336 0.99118 0.000 0.000 0.992 0.008
#> SRR1485563 4 0.4500 0.26399 0.000 0.316 0.000 0.684
#> SRR1311531 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1353076 4 0.3266 0.42660 0.000 0.168 0.000 0.832
#> SRR1480831 2 0.3400 0.60300 0.000 0.820 0.000 0.180
#> SRR1083892 1 0.3569 0.78367 0.804 0.196 0.000 0.000
#> SRR809873 1 0.6075 0.66361 0.636 0.076 0.000 0.288
#> SRR1341854 2 0.2345 0.62408 0.000 0.900 0.000 0.100
#> SRR1399335 4 0.4985 0.27886 0.000 0.468 0.000 0.532
#> SRR1464209 1 0.2760 0.83542 0.872 0.128 0.000 0.000
#> SRR1389886 2 0.3311 0.60331 0.000 0.828 0.000 0.172
#> SRR1400730 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1448008 2 0.5969 0.23925 0.044 0.564 0.000 0.392
#> SRR1087606 1 0.4285 0.84035 0.820 0.104 0.000 0.076
#> SRR1445111 1 0.0188 0.86115 0.996 0.000 0.000 0.004
#> SRR816865 2 0.4454 0.49457 0.000 0.692 0.000 0.308
#> SRR1323360 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.99973 0.000 0.000 1.000 0.000
#> SRR1480329 2 0.4994 -0.00761 0.000 0.520 0.000 0.480
#> SRR1403322 1 0.5623 0.69247 0.660 0.048 0.000 0.292
#> SRR1093625 1 0.0000 0.86115 1.000 0.000 0.000 0.000
#> SRR1479977 4 0.4382 0.50946 0.000 0.296 0.000 0.704
#> SRR1082035 4 0.4932 0.38844 0.032 0.240 0.000 0.728
#> SRR1393046 4 0.7513 0.30365 0.000 0.296 0.216 0.488
#> SRR1466663 2 0.7706 -0.18028 0.224 0.412 0.000 0.364
#> SRR1384456 1 0.0000 0.86115 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 4 0.4088 0.4117 0.000 0.368 0.000 0.632 0.000
#> SRR808862 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1500382 2 0.3857 0.3194 0.000 0.688 0.000 0.312 0.000
#> SRR1322683 4 0.1628 0.6562 0.056 0.008 0.000 0.936 0.000
#> SRR1329811 5 0.0000 0.6093 0.000 0.000 0.000 0.000 1.000
#> SRR1087297 2 0.1952 0.5958 0.004 0.912 0.000 0.084 0.000
#> SRR1072626 2 0.4973 0.3057 0.048 0.632 0.000 0.320 0.000
#> SRR1407428 1 0.3949 0.3151 0.668 0.000 0.000 0.000 0.332
#> SRR1321029 4 0.2929 0.6309 0.000 0.180 0.000 0.820 0.000
#> SRR1500282 5 0.4227 0.1712 0.420 0.000 0.000 0.000 0.580
#> SRR1100496 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1308778 2 0.1522 0.6124 0.012 0.944 0.000 0.044 0.000
#> SRR1445304 2 0.4383 0.1365 0.004 0.572 0.000 0.424 0.000
#> SRR1099378 5 0.1695 0.5817 0.044 0.008 0.000 0.008 0.940
#> SRR1347412 3 0.6508 -0.0407 0.248 0.000 0.488 0.000 0.264
#> SRR1099694 2 0.5189 0.4232 0.012 0.620 0.000 0.036 0.332
#> SRR1088365 4 0.6684 -0.0135 0.240 0.352 0.000 0.408 0.000
#> SRR1325752 2 0.2046 0.6106 0.068 0.916 0.000 0.016 0.000
#> SRR1416713 2 0.1357 0.6098 0.004 0.948 0.000 0.048 0.000
#> SRR1074474 5 0.4306 0.0508 0.492 0.000 0.000 0.000 0.508
#> SRR1469369 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1400507 4 0.2280 0.6612 0.000 0.120 0.000 0.880 0.000
#> SRR1378179 2 0.0579 0.6148 0.008 0.984 0.000 0.008 0.000
#> SRR1377905 2 0.4306 -0.1228 0.000 0.508 0.000 0.492 0.000
#> SRR1089479 1 0.4150 0.2377 0.612 0.000 0.000 0.000 0.388
#> SRR1073365 2 0.4541 0.4105 0.032 0.680 0.000 0.288 0.000
#> SRR1500306 1 0.4442 0.4104 0.688 0.000 0.000 0.028 0.284
#> SRR1101566 4 0.1597 0.6586 0.048 0.012 0.000 0.940 0.000
#> SRR1350503 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1446007 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.6569 0.2161 0.232 0.464 0.000 0.304 0.000
#> SRR1380293 5 0.6655 -0.2854 0.000 0.368 0.000 0.228 0.404
#> SRR1331198 2 0.5014 0.4129 0.008 0.628 0.000 0.032 0.332
#> SRR1092686 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 2 0.5426 0.4422 0.252 0.640 0.000 0.108 0.000
#> SRR1341650 1 0.8142 -0.1640 0.348 0.296 0.000 0.252 0.104
#> SRR1357276 2 0.4161 0.1584 0.000 0.608 0.000 0.392 0.000
#> SRR1498374 4 0.1908 0.6687 0.000 0.092 0.000 0.908 0.000
#> SRR1093721 2 0.4974 0.1302 0.032 0.560 0.000 0.408 0.000
#> SRR1464660 5 0.0000 0.6093 0.000 0.000 0.000 0.000 1.000
#> SRR1402051 4 0.4403 0.5529 0.240 0.004 0.000 0.724 0.032
#> SRR1488734 2 0.1478 0.6090 0.000 0.936 0.000 0.064 0.000
#> SRR1082616 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1099427 4 0.3934 0.4893 0.000 0.008 0.276 0.716 0.000
#> SRR1453093 1 0.6710 -0.2096 0.408 0.340 0.000 0.252 0.000
#> SRR1357064 5 0.0794 0.6046 0.028 0.000 0.000 0.000 0.972
#> SRR811237 2 0.5906 0.3749 0.284 0.576 0.000 0.140 0.000
#> SRR1100848 2 0.5346 0.3598 0.016 0.552 0.000 0.028 0.404
#> SRR1346755 4 0.2733 0.6554 0.016 0.080 0.000 0.888 0.016
#> SRR1472529 4 0.3134 0.6552 0.032 0.120 0.000 0.848 0.000
#> SRR1398905 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1082733 2 0.5595 0.4065 0.124 0.624 0.000 0.252 0.000
#> SRR1308035 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 4 0.5930 0.2508 0.000 0.372 0.000 0.516 0.112
#> SRR1455825 2 0.4829 -0.0730 0.020 0.496 0.000 0.484 0.000
#> SRR1389300 4 0.4108 0.4806 0.008 0.308 0.000 0.684 0.000
#> SRR812246 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 2 0.5993 0.3854 0.248 0.580 0.000 0.172 0.000
#> SRR1415567 1 0.4192 0.1632 0.596 0.000 0.000 0.000 0.404
#> SRR1331900 4 0.2127 0.6657 0.000 0.108 0.000 0.892 0.000
#> SRR1452099 5 0.4002 0.4573 0.152 0.044 0.000 0.008 0.796
#> SRR1352346 2 0.5378 0.5043 0.088 0.736 0.000 0.076 0.100
#> SRR1364034 2 0.5666 0.4265 0.244 0.620 0.000 0.136 0.000
#> SRR1086046 1 0.2546 0.5526 0.904 0.012 0.000 0.036 0.048
#> SRR1407226 1 0.5441 0.1991 0.572 0.020 0.000 0.032 0.376
#> SRR1319363 1 0.4808 0.4357 0.748 0.028 0.000 0.052 0.172
#> SRR1446961 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1486650 5 0.4306 0.0508 0.492 0.000 0.000 0.000 0.508
#> SRR1470152 5 0.0000 0.6093 0.000 0.000 0.000 0.000 1.000
#> SRR1454785 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1092329 4 0.1818 0.6673 0.024 0.044 0.000 0.932 0.000
#> SRR1091476 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 4 0.5797 0.3724 0.132 0.276 0.000 0.592 0.000
#> SRR1366873 4 0.1628 0.6696 0.008 0.056 0.000 0.936 0.000
#> SRR1398114 2 0.5148 0.1325 0.040 0.528 0.000 0.432 0.000
#> SRR1089950 5 0.4997 0.0641 0.456 0.012 0.000 0.012 0.520
#> SRR1433272 2 0.5456 0.4163 0.028 0.592 0.000 0.028 0.352
#> SRR1075314 1 0.1403 0.5583 0.952 0.000 0.000 0.024 0.024
#> SRR1085590 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1100752 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 4 0.3166 0.6248 0.020 0.112 0.000 0.856 0.012
#> SRR1333263 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1310231 2 0.1197 0.6111 0.000 0.952 0.000 0.048 0.000
#> SRR1094144 2 0.5983 0.3894 0.252 0.580 0.000 0.168 0.000
#> SRR1092160 2 0.5380 0.3071 0.012 0.516 0.000 0.032 0.440
#> SRR1320300 4 0.4171 0.3338 0.000 0.396 0.000 0.604 0.000
#> SRR1322747 3 0.1341 0.9186 0.000 0.056 0.944 0.000 0.000
#> SRR1432719 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 2 0.5612 0.4303 0.248 0.624 0.000 0.128 0.000
#> SRR1087511 4 0.4734 0.4647 0.312 0.036 0.000 0.652 0.000
#> SRR1470336 1 0.4350 0.4224 0.704 0.000 0.000 0.028 0.268
#> SRR1322536 1 0.2388 0.5589 0.900 0.000 0.000 0.028 0.072
#> SRR1100824 5 0.2605 0.5358 0.148 0.000 0.000 0.000 0.852
#> SRR1085951 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1322046 2 0.1894 0.5996 0.008 0.920 0.000 0.072 0.000
#> SRR1316420 5 0.3913 0.3501 0.324 0.000 0.000 0.000 0.676
#> SRR1070913 4 0.1774 0.6682 0.016 0.052 0.000 0.932 0.000
#> SRR1345806 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.3003 0.5988 0.016 0.872 0.000 0.020 0.092
#> SRR1337666 2 0.5512 0.3615 0.004 0.568 0.000 0.064 0.364
#> SRR1076823 1 0.1608 0.5598 0.928 0.000 0.000 0.000 0.072
#> SRR1093954 2 0.6547 0.2249 0.232 0.472 0.000 0.296 0.000
#> SRR1451921 1 0.2959 0.5016 0.864 0.100 0.000 0.036 0.000
#> SRR1491257 5 0.1341 0.5985 0.056 0.000 0.000 0.000 0.944
#> SRR1416979 2 0.3875 0.5485 0.012 0.816 0.000 0.124 0.048
#> SRR1419015 1 0.3873 0.4864 0.808 0.012 0.004 0.024 0.152
#> SRR817649 2 0.5096 0.2564 0.012 0.500 0.000 0.016 0.472
#> SRR1466376 2 0.1484 0.6111 0.008 0.944 0.000 0.048 0.000
#> SRR1392055 4 0.2966 0.6388 0.000 0.184 0.000 0.816 0.000
#> SRR1120913 2 0.2629 0.5616 0.004 0.860 0.000 0.136 0.000
#> SRR1120869 2 0.2077 0.6075 0.040 0.920 0.000 0.040 0.000
#> SRR1319419 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR818694 4 0.6399 0.2568 0.308 0.196 0.000 0.496 0.000
#> SRR1465653 5 0.0000 0.6093 0.000 0.000 0.000 0.000 1.000
#> SRR1475952 1 0.3861 0.4116 0.728 0.000 0.000 0.008 0.264
#> SRR1465040 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 4 0.4375 0.3100 0.004 0.420 0.000 0.576 0.000
#> SRR810129 2 0.4323 0.2850 0.012 0.656 0.000 0.332 0.000
#> SRR1400141 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 5 0.4192 0.2327 0.404 0.000 0.000 0.000 0.596
#> SRR1437576 4 0.3798 0.6394 0.000 0.128 0.064 0.808 0.000
#> SRR814407 1 0.6343 0.2230 0.516 0.000 0.200 0.000 0.284
#> SRR1332403 2 0.0566 0.6157 0.004 0.984 0.000 0.012 0.000
#> SRR1099598 4 0.6245 0.2547 0.236 0.220 0.000 0.544 0.000
#> SRR1327723 2 0.0992 0.6132 0.008 0.968 0.000 0.024 0.000
#> SRR1392525 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1320536 5 0.4306 0.0508 0.492 0.000 0.000 0.000 0.508
#> SRR1083824 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1351390 1 0.4608 0.3433 0.640 0.000 0.000 0.024 0.336
#> SRR1309141 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1452803 2 0.1197 0.6099 0.000 0.952 0.000 0.048 0.000
#> SRR811631 3 0.0703 0.9564 0.000 0.000 0.976 0.024 0.000
#> SRR1485563 4 0.6638 0.1625 0.240 0.320 0.000 0.440 0.000
#> SRR1311531 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 4 0.5764 0.3742 0.236 0.152 0.000 0.612 0.000
#> SRR1480831 2 0.1522 0.6128 0.044 0.944 0.000 0.012 0.000
#> SRR1083892 5 0.0609 0.6059 0.020 0.000 0.000 0.000 0.980
#> SRR809873 1 0.2228 0.5319 0.916 0.020 0.000 0.056 0.008
#> SRR1341854 2 0.0968 0.6147 0.012 0.972 0.000 0.012 0.004
#> SRR1399335 4 0.4264 0.3908 0.004 0.376 0.000 0.620 0.000
#> SRR1464209 5 0.0000 0.6093 0.000 0.000 0.000 0.000 1.000
#> SRR1389886 2 0.1608 0.6066 0.000 0.928 0.000 0.072 0.000
#> SRR1400730 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1448008 2 0.6398 0.1805 0.300 0.500 0.000 0.200 0.000
#> SRR1087606 5 0.1965 0.5516 0.096 0.000 0.000 0.000 0.904
#> SRR1445111 5 0.4304 0.0241 0.484 0.000 0.000 0.000 0.516
#> SRR816865 2 0.5657 0.4242 0.256 0.616 0.000 0.128 0.000
#> SRR1323360 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.0000 0.9804 0.000 0.000 1.000 0.000 0.000
#> SRR1480329 4 0.4517 0.2198 0.008 0.436 0.000 0.556 0.000
#> SRR1403322 1 0.0404 0.5595 0.988 0.000 0.000 0.000 0.012
#> SRR1093625 1 0.4306 -0.0972 0.508 0.000 0.000 0.000 0.492
#> SRR1479977 4 0.2389 0.6605 0.004 0.116 0.000 0.880 0.000
#> SRR1082035 4 0.4588 0.5055 0.056 0.208 0.000 0.732 0.004
#> SRR1393046 4 0.5904 0.4599 0.000 0.204 0.196 0.600 0.000
#> SRR1466663 2 0.7213 -0.0696 0.016 0.352 0.000 0.332 0.300
#> SRR1384456 5 0.4305 0.0615 0.488 0.000 0.000 0.000 0.512
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 6 0.5048 0.4204 0.008 0.344 0.000 0.068 0.000 0.580
#> SRR808862 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1500382 2 0.4941 0.4475 0.008 0.660 0.000 0.104 0.000 0.228
#> SRR1322683 6 0.1477 0.6595 0.008 0.004 0.000 0.048 0.000 0.940
#> SRR1329811 5 0.0000 0.6493 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1087297 2 0.1951 0.6859 0.004 0.916 0.000 0.060 0.000 0.020
#> SRR1072626 2 0.6060 0.2154 0.012 0.492 0.000 0.204 0.000 0.292
#> SRR1407428 1 0.2728 0.6004 0.860 0.000 0.000 0.040 0.100 0.000
#> SRR1321029 6 0.2494 0.6853 0.000 0.120 0.000 0.016 0.000 0.864
#> SRR1500282 5 0.5002 0.0530 0.364 0.000 0.000 0.080 0.556 0.000
#> SRR1100496 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1308778 2 0.2723 0.6452 0.004 0.856 0.000 0.120 0.000 0.020
#> SRR1445304 2 0.6186 0.1362 0.008 0.444 0.000 0.268 0.000 0.280
#> SRR1099378 5 0.1495 0.6327 0.020 0.004 0.000 0.020 0.948 0.008
#> SRR1347412 3 0.6291 -0.0469 0.340 0.000 0.472 0.036 0.152 0.000
#> SRR1099694 2 0.4782 0.5569 0.008 0.696 0.000 0.040 0.228 0.028
#> SRR1088365 4 0.4094 0.6309 0.000 0.088 0.000 0.744 0.000 0.168
#> SRR1325752 2 0.5341 0.5089 0.156 0.648 0.000 0.180 0.008 0.008
#> SRR1416713 2 0.1367 0.6845 0.000 0.944 0.000 0.044 0.000 0.012
#> SRR1074474 1 0.4760 0.3988 0.604 0.000 0.000 0.068 0.328 0.000
#> SRR1469369 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1400507 6 0.2554 0.6880 0.004 0.092 0.000 0.028 0.000 0.876
#> SRR1378179 2 0.1806 0.6765 0.000 0.908 0.000 0.088 0.000 0.004
#> SRR1377905 6 0.4789 0.1891 0.004 0.460 0.000 0.032 0.004 0.500
#> SRR1089479 1 0.3460 0.5546 0.760 0.000 0.000 0.020 0.220 0.000
#> SRR1073365 4 0.5595 0.2595 0.000 0.392 0.000 0.464 0.000 0.144
#> SRR1500306 1 0.3526 0.6022 0.828 0.000 0.000 0.056 0.088 0.028
#> SRR1101566 6 0.0363 0.6653 0.000 0.000 0.000 0.012 0.000 0.988
#> SRR1350503 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1446007 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 4 0.4602 0.6411 0.000 0.160 0.000 0.696 0.000 0.144
#> SRR1380293 5 0.6502 -0.1571 0.008 0.392 0.000 0.040 0.428 0.132
#> SRR1331198 2 0.3166 0.6120 0.008 0.800 0.000 0.008 0.184 0.000
#> SRR1092686 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.3192 0.6361 0.004 0.216 0.000 0.776 0.000 0.004
#> SRR1341650 4 0.3893 0.6080 0.072 0.040 0.000 0.824 0.036 0.028
#> SRR1357276 2 0.4351 0.4463 0.008 0.692 0.000 0.044 0.000 0.256
#> SRR1498374 6 0.2066 0.6816 0.000 0.052 0.000 0.040 0.000 0.908
#> SRR1093721 2 0.5680 0.2220 0.036 0.548 0.000 0.080 0.000 0.336
#> SRR1464660 5 0.0000 0.6493 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1402051 6 0.4838 0.5033 0.216 0.004 0.000 0.056 0.028 0.696
#> SRR1488734 2 0.2622 0.6597 0.004 0.868 0.000 0.104 0.000 0.024
#> SRR1082616 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1099427 6 0.3649 0.5431 0.000 0.000 0.196 0.040 0.000 0.764
#> SRR1453093 1 0.7554 -0.1119 0.336 0.168 0.000 0.280 0.000 0.216
#> SRR1357064 5 0.3254 0.5828 0.124 0.000 0.000 0.056 0.820 0.000
#> SRR811237 4 0.5445 0.5836 0.056 0.216 0.000 0.648 0.000 0.080
#> SRR1100848 2 0.5276 0.4362 0.008 0.620 0.000 0.056 0.292 0.024
#> SRR1346755 6 0.3161 0.6377 0.000 0.028 0.000 0.136 0.008 0.828
#> SRR1472529 6 0.3621 0.6480 0.008 0.148 0.000 0.048 0.000 0.796
#> SRR1398905 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1082733 4 0.5064 0.5272 0.004 0.300 0.000 0.604 0.000 0.092
#> SRR1308035 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.5732 -0.0734 0.012 0.464 0.000 0.012 0.080 0.432
#> SRR1455825 2 0.5018 0.3031 0.012 0.604 0.000 0.052 0.004 0.328
#> SRR1389300 6 0.5696 0.3676 0.004 0.340 0.000 0.152 0.000 0.504
#> SRR812246 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.3152 0.6449 0.004 0.196 0.000 0.792 0.000 0.008
#> SRR1415567 1 0.4011 0.5289 0.736 0.000 0.000 0.060 0.204 0.000
#> SRR1331900 6 0.2839 0.6786 0.004 0.092 0.000 0.044 0.000 0.860
#> SRR1452099 5 0.4828 0.4835 0.144 0.064 0.000 0.048 0.736 0.008
#> SRR1352346 2 0.6593 0.3015 0.188 0.536 0.000 0.220 0.032 0.024
#> SRR1364034 4 0.3301 0.6365 0.004 0.216 0.000 0.772 0.000 0.008
#> SRR1086046 1 0.4647 0.5553 0.740 0.040 0.000 0.172 0.020 0.028
#> SRR1407226 4 0.5898 -0.2565 0.380 0.000 0.000 0.416 0.204 0.000
#> SRR1319363 4 0.5030 0.0948 0.316 0.000 0.000 0.588 0.096 0.000
#> SRR1446961 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1486650 1 0.4760 0.3988 0.604 0.000 0.000 0.068 0.328 0.000
#> SRR1470152 5 0.0000 0.6493 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1454785 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 6 0.0820 0.6705 0.000 0.012 0.000 0.016 0.000 0.972
#> SRR1091476 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 6 0.6819 0.2583 0.152 0.232 0.000 0.116 0.000 0.500
#> SRR1366873 6 0.2164 0.6692 0.000 0.032 0.000 0.068 0.000 0.900
#> SRR1398114 4 0.5828 0.3712 0.004 0.284 0.000 0.512 0.000 0.200
#> SRR1089950 5 0.5849 -0.0861 0.432 0.016 0.000 0.076 0.460 0.016
#> SRR1433272 2 0.6046 0.3682 0.004 0.492 0.000 0.144 0.344 0.016
#> SRR1075314 1 0.3098 0.5925 0.812 0.000 0.000 0.164 0.000 0.024
#> SRR1085590 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100752 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 6 0.4177 0.4956 0.000 0.032 0.000 0.280 0.004 0.684
#> SRR1333263 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1310231 2 0.1946 0.6773 0.004 0.912 0.000 0.072 0.000 0.012
#> SRR1094144 4 0.3152 0.6453 0.004 0.196 0.000 0.792 0.000 0.008
#> SRR1092160 2 0.5207 0.3498 0.008 0.572 0.000 0.040 0.360 0.020
#> SRR1320300 6 0.5994 0.1358 0.008 0.360 0.000 0.180 0.000 0.452
#> SRR1322747 3 0.1765 0.8720 0.000 0.096 0.904 0.000 0.000 0.000
#> SRR1432719 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100728 4 0.3163 0.6377 0.004 0.212 0.000 0.780 0.000 0.004
#> SRR1087511 6 0.5784 -0.1104 0.152 0.004 0.000 0.412 0.000 0.432
#> SRR1470336 1 0.2550 0.6248 0.892 0.000 0.000 0.048 0.036 0.024
#> SRR1322536 1 0.3738 0.5982 0.808 0.000 0.000 0.116 0.044 0.032
#> SRR1100824 5 0.3405 0.5636 0.112 0.000 0.000 0.076 0.812 0.000
#> SRR1085951 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1322046 2 0.1007 0.6857 0.004 0.968 0.000 0.016 0.004 0.008
#> SRR1316420 5 0.4435 0.3839 0.264 0.000 0.000 0.064 0.672 0.000
#> SRR1070913 6 0.2001 0.6784 0.000 0.048 0.000 0.040 0.000 0.912
#> SRR1345806 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.2594 0.6723 0.000 0.880 0.000 0.056 0.060 0.004
#> SRR1337666 2 0.4364 0.5238 0.008 0.684 0.000 0.008 0.276 0.024
#> SRR1076823 1 0.1010 0.6309 0.960 0.000 0.000 0.036 0.004 0.000
#> SRR1093954 4 0.4459 0.6505 0.000 0.156 0.000 0.712 0.000 0.132
#> SRR1451921 1 0.5064 0.4604 0.668 0.056 0.000 0.232 0.000 0.044
#> SRR1491257 5 0.3772 0.5425 0.160 0.000 0.000 0.068 0.772 0.000
#> SRR1416979 2 0.4054 0.6318 0.012 0.808 0.000 0.068 0.040 0.072
#> SRR1419015 1 0.5300 0.3495 0.496 0.000 0.000 0.400 0.104 0.000
#> SRR817649 5 0.5142 -0.0721 0.008 0.432 0.000 0.044 0.508 0.008
#> SRR1466376 2 0.1138 0.6875 0.004 0.960 0.000 0.024 0.000 0.012
#> SRR1392055 6 0.4320 0.5870 0.008 0.240 0.000 0.048 0.000 0.704
#> SRR1120913 2 0.2939 0.6741 0.008 0.860 0.000 0.060 0.000 0.072
#> SRR1120869 2 0.4002 0.4266 0.000 0.660 0.000 0.320 0.000 0.020
#> SRR1319419 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR816495 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR818694 4 0.6513 0.2444 0.132 0.068 0.000 0.480 0.000 0.320
#> SRR1465653 5 0.0000 0.6493 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1475952 1 0.1049 0.6286 0.960 0.000 0.000 0.008 0.032 0.000
#> SRR1465040 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 6 0.5930 0.3337 0.008 0.324 0.000 0.180 0.000 0.488
#> SRR810129 2 0.5950 0.2479 0.008 0.512 0.000 0.232 0.000 0.248
#> SRR1400141 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 5 0.4962 0.0112 0.416 0.000 0.000 0.068 0.516 0.000
#> SRR1437576 6 0.3695 0.6626 0.000 0.084 0.044 0.052 0.000 0.820
#> SRR814407 1 0.6068 0.3519 0.540 0.000 0.132 0.040 0.288 0.000
#> SRR1332403 2 0.2191 0.6571 0.004 0.876 0.000 0.120 0.000 0.000
#> SRR1099598 4 0.4389 0.5552 0.008 0.048 0.000 0.692 0.000 0.252
#> SRR1327723 2 0.1285 0.6790 0.004 0.944 0.000 0.052 0.000 0.000
#> SRR1392525 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1320536 1 0.4760 0.3988 0.604 0.000 0.000 0.068 0.328 0.000
#> SRR1083824 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1351390 1 0.4972 0.3978 0.628 0.000 0.000 0.044 0.300 0.028
#> SRR1309141 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1452803 2 0.1644 0.6822 0.004 0.932 0.000 0.052 0.000 0.012
#> SRR811631 3 0.1918 0.8806 0.000 0.000 0.904 0.008 0.000 0.088
#> SRR1485563 4 0.6695 0.2880 0.052 0.200 0.000 0.440 0.000 0.308
#> SRR1311531 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.4365 0.5116 0.004 0.040 0.000 0.664 0.000 0.292
#> SRR1480831 2 0.2346 0.6536 0.008 0.868 0.000 0.124 0.000 0.000
#> SRR1083892 5 0.2796 0.6182 0.080 0.008 0.000 0.044 0.868 0.000
#> SRR809873 4 0.3868 -0.0406 0.496 0.000 0.000 0.504 0.000 0.000
#> SRR1341854 2 0.1297 0.6831 0.000 0.948 0.000 0.040 0.012 0.000
#> SRR1399335 6 0.5842 0.4220 0.008 0.272 0.000 0.192 0.000 0.528
#> SRR1464209 5 0.0820 0.6460 0.012 0.000 0.000 0.016 0.972 0.000
#> SRR1389886 2 0.3375 0.6433 0.008 0.824 0.000 0.112 0.000 0.056
#> SRR1400730 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1448008 2 0.6455 0.1237 0.384 0.440 0.000 0.088 0.000 0.088
#> SRR1087606 5 0.2222 0.5909 0.084 0.000 0.000 0.008 0.896 0.012
#> SRR1445111 1 0.4310 0.3591 0.580 0.000 0.000 0.024 0.396 0.000
#> SRR816865 4 0.3163 0.6377 0.004 0.212 0.000 0.780 0.000 0.004
#> SRR1323360 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.0000 0.9772 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1480329 6 0.5675 0.1635 0.028 0.396 0.000 0.080 0.000 0.496
#> SRR1403322 1 0.1814 0.6224 0.900 0.000 0.000 0.100 0.000 0.000
#> SRR1093625 1 0.4703 0.4184 0.620 0.000 0.000 0.068 0.312 0.000
#> SRR1479977 6 0.2214 0.6894 0.000 0.096 0.000 0.016 0.000 0.888
#> SRR1082035 4 0.5268 0.2698 0.016 0.060 0.000 0.572 0.004 0.348
#> SRR1393046 6 0.5653 0.5318 0.004 0.208 0.120 0.036 0.000 0.632
#> SRR1466663 5 0.7967 -0.1258 0.016 0.284 0.000 0.172 0.288 0.240
#> SRR1384456 1 0.4760 0.3988 0.604 0.000 0.000 0.068 0.328 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "pam"]
# you can also extract it by
# res = res_list["CV:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 1.000 0.984 0.994 0.2851 0.716 0.716
#> 3 3 0.451 0.678 0.837 0.8681 0.754 0.658
#> 4 4 0.521 0.625 0.800 0.2538 0.747 0.509
#> 5 5 0.566 0.591 0.787 0.1025 0.910 0.735
#> 6 6 0.603 0.648 0.803 0.0297 0.950 0.833
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
#> SRR810713 2 0.0000 0.9961 0.000 1.000
#> SRR808862 1 0.0000 0.9839 1.000 0.000
#> SRR1500382 2 0.0000 0.9961 0.000 1.000
#> SRR1322683 2 0.0000 0.9961 0.000 1.000
#> SRR1329811 2 0.0000 0.9961 0.000 1.000
#> SRR1087297 2 0.0000 0.9961 0.000 1.000
#> SRR1072626 2 0.0000 0.9961 0.000 1.000
#> SRR1407428 2 0.0000 0.9961 0.000 1.000
#> SRR1321029 2 0.0000 0.9961 0.000 1.000
#> SRR1500282 2 0.0000 0.9961 0.000 1.000
#> SRR1100496 1 0.0000 0.9839 1.000 0.000
#> SRR1308778 2 0.0000 0.9961 0.000 1.000
#> SRR1445304 2 0.0000 0.9961 0.000 1.000
#> SRR1099378 2 0.0000 0.9961 0.000 1.000
#> SRR1347412 2 0.1184 0.9798 0.016 0.984
#> SRR1099694 2 0.0000 0.9961 0.000 1.000
#> SRR1088365 2 0.0000 0.9961 0.000 1.000
#> SRR1325752 2 0.0000 0.9961 0.000 1.000
#> SRR1416713 2 0.0000 0.9961 0.000 1.000
#> SRR1074474 2 0.0000 0.9961 0.000 1.000
#> SRR1469369 1 0.0000 0.9839 1.000 0.000
#> SRR1400507 2 0.0000 0.9961 0.000 1.000
#> SRR1378179 2 0.0000 0.9961 0.000 1.000
#> SRR1377905 2 0.0000 0.9961 0.000 1.000
#> SRR1089479 2 0.0000 0.9961 0.000 1.000
#> SRR1073365 2 0.0000 0.9961 0.000 1.000
#> SRR1500306 2 0.0000 0.9961 0.000 1.000
#> SRR1101566 2 0.0000 0.9961 0.000 1.000
#> SRR1350503 1 0.0000 0.9839 1.000 0.000
#> SRR1446007 1 0.0000 0.9839 1.000 0.000
#> SRR1102875 2 0.0000 0.9961 0.000 1.000
#> SRR1380293 2 0.0000 0.9961 0.000 1.000
#> SRR1331198 2 0.0000 0.9961 0.000 1.000
#> SRR1092686 1 0.0000 0.9839 1.000 0.000
#> SRR1069421 2 0.0000 0.9961 0.000 1.000
#> SRR1341650 2 0.0000 0.9961 0.000 1.000
#> SRR1357276 2 0.0000 0.9961 0.000 1.000
#> SRR1498374 2 0.0000 0.9961 0.000 1.000
#> SRR1093721 2 0.0000 0.9961 0.000 1.000
#> SRR1464660 2 0.0000 0.9961 0.000 1.000
#> SRR1402051 2 0.0000 0.9961 0.000 1.000
#> SRR1488734 2 0.0000 0.9961 0.000 1.000
#> SRR1082616 1 0.0000 0.9839 1.000 0.000
#> SRR1099427 2 0.0000 0.9961 0.000 1.000
#> SRR1453093 2 0.0000 0.9961 0.000 1.000
#> SRR1357064 2 0.0000 0.9961 0.000 1.000
#> SRR811237 2 0.0000 0.9961 0.000 1.000
#> SRR1100848 2 0.0000 0.9961 0.000 1.000
#> SRR1346755 2 0.0000 0.9961 0.000 1.000
#> SRR1472529 2 0.0000 0.9961 0.000 1.000
#> SRR1398905 1 0.0000 0.9839 1.000 0.000
#> SRR1082733 2 0.0000 0.9961 0.000 1.000
#> SRR1308035 1 0.0000 0.9839 1.000 0.000
#> SRR1466445 1 0.0000 0.9839 1.000 0.000
#> SRR1359080 2 0.0000 0.9961 0.000 1.000
#> SRR1455825 2 0.0000 0.9961 0.000 1.000
#> SRR1389300 2 0.0000 0.9961 0.000 1.000
#> SRR812246 1 0.0000 0.9839 1.000 0.000
#> SRR1076632 2 0.0000 0.9961 0.000 1.000
#> SRR1415567 2 0.0000 0.9961 0.000 1.000
#> SRR1331900 2 0.0000 0.9961 0.000 1.000
#> SRR1452099 2 0.0000 0.9961 0.000 1.000
#> SRR1352346 2 0.0000 0.9961 0.000 1.000
#> SRR1364034 2 0.0000 0.9961 0.000 1.000
#> SRR1086046 2 0.0000 0.9961 0.000 1.000
#> SRR1407226 2 0.0000 0.9961 0.000 1.000
#> SRR1319363 2 0.0000 0.9961 0.000 1.000
#> SRR1446961 1 0.0672 0.9765 0.992 0.008
#> SRR1486650 2 0.0000 0.9961 0.000 1.000
#> SRR1470152 2 0.0000 0.9961 0.000 1.000
#> SRR1454785 1 0.0000 0.9839 1.000 0.000
#> SRR1092329 2 0.0000 0.9961 0.000 1.000
#> SRR1091476 1 0.0000 0.9839 1.000 0.000
#> SRR1073775 2 0.0000 0.9961 0.000 1.000
#> SRR1366873 2 0.0000 0.9961 0.000 1.000
#> SRR1398114 2 0.0000 0.9961 0.000 1.000
#> SRR1089950 2 0.0000 0.9961 0.000 1.000
#> SRR1433272 2 0.0000 0.9961 0.000 1.000
#> SRR1075314 2 0.0000 0.9961 0.000 1.000
#> SRR1085590 2 0.9993 0.0325 0.484 0.516
#> SRR1100752 1 0.0000 0.9839 1.000 0.000
#> SRR1391494 2 0.0000 0.9961 0.000 1.000
#> SRR1333263 2 0.0000 0.9961 0.000 1.000
#> SRR1310231 2 0.0000 0.9961 0.000 1.000
#> SRR1094144 2 0.0000 0.9961 0.000 1.000
#> SRR1092160 2 0.0000 0.9961 0.000 1.000
#> SRR1320300 2 0.0000 0.9961 0.000 1.000
#> SRR1322747 2 0.0000 0.9961 0.000 1.000
#> SRR1432719 1 0.0000 0.9839 1.000 0.000
#> SRR1100728 2 0.0000 0.9961 0.000 1.000
#> SRR1087511 2 0.0000 0.9961 0.000 1.000
#> SRR1470336 2 0.0000 0.9961 0.000 1.000
#> SRR1322536 2 0.0000 0.9961 0.000 1.000
#> SRR1100824 2 0.0000 0.9961 0.000 1.000
#> SRR1085951 1 0.0000 0.9839 1.000 0.000
#> SRR1322046 2 0.0000 0.9961 0.000 1.000
#> SRR1316420 2 0.0000 0.9961 0.000 1.000
#> SRR1070913 2 0.0000 0.9961 0.000 1.000
#> SRR1345806 1 0.0000 0.9839 1.000 0.000
#> SRR1313872 2 0.0000 0.9961 0.000 1.000
#> SRR1337666 2 0.0000 0.9961 0.000 1.000
#> SRR1076823 2 0.0000 0.9961 0.000 1.000
#> SRR1093954 2 0.0000 0.9961 0.000 1.000
#> SRR1451921 2 0.0000 0.9961 0.000 1.000
#> SRR1491257 2 0.0000 0.9961 0.000 1.000
#> SRR1416979 2 0.0000 0.9961 0.000 1.000
#> SRR1419015 2 0.0000 0.9961 0.000 1.000
#> SRR817649 2 0.0000 0.9961 0.000 1.000
#> SRR1466376 2 0.0000 0.9961 0.000 1.000
#> SRR1392055 2 0.0000 0.9961 0.000 1.000
#> SRR1120913 2 0.0000 0.9961 0.000 1.000
#> SRR1120869 2 0.0000 0.9961 0.000 1.000
#> SRR1319419 1 0.0000 0.9839 1.000 0.000
#> SRR816495 1 0.0000 0.9839 1.000 0.000
#> SRR818694 2 0.0000 0.9961 0.000 1.000
#> SRR1465653 2 0.0000 0.9961 0.000 1.000
#> SRR1475952 2 0.0000 0.9961 0.000 1.000
#> SRR1465040 1 0.0000 0.9839 1.000 0.000
#> SRR1088461 2 0.0000 0.9961 0.000 1.000
#> SRR810129 2 0.0000 0.9961 0.000 1.000
#> SRR1400141 1 0.0000 0.9839 1.000 0.000
#> SRR1349585 2 0.0000 0.9961 0.000 1.000
#> SRR1437576 2 0.0000 0.9961 0.000 1.000
#> SRR814407 1 0.9754 0.3071 0.592 0.408
#> SRR1332403 2 0.0000 0.9961 0.000 1.000
#> SRR1099598 2 0.0000 0.9961 0.000 1.000
#> SRR1327723 2 0.0000 0.9961 0.000 1.000
#> SRR1392525 2 0.0000 0.9961 0.000 1.000
#> SRR1320536 2 0.0000 0.9961 0.000 1.000
#> SRR1083824 2 0.0000 0.9961 0.000 1.000
#> SRR1351390 2 0.0000 0.9961 0.000 1.000
#> SRR1309141 2 0.0000 0.9961 0.000 1.000
#> SRR1452803 2 0.0000 0.9961 0.000 1.000
#> SRR811631 2 0.0000 0.9961 0.000 1.000
#> SRR1485563 2 0.0000 0.9961 0.000 1.000
#> SRR1311531 1 0.0000 0.9839 1.000 0.000
#> SRR1353076 2 0.0000 0.9961 0.000 1.000
#> SRR1480831 2 0.0000 0.9961 0.000 1.000
#> SRR1083892 2 0.0000 0.9961 0.000 1.000
#> SRR809873 2 0.0000 0.9961 0.000 1.000
#> SRR1341854 2 0.0000 0.9961 0.000 1.000
#> SRR1399335 2 0.0000 0.9961 0.000 1.000
#> SRR1464209 2 0.0000 0.9961 0.000 1.000
#> SRR1389886 2 0.0000 0.9961 0.000 1.000
#> SRR1400730 1 0.0000 0.9839 1.000 0.000
#> SRR1448008 2 0.0000 0.9961 0.000 1.000
#> SRR1087606 2 0.0000 0.9961 0.000 1.000
#> SRR1445111 2 0.0000 0.9961 0.000 1.000
#> SRR816865 2 0.0000 0.9961 0.000 1.000
#> SRR1323360 1 0.0000 0.9839 1.000 0.000
#> SRR1417364 1 0.0000 0.9839 1.000 0.000
#> SRR1480329 2 0.0000 0.9961 0.000 1.000
#> SRR1403322 2 0.0000 0.9961 0.000 1.000
#> SRR1093625 2 0.0000 0.9961 0.000 1.000
#> SRR1479977 2 0.0000 0.9961 0.000 1.000
#> SRR1082035 2 0.0000 0.9961 0.000 1.000
#> SRR1393046 2 0.0000 0.9961 0.000 1.000
#> SRR1466663 2 0.0000 0.9961 0.000 1.000
#> SRR1384456 2 0.0000 0.9961 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.3192 0.761 0.112 0.888 0.000
#> SRR808862 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1322683 2 0.0424 0.767 0.008 0.992 0.000
#> SRR1329811 2 0.1411 0.754 0.036 0.964 0.000
#> SRR1087297 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1072626 2 0.5529 0.692 0.296 0.704 0.000
#> SRR1407428 1 0.1643 0.631 0.956 0.044 0.000
#> SRR1321029 2 0.0237 0.771 0.004 0.996 0.000
#> SRR1500282 1 0.5016 0.587 0.760 0.240 0.000
#> SRR1100496 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1308778 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1445304 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1099378 2 0.5905 0.427 0.352 0.648 0.000
#> SRR1347412 1 0.5497 0.501 0.708 0.292 0.000
#> SRR1099694 2 0.5254 0.709 0.264 0.736 0.000
#> SRR1088365 2 0.5948 0.612 0.360 0.640 0.000
#> SRR1325752 2 0.5431 0.602 0.284 0.716 0.000
#> SRR1416713 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1074474 1 0.3116 0.646 0.892 0.108 0.000
#> SRR1469369 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1400507 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1378179 2 0.0424 0.771 0.008 0.992 0.000
#> SRR1377905 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1089479 1 0.3192 0.647 0.888 0.112 0.000
#> SRR1073365 2 0.5497 0.695 0.292 0.708 0.000
#> SRR1500306 1 0.4291 0.557 0.820 0.180 0.000
#> SRR1101566 2 0.5560 0.692 0.300 0.700 0.000
#> SRR1350503 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1102875 2 0.5560 0.689 0.300 0.700 0.000
#> SRR1380293 2 0.0237 0.769 0.004 0.996 0.000
#> SRR1331198 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1092686 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1069421 2 0.4654 0.673 0.208 0.792 0.000
#> SRR1341650 2 0.6204 0.500 0.424 0.576 0.000
#> SRR1357276 2 0.2261 0.769 0.068 0.932 0.000
#> SRR1498374 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1093721 2 0.4842 0.738 0.224 0.776 0.000
#> SRR1464660 2 0.3619 0.633 0.136 0.864 0.000
#> SRR1402051 1 0.6295 -0.158 0.528 0.472 0.000
#> SRR1488734 2 0.4399 0.718 0.188 0.812 0.000
#> SRR1082616 3 0.0237 0.969 0.004 0.000 0.996
#> SRR1099427 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1453093 2 0.4452 0.719 0.192 0.808 0.000
#> SRR1357064 1 0.6280 0.377 0.540 0.460 0.000
#> SRR811237 2 0.5058 0.684 0.244 0.756 0.000
#> SRR1100848 2 0.4796 0.694 0.220 0.780 0.000
#> SRR1346755 2 0.0424 0.770 0.008 0.992 0.000
#> SRR1472529 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1398905 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1082733 2 0.5497 0.695 0.292 0.708 0.000
#> SRR1308035 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1359080 2 0.4399 0.718 0.188 0.812 0.000
#> SRR1455825 2 0.5497 0.695 0.292 0.708 0.000
#> SRR1389300 2 0.3038 0.758 0.104 0.896 0.000
#> SRR812246 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1076632 2 0.5591 0.685 0.304 0.696 0.000
#> SRR1415567 1 0.3116 0.646 0.892 0.108 0.000
#> SRR1331900 2 0.5397 0.706 0.280 0.720 0.000
#> SRR1452099 2 0.5529 0.582 0.296 0.704 0.000
#> SRR1352346 2 0.0424 0.767 0.008 0.992 0.000
#> SRR1364034 2 0.3879 0.762 0.152 0.848 0.000
#> SRR1086046 2 0.4555 0.710 0.200 0.800 0.000
#> SRR1407226 1 0.2448 0.605 0.924 0.076 0.000
#> SRR1319363 2 0.6309 0.269 0.496 0.504 0.000
#> SRR1446961 3 0.0661 0.959 0.004 0.008 0.988
#> SRR1486650 1 0.3116 0.646 0.892 0.108 0.000
#> SRR1470152 2 0.3752 0.624 0.144 0.856 0.000
#> SRR1454785 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1092329 2 0.4062 0.738 0.164 0.836 0.000
#> SRR1091476 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1073775 2 0.5760 0.660 0.328 0.672 0.000
#> SRR1366873 2 0.3116 0.758 0.108 0.892 0.000
#> SRR1398114 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1089950 2 0.6274 0.154 0.456 0.544 0.000
#> SRR1433272 2 0.1411 0.761 0.036 0.964 0.000
#> SRR1075314 1 0.6305 -0.202 0.516 0.484 0.000
#> SRR1085590 3 0.9521 -0.221 0.192 0.368 0.440
#> SRR1100752 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1391494 2 0.2448 0.771 0.076 0.924 0.000
#> SRR1333263 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1310231 2 0.0592 0.771 0.012 0.988 0.000
#> SRR1094144 2 0.5905 0.627 0.352 0.648 0.000
#> SRR1092160 2 0.4399 0.718 0.188 0.812 0.000
#> SRR1320300 2 0.5497 0.695 0.292 0.708 0.000
#> SRR1322747 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1432719 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1100728 2 0.6095 0.550 0.392 0.608 0.000
#> SRR1087511 2 0.6291 0.337 0.468 0.532 0.000
#> SRR1470336 1 0.1643 0.625 0.956 0.044 0.000
#> SRR1322536 1 0.6295 -0.167 0.528 0.472 0.000
#> SRR1100824 1 0.6280 -0.115 0.540 0.460 0.000
#> SRR1085951 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1316420 1 0.6260 0.419 0.552 0.448 0.000
#> SRR1070913 2 0.3116 0.758 0.108 0.892 0.000
#> SRR1345806 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1313872 2 0.1860 0.746 0.052 0.948 0.000
#> SRR1337666 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1076823 1 0.1753 0.634 0.952 0.048 0.000
#> SRR1093954 2 0.5529 0.692 0.296 0.704 0.000
#> SRR1451921 2 0.6045 0.583 0.380 0.620 0.000
#> SRR1491257 2 0.1163 0.758 0.028 0.972 0.000
#> SRR1416979 2 0.4399 0.718 0.188 0.812 0.000
#> SRR1419015 2 0.5058 0.630 0.244 0.756 0.000
#> SRR817649 2 0.4504 0.714 0.196 0.804 0.000
#> SRR1466376 2 0.2625 0.765 0.084 0.916 0.000
#> SRR1392055 2 0.3267 0.762 0.116 0.884 0.000
#> SRR1120913 2 0.0592 0.765 0.012 0.988 0.000
#> SRR1120869 2 0.5497 0.695 0.292 0.708 0.000
#> SRR1319419 3 0.0237 0.969 0.004 0.000 0.996
#> SRR816495 3 0.0000 0.972 0.000 0.000 1.000
#> SRR818694 2 0.6126 0.523 0.400 0.600 0.000
#> SRR1465653 2 0.1031 0.760 0.024 0.976 0.000
#> SRR1475952 1 0.0237 0.607 0.996 0.004 0.000
#> SRR1465040 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1088461 2 0.5497 0.695 0.292 0.708 0.000
#> SRR810129 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1400141 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1349585 1 0.5706 0.504 0.680 0.320 0.000
#> SRR1437576 2 0.0237 0.768 0.004 0.996 0.000
#> SRR814407 1 0.8637 0.114 0.456 0.100 0.444
#> SRR1332403 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1099598 2 0.5678 0.672 0.316 0.684 0.000
#> SRR1327723 2 0.0592 0.773 0.012 0.988 0.000
#> SRR1392525 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1320536 1 0.3116 0.646 0.892 0.108 0.000
#> SRR1083824 2 0.4452 0.718 0.192 0.808 0.000
#> SRR1351390 1 0.6274 -0.112 0.544 0.456 0.000
#> SRR1309141 2 0.1289 0.762 0.032 0.968 0.000
#> SRR1452803 2 0.0000 0.769 0.000 1.000 0.000
#> SRR811631 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1485563 2 0.5835 0.644 0.340 0.660 0.000
#> SRR1311531 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1353076 2 0.4121 0.759 0.168 0.832 0.000
#> SRR1480831 2 0.3192 0.761 0.112 0.888 0.000
#> SRR1083892 2 0.1529 0.760 0.040 0.960 0.000
#> SRR809873 1 0.6274 -0.112 0.544 0.456 0.000
#> SRR1341854 2 0.0000 0.769 0.000 1.000 0.000
#> SRR1399335 2 0.4504 0.720 0.196 0.804 0.000
#> SRR1464209 1 0.6062 0.394 0.616 0.384 0.000
#> SRR1389886 2 0.3038 0.758 0.104 0.896 0.000
#> SRR1400730 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1448008 2 0.4605 0.720 0.204 0.796 0.000
#> SRR1087606 2 0.6267 0.155 0.452 0.548 0.000
#> SRR1445111 1 0.3116 0.646 0.892 0.108 0.000
#> SRR816865 2 0.5591 0.688 0.304 0.696 0.000
#> SRR1323360 3 0.0000 0.972 0.000 0.000 1.000
#> SRR1417364 3 0.0237 0.969 0.004 0.000 0.996
#> SRR1480329 2 0.2625 0.769 0.084 0.916 0.000
#> SRR1403322 1 0.6295 -0.175 0.528 0.472 0.000
#> SRR1093625 1 0.3116 0.646 0.892 0.108 0.000
#> SRR1479977 2 0.3267 0.761 0.116 0.884 0.000
#> SRR1082035 1 0.6274 -0.112 0.544 0.456 0.000
#> SRR1393046 2 0.0237 0.768 0.004 0.996 0.000
#> SRR1466663 2 0.5016 0.710 0.240 0.760 0.000
#> SRR1384456 1 0.3116 0.646 0.892 0.108 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 4 0.3444 0.4812 0.000 0.184 0.000 0.816
#> SRR808862 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.4356 0.7681 0.000 0.708 0.000 0.292
#> SRR1322683 2 0.3801 0.7478 0.000 0.780 0.000 0.220
#> SRR1329811 2 0.4399 0.7423 0.020 0.768 0.000 0.212
#> SRR1087297 2 0.4454 0.7651 0.000 0.692 0.000 0.308
#> SRR1072626 4 0.4746 -0.3035 0.000 0.368 0.000 0.632
#> SRR1407428 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1321029 2 0.4331 0.7694 0.000 0.712 0.000 0.288
#> SRR1500282 4 0.7761 -0.3262 0.376 0.236 0.000 0.388
#> SRR1100496 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR1308778 2 0.4382 0.7687 0.000 0.704 0.000 0.296
#> SRR1445304 2 0.4898 0.6878 0.000 0.584 0.000 0.416
#> SRR1099378 2 0.4453 0.3239 0.012 0.744 0.000 0.244
#> SRR1347412 1 0.4543 0.7541 0.676 0.324 0.000 0.000
#> SRR1099694 4 0.4925 -0.4523 0.000 0.428 0.000 0.572
#> SRR1088365 4 0.0707 0.6808 0.020 0.000 0.000 0.980
#> SRR1325752 2 0.6340 0.5408 0.064 0.528 0.000 0.408
#> SRR1416713 2 0.4406 0.7663 0.000 0.700 0.000 0.300
#> SRR1074474 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.0336 0.9535 0.000 0.008 0.992 0.000
#> SRR1400507 2 0.4925 0.6711 0.000 0.572 0.000 0.428
#> SRR1378179 2 0.4477 0.7647 0.000 0.688 0.000 0.312
#> SRR1377905 2 0.4072 0.7628 0.000 0.748 0.000 0.252
#> SRR1089479 1 0.6875 0.6326 0.596 0.220 0.000 0.184
#> SRR1073365 4 0.0188 0.6813 0.000 0.004 0.000 0.996
#> SRR1500306 1 0.7790 0.3649 0.408 0.252 0.000 0.340
#> SRR1101566 4 0.1940 0.6550 0.000 0.076 0.000 0.924
#> SRR1350503 3 0.0469 0.9512 0.000 0.012 0.988 0.000
#> SRR1446007 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR1102875 4 0.0188 0.6813 0.000 0.004 0.000 0.996
#> SRR1380293 2 0.4431 0.7661 0.000 0.696 0.000 0.304
#> SRR1331198 2 0.4331 0.7682 0.000 0.712 0.000 0.288
#> SRR1092686 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.6678 0.6774 0.148 0.612 0.000 0.240
#> SRR1341650 4 0.3351 0.6162 0.148 0.008 0.000 0.844
#> SRR1357276 2 0.4790 0.7252 0.000 0.620 0.000 0.380
#> SRR1498374 4 0.4454 0.1796 0.000 0.308 0.000 0.692
#> SRR1093721 4 0.4250 0.2016 0.000 0.276 0.000 0.724
#> SRR1464660 2 0.1938 0.5352 0.012 0.936 0.000 0.052
#> SRR1402051 2 0.7252 -0.2300 0.144 0.436 0.000 0.420
#> SRR1488734 2 0.4999 0.5531 0.000 0.508 0.000 0.492
#> SRR1082616 3 0.2011 0.8997 0.000 0.080 0.920 0.000
#> SRR1099427 2 0.3942 0.7435 0.000 0.764 0.000 0.236
#> SRR1453093 4 0.2408 0.6149 0.000 0.104 0.000 0.896
#> SRR1357064 1 0.2988 0.7295 0.876 0.012 0.000 0.112
#> SRR811237 4 0.4454 0.0834 0.000 0.308 0.000 0.692
#> SRR1100848 2 0.5750 0.5687 0.028 0.532 0.000 0.440
#> SRR1346755 2 0.4304 0.7104 0.000 0.716 0.000 0.284
#> SRR1472529 2 0.4888 0.6899 0.000 0.588 0.000 0.412
#> SRR1398905 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1082733 4 0.0188 0.6813 0.000 0.004 0.000 0.996
#> SRR1308035 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1359080 4 0.4830 -0.2531 0.000 0.392 0.000 0.608
#> SRR1455825 4 0.0336 0.6797 0.000 0.008 0.000 0.992
#> SRR1389300 4 0.3528 0.4668 0.000 0.192 0.000 0.808
#> SRR812246 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR1076632 4 0.0000 0.6816 0.000 0.000 0.000 1.000
#> SRR1415567 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1331900 4 0.0469 0.6776 0.000 0.012 0.000 0.988
#> SRR1452099 2 0.7082 0.4504 0.124 0.448 0.000 0.428
#> SRR1352346 2 0.5411 0.7639 0.032 0.656 0.000 0.312
#> SRR1364034 2 0.5000 0.5934 0.000 0.504 0.000 0.496
#> SRR1086046 4 0.2714 0.6061 0.004 0.112 0.000 0.884
#> SRR1407226 1 0.6555 0.6916 0.632 0.212 0.000 0.156
#> SRR1319363 2 0.7106 0.2085 0.148 0.528 0.000 0.324
#> SRR1446961 3 0.2469 0.8700 0.000 0.108 0.892 0.000
#> SRR1486650 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1470152 2 0.2500 0.5167 0.044 0.916 0.000 0.040
#> SRR1454785 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1092329 2 0.4761 0.6128 0.000 0.628 0.000 0.372
#> SRR1091476 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1073775 4 0.0469 0.6819 0.012 0.000 0.000 0.988
#> SRR1366873 4 0.3569 0.4663 0.000 0.196 0.000 0.804
#> SRR1398114 4 0.3486 0.4713 0.000 0.188 0.000 0.812
#> SRR1089950 2 0.6339 0.1711 0.148 0.656 0.000 0.196
#> SRR1433272 2 0.4883 0.7709 0.016 0.696 0.000 0.288
#> SRR1075314 4 0.4951 0.4131 0.044 0.212 0.000 0.744
#> SRR1085590 3 0.7874 -0.1017 0.000 0.336 0.380 0.284
#> SRR1100752 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.4406 0.7152 0.000 0.700 0.000 0.300
#> SRR1333263 2 0.3726 0.7457 0.000 0.788 0.000 0.212
#> SRR1310231 2 0.4522 0.7612 0.000 0.680 0.000 0.320
#> SRR1094144 4 0.1118 0.6762 0.036 0.000 0.000 0.964
#> SRR1092160 2 0.4998 0.5579 0.000 0.512 0.000 0.488
#> SRR1320300 4 0.0000 0.6816 0.000 0.000 0.000 1.000
#> SRR1322747 2 0.3764 0.7457 0.000 0.784 0.000 0.216
#> SRR1432719 3 0.0336 0.9535 0.000 0.008 0.992 0.000
#> SRR1100728 4 0.1854 0.6738 0.048 0.012 0.000 0.940
#> SRR1087511 4 0.4328 0.4308 0.008 0.244 0.000 0.748
#> SRR1470336 1 0.5184 0.7799 0.732 0.212 0.000 0.056
#> SRR1322536 4 0.5136 0.3924 0.048 0.224 0.000 0.728
#> SRR1100824 4 0.6731 0.2056 0.156 0.236 0.000 0.608
#> SRR1085951 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1322046 2 0.4331 0.7682 0.000 0.712 0.000 0.288
#> SRR1316420 1 0.4250 0.7645 0.724 0.276 0.000 0.000
#> SRR1070913 2 0.5050 0.6918 0.004 0.588 0.000 0.408
#> SRR1345806 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR1313872 2 0.6448 0.7175 0.120 0.628 0.000 0.252
#> SRR1337666 2 0.4331 0.7682 0.000 0.712 0.000 0.288
#> SRR1076823 1 0.3486 0.7068 0.812 0.000 0.000 0.188
#> SRR1093954 4 0.0188 0.6813 0.000 0.004 0.000 0.996
#> SRR1451921 4 0.7273 -0.3943 0.148 0.400 0.000 0.452
#> SRR1491257 2 0.7168 0.6589 0.192 0.552 0.000 0.256
#> SRR1416979 2 0.4994 0.5642 0.000 0.520 0.000 0.480
#> SRR1419015 4 0.5016 0.1684 0.004 0.396 0.000 0.600
#> SRR817649 2 0.5165 0.5591 0.004 0.512 0.000 0.484
#> SRR1466376 2 0.4843 0.7105 0.000 0.604 0.000 0.396
#> SRR1392055 2 0.4925 0.6827 0.000 0.572 0.000 0.428
#> SRR1120913 2 0.4621 0.7698 0.008 0.708 0.000 0.284
#> SRR1120869 4 0.0188 0.6813 0.000 0.004 0.000 0.996
#> SRR1319419 3 0.1867 0.9065 0.000 0.072 0.928 0.000
#> SRR816495 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR818694 4 0.1637 0.6649 0.000 0.060 0.000 0.940
#> SRR1465653 2 0.5113 0.7684 0.032 0.704 0.000 0.264
#> SRR1475952 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1465040 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1088461 4 0.0188 0.6810 0.000 0.004 0.000 0.996
#> SRR810129 2 0.4888 0.6899 0.000 0.588 0.000 0.412
#> SRR1400141 3 0.0188 0.9551 0.000 0.004 0.996 0.000
#> SRR1349585 1 0.0336 0.8270 0.992 0.008 0.000 0.000
#> SRR1437576 2 0.3801 0.7480 0.000 0.780 0.000 0.220
#> SRR814407 4 0.9639 -0.1635 0.132 0.280 0.248 0.340
#> SRR1332403 4 0.4406 0.1977 0.000 0.300 0.000 0.700
#> SRR1099598 4 0.0000 0.6816 0.000 0.000 0.000 1.000
#> SRR1327723 2 0.4661 0.7512 0.000 0.652 0.000 0.348
#> SRR1392525 2 0.3764 0.7452 0.000 0.784 0.000 0.216
#> SRR1320536 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.4843 0.5642 0.000 0.604 0.000 0.396
#> SRR1351390 2 0.6594 0.1258 0.148 0.624 0.000 0.228
#> SRR1309141 2 0.5184 0.7284 0.056 0.732 0.000 0.212
#> SRR1452803 2 0.4356 0.7681 0.000 0.708 0.000 0.292
#> SRR811631 2 0.3726 0.7457 0.000 0.788 0.000 0.212
#> SRR1485563 4 0.2271 0.6175 0.008 0.076 0.000 0.916
#> SRR1311531 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1353076 4 0.2814 0.5560 0.000 0.132 0.000 0.868
#> SRR1480831 2 0.4925 0.6802 0.000 0.572 0.000 0.428
#> SRR1083892 2 0.5078 0.7698 0.028 0.700 0.000 0.272
#> SRR809873 4 0.6472 0.2597 0.148 0.212 0.000 0.640
#> SRR1341854 2 0.4477 0.7628 0.000 0.688 0.000 0.312
#> SRR1399335 4 0.2408 0.6137 0.000 0.104 0.000 0.896
#> SRR1464209 1 0.7521 0.3761 0.420 0.396 0.000 0.184
#> SRR1389886 2 0.4985 0.6101 0.000 0.532 0.000 0.468
#> SRR1400730 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1448008 4 0.3610 0.4471 0.000 0.200 0.000 0.800
#> SRR1087606 2 0.6303 0.1773 0.148 0.660 0.000 0.192
#> SRR1445111 1 0.3569 0.7906 0.804 0.196 0.000 0.000
#> SRR816865 4 0.0524 0.6812 0.004 0.008 0.000 0.988
#> SRR1323360 3 0.0000 0.9555 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.1940 0.9032 0.000 0.076 0.924 0.000
#> SRR1480329 2 0.4888 0.6966 0.000 0.588 0.000 0.412
#> SRR1403322 4 0.5003 0.5275 0.148 0.084 0.000 0.768
#> SRR1093625 1 0.0000 0.8272 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.4888 0.6985 0.000 0.588 0.000 0.412
#> SRR1082035 4 0.6504 0.2631 0.148 0.216 0.000 0.636
#> SRR1393046 2 0.3764 0.7475 0.000 0.784 0.000 0.216
#> SRR1466663 4 0.6709 -0.5480 0.088 0.456 0.000 0.456
#> SRR1384456 1 0.0000 0.8272 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 4 0.3508 0.57100 0.000 0.252 0.000 0.748 0.000
#> SRR808862 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1500382 2 0.0324 0.73480 0.000 0.992 0.000 0.004 0.004
#> SRR1322683 2 0.3861 0.64402 0.000 0.728 0.000 0.008 0.264
#> SRR1329811 2 0.3548 0.58496 0.012 0.796 0.000 0.004 0.188
#> SRR1087297 2 0.0404 0.73732 0.000 0.988 0.000 0.012 0.000
#> SRR1072626 2 0.4273 0.45435 0.000 0.552 0.000 0.448 0.000
#> SRR1407428 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.3123 0.70010 0.000 0.828 0.000 0.012 0.160
#> SRR1500282 5 0.7189 0.29434 0.284 0.032 0.000 0.220 0.464
#> SRR1100496 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR1308778 2 0.0000 0.73445 0.000 1.000 0.000 0.000 0.000
#> SRR1445304 2 0.2690 0.70167 0.000 0.844 0.000 0.156 0.000
#> SRR1099378 2 0.6648 -0.04060 0.004 0.484 0.000 0.240 0.272
#> SRR1347412 5 0.5309 -0.07692 0.364 0.000 0.060 0.000 0.576
#> SRR1099694 2 0.3949 0.58626 0.000 0.668 0.000 0.332 0.000
#> SRR1088365 4 0.0671 0.70900 0.004 0.016 0.000 0.980 0.000
#> SRR1325752 2 0.3789 0.63253 0.020 0.768 0.000 0.212 0.000
#> SRR1416713 2 0.0324 0.73480 0.000 0.992 0.000 0.004 0.004
#> SRR1074474 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.1043 0.79336 0.000 0.000 0.960 0.000 0.040
#> SRR1400507 2 0.2966 0.68562 0.000 0.816 0.000 0.184 0.000
#> SRR1378179 2 0.1197 0.73685 0.000 0.952 0.000 0.048 0.000
#> SRR1377905 2 0.1270 0.73079 0.000 0.948 0.000 0.000 0.052
#> SRR1089479 1 0.6730 -0.04040 0.504 0.012 0.000 0.220 0.264
#> SRR1073365 4 0.1410 0.71518 0.000 0.060 0.000 0.940 0.000
#> SRR1500306 4 0.7765 -0.44762 0.264 0.064 0.000 0.396 0.276
#> SRR1101566 4 0.3508 0.51533 0.000 0.000 0.000 0.748 0.252
#> SRR1350503 3 0.0794 0.79855 0.000 0.000 0.972 0.000 0.028
#> SRR1446007 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 4 0.1043 0.71311 0.000 0.040 0.000 0.960 0.000
#> SRR1380293 2 0.0290 0.73632 0.000 0.992 0.000 0.008 0.000
#> SRR1331198 2 0.0324 0.73480 0.000 0.992 0.000 0.004 0.004
#> SRR1092686 3 0.0609 0.80780 0.000 0.000 0.980 0.000 0.020
#> SRR1069421 2 0.3807 0.69295 0.088 0.828 0.000 0.072 0.012
#> SRR1341650 4 0.4666 0.52627 0.088 0.000 0.000 0.732 0.180
#> SRR1357276 2 0.1965 0.72507 0.000 0.904 0.000 0.096 0.000
#> SRR1498374 4 0.6304 0.12708 0.000 0.384 0.000 0.460 0.156
#> SRR1093721 4 0.4291 -0.03649 0.000 0.464 0.000 0.536 0.000
#> SRR1464660 2 0.4367 0.02130 0.004 0.580 0.000 0.000 0.416
#> SRR1402051 4 0.7949 -0.34539 0.080 0.272 0.000 0.372 0.276
#> SRR1488734 2 0.3305 0.64044 0.000 0.776 0.000 0.224 0.000
#> SRR1082616 3 0.4152 0.56512 0.000 0.000 0.692 0.012 0.296
#> SRR1099427 2 0.4339 0.61844 0.000 0.684 0.000 0.020 0.296
#> SRR1453093 4 0.2471 0.62509 0.000 0.136 0.000 0.864 0.000
#> SRR1357064 1 0.1410 0.71027 0.940 0.060 0.000 0.000 0.000
#> SRR811237 2 0.4242 0.33522 0.000 0.572 0.000 0.428 0.000
#> SRR1100848 2 0.3550 0.63075 0.004 0.760 0.000 0.236 0.000
#> SRR1346755 2 0.4666 0.62913 0.000 0.704 0.000 0.056 0.240
#> SRR1472529 2 0.2773 0.70018 0.000 0.836 0.000 0.164 0.000
#> SRR1398905 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1082733 4 0.1732 0.71200 0.000 0.080 0.000 0.920 0.000
#> SRR1308035 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1466445 3 0.0404 0.80786 0.000 0.000 0.988 0.000 0.012
#> SRR1359080 2 0.3913 0.50658 0.000 0.676 0.000 0.324 0.000
#> SRR1455825 4 0.1121 0.71309 0.000 0.044 0.000 0.956 0.000
#> SRR1389300 4 0.3636 0.55385 0.000 0.272 0.000 0.728 0.000
#> SRR812246 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 4 0.1043 0.71311 0.000 0.040 0.000 0.960 0.000
#> SRR1415567 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 4 0.3622 0.64167 0.000 0.056 0.000 0.820 0.124
#> SRR1452099 2 0.4923 0.56453 0.068 0.680 0.000 0.252 0.000
#> SRR1352346 2 0.1372 0.73654 0.016 0.956 0.000 0.024 0.004
#> SRR1364034 2 0.3336 0.67361 0.000 0.772 0.000 0.228 0.000
#> SRR1086046 4 0.2674 0.61506 0.004 0.140 0.000 0.856 0.000
#> SRR1407226 1 0.6453 0.21036 0.552 0.012 0.000 0.180 0.256
#> SRR1319363 2 0.7582 0.09205 0.088 0.456 0.000 0.304 0.152
#> SRR1446961 3 0.4127 0.54566 0.000 0.008 0.680 0.000 0.312
#> SRR1486650 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 2 0.5569 0.01938 0.080 0.556 0.000 0.000 0.364
#> SRR1454785 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1092329 2 0.4617 0.65013 0.000 0.716 0.000 0.060 0.224
#> SRR1091476 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1073775 4 0.0510 0.70313 0.000 0.016 0.000 0.984 0.000
#> SRR1366873 4 0.4496 0.58085 0.000 0.092 0.000 0.752 0.156
#> SRR1398114 4 0.3612 0.55651 0.000 0.268 0.000 0.732 0.000
#> SRR1089950 2 0.7918 -0.24967 0.088 0.404 0.000 0.232 0.276
#> SRR1433272 2 0.0613 0.73667 0.004 0.984 0.000 0.008 0.004
#> SRR1075314 4 0.5025 0.35236 0.016 0.040 0.000 0.680 0.264
#> SRR1085590 3 0.7915 -0.00772 0.000 0.220 0.444 0.112 0.224
#> SRR1100752 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1391494 2 0.4243 0.63916 0.000 0.712 0.000 0.024 0.264
#> SRR1333263 2 0.5002 0.57617 0.000 0.636 0.052 0.000 0.312
#> SRR1310231 2 0.0794 0.73673 0.000 0.972 0.000 0.028 0.000
#> SRR1094144 4 0.1117 0.70369 0.016 0.020 0.000 0.964 0.000
#> SRR1092160 2 0.3452 0.63309 0.000 0.756 0.000 0.244 0.000
#> SRR1320300 4 0.1043 0.71385 0.000 0.040 0.000 0.960 0.000
#> SRR1322747 2 0.5272 0.56445 0.000 0.624 0.060 0.004 0.312
#> SRR1432719 3 0.1341 0.78535 0.000 0.000 0.944 0.000 0.056
#> SRR1100728 4 0.1725 0.71416 0.020 0.044 0.000 0.936 0.000
#> SRR1087511 4 0.2068 0.67370 0.000 0.004 0.000 0.904 0.092
#> SRR1470336 1 0.5315 0.46111 0.664 0.020 0.000 0.052 0.264
#> SRR1322536 4 0.4751 0.17697 0.008 0.008 0.000 0.564 0.420
#> SRR1100824 4 0.5705 0.12623 0.088 0.008 0.000 0.604 0.300
#> SRR1085951 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1322046 2 0.0451 0.73568 0.000 0.988 0.000 0.008 0.004
#> SRR1316420 1 0.5754 0.26305 0.604 0.136 0.000 0.000 0.260
#> SRR1070913 2 0.3006 0.70454 0.004 0.836 0.000 0.156 0.004
#> SRR1345806 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.2728 0.71665 0.068 0.888 0.000 0.040 0.004
#> SRR1337666 2 0.0324 0.73480 0.000 0.992 0.000 0.004 0.004
#> SRR1076823 1 0.3366 0.43915 0.784 0.004 0.000 0.212 0.000
#> SRR1093954 4 0.0963 0.71374 0.000 0.036 0.000 0.964 0.000
#> SRR1451921 2 0.5505 0.48363 0.084 0.588 0.000 0.328 0.000
#> SRR1491257 2 0.5604 0.42720 0.240 0.628 0.000 0.000 0.132
#> SRR1416979 2 0.3586 0.61309 0.000 0.736 0.000 0.264 0.000
#> SRR1419015 2 0.6871 0.02130 0.004 0.388 0.000 0.352 0.256
#> SRR817649 2 0.3210 0.64248 0.000 0.788 0.000 0.212 0.000
#> SRR1466376 2 0.2424 0.71145 0.000 0.868 0.000 0.132 0.000
#> SRR1392055 2 0.2561 0.71009 0.000 0.856 0.000 0.144 0.000
#> SRR1120913 2 0.0162 0.73401 0.000 0.996 0.000 0.000 0.004
#> SRR1120869 4 0.1478 0.71396 0.000 0.064 0.000 0.936 0.000
#> SRR1319419 3 0.3752 0.57549 0.000 0.000 0.708 0.000 0.292
#> SRR816495 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR818694 4 0.0290 0.70479 0.000 0.008 0.000 0.992 0.000
#> SRR1465653 2 0.3692 0.62074 0.028 0.812 0.000 0.008 0.152
#> SRR1475952 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1088461 4 0.1478 0.71380 0.000 0.064 0.000 0.936 0.000
#> SRR810129 2 0.2488 0.70846 0.000 0.872 0.000 0.124 0.004
#> SRR1400141 3 0.0000 0.80735 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 1 0.0290 0.78301 0.992 0.000 0.000 0.000 0.008
#> SRR1437576 2 0.3741 0.64545 0.000 0.732 0.000 0.004 0.264
#> SRR814407 5 0.5582 0.36120 0.068 0.000 0.060 0.168 0.704
#> SRR1332403 4 0.4273 0.30723 0.000 0.448 0.000 0.552 0.000
#> SRR1099598 4 0.1216 0.71158 0.000 0.020 0.000 0.960 0.020
#> SRR1327723 2 0.1792 0.73233 0.000 0.916 0.000 0.084 0.000
#> SRR1392525 2 0.4877 0.58984 0.000 0.652 0.012 0.024 0.312
#> SRR1320536 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.4911 0.59696 0.000 0.652 0.008 0.032 0.308
#> SRR1351390 5 0.7819 0.50200 0.084 0.200 0.000 0.308 0.408
#> SRR1309141 2 0.5063 0.57253 0.000 0.632 0.056 0.000 0.312
#> SRR1452803 2 0.0324 0.73480 0.000 0.992 0.000 0.004 0.004
#> SRR811631 2 0.3752 0.62976 0.000 0.708 0.000 0.000 0.292
#> SRR1485563 4 0.3934 0.43907 0.008 0.276 0.000 0.716 0.000
#> SRR1311531 3 0.1270 0.80488 0.000 0.000 0.948 0.000 0.052
#> SRR1353076 4 0.3143 0.61602 0.000 0.204 0.000 0.796 0.000
#> SRR1480831 2 0.2891 0.70153 0.000 0.824 0.000 0.176 0.000
#> SRR1083892 2 0.0613 0.73704 0.004 0.984 0.000 0.008 0.004
#> SRR809873 4 0.2351 0.64347 0.088 0.016 0.000 0.896 0.000
#> SRR1341854 2 0.0609 0.73587 0.000 0.980 0.000 0.020 0.000
#> SRR1399335 4 0.3039 0.63397 0.000 0.192 0.000 0.808 0.000
#> SRR1464209 5 0.8177 0.48117 0.232 0.156 0.000 0.200 0.412
#> SRR1389886 2 0.3039 0.67281 0.000 0.808 0.000 0.192 0.000
#> SRR1400730 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1448008 4 0.3480 0.49657 0.000 0.248 0.000 0.752 0.000
#> SRR1087606 5 0.7879 0.51978 0.084 0.256 0.000 0.248 0.412
#> SRR1445111 1 0.3741 0.53415 0.732 0.004 0.000 0.000 0.264
#> SRR816865 4 0.1732 0.71243 0.000 0.080 0.000 0.920 0.000
#> SRR1323360 3 0.3934 0.77107 0.000 0.000 0.716 0.008 0.276
#> SRR1417364 3 0.3837 0.55954 0.000 0.000 0.692 0.000 0.308
#> SRR1480329 2 0.3359 0.72216 0.000 0.844 0.000 0.084 0.072
#> SRR1403322 4 0.2448 0.64439 0.088 0.020 0.000 0.892 0.000
#> SRR1093625 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.3074 0.69791 0.000 0.804 0.000 0.196 0.000
#> SRR1082035 4 0.6484 0.39631 0.088 0.056 0.000 0.584 0.272
#> SRR1393046 2 0.3586 0.64603 0.000 0.736 0.000 0.000 0.264
#> SRR1466663 2 0.4465 0.64146 0.056 0.732 0.000 0.212 0.000
#> SRR1384456 1 0.0000 0.78651 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 4 0.2912 0.6272 0.000 0.216 0.000 0.784 0.000 0.000
#> SRR808862 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1500382 2 0.0146 0.7564 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1322683 2 0.3915 0.6582 0.000 0.692 0.004 0.016 0.288 0.000
#> SRR1329811 2 0.3667 0.5381 0.008 0.740 0.000 0.012 0.240 0.000
#> SRR1087297 2 0.0622 0.7595 0.000 0.980 0.000 0.012 0.008 0.000
#> SRR1072626 2 0.4620 0.4890 0.000 0.544 0.000 0.420 0.032 0.004
#> SRR1407428 1 0.0146 0.7897 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1321029 2 0.2805 0.7236 0.000 0.828 0.000 0.012 0.160 0.000
#> SRR1500282 5 0.4904 0.4905 0.140 0.028 0.000 0.124 0.708 0.000
#> SRR1100496 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1308778 2 0.0146 0.7560 0.000 0.996 0.000 0.000 0.004 0.000
#> SRR1445304 2 0.2595 0.7266 0.000 0.836 0.000 0.160 0.004 0.000
#> SRR1099378 5 0.5973 0.5144 0.000 0.308 0.000 0.216 0.472 0.004
#> SRR1347412 5 0.3571 0.1524 0.216 0.004 0.020 0.000 0.760 0.000
#> SRR1099694 2 0.4289 0.6153 0.000 0.660 0.000 0.304 0.032 0.004
#> SRR1088365 4 0.0603 0.7287 0.000 0.016 0.000 0.980 0.004 0.000
#> SRR1325752 2 0.3768 0.6648 0.004 0.772 0.000 0.184 0.036 0.004
#> SRR1416713 2 0.0146 0.7564 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1074474 1 0.0000 0.7904 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.0935 0.8799 0.000 0.000 0.964 0.000 0.032 0.004
#> SRR1400507 2 0.2793 0.7037 0.000 0.800 0.000 0.200 0.000 0.000
#> SRR1378179 2 0.1434 0.7581 0.000 0.940 0.000 0.048 0.012 0.000
#> SRR1377905 2 0.1075 0.7542 0.000 0.952 0.000 0.000 0.048 0.000
#> SRR1089479 5 0.6255 0.3495 0.332 0.008 0.000 0.196 0.456 0.008
#> SRR1073365 4 0.1349 0.7347 0.000 0.056 0.000 0.940 0.004 0.000
#> SRR1500306 5 0.6459 0.5913 0.092 0.064 0.000 0.368 0.468 0.008
#> SRR1101566 4 0.3521 0.5073 0.000 0.004 0.004 0.724 0.268 0.000
#> SRR1350503 3 0.0520 0.8922 0.000 0.000 0.984 0.000 0.008 0.008
#> SRR1446007 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1102875 4 0.1642 0.7203 0.000 0.028 0.000 0.936 0.032 0.004
#> SRR1380293 2 0.0520 0.7581 0.000 0.984 0.000 0.008 0.008 0.000
#> SRR1331198 2 0.0146 0.7564 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1092686 3 0.0363 0.8919 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1069421 2 0.3284 0.7339 0.052 0.844 0.000 0.080 0.024 0.000
#> SRR1341650 4 0.4035 0.5517 0.052 0.000 0.004 0.740 0.204 0.000
#> SRR1357276 2 0.1765 0.7483 0.000 0.904 0.000 0.096 0.000 0.000
#> SRR1498374 4 0.5609 0.2212 0.000 0.348 0.000 0.496 0.156 0.000
#> SRR1093721 4 0.4456 -0.0264 0.000 0.448 0.000 0.524 0.028 0.000
#> SRR1464660 2 0.3991 -0.1030 0.000 0.524 0.000 0.004 0.472 0.000
#> SRR1402051 5 0.6720 0.5331 0.048 0.220 0.000 0.304 0.428 0.000
#> SRR1488734 2 0.3652 0.6667 0.000 0.768 0.000 0.196 0.032 0.004
#> SRR1082616 3 0.4062 0.5807 0.000 0.004 0.640 0.012 0.344 0.000
#> SRR1099427 2 0.4391 0.6280 0.000 0.644 0.008 0.028 0.320 0.000
#> SRR1453093 4 0.2826 0.6227 0.000 0.128 0.000 0.844 0.028 0.000
#> SRR1357064 1 0.1387 0.7129 0.932 0.068 0.000 0.000 0.000 0.000
#> SRR811237 2 0.4460 0.3514 0.000 0.568 0.000 0.404 0.024 0.004
#> SRR1100848 2 0.3839 0.6542 0.000 0.748 0.000 0.212 0.036 0.004
#> SRR1346755 2 0.4595 0.6385 0.000 0.668 0.000 0.084 0.248 0.000
#> SRR1472529 2 0.2778 0.7237 0.000 0.824 0.000 0.168 0.008 0.000
#> SRR1398905 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1082733 4 0.1644 0.7323 0.000 0.076 0.000 0.920 0.004 0.000
#> SRR1308035 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1466445 3 0.0363 0.8919 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1359080 2 0.4253 0.5386 0.000 0.668 0.000 0.296 0.032 0.004
#> SRR1455825 4 0.1719 0.7204 0.000 0.032 0.000 0.932 0.032 0.004
#> SRR1389300 4 0.3076 0.6090 0.000 0.240 0.000 0.760 0.000 0.000
#> SRR812246 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1076632 4 0.0937 0.7331 0.000 0.040 0.000 0.960 0.000 0.000
#> SRR1415567 1 0.0000 0.7904 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 4 0.3130 0.6630 0.000 0.048 0.000 0.828 0.124 0.000
#> SRR1452099 2 0.4950 0.6151 0.040 0.688 0.000 0.220 0.048 0.004
#> SRR1352346 2 0.1452 0.7577 0.012 0.948 0.000 0.020 0.020 0.000
#> SRR1364034 2 0.3151 0.6822 0.000 0.748 0.000 0.252 0.000 0.000
#> SRR1086046 4 0.3042 0.6085 0.000 0.128 0.000 0.836 0.032 0.004
#> SRR1407226 1 0.5863 0.0649 0.472 0.012 0.000 0.140 0.376 0.000
#> SRR1319363 2 0.6917 0.0217 0.052 0.420 0.000 0.288 0.236 0.004
#> SRR1446961 3 0.3847 0.5826 0.000 0.008 0.644 0.000 0.348 0.000
#> SRR1486650 1 0.0000 0.7904 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 2 0.5355 -0.1598 0.092 0.456 0.000 0.004 0.448 0.000
#> SRR1454785 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1092329 2 0.3979 0.6777 0.000 0.712 0.004 0.028 0.256 0.000
#> SRR1091476 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1073775 4 0.1010 0.7063 0.000 0.004 0.000 0.960 0.036 0.000
#> SRR1366873 4 0.3624 0.6263 0.000 0.060 0.000 0.784 0.156 0.000
#> SRR1398114 4 0.3050 0.6111 0.000 0.236 0.000 0.764 0.000 0.000
#> SRR1089950 5 0.6767 0.5397 0.052 0.260 0.000 0.216 0.468 0.004
#> SRR1433272 2 0.0508 0.7590 0.004 0.984 0.000 0.012 0.000 0.000
#> SRR1075314 4 0.4988 -0.3143 0.004 0.048 0.000 0.520 0.424 0.004
#> SRR1085590 3 0.7040 0.1258 0.000 0.216 0.416 0.084 0.284 0.000
#> SRR1100752 6 0.0363 0.9945 0.000 0.000 0.012 0.000 0.000 0.988
#> SRR1391494 2 0.3997 0.6559 0.000 0.688 0.004 0.020 0.288 0.000
#> SRR1333263 2 0.4180 0.6110 0.000 0.628 0.024 0.000 0.348 0.000
#> SRR1310231 2 0.0632 0.7586 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1094144 4 0.1377 0.7237 0.004 0.024 0.000 0.952 0.016 0.004
#> SRR1092160 2 0.3798 0.6596 0.000 0.748 0.000 0.216 0.032 0.004
#> SRR1320300 4 0.1082 0.7335 0.000 0.040 0.000 0.956 0.004 0.000
#> SRR1322747 2 0.4386 0.6044 0.000 0.620 0.028 0.004 0.348 0.000
#> SRR1432719 3 0.0405 0.8911 0.000 0.000 0.988 0.000 0.008 0.004
#> SRR1100728 4 0.1590 0.7359 0.008 0.048 0.000 0.936 0.008 0.000
#> SRR1087511 4 0.1556 0.6960 0.000 0.000 0.000 0.920 0.080 0.000
#> SRR1470336 1 0.5480 0.1144 0.492 0.020 0.000 0.060 0.424 0.004
#> SRR1322536 5 0.4033 0.3616 0.000 0.004 0.000 0.404 0.588 0.004
#> SRR1100824 5 0.5155 0.4431 0.060 0.004 0.000 0.444 0.488 0.004
#> SRR1085951 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1322046 2 0.0260 0.7573 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1316420 1 0.5554 -0.0213 0.456 0.136 0.000 0.000 0.408 0.000
#> SRR1070913 2 0.2632 0.7283 0.000 0.832 0.000 0.164 0.004 0.000
#> SRR1345806 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1313872 2 0.2767 0.7434 0.048 0.880 0.000 0.044 0.028 0.000
#> SRR1337666 2 0.0146 0.7564 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1076823 1 0.3562 0.4648 0.784 0.000 0.000 0.176 0.036 0.004
#> SRR1093954 4 0.1313 0.7278 0.000 0.028 0.000 0.952 0.016 0.004
#> SRR1451921 2 0.5533 0.5391 0.052 0.584 0.000 0.316 0.044 0.004
#> SRR1491257 2 0.5471 0.3633 0.268 0.560 0.000 0.000 0.172 0.000
#> SRR1416979 2 0.3973 0.6407 0.000 0.728 0.000 0.232 0.036 0.004
#> SRR1419015 4 0.6113 0.0241 0.000 0.344 0.000 0.360 0.296 0.000
#> SRR817649 2 0.3660 0.6668 0.000 0.772 0.000 0.188 0.036 0.004
#> SRR1466376 2 0.2300 0.7321 0.000 0.856 0.000 0.144 0.000 0.000
#> SRR1392055 2 0.2442 0.7342 0.000 0.852 0.000 0.144 0.004 0.000
#> SRR1120913 2 0.0000 0.7556 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1120869 4 0.2065 0.7216 0.000 0.052 0.000 0.912 0.032 0.004
#> SRR1319419 3 0.0632 0.8821 0.000 0.000 0.976 0.000 0.024 0.000
#> SRR816495 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR818694 4 0.0000 0.7200 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1465653 2 0.3658 0.5953 0.028 0.772 0.000 0.008 0.192 0.000
#> SRR1475952 1 0.0146 0.7897 0.996 0.000 0.000 0.000 0.000 0.004
#> SRR1465040 6 0.0632 0.9845 0.000 0.000 0.024 0.000 0.000 0.976
#> SRR1088461 4 0.1411 0.7338 0.000 0.060 0.000 0.936 0.004 0.000
#> SRR810129 2 0.2257 0.7342 0.000 0.876 0.000 0.116 0.008 0.000
#> SRR1400141 3 0.0260 0.8936 0.000 0.000 0.992 0.000 0.000 0.008
#> SRR1349585 1 0.0260 0.7876 0.992 0.000 0.000 0.000 0.008 0.000
#> SRR1437576 2 0.3808 0.6603 0.000 0.700 0.004 0.012 0.284 0.000
#> SRR814407 5 0.1579 0.3395 0.020 0.004 0.008 0.024 0.944 0.000
#> SRR1332403 4 0.3789 0.3906 0.000 0.416 0.000 0.584 0.000 0.000
#> SRR1099598 4 0.0820 0.7298 0.000 0.016 0.000 0.972 0.012 0.000
#> SRR1327723 2 0.1866 0.7531 0.000 0.908 0.000 0.084 0.008 0.000
#> SRR1392525 2 0.4699 0.5911 0.000 0.600 0.020 0.024 0.356 0.000
#> SRR1320536 1 0.0000 0.7904 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.3945 0.6119 0.000 0.612 0.008 0.000 0.380 0.000
#> SRR1351390 5 0.5516 0.6160 0.052 0.048 0.000 0.296 0.600 0.004
#> SRR1309141 2 0.4193 0.6103 0.000 0.624 0.024 0.000 0.352 0.000
#> SRR1452803 2 0.0146 0.7564 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR811631 2 0.3852 0.6383 0.000 0.664 0.012 0.000 0.324 0.000
#> SRR1485563 4 0.4274 0.4277 0.004 0.272 0.000 0.688 0.032 0.004
#> SRR1311531 3 0.0363 0.8919 0.000 0.000 0.988 0.000 0.000 0.012
#> SRR1353076 4 0.2631 0.6575 0.000 0.180 0.000 0.820 0.000 0.000
#> SRR1480831 2 0.2946 0.7243 0.000 0.812 0.000 0.176 0.012 0.000
#> SRR1083892 2 0.0405 0.7587 0.004 0.988 0.000 0.008 0.000 0.000
#> SRR809873 4 0.2675 0.6710 0.052 0.020 0.000 0.888 0.036 0.004
#> SRR1341854 2 0.0692 0.7575 0.000 0.976 0.000 0.020 0.004 0.000
#> SRR1399335 4 0.2838 0.6561 0.000 0.188 0.000 0.808 0.004 0.000
#> SRR1464209 5 0.5089 0.4883 0.176 0.000 0.000 0.172 0.648 0.004
#> SRR1389886 2 0.2969 0.6785 0.000 0.776 0.000 0.224 0.000 0.000
#> SRR1400730 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1448008 4 0.3956 0.4942 0.000 0.252 0.000 0.716 0.028 0.004
#> SRR1087606 5 0.5452 0.5903 0.052 0.068 0.000 0.228 0.648 0.004
#> SRR1445111 1 0.4196 0.2728 0.568 0.004 0.000 0.004 0.420 0.004
#> SRR816865 4 0.1387 0.7338 0.000 0.068 0.000 0.932 0.000 0.000
#> SRR1323360 6 0.0260 0.9977 0.000 0.000 0.008 0.000 0.000 0.992
#> SRR1417364 3 0.1556 0.8494 0.000 0.000 0.920 0.000 0.080 0.000
#> SRR1480329 2 0.3068 0.7457 0.000 0.840 0.000 0.088 0.072 0.000
#> SRR1403322 4 0.2745 0.6670 0.052 0.020 0.000 0.884 0.040 0.004
#> SRR1093625 1 0.0146 0.7889 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1479977 2 0.3250 0.7203 0.000 0.788 0.000 0.196 0.012 0.004
#> SRR1082035 4 0.5495 0.4284 0.052 0.060 0.000 0.604 0.284 0.000
#> SRR1393046 2 0.3626 0.6601 0.000 0.704 0.004 0.004 0.288 0.000
#> SRR1466663 2 0.4439 0.6791 0.040 0.740 0.000 0.184 0.032 0.004
#> SRR1384456 1 0.0000 0.7904 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["CV", "mclust"]
# you can also extract it by
# res = res_list["CV:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 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 0.634 0.896 0.946 0.4941 0.497 0.497
#> 3 3 0.691 0.800 0.885 0.2794 0.819 0.653
#> 4 4 0.635 0.697 0.816 0.1035 0.937 0.831
#> 5 5 0.627 0.695 0.818 -0.0483 0.813 0.577
#> 6 6 0.537 0.598 0.724 0.0860 0.928 0.822
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
#> SRR810713 2 0.000 0.9601 0.000 1.000
#> SRR808862 1 0.000 0.9224 1.000 0.000
#> SRR1500382 2 0.000 0.9601 0.000 1.000
#> SRR1322683 2 0.961 0.4336 0.384 0.616
#> SRR1329811 1 0.430 0.9110 0.912 0.088
#> SRR1087297 2 0.000 0.9601 0.000 1.000
#> SRR1072626 2 0.000 0.9601 0.000 1.000
#> SRR1407428 1 0.494 0.9060 0.892 0.108
#> SRR1321029 2 0.000 0.9601 0.000 1.000
#> SRR1500282 1 0.118 0.9215 0.984 0.016
#> SRR1100496 1 0.000 0.9224 1.000 0.000
#> SRR1308778 2 0.000 0.9601 0.000 1.000
#> SRR1445304 2 0.000 0.9601 0.000 1.000
#> SRR1099378 1 0.827 0.7266 0.740 0.260
#> SRR1347412 1 0.000 0.9224 1.000 0.000
#> SRR1099694 2 0.000 0.9601 0.000 1.000
#> SRR1088365 2 0.000 0.9601 0.000 1.000
#> SRR1325752 2 0.163 0.9370 0.024 0.976
#> SRR1416713 2 0.000 0.9601 0.000 1.000
#> SRR1074474 1 0.494 0.9060 0.892 0.108
#> SRR1469369 1 0.000 0.9224 1.000 0.000
#> SRR1400507 2 0.000 0.9601 0.000 1.000
#> SRR1378179 2 0.000 0.9601 0.000 1.000
#> SRR1377905 2 0.955 0.4531 0.376 0.624
#> SRR1089479 1 0.402 0.9127 0.920 0.080
#> SRR1073365 2 0.000 0.9601 0.000 1.000
#> SRR1500306 1 0.552 0.8920 0.872 0.128
#> SRR1101566 2 0.952 0.4625 0.372 0.628
#> SRR1350503 1 0.000 0.9224 1.000 0.000
#> SRR1446007 1 0.000 0.9224 1.000 0.000
#> SRR1102875 2 0.000 0.9601 0.000 1.000
#> SRR1380293 2 0.000 0.9601 0.000 1.000
#> SRR1331198 2 0.000 0.9601 0.000 1.000
#> SRR1092686 1 0.000 0.9224 1.000 0.000
#> SRR1069421 2 0.000 0.9601 0.000 1.000
#> SRR1341650 2 0.952 0.4625 0.372 0.628
#> SRR1357276 2 0.000 0.9601 0.000 1.000
#> SRR1498374 2 0.000 0.9601 0.000 1.000
#> SRR1093721 2 0.000 0.9601 0.000 1.000
#> SRR1464660 1 0.118 0.9215 0.984 0.016
#> SRR1402051 2 0.141 0.9418 0.020 0.980
#> SRR1488734 2 0.000 0.9601 0.000 1.000
#> SRR1082616 1 0.000 0.9224 1.000 0.000
#> SRR1099427 1 0.971 0.2751 0.600 0.400
#> SRR1453093 2 0.000 0.9601 0.000 1.000
#> SRR1357064 1 0.494 0.9060 0.892 0.108
#> SRR811237 2 0.000 0.9601 0.000 1.000
#> SRR1100848 2 0.000 0.9601 0.000 1.000
#> SRR1346755 2 0.952 0.4625 0.372 0.628
#> SRR1472529 2 0.000 0.9601 0.000 1.000
#> SRR1398905 1 0.000 0.9224 1.000 0.000
#> SRR1082733 2 0.000 0.9601 0.000 1.000
#> SRR1308035 1 0.000 0.9224 1.000 0.000
#> SRR1466445 1 0.000 0.9224 1.000 0.000
#> SRR1359080 2 0.000 0.9601 0.000 1.000
#> SRR1455825 2 0.000 0.9601 0.000 1.000
#> SRR1389300 2 0.000 0.9601 0.000 1.000
#> SRR812246 1 0.000 0.9224 1.000 0.000
#> SRR1076632 2 0.000 0.9601 0.000 1.000
#> SRR1415567 1 0.494 0.9060 0.892 0.108
#> SRR1331900 2 0.000 0.9601 0.000 1.000
#> SRR1452099 1 0.671 0.8429 0.824 0.176
#> SRR1352346 1 0.985 0.3742 0.572 0.428
#> SRR1364034 2 0.000 0.9601 0.000 1.000
#> SRR1086046 1 0.574 0.8849 0.864 0.136
#> SRR1407226 1 0.494 0.9060 0.892 0.108
#> SRR1319363 1 0.634 0.8636 0.840 0.160
#> SRR1446961 1 0.000 0.9224 1.000 0.000
#> SRR1486650 1 0.494 0.9060 0.892 0.108
#> SRR1470152 1 0.118 0.9215 0.984 0.016
#> SRR1454785 1 0.000 0.9224 1.000 0.000
#> SRR1092329 2 0.949 0.4712 0.368 0.632
#> SRR1091476 1 0.000 0.9224 1.000 0.000
#> SRR1073775 2 0.000 0.9601 0.000 1.000
#> SRR1366873 2 0.000 0.9601 0.000 1.000
#> SRR1398114 2 0.000 0.9601 0.000 1.000
#> SRR1089950 1 0.753 0.7915 0.784 0.216
#> SRR1433272 2 0.000 0.9601 0.000 1.000
#> SRR1075314 1 0.541 0.8952 0.876 0.124
#> SRR1085590 1 0.000 0.9224 1.000 0.000
#> SRR1100752 1 0.000 0.9224 1.000 0.000
#> SRR1391494 2 0.952 0.4625 0.372 0.628
#> SRR1333263 1 0.000 0.9224 1.000 0.000
#> SRR1310231 2 0.000 0.9601 0.000 1.000
#> SRR1094144 2 0.000 0.9601 0.000 1.000
#> SRR1092160 2 0.000 0.9601 0.000 1.000
#> SRR1320300 2 0.000 0.9601 0.000 1.000
#> SRR1322747 1 0.000 0.9224 1.000 0.000
#> SRR1432719 1 0.000 0.9224 1.000 0.000
#> SRR1100728 2 0.000 0.9601 0.000 1.000
#> SRR1087511 2 0.224 0.9257 0.036 0.964
#> SRR1470336 1 0.541 0.8952 0.876 0.124
#> SRR1322536 1 0.494 0.9060 0.892 0.108
#> SRR1100824 1 0.118 0.9215 0.984 0.016
#> SRR1085951 1 0.000 0.9224 1.000 0.000
#> SRR1322046 2 0.000 0.9601 0.000 1.000
#> SRR1316420 1 0.494 0.9060 0.892 0.108
#> SRR1070913 2 0.000 0.9601 0.000 1.000
#> SRR1345806 1 0.000 0.9224 1.000 0.000
#> SRR1313872 2 0.000 0.9601 0.000 1.000
#> SRR1337666 2 0.000 0.9601 0.000 1.000
#> SRR1076823 1 0.494 0.9060 0.892 0.108
#> SRR1093954 2 0.000 0.9601 0.000 1.000
#> SRR1451921 1 0.662 0.8500 0.828 0.172
#> SRR1491257 1 0.224 0.9198 0.964 0.036
#> SRR1416979 2 0.000 0.9601 0.000 1.000
#> SRR1419015 1 0.118 0.9215 0.984 0.016
#> SRR817649 2 0.000 0.9601 0.000 1.000
#> SRR1466376 2 0.000 0.9601 0.000 1.000
#> SRR1392055 2 0.000 0.9601 0.000 1.000
#> SRR1120913 2 0.000 0.9601 0.000 1.000
#> SRR1120869 2 0.000 0.9601 0.000 1.000
#> SRR1319419 1 0.000 0.9224 1.000 0.000
#> SRR816495 1 0.000 0.9224 1.000 0.000
#> SRR818694 2 0.000 0.9601 0.000 1.000
#> SRR1465653 1 0.541 0.8955 0.876 0.124
#> SRR1475952 1 0.494 0.9060 0.892 0.108
#> SRR1465040 1 0.000 0.9224 1.000 0.000
#> SRR1088461 2 0.000 0.9601 0.000 1.000
#> SRR810129 2 0.000 0.9601 0.000 1.000
#> SRR1400141 1 0.000 0.9224 1.000 0.000
#> SRR1349585 1 0.494 0.9060 0.892 0.108
#> SRR1437576 1 0.997 0.0521 0.532 0.468
#> SRR814407 1 0.000 0.9224 1.000 0.000
#> SRR1332403 2 0.000 0.9601 0.000 1.000
#> SRR1099598 2 0.000 0.9601 0.000 1.000
#> SRR1327723 2 0.000 0.9601 0.000 1.000
#> SRR1392525 1 0.000 0.9224 1.000 0.000
#> SRR1320536 1 0.494 0.9060 0.892 0.108
#> SRR1083824 1 0.000 0.9224 1.000 0.000
#> SRR1351390 1 0.494 0.9060 0.892 0.108
#> SRR1309141 1 0.000 0.9224 1.000 0.000
#> SRR1452803 2 0.000 0.9601 0.000 1.000
#> SRR811631 1 0.000 0.9224 1.000 0.000
#> SRR1485563 2 0.000 0.9601 0.000 1.000
#> SRR1311531 1 0.000 0.9224 1.000 0.000
#> SRR1353076 2 0.000 0.9601 0.000 1.000
#> SRR1480831 2 0.000 0.9601 0.000 1.000
#> SRR1083892 1 0.541 0.8952 0.876 0.124
#> SRR809873 1 0.552 0.8926 0.872 0.128
#> SRR1341854 2 0.000 0.9601 0.000 1.000
#> SRR1399335 2 0.000 0.9601 0.000 1.000
#> SRR1464209 1 0.494 0.9060 0.892 0.108
#> SRR1389886 2 0.000 0.9601 0.000 1.000
#> SRR1400730 1 0.000 0.9224 1.000 0.000
#> SRR1448008 2 0.000 0.9601 0.000 1.000
#> SRR1087606 1 0.529 0.8983 0.880 0.120
#> SRR1445111 1 0.494 0.9060 0.892 0.108
#> SRR816865 2 0.000 0.9601 0.000 1.000
#> SRR1323360 1 0.000 0.9224 1.000 0.000
#> SRR1417364 1 0.000 0.9224 1.000 0.000
#> SRR1480329 2 0.000 0.9601 0.000 1.000
#> SRR1403322 1 0.541 0.8952 0.876 0.124
#> SRR1093625 1 0.494 0.9060 0.892 0.108
#> SRR1479977 2 0.000 0.9601 0.000 1.000
#> SRR1082035 2 0.000 0.9601 0.000 1.000
#> SRR1393046 2 0.961 0.4336 0.384 0.616
#> SRR1466663 2 0.000 0.9601 0.000 1.000
#> SRR1384456 1 0.494 0.9060 0.892 0.108
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR808862 3 0.4555 0.77184 0.200 0.000 0.800
#> SRR1500382 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1322683 3 0.7653 0.43486 0.080 0.276 0.644
#> SRR1329811 1 0.1182 0.91308 0.976 0.012 0.012
#> SRR1087297 2 0.0592 0.91544 0.000 0.988 0.012
#> SRR1072626 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1407428 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1321029 2 0.7412 0.68817 0.124 0.700 0.176
#> SRR1500282 1 0.3941 0.72097 0.844 0.000 0.156
#> SRR1100496 3 0.3941 0.80350 0.156 0.000 0.844
#> SRR1308778 2 0.1753 0.89742 0.000 0.952 0.048
#> SRR1445304 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1099378 1 0.3116 0.84923 0.892 0.108 0.000
#> SRR1347412 3 0.6274 0.39068 0.456 0.000 0.544
#> SRR1099694 2 0.1964 0.90293 0.000 0.944 0.056
#> SRR1088365 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1325752 2 0.4779 0.83209 0.036 0.840 0.124
#> SRR1416713 2 0.0592 0.91544 0.000 0.988 0.012
#> SRR1074474 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1469369 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1400507 2 0.0237 0.91624 0.000 0.996 0.004
#> SRR1378179 2 0.0592 0.91620 0.000 0.988 0.012
#> SRR1377905 3 0.9399 0.07892 0.176 0.372 0.452
#> SRR1089479 1 0.0592 0.91731 0.988 0.012 0.000
#> SRR1073365 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1500306 1 0.1163 0.91696 0.972 0.028 0.000
#> SRR1101566 2 0.9794 0.00833 0.380 0.384 0.236
#> SRR1350503 3 0.3116 0.81459 0.108 0.000 0.892
#> SRR1446007 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1102875 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1380293 2 0.2261 0.89915 0.000 0.932 0.068
#> SRR1331198 2 0.2356 0.89741 0.000 0.928 0.072
#> SRR1092686 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1069421 2 0.4920 0.83120 0.108 0.840 0.052
#> SRR1341650 2 0.9906 0.04327 0.272 0.388 0.340
#> SRR1357276 2 0.2261 0.89915 0.000 0.932 0.068
#> SRR1498374 2 0.5268 0.76638 0.012 0.776 0.212
#> SRR1093721 2 0.0747 0.91656 0.000 0.984 0.016
#> SRR1464660 1 0.1182 0.91308 0.976 0.012 0.012
#> SRR1402051 2 0.8363 0.21678 0.412 0.504 0.084
#> SRR1488734 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1082616 3 0.4002 0.80409 0.160 0.000 0.840
#> SRR1099427 3 0.5597 0.57529 0.020 0.216 0.764
#> SRR1453093 2 0.6087 0.76315 0.144 0.780 0.076
#> SRR1357064 1 0.1337 0.91533 0.972 0.016 0.012
#> SRR811237 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1100848 2 0.1860 0.90398 0.000 0.948 0.052
#> SRR1346755 3 0.9465 0.06934 0.184 0.372 0.444
#> SRR1472529 2 0.2537 0.89448 0.000 0.920 0.080
#> SRR1398905 3 0.5058 0.72993 0.244 0.000 0.756
#> SRR1082733 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1308035 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1466445 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1359080 2 0.2356 0.89741 0.000 0.928 0.072
#> SRR1455825 2 0.0892 0.91421 0.000 0.980 0.020
#> SRR1389300 2 0.0237 0.91624 0.000 0.996 0.004
#> SRR812246 3 0.3482 0.81657 0.128 0.000 0.872
#> SRR1076632 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1415567 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1331900 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1452099 1 0.2878 0.86239 0.904 0.096 0.000
#> SRR1352346 2 0.8957 0.22284 0.376 0.492 0.132
#> SRR1364034 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1086046 1 0.6254 0.75278 0.776 0.108 0.116
#> SRR1407226 1 0.1950 0.90917 0.952 0.040 0.008
#> SRR1319363 1 0.7872 0.55344 0.652 0.236 0.112
#> SRR1446961 3 0.3038 0.81138 0.104 0.000 0.896
#> SRR1486650 1 0.0592 0.91731 0.988 0.012 0.000
#> SRR1470152 1 0.1182 0.91308 0.976 0.012 0.012
#> SRR1454785 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1092329 3 0.9663 0.03235 0.212 0.372 0.416
#> SRR1091476 3 0.4399 0.77385 0.188 0.000 0.812
#> SRR1073775 2 0.3030 0.88160 0.004 0.904 0.092
#> SRR1366873 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1398114 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1089950 1 0.1964 0.89921 0.944 0.056 0.000
#> SRR1433272 2 0.3899 0.87580 0.056 0.888 0.056
#> SRR1075314 1 0.3134 0.89012 0.916 0.032 0.052
#> SRR1085590 3 0.3038 0.81109 0.104 0.000 0.896
#> SRR1100752 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1391494 3 0.9734 0.00402 0.224 0.376 0.400
#> SRR1333263 3 0.2682 0.79750 0.076 0.004 0.920
#> SRR1310231 2 0.0237 0.91626 0.000 0.996 0.004
#> SRR1094144 2 0.1529 0.90748 0.000 0.960 0.040
#> SRR1092160 2 0.4379 0.86187 0.060 0.868 0.072
#> SRR1320300 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1322747 3 0.1491 0.75748 0.016 0.016 0.968
#> SRR1432719 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1100728 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1087511 2 0.8700 0.33211 0.344 0.536 0.120
#> SRR1470336 1 0.1163 0.91696 0.972 0.028 0.000
#> SRR1322536 1 0.1999 0.89987 0.952 0.012 0.036
#> SRR1100824 1 0.4062 0.70687 0.836 0.000 0.164
#> SRR1085951 3 0.5058 0.72993 0.244 0.000 0.756
#> SRR1322046 2 0.1289 0.91165 0.000 0.968 0.032
#> SRR1316420 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1070913 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1345806 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1313872 2 0.3134 0.89335 0.032 0.916 0.052
#> SRR1337666 2 0.3234 0.88960 0.020 0.908 0.072
#> SRR1076823 1 0.2982 0.89020 0.920 0.024 0.056
#> SRR1093954 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1451921 1 0.6255 0.75318 0.776 0.112 0.112
#> SRR1491257 1 0.1182 0.91308 0.976 0.012 0.012
#> SRR1416979 2 0.0592 0.91544 0.000 0.988 0.012
#> SRR1419015 1 0.7329 0.23360 0.544 0.032 0.424
#> SRR817649 2 0.2261 0.89915 0.000 0.932 0.068
#> SRR1466376 2 0.0592 0.91544 0.000 0.988 0.012
#> SRR1392055 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1120913 2 0.0424 0.91591 0.000 0.992 0.008
#> SRR1120869 2 0.1643 0.91024 0.000 0.956 0.044
#> SRR1319419 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR816495 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR818694 2 0.7091 0.70026 0.152 0.724 0.124
#> SRR1465653 1 0.1877 0.91392 0.956 0.032 0.012
#> SRR1475952 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1465040 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1088461 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR810129 2 0.0592 0.91620 0.000 0.988 0.012
#> SRR1400141 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1349585 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1437576 3 0.5681 0.55292 0.016 0.236 0.748
#> SRR814407 3 0.6302 0.32848 0.480 0.000 0.520
#> SRR1332403 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1099598 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1327723 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1392525 3 0.2590 0.79503 0.072 0.004 0.924
#> SRR1320536 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1083824 3 0.1399 0.77064 0.028 0.004 0.968
#> SRR1351390 1 0.0829 0.91649 0.984 0.012 0.004
#> SRR1309141 3 0.1182 0.76065 0.012 0.012 0.976
#> SRR1452803 2 0.0424 0.91596 0.000 0.992 0.008
#> SRR811631 3 0.1337 0.75912 0.016 0.012 0.972
#> SRR1485563 2 0.1643 0.91131 0.000 0.956 0.044
#> SRR1311531 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1353076 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1480831 2 0.0424 0.91582 0.000 0.992 0.008
#> SRR1083892 1 0.1999 0.91215 0.952 0.036 0.012
#> SRR809873 1 0.5804 0.78238 0.800 0.088 0.112
#> SRR1341854 2 0.0592 0.91620 0.000 0.988 0.012
#> SRR1399335 2 0.1860 0.90620 0.000 0.948 0.052
#> SRR1464209 1 0.1337 0.91533 0.972 0.016 0.012
#> SRR1389886 2 0.0000 0.91639 0.000 1.000 0.000
#> SRR1400730 3 0.5058 0.72993 0.244 0.000 0.756
#> SRR1448008 2 0.8909 0.24033 0.376 0.496 0.128
#> SRR1087606 1 0.1525 0.91548 0.964 0.032 0.004
#> SRR1445111 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR816865 2 0.1877 0.90323 0.032 0.956 0.012
#> SRR1323360 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1417364 3 0.3412 0.81839 0.124 0.000 0.876
#> SRR1480329 2 0.1529 0.90731 0.000 0.960 0.040
#> SRR1403322 1 0.4526 0.84002 0.856 0.040 0.104
#> SRR1093625 1 0.0747 0.91963 0.984 0.016 0.000
#> SRR1479977 2 0.3686 0.85092 0.000 0.860 0.140
#> SRR1082035 2 0.2550 0.90107 0.024 0.936 0.040
#> SRR1393046 3 0.7348 0.29177 0.044 0.348 0.608
#> SRR1466663 2 0.5835 0.76561 0.164 0.784 0.052
#> SRR1384456 1 0.0747 0.91963 0.984 0.016 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.1940 0.7650 0.000 0.924 0.000 0.076
#> SRR808862 3 0.2469 0.8138 0.000 0.000 0.892 0.108
#> SRR1500382 2 0.2216 0.7670 0.000 0.908 0.000 0.092
#> SRR1322683 4 0.7547 0.7277 0.008 0.184 0.284 0.524
#> SRR1329811 1 0.3311 0.8216 0.828 0.000 0.000 0.172
#> SRR1087297 2 0.4564 0.5788 0.000 0.672 0.000 0.328
#> SRR1072626 2 0.0592 0.7664 0.000 0.984 0.000 0.016
#> SRR1407428 1 0.1474 0.8523 0.948 0.000 0.000 0.052
#> SRR1321029 4 0.7135 0.4087 0.036 0.364 0.060 0.540
#> SRR1500282 1 0.4898 0.7702 0.780 0.000 0.104 0.116
#> SRR1100496 3 0.0707 0.8502 0.000 0.000 0.980 0.020
#> SRR1308778 2 0.2921 0.7425 0.000 0.860 0.000 0.140
#> SRR1445304 2 0.0469 0.7677 0.000 0.988 0.000 0.012
#> SRR1099378 1 0.3181 0.8431 0.888 0.044 0.004 0.064
#> SRR1347412 3 0.6217 0.4988 0.292 0.000 0.624 0.084
#> SRR1099694 2 0.4991 0.4802 0.004 0.608 0.000 0.388
#> SRR1088365 2 0.0336 0.7693 0.000 0.992 0.000 0.008
#> SRR1325752 2 0.4735 0.6810 0.068 0.784 0.000 0.148
#> SRR1416713 2 0.4164 0.6430 0.000 0.736 0.000 0.264
#> SRR1074474 1 0.1557 0.8493 0.944 0.000 0.000 0.056
#> SRR1469369 3 0.0895 0.8499 0.020 0.000 0.976 0.004
#> SRR1400507 2 0.0336 0.7728 0.000 0.992 0.000 0.008
#> SRR1378179 2 0.1389 0.7700 0.000 0.952 0.000 0.048
#> SRR1377905 4 0.7796 0.8071 0.016 0.236 0.224 0.524
#> SRR1089479 1 0.1637 0.8538 0.940 0.000 0.000 0.060
#> SRR1073365 2 0.0707 0.7647 0.000 0.980 0.000 0.020
#> SRR1500306 1 0.1118 0.8554 0.964 0.000 0.000 0.036
#> SRR1101566 4 0.9223 0.6508 0.220 0.240 0.108 0.432
#> SRR1350503 3 0.2256 0.8296 0.020 0.000 0.924 0.056
#> SRR1446007 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.0592 0.7664 0.000 0.984 0.000 0.016
#> SRR1380293 2 0.5786 0.5538 0.052 0.640 0.000 0.308
#> SRR1331198 2 0.6079 0.3514 0.048 0.544 0.000 0.408
#> SRR1092686 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.6052 0.3549 0.048 0.556 0.000 0.396
#> SRR1341650 4 0.8931 0.7366 0.136 0.244 0.136 0.484
#> SRR1357276 2 0.4776 0.4998 0.000 0.624 0.000 0.376
#> SRR1498374 2 0.6676 -0.0144 0.028 0.516 0.036 0.420
#> SRR1093721 2 0.1557 0.7669 0.000 0.944 0.000 0.056
#> SRR1464660 1 0.3311 0.8216 0.828 0.000 0.000 0.172
#> SRR1402051 1 0.7450 -0.0796 0.504 0.280 0.000 0.216
#> SRR1488734 2 0.1557 0.7691 0.000 0.944 0.000 0.056
#> SRR1082616 3 0.1174 0.8497 0.020 0.000 0.968 0.012
#> SRR1099427 3 0.7685 -0.4917 0.004 0.184 0.412 0.400
#> SRR1453093 2 0.5432 0.5189 0.124 0.740 0.000 0.136
#> SRR1357064 1 0.2647 0.8407 0.880 0.000 0.000 0.120
#> SRR811237 2 0.0000 0.7704 0.000 1.000 0.000 0.000
#> SRR1100848 2 0.5403 0.5247 0.024 0.628 0.000 0.348
#> SRR1346755 4 0.7796 0.8067 0.016 0.236 0.224 0.524
#> SRR1472529 2 0.4837 0.4691 0.004 0.648 0.000 0.348
#> SRR1398905 3 0.2469 0.8138 0.000 0.000 0.892 0.108
#> SRR1082733 2 0.0707 0.7647 0.000 0.980 0.000 0.020
#> SRR1308035 3 0.0336 0.8540 0.000 0.000 0.992 0.008
#> SRR1466445 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1359080 2 0.5161 0.4388 0.000 0.592 0.008 0.400
#> SRR1455825 2 0.3569 0.6759 0.000 0.804 0.000 0.196
#> SRR1389300 2 0.0188 0.7698 0.000 0.996 0.000 0.004
#> SRR812246 3 0.0469 0.8526 0.000 0.000 0.988 0.012
#> SRR1076632 2 0.1637 0.7694 0.000 0.940 0.000 0.060
#> SRR1415567 1 0.1474 0.8505 0.948 0.000 0.000 0.052
#> SRR1331900 2 0.0707 0.7647 0.000 0.980 0.000 0.020
#> SRR1452099 1 0.5220 0.7795 0.796 0.052 0.060 0.092
#> SRR1352346 1 0.8248 -0.2346 0.432 0.364 0.032 0.172
#> SRR1364034 2 0.1557 0.7714 0.000 0.944 0.000 0.056
#> SRR1086046 1 0.4261 0.7478 0.820 0.068 0.000 0.112
#> SRR1407226 1 0.2411 0.8370 0.920 0.040 0.000 0.040
#> SRR1319363 1 0.4549 0.7296 0.804 0.096 0.000 0.100
#> SRR1446961 3 0.3554 0.7807 0.020 0.000 0.844 0.136
#> SRR1486650 1 0.1792 0.8483 0.932 0.000 0.000 0.068
#> SRR1470152 1 0.3311 0.8216 0.828 0.000 0.000 0.172
#> SRR1454785 3 0.0188 0.8545 0.000 0.000 0.996 0.004
#> SRR1092329 4 0.7995 0.8084 0.028 0.236 0.212 0.524
#> SRR1091476 3 0.2469 0.8138 0.000 0.000 0.892 0.108
#> SRR1073775 2 0.4868 0.5628 0.024 0.720 0.000 0.256
#> SRR1366873 2 0.0000 0.7704 0.000 1.000 0.000 0.000
#> SRR1398114 2 0.1557 0.7741 0.000 0.944 0.000 0.056
#> SRR1089950 1 0.3009 0.8328 0.892 0.056 0.000 0.052
#> SRR1433272 2 0.5962 0.5656 0.080 0.660 0.000 0.260
#> SRR1075314 1 0.2908 0.8271 0.896 0.040 0.000 0.064
#> SRR1085590 3 0.4847 0.7106 0.020 0.016 0.764 0.200
#> SRR1100752 3 0.1867 0.8309 0.000 0.000 0.928 0.072
#> SRR1391494 4 0.8042 0.8024 0.032 0.244 0.200 0.524
#> SRR1333263 3 0.4847 0.6946 0.020 0.016 0.764 0.200
#> SRR1310231 2 0.0592 0.7732 0.000 0.984 0.000 0.016
#> SRR1094144 2 0.2081 0.7581 0.000 0.916 0.000 0.084
#> SRR1092160 2 0.6635 0.2990 0.088 0.524 0.000 0.388
#> SRR1320300 2 0.0188 0.7700 0.000 0.996 0.000 0.004
#> SRR1322747 3 0.5839 0.5595 0.024 0.024 0.664 0.288
#> SRR1432719 3 0.0707 0.8494 0.020 0.000 0.980 0.000
#> SRR1100728 2 0.1940 0.7720 0.000 0.924 0.000 0.076
#> SRR1087511 2 0.7746 -0.2815 0.376 0.392 0.000 0.232
#> SRR1470336 1 0.1489 0.8551 0.952 0.004 0.000 0.044
#> SRR1322536 1 0.3056 0.8309 0.888 0.040 0.000 0.072
#> SRR1100824 1 0.5175 0.7463 0.760 0.000 0.120 0.120
#> SRR1085951 3 0.2469 0.8138 0.000 0.000 0.892 0.108
#> SRR1322046 2 0.4978 0.4820 0.004 0.612 0.000 0.384
#> SRR1316420 1 0.1118 0.8551 0.964 0.000 0.000 0.036
#> SRR1070913 2 0.0707 0.7647 0.000 0.980 0.000 0.020
#> SRR1345806 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1313872 2 0.4936 0.6303 0.020 0.700 0.000 0.280
#> SRR1337666 2 0.6458 0.2882 0.072 0.520 0.000 0.408
#> SRR1076823 1 0.2830 0.8281 0.900 0.040 0.000 0.060
#> SRR1093954 2 0.0592 0.7664 0.000 0.984 0.000 0.016
#> SRR1451921 1 0.3850 0.7805 0.840 0.044 0.000 0.116
#> SRR1491257 1 0.3172 0.8267 0.840 0.000 0.000 0.160
#> SRR1416979 2 0.3219 0.7153 0.000 0.836 0.000 0.164
#> SRR1419015 1 0.8564 0.1501 0.452 0.068 0.336 0.144
#> SRR817649 2 0.6491 0.3104 0.076 0.528 0.000 0.396
#> SRR1466376 2 0.4431 0.5898 0.000 0.696 0.000 0.304
#> SRR1392055 2 0.0188 0.7698 0.000 0.996 0.000 0.004
#> SRR1120913 2 0.2589 0.7621 0.000 0.884 0.000 0.116
#> SRR1120869 2 0.2149 0.7660 0.000 0.912 0.000 0.088
#> SRR1319419 3 0.0927 0.8507 0.008 0.000 0.976 0.016
#> SRR816495 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR818694 2 0.6922 0.2041 0.168 0.584 0.000 0.248
#> SRR1465653 1 0.3219 0.8261 0.836 0.000 0.000 0.164
#> SRR1475952 1 0.1824 0.8523 0.936 0.004 0.000 0.060
#> SRR1465040 3 0.0188 0.8545 0.000 0.000 0.996 0.004
#> SRR1088461 2 0.0817 0.7692 0.000 0.976 0.000 0.024
#> SRR810129 2 0.1716 0.7692 0.000 0.936 0.000 0.064
#> SRR1400141 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1349585 1 0.0921 0.8554 0.972 0.000 0.000 0.028
#> SRR1437576 4 0.8397 0.6048 0.032 0.204 0.336 0.428
#> SRR814407 3 0.6300 0.4679 0.308 0.000 0.608 0.084
#> SRR1332403 2 0.1302 0.7699 0.000 0.956 0.000 0.044
#> SRR1099598 2 0.0921 0.7689 0.000 0.972 0.000 0.028
#> SRR1327723 2 0.1940 0.7650 0.000 0.924 0.000 0.076
#> SRR1392525 3 0.5693 0.6218 0.028 0.024 0.696 0.252
#> SRR1320536 1 0.1557 0.8493 0.944 0.000 0.000 0.056
#> SRR1083824 3 0.5434 0.6138 0.020 0.016 0.692 0.272
#> SRR1351390 1 0.3726 0.8193 0.860 0.008 0.092 0.040
#> SRR1309141 3 0.5691 0.5812 0.020 0.024 0.676 0.280
#> SRR1452803 2 0.3726 0.6959 0.000 0.788 0.000 0.212
#> SRR811631 3 0.5716 0.5745 0.020 0.024 0.672 0.284
#> SRR1485563 2 0.2198 0.7670 0.008 0.920 0.000 0.072
#> SRR1311531 3 0.0000 0.8547 0.000 0.000 1.000 0.000
#> SRR1353076 2 0.0000 0.7704 0.000 1.000 0.000 0.000
#> SRR1480831 2 0.0469 0.7677 0.000 0.988 0.000 0.012
#> SRR1083892 1 0.2593 0.8478 0.892 0.004 0.000 0.104
#> SRR809873 1 0.3587 0.7937 0.856 0.040 0.000 0.104
#> SRR1341854 2 0.3528 0.7227 0.000 0.808 0.000 0.192
#> SRR1399335 2 0.4454 0.6065 0.000 0.692 0.000 0.308
#> SRR1464209 1 0.3024 0.8303 0.852 0.000 0.000 0.148
#> SRR1389886 2 0.0707 0.7681 0.000 0.980 0.000 0.020
#> SRR1400730 3 0.2469 0.8138 0.000 0.000 0.892 0.108
#> SRR1448008 4 0.8673 0.4090 0.252 0.352 0.036 0.360
#> SRR1087606 1 0.2760 0.8397 0.872 0.000 0.000 0.128
#> SRR1445111 1 0.1474 0.8543 0.948 0.000 0.000 0.052
#> SRR816865 2 0.3056 0.7540 0.040 0.888 0.000 0.072
#> SRR1323360 3 0.0188 0.8545 0.000 0.000 0.996 0.004
#> SRR1417364 3 0.2563 0.8218 0.020 0.000 0.908 0.072
#> SRR1480329 2 0.1474 0.7667 0.000 0.948 0.000 0.052
#> SRR1403322 1 0.2908 0.8271 0.896 0.040 0.000 0.064
#> SRR1093625 1 0.1557 0.8493 0.944 0.000 0.000 0.056
#> SRR1479977 2 0.4730 0.4425 0.000 0.636 0.000 0.364
#> SRR1082035 2 0.2797 0.7595 0.032 0.900 0.000 0.068
#> SRR1393046 4 0.7514 0.7912 0.004 0.224 0.248 0.524
#> SRR1466663 2 0.7080 0.3042 0.196 0.568 0.000 0.236
#> SRR1384456 1 0.1389 0.8513 0.952 0.000 0.000 0.048
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1956 0.8656 0.000 0.916 0.000 0.076 0.008
#> SRR808862 4 0.3999 1.0000 0.000 0.000 0.344 0.656 0.000
#> SRR1500382 2 0.1768 0.8696 0.000 0.924 0.000 0.072 0.004
#> SRR1322683 3 0.7083 0.1208 0.000 0.360 0.392 0.232 0.016
#> SRR1329811 5 0.1043 0.6721 0.040 0.000 0.000 0.000 0.960
#> SRR1087297 2 0.2208 0.8592 0.000 0.908 0.000 0.072 0.020
#> SRR1072626 2 0.2069 0.8585 0.000 0.912 0.000 0.076 0.012
#> SRR1407428 1 0.1121 0.6537 0.956 0.000 0.000 0.000 0.044
#> SRR1321029 2 0.3887 0.8168 0.020 0.816 0.012 0.140 0.012
#> SRR1500282 1 0.5638 0.3476 0.552 0.000 0.072 0.004 0.372
#> SRR1100496 3 0.0404 0.7325 0.000 0.000 0.988 0.012 0.000
#> SRR1308778 2 0.1704 0.8672 0.000 0.928 0.000 0.068 0.004
#> SRR1445304 2 0.2077 0.8575 0.000 0.908 0.000 0.084 0.008
#> SRR1099378 2 0.5728 0.5383 0.272 0.612 0.000 0.004 0.112
#> SRR1347412 1 0.6827 0.1620 0.484 0.000 0.260 0.012 0.244
#> SRR1099694 2 0.2238 0.8590 0.004 0.912 0.000 0.064 0.020
#> SRR1088365 2 0.2006 0.8598 0.000 0.916 0.000 0.072 0.012
#> SRR1325752 2 0.1739 0.8697 0.024 0.940 0.000 0.032 0.004
#> SRR1416713 2 0.2351 0.8627 0.000 0.896 0.000 0.088 0.016
#> SRR1074474 1 0.2020 0.6470 0.900 0.000 0.000 0.000 0.100
#> SRR1469369 3 0.0162 0.7394 0.000 0.000 0.996 0.004 0.000
#> SRR1400507 2 0.1430 0.8649 0.000 0.944 0.000 0.052 0.004
#> SRR1378179 2 0.1282 0.8673 0.000 0.952 0.000 0.044 0.004
#> SRR1377905 2 0.6456 0.5636 0.004 0.592 0.160 0.224 0.020
#> SRR1089479 1 0.3300 0.5875 0.792 0.000 0.000 0.004 0.204
#> SRR1073365 2 0.2130 0.8571 0.000 0.908 0.000 0.080 0.012
#> SRR1500306 1 0.3048 0.5637 0.820 0.004 0.000 0.000 0.176
#> SRR1101566 2 0.6880 0.6482 0.096 0.632 0.132 0.124 0.016
#> SRR1350503 3 0.1357 0.7300 0.000 0.000 0.948 0.048 0.004
#> SRR1446007 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.2130 0.8571 0.000 0.908 0.000 0.080 0.012
#> SRR1380293 2 0.2141 0.8603 0.004 0.916 0.000 0.064 0.016
#> SRR1331198 2 0.2367 0.8568 0.004 0.904 0.000 0.072 0.020
#> SRR1092686 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 2 0.3739 0.8249 0.024 0.820 0.000 0.136 0.020
#> SRR1341650 2 0.6898 0.5734 0.028 0.588 0.140 0.220 0.024
#> SRR1357276 2 0.2270 0.8586 0.000 0.904 0.000 0.076 0.020
#> SRR1498374 2 0.2925 0.8585 0.040 0.888 0.004 0.056 0.012
#> SRR1093721 2 0.1331 0.8671 0.000 0.952 0.000 0.040 0.008
#> SRR1464660 5 0.1121 0.6704 0.044 0.000 0.000 0.000 0.956
#> SRR1402051 2 0.4892 0.6571 0.280 0.676 0.000 0.016 0.028
#> SRR1488734 2 0.1768 0.8671 0.000 0.924 0.000 0.072 0.004
#> SRR1082616 3 0.0290 0.7364 0.000 0.000 0.992 0.008 0.000
#> SRR1099427 3 0.7144 0.1320 0.012 0.372 0.420 0.184 0.012
#> SRR1453093 2 0.2707 0.8345 0.132 0.860 0.000 0.000 0.008
#> SRR1357064 5 0.2891 0.6910 0.176 0.000 0.000 0.000 0.824
#> SRR811237 2 0.1168 0.8664 0.000 0.960 0.000 0.032 0.008
#> SRR1100848 2 0.2304 0.8577 0.004 0.908 0.000 0.068 0.020
#> SRR1346755 2 0.6750 0.5340 0.020 0.572 0.164 0.232 0.012
#> SRR1472529 2 0.2644 0.8618 0.036 0.896 0.000 0.060 0.008
#> SRR1398905 4 0.3999 1.0000 0.000 0.000 0.344 0.656 0.000
#> SRR1082733 2 0.2130 0.8571 0.000 0.908 0.000 0.080 0.012
#> SRR1308035 3 0.3796 0.0304 0.000 0.000 0.700 0.300 0.000
#> SRR1466445 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.2367 0.8568 0.004 0.904 0.000 0.072 0.020
#> SRR1455825 2 0.2006 0.8704 0.000 0.916 0.000 0.072 0.012
#> SRR1389300 2 0.1571 0.8641 0.000 0.936 0.000 0.060 0.004
#> SRR812246 3 0.0290 0.7364 0.000 0.000 0.992 0.008 0.000
#> SRR1076632 2 0.0451 0.8694 0.000 0.988 0.000 0.004 0.008
#> SRR1415567 1 0.1121 0.6537 0.956 0.000 0.000 0.000 0.044
#> SRR1331900 2 0.2130 0.8571 0.000 0.908 0.000 0.080 0.012
#> SRR1452099 2 0.6104 0.4467 0.296 0.560 0.000 0.004 0.140
#> SRR1352346 2 0.3385 0.8389 0.084 0.856 0.000 0.044 0.016
#> SRR1364034 2 0.1205 0.8700 0.000 0.956 0.000 0.040 0.004
#> SRR1086046 2 0.5156 0.5711 0.320 0.620 0.000 0.000 0.060
#> SRR1407226 5 0.6688 0.1117 0.356 0.240 0.000 0.000 0.404
#> SRR1319363 2 0.5290 0.6020 0.280 0.644 0.000 0.004 0.072
#> SRR1446961 3 0.2536 0.6890 0.000 0.000 0.868 0.128 0.004
#> SRR1486650 1 0.3579 0.5599 0.756 0.000 0.000 0.004 0.240
#> SRR1470152 5 0.1121 0.6704 0.044 0.000 0.000 0.000 0.956
#> SRR1454785 3 0.0703 0.7216 0.000 0.000 0.976 0.024 0.000
#> SRR1092329 2 0.6316 0.5791 0.004 0.600 0.148 0.232 0.016
#> SRR1091476 4 0.3999 1.0000 0.000 0.000 0.344 0.656 0.000
#> SRR1073775 2 0.2541 0.8608 0.068 0.900 0.000 0.020 0.012
#> SRR1366873 2 0.1557 0.8642 0.000 0.940 0.000 0.052 0.008
#> SRR1398114 2 0.0880 0.8694 0.000 0.968 0.000 0.032 0.000
#> SRR1089950 2 0.6924 -0.2283 0.288 0.376 0.000 0.004 0.332
#> SRR1433272 2 0.2807 0.8577 0.032 0.892 0.000 0.056 0.020
#> SRR1075314 1 0.5039 -0.2967 0.512 0.032 0.000 0.000 0.456
#> SRR1085590 3 0.4215 0.6362 0.000 0.052 0.772 0.172 0.004
#> SRR1100752 3 0.4219 -0.4416 0.000 0.000 0.584 0.416 0.000
#> SRR1391494 2 0.6842 0.5461 0.020 0.576 0.156 0.228 0.020
#> SRR1333263 3 0.4082 0.6511 0.000 0.056 0.796 0.140 0.008
#> SRR1310231 2 0.0963 0.8679 0.000 0.964 0.000 0.036 0.000
#> SRR1094144 2 0.1877 0.8622 0.000 0.924 0.000 0.064 0.012
#> SRR1092160 2 0.2367 0.8568 0.004 0.904 0.000 0.072 0.020
#> SRR1320300 2 0.1883 0.8655 0.000 0.932 0.012 0.048 0.008
#> SRR1322747 3 0.5051 0.5845 0.008 0.076 0.728 0.180 0.008
#> SRR1432719 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 2 0.1597 0.8665 0.000 0.940 0.000 0.048 0.012
#> SRR1087511 2 0.4037 0.6898 0.288 0.704 0.000 0.004 0.004
#> SRR1470336 1 0.2068 0.5925 0.904 0.004 0.000 0.000 0.092
#> SRR1322536 5 0.5178 0.2886 0.448 0.032 0.000 0.004 0.516
#> SRR1100824 5 0.3577 0.6182 0.084 0.000 0.076 0.004 0.836
#> SRR1085951 4 0.3999 1.0000 0.000 0.000 0.344 0.656 0.000
#> SRR1322046 2 0.2492 0.8563 0.008 0.900 0.000 0.072 0.020
#> SRR1316420 5 0.3835 0.6209 0.260 0.008 0.000 0.000 0.732
#> SRR1070913 2 0.2077 0.8575 0.000 0.908 0.000 0.084 0.008
#> SRR1345806 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 2 0.2790 0.8570 0.028 0.892 0.000 0.060 0.020
#> SRR1337666 2 0.2367 0.8568 0.004 0.904 0.000 0.072 0.020
#> SRR1076823 1 0.5109 -0.2971 0.504 0.036 0.000 0.000 0.460
#> SRR1093954 2 0.2017 0.8583 0.000 0.912 0.000 0.080 0.008
#> SRR1451921 2 0.4511 0.5941 0.356 0.628 0.000 0.000 0.016
#> SRR1491257 5 0.1410 0.6778 0.060 0.000 0.000 0.000 0.940
#> SRR1416979 2 0.1408 0.8708 0.000 0.948 0.000 0.044 0.008
#> SRR1419015 2 0.7085 0.4529 0.076 0.552 0.096 0.008 0.268
#> SRR817649 2 0.2367 0.8568 0.004 0.904 0.000 0.072 0.020
#> SRR1466376 2 0.2505 0.8614 0.000 0.888 0.000 0.092 0.020
#> SRR1392055 2 0.1638 0.8635 0.000 0.932 0.000 0.064 0.004
#> SRR1120913 2 0.2189 0.8691 0.000 0.904 0.000 0.084 0.012
#> SRR1120869 2 0.0693 0.8698 0.000 0.980 0.000 0.012 0.008
#> SRR1319419 3 0.0771 0.7386 0.000 0.000 0.976 0.020 0.004
#> SRR816495 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR818694 2 0.2976 0.8311 0.132 0.852 0.000 0.004 0.012
#> SRR1465653 5 0.2471 0.6996 0.136 0.000 0.000 0.000 0.864
#> SRR1475952 1 0.0955 0.6446 0.968 0.004 0.000 0.000 0.028
#> SRR1465040 3 0.0703 0.7216 0.000 0.000 0.976 0.024 0.000
#> SRR1088461 2 0.1831 0.8608 0.000 0.920 0.000 0.076 0.004
#> SRR810129 2 0.1571 0.8684 0.000 0.936 0.000 0.060 0.004
#> SRR1400141 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 5 0.3966 0.5491 0.336 0.000 0.000 0.000 0.664
#> SRR1437576 2 0.6702 0.4453 0.012 0.552 0.228 0.200 0.008
#> SRR814407 1 0.6775 0.2565 0.492 0.000 0.220 0.012 0.276
#> SRR1332403 2 0.1892 0.8631 0.000 0.916 0.000 0.080 0.004
#> SRR1099598 2 0.2177 0.8592 0.004 0.908 0.000 0.080 0.008
#> SRR1327723 2 0.1956 0.8655 0.000 0.916 0.000 0.076 0.008
#> SRR1392525 3 0.4336 0.6338 0.000 0.052 0.768 0.172 0.008
#> SRR1320536 1 0.2230 0.6407 0.884 0.000 0.000 0.000 0.116
#> SRR1083824 3 0.4439 0.6265 0.000 0.056 0.760 0.176 0.008
#> SRR1351390 5 0.3895 0.6235 0.264 0.004 0.000 0.004 0.728
#> SRR1309141 3 0.4475 0.6233 0.000 0.056 0.756 0.180 0.008
#> SRR1452803 2 0.2233 0.8645 0.000 0.904 0.000 0.080 0.016
#> SRR811631 3 0.4475 0.6233 0.000 0.056 0.756 0.180 0.008
#> SRR1485563 2 0.0960 0.8704 0.016 0.972 0.000 0.004 0.008
#> SRR1311531 3 0.0000 0.7418 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 2 0.1883 0.8646 0.012 0.932 0.000 0.048 0.008
#> SRR1480831 2 0.2130 0.8571 0.000 0.908 0.000 0.080 0.012
#> SRR1083892 5 0.5841 0.3642 0.212 0.180 0.000 0.000 0.608
#> SRR809873 2 0.5686 0.4438 0.356 0.552 0.000 0.000 0.092
#> SRR1341854 2 0.1740 0.8653 0.000 0.932 0.000 0.056 0.012
#> SRR1399335 2 0.2144 0.8604 0.000 0.912 0.000 0.068 0.020
#> SRR1464209 5 0.2605 0.7003 0.148 0.000 0.000 0.000 0.852
#> SRR1389886 2 0.1952 0.8587 0.000 0.912 0.000 0.084 0.004
#> SRR1400730 4 0.3999 1.0000 0.000 0.000 0.344 0.656 0.000
#> SRR1448008 2 0.4305 0.7785 0.176 0.768 0.000 0.048 0.008
#> SRR1087606 5 0.3790 0.6330 0.248 0.004 0.000 0.004 0.744
#> SRR1445111 1 0.3074 0.5790 0.804 0.000 0.000 0.000 0.196
#> SRR816865 2 0.1983 0.8626 0.060 0.924 0.000 0.008 0.008
#> SRR1323360 3 0.2074 0.6284 0.000 0.000 0.896 0.104 0.000
#> SRR1417364 3 0.1908 0.7120 0.000 0.000 0.908 0.092 0.000
#> SRR1480329 2 0.0798 0.8687 0.000 0.976 0.000 0.016 0.008
#> SRR1403322 1 0.6223 -0.1403 0.512 0.160 0.000 0.000 0.328
#> SRR1093625 1 0.1197 0.6542 0.952 0.000 0.000 0.000 0.048
#> SRR1479977 2 0.2537 0.8649 0.024 0.904 0.000 0.056 0.016
#> SRR1082035 2 0.1588 0.8711 0.016 0.948 0.000 0.028 0.008
#> SRR1393046 2 0.6996 0.1088 0.004 0.432 0.328 0.228 0.008
#> SRR1466663 2 0.4822 0.7849 0.124 0.768 0.000 0.048 0.060
#> SRR1384456 1 0.2127 0.6433 0.892 0.000 0.000 0.000 0.108
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.2527 0.7646 0.108 0.868 0.000 0.024 0.000 0.000
#> SRR808862 4 0.3409 0.9989 0.000 0.000 0.300 0.700 0.000 0.000
#> SRR1500382 2 0.2538 0.7647 0.124 0.860 0.000 0.016 0.000 0.000
#> SRR1322683 2 0.7647 0.3554 0.148 0.428 0.196 0.208 0.000 0.020
#> SRR1329811 5 0.0508 0.7294 0.012 0.000 0.000 0.000 0.984 0.004
#> SRR1087297 2 0.3215 0.7308 0.240 0.756 0.000 0.000 0.000 0.004
#> SRR1072626 2 0.2632 0.7297 0.164 0.832 0.000 0.004 0.000 0.000
#> SRR1407428 6 0.5123 -0.4994 0.368 0.000 0.000 0.024 0.044 0.564
#> SRR1321029 2 0.5748 0.6451 0.252 0.624 0.044 0.056 0.000 0.024
#> SRR1500282 1 0.6768 0.6160 0.464 0.000 0.024 0.020 0.264 0.228
#> SRR1100496 3 0.1806 0.6367 0.004 0.000 0.908 0.088 0.000 0.000
#> SRR1308778 2 0.1866 0.7696 0.084 0.908 0.008 0.000 0.000 0.000
#> SRR1445304 2 0.2868 0.7439 0.132 0.840 0.000 0.028 0.000 0.000
#> SRR1099378 2 0.6062 0.3697 0.032 0.552 0.000 0.008 0.116 0.292
#> SRR1347412 1 0.7831 0.4598 0.464 0.000 0.196 0.076 0.112 0.152
#> SRR1099694 2 0.3470 0.7219 0.248 0.740 0.000 0.000 0.000 0.012
#> SRR1088365 2 0.2662 0.7342 0.152 0.840 0.000 0.004 0.000 0.004
#> SRR1325752 2 0.3279 0.7456 0.060 0.828 0.000 0.000 0.004 0.108
#> SRR1416713 2 0.3487 0.7377 0.224 0.756 0.000 0.020 0.000 0.000
#> SRR1074474 1 0.6002 0.6854 0.448 0.000 0.000 0.028 0.116 0.408
#> SRR1469369 3 0.0858 0.7196 0.004 0.000 0.968 0.028 0.000 0.000
#> SRR1400507 2 0.2422 0.7630 0.072 0.892 0.000 0.024 0.000 0.012
#> SRR1378179 2 0.1204 0.7649 0.056 0.944 0.000 0.000 0.000 0.000
#> SRR1377905 2 0.7624 0.4261 0.168 0.444 0.156 0.208 0.000 0.024
#> SRR1089479 1 0.5741 0.6507 0.472 0.000 0.000 0.012 0.120 0.396
#> SRR1073365 2 0.3065 0.7290 0.152 0.820 0.000 0.028 0.000 0.000
#> SRR1500306 6 0.4667 -0.2324 0.308 0.004 0.000 0.000 0.056 0.632
#> SRR1101566 2 0.7719 0.4936 0.132 0.496 0.120 0.068 0.004 0.180
#> SRR1350503 3 0.2237 0.7066 0.036 0.000 0.896 0.068 0.000 0.000
#> SRR1446007 3 0.0458 0.7232 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1102875 2 0.2743 0.7277 0.164 0.828 0.000 0.008 0.000 0.000
#> SRR1380293 2 0.3494 0.7199 0.252 0.736 0.000 0.000 0.000 0.012
#> SRR1331198 2 0.3564 0.7168 0.264 0.724 0.000 0.000 0.000 0.012
#> SRR1092686 3 0.0458 0.7232 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1069421 2 0.3918 0.7318 0.208 0.748 0.000 0.008 0.000 0.036
#> SRR1341650 2 0.7518 0.4924 0.120 0.496 0.132 0.208 0.004 0.040
#> SRR1357276 2 0.3421 0.7231 0.256 0.736 0.000 0.000 0.000 0.008
#> SRR1498374 2 0.5393 0.7003 0.228 0.656 0.012 0.032 0.000 0.072
#> SRR1093721 2 0.2053 0.7578 0.108 0.888 0.000 0.004 0.000 0.000
#> SRR1464660 5 0.0508 0.7294 0.012 0.000 0.000 0.000 0.984 0.004
#> SRR1402051 2 0.5362 0.5536 0.088 0.596 0.000 0.008 0.008 0.300
#> SRR1488734 2 0.2092 0.7536 0.124 0.876 0.000 0.000 0.000 0.000
#> SRR1082616 3 0.1838 0.6661 0.016 0.000 0.916 0.068 0.000 0.000
#> SRR1099427 2 0.7779 0.2371 0.144 0.388 0.240 0.208 0.000 0.020
#> SRR1453093 6 0.4601 0.3026 0.020 0.348 0.000 0.000 0.020 0.612
#> SRR1357064 5 0.4230 0.3022 0.008 0.008 0.000 0.000 0.584 0.400
#> SRR811237 2 0.1901 0.7596 0.076 0.912 0.000 0.004 0.000 0.008
#> SRR1100848 2 0.3483 0.7267 0.236 0.748 0.000 0.000 0.000 0.016
#> SRR1346755 2 0.7607 0.4422 0.148 0.460 0.152 0.208 0.000 0.032
#> SRR1472529 2 0.5052 0.7169 0.176 0.692 0.000 0.036 0.000 0.096
#> SRR1398905 4 0.3409 0.9989 0.000 0.000 0.300 0.700 0.000 0.000
#> SRR1082733 2 0.2743 0.7277 0.164 0.828 0.000 0.008 0.000 0.000
#> SRR1308035 3 0.3390 0.1878 0.000 0.000 0.704 0.296 0.000 0.000
#> SRR1466445 3 0.0458 0.7232 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1359080 2 0.3541 0.7186 0.260 0.728 0.000 0.000 0.000 0.012
#> SRR1455825 2 0.3343 0.7664 0.176 0.796 0.000 0.024 0.000 0.004
#> SRR1389300 2 0.2669 0.7608 0.108 0.864 0.000 0.024 0.000 0.004
#> SRR812246 3 0.1700 0.6498 0.004 0.000 0.916 0.080 0.000 0.000
#> SRR1076632 2 0.2209 0.7653 0.072 0.900 0.000 0.004 0.000 0.024
#> SRR1415567 6 0.5182 -0.5521 0.408 0.000 0.000 0.020 0.048 0.524
#> SRR1331900 2 0.2949 0.7365 0.140 0.832 0.000 0.028 0.000 0.000
#> SRR1452099 2 0.6846 0.2261 0.064 0.460 0.000 0.012 0.140 0.324
#> SRR1352346 2 0.4406 0.6759 0.056 0.736 0.016 0.000 0.004 0.188
#> SRR1364034 2 0.2112 0.7681 0.088 0.896 0.000 0.000 0.000 0.016
#> SRR1086046 2 0.5602 0.3216 0.040 0.496 0.000 0.000 0.056 0.408
#> SRR1407226 6 0.5582 0.3789 0.016 0.120 0.000 0.008 0.240 0.616
#> SRR1319363 6 0.5112 0.3606 0.020 0.272 0.000 0.004 0.064 0.640
#> SRR1446961 3 0.3344 0.6513 0.044 0.000 0.804 0.152 0.000 0.000
#> SRR1486650 1 0.6278 0.6417 0.408 0.000 0.000 0.024 0.172 0.396
#> SRR1470152 5 0.0508 0.7294 0.012 0.000 0.000 0.000 0.984 0.004
#> SRR1454785 3 0.1267 0.6997 0.000 0.000 0.940 0.060 0.000 0.000
#> SRR1092329 2 0.7522 0.4625 0.144 0.472 0.140 0.212 0.000 0.032
#> SRR1091476 4 0.3409 0.9989 0.000 0.000 0.300 0.700 0.000 0.000
#> SRR1073775 2 0.4144 0.7000 0.072 0.728 0.000 0.000 0.000 0.200
#> SRR1366873 2 0.2537 0.7571 0.088 0.880 0.000 0.024 0.000 0.008
#> SRR1398114 2 0.1075 0.7642 0.048 0.952 0.000 0.000 0.000 0.000
#> SRR1089950 6 0.6394 0.3055 0.020 0.252 0.000 0.012 0.204 0.512
#> SRR1433272 2 0.4067 0.7160 0.212 0.728 0.000 0.000 0.000 0.060
#> SRR1075314 6 0.2039 0.4651 0.000 0.020 0.000 0.000 0.076 0.904
#> SRR1085590 3 0.5055 0.5687 0.080 0.032 0.676 0.212 0.000 0.000
#> SRR1100752 3 0.3482 0.1015 0.000 0.000 0.684 0.316 0.000 0.000
#> SRR1391494 2 0.7556 0.4571 0.144 0.468 0.148 0.208 0.000 0.032
#> SRR1333263 3 0.5168 0.5740 0.104 0.036 0.680 0.180 0.000 0.000
#> SRR1310231 2 0.2126 0.7700 0.072 0.904 0.000 0.020 0.000 0.004
#> SRR1094144 2 0.5350 0.4390 0.152 0.616 0.000 0.008 0.000 0.224
#> SRR1092160 2 0.3518 0.7189 0.256 0.732 0.000 0.000 0.000 0.012
#> SRR1320300 2 0.2053 0.7515 0.108 0.888 0.000 0.004 0.000 0.000
#> SRR1322747 3 0.7336 0.2793 0.124 0.196 0.444 0.228 0.000 0.008
#> SRR1432719 3 0.1498 0.7216 0.028 0.000 0.940 0.032 0.000 0.000
#> SRR1100728 2 0.2261 0.7525 0.104 0.884 0.000 0.008 0.000 0.004
#> SRR1087511 2 0.5084 0.5242 0.052 0.588 0.000 0.000 0.020 0.340
#> SRR1470336 6 0.2145 0.3808 0.040 0.004 0.000 0.012 0.028 0.916
#> SRR1322536 6 0.3984 0.1502 0.000 0.016 0.000 0.000 0.336 0.648
#> SRR1100824 5 0.4241 0.6775 0.044 0.000 0.036 0.012 0.784 0.124
#> SRR1085951 4 0.3547 0.9957 0.004 0.000 0.300 0.696 0.000 0.000
#> SRR1322046 2 0.3437 0.7327 0.236 0.752 0.000 0.004 0.000 0.008
#> SRR1316420 6 0.4851 -0.0426 0.024 0.008 0.000 0.008 0.448 0.512
#> SRR1070913 2 0.3027 0.7376 0.148 0.824 0.000 0.028 0.000 0.000
#> SRR1345806 3 0.0458 0.7232 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1313872 2 0.3620 0.7352 0.184 0.772 0.000 0.000 0.000 0.044
#> SRR1337666 2 0.3586 0.7146 0.268 0.720 0.000 0.000 0.000 0.012
#> SRR1076823 6 0.1908 0.4711 0.000 0.028 0.000 0.000 0.056 0.916
#> SRR1093954 2 0.2669 0.7320 0.156 0.836 0.000 0.008 0.000 0.000
#> SRR1451921 6 0.2701 0.4818 0.004 0.104 0.000 0.000 0.028 0.864
#> SRR1491257 5 0.1643 0.7436 0.008 0.000 0.000 0.000 0.924 0.068
#> SRR1416979 2 0.2482 0.7693 0.148 0.848 0.000 0.004 0.000 0.000
#> SRR1419015 2 0.7961 0.1695 0.088 0.404 0.052 0.008 0.284 0.164
#> SRR817649 2 0.3494 0.7199 0.252 0.736 0.000 0.000 0.000 0.012
#> SRR1466376 2 0.3432 0.7405 0.216 0.764 0.000 0.020 0.000 0.000
#> SRR1392055 2 0.2662 0.7567 0.120 0.856 0.000 0.024 0.000 0.000
#> SRR1120913 2 0.3161 0.7609 0.216 0.776 0.000 0.008 0.000 0.000
#> SRR1120869 2 0.1787 0.7675 0.068 0.920 0.000 0.004 0.000 0.008
#> SRR1319419 3 0.0865 0.7254 0.000 0.000 0.964 0.036 0.000 0.000
#> SRR816495 3 0.0458 0.7232 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR818694 2 0.4830 0.6246 0.056 0.660 0.000 0.000 0.020 0.264
#> SRR1465653 5 0.2203 0.7415 0.016 0.004 0.000 0.000 0.896 0.084
#> SRR1475952 6 0.2846 0.2547 0.100 0.004 0.000 0.012 0.020 0.864
#> SRR1465040 3 0.1267 0.6997 0.000 0.000 0.940 0.060 0.000 0.000
#> SRR1088461 2 0.2553 0.7356 0.144 0.848 0.000 0.008 0.000 0.000
#> SRR810129 2 0.1327 0.7641 0.064 0.936 0.000 0.000 0.000 0.000
#> SRR1400141 3 0.0000 0.7252 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 6 0.5508 0.0918 0.084 0.004 0.000 0.012 0.368 0.532
#> SRR1437576 2 0.7578 0.3768 0.140 0.440 0.188 0.212 0.000 0.020
#> SRR814407 1 0.7897 0.5187 0.460 0.000 0.164 0.072 0.140 0.164
#> SRR1332403 2 0.2706 0.7465 0.124 0.852 0.000 0.024 0.000 0.000
#> SRR1099598 2 0.5373 0.3896 0.152 0.596 0.000 0.004 0.000 0.248
#> SRR1327723 2 0.2320 0.7494 0.132 0.864 0.000 0.004 0.000 0.000
#> SRR1392525 3 0.5626 0.5354 0.112 0.036 0.632 0.216 0.000 0.004
#> SRR1320536 1 0.5997 0.6917 0.456 0.000 0.000 0.028 0.116 0.400
#> SRR1083824 3 0.6169 0.4728 0.108 0.088 0.580 0.224 0.000 0.000
#> SRR1351390 5 0.4333 0.3855 0.020 0.004 0.000 0.000 0.596 0.380
#> SRR1309141 3 0.5756 0.5164 0.116 0.048 0.612 0.224 0.000 0.000
#> SRR1452803 2 0.3404 0.7358 0.224 0.760 0.000 0.016 0.000 0.000
#> SRR811631 3 0.6388 0.4602 0.120 0.084 0.564 0.228 0.000 0.004
#> SRR1485563 2 0.2094 0.7649 0.064 0.908 0.000 0.004 0.000 0.024
#> SRR1311531 3 0.0547 0.7221 0.000 0.000 0.980 0.020 0.000 0.000
#> SRR1353076 2 0.3017 0.7426 0.084 0.844 0.000 0.000 0.000 0.072
#> SRR1480831 2 0.2743 0.7277 0.164 0.828 0.000 0.008 0.000 0.000
#> SRR1083892 6 0.5214 -0.0249 0.012 0.060 0.000 0.000 0.452 0.476
#> SRR809873 6 0.2631 0.4924 0.004 0.076 0.000 0.000 0.044 0.876
#> SRR1341854 2 0.2595 0.7576 0.160 0.836 0.000 0.000 0.000 0.004
#> SRR1399335 2 0.3421 0.7231 0.256 0.736 0.000 0.000 0.000 0.008
#> SRR1464209 5 0.2830 0.7172 0.020 0.000 0.000 0.000 0.836 0.144
#> SRR1389886 2 0.2618 0.7474 0.116 0.860 0.000 0.024 0.000 0.000
#> SRR1400730 4 0.3409 0.9989 0.000 0.000 0.300 0.700 0.000 0.000
#> SRR1448008 2 0.5308 0.6374 0.112 0.636 0.008 0.008 0.000 0.236
#> SRR1087606 5 0.4542 0.4714 0.028 0.004 0.000 0.008 0.636 0.324
#> SRR1445111 1 0.5689 0.6636 0.468 0.000 0.000 0.008 0.124 0.400
#> SRR816865 2 0.2533 0.7606 0.056 0.884 0.000 0.004 0.000 0.056
#> SRR1323360 3 0.2092 0.6131 0.000 0.000 0.876 0.124 0.000 0.000
#> SRR1417364 3 0.2019 0.7072 0.012 0.000 0.900 0.088 0.000 0.000
#> SRR1480329 2 0.1668 0.7695 0.060 0.928 0.000 0.004 0.000 0.008
#> SRR1403322 6 0.2134 0.4877 0.000 0.052 0.000 0.000 0.044 0.904
#> SRR1093625 6 0.5353 -0.6310 0.452 0.000 0.000 0.028 0.048 0.472
#> SRR1479977 2 0.4329 0.7261 0.240 0.700 0.000 0.004 0.000 0.056
#> SRR1082035 2 0.1523 0.7724 0.044 0.940 0.000 0.008 0.000 0.008
#> SRR1393046 2 0.7665 0.3467 0.148 0.424 0.200 0.208 0.000 0.020
#> SRR1466663 2 0.4478 0.7169 0.176 0.716 0.000 0.004 0.000 0.104
#> SRR1384456 1 0.6000 0.6894 0.452 0.000 0.000 0.028 0.116 0.404
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 17467 rows and 159 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 1.000 0.985 0.994 0.3459 0.654 0.654
#> 3 3 0.959 0.951 0.980 0.7285 0.699 0.556
#> 4 4 0.651 0.732 0.861 0.1905 0.862 0.669
#> 5 5 0.653 0.681 0.813 0.1100 0.824 0.484
#> 6 6 0.688 0.580 0.763 0.0432 0.935 0.709
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
#> SRR810713 2 0.0000 0.996 0.000 1.000
#> SRR808862 1 0.0000 0.985 1.000 0.000
#> SRR1500382 2 0.0000 0.996 0.000 1.000
#> SRR1322683 2 0.0000 0.996 0.000 1.000
#> SRR1329811 2 0.0000 0.996 0.000 1.000
#> SRR1087297 2 0.0000 0.996 0.000 1.000
#> SRR1072626 2 0.0000 0.996 0.000 1.000
#> SRR1407428 2 0.0000 0.996 0.000 1.000
#> SRR1321029 2 0.0000 0.996 0.000 1.000
#> SRR1500282 2 0.0000 0.996 0.000 1.000
#> SRR1100496 1 0.0000 0.985 1.000 0.000
#> SRR1308778 2 0.0000 0.996 0.000 1.000
#> SRR1445304 2 0.0000 0.996 0.000 1.000
#> SRR1099378 2 0.0000 0.996 0.000 1.000
#> SRR1347412 1 0.0000 0.985 1.000 0.000
#> SRR1099694 2 0.0000 0.996 0.000 1.000
#> SRR1088365 2 0.0000 0.996 0.000 1.000
#> SRR1325752 2 0.0000 0.996 0.000 1.000
#> SRR1416713 2 0.0000 0.996 0.000 1.000
#> SRR1074474 2 0.0000 0.996 0.000 1.000
#> SRR1469369 1 0.0000 0.985 1.000 0.000
#> SRR1400507 2 0.0000 0.996 0.000 1.000
#> SRR1378179 2 0.0000 0.996 0.000 1.000
#> SRR1377905 2 0.0376 0.992 0.004 0.996
#> SRR1089479 2 0.0000 0.996 0.000 1.000
#> SRR1073365 2 0.0000 0.996 0.000 1.000
#> SRR1500306 2 0.0000 0.996 0.000 1.000
#> SRR1101566 2 0.0000 0.996 0.000 1.000
#> SRR1350503 1 0.0000 0.985 1.000 0.000
#> SRR1446007 1 0.0000 0.985 1.000 0.000
#> SRR1102875 2 0.0000 0.996 0.000 1.000
#> SRR1380293 2 0.0000 0.996 0.000 1.000
#> SRR1331198 2 0.0000 0.996 0.000 1.000
#> SRR1092686 1 0.0000 0.985 1.000 0.000
#> SRR1069421 2 0.0000 0.996 0.000 1.000
#> SRR1341650 2 0.0000 0.996 0.000 1.000
#> SRR1357276 2 0.0000 0.996 0.000 1.000
#> SRR1498374 2 0.0000 0.996 0.000 1.000
#> SRR1093721 2 0.0000 0.996 0.000 1.000
#> SRR1464660 2 0.0000 0.996 0.000 1.000
#> SRR1402051 2 0.0000 0.996 0.000 1.000
#> SRR1488734 2 0.0000 0.996 0.000 1.000
#> SRR1082616 1 0.0000 0.985 1.000 0.000
#> SRR1099427 1 0.7376 0.742 0.792 0.208
#> SRR1453093 2 0.0000 0.996 0.000 1.000
#> SRR1357064 2 0.0000 0.996 0.000 1.000
#> SRR811237 2 0.0000 0.996 0.000 1.000
#> SRR1100848 2 0.0000 0.996 0.000 1.000
#> SRR1346755 2 0.0000 0.996 0.000 1.000
#> SRR1472529 2 0.0000 0.996 0.000 1.000
#> SRR1398905 1 0.0000 0.985 1.000 0.000
#> SRR1082733 2 0.0000 0.996 0.000 1.000
#> SRR1308035 1 0.0000 0.985 1.000 0.000
#> SRR1466445 1 0.0000 0.985 1.000 0.000
#> SRR1359080 2 0.0000 0.996 0.000 1.000
#> SRR1455825 2 0.0000 0.996 0.000 1.000
#> SRR1389300 2 0.0000 0.996 0.000 1.000
#> SRR812246 1 0.0000 0.985 1.000 0.000
#> SRR1076632 2 0.0000 0.996 0.000 1.000
#> SRR1415567 2 0.0000 0.996 0.000 1.000
#> SRR1331900 2 0.0000 0.996 0.000 1.000
#> SRR1452099 2 0.0000 0.996 0.000 1.000
#> SRR1352346 2 0.0000 0.996 0.000 1.000
#> SRR1364034 2 0.0000 0.996 0.000 1.000
#> SRR1086046 2 0.0000 0.996 0.000 1.000
#> SRR1407226 2 0.0000 0.996 0.000 1.000
#> SRR1319363 2 0.0000 0.996 0.000 1.000
#> SRR1446961 1 0.0000 0.985 1.000 0.000
#> SRR1486650 2 0.0000 0.996 0.000 1.000
#> SRR1470152 2 0.0000 0.996 0.000 1.000
#> SRR1454785 1 0.0000 0.985 1.000 0.000
#> SRR1092329 2 0.0000 0.996 0.000 1.000
#> SRR1091476 1 0.0000 0.985 1.000 0.000
#> SRR1073775 2 0.0000 0.996 0.000 1.000
#> SRR1366873 2 0.0000 0.996 0.000 1.000
#> SRR1398114 2 0.0000 0.996 0.000 1.000
#> SRR1089950 2 0.0000 0.996 0.000 1.000
#> SRR1433272 2 0.0000 0.996 0.000 1.000
#> SRR1075314 2 0.0000 0.996 0.000 1.000
#> SRR1085590 1 0.0000 0.985 1.000 0.000
#> SRR1100752 1 0.0000 0.985 1.000 0.000
#> SRR1391494 2 0.0000 0.996 0.000 1.000
#> SRR1333263 1 0.0000 0.985 1.000 0.000
#> SRR1310231 2 0.0000 0.996 0.000 1.000
#> SRR1094144 2 0.0000 0.996 0.000 1.000
#> SRR1092160 2 0.0000 0.996 0.000 1.000
#> SRR1320300 2 0.0000 0.996 0.000 1.000
#> SRR1322747 1 0.0000 0.985 1.000 0.000
#> SRR1432719 1 0.0000 0.985 1.000 0.000
#> SRR1100728 2 0.0000 0.996 0.000 1.000
#> SRR1087511 2 0.0000 0.996 0.000 1.000
#> SRR1470336 2 0.0000 0.996 0.000 1.000
#> SRR1322536 2 0.0000 0.996 0.000 1.000
#> SRR1100824 2 0.0000 0.996 0.000 1.000
#> SRR1085951 1 0.0000 0.985 1.000 0.000
#> SRR1322046 2 0.0000 0.996 0.000 1.000
#> SRR1316420 2 0.0000 0.996 0.000 1.000
#> SRR1070913 2 0.0000 0.996 0.000 1.000
#> SRR1345806 1 0.0000 0.985 1.000 0.000
#> SRR1313872 2 0.0000 0.996 0.000 1.000
#> SRR1337666 2 0.0000 0.996 0.000 1.000
#> SRR1076823 2 0.0000 0.996 0.000 1.000
#> SRR1093954 2 0.0000 0.996 0.000 1.000
#> SRR1451921 2 0.0000 0.996 0.000 1.000
#> SRR1491257 2 0.0000 0.996 0.000 1.000
#> SRR1416979 2 0.0000 0.996 0.000 1.000
#> SRR1419015 2 0.1843 0.968 0.028 0.972
#> SRR817649 2 0.0000 0.996 0.000 1.000
#> SRR1466376 2 0.0000 0.996 0.000 1.000
#> SRR1392055 2 0.0000 0.996 0.000 1.000
#> SRR1120913 2 0.0000 0.996 0.000 1.000
#> SRR1120869 2 0.0000 0.996 0.000 1.000
#> SRR1319419 1 0.0000 0.985 1.000 0.000
#> SRR816495 1 0.0000 0.985 1.000 0.000
#> SRR818694 2 0.0000 0.996 0.000 1.000
#> SRR1465653 2 0.0000 0.996 0.000 1.000
#> SRR1475952 2 0.0000 0.996 0.000 1.000
#> SRR1465040 1 0.0000 0.985 1.000 0.000
#> SRR1088461 2 0.0000 0.996 0.000 1.000
#> SRR810129 2 0.0000 0.996 0.000 1.000
#> SRR1400141 1 0.0000 0.985 1.000 0.000
#> SRR1349585 2 0.0000 0.996 0.000 1.000
#> SRR1437576 2 0.1843 0.968 0.028 0.972
#> SRR814407 2 0.3584 0.924 0.068 0.932
#> SRR1332403 2 0.0000 0.996 0.000 1.000
#> SRR1099598 2 0.0000 0.996 0.000 1.000
#> SRR1327723 2 0.0000 0.996 0.000 1.000
#> SRR1392525 1 0.0000 0.985 1.000 0.000
#> SRR1320536 2 0.0000 0.996 0.000 1.000
#> SRR1083824 1 0.8267 0.656 0.740 0.260
#> SRR1351390 2 0.0000 0.996 0.000 1.000
#> SRR1309141 1 0.0000 0.985 1.000 0.000
#> SRR1452803 2 0.0000 0.996 0.000 1.000
#> SRR811631 1 0.2423 0.948 0.960 0.040
#> SRR1485563 2 0.0000 0.996 0.000 1.000
#> SRR1311531 1 0.0000 0.985 1.000 0.000
#> SRR1353076 2 0.0000 0.996 0.000 1.000
#> SRR1480831 2 0.0000 0.996 0.000 1.000
#> SRR1083892 2 0.0000 0.996 0.000 1.000
#> SRR809873 2 0.0000 0.996 0.000 1.000
#> SRR1341854 2 0.0000 0.996 0.000 1.000
#> SRR1399335 2 0.0000 0.996 0.000 1.000
#> SRR1464209 2 0.0000 0.996 0.000 1.000
#> SRR1389886 2 0.0000 0.996 0.000 1.000
#> SRR1400730 1 0.0000 0.985 1.000 0.000
#> SRR1448008 2 0.0000 0.996 0.000 1.000
#> SRR1087606 2 0.0000 0.996 0.000 1.000
#> SRR1445111 2 0.0000 0.996 0.000 1.000
#> SRR816865 2 0.0000 0.996 0.000 1.000
#> SRR1323360 1 0.0000 0.985 1.000 0.000
#> SRR1417364 1 0.0000 0.985 1.000 0.000
#> SRR1480329 2 0.0000 0.996 0.000 1.000
#> SRR1403322 2 0.0000 0.996 0.000 1.000
#> SRR1093625 2 0.0000 0.996 0.000 1.000
#> SRR1479977 2 0.0000 0.996 0.000 1.000
#> SRR1082035 2 0.0000 0.996 0.000 1.000
#> SRR1393046 2 0.9427 0.425 0.360 0.640
#> SRR1466663 2 0.0000 0.996 0.000 1.000
#> SRR1384456 2 0.0000 0.996 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.984 0.000 1.000 0.000
#> SRR808862 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1500382 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1322683 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1329811 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1087297 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1072626 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1321029 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1500282 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1100496 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1308778 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1099378 1 0.1163 0.937 0.972 0.028 0.000
#> SRR1347412 1 0.0424 0.956 0.992 0.000 0.008
#> SRR1099694 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1325752 2 0.1964 0.929 0.056 0.944 0.000
#> SRR1416713 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1469369 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1400507 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1378179 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1377905 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1089479 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1073365 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1500306 1 0.0237 0.959 0.996 0.004 0.000
#> SRR1101566 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1350503 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1102875 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1092686 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1069421 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1341650 2 0.1399 0.956 0.004 0.968 0.028
#> SRR1357276 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1498374 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1093721 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1464660 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1402051 2 0.1163 0.959 0.028 0.972 0.000
#> SRR1488734 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1082616 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1099427 2 0.4605 0.742 0.000 0.796 0.204
#> SRR1453093 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1357064 1 0.0000 0.962 1.000 0.000 0.000
#> SRR811237 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1100848 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1346755 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1472529 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1398905 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1082733 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1308035 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1359080 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.984 0.000 1.000 0.000
#> SRR812246 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1076632 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1415567 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1452099 1 0.4291 0.757 0.820 0.180 0.000
#> SRR1352346 2 0.5363 0.606 0.276 0.724 0.000
#> SRR1364034 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1086046 1 0.4974 0.675 0.764 0.236 0.000
#> SRR1407226 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1319363 1 0.1860 0.911 0.948 0.052 0.000
#> SRR1446961 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1486650 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1454785 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1092329 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1091476 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1073775 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1089950 1 0.2448 0.885 0.924 0.076 0.000
#> SRR1433272 2 0.0592 0.974 0.012 0.988 0.000
#> SRR1075314 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1085590 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1100752 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1391494 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1333263 3 0.5497 0.592 0.000 0.292 0.708
#> SRR1310231 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1094144 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1092160 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1322747 3 0.5529 0.584 0.000 0.296 0.704
#> SRR1432719 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1100728 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1087511 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1470336 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1322536 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1100824 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1085951 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1322046 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1316420 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1070913 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1345806 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1313872 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1337666 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1076823 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1093954 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1451921 1 0.5529 0.587 0.704 0.296 0.000
#> SRR1491257 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1416979 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1419015 1 0.4887 0.686 0.772 0.228 0.000
#> SRR817649 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1466376 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1120869 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1319419 3 0.0000 0.969 0.000 0.000 1.000
#> SRR816495 3 0.0000 0.969 0.000 0.000 1.000
#> SRR818694 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1465653 1 0.0592 0.952 0.988 0.012 0.000
#> SRR1475952 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1465040 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1088461 2 0.0000 0.984 0.000 1.000 0.000
#> SRR810129 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1400141 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1349585 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1437576 2 0.0000 0.984 0.000 1.000 0.000
#> SRR814407 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1332403 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1099598 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1327723 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1392525 3 0.0424 0.961 0.000 0.008 0.992
#> SRR1320536 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1083824 2 0.4974 0.691 0.000 0.764 0.236
#> SRR1351390 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1309141 3 0.2959 0.854 0.000 0.100 0.900
#> SRR1452803 2 0.0000 0.984 0.000 1.000 0.000
#> SRR811631 2 0.5098 0.671 0.000 0.752 0.248
#> SRR1485563 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1311531 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1353076 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1480831 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1083892 1 0.0000 0.962 1.000 0.000 0.000
#> SRR809873 1 0.0747 0.948 0.984 0.016 0.000
#> SRR1341854 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1464209 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1389886 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1400730 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1448008 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1087606 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.962 1.000 0.000 0.000
#> SRR816865 2 0.0237 0.980 0.004 0.996 0.000
#> SRR1323360 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1417364 3 0.0000 0.969 0.000 0.000 1.000
#> SRR1480329 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1403322 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.962 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1082035 2 0.0000 0.984 0.000 1.000 0.000
#> SRR1393046 2 0.1529 0.947 0.000 0.960 0.040
#> SRR1466663 2 0.4346 0.773 0.184 0.816 0.000
#> SRR1384456 1 0.0000 0.962 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.3801 0.6967 0.000 0.780 0.000 0.220
#> SRR808862 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1500382 2 0.2868 0.7689 0.000 0.864 0.000 0.136
#> SRR1322683 2 0.0927 0.8029 0.016 0.976 0.000 0.008
#> SRR1329811 4 0.0592 0.6913 0.016 0.000 0.000 0.984
#> SRR1087297 2 0.4996 0.0949 0.000 0.516 0.000 0.484
#> SRR1072626 2 0.1474 0.7917 0.052 0.948 0.000 0.000
#> SRR1407428 1 0.2868 0.8608 0.864 0.000 0.000 0.136
#> SRR1321029 2 0.3024 0.7617 0.000 0.852 0.000 0.148
#> SRR1500282 1 0.3873 0.8273 0.772 0.000 0.000 0.228
#> SRR1100496 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1308778 2 0.4746 0.4558 0.000 0.632 0.000 0.368
#> SRR1445304 2 0.2216 0.7891 0.000 0.908 0.000 0.092
#> SRR1099378 4 0.1302 0.6732 0.044 0.000 0.000 0.956
#> SRR1347412 1 0.5200 0.8114 0.744 0.000 0.072 0.184
#> SRR1099694 4 0.3873 0.6728 0.000 0.228 0.000 0.772
#> SRR1088365 2 0.3024 0.7343 0.148 0.852 0.000 0.000
#> SRR1325752 4 0.2973 0.7263 0.000 0.144 0.000 0.856
#> SRR1416713 2 0.4955 0.2463 0.000 0.556 0.000 0.444
#> SRR1074474 1 0.3444 0.8506 0.816 0.000 0.000 0.184
#> SRR1469369 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1400507 2 0.0657 0.8044 0.004 0.984 0.000 0.012
#> SRR1378179 2 0.4679 0.4882 0.000 0.648 0.000 0.352
#> SRR1377905 2 0.4950 0.4312 0.000 0.620 0.004 0.376
#> SRR1089479 1 0.3311 0.8543 0.828 0.000 0.000 0.172
#> SRR1073365 2 0.0672 0.8037 0.008 0.984 0.000 0.008
#> SRR1500306 1 0.2222 0.8600 0.924 0.016 0.000 0.060
#> SRR1101566 2 0.1637 0.7888 0.060 0.940 0.000 0.000
#> SRR1350503 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1446007 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1102875 2 0.2921 0.7408 0.140 0.860 0.000 0.000
#> SRR1380293 4 0.3486 0.7017 0.000 0.188 0.000 0.812
#> SRR1331198 4 0.3610 0.6894 0.000 0.200 0.000 0.800
#> SRR1092686 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1069421 2 0.4817 0.4027 0.000 0.612 0.000 0.388
#> SRR1341650 2 0.3903 0.7506 0.076 0.844 0.080 0.000
#> SRR1357276 2 0.3907 0.6859 0.000 0.768 0.000 0.232
#> SRR1498374 2 0.0817 0.8039 0.000 0.976 0.000 0.024
#> SRR1093721 2 0.0657 0.8043 0.004 0.984 0.000 0.012
#> SRR1464660 4 0.0707 0.6901 0.020 0.000 0.000 0.980
#> SRR1402051 2 0.3545 0.7237 0.164 0.828 0.000 0.008
#> SRR1488734 2 0.3172 0.7520 0.000 0.840 0.000 0.160
#> SRR1082616 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1099427 2 0.4542 0.6482 0.020 0.752 0.228 0.000
#> SRR1453093 2 0.4103 0.6265 0.256 0.744 0.000 0.000
#> SRR1357064 4 0.1637 0.6565 0.060 0.000 0.000 0.940
#> SRR811237 2 0.2814 0.7464 0.132 0.868 0.000 0.000
#> SRR1100848 4 0.3266 0.7179 0.000 0.168 0.000 0.832
#> SRR1346755 2 0.3266 0.7470 0.000 0.832 0.000 0.168
#> SRR1472529 2 0.1474 0.8015 0.000 0.948 0.000 0.052
#> SRR1398905 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1082733 2 0.1022 0.7975 0.032 0.968 0.000 0.000
#> SRR1308035 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1466445 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1359080 4 0.4713 0.4252 0.000 0.360 0.000 0.640
#> SRR1455825 2 0.1792 0.7972 0.000 0.932 0.000 0.068
#> SRR1389300 2 0.2647 0.7779 0.000 0.880 0.000 0.120
#> SRR812246 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1076632 2 0.3842 0.7585 0.128 0.836 0.000 0.036
#> SRR1415567 1 0.3266 0.8552 0.832 0.000 0.000 0.168
#> SRR1331900 2 0.0817 0.8039 0.000 0.976 0.000 0.024
#> SRR1452099 4 0.1109 0.6870 0.028 0.004 0.000 0.968
#> SRR1352346 4 0.1940 0.7215 0.000 0.076 0.000 0.924
#> SRR1364034 2 0.1767 0.8058 0.012 0.944 0.000 0.044
#> SRR1086046 1 0.2530 0.7597 0.888 0.112 0.000 0.000
#> SRR1407226 1 0.3444 0.8506 0.816 0.000 0.000 0.184
#> SRR1319363 1 0.1118 0.8565 0.964 0.000 0.000 0.036
#> SRR1446961 3 0.0188 0.9694 0.000 0.004 0.996 0.000
#> SRR1486650 1 0.3837 0.8293 0.776 0.000 0.000 0.224
#> SRR1470152 4 0.1389 0.6680 0.048 0.000 0.000 0.952
#> SRR1454785 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1092329 2 0.1151 0.8047 0.008 0.968 0.000 0.024
#> SRR1091476 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1073775 2 0.2868 0.7436 0.136 0.864 0.000 0.000
#> SRR1366873 2 0.0592 0.8014 0.016 0.984 0.000 0.000
#> SRR1398114 2 0.1557 0.8021 0.000 0.944 0.000 0.056
#> SRR1089950 1 0.4925 0.5199 0.572 0.000 0.000 0.428
#> SRR1433272 4 0.3024 0.7265 0.000 0.148 0.000 0.852
#> SRR1075314 1 0.1474 0.8134 0.948 0.052 0.000 0.000
#> SRR1085590 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1100752 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1391494 2 0.2814 0.7730 0.000 0.868 0.000 0.132
#> SRR1333263 3 0.3208 0.7859 0.000 0.148 0.848 0.004
#> SRR1310231 2 0.2760 0.7733 0.000 0.872 0.000 0.128
#> SRR1094144 2 0.3311 0.7144 0.172 0.828 0.000 0.000
#> SRR1092160 4 0.3266 0.7176 0.000 0.168 0.000 0.832
#> SRR1320300 2 0.0817 0.7995 0.024 0.976 0.000 0.000
#> SRR1322747 3 0.3837 0.6658 0.000 0.224 0.776 0.000
#> SRR1432719 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1100728 2 0.3168 0.7951 0.060 0.884 0.000 0.056
#> SRR1087511 2 0.3801 0.6678 0.220 0.780 0.000 0.000
#> SRR1470336 1 0.1867 0.8618 0.928 0.000 0.000 0.072
#> SRR1322536 1 0.1557 0.8106 0.944 0.056 0.000 0.000
#> SRR1100824 4 0.4989 -0.3489 0.472 0.000 0.000 0.528
#> SRR1085951 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1322046 4 0.4992 0.0423 0.000 0.476 0.000 0.524
#> SRR1316420 4 0.3444 0.4745 0.184 0.000 0.000 0.816
#> SRR1070913 2 0.1004 0.8048 0.004 0.972 0.000 0.024
#> SRR1345806 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1313872 4 0.4985 0.0711 0.000 0.468 0.000 0.532
#> SRR1337666 4 0.3444 0.7052 0.000 0.184 0.000 0.816
#> SRR1076823 1 0.0336 0.8465 0.992 0.000 0.000 0.008
#> SRR1093954 2 0.1557 0.7897 0.056 0.944 0.000 0.000
#> SRR1451921 1 0.3649 0.6483 0.796 0.204 0.000 0.000
#> SRR1491257 4 0.2814 0.5664 0.132 0.000 0.000 0.868
#> SRR1416979 2 0.4877 0.3484 0.000 0.592 0.000 0.408
#> SRR1419015 1 0.1629 0.8438 0.952 0.024 0.000 0.024
#> SRR817649 4 0.3311 0.7149 0.000 0.172 0.000 0.828
#> SRR1466376 2 0.4877 0.3560 0.000 0.592 0.000 0.408
#> SRR1392055 2 0.1118 0.8033 0.000 0.964 0.000 0.036
#> SRR1120913 2 0.4790 0.4286 0.000 0.620 0.000 0.380
#> SRR1120869 2 0.4164 0.6332 0.000 0.736 0.000 0.264
#> SRR1319419 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR816495 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR818694 2 0.3356 0.7110 0.176 0.824 0.000 0.000
#> SRR1465653 4 0.0376 0.6981 0.004 0.004 0.000 0.992
#> SRR1475952 1 0.1118 0.8569 0.964 0.000 0.000 0.036
#> SRR1465040 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1088461 2 0.0657 0.8028 0.012 0.984 0.000 0.004
#> SRR810129 2 0.3764 0.7005 0.000 0.784 0.000 0.216
#> SRR1400141 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1349585 4 0.4877 -0.1692 0.408 0.000 0.000 0.592
#> SRR1437576 2 0.1978 0.7975 0.000 0.928 0.004 0.068
#> SRR814407 1 0.2868 0.8608 0.864 0.000 0.000 0.136
#> SRR1332403 2 0.2760 0.7736 0.000 0.872 0.000 0.128
#> SRR1099598 2 0.3444 0.7037 0.184 0.816 0.000 0.000
#> SRR1327723 2 0.4454 0.5721 0.000 0.692 0.000 0.308
#> SRR1392525 3 0.1557 0.9112 0.000 0.056 0.944 0.000
#> SRR1320536 1 0.3837 0.8293 0.776 0.000 0.000 0.224
#> SRR1083824 2 0.7914 -0.1400 0.000 0.356 0.332 0.312
#> SRR1351390 1 0.2111 0.8539 0.932 0.024 0.000 0.044
#> SRR1309141 3 0.3024 0.7920 0.000 0.148 0.852 0.000
#> SRR1452803 4 0.4730 0.4153 0.000 0.364 0.000 0.636
#> SRR811631 2 0.5138 0.4176 0.000 0.600 0.392 0.008
#> SRR1485563 2 0.2197 0.7800 0.080 0.916 0.000 0.004
#> SRR1311531 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1353076 2 0.2973 0.7376 0.144 0.856 0.000 0.000
#> SRR1480831 2 0.2101 0.7926 0.060 0.928 0.000 0.012
#> SRR1083892 4 0.0921 0.6842 0.028 0.000 0.000 0.972
#> SRR809873 1 0.1637 0.8074 0.940 0.060 0.000 0.000
#> SRR1341854 4 0.4746 0.4082 0.000 0.368 0.000 0.632
#> SRR1399335 2 0.3311 0.7449 0.000 0.828 0.000 0.172
#> SRR1464209 4 0.1867 0.6428 0.072 0.000 0.000 0.928
#> SRR1389886 2 0.2149 0.7907 0.000 0.912 0.000 0.088
#> SRR1400730 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1448008 2 0.1854 0.7994 0.048 0.940 0.000 0.012
#> SRR1087606 4 0.2647 0.5823 0.120 0.000 0.000 0.880
#> SRR1445111 1 0.3801 0.8321 0.780 0.000 0.000 0.220
#> SRR816865 2 0.5272 0.7055 0.172 0.744 0.000 0.084
#> SRR1323360 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1417364 3 0.0000 0.9734 0.000 0.000 1.000 0.000
#> SRR1480329 2 0.1637 0.7997 0.000 0.940 0.000 0.060
#> SRR1403322 1 0.1022 0.8259 0.968 0.032 0.000 0.000
#> SRR1093625 1 0.3400 0.8518 0.820 0.000 0.000 0.180
#> SRR1479977 2 0.1940 0.7952 0.000 0.924 0.000 0.076
#> SRR1082035 2 0.1398 0.7959 0.040 0.956 0.000 0.004
#> SRR1393046 2 0.6033 0.5946 0.000 0.680 0.204 0.116
#> SRR1466663 4 0.5613 0.3605 0.028 0.380 0.000 0.592
#> SRR1384456 1 0.4331 0.7657 0.712 0.000 0.000 0.288
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.2514 0.7308 0.000 0.896 0.000 0.044 0.060
#> SRR808862 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1500382 2 0.1282 0.7410 0.000 0.952 0.000 0.004 0.044
#> SRR1322683 2 0.4477 0.5576 0.000 0.688 0.008 0.288 0.016
#> SRR1329811 5 0.1430 0.7663 0.052 0.004 0.000 0.000 0.944
#> SRR1087297 2 0.4430 0.6389 0.000 0.708 0.000 0.036 0.256
#> SRR1072626 4 0.3909 0.6717 0.000 0.216 0.000 0.760 0.024
#> SRR1407428 1 0.0510 0.8241 0.984 0.000 0.000 0.016 0.000
#> SRR1321029 2 0.2079 0.7420 0.000 0.916 0.000 0.064 0.020
#> SRR1500282 1 0.2300 0.8276 0.904 0.000 0.000 0.024 0.072
#> SRR1100496 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1308778 2 0.3694 0.7081 0.000 0.796 0.000 0.032 0.172
#> SRR1445304 2 0.2006 0.7401 0.000 0.916 0.000 0.072 0.012
#> SRR1099378 5 0.1717 0.7658 0.052 0.004 0.000 0.008 0.936
#> SRR1347412 1 0.2060 0.8151 0.924 0.000 0.052 0.008 0.016
#> SRR1099694 5 0.2797 0.7587 0.000 0.060 0.000 0.060 0.880
#> SRR1088365 4 0.4425 0.0505 0.000 0.452 0.000 0.544 0.004
#> SRR1325752 5 0.4312 0.6832 0.160 0.040 0.000 0.020 0.780
#> SRR1416713 2 0.4930 0.6129 0.000 0.684 0.000 0.072 0.244
#> SRR1074474 1 0.0000 0.8280 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1400507 2 0.2439 0.7158 0.000 0.876 0.000 0.120 0.004
#> SRR1378179 5 0.4645 0.6188 0.000 0.072 0.000 0.204 0.724
#> SRR1377905 2 0.3443 0.7134 0.000 0.816 0.012 0.008 0.164
#> SRR1089479 1 0.0404 0.8272 0.988 0.000 0.000 0.012 0.000
#> SRR1073365 2 0.5161 0.1606 0.000 0.516 0.000 0.444 0.040
#> SRR1500306 1 0.4582 0.2482 0.572 0.012 0.000 0.416 0.000
#> SRR1101566 2 0.2852 0.6760 0.000 0.828 0.000 0.172 0.000
#> SRR1350503 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1446007 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1102875 4 0.2674 0.7190 0.000 0.140 0.000 0.856 0.004
#> SRR1380293 5 0.1300 0.7809 0.000 0.028 0.000 0.016 0.956
#> SRR1331198 5 0.2795 0.7597 0.000 0.100 0.000 0.028 0.872
#> SRR1092686 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1069421 4 0.6024 0.2231 0.000 0.132 0.000 0.532 0.336
#> SRR1341650 4 0.5706 0.2549 0.000 0.380 0.076 0.540 0.004
#> SRR1357276 2 0.2304 0.7337 0.000 0.892 0.000 0.008 0.100
#> SRR1498374 2 0.2124 0.7237 0.000 0.900 0.000 0.096 0.004
#> SRR1093721 4 0.4959 0.6098 0.000 0.240 0.000 0.684 0.076
#> SRR1464660 5 0.2037 0.7579 0.064 0.004 0.000 0.012 0.920
#> SRR1402051 4 0.4700 0.6374 0.032 0.268 0.000 0.692 0.008
#> SRR1488734 2 0.3758 0.7315 0.000 0.816 0.000 0.096 0.088
#> SRR1082616 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1099427 2 0.3970 0.6102 0.000 0.752 0.224 0.024 0.000
#> SRR1453093 4 0.3452 0.7118 0.032 0.148 0.000 0.820 0.000
#> SRR1357064 5 0.5003 -0.0502 0.464 0.012 0.000 0.012 0.512
#> SRR811237 4 0.2329 0.7223 0.000 0.124 0.000 0.876 0.000
#> SRR1100848 5 0.2304 0.7713 0.000 0.044 0.000 0.048 0.908
#> SRR1346755 2 0.3214 0.7339 0.000 0.844 0.000 0.036 0.120
#> SRR1472529 2 0.3399 0.6910 0.000 0.812 0.000 0.168 0.020
#> SRR1398905 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1082733 2 0.4341 0.4371 0.000 0.628 0.000 0.364 0.008
#> SRR1308035 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1466445 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1359080 5 0.4150 0.2431 0.000 0.388 0.000 0.000 0.612
#> SRR1455825 2 0.6813 -0.0662 0.000 0.356 0.000 0.340 0.304
#> SRR1389300 2 0.1965 0.7459 0.000 0.924 0.000 0.052 0.024
#> SRR812246 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1076632 4 0.3449 0.6750 0.000 0.164 0.000 0.812 0.024
#> SRR1415567 1 0.0162 0.8272 0.996 0.000 0.000 0.004 0.000
#> SRR1331900 2 0.1908 0.7225 0.000 0.908 0.000 0.092 0.000
#> SRR1452099 5 0.2142 0.7794 0.028 0.004 0.000 0.048 0.920
#> SRR1352346 2 0.7058 -0.0752 0.252 0.376 0.000 0.012 0.360
#> SRR1364034 4 0.4732 0.6014 0.000 0.208 0.000 0.716 0.076
#> SRR1086046 4 0.3567 0.6627 0.144 0.032 0.000 0.820 0.004
#> SRR1407226 1 0.3688 0.7544 0.808 0.024 0.000 0.160 0.008
#> SRR1319363 1 0.3388 0.7366 0.792 0.008 0.000 0.200 0.000
#> SRR1446961 3 0.0963 0.9317 0.000 0.036 0.964 0.000 0.000
#> SRR1486650 1 0.1341 0.8290 0.944 0.000 0.000 0.000 0.056
#> SRR1470152 5 0.1892 0.7517 0.080 0.004 0.000 0.000 0.916
#> SRR1454785 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1092329 2 0.4779 0.4622 0.000 0.628 0.000 0.340 0.032
#> SRR1091476 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1073775 4 0.3635 0.6467 0.000 0.248 0.000 0.748 0.004
#> SRR1366873 2 0.2020 0.7202 0.000 0.900 0.000 0.100 0.000
#> SRR1398114 2 0.3283 0.6810 0.000 0.832 0.000 0.140 0.028
#> SRR1089950 1 0.3715 0.6443 0.736 0.000 0.000 0.004 0.260
#> SRR1433272 5 0.1701 0.7750 0.016 0.028 0.000 0.012 0.944
#> SRR1075314 4 0.4251 0.3155 0.372 0.004 0.000 0.624 0.000
#> SRR1085590 3 0.2104 0.8884 0.000 0.000 0.916 0.060 0.024
#> SRR1100752 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 2 0.7068 0.4565 0.000 0.508 0.036 0.236 0.220
#> SRR1333263 3 0.0865 0.9445 0.000 0.024 0.972 0.004 0.000
#> SRR1310231 2 0.3639 0.7173 0.000 0.824 0.000 0.100 0.076
#> SRR1094144 4 0.1942 0.7068 0.000 0.068 0.000 0.920 0.012
#> SRR1092160 5 0.1661 0.7808 0.000 0.036 0.000 0.024 0.940
#> SRR1320300 2 0.2329 0.7113 0.000 0.876 0.000 0.124 0.000
#> SRR1322747 3 0.3622 0.7281 0.000 0.172 0.804 0.016 0.008
#> SRR1432719 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 4 0.4221 0.6555 0.000 0.112 0.000 0.780 0.108
#> SRR1087511 4 0.3543 0.7165 0.060 0.112 0.000 0.828 0.000
#> SRR1470336 1 0.2077 0.7958 0.908 0.008 0.000 0.084 0.000
#> SRR1322536 4 0.4397 0.1708 0.432 0.004 0.000 0.564 0.000
#> SRR1100824 1 0.4648 0.1983 0.524 0.000 0.000 0.012 0.464
#> SRR1085951 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1322046 5 0.5059 0.5393 0.000 0.256 0.000 0.076 0.668
#> SRR1316420 1 0.3511 0.7319 0.800 0.004 0.000 0.012 0.184
#> SRR1070913 2 0.3427 0.6806 0.000 0.796 0.000 0.192 0.012
#> SRR1345806 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1313872 5 0.5455 0.4036 0.004 0.292 0.000 0.080 0.624
#> SRR1337666 5 0.2488 0.7551 0.000 0.124 0.000 0.004 0.872
#> SRR1076823 1 0.3730 0.5354 0.712 0.000 0.000 0.288 0.000
#> SRR1093954 4 0.4003 0.5775 0.000 0.288 0.000 0.704 0.008
#> SRR1451921 4 0.3651 0.6515 0.160 0.028 0.000 0.808 0.004
#> SRR1491257 1 0.4645 0.5497 0.672 0.016 0.000 0.012 0.300
#> SRR1416979 5 0.5334 0.5187 0.000 0.104 0.000 0.244 0.652
#> SRR1419015 1 0.3989 0.6732 0.728 0.008 0.004 0.260 0.000
#> SRR817649 5 0.0992 0.7804 0.000 0.024 0.000 0.008 0.968
#> SRR1466376 2 0.4514 0.6756 0.000 0.740 0.000 0.072 0.188
#> SRR1392055 2 0.2358 0.7228 0.000 0.888 0.000 0.104 0.008
#> SRR1120913 2 0.5474 0.4264 0.000 0.576 0.000 0.076 0.348
#> SRR1120869 5 0.5420 0.3961 0.000 0.076 0.000 0.332 0.592
#> SRR1319419 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR816495 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR818694 4 0.3048 0.7038 0.004 0.176 0.000 0.820 0.000
#> SRR1465653 5 0.2992 0.7396 0.092 0.024 0.000 0.012 0.872
#> SRR1475952 1 0.1768 0.8015 0.924 0.004 0.000 0.072 0.000
#> SRR1465040 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1088461 2 0.2036 0.7303 0.000 0.920 0.000 0.056 0.024
#> SRR810129 2 0.2616 0.7307 0.000 0.888 0.000 0.036 0.076
#> SRR1400141 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1349585 1 0.2909 0.7779 0.848 0.000 0.000 0.012 0.140
#> SRR1437576 2 0.1518 0.7434 0.000 0.952 0.016 0.012 0.020
#> SRR814407 1 0.2690 0.7449 0.844 0.000 0.000 0.156 0.000
#> SRR1332403 2 0.4850 0.6249 0.000 0.700 0.000 0.224 0.076
#> SRR1099598 4 0.3086 0.7084 0.004 0.180 0.000 0.816 0.000
#> SRR1327723 5 0.6215 0.2571 0.000 0.336 0.000 0.156 0.508
#> SRR1392525 3 0.2377 0.8267 0.000 0.000 0.872 0.128 0.000
#> SRR1320536 1 0.1270 0.8289 0.948 0.000 0.000 0.000 0.052
#> SRR1083824 5 0.6746 0.4111 0.000 0.116 0.308 0.044 0.532
#> SRR1351390 1 0.3274 0.6752 0.780 0.000 0.000 0.220 0.000
#> SRR1309141 2 0.4074 0.4426 0.000 0.636 0.364 0.000 0.000
#> SRR1452803 2 0.4866 0.3528 0.000 0.580 0.000 0.028 0.392
#> SRR811631 3 0.6381 0.3493 0.000 0.240 0.588 0.148 0.024
#> SRR1485563 2 0.4268 0.1206 0.000 0.556 0.000 0.444 0.000
#> SRR1311531 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1353076 4 0.3949 0.5096 0.000 0.300 0.000 0.696 0.004
#> SRR1480831 4 0.4756 0.6088 0.000 0.288 0.000 0.668 0.044
#> SRR1083892 5 0.2586 0.7448 0.084 0.012 0.000 0.012 0.892
#> SRR809873 4 0.3837 0.3668 0.308 0.000 0.000 0.692 0.000
#> SRR1341854 5 0.4036 0.6915 0.000 0.068 0.000 0.144 0.788
#> SRR1399335 2 0.2588 0.7282 0.000 0.892 0.000 0.060 0.048
#> SRR1464209 5 0.2522 0.7236 0.108 0.000 0.000 0.012 0.880
#> SRR1389886 2 0.1444 0.7433 0.000 0.948 0.000 0.040 0.012
#> SRR1400730 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1448008 4 0.4141 0.6717 0.000 0.248 0.000 0.728 0.024
#> SRR1087606 5 0.1894 0.7544 0.072 0.000 0.000 0.008 0.920
#> SRR1445111 1 0.1502 0.8289 0.940 0.000 0.000 0.004 0.056
#> SRR816865 4 0.2843 0.6810 0.000 0.144 0.000 0.848 0.008
#> SRR1323360 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1417364 3 0.0000 0.9665 0.000 0.000 1.000 0.000 0.000
#> SRR1480329 2 0.4555 0.6319 0.000 0.720 0.000 0.224 0.056
#> SRR1403322 4 0.4268 0.1060 0.444 0.000 0.000 0.556 0.000
#> SRR1093625 1 0.0000 0.8280 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.3532 0.7191 0.000 0.824 0.000 0.128 0.048
#> SRR1082035 2 0.3439 0.6729 0.008 0.800 0.000 0.188 0.004
#> SRR1393046 2 0.3670 0.6571 0.000 0.796 0.180 0.004 0.020
#> SRR1466663 2 0.5495 0.5639 0.104 0.672 0.000 0.012 0.212
#> SRR1384456 1 0.1908 0.8164 0.908 0.000 0.000 0.000 0.092
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.2056 0.64510 0.000 0.904 0.000 0.080 0.012 0.004
#> SRR808862 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1500382 2 0.1552 0.65603 0.000 0.940 0.000 0.036 0.004 0.020
#> SRR1322683 6 0.4565 0.38490 0.000 0.344 0.004 0.016 0.016 0.620
#> SRR1329811 5 0.1053 0.69255 0.020 0.004 0.000 0.000 0.964 0.012
#> SRR1087297 2 0.5546 0.41930 0.000 0.556 0.000 0.000 0.208 0.236
#> SRR1072626 6 0.3900 0.62329 0.000 0.136 0.000 0.056 0.020 0.788
#> SRR1407428 1 0.1010 0.71908 0.960 0.000 0.000 0.004 0.000 0.036
#> SRR1321029 2 0.1411 0.64950 0.000 0.936 0.000 0.000 0.004 0.060
#> SRR1500282 1 0.3620 0.63758 0.736 0.000 0.000 0.008 0.248 0.008
#> SRR1100496 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1308778 2 0.4699 0.59319 0.000 0.736 0.000 0.064 0.056 0.144
#> SRR1445304 2 0.1649 0.65782 0.000 0.932 0.000 0.032 0.000 0.036
#> SRR1099378 5 0.1894 0.68990 0.016 0.004 0.000 0.012 0.928 0.040
#> SRR1347412 1 0.1003 0.72553 0.964 0.000 0.020 0.000 0.016 0.000
#> SRR1099694 5 0.3962 0.65208 0.000 0.012 0.000 0.024 0.732 0.232
#> SRR1088365 4 0.2923 0.68424 0.000 0.100 0.000 0.848 0.000 0.052
#> SRR1325752 5 0.4889 0.63982 0.128 0.020 0.000 0.024 0.736 0.092
#> SRR1416713 2 0.6602 0.31500 0.000 0.500 0.000 0.076 0.152 0.272
#> SRR1074474 1 0.0622 0.72718 0.980 0.000 0.000 0.000 0.008 0.012
#> SRR1469369 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1400507 2 0.2558 0.60499 0.000 0.840 0.000 0.004 0.000 0.156
#> SRR1378179 5 0.4871 0.51204 0.000 0.016 0.000 0.040 0.592 0.352
#> SRR1377905 2 0.3996 0.62392 0.000 0.808 0.048 0.024 0.100 0.020
#> SRR1089479 1 0.2445 0.68902 0.868 0.000 0.000 0.008 0.004 0.120
#> SRR1073365 6 0.5553 0.22135 0.000 0.360 0.000 0.104 0.012 0.524
#> SRR1500306 1 0.5075 0.19471 0.464 0.000 0.000 0.076 0.000 0.460
#> SRR1101566 2 0.3468 0.46195 0.000 0.712 0.000 0.004 0.000 0.284
#> SRR1350503 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1446007 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1102875 4 0.4700 0.12342 0.000 0.044 0.000 0.500 0.000 0.456
#> SRR1380293 5 0.1938 0.69248 0.000 0.036 0.000 0.004 0.920 0.040
#> SRR1331198 5 0.5257 0.60989 0.000 0.112 0.000 0.020 0.644 0.224
#> SRR1092686 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.1871 0.70666 0.000 0.032 0.000 0.928 0.024 0.016
#> SRR1341650 4 0.3207 0.67947 0.004 0.036 0.084 0.856 0.008 0.012
#> SRR1357276 2 0.1871 0.65821 0.000 0.928 0.000 0.016 0.032 0.024
#> SRR1498374 2 0.1714 0.63716 0.000 0.908 0.000 0.000 0.000 0.092
#> SRR1093721 6 0.3677 0.61563 0.000 0.124 0.000 0.008 0.068 0.800
#> SRR1464660 5 0.1908 0.66224 0.056 0.000 0.000 0.000 0.916 0.028
#> SRR1402051 6 0.5278 0.54922 0.060 0.172 0.000 0.060 0.012 0.696
#> SRR1488734 2 0.5029 0.29156 0.000 0.568 0.000 0.016 0.048 0.368
#> SRR1082616 3 0.0458 0.92689 0.000 0.000 0.984 0.016 0.000 0.000
#> SRR1099427 2 0.3509 0.52514 0.000 0.744 0.240 0.000 0.000 0.016
#> SRR1453093 6 0.3201 0.58797 0.028 0.036 0.000 0.088 0.000 0.848
#> SRR1357064 1 0.5678 0.22741 0.468 0.040 0.000 0.012 0.444 0.036
#> SRR811237 4 0.3885 0.59556 0.000 0.044 0.000 0.736 0.000 0.220
#> SRR1100848 5 0.3804 0.56990 0.000 0.000 0.000 0.008 0.656 0.336
#> SRR1346755 2 0.3971 0.61805 0.000 0.772 0.000 0.012 0.156 0.060
#> SRR1472529 2 0.3955 0.15597 0.000 0.560 0.000 0.000 0.004 0.436
#> SRR1398905 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1082733 4 0.5935 -0.01880 0.000 0.300 0.000 0.456 0.000 0.244
#> SRR1308035 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 5 0.4118 0.35266 0.000 0.352 0.000 0.000 0.628 0.020
#> SRR1455825 6 0.5486 0.35579 0.000 0.296 0.000 0.020 0.100 0.584
#> SRR1389300 2 0.4378 0.52198 0.000 0.704 0.000 0.040 0.016 0.240
#> SRR812246 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.1737 0.71275 0.000 0.040 0.000 0.932 0.008 0.020
#> SRR1415567 1 0.0692 0.72370 0.976 0.000 0.000 0.004 0.000 0.020
#> SRR1331900 2 0.1957 0.63275 0.000 0.888 0.000 0.000 0.000 0.112
#> SRR1452099 5 0.2491 0.70758 0.000 0.000 0.000 0.020 0.868 0.112
#> SRR1352346 2 0.6622 0.23456 0.168 0.520 0.000 0.020 0.256 0.036
#> SRR1364034 4 0.2360 0.69130 0.000 0.044 0.000 0.900 0.012 0.044
#> SRR1086046 6 0.4767 0.36194 0.088 0.000 0.000 0.200 0.016 0.696
#> SRR1407226 1 0.5828 0.01732 0.464 0.020 0.000 0.440 0.040 0.036
#> SRR1319363 4 0.3488 0.59273 0.216 0.000 0.000 0.764 0.016 0.004
#> SRR1446961 3 0.0713 0.91365 0.000 0.028 0.972 0.000 0.000 0.000
#> SRR1486650 1 0.1082 0.72806 0.956 0.000 0.000 0.000 0.040 0.004
#> SRR1470152 5 0.1672 0.68188 0.048 0.000 0.000 0.004 0.932 0.016
#> SRR1454785 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 6 0.4134 0.34832 0.000 0.340 0.000 0.004 0.016 0.640
#> SRR1091476 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 6 0.3018 0.61114 0.000 0.168 0.000 0.012 0.004 0.816
#> SRR1366873 2 0.1863 0.63624 0.000 0.896 0.000 0.000 0.000 0.104
#> SRR1398114 2 0.3878 0.43919 0.000 0.668 0.000 0.320 0.008 0.004
#> SRR1089950 1 0.4417 0.35821 0.556 0.000 0.000 0.000 0.416 0.028
#> SRR1433272 5 0.4388 0.64619 0.044 0.064 0.000 0.052 0.796 0.044
#> SRR1075314 4 0.5887 0.17163 0.200 0.000 0.000 0.404 0.000 0.396
#> SRR1085590 3 0.3212 0.71371 0.000 0.000 0.800 0.016 0.004 0.180
#> SRR1100752 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 2 0.7529 0.27317 0.000 0.444 0.068 0.064 0.288 0.136
#> SRR1333263 3 0.2877 0.79546 0.000 0.020 0.848 0.124 0.008 0.000
#> SRR1310231 2 0.4595 0.44838 0.000 0.664 0.000 0.040 0.016 0.280
#> SRR1094144 4 0.1958 0.69825 0.000 0.000 0.000 0.896 0.004 0.100
#> SRR1092160 5 0.3550 0.67948 0.000 0.008 0.000 0.024 0.780 0.188
#> SRR1320300 2 0.2762 0.58797 0.000 0.804 0.000 0.000 0.000 0.196
#> SRR1322747 3 0.3377 0.72384 0.000 0.056 0.808 0.000 0.000 0.136
#> SRR1432719 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1100728 4 0.1321 0.71078 0.000 0.020 0.000 0.952 0.004 0.024
#> SRR1087511 6 0.4622 0.20869 0.032 0.016 0.000 0.316 0.000 0.636
#> SRR1470336 1 0.4002 0.50736 0.660 0.000 0.000 0.020 0.000 0.320
#> SRR1322536 6 0.5948 -0.10787 0.348 0.000 0.000 0.224 0.000 0.428
#> SRR1100824 1 0.5527 0.37894 0.512 0.000 0.000 0.088 0.384 0.016
#> SRR1085951 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1322046 5 0.5836 0.47760 0.000 0.108 0.000 0.032 0.544 0.316
#> SRR1316420 1 0.4056 0.64308 0.748 0.012 0.000 0.004 0.204 0.032
#> SRR1070913 2 0.3998 0.02849 0.000 0.504 0.000 0.004 0.000 0.492
#> SRR1345806 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 5 0.6460 0.28847 0.004 0.180 0.000 0.028 0.448 0.340
#> SRR1337666 5 0.3448 0.69601 0.000 0.108 0.000 0.004 0.816 0.072
#> SRR1076823 1 0.4212 0.54758 0.688 0.000 0.000 0.048 0.000 0.264
#> SRR1093954 4 0.3876 0.62819 0.000 0.108 0.000 0.772 0.000 0.120
#> SRR1451921 6 0.3307 0.51049 0.044 0.000 0.000 0.148 0.000 0.808
#> SRR1491257 1 0.5423 0.45338 0.576 0.048 0.000 0.004 0.336 0.036
#> SRR1416979 5 0.4620 0.43037 0.000 0.004 0.000 0.032 0.544 0.420
#> SRR1419015 4 0.3605 0.58608 0.224 0.004 0.008 0.756 0.000 0.008
#> SRR817649 5 0.1204 0.70586 0.000 0.000 0.000 0.000 0.944 0.056
#> SRR1466376 2 0.5241 0.40672 0.000 0.616 0.000 0.036 0.056 0.292
#> SRR1392055 2 0.2442 0.61606 0.000 0.852 0.000 0.004 0.000 0.144
#> SRR1120913 5 0.6618 0.17663 0.000 0.304 0.000 0.028 0.388 0.280
#> SRR1120869 5 0.5664 0.51387 0.000 0.008 0.000 0.188 0.568 0.236
#> SRR1319419 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR816495 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR818694 6 0.3703 0.59179 0.004 0.072 0.000 0.132 0.000 0.792
#> SRR1465653 5 0.4177 0.55144 0.140 0.052 0.000 0.000 0.772 0.036
#> SRR1475952 1 0.3345 0.62502 0.776 0.000 0.000 0.020 0.000 0.204
#> SRR1465040 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 2 0.2006 0.64215 0.000 0.892 0.000 0.104 0.000 0.004
#> SRR810129 2 0.2790 0.63628 0.000 0.872 0.000 0.080 0.020 0.028
#> SRR1400141 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 1 0.2491 0.69105 0.836 0.000 0.000 0.000 0.164 0.000
#> SRR1437576 2 0.1867 0.65417 0.000 0.916 0.020 0.000 0.000 0.064
#> SRR814407 1 0.4027 0.63381 0.776 0.000 0.004 0.112 0.004 0.104
#> SRR1332403 2 0.6337 0.24161 0.000 0.440 0.000 0.264 0.016 0.280
#> SRR1099598 6 0.5372 -0.01951 0.004 0.096 0.000 0.412 0.000 0.488
#> SRR1327723 6 0.6731 -0.00986 0.000 0.248 0.000 0.044 0.288 0.420
#> SRR1392525 3 0.0405 0.93019 0.000 0.000 0.988 0.008 0.000 0.004
#> SRR1320536 1 0.1007 0.72717 0.956 0.000 0.000 0.000 0.044 0.000
#> SRR1083824 3 0.6936 -0.22935 0.000 0.052 0.352 0.000 0.300 0.296
#> SRR1351390 1 0.5624 0.39950 0.544 0.000 0.000 0.124 0.012 0.320
#> SRR1309141 2 0.3861 0.43723 0.000 0.672 0.316 0.000 0.004 0.008
#> SRR1452803 2 0.6182 0.17347 0.000 0.492 0.000 0.040 0.340 0.128
#> SRR811631 3 0.5254 0.24153 0.000 0.100 0.564 0.000 0.004 0.332
#> SRR1485563 2 0.5942 0.00493 0.000 0.444 0.000 0.324 0.000 0.232
#> SRR1311531 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.4545 0.52241 0.000 0.192 0.000 0.696 0.000 0.112
#> SRR1480831 6 0.5055 0.53781 0.000 0.168 0.000 0.140 0.016 0.676
#> SRR1083892 5 0.4320 0.58799 0.120 0.036 0.000 0.024 0.784 0.036
#> SRR809873 4 0.3088 0.67299 0.048 0.000 0.000 0.832 0.000 0.120
#> SRR1341854 5 0.5271 0.49757 0.000 0.040 0.000 0.040 0.572 0.348
#> SRR1399335 2 0.3474 0.62013 0.008 0.836 0.000 0.096 0.024 0.036
#> SRR1464209 5 0.3183 0.55429 0.164 0.000 0.000 0.008 0.812 0.016
#> SRR1389886 2 0.2871 0.58260 0.000 0.804 0.000 0.004 0.000 0.192
#> SRR1400730 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1448008 6 0.3300 0.60937 0.008 0.080 0.000 0.060 0.008 0.844
#> SRR1087606 5 0.0862 0.69175 0.008 0.004 0.000 0.000 0.972 0.016
#> SRR1445111 1 0.2398 0.72703 0.888 0.000 0.000 0.004 0.080 0.028
#> SRR816865 4 0.1245 0.71083 0.000 0.032 0.000 0.952 0.000 0.016
#> SRR1323360 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.0000 0.93936 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1480329 6 0.4276 0.46126 0.000 0.304 0.000 0.016 0.016 0.664
#> SRR1403322 4 0.6085 0.16275 0.288 0.000 0.000 0.392 0.000 0.320
#> SRR1093625 1 0.0692 0.72576 0.976 0.000 0.000 0.000 0.004 0.020
#> SRR1479977 2 0.4935 0.28027 0.000 0.556 0.000 0.012 0.044 0.388
#> SRR1082035 2 0.5425 0.50560 0.056 0.676 0.000 0.200 0.020 0.048
#> SRR1393046 2 0.3837 0.60776 0.000 0.784 0.140 0.000 0.008 0.068
#> SRR1466663 2 0.6152 0.43346 0.212 0.612 0.000 0.028 0.104 0.044
#> SRR1384456 1 0.1584 0.72673 0.928 0.000 0.000 0.000 0.064 0.008
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "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 17467 rows and 159 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 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 0.601 0.847 0.916 0.293 0.662 0.662
#> 3 3 0.658 0.783 0.900 0.274 0.955 0.932
#> 4 4 0.589 0.781 0.876 0.188 0.994 0.991
#> 5 5 0.525 0.749 0.828 0.156 0.993 0.989
#> 6 6 0.433 0.460 0.743 0.145 0.932 0.889
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
#> SRR810713 2 0.0000 0.951 0.000 1.000
#> SRR808862 2 0.6712 0.727 0.176 0.824
#> SRR1500382 2 0.0000 0.951 0.000 1.000
#> SRR1322683 2 0.0000 0.951 0.000 1.000
#> SRR1329811 1 0.8555 0.742 0.720 0.280
#> SRR1087297 2 0.0000 0.951 0.000 1.000
#> SRR1072626 2 0.0672 0.947 0.008 0.992
#> SRR1407428 1 0.0000 0.705 1.000 0.000
#> SRR1321029 2 0.0000 0.951 0.000 1.000
#> SRR1500282 1 0.9044 0.726 0.680 0.320
#> SRR1100496 2 0.5842 0.790 0.140 0.860
#> SRR1308778 2 0.1184 0.939 0.016 0.984
#> SRR1445304 2 0.0000 0.951 0.000 1.000
#> SRR1099378 2 0.5178 0.830 0.116 0.884
#> SRR1347412 1 0.2423 0.712 0.960 0.040
#> SRR1099694 2 0.0000 0.951 0.000 1.000
#> SRR1088365 2 0.0000 0.951 0.000 1.000
#> SRR1325752 2 0.2603 0.920 0.044 0.956
#> SRR1416713 2 0.0000 0.951 0.000 1.000
#> SRR1074474 1 0.0000 0.705 1.000 0.000
#> SRR1469369 2 0.0000 0.951 0.000 1.000
#> SRR1400507 2 0.0000 0.951 0.000 1.000
#> SRR1378179 2 0.0000 0.951 0.000 1.000
#> SRR1377905 2 0.0000 0.951 0.000 1.000
#> SRR1089479 1 0.8861 0.731 0.696 0.304
#> SRR1073365 2 0.0000 0.951 0.000 1.000
#> SRR1500306 1 0.9795 0.627 0.584 0.416
#> SRR1101566 2 0.0000 0.951 0.000 1.000
#> SRR1350503 2 0.0000 0.951 0.000 1.000
#> SRR1446007 2 0.0000 0.951 0.000 1.000
#> SRR1102875 2 0.0000 0.951 0.000 1.000
#> SRR1380293 2 0.0000 0.951 0.000 1.000
#> SRR1331198 2 0.0000 0.951 0.000 1.000
#> SRR1092686 2 0.0938 0.944 0.012 0.988
#> SRR1069421 2 0.1843 0.931 0.028 0.972
#> SRR1341650 2 0.4939 0.836 0.108 0.892
#> SRR1357276 2 0.0000 0.951 0.000 1.000
#> SRR1498374 2 0.0000 0.951 0.000 1.000
#> SRR1093721 2 0.0000 0.951 0.000 1.000
#> SRR1464660 1 0.8555 0.742 0.720 0.280
#> SRR1402051 2 0.1843 0.932 0.028 0.972
#> SRR1488734 2 0.0000 0.951 0.000 1.000
#> SRR1082616 2 0.7376 0.642 0.208 0.792
#> SRR1099427 2 0.0000 0.951 0.000 1.000
#> SRR1453093 2 0.3274 0.895 0.060 0.940
#> SRR1357064 1 0.9881 0.592 0.564 0.436
#> SRR811237 2 0.0672 0.947 0.008 0.992
#> SRR1100848 2 0.0000 0.951 0.000 1.000
#> SRR1346755 2 0.0938 0.944 0.012 0.988
#> SRR1472529 2 0.0000 0.951 0.000 1.000
#> SRR1398905 1 0.8955 0.728 0.688 0.312
#> SRR1082733 2 0.0000 0.951 0.000 1.000
#> SRR1308035 2 0.0000 0.951 0.000 1.000
#> SRR1466445 2 0.0376 0.949 0.004 0.996
#> SRR1359080 2 0.0000 0.951 0.000 1.000
#> SRR1455825 2 0.0000 0.951 0.000 1.000
#> SRR1389300 2 0.0000 0.951 0.000 1.000
#> SRR812246 2 0.0672 0.946 0.008 0.992
#> SRR1076632 2 0.0672 0.947 0.008 0.992
#> SRR1415567 1 0.0000 0.705 1.000 0.000
#> SRR1331900 2 0.0000 0.951 0.000 1.000
#> SRR1452099 2 0.3274 0.902 0.060 0.940
#> SRR1352346 1 0.5059 0.713 0.888 0.112
#> SRR1364034 2 0.0000 0.951 0.000 1.000
#> SRR1086046 2 0.4161 0.869 0.084 0.916
#> SRR1407226 1 0.9954 0.542 0.540 0.460
#> SRR1319363 1 0.9983 0.501 0.524 0.476
#> SRR1446961 2 0.0000 0.951 0.000 1.000
#> SRR1486650 1 0.0000 0.705 1.000 0.000
#> SRR1470152 1 0.8555 0.742 0.720 0.280
#> SRR1454785 2 0.0000 0.951 0.000 1.000
#> SRR1092329 2 0.0000 0.951 0.000 1.000
#> SRR1091476 2 0.3584 0.890 0.068 0.932
#> SRR1073775 2 0.0000 0.951 0.000 1.000
#> SRR1366873 2 0.0000 0.951 0.000 1.000
#> SRR1398114 2 0.0000 0.951 0.000 1.000
#> SRR1089950 2 0.6973 0.697 0.188 0.812
#> SRR1433272 2 0.4431 0.860 0.092 0.908
#> SRR1075314 1 0.9850 0.606 0.572 0.428
#> SRR1085590 2 0.0672 0.947 0.008 0.992
#> SRR1100752 2 0.0938 0.944 0.012 0.988
#> SRR1391494 2 0.0000 0.951 0.000 1.000
#> SRR1333263 2 0.4690 0.848 0.100 0.900
#> SRR1310231 2 0.0000 0.951 0.000 1.000
#> SRR1094144 2 0.1414 0.939 0.020 0.980
#> SRR1092160 2 0.0000 0.951 0.000 1.000
#> SRR1320300 2 0.0000 0.951 0.000 1.000
#> SRR1322747 2 0.0000 0.951 0.000 1.000
#> SRR1432719 2 0.0376 0.949 0.004 0.996
#> SRR1100728 2 0.1843 0.931 0.028 0.972
#> SRR1087511 2 0.0000 0.951 0.000 1.000
#> SRR1470336 1 0.9795 0.627 0.584 0.416
#> SRR1322536 1 0.9850 0.606 0.572 0.428
#> SRR1100824 1 0.9954 0.542 0.540 0.460
#> SRR1085951 2 0.5842 0.790 0.140 0.860
#> SRR1322046 2 0.0000 0.951 0.000 1.000
#> SRR1316420 2 0.9970 -0.352 0.468 0.532
#> SRR1070913 2 0.0000 0.951 0.000 1.000
#> SRR1345806 2 0.0376 0.949 0.004 0.996
#> SRR1313872 2 0.0000 0.951 0.000 1.000
#> SRR1337666 2 0.0000 0.951 0.000 1.000
#> SRR1076823 2 0.9977 -0.371 0.472 0.528
#> SRR1093954 2 0.0000 0.951 0.000 1.000
#> SRR1451921 2 0.8081 0.541 0.248 0.752
#> SRR1491257 1 0.9909 0.575 0.556 0.444
#> SRR1416979 2 0.0000 0.951 0.000 1.000
#> SRR1419015 2 0.6623 0.728 0.172 0.828
#> SRR817649 2 0.0376 0.949 0.004 0.996
#> SRR1466376 2 0.0000 0.951 0.000 1.000
#> SRR1392055 2 0.0000 0.951 0.000 1.000
#> SRR1120913 2 0.0000 0.951 0.000 1.000
#> SRR1120869 2 0.0672 0.947 0.008 0.992
#> SRR1319419 2 0.0376 0.949 0.004 0.996
#> SRR816495 2 0.0000 0.951 0.000 1.000
#> SRR818694 2 0.0000 0.951 0.000 1.000
#> SRR1465653 1 0.8555 0.742 0.720 0.280
#> SRR1475952 1 0.1414 0.709 0.980 0.020
#> SRR1465040 2 0.0000 0.951 0.000 1.000
#> SRR1088461 2 0.0000 0.951 0.000 1.000
#> SRR810129 2 0.0000 0.951 0.000 1.000
#> SRR1400141 2 0.0938 0.944 0.012 0.988
#> SRR1349585 1 0.9909 0.575 0.556 0.444
#> SRR1437576 2 0.0000 0.951 0.000 1.000
#> SRR814407 1 0.8909 0.730 0.692 0.308
#> SRR1332403 2 0.0000 0.951 0.000 1.000
#> SRR1099598 2 0.0376 0.949 0.004 0.996
#> SRR1327723 2 0.0000 0.951 0.000 1.000
#> SRR1392525 2 0.7219 0.660 0.200 0.800
#> SRR1320536 1 0.0000 0.705 1.000 0.000
#> SRR1083824 2 0.0000 0.951 0.000 1.000
#> SRR1351390 2 0.6438 0.743 0.164 0.836
#> SRR1309141 2 0.4690 0.848 0.100 0.900
#> SRR1452803 2 0.0000 0.951 0.000 1.000
#> SRR811631 2 0.0000 0.951 0.000 1.000
#> SRR1485563 2 0.3114 0.906 0.056 0.944
#> SRR1311531 2 0.0000 0.951 0.000 1.000
#> SRR1353076 2 0.0376 0.949 0.004 0.996
#> SRR1480831 2 0.3431 0.891 0.064 0.936
#> SRR1083892 1 0.9881 0.592 0.564 0.436
#> SRR809873 1 0.9983 0.501 0.524 0.476
#> SRR1341854 2 0.0000 0.951 0.000 1.000
#> SRR1399335 2 0.0000 0.951 0.000 1.000
#> SRR1464209 1 0.9881 0.592 0.564 0.436
#> SRR1389886 2 0.0000 0.951 0.000 1.000
#> SRR1400730 1 0.8327 0.743 0.736 0.264
#> SRR1448008 2 0.3274 0.895 0.060 0.940
#> SRR1087606 2 0.6623 0.729 0.172 0.828
#> SRR1445111 1 0.0000 0.705 1.000 0.000
#> SRR816865 2 0.1843 0.931 0.028 0.972
#> SRR1323360 2 0.0000 0.951 0.000 1.000
#> SRR1417364 2 0.0000 0.951 0.000 1.000
#> SRR1480329 2 0.0000 0.951 0.000 1.000
#> SRR1403322 1 0.9248 0.692 0.660 0.340
#> SRR1093625 1 0.0000 0.705 1.000 0.000
#> SRR1479977 2 0.0000 0.951 0.000 1.000
#> SRR1082035 2 0.8386 0.519 0.268 0.732
#> SRR1393046 2 0.0000 0.951 0.000 1.000
#> SRR1466663 2 0.5178 0.827 0.116 0.884
#> SRR1384456 1 0.0000 0.705 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.0000 0.953 0.000 1.000 0.000
#> SRR808862 2 0.5407 0.762 0.104 0.820 0.076
#> SRR1500382 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1322683 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1329811 3 0.1315 0.547 0.020 0.008 0.972
#> SRR1087297 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1072626 2 0.0475 0.950 0.004 0.992 0.004
#> SRR1407428 1 0.4702 0.318 0.788 0.000 0.212
#> SRR1321029 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1500282 3 0.6027 0.503 0.164 0.060 0.776
#> SRR1100496 2 0.4749 0.812 0.076 0.852 0.072
#> SRR1308778 2 0.1453 0.936 0.008 0.968 0.024
#> SRR1445304 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1099378 2 0.4873 0.774 0.024 0.824 0.152
#> SRR1347412 3 0.5835 0.276 0.340 0.000 0.660
#> SRR1099694 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1088365 2 0.0475 0.951 0.004 0.992 0.004
#> SRR1325752 2 0.2663 0.910 0.024 0.932 0.044
#> SRR1416713 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1074474 1 0.5058 0.315 0.756 0.000 0.244
#> SRR1469369 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1400507 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1378179 2 0.0661 0.949 0.004 0.988 0.008
#> SRR1377905 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1089479 3 0.6633 0.470 0.212 0.060 0.728
#> SRR1073365 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1500306 1 0.8473 0.173 0.616 0.176 0.208
#> SRR1101566 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1350503 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1446007 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1102875 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1380293 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1331198 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1092686 2 0.0661 0.948 0.004 0.988 0.008
#> SRR1069421 2 0.1774 0.930 0.016 0.960 0.024
#> SRR1341650 2 0.5481 0.764 0.076 0.816 0.108
#> SRR1357276 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1498374 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1093721 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1464660 3 0.1315 0.547 0.020 0.008 0.972
#> SRR1402051 2 0.1482 0.936 0.012 0.968 0.020
#> SRR1488734 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1082616 2 0.5461 0.667 0.216 0.768 0.016
#> SRR1099427 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1453093 2 0.2165 0.902 0.064 0.936 0.000
#> SRR1357064 3 0.8309 0.477 0.188 0.180 0.632
#> SRR811237 2 0.0475 0.950 0.004 0.992 0.004
#> SRR1100848 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1346755 2 0.0661 0.948 0.004 0.988 0.008
#> SRR1472529 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1398905 3 0.6495 0.484 0.200 0.060 0.740
#> SRR1082733 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1308035 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1466445 2 0.0237 0.951 0.004 0.996 0.000
#> SRR1359080 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.953 0.000 1.000 0.000
#> SRR812246 2 0.0424 0.950 0.000 0.992 0.008
#> SRR1076632 2 0.1015 0.944 0.008 0.980 0.012
#> SRR1415567 1 0.4702 0.318 0.788 0.000 0.212
#> SRR1331900 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1452099 2 0.2636 0.906 0.020 0.932 0.048
#> SRR1352346 1 0.7745 0.210 0.648 0.092 0.260
#> SRR1364034 2 0.0661 0.949 0.004 0.988 0.008
#> SRR1086046 2 0.3183 0.880 0.076 0.908 0.016
#> SRR1407226 3 0.9206 0.291 0.188 0.288 0.524
#> SRR1319363 1 0.7379 0.282 0.584 0.376 0.040
#> SRR1446961 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1486650 1 0.5058 0.315 0.756 0.000 0.244
#> SRR1470152 3 0.1315 0.547 0.020 0.008 0.972
#> SRR1454785 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1092329 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1091476 2 0.3112 0.866 0.004 0.900 0.096
#> SRR1073775 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1398114 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1089950 2 0.7279 0.226 0.036 0.588 0.376
#> SRR1433272 2 0.4485 0.802 0.020 0.844 0.136
#> SRR1075314 1 0.6758 0.310 0.620 0.360 0.020
#> SRR1085590 2 0.0475 0.950 0.004 0.992 0.004
#> SRR1100752 2 0.0661 0.948 0.004 0.988 0.008
#> SRR1391494 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1333263 2 0.4179 0.846 0.072 0.876 0.052
#> SRR1310231 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1094144 2 0.1491 0.937 0.016 0.968 0.016
#> SRR1092160 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1320300 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1322747 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1432719 2 0.0237 0.951 0.004 0.996 0.000
#> SRR1100728 2 0.1774 0.930 0.016 0.960 0.024
#> SRR1087511 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1470336 1 0.8473 0.173 0.616 0.176 0.208
#> SRR1322536 1 0.6758 0.310 0.620 0.360 0.020
#> SRR1100824 3 0.9206 0.291 0.188 0.288 0.524
#> SRR1085951 2 0.4749 0.812 0.076 0.852 0.072
#> SRR1322046 2 0.0475 0.950 0.004 0.992 0.004
#> SRR1316420 3 0.8743 0.365 0.156 0.268 0.576
#> SRR1070913 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1345806 2 0.0237 0.951 0.004 0.996 0.000
#> SRR1313872 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1337666 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1076823 1 0.7174 0.212 0.516 0.460 0.024
#> SRR1093954 2 0.0475 0.951 0.004 0.992 0.004
#> SRR1451921 2 0.5618 0.597 0.260 0.732 0.008
#> SRR1491257 3 0.8542 0.430 0.172 0.220 0.608
#> SRR1416979 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1419015 2 0.5947 0.696 0.172 0.776 0.052
#> SRR817649 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1466376 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1120913 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1120869 2 0.0829 0.946 0.004 0.984 0.012
#> SRR1319419 2 0.0237 0.951 0.004 0.996 0.000
#> SRR816495 2 0.0000 0.953 0.000 1.000 0.000
#> SRR818694 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1465653 3 0.1315 0.547 0.020 0.008 0.972
#> SRR1475952 1 0.2796 0.313 0.908 0.000 0.092
#> SRR1465040 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1088461 2 0.0237 0.952 0.004 0.996 0.000
#> SRR810129 2 0.0237 0.952 0.004 0.996 0.000
#> SRR1400141 2 0.0661 0.948 0.004 0.988 0.008
#> SRR1349585 3 0.8542 0.430 0.172 0.220 0.608
#> SRR1437576 2 0.0000 0.953 0.000 1.000 0.000
#> SRR814407 3 0.6447 0.486 0.196 0.060 0.744
#> SRR1332403 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1099598 2 0.0475 0.951 0.004 0.992 0.004
#> SRR1327723 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1392525 2 0.5318 0.689 0.204 0.780 0.016
#> SRR1320536 1 0.5058 0.315 0.756 0.000 0.244
#> SRR1083824 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1351390 2 0.6796 0.298 0.020 0.612 0.368
#> SRR1309141 2 0.4179 0.846 0.072 0.876 0.052
#> SRR1452803 2 0.0237 0.952 0.004 0.996 0.000
#> SRR811631 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1485563 2 0.2926 0.901 0.040 0.924 0.036
#> SRR1311531 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1353076 2 0.0475 0.951 0.004 0.992 0.004
#> SRR1480831 2 0.2749 0.895 0.064 0.924 0.012
#> SRR1083892 3 0.8309 0.477 0.188 0.180 0.632
#> SRR809873 1 0.7379 0.282 0.584 0.376 0.040
#> SRR1341854 2 0.0475 0.950 0.004 0.992 0.004
#> SRR1399335 2 0.0475 0.951 0.004 0.992 0.004
#> SRR1464209 3 0.8309 0.477 0.188 0.180 0.632
#> SRR1389886 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1400730 3 0.1163 0.539 0.028 0.000 0.972
#> SRR1448008 2 0.2165 0.902 0.064 0.936 0.000
#> SRR1087606 2 0.6721 0.271 0.016 0.604 0.380
#> SRR1445111 3 0.6235 0.165 0.436 0.000 0.564
#> SRR816865 2 0.1774 0.930 0.016 0.960 0.024
#> SRR1323360 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1417364 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1480329 2 0.0237 0.952 0.000 0.996 0.004
#> SRR1403322 1 0.5919 0.317 0.724 0.260 0.016
#> SRR1093625 1 0.5058 0.315 0.756 0.000 0.244
#> SRR1479977 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1082035 2 0.8138 0.400 0.204 0.644 0.152
#> SRR1393046 2 0.0000 0.953 0.000 1.000 0.000
#> SRR1466663 2 0.4565 0.828 0.076 0.860 0.064
#> SRR1384456 1 0.5058 0.315 0.756 0.000 0.244
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0376 0.9140 0.004 0.992 0.004 0.000
#> SRR808862 2 0.5881 0.6777 0.056 0.732 0.176 0.036
#> SRR1500382 2 0.1004 0.9120 0.000 0.972 0.024 0.004
#> SRR1322683 2 0.0707 0.9119 0.000 0.980 0.020 0.000
#> SRR1329811 1 0.1151 0.5626 0.968 0.000 0.024 0.008
#> SRR1087297 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1072626 2 0.1474 0.9062 0.000 0.948 0.052 0.000
#> SRR1407428 4 0.1302 0.8783 0.000 0.000 0.044 0.956
#> SRR1321029 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1500282 1 0.4502 0.4584 0.748 0.000 0.236 0.016
#> SRR1100496 2 0.5325 0.7140 0.048 0.744 0.196 0.012
#> SRR1308778 2 0.2797 0.8856 0.028 0.908 0.056 0.008
#> SRR1445304 2 0.1109 0.9109 0.000 0.968 0.028 0.004
#> SRR1099378 2 0.5944 0.6452 0.140 0.696 0.164 0.000
#> SRR1347412 1 0.5600 0.0877 0.596 0.000 0.028 0.376
#> SRR1099694 2 0.0657 0.9138 0.004 0.984 0.012 0.000
#> SRR1088365 2 0.2310 0.8888 0.008 0.920 0.068 0.004
#> SRR1325752 2 0.4502 0.8032 0.036 0.808 0.144 0.012
#> SRR1416713 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> SRR1074474 4 0.0188 0.8973 0.004 0.000 0.000 0.996
#> SRR1469369 2 0.0707 0.9119 0.000 0.980 0.020 0.000
#> SRR1400507 2 0.0336 0.9136 0.000 0.992 0.008 0.000
#> SRR1378179 2 0.1256 0.9099 0.008 0.964 0.028 0.000
#> SRR1377905 2 0.0188 0.9141 0.000 0.996 0.004 0.000
#> SRR1089479 1 0.5550 0.4046 0.692 0.000 0.248 0.060
#> SRR1073365 2 0.1762 0.9008 0.004 0.944 0.048 0.004
#> SRR1500306 3 0.8009 0.6661 0.168 0.088 0.592 0.152
#> SRR1101566 2 0.0779 0.9129 0.004 0.980 0.016 0.000
#> SRR1350503 2 0.0592 0.9135 0.000 0.984 0.016 0.000
#> SRR1446007 2 0.0469 0.9136 0.000 0.988 0.012 0.000
#> SRR1102875 2 0.1762 0.9008 0.004 0.944 0.048 0.004
#> SRR1380293 2 0.0469 0.9146 0.000 0.988 0.012 0.000
#> SRR1331198 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1092686 2 0.1474 0.9069 0.000 0.948 0.052 0.000
#> SRR1069421 2 0.3575 0.8421 0.020 0.852 0.124 0.004
#> SRR1341650 2 0.6460 0.6153 0.092 0.680 0.204 0.024
#> SRR1357276 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1498374 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1093721 2 0.0779 0.9147 0.004 0.980 0.016 0.000
#> SRR1464660 1 0.1151 0.5626 0.968 0.000 0.024 0.008
#> SRR1402051 2 0.2799 0.8684 0.008 0.884 0.108 0.000
#> SRR1488734 2 0.1004 0.9120 0.000 0.972 0.024 0.004
#> SRR1082616 2 0.6216 0.3072 0.008 0.576 0.372 0.044
#> SRR1099427 2 0.0707 0.9119 0.000 0.980 0.020 0.000
#> SRR1453093 2 0.3356 0.7891 0.000 0.824 0.176 0.000
#> SRR1357064 1 0.7940 0.4824 0.600 0.108 0.112 0.180
#> SRR811237 2 0.1474 0.9062 0.000 0.948 0.052 0.000
#> SRR1100848 2 0.0657 0.9146 0.004 0.984 0.012 0.000
#> SRR1346755 2 0.1022 0.9102 0.000 0.968 0.032 0.000
#> SRR1472529 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1398905 1 0.4831 0.4276 0.704 0.000 0.280 0.016
#> SRR1082733 2 0.0188 0.9143 0.000 0.996 0.004 0.000
#> SRR1308035 2 0.0707 0.9138 0.000 0.980 0.020 0.000
#> SRR1466445 2 0.0592 0.9141 0.000 0.984 0.016 0.000
#> SRR1359080 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1455825 2 0.0188 0.9135 0.000 0.996 0.004 0.000
#> SRR1389300 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR812246 2 0.1256 0.9134 0.008 0.964 0.028 0.000
#> SRR1076632 2 0.3113 0.8605 0.012 0.876 0.108 0.004
#> SRR1415567 4 0.1389 0.8759 0.000 0.000 0.048 0.952
#> SRR1331900 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1452099 2 0.4088 0.8204 0.040 0.820 0.140 0.000
#> SRR1352346 4 0.5151 0.6601 0.048 0.064 0.088 0.800
#> SRR1364034 2 0.1890 0.8983 0.008 0.936 0.056 0.000
#> SRR1086046 2 0.4234 0.7295 0.004 0.764 0.228 0.004
#> SRR1407226 1 0.9254 0.3312 0.460 0.176 0.188 0.176
#> SRR1319363 3 0.5340 0.7411 0.004 0.104 0.756 0.136
#> SRR1446961 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1486650 4 0.0188 0.8973 0.004 0.000 0.000 0.996
#> SRR1470152 1 0.1151 0.5626 0.968 0.000 0.024 0.008
#> SRR1454785 2 0.0707 0.9138 0.000 0.980 0.020 0.000
#> SRR1092329 2 0.0921 0.9087 0.000 0.972 0.028 0.000
#> SRR1091476 2 0.3421 0.8403 0.088 0.868 0.044 0.000
#> SRR1073775 2 0.1302 0.9037 0.000 0.956 0.044 0.000
#> SRR1366873 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1398114 2 0.1209 0.9096 0.000 0.964 0.032 0.004
#> SRR1089950 2 0.7343 0.1505 0.356 0.512 0.120 0.012
#> SRR1433272 2 0.5848 0.6770 0.128 0.716 0.152 0.004
#> SRR1075314 3 0.5462 0.7384 0.000 0.112 0.736 0.152
#> SRR1085590 2 0.1557 0.9041 0.000 0.944 0.056 0.000
#> SRR1100752 2 0.1302 0.9079 0.000 0.956 0.044 0.000
#> SRR1391494 2 0.0469 0.9136 0.000 0.988 0.012 0.000
#> SRR1333263 2 0.5518 0.7288 0.056 0.752 0.168 0.024
#> SRR1310231 2 0.0188 0.9143 0.000 0.996 0.004 0.000
#> SRR1094144 2 0.3375 0.8531 0.012 0.864 0.116 0.008
#> SRR1092160 2 0.0657 0.9138 0.004 0.984 0.012 0.000
#> SRR1320300 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1322747 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1432719 2 0.0817 0.9148 0.000 0.976 0.024 0.000
#> SRR1100728 2 0.3575 0.8421 0.020 0.852 0.124 0.004
#> SRR1087511 2 0.0895 0.9128 0.004 0.976 0.020 0.000
#> SRR1470336 3 0.8009 0.6661 0.168 0.088 0.592 0.152
#> SRR1322536 3 0.5462 0.7384 0.000 0.112 0.736 0.152
#> SRR1100824 1 0.9254 0.3312 0.460 0.176 0.188 0.176
#> SRR1085951 2 0.5363 0.7095 0.048 0.740 0.200 0.012
#> SRR1322046 2 0.1004 0.9116 0.004 0.972 0.024 0.000
#> SRR1316420 1 0.8764 0.3445 0.520 0.192 0.140 0.148
#> SRR1070913 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1345806 2 0.0592 0.9141 0.000 0.984 0.016 0.000
#> SRR1313872 2 0.0336 0.9146 0.000 0.992 0.008 0.000
#> SRR1337666 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1076823 3 0.6216 0.6179 0.004 0.188 0.680 0.128
#> SRR1093954 2 0.2310 0.8888 0.008 0.920 0.068 0.004
#> SRR1451921 2 0.5923 0.3125 0.000 0.580 0.376 0.044
#> SRR1491257 1 0.8382 0.4373 0.560 0.152 0.112 0.176
#> SRR1416979 2 0.1022 0.9092 0.000 0.968 0.032 0.000
#> SRR1419015 2 0.6847 0.2335 0.032 0.536 0.388 0.044
#> SRR817649 2 0.0592 0.9149 0.000 0.984 0.016 0.000
#> SRR1466376 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1392055 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1120913 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1120869 2 0.2926 0.8691 0.012 0.888 0.096 0.004
#> SRR1319419 2 0.0592 0.9141 0.000 0.984 0.016 0.000
#> SRR816495 2 0.0817 0.9139 0.000 0.976 0.024 0.000
#> SRR818694 2 0.1302 0.9037 0.000 0.956 0.044 0.000
#> SRR1465653 1 0.1151 0.5626 0.968 0.000 0.024 0.008
#> SRR1475952 4 0.4761 0.3553 0.000 0.000 0.372 0.628
#> SRR1465040 2 0.0707 0.9138 0.000 0.980 0.020 0.000
#> SRR1088461 2 0.1847 0.9024 0.004 0.940 0.052 0.004
#> SRR810129 2 0.1209 0.9096 0.000 0.964 0.032 0.004
#> SRR1400141 2 0.1474 0.9069 0.000 0.948 0.052 0.000
#> SRR1349585 1 0.8382 0.4373 0.560 0.152 0.112 0.176
#> SRR1437576 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR814407 1 0.4898 0.4351 0.716 0.000 0.260 0.024
#> SRR1332403 2 0.0188 0.9143 0.000 0.996 0.004 0.000
#> SRR1099598 2 0.1389 0.9083 0.000 0.952 0.048 0.000
#> SRR1327723 2 0.0188 0.9136 0.000 0.996 0.004 0.000
#> SRR1392525 2 0.5988 0.4641 0.008 0.632 0.316 0.044
#> SRR1320536 4 0.0188 0.8973 0.004 0.000 0.000 0.996
#> SRR1083824 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1351390 2 0.7138 0.2252 0.340 0.536 0.116 0.008
#> SRR1309141 2 0.5518 0.7288 0.056 0.752 0.168 0.024
#> SRR1452803 2 0.1109 0.9109 0.000 0.968 0.028 0.004
#> SRR811631 2 0.0592 0.9127 0.000 0.984 0.016 0.000
#> SRR1485563 2 0.4413 0.8061 0.028 0.808 0.152 0.012
#> SRR1311531 2 0.0592 0.9135 0.000 0.984 0.016 0.000
#> SRR1353076 2 0.1211 0.9102 0.000 0.960 0.040 0.000
#> SRR1480831 2 0.3751 0.7745 0.004 0.800 0.196 0.000
#> SRR1083892 1 0.7940 0.4824 0.600 0.108 0.112 0.180
#> SRR809873 3 0.5340 0.7411 0.004 0.104 0.756 0.136
#> SRR1341854 2 0.1004 0.9116 0.004 0.972 0.024 0.000
#> SRR1399335 2 0.1994 0.9010 0.008 0.936 0.052 0.004
#> SRR1464209 1 0.7940 0.4824 0.600 0.108 0.112 0.180
#> SRR1389886 2 0.0000 0.9130 0.000 1.000 0.000 0.000
#> SRR1400730 1 0.1109 0.5594 0.968 0.000 0.028 0.004
#> SRR1448008 2 0.3311 0.7839 0.000 0.828 0.172 0.000
#> SRR1087606 2 0.7077 0.2008 0.348 0.528 0.120 0.004
#> SRR1445111 1 0.6336 -0.1359 0.480 0.000 0.060 0.460
#> SRR816865 2 0.3575 0.8421 0.020 0.852 0.124 0.004
#> SRR1323360 2 0.0707 0.9138 0.000 0.980 0.020 0.000
#> SRR1417364 2 0.0336 0.9137 0.000 0.992 0.008 0.000
#> SRR1480329 2 0.0895 0.9129 0.004 0.976 0.020 0.000
#> SRR1403322 3 0.5083 0.5569 0.000 0.036 0.716 0.248
#> SRR1093625 4 0.0188 0.8973 0.004 0.000 0.000 0.996
#> SRR1479977 2 0.0188 0.9129 0.000 0.996 0.004 0.000
#> SRR1082035 2 0.8492 0.2732 0.112 0.548 0.168 0.172
#> SRR1393046 2 0.0469 0.9136 0.000 0.988 0.012 0.000
#> SRR1466663 2 0.5787 0.7083 0.068 0.740 0.164 0.028
#> SRR1384456 4 0.0188 0.8973 0.004 0.000 0.000 0.996
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.2388 0.8588 0.000 0.900 0.028 0.000 0.072
#> SRR808862 2 0.6243 0.6409 0.020 0.660 0.024 0.128 0.168
#> SRR1500382 2 0.2597 0.8511 0.000 0.884 0.024 0.000 0.092
#> SRR1322683 2 0.1544 0.8575 0.000 0.932 0.000 0.068 0.000
#> SRR1329811 3 0.4481 0.5692 0.000 0.000 0.576 0.008 0.416
#> SRR1087297 2 0.1012 0.8668 0.000 0.968 0.020 0.000 0.012
#> SRR1072626 2 0.3191 0.8452 0.000 0.860 0.004 0.084 0.052
#> SRR1407428 1 0.1300 0.8783 0.956 0.000 0.028 0.016 0.000
#> SRR1321029 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1500282 3 0.3209 0.6152 0.004 0.000 0.860 0.060 0.076
#> SRR1100496 2 0.5936 0.6448 0.000 0.648 0.020 0.160 0.172
#> SRR1308778 2 0.3977 0.8039 0.000 0.792 0.016 0.024 0.168
#> SRR1445304 2 0.2722 0.8464 0.000 0.872 0.020 0.000 0.108
#> SRR1099378 2 0.5609 0.4958 0.000 0.576 0.004 0.076 0.344
#> SRR1347412 3 0.6038 0.3826 0.372 0.000 0.516 0.004 0.108
#> SRR1099694 2 0.1243 0.8689 0.000 0.960 0.008 0.004 0.028
#> SRR1088365 2 0.3801 0.8066 0.000 0.808 0.012 0.028 0.152
#> SRR1325752 2 0.5350 0.6957 0.000 0.676 0.016 0.072 0.236
#> SRR1416713 2 0.1372 0.8697 0.000 0.956 0.016 0.004 0.024
#> SRR1074474 1 0.0000 0.8961 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 2 0.1608 0.8563 0.000 0.928 0.000 0.072 0.000
#> SRR1400507 2 0.1399 0.8656 0.000 0.952 0.020 0.028 0.000
#> SRR1378179 2 0.2037 0.8646 0.000 0.920 0.004 0.012 0.064
#> SRR1377905 2 0.1278 0.8693 0.000 0.960 0.016 0.004 0.020
#> SRR1089479 3 0.3643 0.5741 0.044 0.000 0.848 0.072 0.036
#> SRR1073365 2 0.2900 0.8407 0.000 0.864 0.000 0.028 0.108
#> SRR1500306 4 0.5194 0.6120 0.040 0.008 0.200 0.720 0.032
#> SRR1101566 2 0.1704 0.8580 0.000 0.928 0.004 0.068 0.000
#> SRR1350503 2 0.1074 0.8672 0.000 0.968 0.004 0.016 0.012
#> SRR1446007 2 0.0867 0.8664 0.000 0.976 0.008 0.008 0.008
#> SRR1102875 2 0.2900 0.8407 0.000 0.864 0.000 0.028 0.108
#> SRR1380293 2 0.1469 0.8697 0.000 0.948 0.016 0.000 0.036
#> SRR1331198 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1092686 2 0.2270 0.8643 0.000 0.916 0.012 0.020 0.052
#> SRR1069421 2 0.4365 0.7503 0.000 0.736 0.004 0.036 0.224
#> SRR1341650 2 0.6283 0.4658 0.000 0.556 0.028 0.092 0.324
#> SRR1357276 2 0.1310 0.8673 0.000 0.956 0.024 0.000 0.020
#> SRR1498374 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1093721 2 0.2251 0.8658 0.000 0.916 0.008 0.052 0.024
#> SRR1464660 3 0.4481 0.5692 0.000 0.000 0.576 0.008 0.416
#> SRR1402051 2 0.4167 0.7943 0.000 0.788 0.004 0.136 0.072
#> SRR1488734 2 0.2505 0.8513 0.000 0.888 0.020 0.000 0.092
#> SRR1082616 2 0.7200 0.0893 0.012 0.428 0.028 0.392 0.140
#> SRR1099427 2 0.1478 0.8590 0.000 0.936 0.000 0.064 0.000
#> SRR1453093 2 0.4302 0.6934 0.000 0.720 0.000 0.248 0.032
#> SRR1357064 5 0.2494 0.7924 0.032 0.000 0.056 0.008 0.904
#> SRR811237 2 0.3191 0.8452 0.000 0.860 0.004 0.084 0.052
#> SRR1100848 2 0.1173 0.8700 0.000 0.964 0.004 0.012 0.020
#> SRR1346755 2 0.1830 0.8584 0.000 0.924 0.000 0.068 0.008
#> SRR1472529 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1398905 3 0.3410 0.5815 0.000 0.000 0.840 0.092 0.068
#> SRR1082733 2 0.0613 0.8676 0.000 0.984 0.008 0.004 0.004
#> SRR1308035 2 0.1278 0.8672 0.000 0.960 0.004 0.016 0.020
#> SRR1466445 2 0.1095 0.8678 0.000 0.968 0.012 0.008 0.012
#> SRR1359080 2 0.0955 0.8657 0.000 0.968 0.028 0.000 0.004
#> SRR1455825 2 0.0693 0.8673 0.000 0.980 0.012 0.008 0.000
#> SRR1389300 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR812246 2 0.1728 0.8696 0.000 0.940 0.004 0.020 0.036
#> SRR1076632 2 0.4443 0.7671 0.000 0.748 0.008 0.044 0.200
#> SRR1415567 1 0.1399 0.8762 0.952 0.000 0.028 0.020 0.000
#> SRR1331900 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1452099 2 0.4866 0.7498 0.000 0.728 0.004 0.100 0.168
#> SRR1352346 1 0.5738 0.6677 0.728 0.016 0.068 0.104 0.084
#> SRR1364034 2 0.2784 0.8478 0.000 0.872 0.004 0.016 0.108
#> SRR1086046 2 0.5232 0.6242 0.000 0.648 0.000 0.268 0.084
#> SRR1407226 5 0.5090 0.7846 0.032 0.048 0.084 0.056 0.780
#> SRR1319363 4 0.7238 0.6572 0.092 0.040 0.104 0.616 0.148
#> SRR1446961 2 0.0865 0.8657 0.000 0.972 0.024 0.000 0.004
#> SRR1486650 1 0.0000 0.8961 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 3 0.4481 0.5692 0.000 0.000 0.576 0.008 0.416
#> SRR1454785 2 0.1278 0.8672 0.000 0.960 0.004 0.016 0.020
#> SRR1092329 2 0.1851 0.8467 0.000 0.912 0.000 0.088 0.000
#> SRR1091476 2 0.3685 0.8102 0.000 0.816 0.016 0.020 0.148
#> SRR1073775 2 0.2536 0.8253 0.000 0.868 0.000 0.128 0.004
#> SRR1366873 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1398114 2 0.2624 0.8463 0.000 0.872 0.012 0.000 0.116
#> SRR1089950 2 0.7861 -0.1626 0.004 0.372 0.184 0.076 0.364
#> SRR1433272 2 0.5477 0.5179 0.000 0.580 0.004 0.064 0.352
#> SRR1075314 4 0.2201 0.6889 0.040 0.008 0.032 0.920 0.000
#> SRR1085590 2 0.2938 0.8485 0.000 0.876 0.008 0.084 0.032
#> SRR1100752 2 0.2124 0.8648 0.000 0.924 0.012 0.020 0.044
#> SRR1391494 2 0.1502 0.8657 0.000 0.940 0.004 0.000 0.056
#> SRR1333263 2 0.5159 0.6240 0.000 0.644 0.000 0.072 0.284
#> SRR1310231 2 0.0566 0.8671 0.000 0.984 0.012 0.000 0.004
#> SRR1094144 2 0.4687 0.7574 0.000 0.736 0.012 0.052 0.200
#> SRR1092160 2 0.1243 0.8689 0.000 0.960 0.008 0.004 0.028
#> SRR1320300 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1322747 2 0.0771 0.8658 0.000 0.976 0.020 0.000 0.004
#> SRR1432719 2 0.1280 0.8712 0.000 0.960 0.008 0.008 0.024
#> SRR1100728 2 0.4365 0.7503 0.000 0.736 0.004 0.036 0.224
#> SRR1087511 2 0.1928 0.8561 0.000 0.920 0.004 0.072 0.004
#> SRR1470336 4 0.5194 0.6120 0.040 0.008 0.200 0.720 0.032
#> SRR1322536 4 0.2201 0.6889 0.040 0.008 0.032 0.920 0.000
#> SRR1100824 5 0.5090 0.7846 0.032 0.048 0.084 0.056 0.780
#> SRR1085951 2 0.5969 0.6398 0.000 0.644 0.020 0.160 0.176
#> SRR1322046 2 0.1843 0.8666 0.000 0.932 0.008 0.008 0.052
#> SRR1316420 5 0.6433 0.5953 0.032 0.080 0.224 0.028 0.636
#> SRR1070913 2 0.1364 0.8651 0.000 0.952 0.012 0.036 0.000
#> SRR1345806 2 0.1299 0.8690 0.000 0.960 0.008 0.012 0.020
#> SRR1313872 2 0.1012 0.8687 0.000 0.968 0.012 0.000 0.020
#> SRR1337666 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1076823 4 0.7470 0.5430 0.092 0.116 0.064 0.608 0.120
#> SRR1093954 2 0.3801 0.8066 0.000 0.808 0.012 0.028 0.152
#> SRR1451921 2 0.6441 0.1788 0.012 0.468 0.004 0.408 0.108
#> SRR1491257 5 0.3550 0.8286 0.032 0.032 0.068 0.008 0.860
#> SRR1416979 2 0.2295 0.8468 0.000 0.900 0.004 0.088 0.008
#> SRR1419015 2 0.8094 0.1171 0.016 0.424 0.068 0.244 0.248
#> SRR817649 2 0.1399 0.8706 0.000 0.952 0.020 0.000 0.028
#> SRR1466376 2 0.0771 0.8658 0.000 0.976 0.020 0.000 0.004
#> SRR1392055 2 0.1568 0.8661 0.000 0.944 0.020 0.000 0.036
#> SRR1120913 2 0.1117 0.8673 0.000 0.964 0.020 0.000 0.016
#> SRR1120869 2 0.4412 0.7745 0.000 0.756 0.008 0.048 0.188
#> SRR1319419 2 0.1095 0.8678 0.000 0.968 0.012 0.008 0.012
#> SRR816495 2 0.1372 0.8675 0.000 0.956 0.004 0.016 0.024
#> SRR818694 2 0.2753 0.8211 0.000 0.856 0.000 0.136 0.008
#> SRR1465653 3 0.4481 0.5692 0.000 0.000 0.576 0.008 0.416
#> SRR1475952 1 0.4649 0.3048 0.580 0.000 0.016 0.404 0.000
#> SRR1465040 2 0.1074 0.8673 0.000 0.968 0.004 0.012 0.016
#> SRR1088461 2 0.3649 0.8248 0.000 0.824 0.020 0.020 0.136
#> SRR810129 2 0.2624 0.8463 0.000 0.872 0.012 0.000 0.116
#> SRR1400141 2 0.2270 0.8643 0.000 0.916 0.012 0.020 0.052
#> SRR1349585 5 0.3550 0.8286 0.032 0.032 0.068 0.008 0.860
#> SRR1437576 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR814407 3 0.3333 0.5950 0.008 0.000 0.856 0.076 0.060
#> SRR1332403 2 0.0613 0.8676 0.000 0.984 0.008 0.004 0.004
#> SRR1099598 2 0.2300 0.8644 0.000 0.908 0.000 0.052 0.040
#> SRR1327723 2 0.0981 0.8686 0.000 0.972 0.008 0.008 0.012
#> SRR1392525 2 0.6857 0.3249 0.012 0.500 0.016 0.336 0.136
#> SRR1320536 1 0.0000 0.8961 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.1106 0.8662 0.000 0.964 0.024 0.000 0.012
#> SRR1351390 2 0.7702 -0.0927 0.000 0.388 0.180 0.076 0.356
#> SRR1309141 2 0.5159 0.6240 0.000 0.644 0.000 0.072 0.284
#> SRR1452803 2 0.2722 0.8464 0.000 0.872 0.020 0.000 0.108
#> SRR811631 2 0.1571 0.8598 0.000 0.936 0.004 0.060 0.000
#> SRR1485563 2 0.5270 0.7125 0.000 0.692 0.008 0.104 0.196
#> SRR1311531 2 0.1356 0.8685 0.000 0.956 0.004 0.028 0.012
#> SRR1353076 2 0.2074 0.8667 0.000 0.920 0.000 0.044 0.036
#> SRR1480831 2 0.4765 0.6984 0.000 0.708 0.004 0.232 0.056
#> SRR1083892 5 0.2494 0.7924 0.032 0.000 0.056 0.008 0.904
#> SRR809873 4 0.7238 0.6572 0.092 0.040 0.104 0.616 0.148
#> SRR1341854 2 0.1914 0.8658 0.000 0.928 0.008 0.008 0.056
#> SRR1399335 2 0.3694 0.8226 0.000 0.820 0.020 0.020 0.140
#> SRR1464209 5 0.2494 0.7924 0.032 0.000 0.056 0.008 0.904
#> SRR1389886 2 0.0566 0.8663 0.000 0.984 0.012 0.000 0.004
#> SRR1400730 3 0.4288 0.5606 0.000 0.000 0.612 0.004 0.384
#> SRR1448008 2 0.4029 0.7039 0.000 0.744 0.000 0.232 0.024
#> SRR1087606 2 0.7683 -0.1260 0.000 0.380 0.184 0.072 0.364
#> SRR1445111 3 0.5415 0.1919 0.448 0.000 0.508 0.020 0.024
#> SRR816865 2 0.4365 0.7503 0.000 0.736 0.004 0.036 0.224
#> SRR1323360 2 0.1278 0.8672 0.000 0.960 0.004 0.016 0.020
#> SRR1417364 2 0.0771 0.8667 0.000 0.976 0.020 0.000 0.004
#> SRR1480329 2 0.2754 0.8519 0.000 0.884 0.004 0.080 0.032
#> SRR1403322 4 0.6746 0.5674 0.204 0.000 0.104 0.600 0.092
#> SRR1093625 1 0.0000 0.8961 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.0703 0.8646 0.000 0.976 0.024 0.000 0.000
#> SRR1082035 2 0.8151 0.0850 0.136 0.428 0.032 0.080 0.324
#> SRR1393046 2 0.1502 0.8657 0.000 0.940 0.004 0.000 0.056
#> SRR1466663 2 0.5385 0.5785 0.000 0.616 0.004 0.068 0.312
#> SRR1384456 1 0.0000 0.8961 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.2591 0.6387 0.000 0.880 0.052 0.004 0.064 0.000
#> SRR808862 3 0.6742 0.7613 0.012 0.384 0.444 0.008 0.092 0.060
#> SRR1500382 2 0.2973 0.6185 0.004 0.860 0.068 0.004 0.064 0.000
#> SRR1322683 2 0.3123 0.5916 0.000 0.824 0.136 0.000 0.000 0.040
#> SRR1329811 4 0.5278 0.6188 0.000 0.000 0.084 0.472 0.440 0.004
#> SRR1087297 2 0.1138 0.6496 0.000 0.960 0.024 0.004 0.012 0.000
#> SRR1072626 2 0.4393 0.5475 0.000 0.748 0.164 0.000 0.036 0.052
#> SRR1407428 1 0.1755 0.8475 0.932 0.000 0.008 0.032 0.000 0.028
#> SRR1321029 2 0.0790 0.6414 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1500282 4 0.1768 0.5647 0.004 0.000 0.008 0.932 0.044 0.012
#> SRR1100496 3 0.6268 0.7981 0.000 0.360 0.492 0.008 0.088 0.052
#> SRR1308778 2 0.5421 0.4239 0.004 0.652 0.204 0.008 0.120 0.012
#> SRR1445304 2 0.3441 0.6065 0.004 0.836 0.084 0.008 0.064 0.004
#> SRR1099378 2 0.6627 -0.4019 0.000 0.408 0.260 0.000 0.300 0.032
#> SRR1347412 4 0.6349 0.3683 0.356 0.000 0.032 0.480 0.120 0.012
#> SRR1099694 2 0.2238 0.6515 0.000 0.904 0.068 0.008 0.016 0.004
#> SRR1088365 2 0.5273 0.4526 0.004 0.668 0.212 0.008 0.092 0.016
#> SRR1325752 2 0.6546 0.0257 0.004 0.524 0.264 0.008 0.160 0.040
#> SRR1416713 2 0.1546 0.6543 0.000 0.944 0.028 0.004 0.020 0.004
#> SRR1074474 1 0.0146 0.8641 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1469369 2 0.3307 0.5755 0.000 0.808 0.148 0.000 0.000 0.044
#> SRR1400507 2 0.2357 0.6316 0.000 0.872 0.116 0.000 0.000 0.012
#> SRR1378179 2 0.3237 0.6311 0.000 0.840 0.104 0.008 0.044 0.004
#> SRR1377905 2 0.1457 0.6541 0.000 0.948 0.028 0.004 0.016 0.004
#> SRR1089479 4 0.1931 0.5346 0.040 0.000 0.004 0.924 0.004 0.028
#> SRR1073365 2 0.4396 0.5574 0.004 0.752 0.160 0.004 0.068 0.012
#> SRR1500306 6 0.3616 0.5717 0.000 0.000 0.012 0.184 0.024 0.780
#> SRR1101566 2 0.3172 0.5817 0.000 0.816 0.148 0.000 0.000 0.036
#> SRR1350503 2 0.3221 0.4629 0.000 0.736 0.264 0.000 0.000 0.000
#> SRR1446007 2 0.2883 0.5232 0.000 0.788 0.212 0.000 0.000 0.000
#> SRR1102875 2 0.4396 0.5574 0.004 0.752 0.160 0.004 0.068 0.012
#> SRR1380293 2 0.1873 0.6561 0.000 0.924 0.048 0.008 0.020 0.000
#> SRR1331198 2 0.0632 0.6427 0.000 0.976 0.024 0.000 0.000 0.000
#> SRR1092686 2 0.4109 0.3320 0.000 0.648 0.328 0.000 0.024 0.000
#> SRR1069421 2 0.5858 0.2338 0.004 0.588 0.236 0.004 0.152 0.016
#> SRR1341650 2 0.7142 -0.4075 0.000 0.404 0.288 0.024 0.248 0.036
#> SRR1357276 2 0.1722 0.6512 0.000 0.936 0.036 0.008 0.016 0.004
#> SRR1498374 2 0.0790 0.6414 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1093721 2 0.3154 0.6224 0.000 0.836 0.124 0.000 0.020 0.020
#> SRR1464660 4 0.5278 0.6188 0.000 0.000 0.084 0.472 0.440 0.004
#> SRR1402051 2 0.5551 0.2224 0.000 0.624 0.252 0.004 0.040 0.080
#> SRR1488734 2 0.2973 0.6194 0.004 0.860 0.068 0.004 0.064 0.000
#> SRR1082616 2 0.7719 -0.6330 0.000 0.336 0.264 0.040 0.064 0.296
#> SRR1099427 2 0.3014 0.5941 0.000 0.832 0.132 0.000 0.000 0.036
#> SRR1453093 2 0.5461 -0.1604 0.000 0.556 0.308 0.000 0.004 0.132
#> SRR1357064 5 0.0146 0.4768 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR811237 2 0.4393 0.5475 0.000 0.748 0.164 0.000 0.036 0.052
#> SRR1100848 2 0.2060 0.6495 0.000 0.900 0.084 0.000 0.016 0.000
#> SRR1346755 2 0.3304 0.5869 0.000 0.816 0.140 0.000 0.004 0.040
#> SRR1472529 2 0.0632 0.6427 0.000 0.976 0.024 0.000 0.000 0.000
#> SRR1398905 4 0.2122 0.5309 0.000 0.000 0.032 0.916 0.024 0.028
#> SRR1082733 2 0.0982 0.6545 0.000 0.968 0.020 0.004 0.004 0.004
#> SRR1308035 2 0.3288 0.4487 0.000 0.724 0.276 0.000 0.000 0.000
#> SRR1466445 2 0.2996 0.5068 0.000 0.772 0.228 0.000 0.000 0.000
#> SRR1359080 2 0.0972 0.6446 0.000 0.964 0.028 0.008 0.000 0.000
#> SRR1455825 2 0.0717 0.6505 0.000 0.976 0.016 0.000 0.000 0.008
#> SRR1389300 2 0.0713 0.6422 0.000 0.972 0.028 0.000 0.000 0.000
#> SRR812246 2 0.3797 0.4036 0.000 0.692 0.292 0.000 0.016 0.000
#> SRR1076632 2 0.5793 0.2908 0.004 0.600 0.248 0.008 0.124 0.016
#> SRR1415567 1 0.1857 0.8458 0.928 0.000 0.012 0.032 0.000 0.028
#> SRR1331900 2 0.0790 0.6414 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1452099 2 0.6175 -0.1814 0.000 0.528 0.296 0.000 0.128 0.048
#> SRR1352346 1 0.6679 0.5079 0.552 0.004 0.244 0.036 0.036 0.128
#> SRR1364034 2 0.4062 0.5894 0.000 0.780 0.132 0.008 0.072 0.008
#> SRR1086046 2 0.6101 -0.4141 0.000 0.476 0.352 0.000 0.024 0.148
#> SRR1407226 5 0.3541 0.5218 0.000 0.016 0.080 0.036 0.840 0.028
#> SRR1319363 6 0.7601 0.6343 0.072 0.012 0.264 0.148 0.040 0.464
#> SRR1446961 2 0.1700 0.6300 0.000 0.916 0.080 0.000 0.004 0.000
#> SRR1486650 1 0.2094 0.8289 0.908 0.000 0.064 0.000 0.004 0.024
#> SRR1470152 4 0.5278 0.6188 0.000 0.000 0.084 0.472 0.440 0.004
#> SRR1454785 2 0.3266 0.4524 0.000 0.728 0.272 0.000 0.000 0.000
#> SRR1092329 2 0.3481 0.5555 0.000 0.792 0.160 0.000 0.000 0.048
#> SRR1091476 2 0.5408 -0.2581 0.000 0.524 0.364 0.000 0.108 0.004
#> SRR1073775 2 0.4244 0.4347 0.000 0.720 0.200 0.000 0.000 0.080
#> SRR1366873 2 0.0790 0.6414 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1398114 2 0.3580 0.6008 0.004 0.824 0.100 0.008 0.060 0.004
#> SRR1089950 5 0.8245 -0.1305 0.000 0.264 0.168 0.188 0.332 0.048
#> SRR1433272 2 0.6818 -0.3610 0.004 0.408 0.272 0.004 0.284 0.028
#> SRR1075314 6 0.1625 0.6580 0.000 0.000 0.060 0.012 0.000 0.928
#> SRR1085590 2 0.4393 0.4065 0.000 0.708 0.232 0.000 0.016 0.044
#> SRR1100752 2 0.3905 0.3435 0.000 0.668 0.316 0.000 0.016 0.000
#> SRR1391494 2 0.2136 0.6519 0.000 0.904 0.048 0.000 0.048 0.000
#> SRR1333263 2 0.6335 -0.2007 0.000 0.496 0.268 0.000 0.204 0.032
#> SRR1310231 2 0.0982 0.6530 0.000 0.968 0.020 0.004 0.004 0.004
#> SRR1094144 2 0.5983 0.2404 0.004 0.584 0.256 0.008 0.124 0.024
#> SRR1092160 2 0.2238 0.6515 0.000 0.904 0.068 0.008 0.016 0.004
#> SRR1320300 2 0.0790 0.6414 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1322747 2 0.0692 0.6452 0.000 0.976 0.020 0.004 0.000 0.000
#> SRR1432719 2 0.3371 0.5462 0.000 0.780 0.200 0.000 0.016 0.004
#> SRR1100728 2 0.5858 0.2338 0.004 0.588 0.236 0.004 0.152 0.016
#> SRR1087511 2 0.3522 0.5509 0.000 0.784 0.172 0.000 0.000 0.044
#> SRR1470336 6 0.3616 0.5717 0.000 0.000 0.012 0.184 0.024 0.780
#> SRR1322536 6 0.1625 0.6580 0.000 0.000 0.060 0.012 0.000 0.928
#> SRR1100824 5 0.3541 0.5218 0.000 0.016 0.080 0.036 0.840 0.028
#> SRR1085951 3 0.6298 0.7990 0.000 0.356 0.492 0.008 0.092 0.052
#> SRR1322046 2 0.2864 0.6403 0.000 0.864 0.088 0.004 0.040 0.004
#> SRR1316420 5 0.5237 0.4187 0.000 0.064 0.040 0.176 0.700 0.020
#> SRR1070913 2 0.2491 0.6279 0.000 0.868 0.112 0.000 0.000 0.020
#> SRR1345806 2 0.3354 0.4930 0.000 0.752 0.240 0.000 0.004 0.004
#> SRR1313872 2 0.1490 0.6566 0.000 0.948 0.024 0.008 0.016 0.004
#> SRR1337666 2 0.0713 0.6430 0.000 0.972 0.028 0.000 0.000 0.000
#> SRR1076823 6 0.7734 0.5636 0.072 0.060 0.296 0.092 0.024 0.456
#> SRR1093954 2 0.5273 0.4526 0.004 0.668 0.212 0.008 0.092 0.016
#> SRR1451921 3 0.6805 0.5707 0.000 0.332 0.364 0.012 0.020 0.272
#> SRR1491257 5 0.1692 0.5187 0.000 0.008 0.048 0.012 0.932 0.000
#> SRR1416979 2 0.3765 0.5461 0.000 0.780 0.164 0.000 0.008 0.048
#> SRR1419015 2 0.8820 -0.5292 0.016 0.300 0.264 0.076 0.172 0.172
#> SRR817649 2 0.1692 0.6562 0.000 0.932 0.048 0.008 0.012 0.000
#> SRR1466376 2 0.0692 0.6452 0.000 0.976 0.020 0.004 0.000 0.000
#> SRR1392055 2 0.1860 0.6470 0.000 0.928 0.028 0.004 0.036 0.004
#> SRR1120913 2 0.1457 0.6500 0.000 0.948 0.028 0.004 0.016 0.004
#> SRR1120869 2 0.5732 0.3160 0.004 0.612 0.236 0.008 0.124 0.016
#> SRR1319419 2 0.2941 0.5129 0.000 0.780 0.220 0.000 0.000 0.000
#> SRR816495 2 0.3426 0.4427 0.000 0.720 0.276 0.000 0.004 0.000
#> SRR818694 2 0.4376 0.4072 0.000 0.704 0.212 0.000 0.000 0.084
#> SRR1465653 4 0.5278 0.6188 0.000 0.000 0.084 0.472 0.440 0.004
#> SRR1475952 1 0.4178 0.2915 0.560 0.000 0.004 0.008 0.000 0.428
#> SRR1465040 2 0.3198 0.4774 0.000 0.740 0.260 0.000 0.000 0.000
#> SRR1088461 2 0.4372 0.5537 0.004 0.768 0.124 0.008 0.084 0.012
#> SRR810129 2 0.3580 0.6008 0.004 0.824 0.100 0.008 0.060 0.004
#> SRR1400141 2 0.4109 0.3320 0.000 0.648 0.328 0.000 0.024 0.000
#> SRR1349585 5 0.1692 0.5187 0.000 0.008 0.048 0.012 0.932 0.000
#> SRR1437576 2 0.0713 0.6450 0.000 0.972 0.028 0.000 0.000 0.000
#> SRR814407 4 0.1938 0.5447 0.004 0.000 0.016 0.928 0.024 0.028
#> SRR1332403 2 0.0982 0.6545 0.000 0.968 0.020 0.004 0.004 0.004
#> SRR1099598 2 0.3578 0.6059 0.000 0.800 0.152 0.000 0.016 0.032
#> SRR1327723 2 0.1340 0.6560 0.000 0.948 0.040 0.008 0.004 0.000
#> SRR1392525 2 0.7376 -0.6084 0.000 0.404 0.268 0.024 0.060 0.244
#> SRR1320536 1 0.0146 0.8641 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1083824 2 0.1225 0.6489 0.000 0.952 0.036 0.000 0.012 0.000
#> SRR1351390 5 0.8256 -0.2078 0.000 0.280 0.192 0.176 0.308 0.044
#> SRR1309141 2 0.6335 -0.2007 0.000 0.496 0.268 0.000 0.204 0.032
#> SRR1452803 2 0.3441 0.6065 0.004 0.836 0.084 0.008 0.064 0.004
#> SRR811631 2 0.3014 0.6001 0.000 0.832 0.132 0.000 0.000 0.036
#> SRR1485563 2 0.6204 0.1121 0.000 0.576 0.224 0.004 0.140 0.056
#> SRR1311531 2 0.3314 0.4793 0.000 0.740 0.256 0.000 0.000 0.004
#> SRR1353076 2 0.3391 0.6139 0.000 0.812 0.148 0.000 0.016 0.024
#> SRR1480831 2 0.5810 -0.1506 0.000 0.552 0.308 0.004 0.020 0.116
#> SRR1083892 5 0.0146 0.4768 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR809873 6 0.7601 0.6343 0.072 0.012 0.264 0.148 0.040 0.464
#> SRR1341854 2 0.2975 0.6385 0.000 0.860 0.088 0.008 0.040 0.004
#> SRR1399335 2 0.4421 0.5483 0.004 0.764 0.124 0.008 0.088 0.012
#> SRR1464209 5 0.0146 0.4768 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1389886 2 0.0748 0.6493 0.000 0.976 0.016 0.004 0.000 0.004
#> SRR1400730 4 0.5231 0.6159 0.000 0.000 0.084 0.520 0.392 0.004
#> SRR1448008 2 0.5222 -0.0929 0.000 0.584 0.288 0.000 0.000 0.128
#> SRR1087606 5 0.8230 -0.1778 0.000 0.276 0.184 0.176 0.320 0.044
#> SRR1445111 4 0.4762 0.1807 0.428 0.000 0.004 0.532 0.004 0.032
#> SRR816865 2 0.5858 0.2338 0.004 0.588 0.236 0.004 0.152 0.016
#> SRR1323360 2 0.3288 0.4487 0.000 0.724 0.276 0.000 0.000 0.000
#> SRR1417364 2 0.1806 0.6324 0.000 0.908 0.088 0.000 0.004 0.000
#> SRR1480329 2 0.3854 0.5746 0.000 0.796 0.128 0.000 0.028 0.048
#> SRR1403322 6 0.7193 0.5387 0.160 0.000 0.196 0.152 0.008 0.484
#> SRR1093625 1 0.0146 0.8641 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1479977 2 0.0632 0.6427 0.000 0.976 0.024 0.000 0.000 0.000
#> SRR1082035 2 0.8746 -0.4550 0.092 0.320 0.228 0.036 0.260 0.064
#> SRR1393046 2 0.2136 0.6519 0.000 0.904 0.048 0.000 0.048 0.000
#> SRR1466663 2 0.6421 -0.2288 0.000 0.480 0.252 0.000 0.236 0.032
#> SRR1384456 1 0.0146 0.8641 0.996 0.000 0.000 0.000 0.004 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["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 17467 rows and 159 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.975 0.953 0.980 0.4070 0.592 0.592
#> 3 3 0.485 0.703 0.826 0.4201 0.818 0.698
#> 4 4 0.458 0.552 0.728 0.1746 0.893 0.762
#> 5 5 0.534 0.490 0.657 0.0998 0.796 0.493
#> 6 6 0.624 0.556 0.736 0.0648 0.893 0.601
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
#> SRR810713 2 0.0000 0.9861 0.000 1.000
#> SRR808862 1 0.7950 0.6905 0.760 0.240
#> SRR1500382 2 0.0000 0.9861 0.000 1.000
#> SRR1322683 2 0.0000 0.9861 0.000 1.000
#> SRR1329811 1 0.0000 0.9622 1.000 0.000
#> SRR1087297 2 0.0000 0.9861 0.000 1.000
#> SRR1072626 2 0.0000 0.9861 0.000 1.000
#> SRR1407428 1 0.0000 0.9622 1.000 0.000
#> SRR1321029 2 0.0000 0.9861 0.000 1.000
#> SRR1500282 1 0.0000 0.9622 1.000 0.000
#> SRR1100496 2 0.7219 0.7475 0.200 0.800
#> SRR1308778 2 0.0000 0.9861 0.000 1.000
#> SRR1445304 2 0.0000 0.9861 0.000 1.000
#> SRR1099378 1 0.2236 0.9368 0.964 0.036
#> SRR1347412 1 0.0000 0.9622 1.000 0.000
#> SRR1099694 2 0.0000 0.9861 0.000 1.000
#> SRR1088365 2 0.0000 0.9861 0.000 1.000
#> SRR1325752 2 0.9977 0.0642 0.472 0.528
#> SRR1416713 2 0.0000 0.9861 0.000 1.000
#> SRR1074474 1 0.0000 0.9622 1.000 0.000
#> SRR1469369 2 0.0000 0.9861 0.000 1.000
#> SRR1400507 2 0.0000 0.9861 0.000 1.000
#> SRR1378179 2 0.0000 0.9861 0.000 1.000
#> SRR1377905 2 0.0000 0.9861 0.000 1.000
#> SRR1089479 1 0.0000 0.9622 1.000 0.000
#> SRR1073365 2 0.0000 0.9861 0.000 1.000
#> SRR1500306 1 0.0000 0.9622 1.000 0.000
#> SRR1101566 2 0.0000 0.9861 0.000 1.000
#> SRR1350503 2 0.0000 0.9861 0.000 1.000
#> SRR1446007 2 0.0000 0.9861 0.000 1.000
#> SRR1102875 2 0.0000 0.9861 0.000 1.000
#> SRR1380293 2 0.0000 0.9861 0.000 1.000
#> SRR1331198 2 0.0000 0.9861 0.000 1.000
#> SRR1092686 2 0.0000 0.9861 0.000 1.000
#> SRR1069421 2 0.2423 0.9507 0.040 0.960
#> SRR1341650 2 0.7219 0.7475 0.200 0.800
#> SRR1357276 2 0.0000 0.9861 0.000 1.000
#> SRR1498374 2 0.0000 0.9861 0.000 1.000
#> SRR1093721 2 0.0000 0.9861 0.000 1.000
#> SRR1464660 1 0.0000 0.9622 1.000 0.000
#> SRR1402051 2 0.0000 0.9861 0.000 1.000
#> SRR1488734 2 0.0000 0.9861 0.000 1.000
#> SRR1082616 2 0.3733 0.9173 0.072 0.928
#> SRR1099427 2 0.0000 0.9861 0.000 1.000
#> SRR1453093 2 0.0000 0.9861 0.000 1.000
#> SRR1357064 1 0.0000 0.9622 1.000 0.000
#> SRR811237 2 0.0000 0.9861 0.000 1.000
#> SRR1100848 2 0.0000 0.9861 0.000 1.000
#> SRR1346755 2 0.0000 0.9861 0.000 1.000
#> SRR1472529 2 0.0000 0.9861 0.000 1.000
#> SRR1398905 1 0.0000 0.9622 1.000 0.000
#> SRR1082733 2 0.0000 0.9861 0.000 1.000
#> SRR1308035 2 0.0000 0.9861 0.000 1.000
#> SRR1466445 2 0.0000 0.9861 0.000 1.000
#> SRR1359080 2 0.0000 0.9861 0.000 1.000
#> SRR1455825 2 0.0000 0.9861 0.000 1.000
#> SRR1389300 2 0.0000 0.9861 0.000 1.000
#> SRR812246 2 0.0000 0.9861 0.000 1.000
#> SRR1076632 2 0.0000 0.9861 0.000 1.000
#> SRR1415567 1 0.0000 0.9622 1.000 0.000
#> SRR1331900 2 0.0000 0.9861 0.000 1.000
#> SRR1452099 2 0.7219 0.7475 0.200 0.800
#> SRR1352346 1 0.0000 0.9622 1.000 0.000
#> SRR1364034 2 0.0000 0.9861 0.000 1.000
#> SRR1086046 2 0.4690 0.8849 0.100 0.900
#> SRR1407226 1 0.0000 0.9622 1.000 0.000
#> SRR1319363 1 0.1414 0.9492 0.980 0.020
#> SRR1446961 2 0.0000 0.9861 0.000 1.000
#> SRR1486650 1 0.0000 0.9622 1.000 0.000
#> SRR1470152 1 0.0000 0.9622 1.000 0.000
#> SRR1454785 2 0.0000 0.9861 0.000 1.000
#> SRR1092329 2 0.0000 0.9861 0.000 1.000
#> SRR1091476 2 0.0000 0.9861 0.000 1.000
#> SRR1073775 2 0.0000 0.9861 0.000 1.000
#> SRR1366873 2 0.0000 0.9861 0.000 1.000
#> SRR1398114 2 0.0000 0.9861 0.000 1.000
#> SRR1089950 1 0.0000 0.9622 1.000 0.000
#> SRR1433272 2 0.2423 0.9507 0.040 0.960
#> SRR1075314 1 0.5059 0.8603 0.888 0.112
#> SRR1085590 2 0.0000 0.9861 0.000 1.000
#> SRR1100752 2 0.0000 0.9861 0.000 1.000
#> SRR1391494 2 0.0000 0.9861 0.000 1.000
#> SRR1333263 2 0.0672 0.9794 0.008 0.992
#> SRR1310231 2 0.0000 0.9861 0.000 1.000
#> SRR1094144 2 0.2423 0.9507 0.040 0.960
#> SRR1092160 2 0.0000 0.9861 0.000 1.000
#> SRR1320300 2 0.0000 0.9861 0.000 1.000
#> SRR1322747 2 0.0000 0.9861 0.000 1.000
#> SRR1432719 2 0.0000 0.9861 0.000 1.000
#> SRR1100728 2 0.2423 0.9507 0.040 0.960
#> SRR1087511 2 0.0000 0.9861 0.000 1.000
#> SRR1470336 1 0.0000 0.9622 1.000 0.000
#> SRR1322536 1 0.1633 0.9462 0.976 0.024
#> SRR1100824 1 0.0000 0.9622 1.000 0.000
#> SRR1085951 1 0.9661 0.3758 0.608 0.392
#> SRR1322046 2 0.0000 0.9861 0.000 1.000
#> SRR1316420 1 0.0000 0.9622 1.000 0.000
#> SRR1070913 2 0.0000 0.9861 0.000 1.000
#> SRR1345806 2 0.0000 0.9861 0.000 1.000
#> SRR1313872 2 0.0000 0.9861 0.000 1.000
#> SRR1337666 2 0.0000 0.9861 0.000 1.000
#> SRR1076823 1 0.1414 0.9492 0.980 0.020
#> SRR1093954 2 0.0000 0.9861 0.000 1.000
#> SRR1451921 1 0.9983 0.1134 0.524 0.476
#> SRR1491257 1 0.0000 0.9622 1.000 0.000
#> SRR1416979 2 0.0000 0.9861 0.000 1.000
#> SRR1419015 1 0.8443 0.6369 0.728 0.272
#> SRR817649 2 0.0000 0.9861 0.000 1.000
#> SRR1466376 2 0.0000 0.9861 0.000 1.000
#> SRR1392055 2 0.0000 0.9861 0.000 1.000
#> SRR1120913 2 0.0000 0.9861 0.000 1.000
#> SRR1120869 2 0.0000 0.9861 0.000 1.000
#> SRR1319419 2 0.0000 0.9861 0.000 1.000
#> SRR816495 2 0.0000 0.9861 0.000 1.000
#> SRR818694 2 0.0000 0.9861 0.000 1.000
#> SRR1465653 1 0.0000 0.9622 1.000 0.000
#> SRR1475952 1 0.0000 0.9622 1.000 0.000
#> SRR1465040 2 0.0000 0.9861 0.000 1.000
#> SRR1088461 2 0.0000 0.9861 0.000 1.000
#> SRR810129 2 0.0000 0.9861 0.000 1.000
#> SRR1400141 2 0.0000 0.9861 0.000 1.000
#> SRR1349585 1 0.0000 0.9622 1.000 0.000
#> SRR1437576 2 0.0000 0.9861 0.000 1.000
#> SRR814407 1 0.0000 0.9622 1.000 0.000
#> SRR1332403 2 0.0000 0.9861 0.000 1.000
#> SRR1099598 2 0.0000 0.9861 0.000 1.000
#> SRR1327723 2 0.0000 0.9861 0.000 1.000
#> SRR1392525 2 0.0000 0.9861 0.000 1.000
#> SRR1320536 1 0.0000 0.9622 1.000 0.000
#> SRR1083824 2 0.0000 0.9861 0.000 1.000
#> SRR1351390 1 0.0000 0.9622 1.000 0.000
#> SRR1309141 2 0.0000 0.9861 0.000 1.000
#> SRR1452803 2 0.0000 0.9861 0.000 1.000
#> SRR811631 2 0.0000 0.9861 0.000 1.000
#> SRR1485563 2 0.0938 0.9760 0.012 0.988
#> SRR1311531 2 0.0000 0.9861 0.000 1.000
#> SRR1353076 2 0.0000 0.9861 0.000 1.000
#> SRR1480831 2 0.0000 0.9861 0.000 1.000
#> SRR1083892 1 0.0000 0.9622 1.000 0.000
#> SRR809873 1 0.1633 0.9462 0.976 0.024
#> SRR1341854 2 0.0000 0.9861 0.000 1.000
#> SRR1399335 2 0.0000 0.9861 0.000 1.000
#> SRR1464209 1 0.0000 0.9622 1.000 0.000
#> SRR1389886 2 0.0000 0.9861 0.000 1.000
#> SRR1400730 1 0.0000 0.9622 1.000 0.000
#> SRR1448008 2 0.0000 0.9861 0.000 1.000
#> SRR1087606 1 0.0000 0.9622 1.000 0.000
#> SRR1445111 1 0.0000 0.9622 1.000 0.000
#> SRR816865 2 0.2423 0.9507 0.040 0.960
#> SRR1323360 2 0.0000 0.9861 0.000 1.000
#> SRR1417364 2 0.0000 0.9861 0.000 1.000
#> SRR1480329 2 0.0000 0.9861 0.000 1.000
#> SRR1403322 1 0.0000 0.9622 1.000 0.000
#> SRR1093625 1 0.0000 0.9622 1.000 0.000
#> SRR1479977 2 0.0000 0.9861 0.000 1.000
#> SRR1082035 1 0.0000 0.9622 1.000 0.000
#> SRR1393046 2 0.0000 0.9861 0.000 1.000
#> SRR1466663 2 0.2236 0.9544 0.036 0.964
#> SRR1384456 1 0.0000 0.9622 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.3192 0.8153 0.000 0.888 0.112
#> SRR808862 3 0.7084 0.1464 0.336 0.036 0.628
#> SRR1500382 2 0.1529 0.8392 0.000 0.960 0.040
#> SRR1322683 2 0.1964 0.8277 0.000 0.944 0.056
#> SRR1329811 1 0.5902 0.7625 0.680 0.004 0.316
#> SRR1087297 2 0.3038 0.8196 0.000 0.896 0.104
#> SRR1072626 2 0.6309 -0.1829 0.000 0.500 0.500
#> SRR1407428 1 0.0592 0.7734 0.988 0.000 0.012
#> SRR1321029 2 0.0592 0.8389 0.000 0.988 0.012
#> SRR1500282 1 0.3116 0.7783 0.892 0.000 0.108
#> SRR1100496 3 0.4469 0.6804 0.028 0.120 0.852
#> SRR1308778 2 0.4974 0.6776 0.000 0.764 0.236
#> SRR1445304 2 0.3412 0.8082 0.000 0.876 0.124
#> SRR1099378 3 0.3690 0.4337 0.100 0.016 0.884
#> SRR1347412 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR1099694 2 0.3686 0.8019 0.000 0.860 0.140
#> SRR1088365 3 0.6267 0.3738 0.000 0.452 0.548
#> SRR1325752 3 0.6488 0.7169 0.064 0.192 0.744
#> SRR1416713 2 0.2878 0.8232 0.000 0.904 0.096
#> SRR1074474 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR1469369 2 0.3267 0.7976 0.000 0.884 0.116
#> SRR1400507 2 0.0592 0.8389 0.000 0.988 0.012
#> SRR1378179 2 0.5785 0.4831 0.000 0.668 0.332
#> SRR1377905 2 0.2448 0.8313 0.000 0.924 0.076
#> SRR1089479 1 0.1163 0.7760 0.972 0.000 0.028
#> SRR1073365 2 0.3412 0.8080 0.000 0.876 0.124
#> SRR1500306 1 0.3116 0.7559 0.892 0.000 0.108
#> SRR1101566 2 0.2066 0.8264 0.000 0.940 0.060
#> SRR1350503 2 0.2625 0.8114 0.000 0.916 0.084
#> SRR1446007 2 0.2878 0.8047 0.000 0.904 0.096
#> SRR1102875 2 0.4062 0.7796 0.000 0.836 0.164
#> SRR1380293 2 0.3941 0.7883 0.000 0.844 0.156
#> SRR1331198 2 0.0747 0.8406 0.000 0.984 0.016
#> SRR1092686 2 0.5859 0.6086 0.000 0.656 0.344
#> SRR1069421 3 0.5216 0.7439 0.000 0.260 0.740
#> SRR1341650 3 0.5631 0.7057 0.044 0.164 0.792
#> SRR1357276 2 0.1289 0.8403 0.000 0.968 0.032
#> SRR1498374 2 0.0592 0.8389 0.000 0.988 0.012
#> SRR1093721 2 0.2537 0.8404 0.000 0.920 0.080
#> SRR1464660 1 0.5678 0.7652 0.684 0.000 0.316
#> SRR1402051 2 0.6154 0.0415 0.000 0.592 0.408
#> SRR1488734 2 0.3551 0.8025 0.000 0.868 0.132
#> SRR1082616 3 0.4099 0.6990 0.008 0.140 0.852
#> SRR1099427 2 0.1964 0.8277 0.000 0.944 0.056
#> SRR1453093 2 0.6286 -0.0892 0.000 0.536 0.464
#> SRR1357064 1 0.5465 0.7716 0.712 0.000 0.288
#> SRR811237 3 0.6225 0.3948 0.000 0.432 0.568
#> SRR1100848 2 0.4555 0.7735 0.000 0.800 0.200
#> SRR1346755 2 0.2261 0.8288 0.000 0.932 0.068
#> SRR1472529 2 0.0592 0.8389 0.000 0.988 0.012
#> SRR1398905 1 0.2356 0.7688 0.928 0.000 0.072
#> SRR1082733 2 0.3116 0.8175 0.000 0.892 0.108
#> SRR1308035 2 0.3038 0.8039 0.000 0.896 0.104
#> SRR1466445 2 0.3116 0.8020 0.000 0.892 0.108
#> SRR1359080 2 0.0747 0.8406 0.000 0.984 0.016
#> SRR1455825 2 0.0424 0.8393 0.000 0.992 0.008
#> SRR1389300 2 0.0424 0.8393 0.000 0.992 0.008
#> SRR812246 2 0.4974 0.6599 0.000 0.764 0.236
#> SRR1076632 3 0.5363 0.7292 0.000 0.276 0.724
#> SRR1415567 1 0.0424 0.7741 0.992 0.000 0.008
#> SRR1331900 2 0.0592 0.8395 0.000 0.988 0.012
#> SRR1452099 3 0.5058 0.7066 0.032 0.148 0.820
#> SRR1352346 1 0.5706 0.7540 0.680 0.000 0.320
#> SRR1364034 2 0.5706 0.5163 0.000 0.680 0.320
#> SRR1086046 3 0.6587 0.5730 0.016 0.352 0.632
#> SRR1407226 1 0.5835 0.7531 0.660 0.000 0.340
#> SRR1319363 3 0.5928 0.1664 0.296 0.008 0.696
#> SRR1446961 2 0.2356 0.8186 0.000 0.928 0.072
#> SRR1486650 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR1470152 1 0.5431 0.7720 0.716 0.000 0.284
#> SRR1454785 2 0.2625 0.8103 0.000 0.916 0.084
#> SRR1092329 2 0.1643 0.8318 0.000 0.956 0.044
#> SRR1091476 2 0.4842 0.6635 0.000 0.776 0.224
#> SRR1073775 2 0.1860 0.8290 0.000 0.948 0.052
#> SRR1366873 2 0.0424 0.8393 0.000 0.992 0.008
#> SRR1398114 2 0.4974 0.6776 0.000 0.764 0.236
#> SRR1089950 1 0.6204 0.6986 0.576 0.000 0.424
#> SRR1433272 3 0.5016 0.7444 0.000 0.240 0.760
#> SRR1075314 1 0.7293 0.1168 0.496 0.028 0.476
#> SRR1085590 2 0.3941 0.8068 0.000 0.844 0.156
#> SRR1100752 2 0.3038 0.8062 0.000 0.896 0.104
#> SRR1391494 2 0.3752 0.8139 0.000 0.856 0.144
#> SRR1333263 3 0.5016 0.7444 0.000 0.240 0.760
#> SRR1310231 2 0.3116 0.8175 0.000 0.892 0.108
#> SRR1094144 3 0.5058 0.7483 0.000 0.244 0.756
#> SRR1092160 2 0.3192 0.8209 0.000 0.888 0.112
#> SRR1320300 2 0.0592 0.8395 0.000 0.988 0.012
#> SRR1322747 2 0.1163 0.8407 0.000 0.972 0.028
#> SRR1432719 2 0.3879 0.8123 0.000 0.848 0.152
#> SRR1100728 3 0.5178 0.7462 0.000 0.256 0.744
#> SRR1087511 2 0.3752 0.7658 0.000 0.856 0.144
#> SRR1470336 1 0.1753 0.7635 0.952 0.000 0.048
#> SRR1322536 1 0.7395 0.1072 0.492 0.032 0.476
#> SRR1100824 1 0.5905 0.7490 0.648 0.000 0.352
#> SRR1085951 3 0.6144 0.4184 0.132 0.088 0.780
#> SRR1322046 2 0.3551 0.8061 0.000 0.868 0.132
#> SRR1316420 1 0.5560 0.7708 0.700 0.000 0.300
#> SRR1070913 2 0.0892 0.8381 0.000 0.980 0.020
#> SRR1345806 2 0.2959 0.8062 0.000 0.900 0.100
#> SRR1313872 2 0.4235 0.7739 0.000 0.824 0.176
#> SRR1337666 2 0.0747 0.8406 0.000 0.984 0.016
#> SRR1076823 1 0.6476 0.2250 0.548 0.004 0.448
#> SRR1093954 2 0.5058 0.6667 0.000 0.756 0.244
#> SRR1451921 3 0.7422 0.3566 0.344 0.048 0.608
#> SRR1491257 1 0.5591 0.7695 0.696 0.000 0.304
#> SRR1416979 2 0.4291 0.7842 0.000 0.820 0.180
#> SRR1419015 3 0.7014 0.4375 0.208 0.080 0.712
#> SRR817649 2 0.4002 0.7860 0.000 0.840 0.160
#> SRR1466376 2 0.1289 0.8401 0.000 0.968 0.032
#> SRR1392055 2 0.1411 0.8396 0.000 0.964 0.036
#> SRR1120913 2 0.2878 0.8232 0.000 0.904 0.096
#> SRR1120869 3 0.5968 0.5984 0.000 0.364 0.636
#> SRR1319419 2 0.2796 0.8066 0.000 0.908 0.092
#> SRR816495 2 0.2625 0.8103 0.000 0.916 0.084
#> SRR818694 2 0.3116 0.8012 0.000 0.892 0.108
#> SRR1465653 1 0.5845 0.7642 0.688 0.004 0.308
#> SRR1475952 1 0.0892 0.7716 0.980 0.000 0.020
#> SRR1465040 2 0.2878 0.8047 0.000 0.904 0.096
#> SRR1088461 2 0.4931 0.6828 0.000 0.768 0.232
#> SRR810129 2 0.4974 0.6776 0.000 0.764 0.236
#> SRR1400141 2 0.5835 0.6110 0.000 0.660 0.340
#> SRR1349585 1 0.5397 0.7729 0.720 0.000 0.280
#> SRR1437576 2 0.0592 0.8401 0.000 0.988 0.012
#> SRR814407 1 0.2261 0.7694 0.932 0.000 0.068
#> SRR1332403 2 0.3686 0.7969 0.000 0.860 0.140
#> SRR1099598 2 0.6307 -0.1271 0.000 0.512 0.488
#> SRR1327723 2 0.2711 0.8266 0.000 0.912 0.088
#> SRR1392525 3 0.6026 0.4623 0.000 0.376 0.624
#> SRR1320536 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR1083824 2 0.0424 0.8403 0.000 0.992 0.008
#> SRR1351390 1 0.6513 0.6444 0.520 0.004 0.476
#> SRR1309141 2 0.6225 0.2104 0.000 0.568 0.432
#> SRR1452803 2 0.3619 0.7999 0.000 0.864 0.136
#> SRR811631 2 0.1289 0.8344 0.000 0.968 0.032
#> SRR1485563 3 0.5760 0.6332 0.000 0.328 0.672
#> SRR1311531 2 0.2878 0.8047 0.000 0.904 0.096
#> SRR1353076 2 0.4974 0.6764 0.000 0.764 0.236
#> SRR1480831 3 0.6305 0.2233 0.000 0.484 0.516
#> SRR1083892 1 0.5560 0.7698 0.700 0.000 0.300
#> SRR809873 3 0.5953 0.2150 0.280 0.012 0.708
#> SRR1341854 2 0.4178 0.7730 0.000 0.828 0.172
#> SRR1399335 2 0.4291 0.7628 0.000 0.820 0.180
#> SRR1464209 1 0.5591 0.7695 0.696 0.000 0.304
#> SRR1389886 2 0.1964 0.8362 0.000 0.944 0.056
#> SRR1400730 1 0.5882 0.7495 0.652 0.000 0.348
#> SRR1448008 2 0.2878 0.8093 0.000 0.904 0.096
#> SRR1087606 1 0.5859 0.7559 0.656 0.000 0.344
#> SRR1445111 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR816865 3 0.5216 0.7439 0.000 0.260 0.740
#> SRR1323360 2 0.2711 0.8089 0.000 0.912 0.088
#> SRR1417364 2 0.2448 0.8139 0.000 0.924 0.076
#> SRR1480329 2 0.1529 0.8338 0.000 0.960 0.040
#> SRR1403322 1 0.6204 0.2471 0.576 0.000 0.424
#> SRR1093625 1 0.0000 0.7758 1.000 0.000 0.000
#> SRR1479977 2 0.0424 0.8397 0.000 0.992 0.008
#> SRR1082035 1 0.6126 0.7073 0.600 0.000 0.400
#> SRR1393046 2 0.1411 0.8401 0.000 0.964 0.036
#> SRR1466663 3 0.5254 0.7406 0.000 0.264 0.736
#> SRR1384456 1 0.0000 0.7758 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.3688 0.6376 0.000 0.792 0.208 0.000
#> SRR808862 4 0.7919 -0.2348 0.188 0.012 0.368 0.432
#> SRR1500382 2 0.2921 0.6788 0.000 0.860 0.140 0.000
#> SRR1322683 2 0.4197 0.6558 0.000 0.808 0.036 0.156
#> SRR1329811 4 0.6741 0.7884 0.424 0.000 0.092 0.484
#> SRR1087297 2 0.3444 0.6551 0.000 0.816 0.184 0.000
#> SRR1072626 3 0.6457 0.4576 0.000 0.296 0.604 0.100
#> SRR1407428 1 0.0921 0.6523 0.972 0.000 0.000 0.028
#> SRR1321029 2 0.1792 0.7030 0.000 0.932 0.000 0.068
#> SRR1500282 1 0.4967 -0.5598 0.548 0.000 0.000 0.452
#> SRR1100496 3 0.3725 0.5671 0.008 0.000 0.812 0.180
#> SRR1308778 2 0.4981 0.1643 0.000 0.536 0.464 0.000
#> SRR1445304 2 0.4250 0.5654 0.000 0.724 0.276 0.000
#> SRR1099378 3 0.5250 -0.0238 0.008 0.000 0.552 0.440
#> SRR1347412 1 0.0592 0.6367 0.984 0.000 0.000 0.016
#> SRR1099694 2 0.3975 0.6176 0.000 0.760 0.240 0.000
#> SRR1088365 3 0.3837 0.6142 0.000 0.224 0.776 0.000
#> SRR1325752 3 0.2731 0.7010 0.004 0.092 0.896 0.008
#> SRR1416713 2 0.3444 0.6555 0.000 0.816 0.184 0.000
#> SRR1074474 1 0.0000 0.6496 1.000 0.000 0.000 0.000
#> SRR1469369 2 0.6116 0.5151 0.000 0.612 0.068 0.320
#> SRR1400507 2 0.1474 0.7050 0.000 0.948 0.000 0.052
#> SRR1378179 3 0.4830 0.2893 0.000 0.392 0.608 0.000
#> SRR1377905 2 0.3074 0.6740 0.000 0.848 0.152 0.000
#> SRR1089479 1 0.3208 0.5544 0.848 0.000 0.004 0.148
#> SRR1073365 2 0.3837 0.6247 0.000 0.776 0.224 0.000
#> SRR1500306 1 0.6227 0.4560 0.588 0.004 0.056 0.352
#> SRR1101566 2 0.4290 0.6519 0.000 0.800 0.036 0.164
#> SRR1350503 2 0.4922 0.6257 0.000 0.736 0.036 0.228
#> SRR1446007 2 0.5769 0.5716 0.000 0.652 0.056 0.292
#> SRR1102875 2 0.4817 0.3723 0.000 0.612 0.388 0.000
#> SRR1380293 2 0.4730 0.4381 0.000 0.636 0.364 0.000
#> SRR1331198 2 0.1389 0.7040 0.000 0.952 0.048 0.000
#> SRR1092686 3 0.7392 0.2569 0.000 0.248 0.520 0.232
#> SRR1069421 3 0.2546 0.7024 0.000 0.092 0.900 0.008
#> SRR1341650 3 0.2739 0.6649 0.008 0.036 0.912 0.044
#> SRR1357276 2 0.2589 0.6884 0.000 0.884 0.116 0.000
#> SRR1498374 2 0.1792 0.7030 0.000 0.932 0.000 0.068
#> SRR1093721 2 0.3810 0.6999 0.000 0.848 0.060 0.092
#> SRR1464660 4 0.6741 0.7884 0.424 0.000 0.092 0.484
#> SRR1402051 2 0.7344 0.2186 0.000 0.524 0.268 0.208
#> SRR1488734 2 0.4072 0.5970 0.000 0.748 0.252 0.000
#> SRR1082616 3 0.4579 0.5584 0.000 0.032 0.768 0.200
#> SRR1099427 2 0.4197 0.6558 0.000 0.808 0.036 0.156
#> SRR1453093 3 0.7646 0.1682 0.000 0.384 0.408 0.208
#> SRR1357064 4 0.6741 0.7884 0.424 0.000 0.092 0.484
#> SRR811237 3 0.4088 0.6904 0.000 0.140 0.820 0.040
#> SRR1100848 2 0.6050 0.5817 0.000 0.668 0.232 0.100
#> SRR1346755 2 0.4370 0.6557 0.000 0.800 0.044 0.156
#> SRR1472529 2 0.1474 0.7050 0.000 0.948 0.000 0.052
#> SRR1398905 1 0.4995 0.5384 0.720 0.000 0.032 0.248
#> SRR1082733 2 0.3688 0.6382 0.000 0.792 0.208 0.000
#> SRR1308035 2 0.6148 0.5552 0.000 0.636 0.084 0.280
#> SRR1466445 2 0.6016 0.5591 0.000 0.632 0.068 0.300
#> SRR1359080 2 0.1302 0.7046 0.000 0.956 0.044 0.000
#> SRR1455825 2 0.1389 0.7055 0.000 0.952 0.000 0.048
#> SRR1389300 2 0.1302 0.7058 0.000 0.956 0.000 0.044
#> SRR812246 2 0.7395 0.3486 0.000 0.480 0.176 0.344
#> SRR1076632 3 0.2589 0.7010 0.000 0.116 0.884 0.000
#> SRR1415567 1 0.0592 0.6526 0.984 0.000 0.000 0.016
#> SRR1331900 2 0.1389 0.7055 0.000 0.952 0.000 0.048
#> SRR1452099 3 0.3674 0.6074 0.000 0.036 0.848 0.116
#> SRR1352346 1 0.7278 -0.4973 0.528 0.000 0.188 0.284
#> SRR1364034 3 0.4746 0.3504 0.000 0.368 0.632 0.000
#> SRR1086046 3 0.7086 0.4642 0.004 0.140 0.560 0.296
#> SRR1407226 4 0.7273 0.7389 0.400 0.000 0.148 0.452
#> SRR1319363 3 0.5352 0.4906 0.092 0.008 0.760 0.140
#> SRR1446961 2 0.3803 0.6751 0.000 0.836 0.032 0.132
#> SRR1486650 1 0.0000 0.6496 1.000 0.000 0.000 0.000
#> SRR1470152 4 0.6696 0.7837 0.428 0.000 0.088 0.484
#> SRR1454785 2 0.5309 0.6000 0.000 0.700 0.044 0.256
#> SRR1092329 2 0.3542 0.6776 0.000 0.852 0.028 0.120
#> SRR1091476 2 0.6603 0.4818 0.000 0.572 0.100 0.328
#> SRR1073775 2 0.4197 0.6558 0.000 0.808 0.036 0.156
#> SRR1366873 2 0.1474 0.7050 0.000 0.948 0.000 0.052
#> SRR1398114 2 0.4985 0.1555 0.000 0.532 0.468 0.000
#> SRR1089950 4 0.7220 0.4995 0.260 0.000 0.196 0.544
#> SRR1433272 3 0.2988 0.6972 0.000 0.112 0.876 0.012
#> SRR1075314 1 0.8377 0.1729 0.368 0.020 0.360 0.252
#> SRR1085590 2 0.6549 0.5639 0.000 0.612 0.120 0.268
#> SRR1100752 2 0.6133 0.5614 0.000 0.644 0.088 0.268
#> SRR1391494 2 0.5374 0.6128 0.000 0.704 0.244 0.052
#> SRR1333263 3 0.2742 0.6966 0.000 0.076 0.900 0.024
#> SRR1310231 2 0.3801 0.6278 0.000 0.780 0.220 0.000
#> SRR1094144 3 0.2124 0.6985 0.000 0.068 0.924 0.008
#> SRR1092160 2 0.3688 0.6468 0.000 0.792 0.208 0.000
#> SRR1320300 2 0.1389 0.7055 0.000 0.952 0.000 0.048
#> SRR1322747 2 0.2216 0.6955 0.000 0.908 0.092 0.000
#> SRR1432719 2 0.5938 0.5950 0.000 0.676 0.092 0.232
#> SRR1100728 3 0.2546 0.7024 0.000 0.092 0.900 0.008
#> SRR1087511 2 0.6198 0.5131 0.000 0.660 0.116 0.224
#> SRR1470336 1 0.3479 0.6043 0.840 0.000 0.012 0.148
#> SRR1322536 3 0.8387 -0.2228 0.360 0.020 0.364 0.256
#> SRR1100824 4 0.7207 0.7357 0.376 0.000 0.144 0.480
#> SRR1085951 3 0.6058 0.2097 0.028 0.008 0.516 0.448
#> SRR1322046 2 0.3975 0.6147 0.000 0.760 0.240 0.000
#> SRR1316420 4 0.6696 0.7861 0.428 0.000 0.088 0.484
#> SRR1070913 2 0.1743 0.7037 0.000 0.940 0.004 0.056
#> SRR1345806 2 0.5966 0.5668 0.000 0.648 0.072 0.280
#> SRR1313872 2 0.4522 0.5099 0.000 0.680 0.320 0.000
#> SRR1337666 2 0.1302 0.7046 0.000 0.956 0.044 0.000
#> SRR1076823 1 0.8228 0.1773 0.380 0.016 0.372 0.232
#> SRR1093954 2 0.4998 0.0951 0.000 0.512 0.488 0.000
#> SRR1451921 3 0.8102 0.0148 0.280 0.020 0.476 0.224
#> SRR1491257 4 0.6696 0.7861 0.428 0.000 0.088 0.484
#> SRR1416979 2 0.5910 0.5979 0.000 0.688 0.208 0.104
#> SRR1419015 3 0.4685 0.5434 0.052 0.012 0.804 0.132
#> SRR817649 2 0.4382 0.5555 0.000 0.704 0.296 0.000
#> SRR1466376 2 0.2216 0.6955 0.000 0.908 0.092 0.000
#> SRR1392055 2 0.2589 0.6884 0.000 0.884 0.116 0.000
#> SRR1120913 2 0.3311 0.6621 0.000 0.828 0.172 0.000
#> SRR1120869 3 0.3528 0.6494 0.000 0.192 0.808 0.000
#> SRR1319419 2 0.5446 0.5877 0.000 0.680 0.044 0.276
#> SRR816495 2 0.5168 0.6067 0.000 0.712 0.040 0.248
#> SRR818694 2 0.5867 0.5453 0.000 0.688 0.096 0.216
#> SRR1465653 4 0.6741 0.7884 0.424 0.000 0.092 0.484
#> SRR1475952 1 0.2654 0.6299 0.888 0.000 0.004 0.108
#> SRR1465040 2 0.5769 0.5716 0.000 0.652 0.056 0.292
#> SRR1088461 2 0.4977 0.1731 0.000 0.540 0.460 0.000
#> SRR810129 2 0.4985 0.1555 0.000 0.532 0.468 0.000
#> SRR1400141 3 0.7491 0.2179 0.000 0.268 0.500 0.232
#> SRR1349585 4 0.6696 0.7861 0.428 0.000 0.088 0.484
#> SRR1437576 2 0.1042 0.7073 0.000 0.972 0.020 0.008
#> SRR814407 1 0.4833 0.5434 0.740 0.000 0.032 0.228
#> SRR1332403 2 0.4356 0.5456 0.000 0.708 0.292 0.000
#> SRR1099598 3 0.6912 0.4810 0.000 0.272 0.576 0.152
#> SRR1327723 2 0.3311 0.6631 0.000 0.828 0.172 0.000
#> SRR1392525 3 0.3959 0.6867 0.000 0.068 0.840 0.092
#> SRR1320536 1 0.0000 0.6496 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.1356 0.7073 0.000 0.960 0.032 0.008
#> SRR1351390 4 0.6726 0.3157 0.152 0.008 0.200 0.640
#> SRR1309141 3 0.5055 0.3066 0.000 0.368 0.624 0.008
#> SRR1452803 2 0.4331 0.5530 0.000 0.712 0.288 0.000
#> SRR811631 2 0.2401 0.6962 0.000 0.904 0.004 0.092
#> SRR1485563 3 0.4037 0.6933 0.000 0.112 0.832 0.056
#> SRR1311531 2 0.5769 0.5716 0.000 0.652 0.056 0.292
#> SRR1353076 2 0.5277 0.1513 0.000 0.532 0.460 0.008
#> SRR1480831 3 0.5085 0.5532 0.000 0.260 0.708 0.032
#> SRR1083892 4 0.6741 0.7884 0.424 0.000 0.092 0.484
#> SRR809873 3 0.5387 0.4807 0.112 0.008 0.760 0.120
#> SRR1341854 2 0.4830 0.3796 0.000 0.608 0.392 0.000
#> SRR1399335 2 0.4907 0.3110 0.000 0.580 0.420 0.000
#> SRR1464209 4 0.6696 0.7861 0.428 0.000 0.088 0.484
#> SRR1389886 2 0.3219 0.6668 0.000 0.836 0.164 0.000
#> SRR1400730 4 0.6067 0.6747 0.376 0.000 0.052 0.572
#> SRR1448008 2 0.4940 0.6273 0.000 0.776 0.096 0.128
#> SRR1087606 4 0.6775 0.7815 0.412 0.000 0.096 0.492
#> SRR1445111 1 0.0000 0.6496 1.000 0.000 0.000 0.000
#> SRR816865 3 0.2546 0.7024 0.000 0.092 0.900 0.008
#> SRR1323360 2 0.5810 0.5835 0.000 0.672 0.072 0.256
#> SRR1417364 2 0.4761 0.6315 0.000 0.764 0.044 0.192
#> SRR1480329 2 0.4633 0.6559 0.000 0.780 0.048 0.172
#> SRR1403322 1 0.7155 0.3794 0.540 0.000 0.292 0.168
#> SRR1093625 1 0.0000 0.6496 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.1302 0.7058 0.000 0.956 0.000 0.044
#> SRR1082035 4 0.7831 0.5478 0.312 0.000 0.280 0.408
#> SRR1393046 2 0.3024 0.6753 0.000 0.852 0.148 0.000
#> SRR1466663 3 0.3108 0.6985 0.000 0.112 0.872 0.016
#> SRR1384456 1 0.0000 0.6496 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0865 0.6769 0.000 0.972 0.024 0.004 0.000
#> SRR808862 3 0.6513 -0.1860 0.192 0.000 0.424 0.384 0.000
#> SRR1500382 2 0.1270 0.6653 0.000 0.948 0.052 0.000 0.000
#> SRR1322683 3 0.6079 0.4795 0.028 0.320 0.576 0.076 0.000
#> SRR1329811 5 0.0613 0.7996 0.000 0.004 0.008 0.004 0.984
#> SRR1087297 2 0.1041 0.6756 0.000 0.964 0.032 0.004 0.000
#> SRR1072626 4 0.7402 0.0976 0.032 0.352 0.248 0.368 0.000
#> SRR1407428 1 0.2813 0.8290 0.832 0.000 0.000 0.000 0.168
#> SRR1321029 3 0.4450 0.2595 0.000 0.488 0.508 0.004 0.000
#> SRR1500282 5 0.3550 0.4882 0.236 0.000 0.004 0.000 0.760
#> SRR1100496 4 0.3905 0.5542 0.008 0.048 0.096 0.832 0.016
#> SRR1308778 2 0.3366 0.4266 0.000 0.768 0.000 0.232 0.000
#> SRR1445304 2 0.0451 0.6778 0.000 0.988 0.004 0.008 0.000
#> SRR1099378 5 0.5380 0.2030 0.000 0.044 0.004 0.464 0.488
#> SRR1347412 1 0.3177 0.8179 0.792 0.000 0.000 0.000 0.208
#> SRR1099694 2 0.0960 0.6770 0.000 0.972 0.008 0.016 0.004
#> SRR1088365 4 0.4562 0.4222 0.004 0.444 0.004 0.548 0.000
#> SRR1325752 4 0.5104 0.6320 0.000 0.308 0.000 0.632 0.060
#> SRR1416713 2 0.0880 0.6739 0.000 0.968 0.032 0.000 0.000
#> SRR1074474 1 0.3280 0.8279 0.808 0.000 0.004 0.004 0.184
#> SRR1469369 3 0.5046 0.5559 0.068 0.076 0.760 0.096 0.000
#> SRR1400507 3 0.4973 0.2452 0.004 0.480 0.496 0.020 0.000
#> SRR1378179 2 0.4101 0.1857 0.004 0.664 0.000 0.332 0.000
#> SRR1377905 2 0.1544 0.6555 0.000 0.932 0.068 0.000 0.000
#> SRR1089479 1 0.4565 0.7625 0.720 0.000 0.024 0.016 0.240
#> SRR1073365 2 0.0162 0.6781 0.000 0.996 0.004 0.000 0.000
#> SRR1500306 1 0.7577 0.4604 0.500 0.000 0.128 0.240 0.132
#> SRR1101566 3 0.6209 0.4864 0.040 0.312 0.576 0.072 0.000
#> SRR1350503 3 0.5476 0.5883 0.060 0.256 0.660 0.024 0.000
#> SRR1446007 3 0.4451 0.6316 0.060 0.132 0.784 0.024 0.000
#> SRR1102875 2 0.2741 0.5831 0.004 0.860 0.004 0.132 0.000
#> SRR1380293 2 0.1544 0.6534 0.000 0.932 0.000 0.068 0.000
#> SRR1331198 2 0.3430 0.4463 0.000 0.776 0.220 0.000 0.004
#> SRR1092686 3 0.7836 -0.0816 0.060 0.316 0.388 0.232 0.004
#> SRR1069421 4 0.4863 0.6580 0.000 0.272 0.000 0.672 0.056
#> SRR1341650 4 0.4395 0.6444 0.000 0.188 0.000 0.748 0.064
#> SRR1357276 2 0.1965 0.6297 0.000 0.904 0.096 0.000 0.000
#> SRR1498374 3 0.4655 0.2778 0.000 0.476 0.512 0.012 0.000
#> SRR1093721 2 0.5626 0.0384 0.008 0.564 0.364 0.064 0.000
#> SRR1464660 5 0.0451 0.7998 0.000 0.000 0.008 0.004 0.988
#> SRR1402051 3 0.7126 0.4315 0.060 0.180 0.536 0.224 0.000
#> SRR1488734 2 0.0290 0.6770 0.000 0.992 0.000 0.008 0.000
#> SRR1082616 4 0.2268 0.5666 0.012 0.028 0.028 0.924 0.008
#> SRR1099427 3 0.6056 0.4742 0.028 0.328 0.572 0.072 0.000
#> SRR1453093 3 0.7376 0.1101 0.092 0.108 0.448 0.352 0.000
#> SRR1357064 5 0.0727 0.8012 0.004 0.000 0.004 0.012 0.980
#> SRR811237 4 0.4497 0.6549 0.008 0.248 0.028 0.716 0.000
#> SRR1100848 2 0.6533 0.1103 0.024 0.552 0.304 0.116 0.004
#> SRR1346755 3 0.6169 0.4726 0.028 0.332 0.560 0.080 0.000
#> SRR1472529 3 0.4803 0.2210 0.004 0.492 0.492 0.012 0.000
#> SRR1398905 1 0.6878 0.6468 0.580 0.000 0.068 0.152 0.200
#> SRR1082733 2 0.0955 0.6766 0.000 0.968 0.028 0.004 0.000
#> SRR1308035 3 0.5509 0.6177 0.060 0.144 0.724 0.068 0.004
#> SRR1466445 3 0.5134 0.6273 0.060 0.132 0.752 0.052 0.004
#> SRR1359080 2 0.3424 0.4171 0.000 0.760 0.240 0.000 0.000
#> SRR1455825 2 0.4659 -0.2411 0.000 0.500 0.488 0.012 0.000
#> SRR1389300 2 0.4446 -0.1922 0.000 0.520 0.476 0.004 0.000
#> SRR812246 3 0.4686 0.5776 0.068 0.060 0.792 0.076 0.004
#> SRR1076632 4 0.5071 0.5979 0.004 0.340 0.000 0.616 0.040
#> SRR1415567 1 0.3167 0.8296 0.820 0.000 0.004 0.004 0.172
#> SRR1331900 2 0.4656 -0.2224 0.000 0.508 0.480 0.012 0.000
#> SRR1452099 4 0.3427 0.5936 0.004 0.068 0.032 0.864 0.032
#> SRR1352346 5 0.6686 0.4568 0.220 0.044 0.012 0.116 0.608
#> SRR1364034 2 0.4151 0.1478 0.004 0.652 0.000 0.344 0.000
#> SRR1086046 4 0.6351 0.2753 0.120 0.032 0.228 0.616 0.004
#> SRR1407226 5 0.4318 0.6579 0.032 0.000 0.004 0.228 0.736
#> SRR1319363 4 0.3628 0.5363 0.052 0.016 0.004 0.848 0.080
#> SRR1446961 3 0.5495 0.4419 0.048 0.408 0.536 0.008 0.000
#> SRR1486650 1 0.3402 0.8274 0.804 0.000 0.008 0.004 0.184
#> SRR1470152 5 0.0290 0.7982 0.000 0.000 0.008 0.000 0.992
#> SRR1454785 3 0.5461 0.6175 0.060 0.180 0.712 0.044 0.004
#> SRR1092329 3 0.5763 0.4330 0.016 0.364 0.560 0.060 0.000
#> SRR1091476 3 0.5728 0.6096 0.064 0.128 0.724 0.068 0.016
#> SRR1073775 3 0.6193 0.4848 0.036 0.312 0.576 0.076 0.000
#> SRR1366873 2 0.4658 -0.2336 0.000 0.504 0.484 0.012 0.000
#> SRR1398114 2 0.3452 0.4040 0.000 0.756 0.000 0.244 0.000
#> SRR1089950 5 0.6439 0.5713 0.088 0.008 0.044 0.248 0.612
#> SRR1433272 4 0.5260 0.6076 0.000 0.332 0.000 0.604 0.064
#> SRR1075314 4 0.6092 -0.1933 0.412 0.000 0.124 0.464 0.000
#> SRR1085590 3 0.5434 0.6200 0.044 0.192 0.708 0.052 0.004
#> SRR1100752 3 0.5625 0.6145 0.060 0.156 0.712 0.068 0.004
#> SRR1391494 2 0.4359 0.4965 0.004 0.756 0.188 0.052 0.000
#> SRR1333263 4 0.4885 0.6544 0.000 0.276 0.000 0.668 0.056
#> SRR1310231 2 0.0771 0.6775 0.000 0.976 0.020 0.004 0.000
#> SRR1094144 4 0.4531 0.6663 0.004 0.248 0.004 0.716 0.028
#> SRR1092160 2 0.2074 0.6587 0.000 0.920 0.060 0.016 0.004
#> SRR1320300 2 0.4774 -0.1346 0.004 0.540 0.444 0.012 0.000
#> SRR1322747 2 0.2471 0.5809 0.000 0.864 0.136 0.000 0.000
#> SRR1432719 3 0.6262 0.5343 0.060 0.260 0.620 0.052 0.008
#> SRR1100728 4 0.4975 0.6588 0.004 0.276 0.000 0.668 0.052
#> SRR1087511 3 0.6905 0.4669 0.084 0.200 0.584 0.132 0.000
#> SRR1470336 1 0.5113 0.6897 0.756 0.000 0.088 0.084 0.072
#> SRR1322536 4 0.6092 -0.1933 0.412 0.000 0.124 0.464 0.000
#> SRR1100824 5 0.2471 0.7436 0.000 0.000 0.000 0.136 0.864
#> SRR1085951 4 0.6077 0.2072 0.012 0.000 0.312 0.568 0.108
#> SRR1322046 2 0.0613 0.6779 0.004 0.984 0.008 0.004 0.000
#> SRR1316420 5 0.0404 0.8023 0.000 0.000 0.000 0.012 0.988
#> SRR1070913 3 0.5050 0.2540 0.004 0.476 0.496 0.024 0.000
#> SRR1345806 3 0.5339 0.6235 0.060 0.152 0.732 0.052 0.004
#> SRR1313872 2 0.1197 0.6648 0.000 0.952 0.000 0.048 0.000
#> SRR1337666 2 0.3491 0.4332 0.000 0.768 0.228 0.000 0.004
#> SRR1076823 4 0.6300 -0.1756 0.400 0.000 0.120 0.472 0.008
#> SRR1093954 2 0.3817 0.3877 0.004 0.740 0.004 0.252 0.000
#> SRR1451921 4 0.5577 0.1764 0.256 0.000 0.120 0.624 0.000
#> SRR1491257 5 0.0404 0.8023 0.000 0.000 0.000 0.012 0.988
#> SRR1416979 2 0.6476 -0.1488 0.020 0.484 0.384 0.112 0.000
#> SRR1419015 4 0.3221 0.5580 0.024 0.032 0.000 0.868 0.076
#> SRR817649 2 0.0451 0.6776 0.000 0.988 0.000 0.008 0.004
#> SRR1466376 2 0.2280 0.6010 0.000 0.880 0.120 0.000 0.000
#> SRR1392055 2 0.1851 0.6378 0.000 0.912 0.088 0.000 0.000
#> SRR1120913 2 0.1043 0.6712 0.000 0.960 0.040 0.000 0.000
#> SRR1120869 4 0.4874 0.4054 0.004 0.452 0.000 0.528 0.016
#> SRR1319419 3 0.5281 0.6269 0.060 0.160 0.732 0.044 0.004
#> SRR816495 3 0.5351 0.6179 0.060 0.184 0.716 0.036 0.004
#> SRR818694 3 0.6916 0.4694 0.088 0.212 0.580 0.120 0.000
#> SRR1465653 5 0.0613 0.7996 0.000 0.004 0.008 0.004 0.984
#> SRR1475952 1 0.3056 0.8038 0.860 0.000 0.008 0.020 0.112
#> SRR1465040 3 0.4495 0.6317 0.060 0.136 0.780 0.024 0.000
#> SRR1088461 2 0.3579 0.4064 0.000 0.756 0.004 0.240 0.000
#> SRR810129 2 0.3452 0.4040 0.000 0.756 0.000 0.244 0.000
#> SRR1400141 3 0.7789 -0.0268 0.060 0.296 0.412 0.228 0.004
#> SRR1349585 5 0.0727 0.8012 0.004 0.000 0.004 0.012 0.980
#> SRR1437576 2 0.3876 0.2500 0.000 0.684 0.316 0.000 0.000
#> SRR814407 1 0.6488 0.6682 0.592 0.000 0.036 0.140 0.232
#> SRR1332403 2 0.0609 0.6738 0.000 0.980 0.000 0.020 0.000
#> SRR1099598 4 0.8020 0.2008 0.084 0.296 0.276 0.344 0.000
#> SRR1327723 2 0.1121 0.6699 0.000 0.956 0.044 0.000 0.000
#> SRR1392525 4 0.3935 0.6621 0.004 0.200 0.024 0.772 0.000
#> SRR1320536 1 0.3280 0.8279 0.808 0.000 0.004 0.004 0.184
#> SRR1083824 2 0.3809 0.3691 0.000 0.736 0.256 0.008 0.000
#> SRR1351390 5 0.7534 0.4005 0.112 0.000 0.128 0.272 0.488
#> SRR1309141 2 0.4978 -0.2965 0.000 0.496 0.000 0.476 0.028
#> SRR1452803 2 0.0510 0.6749 0.000 0.984 0.000 0.016 0.000
#> SRR811631 3 0.4934 0.3545 0.004 0.432 0.544 0.020 0.000
#> SRR1485563 4 0.3648 0.6595 0.004 0.188 0.016 0.792 0.000
#> SRR1311531 3 0.4859 0.6308 0.060 0.140 0.764 0.032 0.004
#> SRR1353076 2 0.4482 0.3980 0.004 0.712 0.032 0.252 0.000
#> SRR1480831 2 0.4905 -0.2099 0.012 0.516 0.008 0.464 0.000
#> SRR1083892 5 0.0727 0.8012 0.004 0.000 0.004 0.012 0.980
#> SRR809873 4 0.3646 0.5390 0.064 0.016 0.004 0.848 0.068
#> SRR1341854 2 0.2548 0.6108 0.004 0.876 0.004 0.116 0.000
#> SRR1399335 2 0.3274 0.4459 0.000 0.780 0.000 0.220 0.000
#> SRR1464209 5 0.0404 0.8023 0.000 0.000 0.000 0.012 0.988
#> SRR1389886 2 0.1197 0.6676 0.000 0.952 0.048 0.000 0.000
#> SRR1400730 5 0.3113 0.7014 0.016 0.000 0.100 0.020 0.864
#> SRR1448008 3 0.6498 0.4599 0.036 0.308 0.552 0.104 0.000
#> SRR1087606 5 0.0981 0.7991 0.012 0.000 0.008 0.008 0.972
#> SRR1445111 1 0.2966 0.8286 0.816 0.000 0.000 0.000 0.184
#> SRR816865 4 0.4975 0.6588 0.004 0.276 0.000 0.668 0.052
#> SRR1323360 3 0.5604 0.6152 0.060 0.160 0.712 0.064 0.004
#> SRR1417364 3 0.6112 0.5494 0.060 0.292 0.604 0.040 0.004
#> SRR1480329 2 0.7018 -0.2051 0.064 0.424 0.416 0.096 0.000
#> SRR1403322 1 0.5473 0.4166 0.548 0.000 0.048 0.396 0.008
#> SRR1093625 1 0.3280 0.8279 0.808 0.000 0.004 0.004 0.184
#> SRR1479977 2 0.4440 -0.1823 0.000 0.528 0.468 0.004 0.000
#> SRR1082035 5 0.4992 0.5480 0.000 0.028 0.012 0.320 0.640
#> SRR1393046 2 0.1341 0.6642 0.000 0.944 0.056 0.000 0.000
#> SRR1466663 4 0.5197 0.6225 0.000 0.316 0.000 0.620 0.064
#> SRR1384456 1 0.3280 0.8279 0.808 0.000 0.004 0.004 0.184
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.1129 0.7272 0.008 0.964 0.012 0.004 0.000 0.012
#> SRR808862 3 0.7100 0.1177 0.092 0.000 0.444 0.160 0.008 0.296
#> SRR1500382 2 0.1434 0.7223 0.008 0.948 0.020 0.000 0.000 0.024
#> SRR1322683 6 0.5440 0.5515 0.000 0.152 0.296 0.000 0.000 0.552
#> SRR1329811 5 0.0748 0.8343 0.004 0.000 0.000 0.004 0.976 0.016
#> SRR1087297 2 0.1180 0.7257 0.004 0.960 0.024 0.004 0.000 0.008
#> SRR1072626 6 0.6632 0.4409 0.000 0.204 0.088 0.184 0.000 0.524
#> SRR1407428 1 0.2147 0.8049 0.896 0.000 0.000 0.000 0.084 0.020
#> SRR1321029 2 0.6232 -0.2914 0.004 0.372 0.308 0.000 0.000 0.316
#> SRR1500282 5 0.4075 0.5851 0.204 0.000 0.016 0.000 0.744 0.036
#> SRR1100496 4 0.2847 0.6856 0.020 0.012 0.080 0.876 0.004 0.008
#> SRR1308778 2 0.3133 0.5071 0.008 0.780 0.000 0.212 0.000 0.000
#> SRR1445304 2 0.0862 0.7258 0.008 0.972 0.000 0.016 0.000 0.004
#> SRR1099378 4 0.5044 0.0524 0.020 0.008 0.000 0.544 0.404 0.024
#> SRR1347412 1 0.3680 0.7622 0.796 0.000 0.016 0.000 0.148 0.040
#> SRR1099694 2 0.1749 0.7218 0.004 0.936 0.012 0.032 0.000 0.016
#> SRR1088365 4 0.3608 0.7479 0.004 0.248 0.000 0.736 0.000 0.012
#> SRR1325752 4 0.3511 0.7813 0.000 0.200 0.004 0.776 0.016 0.004
#> SRR1416713 2 0.0909 0.7250 0.000 0.968 0.020 0.000 0.000 0.012
#> SRR1074474 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 0.000
#> SRR1469369 6 0.4360 0.4554 0.004 0.016 0.312 0.012 0.000 0.656
#> SRR1400507 6 0.6049 0.4474 0.000 0.292 0.292 0.000 0.000 0.416
#> SRR1378179 2 0.4076 0.2011 0.004 0.636 0.000 0.348 0.000 0.012
#> SRR1377905 2 0.1984 0.7016 0.000 0.912 0.032 0.000 0.000 0.056
#> SRR1089479 1 0.5754 0.6518 0.620 0.000 0.024 0.012 0.124 0.220
#> SRR1073365 2 0.1138 0.7242 0.004 0.960 0.000 0.024 0.000 0.012
#> SRR1500306 6 0.6284 -0.3889 0.288 0.000 0.016 0.092 0.052 0.552
#> SRR1101566 6 0.5497 0.5495 0.004 0.140 0.300 0.000 0.000 0.556
#> SRR1350503 3 0.2355 0.7733 0.004 0.112 0.876 0.000 0.000 0.008
#> SRR1446007 3 0.1261 0.7905 0.000 0.024 0.952 0.000 0.000 0.024
#> SRR1102875 2 0.2214 0.6772 0.004 0.892 0.000 0.092 0.000 0.012
#> SRR1380293 2 0.1082 0.7163 0.004 0.956 0.000 0.040 0.000 0.000
#> SRR1331198 2 0.3395 0.6147 0.004 0.816 0.124 0.000 0.000 0.056
#> SRR1092686 3 0.5187 0.5289 0.008 0.140 0.656 0.192 0.000 0.004
#> SRR1069421 4 0.3154 0.7891 0.004 0.184 0.000 0.800 0.012 0.000
#> SRR1341650 4 0.3021 0.7627 0.024 0.080 0.008 0.868 0.016 0.004
#> SRR1357276 2 0.1909 0.7071 0.004 0.920 0.052 0.000 0.000 0.024
#> SRR1498374 2 0.6241 -0.3182 0.004 0.360 0.308 0.000 0.000 0.328
#> SRR1093721 6 0.6008 0.4678 0.000 0.316 0.168 0.016 0.000 0.500
#> SRR1464660 5 0.0748 0.8343 0.004 0.000 0.000 0.004 0.976 0.016
#> SRR1402051 6 0.5504 0.5362 0.008 0.076 0.244 0.036 0.000 0.636
#> SRR1488734 2 0.1080 0.7203 0.004 0.960 0.000 0.032 0.000 0.004
#> SRR1082616 4 0.2266 0.6930 0.024 0.000 0.012 0.908 0.004 0.052
#> SRR1099427 6 0.5557 0.5498 0.004 0.148 0.300 0.000 0.000 0.548
#> SRR1453093 6 0.5124 0.4560 0.012 0.028 0.140 0.112 0.000 0.708
#> SRR1357064 5 0.0520 0.8353 0.008 0.000 0.000 0.008 0.984 0.000
#> SRR811237 4 0.3770 0.7612 0.000 0.148 0.000 0.776 0.000 0.076
#> SRR1100848 6 0.6296 0.4411 0.004 0.320 0.132 0.040 0.000 0.504
#> SRR1346755 6 0.5558 0.5566 0.000 0.156 0.284 0.004 0.000 0.556
#> SRR1472529 6 0.6061 0.4273 0.000 0.308 0.284 0.000 0.000 0.408
#> SRR1398905 1 0.7335 0.5412 0.488 0.000 0.044 0.096 0.120 0.252
#> SRR1082733 2 0.1109 0.7279 0.004 0.964 0.016 0.012 0.000 0.004
#> SRR1308035 3 0.2122 0.8184 0.008 0.040 0.912 0.040 0.000 0.000
#> SRR1466445 3 0.1546 0.8004 0.000 0.016 0.944 0.020 0.000 0.020
#> SRR1359080 2 0.3777 0.5819 0.004 0.788 0.124 0.000 0.000 0.084
#> SRR1455825 2 0.6112 -0.3091 0.000 0.368 0.300 0.000 0.000 0.332
#> SRR1389300 2 0.6111 -0.2985 0.000 0.372 0.304 0.000 0.000 0.324
#> SRR812246 3 0.2606 0.8005 0.008 0.028 0.896 0.036 0.000 0.032
#> SRR1076632 4 0.3301 0.7740 0.004 0.216 0.000 0.772 0.000 0.008
#> SRR1415567 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 0.000
#> SRR1331900 2 0.6221 -0.2788 0.004 0.380 0.296 0.000 0.000 0.320
#> SRR1452099 4 0.2332 0.7063 0.020 0.008 0.016 0.912 0.004 0.040
#> SRR1352346 5 0.6607 0.2322 0.324 0.064 0.004 0.132 0.476 0.000
#> SRR1364034 2 0.4127 0.1617 0.004 0.620 0.000 0.364 0.000 0.012
#> SRR1086046 6 0.4849 0.0576 0.044 0.004 0.024 0.260 0.000 0.668
#> SRR1407226 5 0.4590 0.5188 0.024 0.000 0.008 0.328 0.632 0.008
#> SRR1319363 4 0.2529 0.6894 0.044 0.000 0.012 0.900 0.020 0.024
#> SRR1446961 3 0.4929 0.2256 0.004 0.324 0.600 0.000 0.000 0.072
#> SRR1486650 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 0.000
#> SRR1470152 5 0.0748 0.8343 0.004 0.000 0.000 0.004 0.976 0.016
#> SRR1454785 3 0.1531 0.8194 0.000 0.068 0.928 0.004 0.000 0.000
#> SRR1092329 6 0.5763 0.5290 0.000 0.208 0.292 0.000 0.000 0.500
#> SRR1091476 3 0.3171 0.7992 0.008 0.048 0.868 0.040 0.004 0.032
#> SRR1073775 6 0.5454 0.5533 0.000 0.156 0.292 0.000 0.000 0.552
#> SRR1366873 2 0.6233 -0.3035 0.004 0.368 0.300 0.000 0.000 0.328
#> SRR1398114 2 0.3189 0.4679 0.004 0.760 0.000 0.236 0.000 0.000
#> SRR1089950 5 0.6265 0.4994 0.052 0.000 0.000 0.188 0.552 0.208
#> SRR1433272 4 0.3836 0.7556 0.004 0.248 0.000 0.728 0.016 0.004
#> SRR1075314 6 0.6152 -0.2901 0.244 0.000 0.012 0.232 0.004 0.508
#> SRR1085590 3 0.4031 0.6856 0.004 0.052 0.796 0.036 0.000 0.112
#> SRR1100752 3 0.2384 0.8209 0.008 0.056 0.896 0.040 0.000 0.000
#> SRR1391494 2 0.5944 -0.1232 0.000 0.476 0.096 0.036 0.000 0.392
#> SRR1333263 4 0.3437 0.7887 0.012 0.160 0.004 0.808 0.012 0.004
#> SRR1310231 2 0.0767 0.7272 0.008 0.976 0.012 0.004 0.000 0.000
#> SRR1094144 4 0.2595 0.7904 0.000 0.160 0.000 0.836 0.000 0.004
#> SRR1092160 2 0.2973 0.6960 0.004 0.872 0.036 0.032 0.000 0.056
#> SRR1320300 2 0.6018 -0.2279 0.000 0.416 0.252 0.000 0.000 0.332
#> SRR1322747 2 0.1867 0.7034 0.000 0.916 0.064 0.000 0.000 0.020
#> SRR1432719 3 0.3271 0.7551 0.004 0.144 0.820 0.028 0.000 0.004
#> SRR1100728 4 0.3121 0.7900 0.004 0.180 0.000 0.804 0.012 0.000
#> SRR1087511 6 0.4476 0.5154 0.004 0.040 0.248 0.012 0.000 0.696
#> SRR1470336 1 0.5080 0.5588 0.516 0.000 0.012 0.028 0.012 0.432
#> SRR1322536 6 0.6118 -0.2787 0.240 0.000 0.012 0.228 0.004 0.516
#> SRR1100824 5 0.3499 0.7031 0.012 0.000 0.008 0.196 0.780 0.004
#> SRR1085951 4 0.6409 -0.0629 0.024 0.000 0.408 0.448 0.044 0.076
#> SRR1322046 2 0.1988 0.7206 0.004 0.924 0.016 0.040 0.000 0.016
#> SRR1316420 5 0.0405 0.8358 0.000 0.000 0.000 0.008 0.988 0.004
#> SRR1070913 6 0.5951 0.5008 0.000 0.268 0.276 0.000 0.000 0.456
#> SRR1345806 3 0.1760 0.8217 0.004 0.048 0.928 0.020 0.000 0.000
#> SRR1313872 2 0.1364 0.7128 0.004 0.944 0.000 0.048 0.000 0.004
#> SRR1337666 2 0.3454 0.6102 0.004 0.812 0.124 0.000 0.000 0.060
#> SRR1076823 6 0.6618 -0.3307 0.256 0.000 0.020 0.284 0.008 0.432
#> SRR1093954 2 0.3767 0.3924 0.004 0.708 0.000 0.276 0.000 0.012
#> SRR1451921 6 0.5765 -0.1891 0.140 0.000 0.008 0.368 0.000 0.484
#> SRR1491257 5 0.0405 0.8358 0.000 0.000 0.000 0.008 0.988 0.004
#> SRR1416979 6 0.6551 0.5421 0.004 0.244 0.216 0.040 0.000 0.496
#> SRR1419015 4 0.2156 0.6979 0.028 0.000 0.012 0.920 0.020 0.020
#> SRR817649 2 0.1036 0.7243 0.008 0.964 0.004 0.024 0.000 0.000
#> SRR1466376 2 0.1890 0.7034 0.000 0.916 0.060 0.000 0.000 0.024
#> SRR1392055 2 0.1890 0.7125 0.008 0.924 0.044 0.000 0.000 0.024
#> SRR1120913 2 0.1088 0.7245 0.000 0.960 0.024 0.000 0.000 0.016
#> SRR1120869 4 0.3840 0.6998 0.008 0.288 0.000 0.696 0.000 0.008
#> SRR1319419 3 0.1327 0.8157 0.000 0.064 0.936 0.000 0.000 0.000
#> SRR816495 3 0.1444 0.8162 0.000 0.072 0.928 0.000 0.000 0.000
#> SRR818694 6 0.4538 0.5184 0.004 0.044 0.248 0.012 0.000 0.692
#> SRR1465653 5 0.0748 0.8343 0.004 0.000 0.000 0.004 0.976 0.016
#> SRR1475952 1 0.2085 0.7807 0.912 0.000 0.000 0.008 0.024 0.056
#> SRR1465040 3 0.1168 0.7941 0.000 0.028 0.956 0.000 0.000 0.016
#> SRR1088461 2 0.3411 0.4768 0.008 0.756 0.000 0.232 0.000 0.004
#> SRR810129 2 0.3329 0.4670 0.004 0.756 0.000 0.236 0.000 0.004
#> SRR1400141 3 0.4848 0.5742 0.008 0.124 0.684 0.184 0.000 0.000
#> SRR1349585 5 0.0665 0.8353 0.008 0.000 0.000 0.008 0.980 0.004
#> SRR1437576 2 0.4261 0.5096 0.000 0.732 0.156 0.000 0.000 0.112
#> SRR814407 1 0.7052 0.5625 0.504 0.000 0.028 0.080 0.132 0.256
#> SRR1332403 2 0.1082 0.7160 0.004 0.956 0.000 0.040 0.000 0.000
#> SRR1099598 6 0.6438 0.4054 0.004 0.148 0.084 0.196 0.000 0.568
#> SRR1327723 2 0.1321 0.7250 0.000 0.952 0.024 0.004 0.000 0.020
#> SRR1392525 4 0.2468 0.7766 0.008 0.092 0.004 0.884 0.000 0.012
#> SRR1320536 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 0.000
#> SRR1083824 2 0.3753 0.5429 0.004 0.748 0.220 0.000 0.000 0.028
#> SRR1351390 6 0.6911 -0.3095 0.056 0.000 0.028 0.120 0.332 0.464
#> SRR1309141 4 0.4613 0.6193 0.016 0.340 0.008 0.624 0.008 0.004
#> SRR1452803 2 0.1049 0.7192 0.008 0.960 0.000 0.032 0.000 0.000
#> SRR811631 6 0.6031 0.4729 0.000 0.268 0.312 0.000 0.000 0.420
#> SRR1485563 4 0.3178 0.7611 0.016 0.080 0.000 0.848 0.000 0.056
#> SRR1311531 3 0.1124 0.8037 0.000 0.036 0.956 0.000 0.000 0.008
#> SRR1353076 2 0.5353 0.3141 0.004 0.604 0.004 0.264 0.000 0.124
#> SRR1480831 4 0.5281 0.2336 0.004 0.448 0.000 0.464 0.000 0.084
#> SRR1083892 5 0.0520 0.8353 0.008 0.000 0.000 0.008 0.984 0.000
#> SRR809873 4 0.2441 0.6889 0.044 0.000 0.012 0.904 0.016 0.024
#> SRR1341854 2 0.2548 0.6679 0.004 0.876 0.004 0.100 0.000 0.016
#> SRR1399335 2 0.3012 0.5254 0.008 0.796 0.000 0.196 0.000 0.000
#> SRR1464209 5 0.0405 0.8358 0.004 0.000 0.000 0.008 0.988 0.000
#> SRR1389886 2 0.1261 0.7261 0.004 0.956 0.028 0.004 0.000 0.008
#> SRR1400730 5 0.2944 0.7582 0.008 0.000 0.088 0.008 0.864 0.032
#> SRR1448008 6 0.5687 0.5548 0.000 0.160 0.284 0.008 0.000 0.548
#> SRR1087606 5 0.0748 0.8333 0.004 0.000 0.000 0.004 0.976 0.016
#> SRR1445111 1 0.2537 0.8031 0.880 0.000 0.008 0.000 0.088 0.024
#> SRR816865 4 0.3121 0.7900 0.004 0.180 0.000 0.804 0.012 0.000
#> SRR1323360 3 0.2384 0.8209 0.008 0.056 0.896 0.040 0.000 0.000
#> SRR1417364 3 0.3183 0.6918 0.004 0.200 0.788 0.000 0.000 0.008
#> SRR1480329 6 0.5516 0.5636 0.004 0.204 0.172 0.008 0.000 0.612
#> SRR1403322 1 0.6290 0.4951 0.472 0.000 0.012 0.260 0.004 0.252
#> SRR1093625 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 0.000
#> SRR1479977 2 0.6195 -0.2381 0.004 0.400 0.292 0.000 0.000 0.304
#> SRR1082035 5 0.5232 0.4626 0.024 0.008 0.004 0.340 0.592 0.032
#> SRR1393046 2 0.1341 0.7213 0.000 0.948 0.028 0.000 0.000 0.024
#> SRR1466663 4 0.3717 0.7783 0.012 0.200 0.000 0.768 0.016 0.004
#> SRR1384456 1 0.1753 0.8060 0.912 0.000 0.004 0.000 0.084 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", "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 17467 rows and 159 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 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 0.986 0.952 0.981 0.4789 0.524 0.524
#> 3 3 0.731 0.807 0.903 0.3815 0.739 0.532
#> 4 4 0.630 0.636 0.783 0.1217 0.833 0.554
#> 5 5 0.795 0.809 0.888 0.0675 0.912 0.679
#> 6 6 0.778 0.718 0.839 0.0428 0.937 0.715
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
#> SRR810713 2 0.0000 0.979 0.000 1.000
#> SRR808862 1 0.0000 0.982 1.000 0.000
#> SRR1500382 2 0.0000 0.979 0.000 1.000
#> SRR1322683 2 0.0000 0.979 0.000 1.000
#> SRR1329811 1 0.0000 0.982 1.000 0.000
#> SRR1087297 2 0.0000 0.979 0.000 1.000
#> SRR1072626 2 0.0000 0.979 0.000 1.000
#> SRR1407428 1 0.0000 0.982 1.000 0.000
#> SRR1321029 2 0.0000 0.979 0.000 1.000
#> SRR1500282 1 0.0000 0.982 1.000 0.000
#> SRR1100496 1 0.0000 0.982 1.000 0.000
#> SRR1308778 2 0.0000 0.979 0.000 1.000
#> SRR1445304 2 0.0000 0.979 0.000 1.000
#> SRR1099378 1 0.0000 0.982 1.000 0.000
#> SRR1347412 1 0.0000 0.982 1.000 0.000
#> SRR1099694 2 0.0000 0.979 0.000 1.000
#> SRR1088365 2 0.0000 0.979 0.000 1.000
#> SRR1325752 1 0.0000 0.982 1.000 0.000
#> SRR1416713 2 0.0000 0.979 0.000 1.000
#> SRR1074474 1 0.0000 0.982 1.000 0.000
#> SRR1469369 2 0.0000 0.979 0.000 1.000
#> SRR1400507 2 0.0000 0.979 0.000 1.000
#> SRR1378179 2 0.0000 0.979 0.000 1.000
#> SRR1377905 2 0.0000 0.979 0.000 1.000
#> SRR1089479 1 0.0000 0.982 1.000 0.000
#> SRR1073365 2 0.0000 0.979 0.000 1.000
#> SRR1500306 1 0.0000 0.982 1.000 0.000
#> SRR1101566 2 0.0000 0.979 0.000 1.000
#> SRR1350503 2 0.0000 0.979 0.000 1.000
#> SRR1446007 2 0.0000 0.979 0.000 1.000
#> SRR1102875 2 0.0000 0.979 0.000 1.000
#> SRR1380293 2 0.0000 0.979 0.000 1.000
#> SRR1331198 2 0.0000 0.979 0.000 1.000
#> SRR1092686 2 0.0000 0.979 0.000 1.000
#> SRR1069421 1 0.2043 0.956 0.968 0.032
#> SRR1341650 1 0.0000 0.982 1.000 0.000
#> SRR1357276 2 0.0000 0.979 0.000 1.000
#> SRR1498374 2 0.0000 0.979 0.000 1.000
#> SRR1093721 2 0.0000 0.979 0.000 1.000
#> SRR1464660 1 0.0000 0.982 1.000 0.000
#> SRR1402051 2 0.9909 0.196 0.444 0.556
#> SRR1488734 2 0.0000 0.979 0.000 1.000
#> SRR1082616 1 0.0000 0.982 1.000 0.000
#> SRR1099427 2 0.0000 0.979 0.000 1.000
#> SRR1453093 2 0.0000 0.979 0.000 1.000
#> SRR1357064 1 0.0000 0.982 1.000 0.000
#> SRR811237 2 0.0000 0.979 0.000 1.000
#> SRR1100848 2 0.0000 0.979 0.000 1.000
#> SRR1346755 2 0.0000 0.979 0.000 1.000
#> SRR1472529 2 0.0000 0.979 0.000 1.000
#> SRR1398905 1 0.0000 0.982 1.000 0.000
#> SRR1082733 2 0.0000 0.979 0.000 1.000
#> SRR1308035 2 0.0000 0.979 0.000 1.000
#> SRR1466445 2 0.0000 0.979 0.000 1.000
#> SRR1359080 2 0.0000 0.979 0.000 1.000
#> SRR1455825 2 0.0000 0.979 0.000 1.000
#> SRR1389300 2 0.0000 0.979 0.000 1.000
#> SRR812246 2 0.9970 0.122 0.468 0.532
#> SRR1076632 1 0.2603 0.946 0.956 0.044
#> SRR1415567 1 0.0000 0.982 1.000 0.000
#> SRR1331900 2 0.0000 0.979 0.000 1.000
#> SRR1452099 1 0.0000 0.982 1.000 0.000
#> SRR1352346 1 0.0000 0.982 1.000 0.000
#> SRR1364034 2 0.0000 0.979 0.000 1.000
#> SRR1086046 1 0.0000 0.982 1.000 0.000
#> SRR1407226 1 0.0000 0.982 1.000 0.000
#> SRR1319363 1 0.0000 0.982 1.000 0.000
#> SRR1446961 2 0.0000 0.979 0.000 1.000
#> SRR1486650 1 0.0000 0.982 1.000 0.000
#> SRR1470152 1 0.0000 0.982 1.000 0.000
#> SRR1454785 2 0.0000 0.979 0.000 1.000
#> SRR1092329 2 0.0000 0.979 0.000 1.000
#> SRR1091476 1 0.6887 0.769 0.816 0.184
#> SRR1073775 2 0.0000 0.979 0.000 1.000
#> SRR1366873 2 0.0000 0.979 0.000 1.000
#> SRR1398114 2 0.0000 0.979 0.000 1.000
#> SRR1089950 1 0.0000 0.982 1.000 0.000
#> SRR1433272 1 0.2043 0.956 0.968 0.032
#> SRR1075314 1 0.0000 0.982 1.000 0.000
#> SRR1085590 2 0.0000 0.979 0.000 1.000
#> SRR1100752 2 0.0000 0.979 0.000 1.000
#> SRR1391494 2 0.0000 0.979 0.000 1.000
#> SRR1333263 1 0.9732 0.318 0.596 0.404
#> SRR1310231 2 0.0000 0.979 0.000 1.000
#> SRR1094144 1 0.2778 0.942 0.952 0.048
#> SRR1092160 2 0.0000 0.979 0.000 1.000
#> SRR1320300 2 0.0000 0.979 0.000 1.000
#> SRR1322747 2 0.0000 0.979 0.000 1.000
#> SRR1432719 2 0.0000 0.979 0.000 1.000
#> SRR1100728 1 0.2778 0.942 0.952 0.048
#> SRR1087511 2 0.0000 0.979 0.000 1.000
#> SRR1470336 1 0.0000 0.982 1.000 0.000
#> SRR1322536 1 0.0000 0.982 1.000 0.000
#> SRR1100824 1 0.0000 0.982 1.000 0.000
#> SRR1085951 1 0.0000 0.982 1.000 0.000
#> SRR1322046 2 0.0000 0.979 0.000 1.000
#> SRR1316420 1 0.0000 0.982 1.000 0.000
#> SRR1070913 2 0.0000 0.979 0.000 1.000
#> SRR1345806 2 0.0000 0.979 0.000 1.000
#> SRR1313872 2 0.0000 0.979 0.000 1.000
#> SRR1337666 2 0.0000 0.979 0.000 1.000
#> SRR1076823 1 0.0000 0.982 1.000 0.000
#> SRR1093954 2 0.0000 0.979 0.000 1.000
#> SRR1451921 1 0.0000 0.982 1.000 0.000
#> SRR1491257 1 0.0000 0.982 1.000 0.000
#> SRR1416979 2 0.0000 0.979 0.000 1.000
#> SRR1419015 1 0.0000 0.982 1.000 0.000
#> SRR817649 2 0.3879 0.902 0.076 0.924
#> SRR1466376 2 0.0000 0.979 0.000 1.000
#> SRR1392055 2 0.0000 0.979 0.000 1.000
#> SRR1120913 2 0.0000 0.979 0.000 1.000
#> SRR1120869 2 0.8443 0.622 0.272 0.728
#> SRR1319419 2 0.0000 0.979 0.000 1.000
#> SRR816495 2 0.0000 0.979 0.000 1.000
#> SRR818694 2 0.0000 0.979 0.000 1.000
#> SRR1465653 1 0.0000 0.982 1.000 0.000
#> SRR1475952 1 0.0000 0.982 1.000 0.000
#> SRR1465040 2 0.0000 0.979 0.000 1.000
#> SRR1088461 2 0.0000 0.979 0.000 1.000
#> SRR810129 2 0.0000 0.979 0.000 1.000
#> SRR1400141 2 0.0000 0.979 0.000 1.000
#> SRR1349585 1 0.0000 0.982 1.000 0.000
#> SRR1437576 2 0.0000 0.979 0.000 1.000
#> SRR814407 1 0.0000 0.982 1.000 0.000
#> SRR1332403 2 0.0000 0.979 0.000 1.000
#> SRR1099598 2 0.0000 0.979 0.000 1.000
#> SRR1327723 2 0.0000 0.979 0.000 1.000
#> SRR1392525 2 0.9491 0.416 0.368 0.632
#> SRR1320536 1 0.0000 0.982 1.000 0.000
#> SRR1083824 2 0.0000 0.979 0.000 1.000
#> SRR1351390 1 0.0000 0.982 1.000 0.000
#> SRR1309141 2 0.6973 0.760 0.188 0.812
#> SRR1452803 2 0.0000 0.979 0.000 1.000
#> SRR811631 2 0.0000 0.979 0.000 1.000
#> SRR1485563 1 0.2948 0.938 0.948 0.052
#> SRR1311531 2 0.0000 0.979 0.000 1.000
#> SRR1353076 2 0.0000 0.979 0.000 1.000
#> SRR1480831 2 0.0000 0.979 0.000 1.000
#> SRR1083892 1 0.0000 0.982 1.000 0.000
#> SRR809873 1 0.0000 0.982 1.000 0.000
#> SRR1341854 2 0.0000 0.979 0.000 1.000
#> SRR1399335 2 0.0000 0.979 0.000 1.000
#> SRR1464209 1 0.0000 0.982 1.000 0.000
#> SRR1389886 2 0.0000 0.979 0.000 1.000
#> SRR1400730 1 0.0000 0.982 1.000 0.000
#> SRR1448008 2 0.0000 0.979 0.000 1.000
#> SRR1087606 1 0.0000 0.982 1.000 0.000
#> SRR1445111 1 0.0000 0.982 1.000 0.000
#> SRR816865 1 0.7528 0.725 0.784 0.216
#> SRR1323360 2 0.0000 0.979 0.000 1.000
#> SRR1417364 2 0.0000 0.979 0.000 1.000
#> SRR1480329 2 0.7056 0.757 0.192 0.808
#> SRR1403322 1 0.0000 0.982 1.000 0.000
#> SRR1093625 1 0.0000 0.982 1.000 0.000
#> SRR1479977 2 0.0000 0.979 0.000 1.000
#> SRR1082035 1 0.0000 0.982 1.000 0.000
#> SRR1393046 2 0.0000 0.979 0.000 1.000
#> SRR1466663 1 0.0376 0.979 0.996 0.004
#> SRR1384456 1 0.0000 0.982 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.5397 0.710 0.000 0.720 0.280
#> SRR808862 1 0.1878 0.919 0.952 0.044 0.004
#> SRR1500382 2 0.6302 0.278 0.000 0.520 0.480
#> SRR1322683 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1329811 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1087297 2 0.5431 0.706 0.000 0.716 0.284
#> SRR1072626 2 0.5465 0.534 0.000 0.712 0.288
#> SRR1407428 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1321029 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1500282 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1100496 1 0.6410 0.452 0.576 0.420 0.004
#> SRR1308778 2 0.1643 0.807 0.000 0.956 0.044
#> SRR1445304 2 0.5291 0.720 0.000 0.732 0.268
#> SRR1099378 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1347412 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1099694 2 0.5397 0.710 0.000 0.720 0.280
#> SRR1088365 2 0.0000 0.800 0.000 1.000 0.000
#> SRR1325752 1 0.5497 0.669 0.708 0.292 0.000
#> SRR1416713 2 0.5397 0.710 0.000 0.720 0.280
#> SRR1074474 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1469369 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1400507 3 0.0747 0.905 0.000 0.016 0.984
#> SRR1378179 2 0.0000 0.800 0.000 1.000 0.000
#> SRR1377905 3 0.6111 0.201 0.000 0.396 0.604
#> SRR1089479 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1073365 2 0.5363 0.714 0.000 0.724 0.276
#> SRR1500306 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1101566 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1350503 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1102875 2 0.1964 0.806 0.000 0.944 0.056
#> SRR1380293 2 0.5291 0.720 0.000 0.732 0.268
#> SRR1331198 3 0.2796 0.840 0.000 0.092 0.908
#> SRR1092686 2 0.1860 0.795 0.000 0.948 0.052
#> SRR1069421 2 0.1031 0.793 0.024 0.976 0.000
#> SRR1341650 1 0.5835 0.619 0.660 0.340 0.000
#> SRR1357276 3 0.3816 0.772 0.000 0.148 0.852
#> SRR1498374 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1093721 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1464660 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1402051 3 0.2793 0.858 0.028 0.044 0.928
#> SRR1488734 2 0.5291 0.720 0.000 0.732 0.268
#> SRR1082616 1 0.5291 0.726 0.732 0.268 0.000
#> SRR1099427 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1453093 3 0.5327 0.567 0.000 0.272 0.728
#> SRR1357064 1 0.0000 0.941 1.000 0.000 0.000
#> SRR811237 2 0.0237 0.800 0.000 0.996 0.004
#> SRR1100848 3 0.1529 0.882 0.000 0.040 0.960
#> SRR1346755 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1472529 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1398905 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1082733 2 0.5363 0.714 0.000 0.724 0.276
#> SRR1308035 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1359080 3 0.2625 0.848 0.000 0.084 0.916
#> SRR1455825 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1389300 3 0.0892 0.903 0.000 0.020 0.980
#> SRR812246 3 0.6201 0.630 0.208 0.044 0.748
#> SRR1076632 2 0.0892 0.794 0.020 0.980 0.000
#> SRR1415567 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1331900 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1452099 1 0.5254 0.730 0.736 0.264 0.000
#> SRR1352346 1 0.0237 0.939 0.996 0.004 0.000
#> SRR1364034 2 0.0000 0.800 0.000 1.000 0.000
#> SRR1086046 1 0.1643 0.920 0.956 0.044 0.000
#> SRR1407226 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1319363 1 0.5291 0.726 0.732 0.268 0.000
#> SRR1446961 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1486650 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1454785 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1092329 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1091476 3 0.5678 0.516 0.316 0.000 0.684
#> SRR1073775 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1366873 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1398114 2 0.1643 0.807 0.000 0.956 0.044
#> SRR1089950 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1433272 2 0.0892 0.794 0.020 0.980 0.000
#> SRR1075314 1 0.1643 0.920 0.956 0.044 0.000
#> SRR1085590 3 0.0237 0.906 0.000 0.004 0.996
#> SRR1100752 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1391494 3 0.5785 0.369 0.000 0.332 0.668
#> SRR1333263 2 0.2772 0.745 0.080 0.916 0.004
#> SRR1310231 2 0.5397 0.710 0.000 0.720 0.280
#> SRR1094144 2 0.1031 0.793 0.024 0.976 0.000
#> SRR1092160 3 0.5465 0.522 0.000 0.288 0.712
#> SRR1320300 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1322747 3 0.5835 0.371 0.000 0.340 0.660
#> SRR1432719 3 0.0424 0.905 0.000 0.008 0.992
#> SRR1100728 2 0.1031 0.793 0.024 0.976 0.000
#> SRR1087511 3 0.1643 0.879 0.000 0.044 0.956
#> SRR1470336 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1322536 1 0.1643 0.920 0.956 0.044 0.000
#> SRR1100824 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1085951 1 0.1878 0.919 0.952 0.044 0.004
#> SRR1322046 2 0.5397 0.710 0.000 0.720 0.280
#> SRR1316420 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1070913 3 0.0747 0.905 0.000 0.016 0.984
#> SRR1345806 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1313872 2 0.5291 0.720 0.000 0.732 0.268
#> SRR1337666 3 0.2711 0.844 0.000 0.088 0.912
#> SRR1076823 1 0.1643 0.920 0.956 0.044 0.000
#> SRR1093954 2 0.1411 0.806 0.000 0.964 0.036
#> SRR1451921 1 0.5291 0.726 0.732 0.268 0.000
#> SRR1491257 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1416979 3 0.1411 0.886 0.000 0.036 0.964
#> SRR1419015 1 0.5291 0.726 0.732 0.268 0.000
#> SRR817649 2 0.6827 0.697 0.192 0.728 0.080
#> SRR1466376 3 0.6062 0.234 0.000 0.384 0.616
#> SRR1392055 3 0.6295 -0.136 0.000 0.472 0.528
#> SRR1120913 2 0.5529 0.690 0.000 0.704 0.296
#> SRR1120869 2 0.0592 0.797 0.012 0.988 0.000
#> SRR1319419 3 0.0000 0.907 0.000 0.000 1.000
#> SRR816495 3 0.0000 0.907 0.000 0.000 1.000
#> SRR818694 3 0.1289 0.889 0.000 0.032 0.968
#> SRR1465653 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1465040 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1088461 2 0.1643 0.807 0.000 0.956 0.044
#> SRR810129 2 0.1643 0.807 0.000 0.956 0.044
#> SRR1400141 2 0.4887 0.676 0.000 0.772 0.228
#> SRR1349585 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1437576 3 0.0892 0.903 0.000 0.020 0.980
#> SRR814407 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1332403 2 0.5216 0.725 0.000 0.740 0.260
#> SRR1099598 2 0.5363 0.552 0.000 0.724 0.276
#> SRR1327723 2 0.5733 0.648 0.000 0.676 0.324
#> SRR1392525 2 0.3045 0.756 0.064 0.916 0.020
#> SRR1320536 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1083824 3 0.1031 0.901 0.000 0.024 0.976
#> SRR1351390 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1309141 2 0.2173 0.807 0.008 0.944 0.048
#> SRR1452803 2 0.5291 0.720 0.000 0.732 0.268
#> SRR811631 3 0.0237 0.907 0.000 0.004 0.996
#> SRR1485563 2 0.5785 0.312 0.332 0.668 0.000
#> SRR1311531 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1353076 2 0.1643 0.807 0.000 0.956 0.044
#> SRR1480831 2 0.0000 0.800 0.000 1.000 0.000
#> SRR1083892 1 0.0000 0.941 1.000 0.000 0.000
#> SRR809873 1 0.5291 0.726 0.732 0.268 0.000
#> SRR1341854 2 0.4178 0.771 0.000 0.828 0.172
#> SRR1399335 2 0.1643 0.807 0.000 0.956 0.044
#> SRR1464209 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1389886 2 0.5431 0.706 0.000 0.716 0.284
#> SRR1400730 1 0.0237 0.938 0.996 0.000 0.004
#> SRR1448008 3 0.1289 0.889 0.000 0.032 0.968
#> SRR1087606 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.941 1.000 0.000 0.000
#> SRR816865 2 0.0892 0.794 0.020 0.980 0.000
#> SRR1323360 3 0.0000 0.907 0.000 0.000 1.000
#> SRR1417364 3 0.0237 0.906 0.000 0.004 0.996
#> SRR1480329 3 0.4963 0.689 0.200 0.008 0.792
#> SRR1403322 1 0.1643 0.920 0.956 0.044 0.000
#> SRR1093625 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1479977 3 0.0892 0.903 0.000 0.020 0.980
#> SRR1082035 1 0.0000 0.941 1.000 0.000 0.000
#> SRR1393046 2 0.6299 0.283 0.000 0.524 0.476
#> SRR1466663 2 0.4605 0.591 0.204 0.796 0.000
#> SRR1384456 1 0.0000 0.941 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.0592 0.8455 0.000 0.984 0.016 0.000
#> SRR808862 4 0.7611 0.1986 0.256 0.000 0.268 0.476
#> SRR1500382 2 0.2011 0.8262 0.000 0.920 0.080 0.000
#> SRR1322683 3 0.2530 0.6502 0.000 0.112 0.888 0.000
#> SRR1329811 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1087297 2 0.1118 0.8446 0.000 0.964 0.036 0.000
#> SRR1072626 4 0.5859 0.1684 0.000 0.032 0.472 0.496
#> SRR1407428 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1321029 3 0.4250 0.5915 0.000 0.276 0.724 0.000
#> SRR1500282 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1100496 4 0.2611 0.5565 0.096 0.000 0.008 0.896
#> SRR1308778 2 0.2760 0.7557 0.000 0.872 0.000 0.128
#> SRR1445304 2 0.0921 0.8341 0.000 0.972 0.000 0.028
#> SRR1099378 1 0.2011 0.8535 0.920 0.000 0.000 0.080
#> SRR1347412 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1099694 2 0.1388 0.8458 0.000 0.960 0.028 0.012
#> SRR1088365 4 0.4761 0.4334 0.000 0.372 0.000 0.628
#> SRR1325752 1 0.4797 0.5158 0.720 0.020 0.000 0.260
#> SRR1416713 2 0.1302 0.8427 0.000 0.956 0.044 0.000
#> SRR1074474 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.1637 0.6049 0.000 0.000 0.940 0.060
#> SRR1400507 3 0.4406 0.5532 0.000 0.300 0.700 0.000
#> SRR1378179 2 0.4072 0.5715 0.000 0.748 0.000 0.252
#> SRR1377905 2 0.2345 0.8095 0.000 0.900 0.100 0.000
#> SRR1089479 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1073365 2 0.1174 0.8448 0.000 0.968 0.020 0.012
#> SRR1500306 1 0.1398 0.8771 0.956 0.000 0.040 0.004
#> SRR1101566 3 0.2469 0.6503 0.000 0.108 0.892 0.000
#> SRR1350503 3 0.5925 0.5699 0.000 0.068 0.648 0.284
#> SRR1446007 3 0.5038 0.5637 0.000 0.020 0.684 0.296
#> SRR1102875 2 0.1867 0.8092 0.000 0.928 0.000 0.072
#> SRR1380293 2 0.1022 0.8329 0.000 0.968 0.000 0.032
#> SRR1331198 2 0.2921 0.7673 0.000 0.860 0.140 0.000
#> SRR1092686 4 0.6094 -0.1945 0.000 0.048 0.416 0.536
#> SRR1069421 4 0.5130 0.5232 0.020 0.312 0.000 0.668
#> SRR1341650 4 0.5018 0.4341 0.332 0.012 0.000 0.656
#> SRR1357276 2 0.2281 0.8136 0.000 0.904 0.096 0.000
#> SRR1498374 3 0.4250 0.5915 0.000 0.276 0.724 0.000
#> SRR1093721 3 0.3726 0.6188 0.000 0.212 0.788 0.000
#> SRR1464660 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1402051 3 0.5926 0.4700 0.012 0.080 0.708 0.200
#> SRR1488734 2 0.0707 0.8371 0.000 0.980 0.000 0.020
#> SRR1082616 4 0.3787 0.5775 0.124 0.000 0.036 0.840
#> SRR1099427 3 0.2408 0.6502 0.000 0.104 0.896 0.000
#> SRR1453093 3 0.5802 0.0227 0.008 0.020 0.568 0.404
#> SRR1357064 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR811237 4 0.6478 0.5216 0.000 0.132 0.236 0.632
#> SRR1100848 3 0.6248 0.4263 0.000 0.120 0.656 0.224
#> SRR1346755 3 0.2593 0.6491 0.000 0.104 0.892 0.004
#> SRR1472529 3 0.4564 0.5163 0.000 0.328 0.672 0.000
#> SRR1398905 1 0.0592 0.9036 0.984 0.000 0.000 0.016
#> SRR1082733 2 0.0592 0.8454 0.000 0.984 0.016 0.000
#> SRR1308035 3 0.5213 0.5443 0.000 0.020 0.652 0.328
#> SRR1466445 3 0.5173 0.5502 0.000 0.020 0.660 0.320
#> SRR1359080 2 0.4164 0.5760 0.000 0.736 0.264 0.000
#> SRR1455825 3 0.4697 0.4823 0.000 0.356 0.644 0.000
#> SRR1389300 3 0.4697 0.4823 0.000 0.356 0.644 0.000
#> SRR812246 3 0.5130 0.5415 0.000 0.016 0.652 0.332
#> SRR1076632 4 0.5289 0.4821 0.020 0.344 0.000 0.636
#> SRR1415567 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1331900 3 0.4843 0.3991 0.000 0.396 0.604 0.000
#> SRR1452099 4 0.5130 0.4240 0.332 0.000 0.016 0.652
#> SRR1352346 1 0.0592 0.9020 0.984 0.000 0.000 0.016
#> SRR1364034 2 0.4431 0.4704 0.000 0.696 0.000 0.304
#> SRR1086046 1 0.7314 0.0381 0.488 0.000 0.164 0.348
#> SRR1407226 1 0.0592 0.9076 0.984 0.000 0.000 0.016
#> SRR1319363 4 0.4855 0.3365 0.400 0.000 0.000 0.600
#> SRR1446961 3 0.6170 0.6104 0.000 0.136 0.672 0.192
#> SRR1486650 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1454785 3 0.5698 0.5517 0.000 0.044 0.636 0.320
#> SRR1092329 3 0.2973 0.6461 0.000 0.144 0.856 0.000
#> SRR1091476 3 0.6658 0.4937 0.060 0.020 0.592 0.328
#> SRR1073775 3 0.2704 0.6493 0.000 0.124 0.876 0.000
#> SRR1366873 3 0.4697 0.4823 0.000 0.356 0.644 0.000
#> SRR1398114 2 0.3024 0.7337 0.000 0.852 0.000 0.148
#> SRR1089950 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1433272 4 0.5193 0.5063 0.020 0.324 0.000 0.656
#> SRR1075314 1 0.6023 0.3097 0.600 0.000 0.056 0.344
#> SRR1085590 3 0.5130 0.5422 0.000 0.016 0.652 0.332
#> SRR1100752 3 0.5773 0.5378 0.000 0.044 0.620 0.336
#> SRR1391494 3 0.4978 0.4745 0.000 0.324 0.664 0.012
#> SRR1333263 4 0.2489 0.5759 0.020 0.068 0.000 0.912
#> SRR1310231 2 0.0469 0.8449 0.000 0.988 0.012 0.000
#> SRR1094144 4 0.5407 0.5395 0.036 0.296 0.000 0.668
#> SRR1092160 2 0.3324 0.7746 0.000 0.852 0.136 0.012
#> SRR1320300 2 0.4992 -0.0406 0.000 0.524 0.476 0.000
#> SRR1322747 2 0.1474 0.8405 0.000 0.948 0.052 0.000
#> SRR1432719 3 0.6951 0.4754 0.000 0.132 0.544 0.324
#> SRR1100728 4 0.5130 0.5232 0.020 0.312 0.000 0.668
#> SRR1087511 3 0.2565 0.6319 0.000 0.056 0.912 0.032
#> SRR1470336 1 0.1211 0.8794 0.960 0.000 0.040 0.000
#> SRR1322536 1 0.6091 0.3014 0.596 0.000 0.060 0.344
#> SRR1100824 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1085951 4 0.6703 0.3678 0.232 0.000 0.156 0.612
#> SRR1322046 2 0.1256 0.8461 0.000 0.964 0.028 0.008
#> SRR1316420 1 0.0469 0.9088 0.988 0.000 0.000 0.012
#> SRR1070913 3 0.4277 0.5519 0.000 0.280 0.720 0.000
#> SRR1345806 3 0.5291 0.5481 0.000 0.024 0.652 0.324
#> SRR1313872 2 0.1398 0.8356 0.000 0.956 0.004 0.040
#> SRR1337666 2 0.3172 0.7429 0.000 0.840 0.160 0.000
#> SRR1076823 1 0.4800 0.3946 0.656 0.000 0.004 0.340
#> SRR1093954 2 0.3400 0.6950 0.000 0.820 0.000 0.180
#> SRR1451921 4 0.6054 0.3853 0.352 0.000 0.056 0.592
#> SRR1491257 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1416979 3 0.6042 0.4373 0.000 0.104 0.672 0.224
#> SRR1419015 4 0.4804 0.3657 0.384 0.000 0.000 0.616
#> SRR817649 2 0.1833 0.8191 0.032 0.944 0.000 0.024
#> SRR1466376 2 0.1557 0.8389 0.000 0.944 0.056 0.000
#> SRR1392055 2 0.2011 0.8263 0.000 0.920 0.080 0.000
#> SRR1120913 2 0.1302 0.8427 0.000 0.956 0.044 0.000
#> SRR1120869 2 0.5427 0.1334 0.016 0.568 0.000 0.416
#> SRR1319419 3 0.5698 0.5517 0.000 0.044 0.636 0.320
#> SRR816495 3 0.5947 0.5539 0.000 0.060 0.628 0.312
#> SRR818694 3 0.3037 0.6344 0.000 0.076 0.888 0.036
#> SRR1465653 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1475952 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1465040 3 0.5038 0.5637 0.000 0.020 0.684 0.296
#> SRR1088461 2 0.3249 0.7440 0.000 0.852 0.008 0.140
#> SRR810129 2 0.3024 0.7337 0.000 0.852 0.000 0.148
#> SRR1400141 4 0.5682 -0.2668 0.000 0.024 0.456 0.520
#> SRR1349585 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1437576 2 0.4624 0.4071 0.000 0.660 0.340 0.000
#> SRR814407 1 0.0188 0.9088 0.996 0.000 0.000 0.004
#> SRR1332403 2 0.1211 0.8285 0.000 0.960 0.000 0.040
#> SRR1099598 4 0.6149 0.1689 0.000 0.048 0.472 0.480
#> SRR1327723 2 0.1302 0.8427 0.000 0.956 0.044 0.000
#> SRR1392525 4 0.0844 0.5260 0.012 0.004 0.004 0.980
#> SRR1320536 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.5122 0.6452 0.000 0.756 0.164 0.080
#> SRR1351390 1 0.0817 0.8943 0.976 0.000 0.024 0.000
#> SRR1309141 4 0.5682 -0.0532 0.000 0.456 0.024 0.520
#> SRR1452803 2 0.0921 0.8341 0.000 0.972 0.000 0.028
#> SRR811631 3 0.3356 0.6503 0.000 0.176 0.824 0.000
#> SRR1485563 4 0.7285 0.5566 0.092 0.064 0.208 0.636
#> SRR1311531 3 0.5085 0.5599 0.000 0.020 0.676 0.304
#> SRR1353076 2 0.7093 0.4116 0.000 0.568 0.220 0.212
#> SRR1480831 4 0.6383 0.5050 0.000 0.292 0.096 0.612
#> SRR1083892 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR809873 4 0.4790 0.3735 0.380 0.000 0.000 0.620
#> SRR1341854 2 0.2760 0.7607 0.000 0.872 0.000 0.128
#> SRR1399335 2 0.2081 0.7973 0.000 0.916 0.000 0.084
#> SRR1464209 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1389886 2 0.1118 0.8444 0.000 0.964 0.036 0.000
#> SRR1400730 1 0.3647 0.7332 0.832 0.000 0.016 0.152
#> SRR1448008 3 0.4718 0.5989 0.000 0.116 0.792 0.092
#> SRR1087606 1 0.0592 0.9082 0.984 0.000 0.000 0.016
#> SRR1445111 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR816865 4 0.5130 0.5232 0.020 0.312 0.000 0.668
#> SRR1323360 3 0.5736 0.5451 0.000 0.044 0.628 0.328
#> SRR1417364 3 0.7203 0.4904 0.000 0.164 0.524 0.312
#> SRR1480329 3 0.6720 0.4570 0.216 0.152 0.628 0.004
#> SRR1403322 1 0.4855 0.2537 0.600 0.000 0.000 0.400
#> SRR1093625 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1479977 3 0.4804 0.4275 0.000 0.384 0.616 0.000
#> SRR1082035 1 0.0000 0.9102 1.000 0.000 0.000 0.000
#> SRR1393046 2 0.1792 0.8328 0.000 0.932 0.068 0.000
#> SRR1466663 4 0.6686 0.5953 0.180 0.200 0.000 0.620
#> SRR1384456 1 0.0000 0.9102 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0162 0.9097 0.000 0.996 0.000 0.000 0.004
#> SRR808862 3 0.4312 0.7146 0.176 0.000 0.772 0.020 0.032
#> SRR1500382 2 0.0404 0.9068 0.000 0.988 0.000 0.000 0.012
#> SRR1322683 5 0.0912 0.8371 0.000 0.016 0.012 0.000 0.972
#> SRR1329811 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1087297 2 0.0000 0.9104 0.000 1.000 0.000 0.000 0.000
#> SRR1072626 5 0.0794 0.8129 0.000 0.000 0.000 0.028 0.972
#> SRR1407428 1 0.0932 0.8832 0.972 0.000 0.004 0.020 0.004
#> SRR1321029 5 0.4416 0.5913 0.000 0.356 0.012 0.000 0.632
#> SRR1500282 1 0.0609 0.8884 0.980 0.000 0.000 0.020 0.000
#> SRR1100496 4 0.3906 0.7977 0.084 0.000 0.112 0.804 0.000
#> SRR1308778 2 0.2329 0.8553 0.000 0.876 0.000 0.124 0.000
#> SRR1445304 2 0.0880 0.9062 0.000 0.968 0.000 0.032 0.000
#> SRR1099378 1 0.3480 0.7206 0.752 0.000 0.000 0.248 0.000
#> SRR1347412 1 0.0324 0.8884 0.992 0.000 0.000 0.004 0.004
#> SRR1099694 2 0.0671 0.9112 0.000 0.980 0.000 0.016 0.004
#> SRR1088365 4 0.2488 0.7910 0.000 0.124 0.004 0.872 0.000
#> SRR1325752 4 0.4227 0.4115 0.420 0.000 0.000 0.580 0.000
#> SRR1416713 2 0.0162 0.9097 0.000 0.996 0.000 0.000 0.004
#> SRR1074474 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
#> SRR1469369 5 0.1124 0.8097 0.000 0.000 0.036 0.004 0.960
#> SRR1400507 5 0.2574 0.8135 0.000 0.112 0.012 0.000 0.876
#> SRR1378179 2 0.3913 0.5537 0.000 0.676 0.000 0.324 0.000
#> SRR1377905 2 0.1908 0.8415 0.000 0.908 0.000 0.000 0.092
#> SRR1089479 1 0.0833 0.8847 0.976 0.000 0.004 0.016 0.004
#> SRR1073365 2 0.0609 0.9104 0.000 0.980 0.000 0.020 0.000
#> SRR1500306 1 0.3351 0.7690 0.828 0.000 0.004 0.020 0.148
#> SRR1101566 5 0.0912 0.8371 0.000 0.016 0.012 0.000 0.972
#> SRR1350503 3 0.1205 0.9309 0.000 0.040 0.956 0.000 0.004
#> SRR1446007 3 0.0404 0.9528 0.000 0.000 0.988 0.000 0.012
#> SRR1102875 2 0.2074 0.8726 0.000 0.896 0.000 0.104 0.000
#> SRR1380293 2 0.1205 0.9043 0.004 0.956 0.000 0.040 0.000
#> SRR1331198 2 0.0880 0.8948 0.000 0.968 0.000 0.000 0.032
#> SRR1092686 3 0.0609 0.9434 0.000 0.000 0.980 0.020 0.000
#> SRR1069421 4 0.1202 0.8309 0.004 0.032 0.004 0.960 0.000
#> SRR1341650 4 0.2177 0.8180 0.080 0.004 0.008 0.908 0.000
#> SRR1357276 2 0.0510 0.9047 0.000 0.984 0.000 0.000 0.016
#> SRR1498374 5 0.4387 0.6017 0.000 0.348 0.012 0.000 0.640
#> SRR1093721 5 0.1082 0.8387 0.000 0.028 0.008 0.000 0.964
#> SRR1464660 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1402051 5 0.0740 0.8325 0.000 0.008 0.008 0.004 0.980
#> SRR1488734 2 0.0404 0.9111 0.000 0.988 0.000 0.012 0.000
#> SRR1082616 4 0.4313 0.8069 0.100 0.000 0.024 0.800 0.076
#> SRR1099427 5 0.0566 0.8330 0.000 0.004 0.012 0.000 0.984
#> SRR1453093 5 0.0963 0.8054 0.000 0.000 0.000 0.036 0.964
#> SRR1357064 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR811237 4 0.3278 0.7665 0.000 0.020 0.000 0.824 0.156
#> SRR1100848 5 0.1243 0.8384 0.000 0.028 0.008 0.004 0.960
#> SRR1346755 5 0.0693 0.8347 0.000 0.008 0.012 0.000 0.980
#> SRR1472529 5 0.3081 0.7899 0.000 0.156 0.012 0.000 0.832
#> SRR1398905 1 0.1059 0.8822 0.968 0.000 0.008 0.020 0.004
#> SRR1082733 2 0.0290 0.9111 0.000 0.992 0.000 0.008 0.000
#> SRR1308035 3 0.0324 0.9549 0.000 0.004 0.992 0.000 0.004
#> SRR1466445 3 0.0404 0.9528 0.000 0.000 0.988 0.000 0.012
#> SRR1359080 2 0.2439 0.8034 0.000 0.876 0.004 0.000 0.120
#> SRR1455825 5 0.4339 0.6192 0.000 0.336 0.012 0.000 0.652
#> SRR1389300 5 0.4482 0.5543 0.000 0.376 0.012 0.000 0.612
#> SRR812246 3 0.0290 0.9480 0.000 0.000 0.992 0.000 0.008
#> SRR1076632 4 0.2166 0.8224 0.012 0.072 0.004 0.912 0.000
#> SRR1415567 1 0.0833 0.8847 0.976 0.000 0.004 0.016 0.004
#> SRR1331900 5 0.4457 0.5679 0.000 0.368 0.012 0.000 0.620
#> SRR1452099 4 0.3436 0.8041 0.080 0.000 0.012 0.852 0.056
#> SRR1352346 1 0.0794 0.8872 0.972 0.000 0.000 0.028 0.000
#> SRR1364034 2 0.4074 0.4648 0.000 0.636 0.000 0.364 0.000
#> SRR1086046 5 0.6858 -0.1195 0.244 0.000 0.008 0.300 0.448
#> SRR1407226 1 0.2020 0.8692 0.900 0.000 0.000 0.100 0.000
#> SRR1319363 4 0.3246 0.7916 0.184 0.000 0.008 0.808 0.000
#> SRR1446961 3 0.3085 0.8193 0.000 0.116 0.852 0.000 0.032
#> SRR1486650 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
#> SRR1470152 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1454785 3 0.0290 0.9547 0.000 0.008 0.992 0.000 0.000
#> SRR1092329 5 0.1281 0.8378 0.000 0.032 0.012 0.000 0.956
#> SRR1091476 3 0.0324 0.9540 0.004 0.004 0.992 0.000 0.000
#> SRR1073775 5 0.1012 0.8379 0.000 0.020 0.012 0.000 0.968
#> SRR1366873 5 0.4323 0.6236 0.000 0.332 0.012 0.000 0.656
#> SRR1398114 2 0.2516 0.8407 0.000 0.860 0.000 0.140 0.000
#> SRR1089950 1 0.0451 0.8878 0.988 0.000 0.000 0.004 0.008
#> SRR1433272 4 0.1124 0.8276 0.004 0.036 0.000 0.960 0.000
#> SRR1075314 1 0.6950 -0.0424 0.416 0.000 0.008 0.312 0.264
#> SRR1085590 3 0.0703 0.9455 0.000 0.000 0.976 0.000 0.024
#> SRR1100752 3 0.0290 0.9547 0.000 0.008 0.992 0.000 0.000
#> SRR1391494 5 0.2122 0.8279 0.000 0.036 0.008 0.032 0.924
#> SRR1333263 4 0.1728 0.8258 0.004 0.020 0.036 0.940 0.000
#> SRR1310231 2 0.0162 0.9107 0.000 0.996 0.000 0.004 0.000
#> SRR1094144 4 0.2437 0.8346 0.060 0.032 0.004 0.904 0.000
#> SRR1092160 2 0.2408 0.8377 0.000 0.892 0.000 0.016 0.092
#> SRR1320300 5 0.4430 0.5828 0.000 0.360 0.012 0.000 0.628
#> SRR1322747 2 0.0162 0.9097 0.000 0.996 0.000 0.000 0.004
#> SRR1432719 3 0.0290 0.9547 0.000 0.008 0.992 0.000 0.000
#> SRR1100728 4 0.1285 0.8300 0.004 0.036 0.004 0.956 0.000
#> SRR1087511 5 0.0324 0.8273 0.000 0.004 0.000 0.004 0.992
#> SRR1470336 1 0.2490 0.8357 0.896 0.000 0.004 0.020 0.080
#> SRR1322536 1 0.6978 -0.0428 0.408 0.000 0.008 0.300 0.284
#> SRR1100824 1 0.2329 0.8571 0.876 0.000 0.000 0.124 0.000
#> SRR1085951 3 0.4914 0.6301 0.092 0.000 0.704 0.204 0.000
#> SRR1322046 2 0.0566 0.9114 0.000 0.984 0.000 0.012 0.004
#> SRR1316420 1 0.1732 0.8779 0.920 0.000 0.000 0.080 0.000
#> SRR1070913 5 0.2006 0.8288 0.000 0.072 0.012 0.000 0.916
#> SRR1345806 3 0.0324 0.9549 0.000 0.004 0.992 0.000 0.004
#> SRR1313872 2 0.2020 0.8752 0.000 0.900 0.000 0.100 0.000
#> SRR1337666 2 0.1043 0.8892 0.000 0.960 0.000 0.000 0.040
#> SRR1076823 1 0.5344 0.2737 0.596 0.000 0.008 0.348 0.048
#> SRR1093954 2 0.2732 0.8215 0.000 0.840 0.000 0.160 0.000
#> SRR1451921 4 0.5075 0.7512 0.124 0.000 0.008 0.720 0.148
#> SRR1491257 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1416979 5 0.1356 0.8384 0.000 0.028 0.012 0.004 0.956
#> SRR1419015 4 0.3365 0.7955 0.180 0.000 0.008 0.808 0.004
#> SRR817649 2 0.0865 0.9096 0.004 0.972 0.000 0.024 0.000
#> SRR1466376 2 0.0162 0.9097 0.000 0.996 0.000 0.000 0.004
#> SRR1392055 2 0.0404 0.9068 0.000 0.988 0.000 0.000 0.012
#> SRR1120913 2 0.0162 0.9097 0.000 0.996 0.000 0.000 0.004
#> SRR1120869 4 0.4122 0.5087 0.004 0.304 0.004 0.688 0.000
#> SRR1319419 3 0.0451 0.9546 0.000 0.008 0.988 0.000 0.004
#> SRR816495 3 0.0451 0.9546 0.000 0.008 0.988 0.000 0.004
#> SRR818694 5 0.0324 0.8273 0.000 0.004 0.000 0.004 0.992
#> SRR1465653 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1475952 1 0.1471 0.8754 0.952 0.000 0.004 0.020 0.024
#> SRR1465040 3 0.0404 0.9528 0.000 0.000 0.988 0.000 0.012
#> SRR1088461 2 0.2424 0.8459 0.000 0.868 0.000 0.132 0.000
#> SRR810129 2 0.2516 0.8407 0.000 0.860 0.000 0.140 0.000
#> SRR1400141 3 0.0566 0.9490 0.000 0.004 0.984 0.012 0.000
#> SRR1349585 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1437576 2 0.2771 0.7811 0.000 0.860 0.012 0.000 0.128
#> SRR814407 1 0.1059 0.8822 0.968 0.000 0.008 0.020 0.004
#> SRR1332403 2 0.1410 0.8964 0.000 0.940 0.000 0.060 0.000
#> SRR1099598 5 0.1282 0.8027 0.000 0.004 0.000 0.044 0.952
#> SRR1327723 2 0.0324 0.9103 0.000 0.992 0.000 0.004 0.004
#> SRR1392525 4 0.3613 0.8025 0.032 0.000 0.104 0.840 0.024
#> SRR1320536 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
#> SRR1083824 2 0.2843 0.7955 0.000 0.848 0.144 0.000 0.008
#> SRR1351390 1 0.1267 0.8787 0.960 0.000 0.004 0.012 0.024
#> SRR1309141 4 0.5751 0.3439 0.000 0.348 0.100 0.552 0.000
#> SRR1452803 2 0.1121 0.9025 0.000 0.956 0.000 0.044 0.000
#> SRR811631 5 0.2522 0.8152 0.000 0.108 0.012 0.000 0.880
#> SRR1485563 4 0.3629 0.8180 0.092 0.000 0.004 0.832 0.072
#> SRR1311531 3 0.0404 0.9528 0.000 0.000 0.988 0.000 0.012
#> SRR1353076 2 0.6622 0.0633 0.000 0.416 0.000 0.220 0.364
#> SRR1480831 4 0.4648 0.7366 0.000 0.104 0.000 0.740 0.156
#> SRR1083892 1 0.2020 0.8710 0.900 0.000 0.000 0.100 0.000
#> SRR809873 4 0.3250 0.8017 0.168 0.000 0.008 0.820 0.004
#> SRR1341854 2 0.2124 0.8766 0.000 0.900 0.000 0.096 0.004
#> SRR1399335 2 0.2074 0.8680 0.000 0.896 0.000 0.104 0.000
#> SRR1464209 1 0.1965 0.8729 0.904 0.000 0.000 0.096 0.000
#> SRR1389886 2 0.0000 0.9104 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 1 0.2989 0.8437 0.868 0.000 0.072 0.060 0.000
#> SRR1448008 5 0.1329 0.8386 0.000 0.032 0.008 0.004 0.956
#> SRR1087606 1 0.1908 0.8743 0.908 0.000 0.000 0.092 0.000
#> SRR1445111 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
#> SRR816865 4 0.1285 0.8300 0.004 0.036 0.004 0.956 0.000
#> SRR1323360 3 0.0290 0.9547 0.000 0.008 0.992 0.000 0.000
#> SRR1417364 3 0.0963 0.9365 0.000 0.036 0.964 0.000 0.000
#> SRR1480329 5 0.0290 0.8315 0.000 0.008 0.000 0.000 0.992
#> SRR1403322 4 0.4501 0.6671 0.276 0.000 0.008 0.696 0.020
#> SRR1093625 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
#> SRR1479977 5 0.4604 0.4395 0.000 0.428 0.012 0.000 0.560
#> SRR1082035 1 0.0404 0.8890 0.988 0.000 0.000 0.012 0.000
#> SRR1393046 2 0.0290 0.9083 0.000 0.992 0.000 0.000 0.008
#> SRR1466663 4 0.1740 0.8259 0.056 0.012 0.000 0.932 0.000
#> SRR1384456 1 0.0451 0.8880 0.988 0.000 0.000 0.008 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.0881 0.846 0.008 0.972 0.000 0.008 0.000 0.012
#> SRR808862 1 0.3765 0.148 0.596 0.000 0.404 0.000 0.000 0.000
#> SRR1500382 2 0.0862 0.846 0.008 0.972 0.000 0.004 0.000 0.016
#> SRR1322683 6 0.0458 0.839 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1329811 5 0.0000 0.859 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1087297 2 0.0665 0.845 0.008 0.980 0.000 0.008 0.004 0.000
#> SRR1072626 6 0.2897 0.785 0.088 0.000 0.000 0.060 0.000 0.852
#> SRR1407428 1 0.3620 0.665 0.648 0.000 0.000 0.000 0.352 0.000
#> SRR1321029 6 0.4174 0.519 0.016 0.352 0.004 0.000 0.000 0.628
#> SRR1500282 5 0.2300 0.728 0.144 0.000 0.000 0.000 0.856 0.000
#> SRR1100496 4 0.4654 0.651 0.252 0.000 0.060 0.676 0.012 0.000
#> SRR1308778 2 0.3690 0.627 0.012 0.700 0.000 0.288 0.000 0.000
#> SRR1445304 2 0.1124 0.842 0.008 0.956 0.000 0.036 0.000 0.000
#> SRR1099378 5 0.3341 0.655 0.068 0.000 0.000 0.116 0.816 0.000
#> SRR1347412 1 0.3857 0.504 0.532 0.000 0.000 0.000 0.468 0.000
#> SRR1099694 2 0.2721 0.834 0.024 0.884 0.000 0.068 0.012 0.012
#> SRR1088365 4 0.0725 0.733 0.012 0.012 0.000 0.976 0.000 0.000
#> SRR1325752 4 0.5068 0.417 0.240 0.000 0.000 0.624 0.136 0.000
#> SRR1416713 2 0.0653 0.845 0.004 0.980 0.000 0.004 0.000 0.012
#> SRR1074474 1 0.3810 0.589 0.572 0.000 0.000 0.000 0.428 0.000
#> SRR1469369 6 0.2446 0.794 0.124 0.000 0.012 0.000 0.000 0.864
#> SRR1400507 6 0.1010 0.833 0.004 0.036 0.000 0.000 0.000 0.960
#> SRR1378179 4 0.4242 -0.134 0.016 0.448 0.000 0.536 0.000 0.000
#> SRR1377905 2 0.2432 0.794 0.024 0.876 0.000 0.000 0.000 0.100
#> SRR1089479 1 0.3647 0.661 0.640 0.000 0.000 0.000 0.360 0.000
#> SRR1073365 2 0.2418 0.826 0.016 0.884 0.000 0.092 0.000 0.008
#> SRR1500306 1 0.3440 0.667 0.776 0.000 0.000 0.000 0.196 0.028
#> SRR1101566 6 0.0603 0.839 0.016 0.004 0.000 0.000 0.000 0.980
#> SRR1350503 3 0.0777 0.933 0.000 0.024 0.972 0.000 0.000 0.004
#> SRR1446007 3 0.0146 0.952 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1102875 2 0.4127 0.533 0.012 0.620 0.000 0.364 0.000 0.004
#> SRR1380293 2 0.2151 0.839 0.012 0.916 0.000 0.032 0.036 0.004
#> SRR1331198 2 0.1515 0.833 0.020 0.944 0.000 0.000 0.008 0.028
#> SRR1092686 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1069421 4 0.0547 0.744 0.020 0.000 0.000 0.980 0.000 0.000
#> SRR1341650 4 0.4700 0.675 0.180 0.000 0.008 0.700 0.112 0.000
#> SRR1357276 2 0.1312 0.842 0.012 0.956 0.000 0.004 0.008 0.020
#> SRR1498374 6 0.4148 0.531 0.016 0.344 0.004 0.000 0.000 0.636
#> SRR1093721 6 0.1196 0.838 0.040 0.008 0.000 0.000 0.000 0.952
#> SRR1464660 5 0.0000 0.859 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1402051 6 0.0547 0.839 0.020 0.000 0.000 0.000 0.000 0.980
#> SRR1488734 2 0.1967 0.828 0.012 0.904 0.000 0.084 0.000 0.000
#> SRR1082616 4 0.4165 0.523 0.420 0.000 0.004 0.568 0.000 0.008
#> SRR1099427 6 0.0458 0.839 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1453093 6 0.3280 0.761 0.152 0.004 0.000 0.032 0.000 0.812
#> SRR1357064 5 0.0146 0.860 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR811237 4 0.3183 0.712 0.060 0.000 0.000 0.828 0.000 0.112
#> SRR1100848 6 0.2598 0.815 0.080 0.016 0.000 0.016 0.004 0.884
#> SRR1346755 6 0.0458 0.839 0.016 0.000 0.000 0.000 0.000 0.984
#> SRR1472529 6 0.1812 0.810 0.008 0.080 0.000 0.000 0.000 0.912
#> SRR1398905 1 0.3101 0.685 0.756 0.000 0.000 0.000 0.244 0.000
#> SRR1082733 2 0.1820 0.841 0.012 0.924 0.000 0.056 0.000 0.008
#> SRR1308035 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1359080 2 0.2623 0.763 0.016 0.852 0.000 0.000 0.000 0.132
#> SRR1455825 6 0.4064 0.507 0.016 0.360 0.000 0.000 0.000 0.624
#> SRR1389300 6 0.4168 0.422 0.016 0.400 0.000 0.000 0.000 0.584
#> SRR812246 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1076632 4 0.0146 0.739 0.004 0.000 0.000 0.996 0.000 0.000
#> SRR1415567 1 0.3647 0.661 0.640 0.000 0.000 0.000 0.360 0.000
#> SRR1331900 6 0.4159 0.430 0.016 0.396 0.000 0.000 0.000 0.588
#> SRR1452099 4 0.5465 0.583 0.308 0.004 0.004 0.584 0.092 0.008
#> SRR1352346 5 0.3855 0.431 0.272 0.000 0.000 0.024 0.704 0.000
#> SRR1364034 4 0.3912 0.230 0.012 0.340 0.000 0.648 0.000 0.000
#> SRR1086046 1 0.2305 0.592 0.892 0.004 0.000 0.004 0.012 0.088
#> SRR1407226 5 0.3514 0.705 0.108 0.000 0.000 0.088 0.804 0.000
#> SRR1319363 4 0.4228 0.518 0.392 0.000 0.000 0.588 0.020 0.000
#> SRR1446961 3 0.4341 0.687 0.016 0.152 0.748 0.000 0.000 0.084
#> SRR1486650 1 0.3838 0.554 0.552 0.000 0.000 0.000 0.448 0.000
#> SRR1470152 5 0.0000 0.859 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1454785 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1092329 6 0.0291 0.839 0.004 0.004 0.000 0.000 0.000 0.992
#> SRR1091476 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 6 0.0291 0.839 0.004 0.004 0.000 0.000 0.000 0.992
#> SRR1366873 6 0.4026 0.526 0.016 0.348 0.000 0.000 0.000 0.636
#> SRR1398114 2 0.3992 0.517 0.012 0.624 0.000 0.364 0.000 0.000
#> SRR1089950 5 0.3330 0.451 0.284 0.000 0.000 0.000 0.716 0.000
#> SRR1433272 4 0.2734 0.730 0.024 0.008 0.000 0.864 0.104 0.000
#> SRR1075314 1 0.1693 0.622 0.932 0.000 0.000 0.004 0.020 0.044
#> SRR1085590 3 0.1452 0.917 0.008 0.004 0.948 0.008 0.000 0.032
#> SRR1100752 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 6 0.1065 0.835 0.008 0.008 0.000 0.020 0.000 0.964
#> SRR1333263 4 0.3300 0.731 0.068 0.000 0.016 0.840 0.076 0.000
#> SRR1310231 2 0.0717 0.844 0.008 0.976 0.000 0.016 0.000 0.000
#> SRR1094144 4 0.0632 0.744 0.024 0.000 0.000 0.976 0.000 0.000
#> SRR1092160 2 0.3637 0.792 0.028 0.832 0.000 0.012 0.044 0.084
#> SRR1320300 6 0.4242 0.402 0.012 0.412 0.000 0.004 0.000 0.572
#> SRR1322747 2 0.0508 0.845 0.000 0.984 0.000 0.004 0.000 0.012
#> SRR1432719 3 0.0146 0.952 0.004 0.000 0.996 0.000 0.000 0.000
#> SRR1100728 4 0.0547 0.744 0.020 0.000 0.000 0.980 0.000 0.000
#> SRR1087511 6 0.1556 0.822 0.080 0.000 0.000 0.000 0.000 0.920
#> SRR1470336 1 0.3398 0.685 0.740 0.000 0.000 0.000 0.252 0.008
#> SRR1322536 1 0.1511 0.618 0.940 0.000 0.000 0.004 0.012 0.044
#> SRR1100824 5 0.1528 0.821 0.016 0.000 0.000 0.048 0.936 0.000
#> SRR1085951 3 0.6817 0.297 0.240 0.000 0.492 0.100 0.168 0.000
#> SRR1322046 2 0.2604 0.821 0.020 0.872 0.000 0.100 0.000 0.008
#> SRR1316420 5 0.0260 0.858 0.008 0.000 0.000 0.000 0.992 0.000
#> SRR1070913 6 0.0603 0.837 0.004 0.016 0.000 0.000 0.000 0.980
#> SRR1345806 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1313872 2 0.3204 0.806 0.016 0.856 0.000 0.036 0.080 0.012
#> SRR1337666 2 0.1806 0.827 0.020 0.928 0.000 0.000 0.008 0.044
#> SRR1076823 1 0.1334 0.628 0.948 0.000 0.000 0.020 0.032 0.000
#> SRR1093954 2 0.4175 0.320 0.012 0.524 0.000 0.464 0.000 0.000
#> SRR1451921 1 0.1563 0.582 0.932 0.000 0.000 0.056 0.000 0.012
#> SRR1491257 5 0.0146 0.860 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1416979 6 0.1251 0.836 0.024 0.008 0.000 0.012 0.000 0.956
#> SRR1419015 4 0.4209 0.531 0.384 0.000 0.000 0.596 0.020 0.000
#> SRR817649 2 0.3970 0.621 0.016 0.712 0.000 0.012 0.260 0.000
#> SRR1466376 2 0.0717 0.842 0.008 0.976 0.000 0.000 0.000 0.016
#> SRR1392055 2 0.0820 0.845 0.012 0.972 0.000 0.000 0.000 0.016
#> SRR1120913 2 0.0653 0.845 0.004 0.980 0.000 0.004 0.000 0.012
#> SRR1120869 4 0.1196 0.725 0.008 0.040 0.000 0.952 0.000 0.000
#> SRR1319419 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR816495 3 0.0146 0.952 0.000 0.004 0.996 0.000 0.000 0.000
#> SRR818694 6 0.1858 0.816 0.092 0.004 0.000 0.000 0.000 0.904
#> SRR1465653 5 0.0000 0.859 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1475952 1 0.3371 0.684 0.708 0.000 0.000 0.000 0.292 0.000
#> SRR1465040 3 0.0146 0.952 0.000 0.004 0.996 0.000 0.000 0.000
#> SRR1088461 2 0.4004 0.565 0.012 0.656 0.000 0.328 0.000 0.004
#> SRR810129 2 0.4004 0.511 0.012 0.620 0.000 0.368 0.000 0.000
#> SRR1400141 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1349585 5 0.0458 0.855 0.016 0.000 0.000 0.000 0.984 0.000
#> SRR1437576 2 0.2706 0.728 0.008 0.832 0.000 0.000 0.000 0.160
#> SRR814407 1 0.3175 0.686 0.744 0.000 0.000 0.000 0.256 0.000
#> SRR1332403 2 0.2692 0.792 0.012 0.840 0.000 0.148 0.000 0.000
#> SRR1099598 6 0.3270 0.764 0.120 0.000 0.000 0.060 0.000 0.820
#> SRR1327723 2 0.1511 0.844 0.012 0.944 0.000 0.032 0.000 0.012
#> SRR1392525 4 0.3702 0.719 0.164 0.000 0.044 0.784 0.000 0.008
#> SRR1320536 1 0.3833 0.561 0.556 0.000 0.000 0.000 0.444 0.000
#> SRR1083824 2 0.3149 0.758 0.016 0.836 0.124 0.000 0.000 0.024
#> SRR1351390 5 0.3852 0.185 0.384 0.000 0.000 0.000 0.612 0.004
#> SRR1309141 4 0.5386 0.647 0.032 0.184 0.064 0.688 0.032 0.000
#> SRR1452803 2 0.1757 0.830 0.008 0.916 0.000 0.076 0.000 0.000
#> SRR811631 6 0.0858 0.834 0.004 0.028 0.000 0.000 0.000 0.968
#> SRR1485563 4 0.3645 0.687 0.236 0.000 0.000 0.740 0.000 0.024
#> SRR1311531 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1353076 4 0.6342 0.159 0.016 0.256 0.000 0.436 0.000 0.292
#> SRR1480831 4 0.5291 0.580 0.128 0.124 0.000 0.688 0.000 0.060
#> SRR1083892 5 0.0146 0.859 0.000 0.000 0.000 0.004 0.996 0.000
#> SRR809873 4 0.4131 0.535 0.384 0.000 0.000 0.600 0.016 0.000
#> SRR1341854 2 0.4382 0.517 0.020 0.612 0.000 0.360 0.000 0.008
#> SRR1399335 2 0.2841 0.772 0.012 0.824 0.000 0.164 0.000 0.000
#> SRR1464209 5 0.0146 0.860 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1389886 2 0.0665 0.846 0.008 0.980 0.000 0.008 0.000 0.004
#> SRR1400730 5 0.1124 0.835 0.008 0.000 0.036 0.000 0.956 0.000
#> SRR1448008 6 0.2046 0.834 0.060 0.032 0.000 0.000 0.000 0.908
#> SRR1087606 5 0.0000 0.859 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1445111 1 0.3756 0.622 0.600 0.000 0.000 0.000 0.400 0.000
#> SRR816865 4 0.0547 0.744 0.020 0.000 0.000 0.980 0.000 0.000
#> SRR1323360 3 0.0000 0.954 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 3 0.1523 0.903 0.008 0.044 0.940 0.000 0.000 0.008
#> SRR1480329 6 0.1700 0.822 0.080 0.000 0.000 0.000 0.004 0.916
#> SRR1403322 1 0.2214 0.575 0.888 0.000 0.000 0.096 0.016 0.000
#> SRR1093625 1 0.3804 0.594 0.576 0.000 0.000 0.000 0.424 0.000
#> SRR1479977 2 0.4260 -0.129 0.016 0.512 0.000 0.000 0.000 0.472
#> SRR1082035 5 0.2941 0.593 0.220 0.000 0.000 0.000 0.780 0.000
#> SRR1393046 2 0.0951 0.845 0.008 0.968 0.000 0.004 0.000 0.020
#> SRR1466663 4 0.3943 0.706 0.076 0.008 0.000 0.776 0.140 0.000
#> SRR1384456 1 0.3828 0.570 0.560 0.000 0.000 0.000 0.440 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "pam"]
# you can also extract it by
# res = res_list["MAD:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 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 0.257 0.685 0.834 0.4612 0.511 0.511
#> 3 3 0.387 0.722 0.843 0.2982 0.847 0.717
#> 4 4 0.413 0.484 0.689 0.1808 0.756 0.483
#> 5 5 0.640 0.689 0.828 0.0690 0.791 0.431
#> 6 6 0.699 0.660 0.814 0.0583 0.895 0.613
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
#> SRR810713 2 0.0376 0.8391 0.004 0.996
#> SRR808862 1 0.6048 0.7433 0.852 0.148
#> SRR1500382 2 0.0000 0.8396 0.000 1.000
#> SRR1322683 2 0.0938 0.8373 0.012 0.988
#> SRR1329811 1 0.9580 0.5051 0.620 0.380
#> SRR1087297 2 0.2043 0.8286 0.032 0.968
#> SRR1072626 2 0.5519 0.7690 0.128 0.872
#> SRR1407428 1 0.1414 0.7131 0.980 0.020
#> SRR1321029 2 0.0000 0.8396 0.000 1.000
#> SRR1500282 1 0.2236 0.7109 0.964 0.036
#> SRR1100496 1 0.7745 0.7422 0.772 0.228
#> SRR1308778 2 0.2603 0.8228 0.044 0.956
#> SRR1445304 2 0.0000 0.8396 0.000 1.000
#> SRR1099378 1 0.5059 0.7454 0.888 0.112
#> SRR1347412 1 0.4298 0.7096 0.912 0.088
#> SRR1099694 2 0.2603 0.8301 0.044 0.956
#> SRR1088365 1 0.9087 0.6973 0.676 0.324
#> SRR1325752 1 0.7883 0.7446 0.764 0.236
#> SRR1416713 2 0.2043 0.8286 0.032 0.968
#> SRR1074474 1 0.0938 0.7119 0.988 0.012
#> SRR1469369 2 0.5842 0.7658 0.140 0.860
#> SRR1400507 2 0.0000 0.8396 0.000 1.000
#> SRR1378179 2 0.8327 0.4898 0.264 0.736
#> SRR1377905 2 0.0938 0.8373 0.012 0.988
#> SRR1089479 1 0.0000 0.7113 1.000 0.000
#> SRR1073365 2 0.2423 0.8245 0.040 0.960
#> SRR1500306 2 0.8144 0.6495 0.252 0.748
#> SRR1101566 2 0.5737 0.7422 0.136 0.864
#> SRR1350503 2 0.0000 0.8396 0.000 1.000
#> SRR1446007 2 0.2603 0.8257 0.044 0.956
#> SRR1102875 2 0.2603 0.8228 0.044 0.956
#> SRR1380293 2 0.0938 0.8373 0.012 0.988
#> SRR1331198 2 0.0938 0.8373 0.012 0.988
#> SRR1092686 1 0.9427 0.6499 0.640 0.360
#> SRR1069421 1 0.8267 0.7343 0.740 0.260
#> SRR1341650 1 0.7745 0.7422 0.772 0.228
#> SRR1357276 2 0.0000 0.8396 0.000 1.000
#> SRR1498374 2 0.0000 0.8396 0.000 1.000
#> SRR1093721 2 0.0000 0.8396 0.000 1.000
#> SRR1464660 1 0.9286 0.5293 0.656 0.344
#> SRR1402051 2 0.8207 0.6002 0.256 0.744
#> SRR1488734 2 0.2236 0.8272 0.036 0.964
#> SRR1082616 1 0.7453 0.7472 0.788 0.212
#> SRR1099427 2 0.3584 0.8142 0.068 0.932
#> SRR1453093 2 0.6623 0.7382 0.172 0.828
#> SRR1357064 1 0.5059 0.7001 0.888 0.112
#> SRR811237 2 0.9209 0.4394 0.336 0.664
#> SRR1100848 2 0.5059 0.7922 0.112 0.888
#> SRR1346755 2 0.5629 0.7704 0.132 0.868
#> SRR1472529 2 0.0000 0.8396 0.000 1.000
#> SRR1398905 1 0.2603 0.7109 0.956 0.044
#> SRR1082733 2 0.9552 -0.0369 0.376 0.624
#> SRR1308035 1 0.9710 0.6262 0.600 0.400
#> SRR1466445 1 0.9833 0.5899 0.576 0.424
#> SRR1359080 2 0.0938 0.8373 0.012 0.988
#> SRR1455825 2 0.0376 0.8391 0.004 0.996
#> SRR1389300 2 0.0000 0.8396 0.000 1.000
#> SRR812246 2 0.6531 0.7422 0.168 0.832
#> SRR1076632 1 0.9775 0.5717 0.588 0.412
#> SRR1415567 1 0.0000 0.7113 1.000 0.000
#> SRR1331900 2 0.0000 0.8396 0.000 1.000
#> SRR1452099 1 0.8081 0.7374 0.752 0.248
#> SRR1352346 2 0.8955 0.5496 0.312 0.688
#> SRR1364034 1 0.9996 0.4549 0.512 0.488
#> SRR1086046 2 0.6148 0.7766 0.152 0.848
#> SRR1407226 1 0.0938 0.7119 0.988 0.012
#> SRR1319363 1 0.5294 0.7453 0.880 0.120
#> SRR1446961 2 0.0938 0.8373 0.012 0.988
#> SRR1486650 1 0.5294 0.6870 0.880 0.120
#> SRR1470152 2 0.9944 0.1776 0.456 0.544
#> SRR1454785 1 0.9933 0.5582 0.548 0.452
#> SRR1092329 2 0.1184 0.8369 0.016 0.984
#> SRR1091476 1 0.9248 0.6418 0.660 0.340
#> SRR1073775 2 0.0000 0.8396 0.000 1.000
#> SRR1366873 2 0.0000 0.8396 0.000 1.000
#> SRR1398114 2 0.9933 -0.3322 0.452 0.548
#> SRR1089950 2 0.8813 0.5586 0.300 0.700
#> SRR1433272 1 0.9909 0.5501 0.556 0.444
#> SRR1075314 2 0.9686 0.4392 0.396 0.604
#> SRR1085590 1 0.9710 0.6262 0.600 0.400
#> SRR1100752 1 0.9933 0.5582 0.548 0.452
#> SRR1391494 2 0.6148 0.7392 0.152 0.848
#> SRR1333263 1 0.8555 0.7217 0.720 0.280
#> SRR1310231 2 0.2043 0.8286 0.032 0.968
#> SRR1094144 1 0.8327 0.7339 0.736 0.264
#> SRR1092160 2 0.0938 0.8373 0.012 0.988
#> SRR1320300 2 0.0000 0.8396 0.000 1.000
#> SRR1322747 2 0.0000 0.8396 0.000 1.000
#> SRR1432719 2 0.9996 -0.4269 0.488 0.512
#> SRR1100728 1 0.8386 0.7274 0.732 0.268
#> SRR1087511 2 0.6801 0.7212 0.180 0.820
#> SRR1470336 2 0.8661 0.5911 0.288 0.712
#> SRR1322536 2 0.9358 0.4895 0.352 0.648
#> SRR1100824 1 0.0000 0.7113 1.000 0.000
#> SRR1085951 1 0.6343 0.7461 0.840 0.160
#> SRR1322046 1 0.9963 0.4788 0.536 0.464
#> SRR1316420 2 0.9815 0.3510 0.420 0.580
#> SRR1070913 2 0.0000 0.8396 0.000 1.000
#> SRR1345806 1 0.9993 0.4647 0.516 0.484
#> SRR1313872 1 0.9993 0.5020 0.516 0.484
#> SRR1337666 2 0.0938 0.8373 0.012 0.988
#> SRR1076823 1 0.2603 0.7324 0.956 0.044
#> SRR1093954 2 0.2603 0.8228 0.044 0.956
#> SRR1451921 1 0.7815 0.7420 0.768 0.232
#> SRR1491257 1 0.8081 0.7044 0.752 0.248
#> SRR1416979 2 0.7674 0.6531 0.224 0.776
#> SRR1419015 1 0.7453 0.7468 0.788 0.212
#> SRR817649 2 0.2236 0.8338 0.036 0.964
#> SRR1466376 2 0.0000 0.8396 0.000 1.000
#> SRR1392055 2 0.0000 0.8396 0.000 1.000
#> SRR1120913 2 0.0938 0.8373 0.012 0.988
#> SRR1120869 1 0.9358 0.6676 0.648 0.352
#> SRR1319419 2 0.9170 0.1595 0.332 0.668
#> SRR816495 2 0.0938 0.8373 0.012 0.988
#> SRR818694 2 0.4939 0.7936 0.108 0.892
#> SRR1465653 2 0.7950 0.6160 0.240 0.760
#> SRR1475952 2 0.9998 0.2589 0.492 0.508
#> SRR1465040 2 0.2778 0.8243 0.048 0.952
#> SRR1088461 2 0.9963 -0.3620 0.464 0.536
#> SRR810129 2 0.5519 0.7487 0.128 0.872
#> SRR1400141 1 0.9710 0.6262 0.600 0.400
#> SRR1349585 1 0.4562 0.7000 0.904 0.096
#> SRR1437576 2 0.0000 0.8396 0.000 1.000
#> SRR814407 1 0.2236 0.7115 0.964 0.036
#> SRR1332403 2 0.9909 -0.2998 0.444 0.556
#> SRR1099598 2 0.8081 0.6730 0.248 0.752
#> SRR1327723 2 0.2043 0.8286 0.032 0.968
#> SRR1392525 1 0.8861 0.7050 0.696 0.304
#> SRR1320536 1 0.0938 0.7119 0.988 0.012
#> SRR1083824 2 0.0938 0.8373 0.012 0.988
#> SRR1351390 2 0.7883 0.6634 0.236 0.764
#> SRR1309141 1 0.9686 0.6468 0.604 0.396
#> SRR1452803 2 0.2603 0.8228 0.044 0.956
#> SRR811631 2 0.0938 0.8373 0.012 0.988
#> SRR1485563 1 0.8016 0.7339 0.756 0.244
#> SRR1311531 2 0.1633 0.8350 0.024 0.976
#> SRR1353076 2 0.5519 0.7677 0.128 0.872
#> SRR1480831 2 0.5629 0.7650 0.132 0.868
#> SRR1083892 1 0.4562 0.7000 0.904 0.096
#> SRR809873 1 0.5294 0.7453 0.880 0.120
#> SRR1341854 1 0.9732 0.6181 0.596 0.404
#> SRR1399335 1 1.0000 0.4960 0.500 0.500
#> SRR1464209 1 0.4161 0.7018 0.916 0.084
#> SRR1389886 2 0.0000 0.8396 0.000 1.000
#> SRR1400730 1 0.6148 0.7041 0.848 0.152
#> SRR1448008 2 0.3431 0.8152 0.064 0.936
#> SRR1087606 2 0.8661 0.5626 0.288 0.712
#> SRR1445111 1 0.7883 0.5597 0.764 0.236
#> SRR816865 1 0.8443 0.7258 0.728 0.272
#> SRR1323360 1 0.9710 0.6262 0.600 0.400
#> SRR1417364 2 0.0938 0.8373 0.012 0.988
#> SRR1480329 2 0.7139 0.7034 0.196 0.804
#> SRR1403322 1 0.5294 0.7453 0.880 0.120
#> SRR1093625 1 0.0938 0.7119 0.988 0.012
#> SRR1479977 2 0.0000 0.8396 0.000 1.000
#> SRR1082035 1 0.9460 0.5377 0.636 0.364
#> SRR1393046 2 0.0000 0.8396 0.000 1.000
#> SRR1466663 1 0.8661 0.7283 0.712 0.288
#> SRR1384456 1 0.0938 0.7119 0.988 0.012
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.1860 0.819 0.000 0.948 0.052
#> SRR808862 3 0.1182 0.767 0.012 0.012 0.976
#> SRR1500382 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1322683 2 0.0424 0.833 0.000 0.992 0.008
#> SRR1329811 2 0.9683 -0.351 0.216 0.416 0.368
#> SRR1087297 2 0.0892 0.829 0.000 0.980 0.020
#> SRR1072626 2 0.5327 0.695 0.000 0.728 0.272
#> SRR1407428 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1321029 2 0.3686 0.788 0.000 0.860 0.140
#> SRR1500282 1 0.0747 0.903 0.984 0.000 0.016
#> SRR1100496 3 0.0000 0.763 0.000 0.000 1.000
#> SRR1308778 2 0.2165 0.811 0.000 0.936 0.064
#> SRR1445304 2 0.1031 0.829 0.000 0.976 0.024
#> SRR1099378 3 0.5174 0.733 0.128 0.048 0.824
#> SRR1347412 1 0.0237 0.907 0.996 0.000 0.004
#> SRR1099694 2 0.0424 0.831 0.000 0.992 0.008
#> SRR1088365 3 0.3715 0.768 0.004 0.128 0.868
#> SRR1325752 3 0.6699 0.730 0.092 0.164 0.744
#> SRR1416713 2 0.0237 0.832 0.000 0.996 0.004
#> SRR1074474 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1469369 2 0.5465 0.677 0.000 0.712 0.288
#> SRR1400507 2 0.0424 0.833 0.000 0.992 0.008
#> SRR1378179 2 0.6140 0.211 0.000 0.596 0.404
#> SRR1377905 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1089479 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1073365 2 0.1031 0.829 0.000 0.976 0.024
#> SRR1500306 2 0.7772 0.676 0.172 0.676 0.152
#> SRR1101566 2 0.5581 0.758 0.036 0.788 0.176
#> SRR1350503 2 0.3619 0.790 0.000 0.864 0.136
#> SRR1446007 2 0.4702 0.750 0.000 0.788 0.212
#> SRR1102875 2 0.2356 0.810 0.000 0.928 0.072
#> SRR1380293 2 0.0424 0.831 0.000 0.992 0.008
#> SRR1331198 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1092686 3 0.1964 0.769 0.000 0.056 0.944
#> SRR1069421 3 0.3918 0.765 0.004 0.140 0.856
#> SRR1341650 3 0.1753 0.759 0.048 0.000 0.952
#> SRR1357276 2 0.0237 0.832 0.000 0.996 0.004
#> SRR1498374 2 0.3686 0.788 0.000 0.860 0.140
#> SRR1093721 2 0.3551 0.792 0.000 0.868 0.132
#> SRR1464660 3 0.9783 0.367 0.256 0.312 0.432
#> SRR1402051 2 0.6910 0.708 0.120 0.736 0.144
#> SRR1488734 2 0.0592 0.831 0.000 0.988 0.012
#> SRR1082616 3 0.0000 0.763 0.000 0.000 1.000
#> SRR1099427 2 0.5461 0.746 0.008 0.748 0.244
#> SRR1453093 2 0.6744 0.654 0.032 0.668 0.300
#> SRR1357064 1 0.8337 0.119 0.536 0.088 0.376
#> SRR811237 2 0.6225 0.402 0.000 0.568 0.432
#> SRR1100848 2 0.4178 0.767 0.000 0.828 0.172
#> SRR1346755 2 0.5859 0.641 0.000 0.656 0.344
#> SRR1472529 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1398905 3 0.3310 0.767 0.028 0.064 0.908
#> SRR1082733 2 0.6260 -0.214 0.000 0.552 0.448
#> SRR1308035 3 0.2261 0.765 0.000 0.068 0.932
#> SRR1466445 3 0.3116 0.761 0.000 0.108 0.892
#> SRR1359080 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.832 0.000 1.000 0.000
#> SRR812246 2 0.5431 0.687 0.000 0.716 0.284
#> SRR1076632 3 0.3481 0.769 0.052 0.044 0.904
#> SRR1415567 1 0.1289 0.883 0.968 0.000 0.032
#> SRR1331900 2 0.0237 0.833 0.000 0.996 0.004
#> SRR1452099 3 0.0747 0.767 0.000 0.016 0.984
#> SRR1352346 2 0.6600 0.451 0.384 0.604 0.012
#> SRR1364034 3 0.5650 0.667 0.000 0.312 0.688
#> SRR1086046 2 0.7250 0.664 0.056 0.656 0.288
#> SRR1407226 3 0.6180 0.308 0.416 0.000 0.584
#> SRR1319363 3 0.4937 0.715 0.148 0.028 0.824
#> SRR1446961 2 0.2066 0.822 0.000 0.940 0.060
#> SRR1486650 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1470152 1 0.4326 0.761 0.844 0.144 0.012
#> SRR1454785 3 0.4121 0.726 0.000 0.168 0.832
#> SRR1092329 2 0.3879 0.805 0.000 0.848 0.152
#> SRR1091476 3 0.3038 0.762 0.000 0.104 0.896
#> SRR1073775 2 0.3038 0.805 0.000 0.896 0.104
#> SRR1366873 2 0.0237 0.833 0.000 0.996 0.004
#> SRR1398114 3 0.6154 0.525 0.000 0.408 0.592
#> SRR1089950 2 0.7101 0.672 0.216 0.704 0.080
#> SRR1433272 3 0.5706 0.662 0.000 0.320 0.680
#> SRR1075314 2 0.8622 0.539 0.132 0.572 0.296
#> SRR1085590 3 0.3192 0.772 0.000 0.112 0.888
#> SRR1100752 3 0.4178 0.726 0.000 0.172 0.828
#> SRR1391494 2 0.5119 0.777 0.028 0.812 0.160
#> SRR1333263 3 0.2448 0.780 0.000 0.076 0.924
#> SRR1310231 2 0.0892 0.833 0.000 0.980 0.020
#> SRR1094144 3 0.4741 0.757 0.020 0.152 0.828
#> SRR1092160 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1320300 2 0.1860 0.817 0.000 0.948 0.052
#> SRR1322747 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1432719 3 0.4504 0.729 0.000 0.196 0.804
#> SRR1100728 3 0.3686 0.764 0.000 0.140 0.860
#> SRR1087511 2 0.5986 0.735 0.024 0.736 0.240
#> SRR1470336 1 0.6034 0.633 0.752 0.212 0.036
#> SRR1322536 2 0.8543 0.544 0.128 0.580 0.292
#> SRR1100824 3 0.5406 0.649 0.224 0.012 0.764
#> SRR1085951 3 0.0661 0.764 0.004 0.008 0.988
#> SRR1322046 3 0.5560 0.680 0.000 0.300 0.700
#> SRR1316420 2 0.9298 0.184 0.376 0.460 0.164
#> SRR1070913 2 0.0237 0.833 0.000 0.996 0.004
#> SRR1345806 3 0.3192 0.759 0.000 0.112 0.888
#> SRR1313872 3 0.6252 0.520 0.000 0.444 0.556
#> SRR1337666 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1076823 3 0.4504 0.677 0.196 0.000 0.804
#> SRR1093954 2 0.2537 0.809 0.000 0.920 0.080
#> SRR1451921 3 0.4768 0.766 0.052 0.100 0.848
#> SRR1491257 3 0.9539 0.334 0.336 0.204 0.460
#> SRR1416979 2 0.6307 0.356 0.000 0.512 0.488
#> SRR1419015 3 0.1753 0.759 0.048 0.000 0.952
#> SRR817649 2 0.1753 0.824 0.000 0.952 0.048
#> SRR1466376 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1392055 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1120913 2 0.0892 0.830 0.000 0.980 0.020
#> SRR1120869 3 0.1753 0.779 0.000 0.048 0.952
#> SRR1319419 3 0.6026 0.418 0.000 0.376 0.624
#> SRR816495 2 0.3941 0.784 0.000 0.844 0.156
#> SRR818694 2 0.5881 0.735 0.016 0.728 0.256
#> SRR1465653 2 0.6096 0.592 0.280 0.704 0.016
#> SRR1475952 1 0.0237 0.906 0.996 0.000 0.004
#> SRR1465040 2 0.4887 0.737 0.000 0.772 0.228
#> SRR1088461 3 0.6148 0.603 0.004 0.356 0.640
#> SRR810129 2 0.3192 0.789 0.000 0.888 0.112
#> SRR1400141 3 0.2261 0.765 0.000 0.068 0.932
#> SRR1349585 1 0.0892 0.901 0.980 0.000 0.020
#> SRR1437576 2 0.0000 0.832 0.000 1.000 0.000
#> SRR814407 1 0.6026 0.357 0.624 0.000 0.376
#> SRR1332403 3 0.6180 0.517 0.000 0.416 0.584
#> SRR1099598 2 0.7558 0.683 0.124 0.688 0.188
#> SRR1327723 2 0.0424 0.831 0.000 0.992 0.008
#> SRR1392525 3 0.0000 0.763 0.000 0.000 1.000
#> SRR1320536 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1083824 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1351390 2 0.7039 0.701 0.128 0.728 0.144
#> SRR1309141 3 0.4452 0.767 0.000 0.192 0.808
#> SRR1452803 2 0.0592 0.831 0.000 0.988 0.012
#> SRR811631 2 0.0237 0.833 0.000 0.996 0.004
#> SRR1485563 3 0.6915 0.702 0.124 0.140 0.736
#> SRR1311531 2 0.4399 0.764 0.000 0.812 0.188
#> SRR1353076 2 0.5098 0.691 0.000 0.752 0.248
#> SRR1480831 2 0.5016 0.703 0.000 0.760 0.240
#> SRR1083892 1 0.2806 0.866 0.928 0.040 0.032
#> SRR809873 3 0.2878 0.740 0.096 0.000 0.904
#> SRR1341854 3 0.5363 0.699 0.000 0.276 0.724
#> SRR1399335 3 0.5882 0.653 0.000 0.348 0.652
#> SRR1464209 1 0.0892 0.901 0.980 0.000 0.020
#> SRR1389886 2 0.1964 0.815 0.000 0.944 0.056
#> SRR1400730 3 0.6990 0.634 0.164 0.108 0.728
#> SRR1448008 2 0.5216 0.734 0.000 0.740 0.260
#> SRR1087606 2 0.7607 0.440 0.364 0.584 0.052
#> SRR1445111 1 0.0000 0.908 1.000 0.000 0.000
#> SRR816865 3 0.3752 0.763 0.000 0.144 0.856
#> SRR1323360 3 0.2261 0.765 0.000 0.068 0.932
#> SRR1417364 2 0.4291 0.770 0.000 0.820 0.180
#> SRR1480329 2 0.4960 0.774 0.128 0.832 0.040
#> SRR1403322 3 0.3941 0.712 0.156 0.000 0.844
#> SRR1093625 1 0.0000 0.908 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1082035 3 0.9454 0.324 0.180 0.388 0.432
#> SRR1393046 2 0.0000 0.832 0.000 1.000 0.000
#> SRR1466663 3 0.5680 0.737 0.024 0.212 0.764
#> SRR1384456 1 0.0000 0.908 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.2111 0.7335 0.000 0.932 0.024 0.044
#> SRR808862 3 0.4914 0.2800 0.000 0.044 0.748 0.208
#> SRR1500382 2 0.1716 0.7415 0.000 0.936 0.000 0.064
#> SRR1322683 2 0.5688 0.0671 0.000 0.512 0.024 0.464
#> SRR1329811 2 0.7114 0.2769 0.220 0.584 0.004 0.192
#> SRR1087297 2 0.0000 0.7410 0.000 1.000 0.000 0.000
#> SRR1072626 4 0.6352 0.5305 0.000 0.188 0.156 0.656
#> SRR1407428 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1321029 4 0.7597 0.4985 0.000 0.204 0.356 0.440
#> SRR1500282 1 0.5772 0.7440 0.672 0.000 0.068 0.260
#> SRR1100496 3 0.0188 0.5255 0.000 0.000 0.996 0.004
#> SRR1308778 2 0.1576 0.7401 0.000 0.948 0.004 0.048
#> SRR1445304 2 0.1389 0.7406 0.000 0.952 0.000 0.048
#> SRR1099378 3 0.6204 0.4664 0.000 0.052 0.500 0.448
#> SRR1347412 1 0.3052 0.8127 0.860 0.000 0.004 0.136
#> SRR1099694 2 0.1661 0.7351 0.000 0.944 0.004 0.052
#> SRR1088365 3 0.6326 0.4907 0.000 0.108 0.636 0.256
#> SRR1325752 2 0.7811 -0.0887 0.000 0.404 0.260 0.336
#> SRR1416713 2 0.1792 0.7417 0.000 0.932 0.000 0.068
#> SRR1074474 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1469369 4 0.6885 0.4681 0.000 0.104 0.436 0.460
#> SRR1400507 2 0.5668 0.0745 0.000 0.532 0.024 0.444
#> SRR1378179 2 0.4105 0.6520 0.000 0.812 0.156 0.032
#> SRR1377905 2 0.2197 0.7417 0.000 0.916 0.004 0.080
#> SRR1089479 1 0.2149 0.8268 0.912 0.000 0.000 0.088
#> SRR1073365 2 0.0336 0.7407 0.000 0.992 0.000 0.008
#> SRR1500306 4 0.5837 0.5154 0.012 0.084 0.184 0.720
#> SRR1101566 4 0.7300 0.5189 0.000 0.156 0.372 0.472
#> SRR1350503 2 0.7818 -0.2472 0.000 0.388 0.356 0.256
#> SRR1446007 4 0.7510 0.4769 0.000 0.184 0.380 0.436
#> SRR1102875 2 0.1743 0.7388 0.000 0.940 0.004 0.056
#> SRR1380293 2 0.1004 0.7374 0.000 0.972 0.004 0.024
#> SRR1331198 2 0.1489 0.7346 0.000 0.952 0.004 0.044
#> SRR1092686 3 0.2773 0.5058 0.000 0.072 0.900 0.028
#> SRR1069421 3 0.6399 0.4864 0.000 0.104 0.620 0.276
#> SRR1341650 3 0.4936 0.5214 0.000 0.020 0.700 0.280
#> SRR1357276 2 0.0000 0.7410 0.000 1.000 0.000 0.000
#> SRR1498374 4 0.7640 0.5026 0.000 0.212 0.356 0.432
#> SRR1093721 2 0.7421 -0.0900 0.000 0.484 0.332 0.184
#> SRR1464660 2 0.9945 -0.2475 0.220 0.300 0.228 0.252
#> SRR1402051 4 0.4322 0.5396 0.000 0.152 0.044 0.804
#> SRR1488734 2 0.1389 0.7406 0.000 0.952 0.000 0.048
#> SRR1082616 3 0.4008 0.5289 0.000 0.000 0.756 0.244
#> SRR1099427 4 0.6245 0.5662 0.000 0.164 0.168 0.668
#> SRR1453093 4 0.6295 0.4921 0.000 0.132 0.212 0.656
#> SRR1357064 3 0.9592 -0.2317 0.296 0.116 0.304 0.284
#> SRR811237 4 0.6715 0.4472 0.000 0.144 0.252 0.604
#> SRR1100848 4 0.6746 0.4361 0.000 0.340 0.108 0.552
#> SRR1346755 4 0.6929 0.4868 0.000 0.108 0.440 0.452
#> SRR1472529 2 0.4453 0.5933 0.000 0.744 0.012 0.244
#> SRR1398905 3 0.4643 0.4932 0.048 0.048 0.828 0.076
#> SRR1082733 2 0.2987 0.6970 0.000 0.880 0.104 0.016
#> SRR1308035 3 0.3392 0.4833 0.000 0.072 0.872 0.056
#> SRR1466445 3 0.4300 0.4285 0.000 0.088 0.820 0.092
#> SRR1359080 2 0.2530 0.7313 0.000 0.896 0.004 0.100
#> SRR1455825 2 0.4053 0.5966 0.000 0.768 0.004 0.228
#> SRR1389300 2 0.4088 0.5965 0.000 0.764 0.004 0.232
#> SRR812246 3 0.7558 -0.4689 0.000 0.196 0.444 0.360
#> SRR1076632 3 0.5392 0.5178 0.000 0.040 0.680 0.280
#> SRR1415567 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1331900 2 0.5088 0.1746 0.000 0.572 0.004 0.424
#> SRR1452099 3 0.4103 0.5316 0.000 0.000 0.744 0.256
#> SRR1352346 2 0.6117 0.5157 0.120 0.688 0.004 0.188
#> SRR1364034 2 0.3895 0.6205 0.000 0.804 0.184 0.012
#> SRR1086046 4 0.6360 0.5041 0.000 0.180 0.164 0.656
#> SRR1407226 3 0.7551 0.1933 0.272 0.008 0.528 0.192
#> SRR1319363 3 0.4843 0.4815 0.000 0.000 0.604 0.396
#> SRR1446961 2 0.4931 0.5909 0.000 0.776 0.132 0.092
#> SRR1486650 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.7317 0.5858 0.528 0.204 0.000 0.268
#> SRR1454785 3 0.4948 0.3827 0.000 0.124 0.776 0.100
#> SRR1092329 4 0.5615 0.5655 0.000 0.188 0.096 0.716
#> SRR1091476 3 0.4163 0.4447 0.000 0.076 0.828 0.096
#> SRR1073775 4 0.7585 0.5137 0.000 0.224 0.304 0.472
#> SRR1366873 2 0.5119 0.1327 0.000 0.556 0.004 0.440
#> SRR1398114 2 0.3962 0.6529 0.000 0.832 0.124 0.044
#> SRR1089950 4 0.6660 0.3043 0.220 0.104 0.020 0.656
#> SRR1433272 3 0.5987 0.1031 0.000 0.440 0.520 0.040
#> SRR1075314 4 0.5495 0.4977 0.000 0.096 0.176 0.728
#> SRR1085590 3 0.2466 0.5101 0.000 0.056 0.916 0.028
#> SRR1100752 3 0.3427 0.4713 0.000 0.112 0.860 0.028
#> SRR1391494 4 0.6337 0.1687 0.000 0.468 0.060 0.472
#> SRR1333263 3 0.5168 0.5284 0.000 0.040 0.712 0.248
#> SRR1310231 2 0.1576 0.7412 0.000 0.948 0.004 0.048
#> SRR1094144 3 0.6873 0.4507 0.000 0.148 0.580 0.272
#> SRR1092160 2 0.1743 0.7322 0.000 0.940 0.004 0.056
#> SRR1320300 2 0.5028 0.1814 0.000 0.596 0.004 0.400
#> SRR1322747 2 0.1978 0.7399 0.000 0.928 0.004 0.068
#> SRR1432719 3 0.6252 0.0167 0.000 0.432 0.512 0.056
#> SRR1100728 3 0.6323 0.4895 0.000 0.112 0.640 0.248
#> SRR1087511 4 0.7240 0.5124 0.000 0.144 0.400 0.456
#> SRR1470336 1 0.6467 0.3801 0.508 0.044 0.012 0.436
#> SRR1322536 4 0.5188 0.5205 0.000 0.096 0.148 0.756
#> SRR1100824 3 0.7315 0.2301 0.232 0.004 0.556 0.208
#> SRR1085951 3 0.1489 0.5223 0.000 0.044 0.952 0.004
#> SRR1322046 2 0.4323 0.5914 0.000 0.788 0.184 0.028
#> SRR1316420 4 0.7366 0.1152 0.220 0.096 0.060 0.624
#> SRR1070913 2 0.4621 0.5449 0.000 0.708 0.008 0.284
#> SRR1345806 3 0.5473 0.2518 0.000 0.084 0.724 0.192
#> SRR1313872 2 0.3404 0.6767 0.000 0.864 0.104 0.032
#> SRR1337666 2 0.1978 0.7436 0.000 0.928 0.004 0.068
#> SRR1076823 4 0.6287 -0.2277 0.028 0.020 0.396 0.556
#> SRR1093954 2 0.1767 0.7337 0.000 0.944 0.044 0.012
#> SRR1451921 3 0.6393 0.2379 0.000 0.064 0.480 0.456
#> SRR1491257 3 0.9555 0.1054 0.220 0.156 0.400 0.224
#> SRR1416979 4 0.6794 0.3478 0.000 0.116 0.328 0.556
#> SRR1419015 3 0.4277 0.5260 0.000 0.000 0.720 0.280
#> SRR817649 2 0.1557 0.7261 0.000 0.944 0.000 0.056
#> SRR1466376 2 0.2053 0.7404 0.000 0.924 0.004 0.072
#> SRR1392055 2 0.1302 0.7409 0.000 0.956 0.000 0.044
#> SRR1120913 2 0.2197 0.7418 0.000 0.916 0.004 0.080
#> SRR1120869 3 0.3052 0.5122 0.000 0.136 0.860 0.004
#> SRR1319419 3 0.7138 -0.1299 0.000 0.180 0.552 0.268
#> SRR816495 2 0.6602 0.0856 0.000 0.552 0.356 0.092
#> SRR818694 4 0.7006 0.5369 0.000 0.132 0.340 0.528
#> SRR1465653 2 0.7292 0.2184 0.220 0.560 0.004 0.216
#> SRR1475952 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1465040 4 0.7344 0.4949 0.000 0.160 0.380 0.460
#> SRR1088461 4 0.7714 0.1569 0.000 0.292 0.260 0.448
#> SRR810129 2 0.2919 0.7295 0.000 0.896 0.044 0.060
#> SRR1400141 3 0.3312 0.4860 0.000 0.072 0.876 0.052
#> SRR1349585 1 0.6071 0.7447 0.676 0.008 0.076 0.240
#> SRR1437576 2 0.2266 0.7367 0.000 0.912 0.004 0.084
#> SRR814407 1 0.7247 0.5291 0.544 0.000 0.240 0.216
#> SRR1332403 2 0.2976 0.6836 0.000 0.872 0.120 0.008
#> SRR1099598 4 0.5109 0.5344 0.000 0.196 0.060 0.744
#> SRR1327723 2 0.0336 0.7409 0.000 0.992 0.000 0.008
#> SRR1392525 3 0.3975 0.5310 0.000 0.000 0.760 0.240
#> SRR1320536 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.1209 0.7361 0.000 0.964 0.004 0.032
#> SRR1351390 4 0.4994 0.4621 0.000 0.048 0.208 0.744
#> SRR1309141 3 0.5236 0.2864 0.000 0.432 0.560 0.008
#> SRR1452803 2 0.0336 0.7418 0.000 0.992 0.000 0.008
#> SRR811631 2 0.5137 0.1486 0.000 0.544 0.004 0.452
#> SRR1485563 4 0.6214 -0.0464 0.000 0.064 0.360 0.576
#> SRR1311531 4 0.7641 0.4571 0.000 0.208 0.376 0.416
#> SRR1353076 4 0.7220 0.3600 0.000 0.384 0.144 0.472
#> SRR1480831 4 0.6742 0.4902 0.000 0.232 0.160 0.608
#> SRR1083892 1 0.7275 0.6947 0.592 0.028 0.112 0.268
#> SRR809873 3 0.5108 0.5141 0.000 0.020 0.672 0.308
#> SRR1341854 2 0.4540 0.6147 0.000 0.772 0.196 0.032
#> SRR1399335 2 0.5383 -0.0301 0.000 0.536 0.452 0.012
#> SRR1464209 1 0.6614 0.7125 0.620 0.016 0.076 0.288
#> SRR1389886 2 0.1576 0.7401 0.000 0.948 0.004 0.048
#> SRR1400730 3 0.5374 0.3975 0.000 0.052 0.704 0.244
#> SRR1448008 4 0.6416 0.5447 0.000 0.200 0.152 0.648
#> SRR1087606 4 0.7423 0.0339 0.220 0.216 0.008 0.556
#> SRR1445111 1 0.0188 0.8397 0.996 0.000 0.000 0.004
#> SRR816865 3 0.6323 0.4895 0.000 0.112 0.640 0.248
#> SRR1323360 3 0.3312 0.4854 0.000 0.072 0.876 0.052
#> SRR1417364 2 0.6014 0.1829 0.000 0.588 0.360 0.052
#> SRR1480329 4 0.5132 0.1301 0.000 0.448 0.004 0.548
#> SRR1403322 3 0.7028 0.4378 0.148 0.000 0.548 0.304
#> SRR1093625 1 0.0000 0.8402 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.4088 0.5965 0.000 0.764 0.004 0.232
#> SRR1082035 4 0.9350 0.1525 0.196 0.140 0.232 0.432
#> SRR1393046 2 0.2149 0.7418 0.000 0.912 0.000 0.088
#> SRR1466663 3 0.7357 0.3692 0.000 0.192 0.512 0.296
#> SRR1384456 1 0.0000 0.8402 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.0162 0.8724 0.000 0.996 0.004 0.000 0.000
#> SRR808862 3 0.3689 0.6657 0.000 0.000 0.740 0.256 0.004
#> SRR1500382 2 0.0404 0.8719 0.000 0.988 0.012 0.000 0.000
#> SRR1322683 2 0.4118 0.5932 0.000 0.660 0.336 0.000 0.004
#> SRR1329811 5 0.2230 0.6771 0.000 0.116 0.000 0.000 0.884
#> SRR1087297 2 0.0794 0.8668 0.000 0.972 0.028 0.000 0.000
#> SRR1072626 4 0.4866 0.5246 0.000 0.028 0.392 0.580 0.000
#> SRR1407428 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.1908 0.6694 0.000 0.092 0.908 0.000 0.000
#> SRR1500282 5 0.0290 0.7407 0.008 0.000 0.000 0.000 0.992
#> SRR1100496 3 0.4557 0.4636 0.000 0.000 0.516 0.476 0.008
#> SRR1308778 2 0.0451 0.8728 0.000 0.988 0.008 0.004 0.000
#> SRR1445304 2 0.0566 0.8722 0.000 0.984 0.012 0.004 0.000
#> SRR1099378 5 0.4735 0.5368 0.000 0.004 0.020 0.352 0.624
#> SRR1347412 1 0.4066 0.5473 0.672 0.000 0.004 0.000 0.324
#> SRR1099694 2 0.1082 0.8664 0.000 0.964 0.028 0.008 0.000
#> SRR1088365 4 0.0290 0.7223 0.000 0.008 0.000 0.992 0.000
#> SRR1325752 4 0.5563 0.5199 0.000 0.280 0.012 0.632 0.076
#> SRR1416713 2 0.0404 0.8719 0.000 0.988 0.012 0.000 0.000
#> SRR1074474 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.1082 0.6660 0.000 0.028 0.964 0.008 0.000
#> SRR1400507 2 0.3949 0.6017 0.000 0.668 0.332 0.000 0.000
#> SRR1378179 2 0.1121 0.8612 0.000 0.956 0.000 0.044 0.000
#> SRR1377905 2 0.0510 0.8730 0.000 0.984 0.016 0.000 0.000
#> SRR1089479 1 0.4161 0.2987 0.608 0.000 0.000 0.000 0.392
#> SRR1073365 2 0.1082 0.8664 0.000 0.964 0.028 0.008 0.000
#> SRR1500306 5 0.4307 0.6285 0.004 0.016 0.236 0.008 0.736
#> SRR1101566 3 0.1251 0.6625 0.000 0.036 0.956 0.008 0.000
#> SRR1350503 3 0.3039 0.6405 0.000 0.192 0.808 0.000 0.000
#> SRR1446007 3 0.0703 0.6741 0.000 0.024 0.976 0.000 0.000
#> SRR1102875 2 0.0290 0.8725 0.000 0.992 0.000 0.008 0.000
#> SRR1380293 2 0.1124 0.8681 0.000 0.960 0.036 0.004 0.000
#> SRR1331198 2 0.0963 0.8682 0.000 0.964 0.036 0.000 0.000
#> SRR1092686 3 0.3983 0.6395 0.000 0.000 0.660 0.340 0.000
#> SRR1069421 4 0.1282 0.7121 0.000 0.044 0.000 0.952 0.004
#> SRR1341650 4 0.0451 0.7191 0.000 0.004 0.000 0.988 0.008
#> SRR1357276 2 0.0794 0.8668 0.000 0.972 0.028 0.000 0.000
#> SRR1498374 3 0.1851 0.6701 0.000 0.088 0.912 0.000 0.000
#> SRR1093721 3 0.3430 0.6152 0.000 0.220 0.776 0.004 0.000
#> SRR1464660 5 0.1357 0.7301 0.000 0.048 0.000 0.004 0.948
#> SRR1402051 4 0.5475 0.5779 0.000 0.028 0.336 0.604 0.032
#> SRR1488734 2 0.0162 0.8727 0.000 0.996 0.000 0.004 0.000
#> SRR1082616 4 0.0324 0.7194 0.000 0.000 0.004 0.992 0.004
#> SRR1099427 3 0.5176 -0.4043 0.000 0.040 0.492 0.468 0.000
#> SRR1453093 4 0.4796 0.6132 0.000 0.028 0.280 0.680 0.012
#> SRR1357064 5 0.0000 0.7423 0.000 0.000 0.000 0.000 1.000
#> SRR811237 4 0.3909 0.6798 0.000 0.024 0.216 0.760 0.000
#> SRR1100848 4 0.5611 0.6059 0.000 0.152 0.212 0.636 0.000
#> SRR1346755 3 0.2848 0.6496 0.000 0.028 0.868 0.104 0.000
#> SRR1472529 2 0.2074 0.8252 0.000 0.896 0.104 0.000 0.000
#> SRR1398905 3 0.5684 0.4713 0.012 0.000 0.504 0.432 0.052
#> SRR1082733 2 0.1661 0.8580 0.000 0.940 0.036 0.024 0.000
#> SRR1308035 3 0.4218 0.6471 0.000 0.004 0.668 0.324 0.004
#> SRR1466445 3 0.3661 0.6721 0.000 0.000 0.724 0.276 0.000
#> SRR1359080 2 0.0609 0.8694 0.000 0.980 0.020 0.000 0.000
#> SRR1455825 2 0.2020 0.8267 0.000 0.900 0.100 0.000 0.000
#> SRR1389300 2 0.1965 0.8282 0.000 0.904 0.096 0.000 0.000
#> SRR812246 3 0.3241 0.6789 0.000 0.024 0.832 0.144 0.000
#> SRR1076632 4 0.0579 0.7224 0.000 0.008 0.000 0.984 0.008
#> SRR1415567 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.3661 0.6571 0.000 0.724 0.276 0.000 0.000
#> SRR1452099 4 0.0898 0.7088 0.000 0.000 0.020 0.972 0.008
#> SRR1352346 2 0.4504 0.2252 0.000 0.564 0.008 0.000 0.428
#> SRR1364034 2 0.1197 0.8607 0.000 0.952 0.000 0.048 0.000
#> SRR1086046 4 0.5543 0.6401 0.000 0.008 0.164 0.672 0.156
#> SRR1407226 5 0.5491 0.3123 0.052 0.000 0.004 0.452 0.492
#> SRR1319363 4 0.1430 0.7132 0.000 0.000 0.004 0.944 0.052
#> SRR1446961 2 0.3661 0.6125 0.000 0.724 0.276 0.000 0.000
#> SRR1486650 1 0.0162 0.9160 0.996 0.000 0.000 0.000 0.004
#> SRR1470152 5 0.0703 0.7404 0.000 0.024 0.000 0.000 0.976
#> SRR1454785 3 0.4503 0.6731 0.000 0.036 0.696 0.268 0.000
#> SRR1092329 4 0.5766 0.4920 0.000 0.092 0.392 0.516 0.000
#> SRR1091476 3 0.4338 0.6602 0.000 0.008 0.684 0.300 0.008
#> SRR1073775 3 0.1557 0.6584 0.000 0.052 0.940 0.008 0.000
#> SRR1366873 2 0.3932 0.6048 0.000 0.672 0.328 0.000 0.000
#> SRR1398114 2 0.2179 0.8151 0.000 0.888 0.000 0.112 0.000
#> SRR1089950 5 0.4327 0.6376 0.004 0.016 0.224 0.012 0.744
#> SRR1433272 2 0.4268 0.5188 0.000 0.648 0.000 0.344 0.008
#> SRR1075314 4 0.6160 0.6275 0.000 0.028 0.184 0.632 0.156
#> SRR1085590 3 0.4101 0.6418 0.000 0.000 0.664 0.332 0.004
#> SRR1100752 3 0.4457 0.6441 0.000 0.012 0.656 0.328 0.004
#> SRR1391494 2 0.5924 0.4315 0.000 0.524 0.376 0.096 0.004
#> SRR1333263 4 0.0451 0.7174 0.000 0.000 0.004 0.988 0.008
#> SRR1310231 2 0.0162 0.8727 0.000 0.996 0.000 0.004 0.000
#> SRR1094144 4 0.1205 0.7232 0.000 0.040 0.000 0.956 0.004
#> SRR1092160 2 0.1124 0.8681 0.000 0.960 0.036 0.004 0.000
#> SRR1320300 2 0.3790 0.6584 0.000 0.724 0.272 0.004 0.000
#> SRR1322747 2 0.0000 0.8725 0.000 1.000 0.000 0.000 0.000
#> SRR1432719 3 0.4728 0.5617 0.000 0.296 0.664 0.040 0.000
#> SRR1100728 4 0.0162 0.7198 0.000 0.000 0.000 0.996 0.004
#> SRR1087511 3 0.1041 0.6655 0.000 0.032 0.964 0.004 0.000
#> SRR1470336 5 0.4351 0.6249 0.028 0.000 0.244 0.004 0.724
#> SRR1322536 4 0.6668 0.5403 0.000 0.028 0.284 0.540 0.148
#> SRR1100824 5 0.4218 0.5688 0.004 0.000 0.004 0.324 0.668
#> SRR1085951 3 0.4528 0.5006 0.000 0.000 0.548 0.444 0.008
#> SRR1322046 2 0.3283 0.7665 0.000 0.832 0.028 0.140 0.000
#> SRR1316420 5 0.0324 0.7428 0.000 0.004 0.004 0.000 0.992
#> SRR1070913 2 0.3242 0.7386 0.000 0.784 0.216 0.000 0.000
#> SRR1345806 3 0.3906 0.6740 0.000 0.016 0.744 0.240 0.000
#> SRR1313872 2 0.1243 0.8660 0.000 0.960 0.028 0.008 0.004
#> SRR1337666 2 0.0510 0.8731 0.000 0.984 0.016 0.000 0.000
#> SRR1076823 4 0.5162 0.6804 0.052 0.004 0.104 0.756 0.084
#> SRR1093954 2 0.1043 0.8651 0.000 0.960 0.000 0.040 0.000
#> SRR1451921 4 0.2674 0.7224 0.000 0.008 0.084 0.888 0.020
#> SRR1491257 5 0.6056 0.4588 0.000 0.208 0.012 0.164 0.616
#> SRR1416979 4 0.4550 0.6120 0.000 0.036 0.276 0.688 0.000
#> SRR1419015 4 0.0451 0.7177 0.000 0.000 0.004 0.988 0.008
#> SRR817649 2 0.1828 0.8572 0.000 0.936 0.028 0.004 0.032
#> SRR1466376 2 0.0162 0.8724 0.000 0.996 0.004 0.000 0.000
#> SRR1392055 2 0.0290 0.8724 0.000 0.992 0.008 0.000 0.000
#> SRR1120913 2 0.0290 0.8724 0.000 0.992 0.008 0.000 0.000
#> SRR1120869 4 0.6385 -0.3433 0.000 0.132 0.388 0.472 0.008
#> SRR1319419 3 0.3051 0.6995 0.000 0.060 0.864 0.076 0.000
#> SRR816495 3 0.3816 0.5608 0.000 0.304 0.696 0.000 0.000
#> SRR818694 3 0.2879 0.5743 0.000 0.032 0.868 0.100 0.000
#> SRR1465653 5 0.1544 0.7171 0.000 0.068 0.000 0.000 0.932
#> SRR1475952 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.1043 0.6680 0.000 0.040 0.960 0.000 0.000
#> SRR1088461 4 0.5786 0.6096 0.000 0.168 0.196 0.632 0.004
#> SRR810129 2 0.1195 0.8673 0.000 0.960 0.012 0.028 0.000
#> SRR1400141 3 0.4253 0.6415 0.000 0.004 0.660 0.332 0.004
#> SRR1349585 5 0.3577 0.6928 0.084 0.000 0.004 0.076 0.836
#> SRR1437576 2 0.0290 0.8732 0.000 0.992 0.008 0.000 0.000
#> SRR814407 5 0.3278 0.6682 0.020 0.000 0.000 0.156 0.824
#> SRR1332403 2 0.1012 0.8686 0.000 0.968 0.012 0.020 0.000
#> SRR1099598 4 0.6844 0.5343 0.000 0.120 0.308 0.524 0.048
#> SRR1327723 2 0.0794 0.8668 0.000 0.972 0.028 0.000 0.000
#> SRR1392525 4 0.0992 0.7151 0.000 0.000 0.024 0.968 0.008
#> SRR1320536 1 0.0162 0.9160 0.996 0.000 0.000 0.000 0.004
#> SRR1083824 2 0.0794 0.8668 0.000 0.972 0.028 0.000 0.000
#> SRR1351390 5 0.3676 0.6466 0.004 0.000 0.232 0.004 0.760
#> SRR1309141 2 0.5468 0.2553 0.000 0.516 0.044 0.432 0.008
#> SRR1452803 2 0.0992 0.8684 0.000 0.968 0.024 0.008 0.000
#> SRR811631 2 0.3949 0.6017 0.000 0.668 0.332 0.000 0.000
#> SRR1485563 4 0.4599 0.7027 0.000 0.028 0.132 0.776 0.064
#> SRR1311531 3 0.0290 0.6775 0.000 0.008 0.992 0.000 0.000
#> SRR1353076 4 0.5403 0.5876 0.000 0.248 0.108 0.644 0.000
#> SRR1480831 4 0.5263 0.6358 0.000 0.144 0.176 0.680 0.000
#> SRR1083892 5 0.0955 0.7447 0.000 0.000 0.004 0.028 0.968
#> SRR809873 4 0.0404 0.7185 0.000 0.000 0.000 0.988 0.012
#> SRR1341854 2 0.1197 0.8606 0.000 0.952 0.000 0.048 0.000
#> SRR1399335 2 0.4776 0.5565 0.000 0.668 0.028 0.296 0.008
#> SRR1464209 5 0.0000 0.7423 0.000 0.000 0.000 0.000 1.000
#> SRR1389886 2 0.0000 0.8725 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 5 0.4711 0.6186 0.000 0.000 0.116 0.148 0.736
#> SRR1448008 4 0.5523 0.5679 0.000 0.088 0.320 0.592 0.000
#> SRR1087606 5 0.0451 0.7425 0.000 0.008 0.004 0.000 0.988
#> SRR1445111 1 0.0609 0.9048 0.980 0.000 0.000 0.000 0.020
#> SRR816865 4 0.0162 0.7198 0.000 0.000 0.000 0.996 0.004
#> SRR1323360 3 0.4403 0.6501 0.000 0.012 0.668 0.316 0.004
#> SRR1417364 3 0.3983 0.5228 0.000 0.340 0.660 0.000 0.000
#> SRR1480329 2 0.7357 0.0335 0.000 0.380 0.332 0.028 0.260
#> SRR1403322 4 0.2694 0.7176 0.076 0.000 0.032 0.888 0.004
#> SRR1093625 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.2020 0.8267 0.000 0.900 0.100 0.000 0.000
#> SRR1082035 5 0.7759 0.4460 0.000 0.124 0.192 0.200 0.484
#> SRR1393046 2 0.0404 0.8719 0.000 0.988 0.012 0.000 0.000
#> SRR1466663 4 0.4153 0.6067 0.000 0.192 0.008 0.768 0.032
#> SRR1384456 1 0.0000 0.9178 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.1610 0.8192 0.000 0.916 0.000 0.000 0.000 0.084
#> SRR808862 3 0.2455 0.8165 0.000 0.000 0.872 0.112 0.004 0.012
#> SRR1500382 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1322683 2 0.5136 0.1780 0.000 0.496 0.084 0.000 0.000 0.420
#> SRR1329811 5 0.0713 0.7227 0.000 0.028 0.000 0.000 0.972 0.000
#> SRR1087297 2 0.0146 0.8681 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1072626 6 0.2383 0.6792 0.000 0.000 0.024 0.096 0.000 0.880
#> SRR1407428 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.3627 0.7308 0.000 0.080 0.792 0.000 0.000 0.128
#> SRR1500282 5 0.0146 0.7302 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1100496 4 0.1141 0.7054 0.000 0.000 0.052 0.948 0.000 0.000
#> SRR1308778 2 0.0436 0.8666 0.000 0.988 0.004 0.004 0.000 0.004
#> SRR1445304 2 0.0146 0.8679 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1099378 4 0.5222 0.3160 0.000 0.000 0.000 0.584 0.128 0.288
#> SRR1347412 1 0.5137 0.5544 0.664 0.000 0.000 0.024 0.212 0.100
#> SRR1099694 2 0.0291 0.8674 0.000 0.992 0.000 0.004 0.000 0.004
#> SRR1088365 4 0.4389 0.1503 0.000 0.000 0.024 0.528 0.000 0.448
#> SRR1325752 6 0.5897 0.2262 0.000 0.100 0.020 0.260 0.024 0.596
#> SRR1416713 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1074474 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 6 0.3930 0.2819 0.000 0.000 0.420 0.004 0.000 0.576
#> SRR1400507 2 0.5118 0.2226 0.000 0.512 0.084 0.000 0.000 0.404
#> SRR1378179 2 0.3543 0.5956 0.000 0.720 0.004 0.272 0.000 0.004
#> SRR1377905 2 0.0146 0.8679 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1089479 1 0.3574 0.7393 0.804 0.000 0.000 0.036 0.144 0.016
#> SRR1073365 2 0.0436 0.8668 0.000 0.988 0.004 0.004 0.000 0.004
#> SRR1500306 5 0.5019 0.3050 0.000 0.000 0.012 0.044 0.476 0.468
#> SRR1101566 6 0.3945 0.3677 0.000 0.008 0.380 0.000 0.000 0.612
#> SRR1350503 3 0.1918 0.7957 0.000 0.088 0.904 0.000 0.000 0.008
#> SRR1446007 3 0.0713 0.8049 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1102875 2 0.0551 0.8660 0.000 0.984 0.004 0.004 0.000 0.008
#> SRR1380293 2 0.0146 0.8679 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1331198 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1092686 3 0.1700 0.8355 0.000 0.000 0.916 0.080 0.000 0.004
#> SRR1069421 4 0.3079 0.6871 0.000 0.028 0.008 0.836 0.000 0.128
#> SRR1341650 4 0.1155 0.7214 0.000 0.004 0.004 0.956 0.000 0.036
#> SRR1357276 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1498374 3 0.4766 0.3825 0.000 0.072 0.612 0.000 0.000 0.316
#> SRR1093721 3 0.3860 0.5740 0.000 0.036 0.728 0.000 0.000 0.236
#> SRR1464660 5 0.0508 0.7291 0.000 0.012 0.000 0.004 0.984 0.000
#> SRR1402051 6 0.3324 0.6668 0.000 0.000 0.080 0.060 0.020 0.840
#> SRR1488734 2 0.0146 0.8679 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1082616 4 0.4403 0.0974 0.000 0.000 0.024 0.508 0.000 0.468
#> SRR1099427 6 0.2113 0.6850 0.000 0.008 0.092 0.004 0.000 0.896
#> SRR1453093 6 0.2662 0.6611 0.000 0.000 0.024 0.120 0.000 0.856
#> SRR1357064 5 0.0146 0.7316 0.000 0.000 0.000 0.004 0.996 0.000
#> SRR811237 6 0.3283 0.6375 0.000 0.000 0.036 0.160 0.000 0.804
#> SRR1100848 6 0.4157 0.6652 0.000 0.060 0.060 0.092 0.000 0.788
#> SRR1346755 3 0.4415 0.0763 0.000 0.004 0.556 0.020 0.000 0.420
#> SRR1472529 2 0.2996 0.6769 0.000 0.772 0.000 0.000 0.000 0.228
#> SRR1398905 3 0.4963 0.3861 0.028 0.000 0.568 0.376 0.028 0.000
#> SRR1082733 2 0.1075 0.8408 0.000 0.952 0.048 0.000 0.000 0.000
#> SRR1308035 3 0.1663 0.8349 0.000 0.000 0.912 0.088 0.000 0.000
#> SRR1466445 3 0.1265 0.8314 0.000 0.000 0.948 0.044 0.000 0.008
#> SRR1359080 2 0.2482 0.7621 0.000 0.848 0.004 0.000 0.000 0.148
#> SRR1455825 2 0.3342 0.6701 0.000 0.760 0.012 0.000 0.000 0.228
#> SRR1389300 2 0.3103 0.6978 0.000 0.784 0.008 0.000 0.000 0.208
#> SRR812246 3 0.1788 0.8376 0.000 0.004 0.916 0.076 0.000 0.004
#> SRR1076632 4 0.1901 0.7190 0.000 0.000 0.028 0.924 0.008 0.040
#> SRR1415567 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.4277 0.4420 0.000 0.616 0.028 0.000 0.000 0.356
#> SRR1452099 4 0.1124 0.7214 0.000 0.000 0.008 0.956 0.000 0.036
#> SRR1352346 5 0.6325 0.3658 0.000 0.364 0.004 0.036 0.464 0.132
#> SRR1364034 2 0.3738 0.5276 0.000 0.680 0.004 0.312 0.000 0.004
#> SRR1086046 6 0.6980 0.3595 0.000 0.004 0.144 0.172 0.172 0.508
#> SRR1407226 4 0.2764 0.6256 0.008 0.000 0.000 0.864 0.028 0.100
#> SRR1319363 4 0.3290 0.6272 0.000 0.000 0.000 0.744 0.004 0.252
#> SRR1446961 2 0.4585 0.6009 0.000 0.692 0.192 0.000 0.000 0.116
#> SRR1486650 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0260 0.7311 0.000 0.008 0.000 0.000 0.992 0.000
#> SRR1454785 3 0.1802 0.8381 0.000 0.012 0.916 0.072 0.000 0.000
#> SRR1092329 6 0.2163 0.6853 0.000 0.004 0.096 0.008 0.000 0.892
#> SRR1091476 3 0.1556 0.8372 0.000 0.000 0.920 0.080 0.000 0.000
#> SRR1073775 6 0.3690 0.5467 0.000 0.012 0.288 0.000 0.000 0.700
#> SRR1366873 2 0.5191 0.2163 0.000 0.508 0.092 0.000 0.000 0.400
#> SRR1398114 2 0.1477 0.8346 0.000 0.940 0.004 0.008 0.000 0.048
#> SRR1089950 5 0.4984 0.3132 0.000 0.004 0.000 0.056 0.480 0.460
#> SRR1433272 4 0.2558 0.6118 0.000 0.156 0.000 0.840 0.000 0.004
#> SRR1075314 6 0.1710 0.6668 0.000 0.000 0.016 0.028 0.020 0.936
#> SRR1085590 3 0.1714 0.8337 0.000 0.000 0.908 0.092 0.000 0.000
#> SRR1100752 3 0.2320 0.8178 0.000 0.004 0.864 0.132 0.000 0.000
#> SRR1391494 6 0.6611 0.0931 0.000 0.380 0.128 0.072 0.000 0.420
#> SRR1333263 4 0.1124 0.7214 0.000 0.000 0.008 0.956 0.000 0.036
#> SRR1310231 2 0.0692 0.8619 0.000 0.976 0.020 0.004 0.000 0.000
#> SRR1094144 4 0.4621 0.1386 0.000 0.008 0.024 0.520 0.000 0.448
#> SRR1092160 2 0.0405 0.8676 0.000 0.988 0.008 0.004 0.000 0.000
#> SRR1320300 6 0.4071 0.4598 0.000 0.304 0.020 0.004 0.000 0.672
#> SRR1322747 2 0.0260 0.8677 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1432719 3 0.2145 0.8130 0.000 0.072 0.900 0.028 0.000 0.000
#> SRR1100728 4 0.1564 0.7190 0.000 0.000 0.024 0.936 0.000 0.040
#> SRR1087511 3 0.3699 0.4224 0.000 0.000 0.660 0.004 0.000 0.336
#> SRR1470336 5 0.6435 0.4555 0.164 0.000 0.000 0.044 0.472 0.320
#> SRR1322536 6 0.1262 0.6721 0.000 0.000 0.008 0.020 0.016 0.956
#> SRR1100824 4 0.2432 0.6286 0.000 0.000 0.000 0.876 0.024 0.100
#> SRR1085951 4 0.3717 0.2065 0.000 0.000 0.384 0.616 0.000 0.000
#> SRR1322046 2 0.2575 0.7697 0.000 0.872 0.024 0.100 0.000 0.004
#> SRR1316420 5 0.2728 0.7183 0.000 0.000 0.000 0.040 0.860 0.100
#> SRR1070913 2 0.4810 0.4839 0.000 0.624 0.084 0.000 0.000 0.292
#> SRR1345806 3 0.1644 0.8371 0.000 0.004 0.920 0.076 0.000 0.000
#> SRR1313872 2 0.0146 0.8679 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1337666 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1076823 6 0.4113 0.5148 0.020 0.000 0.012 0.172 0.028 0.768
#> SRR1093954 2 0.3820 0.3952 0.000 0.660 0.004 0.004 0.000 0.332
#> SRR1451921 6 0.4474 0.1547 0.000 0.000 0.024 0.412 0.004 0.560
#> SRR1491257 5 0.5220 0.1345 0.000 0.100 0.000 0.372 0.528 0.000
#> SRR1416979 6 0.4311 0.5951 0.000 0.000 0.196 0.088 0.000 0.716
#> SRR1419015 4 0.1124 0.7214 0.000 0.000 0.008 0.956 0.000 0.036
#> SRR817649 2 0.1080 0.8513 0.000 0.960 0.004 0.004 0.032 0.000
#> SRR1466376 2 0.0146 0.8679 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1392055 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1120913 2 0.0146 0.8681 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1120869 4 0.1405 0.7113 0.000 0.024 0.024 0.948 0.000 0.004
#> SRR1319419 3 0.0717 0.8155 0.000 0.016 0.976 0.000 0.000 0.008
#> SRR816495 3 0.1863 0.7861 0.000 0.104 0.896 0.000 0.000 0.000
#> SRR818694 6 0.3489 0.5521 0.000 0.004 0.288 0.000 0.000 0.708
#> SRR1465653 5 0.0632 0.7248 0.000 0.024 0.000 0.000 0.976 0.000
#> SRR1475952 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.2871 0.6537 0.000 0.004 0.804 0.000 0.000 0.192
#> SRR1088461 6 0.5828 0.2895 0.000 0.392 0.024 0.104 0.000 0.480
#> SRR810129 2 0.0748 0.8624 0.000 0.976 0.004 0.004 0.000 0.016
#> SRR1400141 3 0.1714 0.8334 0.000 0.000 0.908 0.092 0.000 0.000
#> SRR1349585 5 0.5909 0.5340 0.200 0.000 0.000 0.084 0.616 0.100
#> SRR1437576 2 0.0520 0.8655 0.000 0.984 0.008 0.000 0.000 0.008
#> SRR814407 5 0.3949 0.6710 0.032 0.000 0.020 0.136 0.796 0.016
#> SRR1332403 2 0.0436 0.8666 0.000 0.988 0.004 0.004 0.000 0.004
#> SRR1099598 6 0.1245 0.6853 0.000 0.000 0.032 0.016 0.000 0.952
#> SRR1327723 2 0.0146 0.8680 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1392525 4 0.2511 0.7029 0.000 0.000 0.064 0.880 0.000 0.056
#> SRR1320536 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.0260 0.8671 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1351390 5 0.4122 0.6525 0.000 0.000 0.000 0.048 0.704 0.248
#> SRR1309141 4 0.4700 0.4358 0.000 0.304 0.008 0.636 0.000 0.052
#> SRR1452803 2 0.0436 0.8666 0.000 0.988 0.004 0.004 0.000 0.004
#> SRR811631 2 0.5071 0.2927 0.000 0.540 0.084 0.000 0.000 0.376
#> SRR1485563 6 0.1588 0.6570 0.000 0.000 0.000 0.072 0.004 0.924
#> SRR1311531 3 0.0713 0.8049 0.000 0.000 0.972 0.000 0.000 0.028
#> SRR1353076 6 0.5787 0.3472 0.000 0.348 0.020 0.116 0.000 0.516
#> SRR1480831 6 0.3425 0.6596 0.000 0.024 0.032 0.120 0.000 0.824
#> SRR1083892 5 0.3927 0.6951 0.000 0.000 0.004 0.120 0.776 0.100
#> SRR809873 4 0.2632 0.6543 0.000 0.000 0.004 0.832 0.000 0.164
#> SRR1341854 2 0.0436 0.8666 0.000 0.988 0.004 0.004 0.000 0.004
#> SRR1399335 4 0.4211 0.2084 0.000 0.456 0.008 0.532 0.000 0.004
#> SRR1464209 5 0.0146 0.7316 0.000 0.000 0.000 0.004 0.996 0.000
#> SRR1389886 2 0.0000 0.8680 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1400730 5 0.3319 0.6043 0.000 0.000 0.036 0.164 0.800 0.000
#> SRR1448008 6 0.4103 0.6676 0.000 0.032 0.168 0.036 0.000 0.764
#> SRR1087606 5 0.2800 0.7192 0.000 0.004 0.000 0.036 0.860 0.100
#> SRR1445111 1 0.0603 0.9288 0.980 0.000 0.000 0.000 0.016 0.004
#> SRR816865 4 0.1196 0.7211 0.000 0.000 0.008 0.952 0.000 0.040
#> SRR1323360 3 0.1556 0.8372 0.000 0.000 0.920 0.080 0.000 0.000
#> SRR1417364 3 0.2003 0.7756 0.000 0.116 0.884 0.000 0.000 0.000
#> SRR1480329 6 0.4816 0.5910 0.000 0.040 0.076 0.032 0.092 0.760
#> SRR1403322 4 0.5361 0.5045 0.092 0.000 0.020 0.644 0.008 0.236
#> SRR1093625 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.3245 0.6731 0.000 0.764 0.008 0.000 0.000 0.228
#> SRR1082035 4 0.5259 0.0571 0.000 0.012 0.000 0.472 0.064 0.452
#> SRR1393046 2 0.0146 0.8679 0.000 0.996 0.004 0.000 0.000 0.000
#> SRR1466663 4 0.5501 0.3723 0.000 0.236 0.000 0.564 0.000 0.200
#> SRR1384456 1 0.0000 0.9420 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["MAD", "mclust"]
# you can also extract it by
# res = res_list["MAD:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 0.948 0.961 0.983 0.4188 0.581 0.581
#> 3 3 0.818 0.892 0.951 0.5919 0.720 0.530
#> 4 4 0.674 0.748 0.823 0.0813 0.966 0.903
#> 5 5 0.475 0.517 0.669 0.0131 0.858 0.600
#> 6 6 0.446 0.460 0.610 0.0270 0.850 0.554
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
#> SRR810713 2 0.0000 0.988 0.000 1.000
#> SRR808862 1 0.0000 0.969 1.000 0.000
#> SRR1500382 2 0.0000 0.988 0.000 1.000
#> SRR1322683 2 0.0000 0.988 0.000 1.000
#> SRR1329811 1 0.0000 0.969 1.000 0.000
#> SRR1087297 2 0.0000 0.988 0.000 1.000
#> SRR1072626 2 0.0000 0.988 0.000 1.000
#> SRR1407428 1 0.0000 0.969 1.000 0.000
#> SRR1321029 2 0.0000 0.988 0.000 1.000
#> SRR1500282 1 0.0000 0.969 1.000 0.000
#> SRR1100496 2 0.7219 0.755 0.200 0.800
#> SRR1308778 2 0.0000 0.988 0.000 1.000
#> SRR1445304 2 0.0000 0.988 0.000 1.000
#> SRR1099378 1 0.9795 0.332 0.584 0.416
#> SRR1347412 1 0.0000 0.969 1.000 0.000
#> SRR1099694 2 0.0000 0.988 0.000 1.000
#> SRR1088365 2 0.0000 0.988 0.000 1.000
#> SRR1325752 1 0.7139 0.753 0.804 0.196
#> SRR1416713 2 0.0000 0.988 0.000 1.000
#> SRR1074474 1 0.0000 0.969 1.000 0.000
#> SRR1469369 2 0.0000 0.988 0.000 1.000
#> SRR1400507 2 0.0000 0.988 0.000 1.000
#> SRR1378179 2 0.0000 0.988 0.000 1.000
#> SRR1377905 2 0.0000 0.988 0.000 1.000
#> SRR1089479 1 0.0000 0.969 1.000 0.000
#> SRR1073365 2 0.0000 0.988 0.000 1.000
#> SRR1500306 1 0.0000 0.969 1.000 0.000
#> SRR1101566 2 0.0000 0.988 0.000 1.000
#> SRR1350503 2 0.0000 0.988 0.000 1.000
#> SRR1446007 2 0.0000 0.988 0.000 1.000
#> SRR1102875 2 0.0000 0.988 0.000 1.000
#> SRR1380293 2 0.0000 0.988 0.000 1.000
#> SRR1331198 2 0.0000 0.988 0.000 1.000
#> SRR1092686 2 0.0000 0.988 0.000 1.000
#> SRR1069421 2 0.0672 0.980 0.008 0.992
#> SRR1341650 2 0.6801 0.785 0.180 0.820
#> SRR1357276 2 0.0000 0.988 0.000 1.000
#> SRR1498374 2 0.0000 0.988 0.000 1.000
#> SRR1093721 2 0.0000 0.988 0.000 1.000
#> SRR1464660 1 0.0000 0.969 1.000 0.000
#> SRR1402051 2 0.0000 0.988 0.000 1.000
#> SRR1488734 2 0.0000 0.988 0.000 1.000
#> SRR1082616 2 0.0938 0.977 0.012 0.988
#> SRR1099427 2 0.0000 0.988 0.000 1.000
#> SRR1453093 2 0.0000 0.988 0.000 1.000
#> SRR1357064 1 0.0000 0.969 1.000 0.000
#> SRR811237 2 0.0000 0.988 0.000 1.000
#> SRR1100848 2 0.0000 0.988 0.000 1.000
#> SRR1346755 2 0.0000 0.988 0.000 1.000
#> SRR1472529 2 0.0000 0.988 0.000 1.000
#> SRR1398905 1 0.0000 0.969 1.000 0.000
#> SRR1082733 2 0.0000 0.988 0.000 1.000
#> SRR1308035 2 0.0000 0.988 0.000 1.000
#> SRR1466445 2 0.0000 0.988 0.000 1.000
#> SRR1359080 2 0.0000 0.988 0.000 1.000
#> SRR1455825 2 0.0000 0.988 0.000 1.000
#> SRR1389300 2 0.0000 0.988 0.000 1.000
#> SRR812246 2 0.0000 0.988 0.000 1.000
#> SRR1076632 2 0.0000 0.988 0.000 1.000
#> SRR1415567 1 0.0000 0.969 1.000 0.000
#> SRR1331900 2 0.0000 0.988 0.000 1.000
#> SRR1452099 2 0.6438 0.807 0.164 0.836
#> SRR1352346 1 0.0000 0.969 1.000 0.000
#> SRR1364034 2 0.0000 0.988 0.000 1.000
#> SRR1086046 2 0.1184 0.973 0.016 0.984
#> SRR1407226 1 0.0000 0.969 1.000 0.000
#> SRR1319363 1 0.0000 0.969 1.000 0.000
#> SRR1446961 2 0.0000 0.988 0.000 1.000
#> SRR1486650 1 0.0000 0.969 1.000 0.000
#> SRR1470152 1 0.0000 0.969 1.000 0.000
#> SRR1454785 2 0.0000 0.988 0.000 1.000
#> SRR1092329 2 0.0000 0.988 0.000 1.000
#> SRR1091476 1 0.7674 0.725 0.776 0.224
#> SRR1073775 2 0.0000 0.988 0.000 1.000
#> SRR1366873 2 0.0000 0.988 0.000 1.000
#> SRR1398114 2 0.0000 0.988 0.000 1.000
#> SRR1089950 1 0.1633 0.951 0.976 0.024
#> SRR1433272 2 0.7528 0.731 0.216 0.784
#> SRR1075314 1 0.0000 0.969 1.000 0.000
#> SRR1085590 2 0.0000 0.988 0.000 1.000
#> SRR1100752 2 0.0000 0.988 0.000 1.000
#> SRR1391494 2 0.0000 0.988 0.000 1.000
#> SRR1333263 2 0.0000 0.988 0.000 1.000
#> SRR1310231 2 0.0000 0.988 0.000 1.000
#> SRR1094144 2 0.7299 0.749 0.204 0.796
#> SRR1092160 2 0.0000 0.988 0.000 1.000
#> SRR1320300 2 0.0000 0.988 0.000 1.000
#> SRR1322747 2 0.0000 0.988 0.000 1.000
#> SRR1432719 2 0.0000 0.988 0.000 1.000
#> SRR1100728 2 0.6801 0.785 0.180 0.820
#> SRR1087511 2 0.0000 0.988 0.000 1.000
#> SRR1470336 1 0.0000 0.969 1.000 0.000
#> SRR1322536 1 0.0000 0.969 1.000 0.000
#> SRR1100824 1 0.0000 0.969 1.000 0.000
#> SRR1085951 1 0.1414 0.953 0.980 0.020
#> SRR1322046 2 0.0000 0.988 0.000 1.000
#> SRR1316420 1 0.0000 0.969 1.000 0.000
#> SRR1070913 2 0.0000 0.988 0.000 1.000
#> SRR1345806 2 0.0000 0.988 0.000 1.000
#> SRR1313872 2 0.0000 0.988 0.000 1.000
#> SRR1337666 2 0.0000 0.988 0.000 1.000
#> SRR1076823 1 0.0000 0.969 1.000 0.000
#> SRR1093954 2 0.0000 0.988 0.000 1.000
#> SRR1451921 1 0.0000 0.969 1.000 0.000
#> SRR1491257 1 0.0000 0.969 1.000 0.000
#> SRR1416979 2 0.0000 0.988 0.000 1.000
#> SRR1419015 1 0.0672 0.963 0.992 0.008
#> SRR817649 2 0.0000 0.988 0.000 1.000
#> SRR1466376 2 0.0000 0.988 0.000 1.000
#> SRR1392055 2 0.0000 0.988 0.000 1.000
#> SRR1120913 2 0.0000 0.988 0.000 1.000
#> SRR1120869 2 0.0000 0.988 0.000 1.000
#> SRR1319419 2 0.0000 0.988 0.000 1.000
#> SRR816495 2 0.0000 0.988 0.000 1.000
#> SRR818694 2 0.0000 0.988 0.000 1.000
#> SRR1465653 1 0.0000 0.969 1.000 0.000
#> SRR1475952 1 0.0000 0.969 1.000 0.000
#> SRR1465040 2 0.0000 0.988 0.000 1.000
#> SRR1088461 2 0.0000 0.988 0.000 1.000
#> SRR810129 2 0.0000 0.988 0.000 1.000
#> SRR1400141 2 0.0000 0.988 0.000 1.000
#> SRR1349585 1 0.0000 0.969 1.000 0.000
#> SRR1437576 2 0.0000 0.988 0.000 1.000
#> SRR814407 1 0.0000 0.969 1.000 0.000
#> SRR1332403 2 0.0000 0.988 0.000 1.000
#> SRR1099598 2 0.0000 0.988 0.000 1.000
#> SRR1327723 2 0.0000 0.988 0.000 1.000
#> SRR1392525 2 0.0000 0.988 0.000 1.000
#> SRR1320536 1 0.0000 0.969 1.000 0.000
#> SRR1083824 2 0.0000 0.988 0.000 1.000
#> SRR1351390 1 0.6048 0.825 0.852 0.148
#> SRR1309141 2 0.0000 0.988 0.000 1.000
#> SRR1452803 2 0.0000 0.988 0.000 1.000
#> SRR811631 2 0.0000 0.988 0.000 1.000
#> SRR1485563 2 0.0000 0.988 0.000 1.000
#> SRR1311531 2 0.0000 0.988 0.000 1.000
#> SRR1353076 2 0.0000 0.988 0.000 1.000
#> SRR1480831 2 0.0000 0.988 0.000 1.000
#> SRR1083892 1 0.0000 0.969 1.000 0.000
#> SRR809873 1 0.0000 0.969 1.000 0.000
#> SRR1341854 2 0.0000 0.988 0.000 1.000
#> SRR1399335 2 0.0000 0.988 0.000 1.000
#> SRR1464209 1 0.0000 0.969 1.000 0.000
#> SRR1389886 2 0.0000 0.988 0.000 1.000
#> SRR1400730 1 0.0000 0.969 1.000 0.000
#> SRR1448008 2 0.0000 0.988 0.000 1.000
#> SRR1087606 1 0.1843 0.947 0.972 0.028
#> SRR1445111 1 0.0000 0.969 1.000 0.000
#> SRR816865 2 0.5842 0.837 0.140 0.860
#> SRR1323360 2 0.0000 0.988 0.000 1.000
#> SRR1417364 2 0.0000 0.988 0.000 1.000
#> SRR1480329 2 0.0000 0.988 0.000 1.000
#> SRR1403322 1 0.0000 0.969 1.000 0.000
#> SRR1093625 1 0.0000 0.969 1.000 0.000
#> SRR1479977 2 0.0000 0.988 0.000 1.000
#> SRR1082035 1 0.9427 0.474 0.640 0.360
#> SRR1393046 2 0.0000 0.988 0.000 1.000
#> SRR1466663 2 0.0000 0.988 0.000 1.000
#> SRR1384456 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
#> SRR810713 2 0.0592 0.9190 0.000 0.988 0.012
#> SRR808862 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1500382 2 0.0424 0.9195 0.000 0.992 0.008
#> SRR1322683 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1329811 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1087297 2 0.1643 0.9075 0.000 0.956 0.044
#> SRR1072626 2 0.4062 0.8229 0.000 0.836 0.164
#> SRR1407428 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1321029 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1500282 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1100496 2 0.6373 0.3624 0.408 0.588 0.004
#> SRR1308778 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1099378 1 0.3482 0.8528 0.872 0.128 0.000
#> SRR1347412 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1099694 2 0.1643 0.9080 0.000 0.956 0.044
#> SRR1088365 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1325752 1 0.0747 0.9701 0.984 0.016 0.000
#> SRR1416713 2 0.0747 0.9180 0.000 0.984 0.016
#> SRR1074474 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1469369 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1400507 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1378179 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1377905 2 0.6168 0.2860 0.000 0.588 0.412
#> SRR1089479 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1073365 2 0.0592 0.9190 0.000 0.988 0.012
#> SRR1500306 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1101566 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1350503 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1446007 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1102875 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1380293 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1331198 3 0.1529 0.9159 0.000 0.040 0.960
#> SRR1092686 2 0.5988 0.4481 0.000 0.632 0.368
#> SRR1069421 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1341650 2 0.4654 0.7522 0.208 0.792 0.000
#> SRR1357276 2 0.3267 0.8644 0.000 0.884 0.116
#> SRR1498374 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1093721 3 0.3752 0.8095 0.000 0.144 0.856
#> SRR1464660 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1402051 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1488734 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1082616 1 0.2229 0.9365 0.944 0.044 0.012
#> SRR1099427 3 0.0237 0.9409 0.000 0.004 0.996
#> SRR1453093 1 0.2031 0.9432 0.952 0.016 0.032
#> SRR1357064 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR811237 2 0.0892 0.9175 0.000 0.980 0.020
#> SRR1100848 3 0.4121 0.7806 0.000 0.168 0.832
#> SRR1346755 3 0.2356 0.8894 0.000 0.072 0.928
#> SRR1472529 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1398905 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1082733 2 0.3752 0.8429 0.000 0.856 0.144
#> SRR1308035 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1466445 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1359080 3 0.2261 0.8951 0.000 0.068 0.932
#> SRR1455825 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1389300 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR812246 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1076632 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1415567 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1331900 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1452099 1 0.9074 0.1598 0.500 0.352 0.148
#> SRR1352346 1 0.0592 0.9734 0.988 0.012 0.000
#> SRR1364034 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1086046 1 0.1267 0.9592 0.972 0.004 0.024
#> SRR1407226 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1319363 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1446961 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1486650 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1454785 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1092329 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1091476 1 0.0592 0.9717 0.988 0.000 0.012
#> SRR1073775 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1366873 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1398114 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1089950 1 0.0237 0.9788 0.996 0.004 0.000
#> SRR1433272 2 0.3038 0.8587 0.104 0.896 0.000
#> SRR1075314 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1085590 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1100752 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1391494 2 0.3340 0.8639 0.000 0.880 0.120
#> SRR1333263 2 0.1163 0.9092 0.028 0.972 0.000
#> SRR1310231 2 0.0424 0.9195 0.000 0.992 0.008
#> SRR1094144 2 0.3482 0.8393 0.128 0.872 0.000
#> SRR1092160 3 0.6062 0.3893 0.000 0.384 0.616
#> SRR1320300 2 0.6299 0.1752 0.000 0.524 0.476
#> SRR1322747 2 0.4842 0.7447 0.000 0.776 0.224
#> SRR1432719 3 0.0892 0.9302 0.000 0.020 0.980
#> SRR1100728 2 0.2711 0.8708 0.088 0.912 0.000
#> SRR1087511 3 0.3340 0.8361 0.120 0.000 0.880
#> SRR1470336 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1322536 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1100824 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1085951 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1322046 2 0.0892 0.9174 0.000 0.980 0.020
#> SRR1316420 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1070913 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1345806 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1313872 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1337666 3 0.2625 0.8819 0.000 0.084 0.916
#> SRR1076823 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1093954 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1451921 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1491257 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1416979 3 0.5988 0.3787 0.000 0.368 0.632
#> SRR1419015 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR817649 2 0.0237 0.9196 0.000 0.996 0.004
#> SRR1466376 2 0.4062 0.8197 0.000 0.836 0.164
#> SRR1392055 2 0.3192 0.8691 0.000 0.888 0.112
#> SRR1120913 2 0.2261 0.8960 0.000 0.932 0.068
#> SRR1120869 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1319419 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR816495 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR818694 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1465653 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1465040 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1088461 2 0.0424 0.9195 0.000 0.992 0.008
#> SRR810129 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1400141 3 0.3412 0.8338 0.000 0.124 0.876
#> SRR1349585 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1437576 3 0.6286 0.0276 0.000 0.464 0.536
#> SRR814407 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1332403 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1099598 2 0.4399 0.7954 0.000 0.812 0.188
#> SRR1327723 2 0.3038 0.8733 0.000 0.896 0.104
#> SRR1392525 2 0.3851 0.8463 0.004 0.860 0.136
#> SRR1320536 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1083824 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1351390 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1309141 2 0.0424 0.9197 0.000 0.992 0.008
#> SRR1452803 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR811631 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1485563 2 0.3454 0.8598 0.104 0.888 0.008
#> SRR1311531 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1353076 2 0.3482 0.8567 0.000 0.872 0.128
#> SRR1480831 2 0.0892 0.9173 0.000 0.980 0.020
#> SRR1083892 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR809873 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1341854 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1399335 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1464209 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1389886 2 0.0747 0.9181 0.000 0.984 0.016
#> SRR1400730 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1448008 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1087606 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR816865 2 0.0592 0.9161 0.012 0.988 0.000
#> SRR1323360 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1417364 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1480329 3 0.6274 0.0760 0.000 0.456 0.544
#> SRR1403322 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.9819 1.000 0.000 0.000
#> SRR1479977 3 0.0000 0.9435 0.000 0.000 1.000
#> SRR1082035 1 0.3412 0.8583 0.876 0.124 0.000
#> SRR1393046 2 0.3482 0.8542 0.000 0.872 0.128
#> SRR1466663 2 0.0000 0.9196 0.000 1.000 0.000
#> SRR1384456 1 0.0000 0.9819 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.5453 0.66584 0.000 0.592 0.020 NA
#> SRR808862 1 0.3668 0.82372 0.808 0.004 0.000 NA
#> SRR1500382 2 0.4718 0.71883 0.000 0.708 0.012 NA
#> SRR1322683 3 0.2589 0.83862 0.000 0.000 0.884 NA
#> SRR1329811 1 0.0592 0.91226 0.984 0.000 0.000 NA
#> SRR1087297 2 0.4951 0.72996 0.000 0.744 0.044 NA
#> SRR1072626 2 0.6862 0.51166 0.000 0.560 0.128 NA
#> SRR1407428 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1321029 3 0.1118 0.84744 0.000 0.000 0.964 NA
#> SRR1500282 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR1100496 2 0.7752 0.24160 0.264 0.436 0.000 NA
#> SRR1308778 2 0.0657 0.77066 0.000 0.984 0.012 NA
#> SRR1445304 2 0.5018 0.69561 0.000 0.656 0.012 NA
#> SRR1099378 1 0.4471 0.73716 0.768 0.212 0.004 NA
#> SRR1347412 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR1099694 2 0.5859 0.66802 0.000 0.704 0.140 NA
#> SRR1088365 2 0.2329 0.75595 0.000 0.916 0.012 NA
#> SRR1325752 1 0.4936 0.52902 0.652 0.340 0.000 NA
#> SRR1416713 2 0.5310 0.65513 0.000 0.576 0.012 NA
#> SRR1074474 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1469369 3 0.5368 0.67024 0.000 0.024 0.636 NA
#> SRR1400507 3 0.2589 0.83879 0.000 0.000 0.884 NA
#> SRR1378179 2 0.0524 0.77037 0.000 0.988 0.008 NA
#> SRR1377905 3 0.7851 -0.06432 0.000 0.324 0.396 NA
#> SRR1089479 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR1073365 2 0.5364 0.66514 0.000 0.592 0.016 NA
#> SRR1500306 1 0.1978 0.89684 0.928 0.004 0.000 NA
#> SRR1101566 3 0.2921 0.83176 0.000 0.000 0.860 NA
#> SRR1350503 3 0.1209 0.84836 0.000 0.004 0.964 NA
#> SRR1446007 3 0.2408 0.84598 0.000 0.000 0.896 NA
#> SRR1102875 2 0.0657 0.77156 0.000 0.984 0.012 NA
#> SRR1380293 2 0.2611 0.76671 0.000 0.896 0.008 NA
#> SRR1331198 3 0.4387 0.76915 0.000 0.052 0.804 NA
#> SRR1092686 2 0.6778 0.36858 0.000 0.552 0.336 NA
#> SRR1069421 2 0.1118 0.76461 0.000 0.964 0.000 NA
#> SRR1341650 2 0.6357 0.57719 0.184 0.656 0.000 NA
#> SRR1357276 2 0.6756 0.59066 0.000 0.612 0.188 NA
#> SRR1498374 3 0.0921 0.84889 0.000 0.000 0.972 NA
#> SRR1093721 3 0.4793 0.70338 0.000 0.204 0.756 NA
#> SRR1464660 1 0.0592 0.91226 0.984 0.000 0.000 NA
#> SRR1402051 3 0.4855 0.74096 0.000 0.020 0.712 NA
#> SRR1488734 2 0.2402 0.77066 0.000 0.912 0.012 NA
#> SRR1082616 1 0.8327 0.30944 0.444 0.272 0.024 NA
#> SRR1099427 3 0.4499 0.79871 0.000 0.048 0.792 NA
#> SRR1453093 1 0.9356 0.20909 0.384 0.192 0.116 NA
#> SRR1357064 1 0.0376 0.91234 0.992 0.004 0.000 NA
#> SRR811237 2 0.5113 0.64683 0.000 0.712 0.036 NA
#> SRR1100848 3 0.5496 0.66135 0.000 0.232 0.704 NA
#> SRR1346755 3 0.5376 0.75686 0.000 0.088 0.736 NA
#> SRR1472529 3 0.2924 0.81628 0.000 0.100 0.884 NA
#> SRR1398905 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR1082733 2 0.6568 0.60732 0.000 0.512 0.080 NA
#> SRR1308035 3 0.2281 0.84851 0.000 0.000 0.904 NA
#> SRR1466445 3 0.2593 0.84728 0.000 0.004 0.892 NA
#> SRR1359080 3 0.4998 0.71791 0.000 0.052 0.748 NA
#> SRR1455825 3 0.0592 0.84958 0.000 0.000 0.984 NA
#> SRR1389300 3 0.1042 0.85107 0.000 0.008 0.972 NA
#> SRR812246 3 0.2773 0.83875 0.000 0.004 0.880 NA
#> SRR1076632 2 0.2125 0.75325 0.000 0.920 0.004 NA
#> SRR1415567 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1331900 3 0.2142 0.84116 0.000 0.056 0.928 NA
#> SRR1452099 2 0.8806 0.21572 0.276 0.420 0.052 NA
#> SRR1352346 1 0.2266 0.87729 0.912 0.084 0.000 NA
#> SRR1364034 2 0.0657 0.77066 0.000 0.984 0.012 NA
#> SRR1086046 1 0.7649 0.59221 0.580 0.072 0.080 NA
#> SRR1407226 1 0.0188 0.91245 0.996 0.004 0.000 NA
#> SRR1319363 1 0.2179 0.89296 0.924 0.012 0.000 NA
#> SRR1446961 3 0.1716 0.84315 0.000 0.000 0.936 NA
#> SRR1486650 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1470152 1 0.0469 0.91245 0.988 0.000 0.000 NA
#> SRR1454785 3 0.1716 0.84315 0.000 0.000 0.936 NA
#> SRR1092329 3 0.1940 0.84643 0.000 0.000 0.924 NA
#> SRR1091476 1 0.2010 0.88014 0.932 0.004 0.060 NA
#> SRR1073775 3 0.2647 0.83780 0.000 0.000 0.880 NA
#> SRR1366873 3 0.0707 0.85099 0.000 0.000 0.980 NA
#> SRR1398114 2 0.0657 0.77156 0.000 0.984 0.012 NA
#> SRR1089950 1 0.1930 0.89204 0.936 0.056 0.004 NA
#> SRR1433272 2 0.1743 0.75243 0.056 0.940 0.000 NA
#> SRR1075314 1 0.4122 0.80518 0.760 0.004 0.000 NA
#> SRR1085590 3 0.2714 0.84955 0.000 0.004 0.884 NA
#> SRR1100752 3 0.2773 0.82730 0.000 0.004 0.880 NA
#> SRR1391494 2 0.4565 0.71185 0.000 0.796 0.140 NA
#> SRR1333263 2 0.1247 0.77047 0.012 0.968 0.004 NA
#> SRR1310231 2 0.5069 0.70156 0.000 0.664 0.016 NA
#> SRR1094144 2 0.5687 0.61416 0.068 0.684 0.000 NA
#> SRR1092160 3 0.6397 0.58676 0.000 0.164 0.652 NA
#> SRR1320300 3 0.7153 -0.01713 0.000 0.424 0.444 NA
#> SRR1322747 2 0.7216 0.52822 0.000 0.448 0.140 NA
#> SRR1432719 3 0.3052 0.81734 0.000 0.004 0.860 NA
#> SRR1100728 2 0.3652 0.72455 0.052 0.856 0.000 NA
#> SRR1087511 3 0.5976 0.65007 0.012 0.032 0.616 NA
#> SRR1470336 1 0.1978 0.89684 0.928 0.004 0.000 NA
#> SRR1322536 1 0.2773 0.88117 0.880 0.004 0.000 NA
#> SRR1100824 1 0.0336 0.91231 0.992 0.000 0.000 NA
#> SRR1085951 1 0.2281 0.88261 0.904 0.000 0.000 NA
#> SRR1322046 2 0.4436 0.74581 0.000 0.800 0.052 NA
#> SRR1316420 1 0.0376 0.91234 0.992 0.004 0.000 NA
#> SRR1070913 3 0.0927 0.85252 0.000 0.008 0.976 NA
#> SRR1345806 3 0.2011 0.85011 0.000 0.000 0.920 NA
#> SRR1313872 2 0.2918 0.76309 0.000 0.876 0.008 NA
#> SRR1337666 3 0.5658 0.74113 0.040 0.056 0.756 NA
#> SRR1076823 1 0.4122 0.79849 0.760 0.004 0.000 NA
#> SRR1093954 2 0.0469 0.77107 0.000 0.988 0.012 NA
#> SRR1451921 1 0.4372 0.77776 0.728 0.004 0.000 NA
#> SRR1491257 1 0.0336 0.91231 0.992 0.000 0.000 NA
#> SRR1416979 3 0.5590 0.62316 0.000 0.244 0.692 NA
#> SRR1419015 1 0.4284 0.78957 0.764 0.012 0.000 NA
#> SRR817649 2 0.4810 0.75572 0.064 0.808 0.020 NA
#> SRR1466376 2 0.6915 0.56587 0.000 0.476 0.108 NA
#> SRR1392055 2 0.6354 0.61418 0.000 0.520 0.064 NA
#> SRR1120913 2 0.6413 0.60954 0.000 0.516 0.068 NA
#> SRR1120869 2 0.0376 0.77004 0.000 0.992 0.004 NA
#> SRR1319419 3 0.1022 0.84861 0.000 0.000 0.968 NA
#> SRR816495 3 0.2469 0.83110 0.000 0.000 0.892 NA
#> SRR818694 3 0.5018 0.69086 0.000 0.012 0.656 NA
#> SRR1465653 1 0.0592 0.91226 0.984 0.000 0.000 NA
#> SRR1475952 1 0.1902 0.89801 0.932 0.004 0.000 NA
#> SRR1465040 3 0.2216 0.84328 0.000 0.000 0.908 NA
#> SRR1088461 2 0.0707 0.77080 0.000 0.980 0.020 NA
#> SRR810129 2 0.0657 0.77156 0.000 0.984 0.012 NA
#> SRR1400141 3 0.4786 0.77041 0.000 0.104 0.788 NA
#> SRR1349585 1 0.0376 0.91234 0.992 0.004 0.000 NA
#> SRR1437576 3 0.7597 0.00478 0.000 0.356 0.440 NA
#> SRR814407 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR1332403 2 0.5093 0.69085 0.000 0.640 0.012 NA
#> SRR1099598 2 0.7019 0.46989 0.000 0.524 0.132 NA
#> SRR1327723 2 0.6222 0.62420 0.000 0.532 0.056 NA
#> SRR1392525 2 0.6872 0.51429 0.008 0.564 0.096 NA
#> SRR1320536 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1083824 3 0.3443 0.80422 0.000 0.016 0.848 NA
#> SRR1351390 1 0.1471 0.90453 0.960 0.012 0.024 NA
#> SRR1309141 2 0.1042 0.77267 0.000 0.972 0.008 NA
#> SRR1452803 2 0.2255 0.77026 0.000 0.920 0.012 NA
#> SRR811631 3 0.1211 0.85092 0.000 0.000 0.960 NA
#> SRR1485563 2 0.6465 0.59175 0.056 0.636 0.024 NA
#> SRR1311531 3 0.2408 0.84724 0.000 0.000 0.896 NA
#> SRR1353076 2 0.5280 0.67741 0.000 0.752 0.120 NA
#> SRR1480831 2 0.5444 0.62848 0.000 0.688 0.048 NA
#> SRR1083892 1 0.0376 0.91234 0.992 0.004 0.000 NA
#> SRR809873 1 0.3032 0.86052 0.868 0.008 0.000 NA
#> SRR1341854 2 0.1584 0.77368 0.000 0.952 0.012 NA
#> SRR1399335 2 0.2610 0.76834 0.000 0.900 0.012 NA
#> SRR1464209 1 0.0336 0.91231 0.992 0.000 0.000 NA
#> SRR1389886 2 0.5476 0.66067 0.000 0.584 0.020 NA
#> SRR1400730 1 0.0188 0.91234 0.996 0.000 0.000 NA
#> SRR1448008 3 0.3123 0.82451 0.000 0.000 0.844 NA
#> SRR1087606 1 0.0844 0.91078 0.980 0.012 0.004 NA
#> SRR1445111 1 0.0188 0.91205 0.996 0.000 0.000 NA
#> SRR816865 2 0.2473 0.74794 0.012 0.908 0.000 NA
#> SRR1323360 3 0.2216 0.83646 0.000 0.000 0.908 NA
#> SRR1417364 3 0.2647 0.82594 0.000 0.000 0.880 NA
#> SRR1480329 2 0.7003 0.05477 0.000 0.460 0.424 NA
#> SRR1403322 1 0.1978 0.89684 0.928 0.004 0.000 NA
#> SRR1093625 1 0.0921 0.90973 0.972 0.000 0.000 NA
#> SRR1479977 3 0.1211 0.84787 0.000 0.000 0.960 NA
#> SRR1082035 1 0.4773 0.64236 0.708 0.280 0.004 NA
#> SRR1393046 2 0.6638 0.58865 0.000 0.496 0.084 NA
#> SRR1466663 2 0.0524 0.76979 0.000 0.988 0.004 NA
#> SRR1384456 1 0.0921 0.90973 0.972 0.000 0.000 NA
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1043 0.65038 0.000 0.960 0.040 0.000 0.000
#> SRR808862 1 0.6058 0.70768 0.676 0.000 0.148 0.084 0.092
#> SRR1500382 2 0.2067 0.66319 0.000 0.920 0.032 0.048 0.000
#> SRR1322683 5 0.6264 0.68310 0.000 0.160 0.344 0.000 0.496
#> SRR1329811 1 0.4594 0.76098 0.680 0.000 0.000 0.036 0.284
#> SRR1087297 2 0.3090 0.65769 0.000 0.860 0.088 0.052 0.000
#> SRR1072626 4 0.7369 0.32196 0.000 0.268 0.056 0.480 0.196
#> SRR1407428 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1321029 3 0.3574 0.59415 0.000 0.168 0.804 0.000 0.028
#> SRR1500282 1 0.1410 0.80332 0.940 0.000 0.000 0.000 0.060
#> SRR1100496 4 0.6889 0.46745 0.200 0.076 0.012 0.608 0.104
#> SRR1308778 2 0.4387 0.44699 0.000 0.640 0.012 0.348 0.000
#> SRR1445304 2 0.1928 0.64968 0.000 0.920 0.004 0.072 0.004
#> SRR1099378 1 0.6140 0.48555 0.576 0.100 0.000 0.304 0.020
#> SRR1347412 1 0.1809 0.80652 0.928 0.000 0.012 0.000 0.060
#> SRR1099694 2 0.4210 0.65932 0.000 0.780 0.096 0.124 0.000
#> SRR1088365 2 0.4452 0.09005 0.000 0.500 0.004 0.496 0.000
#> SRR1325752 1 0.6092 0.28351 0.520 0.092 0.012 0.376 0.000
#> SRR1416713 2 0.1282 0.64830 0.000 0.952 0.044 0.000 0.004
#> SRR1074474 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1469369 5 0.6699 0.67375 0.000 0.124 0.220 0.064 0.592
#> SRR1400507 5 0.6244 0.69141 0.000 0.160 0.336 0.000 0.504
#> SRR1378179 2 0.4517 0.34176 0.000 0.600 0.012 0.388 0.000
#> SRR1377905 2 0.4003 0.31524 0.000 0.704 0.288 0.008 0.000
#> SRR1089479 1 0.0290 0.79989 0.992 0.000 0.008 0.000 0.000
#> SRR1073365 2 0.1124 0.64855 0.000 0.960 0.036 0.000 0.004
#> SRR1500306 1 0.5190 0.74329 0.736 0.000 0.148 0.072 0.044
#> SRR1101566 5 0.6087 0.72214 0.000 0.160 0.288 0.000 0.552
#> SRR1350503 3 0.3488 0.59600 0.000 0.168 0.808 0.000 0.024
#> SRR1446007 3 0.6341 -0.45137 0.000 0.160 0.444 0.000 0.396
#> SRR1102875 2 0.3480 0.57895 0.000 0.752 0.000 0.248 0.000
#> SRR1380293 2 0.3318 0.62699 0.000 0.808 0.012 0.180 0.000
#> SRR1331198 3 0.4108 0.50635 0.000 0.308 0.684 0.008 0.000
#> SRR1092686 2 0.5114 0.59764 0.000 0.704 0.180 0.112 0.004
#> SRR1069421 4 0.4659 -0.06838 0.000 0.488 0.012 0.500 0.000
#> SRR1341650 4 0.6557 0.54224 0.132 0.232 0.012 0.600 0.024
#> SRR1357276 2 0.3736 0.63948 0.000 0.808 0.140 0.052 0.000
#> SRR1498374 3 0.4215 0.57745 0.000 0.168 0.768 0.000 0.064
#> SRR1093721 2 0.7367 -0.00357 0.000 0.484 0.256 0.056 0.204
#> SRR1464660 1 0.4594 0.76098 0.680 0.000 0.000 0.036 0.284
#> SRR1402051 5 0.6770 0.72086 0.000 0.136 0.268 0.044 0.552
#> SRR1488734 2 0.3081 0.63714 0.000 0.832 0.012 0.156 0.000
#> SRR1082616 4 0.7933 0.38119 0.204 0.076 0.016 0.476 0.228
#> SRR1099427 5 0.6506 0.70869 0.000 0.172 0.228 0.024 0.576
#> SRR1453093 4 0.9451 0.15177 0.212 0.112 0.100 0.296 0.280
#> SRR1357064 1 0.3461 0.79565 0.772 0.000 0.000 0.004 0.224
#> SRR811237 4 0.6000 0.36040 0.000 0.340 0.016 0.560 0.084
#> SRR1100848 2 0.8287 -0.46197 0.000 0.328 0.280 0.124 0.268
#> SRR1346755 5 0.6880 0.66732 0.000 0.176 0.216 0.048 0.560
#> SRR1472529 3 0.6194 0.16264 0.000 0.388 0.472 0.000 0.140
#> SRR1398905 1 0.2362 0.80106 0.900 0.000 0.084 0.008 0.008
#> SRR1082733 2 0.2193 0.62881 0.000 0.900 0.092 0.000 0.008
#> SRR1308035 3 0.6334 -0.42370 0.000 0.160 0.452 0.000 0.388
#> SRR1466445 3 0.6334 -0.42370 0.000 0.160 0.452 0.000 0.388
#> SRR1359080 3 0.3999 0.47462 0.000 0.344 0.656 0.000 0.000
#> SRR1455825 3 0.5195 0.49184 0.000 0.168 0.688 0.000 0.144
#> SRR1389300 3 0.5578 0.42800 0.000 0.180 0.644 0.000 0.176
#> SRR812246 5 0.6952 0.68997 0.000 0.128 0.320 0.048 0.504
#> SRR1076632 4 0.4306 0.38566 0.000 0.328 0.012 0.660 0.000
#> SRR1415567 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1331900 3 0.6043 0.30088 0.000 0.320 0.540 0.000 0.140
#> SRR1452099 4 0.7551 0.49544 0.180 0.088 0.028 0.568 0.136
#> SRR1352346 1 0.5854 0.70031 0.692 0.068 0.004 0.168 0.068
#> SRR1364034 2 0.3796 0.52762 0.000 0.700 0.000 0.300 0.000
#> SRR1086046 4 0.8201 -0.02314 0.316 0.012 0.072 0.352 0.248
#> SRR1407226 1 0.4122 0.80722 0.796 0.000 0.008 0.064 0.132
#> SRR1319363 1 0.5410 0.73420 0.724 0.056 0.036 0.172 0.012
#> SRR1446961 3 0.2732 0.59539 0.000 0.160 0.840 0.000 0.000
#> SRR1486650 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1470152 1 0.4250 0.77952 0.720 0.000 0.000 0.028 0.252
#> SRR1454785 3 0.3695 0.59182 0.000 0.164 0.800 0.000 0.036
#> SRR1092329 5 0.6373 0.44885 0.000 0.164 0.416 0.000 0.420
#> SRR1091476 1 0.6117 0.58015 0.700 0.104 0.112 0.064 0.020
#> SRR1073775 5 0.6254 0.68805 0.000 0.160 0.340 0.000 0.500
#> SRR1366873 3 0.5981 0.19383 0.000 0.160 0.576 0.000 0.264
#> SRR1398114 2 0.3774 0.53184 0.000 0.704 0.000 0.296 0.000
#> SRR1089950 1 0.5550 0.70051 0.700 0.064 0.004 0.192 0.040
#> SRR1433272 2 0.5214 0.13482 0.024 0.540 0.012 0.424 0.000
#> SRR1075314 1 0.6889 0.64307 0.600 0.000 0.148 0.144 0.108
#> SRR1085590 3 0.6372 -0.36678 0.000 0.168 0.456 0.000 0.376
#> SRR1100752 3 0.3171 0.59486 0.000 0.176 0.816 0.008 0.000
#> SRR1391494 2 0.4973 0.63146 0.000 0.736 0.120 0.132 0.012
#> SRR1333263 2 0.4270 0.41379 0.000 0.668 0.012 0.320 0.000
#> SRR1310231 2 0.1399 0.65793 0.000 0.952 0.028 0.020 0.000
#> SRR1094144 4 0.4110 0.55175 0.028 0.184 0.012 0.776 0.000
#> SRR1092160 3 0.5000 0.37673 0.000 0.388 0.576 0.036 0.000
#> SRR1320300 2 0.6530 0.32465 0.000 0.588 0.168 0.032 0.212
#> SRR1322747 2 0.2583 0.59261 0.000 0.864 0.132 0.000 0.004
#> SRR1432719 3 0.3388 0.58518 0.000 0.200 0.792 0.008 0.000
#> SRR1100728 4 0.4464 0.42639 0.008 0.304 0.012 0.676 0.000
#> SRR1087511 5 0.6347 0.69322 0.000 0.144 0.204 0.036 0.616
#> SRR1470336 1 0.5049 0.74625 0.748 0.000 0.140 0.068 0.044
#> SRR1322536 1 0.6618 0.67083 0.628 0.000 0.148 0.116 0.108
#> SRR1100824 1 0.3461 0.79565 0.772 0.000 0.000 0.004 0.224
#> SRR1085951 1 0.5182 0.76891 0.680 0.000 0.000 0.112 0.208
#> SRR1322046 2 0.3164 0.66224 0.000 0.852 0.044 0.104 0.000
#> SRR1316420 1 0.3954 0.79746 0.772 0.000 0.000 0.036 0.192
#> SRR1070913 3 0.6043 0.23117 0.000 0.176 0.572 0.000 0.252
#> SRR1345806 3 0.6281 -0.27327 0.000 0.160 0.488 0.000 0.352
#> SRR1313872 2 0.3203 0.63512 0.000 0.820 0.012 0.168 0.000
#> SRR1337666 3 0.4464 0.50524 0.012 0.304 0.676 0.008 0.000
#> SRR1076823 1 0.7024 0.62288 0.584 0.000 0.148 0.160 0.108
#> SRR1093954 2 0.3816 0.52259 0.000 0.696 0.000 0.304 0.000
#> SRR1451921 1 0.7445 0.53950 0.520 0.000 0.148 0.224 0.108
#> SRR1491257 1 0.3720 0.79323 0.760 0.000 0.000 0.012 0.228
#> SRR1416979 5 0.7899 0.39891 0.000 0.260 0.284 0.076 0.380
#> SRR1419015 1 0.6770 0.30945 0.452 0.056 0.004 0.420 0.068
#> SRR817649 2 0.4378 0.59243 0.040 0.760 0.012 0.188 0.000
#> SRR1466376 2 0.2439 0.61131 0.000 0.876 0.120 0.000 0.004
#> SRR1392055 2 0.1952 0.63767 0.000 0.912 0.084 0.000 0.004
#> SRR1120913 2 0.2011 0.63267 0.000 0.908 0.088 0.000 0.004
#> SRR1120869 2 0.4637 0.13741 0.000 0.536 0.012 0.452 0.000
#> SRR1319419 3 0.5162 0.45840 0.000 0.160 0.692 0.000 0.148
#> SRR816495 3 0.3048 0.59936 0.000 0.176 0.820 0.000 0.004
#> SRR818694 5 0.5961 0.70338 0.000 0.156 0.204 0.012 0.628
#> SRR1465653 1 0.4594 0.76098 0.680 0.000 0.000 0.036 0.284
#> SRR1475952 1 0.3931 0.76455 0.832 0.000 0.072 0.056 0.040
#> SRR1465040 5 0.6347 0.50327 0.000 0.160 0.408 0.000 0.432
#> SRR1088461 2 0.4314 0.54427 0.000 0.700 0.016 0.280 0.004
#> SRR810129 2 0.3774 0.53282 0.000 0.704 0.000 0.296 0.000
#> SRR1400141 2 0.5320 -0.17439 0.000 0.508 0.452 0.028 0.012
#> SRR1349585 1 0.3461 0.79565 0.772 0.000 0.000 0.004 0.224
#> SRR1437576 2 0.4491 0.41254 0.000 0.708 0.260 0.008 0.024
#> SRR814407 1 0.0609 0.80012 0.980 0.000 0.020 0.000 0.000
#> SRR1332403 2 0.1202 0.64672 0.000 0.960 0.004 0.032 0.004
#> SRR1099598 4 0.7149 0.43142 0.000 0.240 0.044 0.508 0.208
#> SRR1327723 2 0.1952 0.63456 0.000 0.912 0.084 0.000 0.004
#> SRR1392525 4 0.5743 0.57747 0.000 0.140 0.032 0.684 0.144
#> SRR1320536 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1083824 3 0.3855 0.56491 0.000 0.240 0.748 0.008 0.004
#> SRR1351390 1 0.5408 0.72391 0.724 0.008 0.084 0.156 0.028
#> SRR1309141 2 0.3630 0.60943 0.000 0.780 0.016 0.204 0.000
#> SRR1452803 2 0.3318 0.62813 0.000 0.808 0.012 0.180 0.000
#> SRR811631 3 0.6269 -0.09142 0.000 0.168 0.508 0.000 0.324
#> SRR1485563 4 0.5489 0.57348 0.008 0.184 0.020 0.704 0.084
#> SRR1311531 3 0.6341 -0.45137 0.000 0.160 0.444 0.000 0.396
#> SRR1353076 2 0.7054 -0.16533 0.000 0.416 0.032 0.392 0.160
#> SRR1480831 4 0.6264 0.40894 0.000 0.316 0.016 0.552 0.116
#> SRR1083892 1 0.3551 0.79636 0.772 0.000 0.000 0.008 0.220
#> SRR809873 1 0.7092 0.67793 0.624 0.052 0.116 0.156 0.052
#> SRR1341854 2 0.3861 0.55387 0.000 0.712 0.004 0.284 0.000
#> SRR1399335 2 0.3355 0.62461 0.000 0.804 0.012 0.184 0.000
#> SRR1464209 1 0.3461 0.79565 0.772 0.000 0.000 0.004 0.224
#> SRR1389886 2 0.1571 0.64445 0.000 0.936 0.060 0.000 0.004
#> SRR1400730 1 0.3305 0.79652 0.776 0.000 0.000 0.000 0.224
#> SRR1448008 5 0.6514 0.66413 0.000 0.156 0.356 0.008 0.480
#> SRR1087606 1 0.4528 0.79164 0.756 0.004 0.000 0.080 0.160
#> SRR1445111 1 0.0162 0.79986 0.996 0.000 0.004 0.000 0.000
#> SRR816865 4 0.4298 0.33687 0.000 0.352 0.008 0.640 0.000
#> SRR1323360 3 0.3612 0.59818 0.000 0.172 0.800 0.000 0.028
#> SRR1417364 3 0.3474 0.59498 0.000 0.192 0.796 0.008 0.004
#> SRR1480329 2 0.8532 -0.02093 0.004 0.360 0.188 0.208 0.240
#> SRR1403322 1 0.5437 0.73590 0.720 0.000 0.148 0.080 0.052
#> SRR1093625 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
#> SRR1479977 3 0.3734 0.59314 0.000 0.168 0.796 0.000 0.036
#> SRR1082035 1 0.6545 0.47436 0.572 0.112 0.004 0.280 0.032
#> SRR1393046 2 0.2124 0.62812 0.000 0.900 0.096 0.000 0.004
#> SRR1466663 2 0.4627 0.15368 0.000 0.544 0.012 0.444 0.000
#> SRR1384456 1 0.1788 0.79568 0.932 0.000 0.004 0.056 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.4114 0.6255 0.116 0.768 0.108 NA 0.000 0.004
#> SRR808862 6 0.3288 0.7940 0.000 0.000 0.000 NA 0.276 0.724
#> SRR1500382 2 0.3118 0.6650 0.092 0.836 0.072 NA 0.000 0.000
#> SRR1322683 3 0.5195 0.6931 0.000 0.100 0.540 NA 0.000 0.000
#> SRR1329811 5 0.5543 0.1834 0.000 0.000 0.000 NA 0.524 0.156
#> SRR1087297 2 0.3079 0.6665 0.096 0.844 0.056 NA 0.000 0.000
#> SRR1072626 2 0.7301 0.2691 0.248 0.400 0.228 NA 0.000 0.000
#> SRR1407428 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
#> SRR1321029 3 0.3257 0.6885 0.000 0.152 0.816 NA 0.000 0.020
#> SRR1500282 5 0.5563 -0.5818 0.332 0.000 0.000 NA 0.528 0.004
#> SRR1100496 5 0.9094 0.1001 0.200 0.184 0.072 NA 0.360 0.096
#> SRR1308778 2 0.2153 0.6781 0.084 0.900 0.008 NA 0.004 0.000
#> SRR1445304 2 0.3414 0.6630 0.080 0.832 0.076 NA 0.000 0.008
#> SRR1099378 5 0.5434 0.2083 0.024 0.260 0.032 NA 0.648 0.012
#> SRR1347412 5 0.6305 -0.5825 0.312 0.000 0.000 NA 0.504 0.052
#> SRR1099694 2 0.1606 0.6859 0.008 0.932 0.056 NA 0.000 0.000
#> SRR1088365 2 0.4367 0.6028 0.248 0.696 0.048 NA 0.000 0.000
#> SRR1325752 5 0.6935 0.1646 0.076 0.236 0.068 NA 0.564 0.028
#> SRR1416713 2 0.4034 0.6287 0.120 0.780 0.088 NA 0.000 0.008
#> SRR1074474 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
#> SRR1469369 3 0.5479 0.5532 0.000 0.056 0.472 NA 0.012 0.012
#> SRR1400507 3 0.5341 0.7033 0.000 0.108 0.552 NA 0.000 0.004
#> SRR1378179 2 0.2722 0.6683 0.088 0.872 0.004 NA 0.032 0.000
#> SRR1377905 2 0.5128 0.4859 0.116 0.636 0.240 NA 0.000 0.000
#> SRR1089479 5 0.6527 -0.6039 0.320 0.000 0.000 NA 0.480 0.128
#> SRR1073365 2 0.4308 0.6204 0.120 0.756 0.112 NA 0.000 0.008
#> SRR1500306 6 0.4587 0.6589 0.000 0.000 0.000 NA 0.356 0.596
#> SRR1101566 3 0.5211 0.6784 0.000 0.096 0.516 NA 0.000 0.000
#> SRR1350503 3 0.3421 0.6825 0.000 0.160 0.804 NA 0.000 0.020
#> SRR1446007 3 0.5175 0.7150 0.004 0.100 0.588 NA 0.000 0.000
#> SRR1102875 2 0.2278 0.6907 0.044 0.900 0.052 NA 0.000 0.000
#> SRR1380293 2 0.0458 0.6902 0.016 0.984 0.000 NA 0.000 0.000
#> SRR1331198 3 0.4403 0.5577 0.000 0.280 0.676 NA 0.000 0.024
#> SRR1092686 2 0.1913 0.6837 0.012 0.920 0.060 NA 0.004 0.000
#> SRR1069421 2 0.5114 0.5609 0.132 0.704 0.028 NA 0.128 0.000
#> SRR1341650 5 0.7985 -0.0281 0.248 0.316 0.072 NA 0.316 0.008
#> SRR1357276 2 0.3275 0.6468 0.052 0.836 0.100 NA 0.000 0.000
#> SRR1498374 3 0.2631 0.7043 0.000 0.128 0.856 NA 0.000 0.004
#> SRR1093721 2 0.5829 0.0535 0.024 0.524 0.336 NA 0.000 0.000
#> SRR1464660 5 0.5543 0.1834 0.000 0.000 0.000 NA 0.524 0.156
#> SRR1402051 3 0.5376 0.5884 0.000 0.064 0.492 NA 0.012 0.004
#> SRR1488734 2 0.1633 0.6899 0.024 0.932 0.044 NA 0.000 0.000
#> SRR1082616 5 0.9596 0.0428 0.104 0.184 0.084 NA 0.280 0.184
#> SRR1099427 3 0.5596 0.5884 0.008 0.112 0.480 NA 0.000 0.000
#> SRR1453093 3 0.9301 0.0324 0.080 0.100 0.340 NA 0.116 0.204
#> SRR1357064 5 0.3409 0.1857 0.000 0.000 0.000 NA 0.700 0.000
#> SRR811237 2 0.6006 0.4994 0.260 0.568 0.124 NA 0.000 0.000
#> SRR1100848 2 0.7092 -0.1800 0.084 0.384 0.316 NA 0.000 0.000
#> SRR1346755 3 0.6089 0.5395 0.016 0.164 0.444 NA 0.000 0.000
#> SRR1472529 3 0.4745 0.4132 0.012 0.384 0.572 NA 0.000 0.000
#> SRR1398905 5 0.6678 -0.3781 0.156 0.000 0.000 NA 0.480 0.288
#> SRR1082733 2 0.4807 0.5626 0.112 0.700 0.176 NA 0.000 0.008
#> SRR1308035 3 0.5618 0.7167 0.004 0.132 0.544 NA 0.004 0.000
#> SRR1466445 3 0.5528 0.7169 0.004 0.124 0.560 NA 0.004 0.000
#> SRR1359080 3 0.5087 0.5491 0.056 0.248 0.664 NA 0.000 0.016
#> SRR1455825 3 0.3620 0.7095 0.000 0.140 0.804 NA 0.000 0.020
#> SRR1389300 3 0.4324 0.7167 0.000 0.152 0.752 NA 0.000 0.020
#> SRR812246 3 0.5171 0.6105 0.000 0.076 0.512 NA 0.004 0.000
#> SRR1076632 2 0.7177 0.2832 0.292 0.460 0.068 NA 0.152 0.000
#> SRR1415567 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
#> SRR1331900 3 0.4358 0.6015 0.000 0.276 0.680 NA 0.000 0.012
#> SRR1452099 5 0.9327 0.0993 0.132 0.264 0.080 NA 0.300 0.100
#> SRR1352346 5 0.3920 0.2144 0.024 0.092 0.000 NA 0.804 0.004
#> SRR1364034 2 0.2420 0.6874 0.076 0.888 0.032 NA 0.000 0.000
#> SRR1086046 5 0.9117 -0.0212 0.032 0.088 0.204 NA 0.308 0.192
#> SRR1407226 5 0.4119 0.0398 0.084 0.000 0.000 NA 0.760 0.008
#> SRR1319363 5 0.5068 0.1148 0.016 0.040 0.040 NA 0.732 0.156
#> SRR1446961 3 0.3647 0.6850 0.004 0.160 0.796 NA 0.000 0.020
#> SRR1486650 1 0.3966 0.9724 0.552 0.000 0.000 NA 0.444 0.004
#> SRR1470152 5 0.5095 0.1881 0.000 0.000 0.000 NA 0.584 0.104
#> SRR1454785 3 0.2886 0.6992 0.004 0.144 0.836 NA 0.000 0.000
#> SRR1092329 3 0.5199 0.7167 0.000 0.120 0.580 NA 0.000 0.000
#> SRR1091476 5 0.5842 0.0509 0.004 0.072 0.284 NA 0.592 0.008
#> SRR1073775 3 0.5105 0.7006 0.000 0.096 0.564 NA 0.000 0.000
#> SRR1366873 3 0.3956 0.7280 0.000 0.104 0.788 NA 0.000 0.016
#> SRR1398114 2 0.2461 0.6890 0.064 0.888 0.044 NA 0.000 0.000
#> SRR1089950 5 0.3586 0.2041 0.016 0.108 0.008 NA 0.832 0.016
#> SRR1433272 2 0.4152 0.6250 0.080 0.788 0.012 NA 0.108 0.004
#> SRR1075314 6 0.2854 0.8369 0.000 0.000 0.000 NA 0.208 0.792
#> SRR1085590 3 0.5799 0.7128 0.004 0.164 0.528 NA 0.004 0.000
#> SRR1100752 3 0.4052 0.6638 0.004 0.192 0.760 NA 0.004 0.020
#> SRR1391494 2 0.2615 0.6504 0.008 0.852 0.136 NA 0.000 0.000
#> SRR1333263 2 0.2560 0.6607 0.036 0.872 0.000 NA 0.092 0.000
#> SRR1310231 2 0.3285 0.6563 0.116 0.820 0.064 NA 0.000 0.000
#> SRR1094144 2 0.7872 0.0310 0.300 0.316 0.072 NA 0.272 0.004
#> SRR1092160 2 0.4947 -0.0325 0.008 0.492 0.464 NA 0.000 0.024
#> SRR1320300 2 0.6052 -0.0797 0.016 0.452 0.404 NA 0.000 0.008
#> SRR1322747 2 0.5138 0.4913 0.120 0.656 0.212 NA 0.000 0.008
#> SRR1432719 3 0.4791 0.5959 0.012 0.244 0.692 NA 0.008 0.024
#> SRR1100728 2 0.7430 0.1624 0.300 0.384 0.064 NA 0.228 0.000
#> SRR1087511 3 0.5074 0.5775 0.000 0.056 0.496 NA 0.000 0.008
#> SRR1470336 6 0.5682 0.5367 0.040 0.000 0.000 NA 0.368 0.524
#> SRR1322536 6 0.2854 0.8369 0.000 0.000 0.000 NA 0.208 0.792
#> SRR1100824 5 0.3428 0.1838 0.000 0.000 0.000 NA 0.696 0.000
#> SRR1085951 5 0.6227 0.1218 0.000 0.024 0.112 NA 0.596 0.044
#> SRR1322046 2 0.1327 0.6829 0.000 0.936 0.064 NA 0.000 0.000
#> SRR1316420 5 0.2793 0.1898 0.000 0.000 0.000 NA 0.800 0.000
#> SRR1070913 3 0.4523 0.7239 0.000 0.144 0.724 NA 0.000 0.008
#> SRR1345806 3 0.5389 0.7244 0.004 0.140 0.584 NA 0.000 0.000
#> SRR1313872 2 0.1448 0.6923 0.016 0.948 0.024 NA 0.012 0.000
#> SRR1337666 3 0.5121 0.5240 0.016 0.292 0.640 NA 0.008 0.024
#> SRR1076823 6 0.2996 0.8360 0.000 0.000 0.000 NA 0.228 0.772
#> SRR1093954 2 0.2641 0.6874 0.072 0.876 0.048 NA 0.000 0.000
#> SRR1451921 6 0.3134 0.8245 0.004 0.000 0.000 NA 0.208 0.784
#> SRR1491257 5 0.3446 0.1836 0.000 0.000 0.000 NA 0.692 0.000
#> SRR1416979 3 0.6687 0.5471 0.040 0.276 0.424 NA 0.000 0.000
#> SRR1419015 5 0.7265 0.0609 0.100 0.048 0.068 NA 0.568 0.184
#> SRR817649 2 0.1353 0.6886 0.024 0.952 0.012 NA 0.012 0.000
#> SRR1466376 2 0.4753 0.5566 0.116 0.708 0.164 NA 0.000 0.008
#> SRR1392055 2 0.4856 0.5649 0.120 0.696 0.172 NA 0.000 0.008
#> SRR1120913 2 0.4726 0.5792 0.120 0.712 0.156 NA 0.000 0.008
#> SRR1120869 2 0.4168 0.6211 0.096 0.784 0.024 NA 0.092 0.000
#> SRR1319419 3 0.3782 0.7168 0.004 0.140 0.784 NA 0.000 0.000
#> SRR816495 3 0.3852 0.6598 0.000 0.192 0.764 NA 0.000 0.020
#> SRR818694 3 0.4955 0.6388 0.000 0.056 0.520 NA 0.000 0.004
#> SRR1465653 5 0.5543 0.1834 0.000 0.000 0.000 NA 0.524 0.156
#> SRR1475952 5 0.6826 -0.4197 0.184 0.000 0.000 NA 0.376 0.376
#> SRR1465040 3 0.5027 0.7132 0.000 0.100 0.596 NA 0.000 0.000
#> SRR1088461 2 0.2471 0.6895 0.052 0.888 0.056 NA 0.000 0.000
#> SRR810129 2 0.2507 0.6880 0.072 0.884 0.040 NA 0.000 0.000
#> SRR1400141 2 0.4310 0.0288 0.000 0.580 0.396 NA 0.000 0.000
#> SRR1349585 5 0.3428 0.1850 0.000 0.000 0.000 NA 0.696 0.000
#> SRR1437576 2 0.4697 0.0162 0.008 0.536 0.432 NA 0.000 0.012
#> SRR814407 5 0.6649 -0.5717 0.296 0.000 0.000 NA 0.480 0.148
#> SRR1332403 2 0.3500 0.6576 0.116 0.820 0.052 NA 0.000 0.008
#> SRR1099598 2 0.7835 0.2145 0.244 0.344 0.252 NA 0.016 0.000
#> SRR1327723 2 0.4652 0.5794 0.116 0.720 0.152 NA 0.000 0.008
#> SRR1392525 2 0.8603 0.1532 0.240 0.368 0.088 NA 0.176 0.016
#> SRR1320536 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
#> SRR1083824 3 0.4310 0.6149 0.000 0.236 0.712 NA 0.000 0.024
#> SRR1351390 5 0.5003 0.1106 0.000 0.032 0.164 NA 0.724 0.048
#> SRR1309141 2 0.1492 0.6851 0.024 0.940 0.000 NA 0.036 0.000
#> SRR1452803 2 0.1334 0.6900 0.020 0.948 0.032 NA 0.000 0.000
#> SRR811631 3 0.5081 0.7308 0.000 0.124 0.676 NA 0.000 0.020
#> SRR1485563 2 0.7968 0.1778 0.260 0.392 0.084 NA 0.196 0.000
#> SRR1311531 3 0.5280 0.7165 0.004 0.108 0.572 NA 0.000 0.000
#> SRR1353076 2 0.7046 0.3729 0.248 0.456 0.180 NA 0.000 0.000
#> SRR1480831 2 0.6275 0.4558 0.256 0.548 0.128 NA 0.000 0.000
#> SRR1083892 5 0.3136 0.1761 0.000 0.000 0.000 NA 0.768 0.004
#> SRR809873 5 0.4357 -0.3800 0.012 0.000 0.000 NA 0.560 0.420
#> SRR1341854 2 0.2113 0.6904 0.060 0.908 0.028 NA 0.000 0.000
#> SRR1399335 2 0.1176 0.6908 0.020 0.956 0.024 NA 0.000 0.000
#> SRR1464209 5 0.3428 0.1850 0.000 0.000 0.000 NA 0.696 0.000
#> SRR1389886 2 0.4657 0.5884 0.120 0.720 0.148 NA 0.000 0.008
#> SRR1400730 5 0.3499 0.1797 0.000 0.000 0.000 NA 0.680 0.000
#> SRR1448008 3 0.5353 0.7037 0.000 0.120 0.528 NA 0.000 0.000
#> SRR1087606 5 0.4035 0.2048 0.004 0.056 0.000 NA 0.744 0.000
#> SRR1445111 5 0.6450 -0.6214 0.332 0.000 0.000 NA 0.480 0.120
#> SRR816865 2 0.5769 0.4529 0.272 0.580 0.016 NA 0.124 0.000
#> SRR1323360 3 0.3142 0.6930 0.004 0.156 0.820 NA 0.000 0.004
#> SRR1417364 3 0.4096 0.6463 0.000 0.204 0.744 NA 0.000 0.024
#> SRR1480329 2 0.7257 0.1359 0.068 0.420 0.336 NA 0.020 0.004
#> SRR1403322 6 0.3371 0.7912 0.000 0.000 0.000 NA 0.292 0.708
#> SRR1093625 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
#> SRR1479977 3 0.2958 0.6875 0.000 0.160 0.824 NA 0.000 0.008
#> SRR1082035 5 0.3744 0.2299 0.036 0.168 0.000 NA 0.784 0.004
#> SRR1393046 2 0.4825 0.5631 0.120 0.700 0.168 NA 0.000 0.008
#> SRR1466663 2 0.4745 0.5871 0.088 0.744 0.028 NA 0.128 0.000
#> SRR1384456 1 0.3950 0.9954 0.564 0.000 0.000 NA 0.432 0.004
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 17467 rows and 159 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.973 0.952 0.980 0.4042 0.603 0.603
#> 3 3 0.406 0.605 0.770 0.4334 0.899 0.836
#> 4 4 0.377 0.468 0.677 0.1667 0.811 0.659
#> 5 5 0.555 0.597 0.744 0.1030 0.774 0.491
#> 6 6 0.642 0.655 0.820 0.0537 0.901 0.668
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
#> SRR810713 2 0.0000 0.980 0.000 1.000
#> SRR808862 1 0.0000 0.976 1.000 0.000
#> SRR1500382 2 0.0000 0.980 0.000 1.000
#> SRR1322683 2 0.0000 0.980 0.000 1.000
#> SRR1329811 1 0.4431 0.891 0.908 0.092
#> SRR1087297 2 0.0000 0.980 0.000 1.000
#> SRR1072626 2 0.0000 0.980 0.000 1.000
#> SRR1407428 1 0.0000 0.976 1.000 0.000
#> SRR1321029 2 0.0000 0.980 0.000 1.000
#> SRR1500282 1 0.0000 0.976 1.000 0.000
#> SRR1100496 2 0.9129 0.516 0.328 0.672
#> SRR1308778 2 0.0000 0.980 0.000 1.000
#> SRR1445304 2 0.0000 0.980 0.000 1.000
#> SRR1099378 1 0.4298 0.897 0.912 0.088
#> SRR1347412 1 0.0000 0.976 1.000 0.000
#> SRR1099694 2 0.0000 0.980 0.000 1.000
#> SRR1088365 2 0.0000 0.980 0.000 1.000
#> SRR1325752 2 0.7950 0.684 0.240 0.760
#> SRR1416713 2 0.0000 0.980 0.000 1.000
#> SRR1074474 1 0.0000 0.976 1.000 0.000
#> SRR1469369 2 0.0000 0.980 0.000 1.000
#> SRR1400507 2 0.0000 0.980 0.000 1.000
#> SRR1378179 2 0.0000 0.980 0.000 1.000
#> SRR1377905 2 0.0000 0.980 0.000 1.000
#> SRR1089479 1 0.0000 0.976 1.000 0.000
#> SRR1073365 2 0.0000 0.980 0.000 1.000
#> SRR1500306 1 0.0000 0.976 1.000 0.000
#> SRR1101566 2 0.0000 0.980 0.000 1.000
#> SRR1350503 2 0.0000 0.980 0.000 1.000
#> SRR1446007 2 0.0000 0.980 0.000 1.000
#> SRR1102875 2 0.0000 0.980 0.000 1.000
#> SRR1380293 2 0.0000 0.980 0.000 1.000
#> SRR1331198 2 0.0000 0.980 0.000 1.000
#> SRR1092686 2 0.0000 0.980 0.000 1.000
#> SRR1069421 2 0.0000 0.980 0.000 1.000
#> SRR1341650 2 0.7674 0.710 0.224 0.776
#> SRR1357276 2 0.0000 0.980 0.000 1.000
#> SRR1498374 2 0.0000 0.980 0.000 1.000
#> SRR1093721 2 0.0000 0.980 0.000 1.000
#> SRR1464660 1 0.0000 0.976 1.000 0.000
#> SRR1402051 2 0.1414 0.962 0.020 0.980
#> SRR1488734 2 0.0000 0.980 0.000 1.000
#> SRR1082616 2 0.6438 0.797 0.164 0.836
#> SRR1099427 2 0.0000 0.980 0.000 1.000
#> SRR1453093 2 0.0000 0.980 0.000 1.000
#> SRR1357064 1 0.0000 0.976 1.000 0.000
#> SRR811237 2 0.0000 0.980 0.000 1.000
#> SRR1100848 2 0.0000 0.980 0.000 1.000
#> SRR1346755 2 0.0000 0.980 0.000 1.000
#> SRR1472529 2 0.0000 0.980 0.000 1.000
#> SRR1398905 1 0.0000 0.976 1.000 0.000
#> SRR1082733 2 0.0000 0.980 0.000 1.000
#> SRR1308035 2 0.0000 0.980 0.000 1.000
#> SRR1466445 2 0.0000 0.980 0.000 1.000
#> SRR1359080 2 0.0000 0.980 0.000 1.000
#> SRR1455825 2 0.0000 0.980 0.000 1.000
#> SRR1389300 2 0.0000 0.980 0.000 1.000
#> SRR812246 2 0.0000 0.980 0.000 1.000
#> SRR1076632 2 0.0000 0.980 0.000 1.000
#> SRR1415567 1 0.0000 0.976 1.000 0.000
#> SRR1331900 2 0.0000 0.980 0.000 1.000
#> SRR1452099 2 0.9710 0.338 0.400 0.600
#> SRR1352346 2 0.8861 0.554 0.304 0.696
#> SRR1364034 2 0.0000 0.980 0.000 1.000
#> SRR1086046 2 0.2236 0.947 0.036 0.964
#> SRR1407226 1 0.0000 0.976 1.000 0.000
#> SRR1319363 1 0.0000 0.976 1.000 0.000
#> SRR1446961 2 0.0000 0.980 0.000 1.000
#> SRR1486650 1 0.0000 0.976 1.000 0.000
#> SRR1470152 1 0.0000 0.976 1.000 0.000
#> SRR1454785 2 0.0000 0.980 0.000 1.000
#> SRR1092329 2 0.0000 0.980 0.000 1.000
#> SRR1091476 2 0.0000 0.980 0.000 1.000
#> SRR1073775 2 0.0000 0.980 0.000 1.000
#> SRR1366873 2 0.0000 0.980 0.000 1.000
#> SRR1398114 2 0.0000 0.980 0.000 1.000
#> SRR1089950 1 0.0938 0.967 0.988 0.012
#> SRR1433272 2 0.0000 0.980 0.000 1.000
#> SRR1075314 1 0.0000 0.976 1.000 0.000
#> SRR1085590 2 0.0000 0.980 0.000 1.000
#> SRR1100752 2 0.0000 0.980 0.000 1.000
#> SRR1391494 2 0.0000 0.980 0.000 1.000
#> SRR1333263 2 0.0000 0.980 0.000 1.000
#> SRR1310231 2 0.0000 0.980 0.000 1.000
#> SRR1094144 2 0.0000 0.980 0.000 1.000
#> SRR1092160 2 0.0000 0.980 0.000 1.000
#> SRR1320300 2 0.0000 0.980 0.000 1.000
#> SRR1322747 2 0.0000 0.980 0.000 1.000
#> SRR1432719 2 0.0000 0.980 0.000 1.000
#> SRR1100728 2 0.0376 0.977 0.004 0.996
#> SRR1087511 2 0.0000 0.980 0.000 1.000
#> SRR1470336 1 0.0000 0.976 1.000 0.000
#> SRR1322536 1 0.0000 0.976 1.000 0.000
#> SRR1100824 1 0.0000 0.976 1.000 0.000
#> SRR1085951 1 0.1414 0.960 0.980 0.020
#> SRR1322046 2 0.0000 0.980 0.000 1.000
#> SRR1316420 1 0.0000 0.976 1.000 0.000
#> SRR1070913 2 0.0000 0.980 0.000 1.000
#> SRR1345806 2 0.0000 0.980 0.000 1.000
#> SRR1313872 2 0.0000 0.980 0.000 1.000
#> SRR1337666 2 0.0000 0.980 0.000 1.000
#> SRR1076823 1 0.0000 0.976 1.000 0.000
#> SRR1093954 2 0.0000 0.980 0.000 1.000
#> SRR1451921 1 0.8327 0.644 0.736 0.264
#> SRR1491257 1 0.0000 0.976 1.000 0.000
#> SRR1416979 2 0.0000 0.980 0.000 1.000
#> SRR1419015 1 0.8713 0.590 0.708 0.292
#> SRR817649 2 0.0000 0.980 0.000 1.000
#> SRR1466376 2 0.0000 0.980 0.000 1.000
#> SRR1392055 2 0.0000 0.980 0.000 1.000
#> SRR1120913 2 0.0000 0.980 0.000 1.000
#> SRR1120869 2 0.0000 0.980 0.000 1.000
#> SRR1319419 2 0.0000 0.980 0.000 1.000
#> SRR816495 2 0.0000 0.980 0.000 1.000
#> SRR818694 2 0.0000 0.980 0.000 1.000
#> SRR1465653 1 0.7453 0.735 0.788 0.212
#> SRR1475952 1 0.0000 0.976 1.000 0.000
#> SRR1465040 2 0.0000 0.980 0.000 1.000
#> SRR1088461 2 0.0000 0.980 0.000 1.000
#> SRR810129 2 0.0000 0.980 0.000 1.000
#> SRR1400141 2 0.0000 0.980 0.000 1.000
#> SRR1349585 1 0.0000 0.976 1.000 0.000
#> SRR1437576 2 0.0000 0.980 0.000 1.000
#> SRR814407 1 0.0000 0.976 1.000 0.000
#> SRR1332403 2 0.0000 0.980 0.000 1.000
#> SRR1099598 2 0.0000 0.980 0.000 1.000
#> SRR1327723 2 0.0000 0.980 0.000 1.000
#> SRR1392525 2 0.0000 0.980 0.000 1.000
#> SRR1320536 1 0.0000 0.976 1.000 0.000
#> SRR1083824 2 0.0000 0.980 0.000 1.000
#> SRR1351390 1 0.0000 0.976 1.000 0.000
#> SRR1309141 2 0.0000 0.980 0.000 1.000
#> SRR1452803 2 0.0000 0.980 0.000 1.000
#> SRR811631 2 0.0000 0.980 0.000 1.000
#> SRR1485563 2 0.0000 0.980 0.000 1.000
#> SRR1311531 2 0.0000 0.980 0.000 1.000
#> SRR1353076 2 0.0000 0.980 0.000 1.000
#> SRR1480831 2 0.0000 0.980 0.000 1.000
#> SRR1083892 1 0.0000 0.976 1.000 0.000
#> SRR809873 1 0.0000 0.976 1.000 0.000
#> SRR1341854 2 0.0000 0.980 0.000 1.000
#> SRR1399335 2 0.0000 0.980 0.000 1.000
#> SRR1464209 1 0.0000 0.976 1.000 0.000
#> SRR1389886 2 0.0000 0.980 0.000 1.000
#> SRR1400730 1 0.0000 0.976 1.000 0.000
#> SRR1448008 2 0.0000 0.980 0.000 1.000
#> SRR1087606 1 0.0000 0.976 1.000 0.000
#> SRR1445111 1 0.0000 0.976 1.000 0.000
#> SRR816865 2 0.0000 0.980 0.000 1.000
#> SRR1323360 2 0.0000 0.980 0.000 1.000
#> SRR1417364 2 0.0000 0.980 0.000 1.000
#> SRR1480329 2 0.0000 0.980 0.000 1.000
#> SRR1403322 1 0.0000 0.976 1.000 0.000
#> SRR1093625 1 0.0000 0.976 1.000 0.000
#> SRR1479977 2 0.0000 0.980 0.000 1.000
#> SRR1082035 2 0.9933 0.163 0.452 0.548
#> SRR1393046 2 0.0000 0.980 0.000 1.000
#> SRR1466663 2 0.0376 0.977 0.004 0.996
#> SRR1384456 1 0.0000 0.976 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.1753 0.7509 0.000 0.952 0.048
#> SRR808862 1 0.6773 0.5238 0.636 0.024 0.340
#> SRR1500382 2 0.2537 0.7458 0.000 0.920 0.080
#> SRR1322683 2 0.5948 0.6057 0.000 0.640 0.360
#> SRR1329811 3 0.8343 0.6022 0.256 0.132 0.612
#> SRR1087297 2 0.4235 0.6798 0.000 0.824 0.176
#> SRR1072626 2 0.5733 0.6382 0.000 0.676 0.324
#> SRR1407428 1 0.0424 0.7064 0.992 0.000 0.008
#> SRR1321029 2 0.3619 0.7229 0.000 0.864 0.136
#> SRR1500282 1 0.4002 0.5765 0.840 0.000 0.160
#> SRR1100496 1 0.9649 0.0104 0.404 0.388 0.208
#> SRR1308778 2 0.4235 0.6813 0.000 0.824 0.176
#> SRR1445304 2 0.2878 0.7358 0.000 0.904 0.096
#> SRR1099378 3 0.7561 0.4932 0.444 0.040 0.516
#> SRR1347412 1 0.3412 0.6191 0.876 0.000 0.124
#> SRR1099694 2 0.4974 0.6201 0.000 0.764 0.236
#> SRR1088365 2 0.1860 0.7611 0.000 0.948 0.052
#> SRR1325752 2 0.8404 0.3327 0.288 0.592 0.120
#> SRR1416713 2 0.4002 0.6951 0.000 0.840 0.160
#> SRR1074474 1 0.0592 0.7014 0.988 0.000 0.012
#> SRR1469369 2 0.6434 0.5778 0.008 0.612 0.380
#> SRR1400507 2 0.4796 0.7081 0.000 0.780 0.220
#> SRR1378179 2 0.3192 0.7283 0.000 0.888 0.112
#> SRR1377905 2 0.3482 0.7191 0.000 0.872 0.128
#> SRR1089479 1 0.0237 0.7039 0.996 0.000 0.004
#> SRR1073365 2 0.1411 0.7527 0.000 0.964 0.036
#> SRR1500306 1 0.5397 0.5960 0.720 0.000 0.280
#> SRR1101566 2 0.5968 0.6018 0.000 0.636 0.364
#> SRR1350503 2 0.4605 0.7181 0.000 0.796 0.204
#> SRR1446007 2 0.5560 0.6542 0.000 0.700 0.300
#> SRR1102875 2 0.0747 0.7589 0.000 0.984 0.016
#> SRR1380293 3 0.6299 0.1030 0.000 0.476 0.524
#> SRR1331198 2 0.6140 0.2814 0.000 0.596 0.404
#> SRR1092686 2 0.4504 0.6962 0.000 0.804 0.196
#> SRR1069421 2 0.4409 0.6848 0.004 0.824 0.172
#> SRR1341650 2 0.8117 0.4299 0.236 0.636 0.128
#> SRR1357276 2 0.5591 0.4800 0.000 0.696 0.304
#> SRR1498374 2 0.3192 0.7578 0.000 0.888 0.112
#> SRR1093721 2 0.3267 0.7482 0.000 0.884 0.116
#> SRR1464660 3 0.7924 0.6046 0.304 0.084 0.612
#> SRR1402051 2 0.8010 0.5034 0.068 0.548 0.384
#> SRR1488734 2 0.2066 0.7482 0.000 0.940 0.060
#> SRR1082616 2 0.9948 0.0687 0.284 0.364 0.352
#> SRR1099427 2 0.5988 0.5980 0.000 0.632 0.368
#> SRR1453093 2 0.6881 0.5548 0.020 0.592 0.388
#> SRR1357064 3 0.6721 0.5750 0.380 0.016 0.604
#> SRR811237 2 0.4842 0.7053 0.000 0.776 0.224
#> SRR1100848 2 0.1529 0.7610 0.000 0.960 0.040
#> SRR1346755 2 0.5835 0.6246 0.000 0.660 0.340
#> SRR1472529 2 0.2356 0.7558 0.000 0.928 0.072
#> SRR1398905 1 0.1753 0.7086 0.952 0.000 0.048
#> SRR1082733 2 0.0424 0.7585 0.000 0.992 0.008
#> SRR1308035 2 0.5948 0.6315 0.000 0.640 0.360
#> SRR1466445 2 0.5497 0.6748 0.000 0.708 0.292
#> SRR1359080 2 0.2959 0.7341 0.000 0.900 0.100
#> SRR1455825 2 0.2165 0.7566 0.000 0.936 0.064
#> SRR1389300 2 0.1643 0.7583 0.000 0.956 0.044
#> SRR812246 2 0.6298 0.6045 0.004 0.608 0.388
#> SRR1076632 2 0.2537 0.7442 0.000 0.920 0.080
#> SRR1415567 1 0.0237 0.7038 0.996 0.000 0.004
#> SRR1331900 2 0.2625 0.7540 0.000 0.916 0.084
#> SRR1452099 1 0.8311 0.2372 0.596 0.292 0.112
#> SRR1352346 3 0.7190 0.4392 0.036 0.356 0.608
#> SRR1364034 2 0.2625 0.7433 0.000 0.916 0.084
#> SRR1086046 2 0.9599 0.2404 0.200 0.412 0.388
#> SRR1407226 1 0.2711 0.6527 0.912 0.000 0.088
#> SRR1319363 1 0.1031 0.7060 0.976 0.000 0.024
#> SRR1446961 2 0.5591 0.5299 0.000 0.696 0.304
#> SRR1486650 1 0.2261 0.6723 0.932 0.000 0.068
#> SRR1470152 3 0.6540 0.5444 0.408 0.008 0.584
#> SRR1454785 2 0.3412 0.7564 0.000 0.876 0.124
#> SRR1092329 2 0.3941 0.7368 0.000 0.844 0.156
#> SRR1091476 3 0.5690 0.2072 0.004 0.288 0.708
#> SRR1073775 2 0.5926 0.6096 0.000 0.644 0.356
#> SRR1366873 2 0.4121 0.7313 0.000 0.832 0.168
#> SRR1398114 2 0.2066 0.7479 0.000 0.940 0.060
#> SRR1089950 1 0.3412 0.6924 0.876 0.000 0.124
#> SRR1433272 2 0.6678 -0.0126 0.008 0.512 0.480
#> SRR1075314 1 0.7311 0.4800 0.580 0.036 0.384
#> SRR1085590 2 0.4291 0.7341 0.000 0.820 0.180
#> SRR1100752 2 0.6244 0.2230 0.000 0.560 0.440
#> SRR1391494 2 0.1529 0.7594 0.000 0.960 0.040
#> SRR1333263 2 0.4645 0.6809 0.008 0.816 0.176
#> SRR1310231 2 0.2537 0.7421 0.000 0.920 0.080
#> SRR1094144 2 0.3918 0.7463 0.004 0.856 0.140
#> SRR1092160 2 0.6045 0.3506 0.000 0.620 0.380
#> SRR1320300 2 0.4121 0.7320 0.000 0.832 0.168
#> SRR1322747 2 0.2165 0.7476 0.000 0.936 0.064
#> SRR1432719 2 0.6291 0.0223 0.000 0.532 0.468
#> SRR1100728 2 0.4615 0.7052 0.020 0.836 0.144
#> SRR1087511 2 0.6753 0.5596 0.016 0.596 0.388
#> SRR1470336 1 0.5016 0.6224 0.760 0.000 0.240
#> SRR1322536 1 0.7114 0.4824 0.584 0.028 0.388
#> SRR1100824 1 0.5926 0.1372 0.644 0.000 0.356
#> SRR1085951 1 0.5360 0.5944 0.768 0.012 0.220
#> SRR1322046 2 0.1643 0.7566 0.000 0.956 0.044
#> SRR1316420 1 0.5254 0.3867 0.736 0.000 0.264
#> SRR1070913 2 0.3551 0.7432 0.000 0.868 0.132
#> SRR1345806 2 0.4974 0.7074 0.000 0.764 0.236
#> SRR1313872 2 0.4654 0.6517 0.000 0.792 0.208
#> SRR1337666 2 0.6302 -0.0313 0.000 0.520 0.480
#> SRR1076823 1 0.4002 0.6729 0.840 0.000 0.160
#> SRR1093954 2 0.0592 0.7579 0.000 0.988 0.012
#> SRR1451921 1 0.8869 0.3800 0.496 0.124 0.380
#> SRR1491257 3 0.6180 0.5339 0.416 0.000 0.584
#> SRR1416979 2 0.2796 0.7546 0.000 0.908 0.092
#> SRR1419015 1 0.5094 0.6473 0.832 0.056 0.112
#> SRR817649 3 0.6180 0.2939 0.000 0.416 0.584
#> SRR1466376 2 0.2537 0.7421 0.000 0.920 0.080
#> SRR1392055 2 0.1860 0.7504 0.000 0.948 0.052
#> SRR1120913 2 0.2356 0.7448 0.000 0.928 0.072
#> SRR1120869 2 0.3116 0.7281 0.000 0.892 0.108
#> SRR1319419 2 0.4452 0.7406 0.000 0.808 0.192
#> SRR816495 2 0.5397 0.6175 0.000 0.720 0.280
#> SRR818694 2 0.6298 0.5733 0.004 0.608 0.388
#> SRR1465653 3 0.8525 0.5835 0.200 0.188 0.612
#> SRR1475952 1 0.3941 0.6753 0.844 0.000 0.156
#> SRR1465040 2 0.5785 0.6303 0.000 0.668 0.332
#> SRR1088461 2 0.1860 0.7579 0.000 0.948 0.052
#> SRR810129 2 0.2796 0.7355 0.000 0.908 0.092
#> SRR1400141 2 0.4062 0.7259 0.000 0.836 0.164
#> SRR1349585 1 0.5882 0.1667 0.652 0.000 0.348
#> SRR1437576 2 0.0892 0.7588 0.000 0.980 0.020
#> SRR814407 1 0.0592 0.7072 0.988 0.000 0.012
#> SRR1332403 2 0.2261 0.7462 0.000 0.932 0.068
#> SRR1099598 2 0.6062 0.5820 0.000 0.616 0.384
#> SRR1327723 2 0.0592 0.7568 0.000 0.988 0.012
#> SRR1392525 2 0.5785 0.6492 0.004 0.696 0.300
#> SRR1320536 1 0.1529 0.6896 0.960 0.000 0.040
#> SRR1083824 2 0.4931 0.6031 0.000 0.768 0.232
#> SRR1351390 1 0.3879 0.6857 0.848 0.000 0.152
#> SRR1309141 2 0.3551 0.7192 0.000 0.868 0.132
#> SRR1452803 2 0.5497 0.5343 0.000 0.708 0.292
#> SRR811631 2 0.4235 0.7278 0.000 0.824 0.176
#> SRR1485563 2 0.5905 0.6147 0.000 0.648 0.352
#> SRR1311531 2 0.5591 0.6667 0.000 0.696 0.304
#> SRR1353076 2 0.5178 0.6876 0.000 0.744 0.256
#> SRR1480831 2 0.5529 0.6601 0.000 0.704 0.296
#> SRR1083892 3 0.7013 0.5849 0.364 0.028 0.608
#> SRR809873 1 0.2796 0.6966 0.908 0.000 0.092
#> SRR1341854 2 0.2537 0.7476 0.000 0.920 0.080
#> SRR1399335 2 0.5397 0.5506 0.000 0.720 0.280
#> SRR1464209 3 0.6215 0.5133 0.428 0.000 0.572
#> SRR1389886 2 0.1753 0.7508 0.000 0.952 0.048
#> SRR1400730 3 0.6309 0.3418 0.500 0.000 0.500
#> SRR1448008 2 0.5254 0.6803 0.000 0.736 0.264
#> SRR1087606 3 0.6267 0.4588 0.452 0.000 0.548
#> SRR1445111 1 0.0892 0.6994 0.980 0.000 0.020
#> SRR816865 2 0.4531 0.6834 0.008 0.824 0.168
#> SRR1323360 2 0.4931 0.7259 0.000 0.768 0.232
#> SRR1417364 2 0.6111 0.2218 0.000 0.604 0.396
#> SRR1480329 2 0.5465 0.6774 0.000 0.712 0.288
#> SRR1403322 1 0.4750 0.6439 0.784 0.000 0.216
#> SRR1093625 1 0.0424 0.7028 0.992 0.000 0.008
#> SRR1479977 2 0.1643 0.7581 0.000 0.956 0.044
#> SRR1082035 1 0.9299 -0.3468 0.432 0.160 0.408
#> SRR1393046 2 0.1289 0.7551 0.000 0.968 0.032
#> SRR1466663 2 0.4749 0.6796 0.012 0.816 0.172
#> SRR1384456 1 0.1411 0.6917 0.964 0.000 0.036
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.1174 0.6688 0.012 0.968 0.020 0.000
#> SRR808862 4 0.5673 0.3018 0.032 0.000 0.372 0.596
#> SRR1500382 2 0.2443 0.6636 0.024 0.924 0.044 0.008
#> SRR1322683 2 0.7179 0.2875 0.000 0.544 0.180 0.276
#> SRR1329811 1 0.5073 0.5054 0.744 0.056 0.200 0.000
#> SRR1087297 2 0.3156 0.6585 0.068 0.884 0.048 0.000
#> SRR1072626 2 0.5608 0.5372 0.000 0.684 0.060 0.256
#> SRR1407428 4 0.4585 0.4773 0.332 0.000 0.000 0.668
#> SRR1321029 2 0.4242 0.6281 0.020 0.836 0.108 0.036
#> SRR1500282 1 0.6265 0.0285 0.588 0.000 0.072 0.340
#> SRR1100496 4 0.9731 0.0480 0.140 0.276 0.280 0.304
#> SRR1308778 2 0.5769 0.4718 0.292 0.652 0.056 0.000
#> SRR1445304 2 0.3308 0.6493 0.092 0.872 0.036 0.000
#> SRR1099378 1 0.4155 0.5391 0.836 0.116 0.032 0.016
#> SRR1347412 1 0.7210 -0.0676 0.492 0.000 0.148 0.360
#> SRR1099694 2 0.5056 0.5661 0.224 0.732 0.044 0.000
#> SRR1088365 2 0.4443 0.6259 0.024 0.812 0.144 0.020
#> SRR1325752 1 0.8351 0.2391 0.508 0.296 0.112 0.084
#> SRR1416713 2 0.3598 0.6447 0.124 0.848 0.028 0.000
#> SRR1074474 4 0.4907 0.3875 0.420 0.000 0.000 0.580
#> SRR1469369 2 0.7669 0.0684 0.000 0.444 0.228 0.328
#> SRR1400507 2 0.5867 0.5022 0.000 0.688 0.096 0.216
#> SRR1378179 2 0.5102 0.5948 0.136 0.764 0.100 0.000
#> SRR1377905 2 0.3325 0.6478 0.112 0.864 0.024 0.000
#> SRR1089479 4 0.4776 0.4420 0.376 0.000 0.000 0.624
#> SRR1073365 2 0.1913 0.6674 0.020 0.940 0.040 0.000
#> SRR1500306 4 0.4205 0.4907 0.056 0.000 0.124 0.820
#> SRR1101566 2 0.7464 0.1874 0.000 0.496 0.208 0.296
#> SRR1350503 2 0.5535 0.3738 0.000 0.656 0.304 0.040
#> SRR1446007 3 0.7047 0.1664 0.000 0.436 0.444 0.120
#> SRR1102875 2 0.2561 0.6633 0.016 0.912 0.068 0.004
#> SRR1380293 2 0.5506 0.1442 0.472 0.512 0.016 0.000
#> SRR1331198 2 0.5092 0.6030 0.140 0.764 0.096 0.000
#> SRR1092686 2 0.5756 0.4056 0.032 0.616 0.348 0.004
#> SRR1069421 2 0.7522 0.3772 0.284 0.552 0.144 0.020
#> SRR1341650 2 0.8441 0.3537 0.244 0.520 0.164 0.072
#> SRR1357276 2 0.4791 0.5880 0.136 0.784 0.080 0.000
#> SRR1498374 2 0.4344 0.6085 0.000 0.816 0.108 0.076
#> SRR1093721 2 0.4388 0.6078 0.000 0.808 0.060 0.132
#> SRR1464660 1 0.4746 0.3482 0.632 0.000 0.368 0.000
#> SRR1402051 4 0.6960 -0.2363 0.000 0.420 0.112 0.468
#> SRR1488734 2 0.1913 0.6678 0.040 0.940 0.020 0.000
#> SRR1082616 4 0.7063 0.3997 0.060 0.120 0.152 0.668
#> SRR1099427 2 0.7216 0.2745 0.000 0.536 0.180 0.284
#> SRR1453093 2 0.7202 0.1370 0.000 0.464 0.140 0.396
#> SRR1357064 1 0.1510 0.5931 0.956 0.016 0.028 0.000
#> SRR811237 2 0.5794 0.6107 0.008 0.728 0.120 0.144
#> SRR1100848 2 0.2224 0.6681 0.000 0.928 0.040 0.032
#> SRR1346755 2 0.5940 0.4887 0.000 0.672 0.088 0.240
#> SRR1472529 2 0.3972 0.6243 0.000 0.840 0.080 0.080
#> SRR1398905 3 0.6107 0.2018 0.088 0.000 0.648 0.264
#> SRR1082733 2 0.1545 0.6716 0.000 0.952 0.040 0.008
#> SRR1308035 3 0.3279 0.6521 0.008 0.088 0.880 0.024
#> SRR1466445 3 0.4932 0.6391 0.000 0.240 0.728 0.032
#> SRR1359080 2 0.2300 0.6627 0.028 0.924 0.048 0.000
#> SRR1455825 2 0.4898 0.5855 0.000 0.780 0.116 0.104
#> SRR1389300 2 0.3439 0.6343 0.000 0.868 0.084 0.048
#> SRR812246 3 0.4274 0.6620 0.012 0.120 0.828 0.040
#> SRR1076632 2 0.6097 0.5679 0.128 0.720 0.132 0.020
#> SRR1415567 4 0.4761 0.4440 0.372 0.000 0.000 0.628
#> SRR1331900 2 0.4953 0.5823 0.000 0.776 0.104 0.120
#> SRR1452099 4 0.9673 0.1775 0.244 0.240 0.152 0.364
#> SRR1352346 1 0.5687 0.3919 0.684 0.248 0.068 0.000
#> SRR1364034 2 0.5000 0.5994 0.100 0.772 0.128 0.000
#> SRR1086046 4 0.6096 0.1605 0.000 0.184 0.136 0.680
#> SRR1407226 1 0.6472 0.2928 0.664 0.020 0.084 0.232
#> SRR1319363 4 0.7579 0.3914 0.312 0.028 0.120 0.540
#> SRR1446961 3 0.5935 0.2876 0.036 0.468 0.496 0.000
#> SRR1486650 1 0.4916 -0.1339 0.576 0.000 0.000 0.424
#> SRR1470152 1 0.4978 0.3369 0.612 0.000 0.384 0.004
#> SRR1454785 3 0.5548 0.2656 0.012 0.448 0.536 0.004
#> SRR1092329 2 0.4686 0.5950 0.000 0.788 0.068 0.144
#> SRR1091476 3 0.3734 0.5812 0.096 0.044 0.856 0.004
#> SRR1073775 2 0.7248 0.2617 0.000 0.532 0.184 0.284
#> SRR1366873 2 0.6397 0.4520 0.000 0.652 0.164 0.184
#> SRR1398114 2 0.4022 0.6357 0.068 0.836 0.096 0.000
#> SRR1089950 1 0.5421 -0.1102 0.548 0.004 0.008 0.440
#> SRR1433272 2 0.6791 0.2180 0.392 0.508 0.100 0.000
#> SRR1075314 4 0.2234 0.5020 0.008 0.004 0.064 0.924
#> SRR1085590 2 0.5308 0.5079 0.000 0.684 0.280 0.036
#> SRR1100752 3 0.3383 0.6226 0.052 0.076 0.872 0.000
#> SRR1391494 2 0.1356 0.6700 0.000 0.960 0.032 0.008
#> SRR1333263 2 0.6669 0.5050 0.184 0.648 0.160 0.008
#> SRR1310231 2 0.2408 0.6637 0.036 0.920 0.044 0.000
#> SRR1094144 2 0.6730 0.5578 0.092 0.692 0.156 0.060
#> SRR1092160 2 0.5699 0.3827 0.380 0.588 0.032 0.000
#> SRR1320300 2 0.5077 0.5735 0.000 0.760 0.080 0.160
#> SRR1322747 2 0.2222 0.6611 0.016 0.924 0.060 0.000
#> SRR1432719 3 0.5857 0.5694 0.108 0.196 0.696 0.000
#> SRR1100728 2 0.7255 0.4784 0.196 0.620 0.156 0.028
#> SRR1087511 2 0.7577 0.0500 0.000 0.428 0.196 0.376
#> SRR1470336 4 0.4332 0.5010 0.072 0.000 0.112 0.816
#> SRR1322536 4 0.2918 0.4735 0.000 0.008 0.116 0.876
#> SRR1100824 1 0.3134 0.5269 0.880 0.008 0.012 0.100
#> SRR1085951 3 0.5256 0.3407 0.064 0.000 0.732 0.204
#> SRR1322046 2 0.1917 0.6704 0.012 0.944 0.036 0.008
#> SRR1316420 1 0.3172 0.4623 0.840 0.000 0.000 0.160
#> SRR1070913 2 0.5250 0.5608 0.000 0.744 0.080 0.176
#> SRR1345806 3 0.6004 0.3851 0.008 0.380 0.580 0.032
#> SRR1313872 2 0.5839 0.4755 0.292 0.648 0.060 0.000
#> SRR1337666 2 0.7216 0.2060 0.284 0.536 0.180 0.000
#> SRR1076823 4 0.3831 0.5329 0.204 0.000 0.004 0.792
#> SRR1093954 2 0.2730 0.6567 0.016 0.896 0.088 0.000
#> SRR1451921 4 0.3509 0.4967 0.012 0.028 0.088 0.872
#> SRR1491257 1 0.1256 0.5876 0.964 0.000 0.028 0.008
#> SRR1416979 2 0.3398 0.6670 0.000 0.872 0.068 0.060
#> SRR1419015 4 0.7609 0.4363 0.244 0.032 0.148 0.576
#> SRR817649 1 0.6179 0.1262 0.552 0.392 0.056 0.000
#> SRR1466376 2 0.2546 0.6624 0.028 0.912 0.060 0.000
#> SRR1392055 2 0.2438 0.6618 0.016 0.924 0.048 0.012
#> SRR1120913 2 0.2002 0.6678 0.044 0.936 0.020 0.000
#> SRR1120869 2 0.5531 0.5735 0.128 0.732 0.140 0.000
#> SRR1319419 3 0.3444 0.6797 0.000 0.184 0.816 0.000
#> SRR816495 3 0.4963 0.6375 0.020 0.284 0.696 0.000
#> SRR818694 2 0.7520 0.1332 0.000 0.464 0.196 0.340
#> SRR1465653 1 0.5727 0.4563 0.688 0.076 0.236 0.000
#> SRR1475952 4 0.4214 0.5315 0.204 0.000 0.016 0.780
#> SRR1465040 2 0.7469 0.0102 0.000 0.472 0.340 0.188
#> SRR1088461 2 0.2775 0.6575 0.020 0.896 0.084 0.000
#> SRR810129 2 0.4982 0.6015 0.136 0.772 0.092 0.000
#> SRR1400141 2 0.5709 0.3522 0.024 0.588 0.384 0.004
#> SRR1349585 1 0.2868 0.5014 0.864 0.000 0.000 0.136
#> SRR1437576 2 0.2699 0.6480 0.000 0.904 0.068 0.028
#> SRR814407 4 0.4454 0.4932 0.308 0.000 0.000 0.692
#> SRR1332403 2 0.2761 0.6604 0.048 0.904 0.048 0.000
#> SRR1099598 2 0.6249 0.3821 0.000 0.592 0.072 0.336
#> SRR1327723 2 0.2376 0.6513 0.000 0.916 0.068 0.016
#> SRR1392525 2 0.7196 0.4061 0.000 0.552 0.212 0.236
#> SRR1320536 4 0.4998 0.2705 0.488 0.000 0.000 0.512
#> SRR1083824 2 0.3840 0.6418 0.052 0.844 0.104 0.000
#> SRR1351390 4 0.5646 0.4124 0.296 0.000 0.048 0.656
#> SRR1309141 2 0.5528 0.5765 0.144 0.732 0.124 0.000
#> SRR1452803 2 0.5678 0.4523 0.316 0.640 0.044 0.000
#> SRR811631 2 0.6240 0.4692 0.000 0.668 0.156 0.176
#> SRR1485563 2 0.6182 0.5134 0.000 0.636 0.088 0.276
#> SRR1311531 3 0.4423 0.6671 0.000 0.176 0.788 0.036
#> SRR1353076 2 0.4789 0.6000 0.000 0.772 0.056 0.172
#> SRR1480831 2 0.5184 0.5799 0.000 0.732 0.056 0.212
#> SRR1083892 1 0.1474 0.5833 0.948 0.052 0.000 0.000
#> SRR809873 4 0.7389 0.4358 0.252 0.020 0.148 0.580
#> SRR1341854 2 0.3833 0.6418 0.072 0.848 0.080 0.000
#> SRR1399335 2 0.6141 0.4351 0.312 0.616 0.072 0.000
#> SRR1464209 1 0.0992 0.5845 0.976 0.004 0.008 0.012
#> SRR1389886 2 0.1936 0.6675 0.028 0.940 0.032 0.000
#> SRR1400730 3 0.4872 0.1340 0.356 0.000 0.640 0.004
#> SRR1448008 2 0.6245 0.4553 0.000 0.648 0.108 0.244
#> SRR1087606 1 0.2845 0.5802 0.896 0.000 0.076 0.028
#> SRR1445111 4 0.6419 0.3390 0.420 0.000 0.068 0.512
#> SRR816865 2 0.7041 0.4796 0.208 0.628 0.144 0.020
#> SRR1323360 3 0.3878 0.6697 0.016 0.156 0.824 0.004
#> SRR1417364 3 0.6133 0.5781 0.088 0.268 0.644 0.000
#> SRR1480329 2 0.7094 0.3491 0.004 0.580 0.168 0.248
#> SRR1403322 4 0.4050 0.5396 0.144 0.000 0.036 0.820
#> SRR1093625 4 0.4877 0.4058 0.408 0.000 0.000 0.592
#> SRR1479977 2 0.3301 0.6377 0.000 0.876 0.076 0.048
#> SRR1082035 1 0.6507 0.4220 0.696 0.116 0.032 0.156
#> SRR1393046 2 0.1661 0.6594 0.000 0.944 0.052 0.004
#> SRR1466663 2 0.6711 0.3907 0.308 0.576 0.116 0.000
#> SRR1384456 4 0.4985 0.3105 0.468 0.000 0.000 0.532
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1942 0.7034 0.000 0.920 0.000 0.068 0.012
#> SRR808862 3 0.3283 0.7548 0.140 0.000 0.832 0.028 0.000
#> SRR1500382 2 0.1485 0.7233 0.000 0.948 0.000 0.020 0.032
#> SRR1322683 2 0.3796 0.6234 0.300 0.700 0.000 0.000 0.000
#> SRR1329811 5 0.1799 0.6905 0.000 0.028 0.020 0.012 0.940
#> SRR1087297 2 0.2795 0.6942 0.000 0.872 0.000 0.028 0.100
#> SRR1072626 2 0.4805 0.6423 0.144 0.728 0.000 0.128 0.000
#> SRR1407428 1 0.5744 0.6747 0.648 0.000 0.008 0.184 0.160
#> SRR1321029 2 0.1251 0.7307 0.008 0.956 0.000 0.000 0.036
#> SRR1500282 5 0.6666 -0.4309 0.412 0.000 0.020 0.132 0.436
#> SRR1100496 4 0.4012 0.5824 0.044 0.032 0.104 0.820 0.000
#> SRR1308778 2 0.6134 0.1546 0.000 0.516 0.000 0.144 0.340
#> SRR1445304 2 0.4627 0.5133 0.000 0.732 0.000 0.188 0.080
#> SRR1099378 5 0.5323 0.4100 0.004 0.076 0.000 0.276 0.644
#> SRR1347412 1 0.6064 0.4661 0.508 0.000 0.044 0.040 0.408
#> SRR1099694 2 0.6326 0.0932 0.000 0.512 0.000 0.188 0.300
#> SRR1088365 4 0.3585 0.7633 0.004 0.220 0.000 0.772 0.004
#> SRR1325752 4 0.4922 0.6477 0.028 0.112 0.000 0.756 0.104
#> SRR1416713 2 0.3532 0.6603 0.000 0.832 0.000 0.076 0.092
#> SRR1074474 1 0.6426 0.6169 0.540 0.000 0.008 0.180 0.272
#> SRR1469369 2 0.3983 0.5844 0.340 0.660 0.000 0.000 0.000
#> SRR1400507 2 0.3109 0.6893 0.200 0.800 0.000 0.000 0.000
#> SRR1378179 4 0.5104 0.7061 0.000 0.284 0.000 0.648 0.068
#> SRR1377905 2 0.4922 0.5218 0.000 0.716 0.000 0.128 0.156
#> SRR1089479 1 0.6025 0.6636 0.612 0.000 0.008 0.180 0.200
#> SRR1073365 2 0.3183 0.6261 0.000 0.828 0.000 0.156 0.016
#> SRR1500306 1 0.1907 0.6099 0.928 0.028 0.000 0.000 0.044
#> SRR1101566 2 0.3876 0.6092 0.316 0.684 0.000 0.000 0.000
#> SRR1350503 2 0.1808 0.7304 0.020 0.936 0.040 0.000 0.004
#> SRR1446007 2 0.4734 0.4966 0.036 0.652 0.312 0.000 0.000
#> SRR1102875 2 0.4264 0.1425 0.000 0.620 0.000 0.376 0.004
#> SRR1380293 5 0.4937 0.4492 0.000 0.264 0.000 0.064 0.672
#> SRR1331198 2 0.3355 0.6679 0.000 0.804 0.000 0.012 0.184
#> SRR1092686 3 0.4967 0.4880 0.000 0.060 0.660 0.280 0.000
#> SRR1069421 4 0.3630 0.7634 0.000 0.204 0.000 0.780 0.016
#> SRR1341650 4 0.2141 0.6740 0.016 0.064 0.004 0.916 0.000
#> SRR1357276 2 0.2971 0.6902 0.000 0.836 0.000 0.008 0.156
#> SRR1498374 2 0.1341 0.7308 0.056 0.944 0.000 0.000 0.000
#> SRR1093721 2 0.2127 0.7230 0.108 0.892 0.000 0.000 0.000
#> SRR1464660 5 0.1364 0.6897 0.000 0.012 0.036 0.000 0.952
#> SRR1402051 2 0.4287 0.4179 0.460 0.540 0.000 0.000 0.000
#> SRR1488734 2 0.2773 0.6714 0.000 0.868 0.000 0.112 0.020
#> SRR1082616 4 0.2952 0.5770 0.088 0.036 0.004 0.872 0.000
#> SRR1099427 2 0.3752 0.6333 0.292 0.708 0.000 0.000 0.000
#> SRR1453093 2 0.4227 0.4860 0.420 0.580 0.000 0.000 0.000
#> SRR1357064 5 0.0727 0.6895 0.012 0.004 0.000 0.004 0.980
#> SRR811237 4 0.4010 0.7599 0.032 0.208 0.000 0.760 0.000
#> SRR1100848 2 0.2026 0.7204 0.012 0.928 0.000 0.044 0.016
#> SRR1346755 2 0.3395 0.6709 0.236 0.764 0.000 0.000 0.000
#> SRR1472529 2 0.1732 0.7270 0.080 0.920 0.000 0.000 0.000
#> SRR1398905 3 0.0451 0.8794 0.008 0.000 0.988 0.000 0.004
#> SRR1082733 2 0.2930 0.6230 0.000 0.832 0.000 0.164 0.004
#> SRR1308035 3 0.0290 0.8888 0.000 0.008 0.992 0.000 0.000
#> SRR1466445 3 0.0510 0.8894 0.000 0.016 0.984 0.000 0.000
#> SRR1359080 2 0.2104 0.7127 0.000 0.916 0.000 0.024 0.060
#> SRR1455825 2 0.2424 0.7165 0.132 0.868 0.000 0.000 0.000
#> SRR1389300 2 0.1121 0.7296 0.044 0.956 0.000 0.000 0.000
#> SRR812246 3 0.0290 0.8888 0.000 0.008 0.992 0.000 0.000
#> SRR1076632 4 0.3659 0.7624 0.000 0.220 0.000 0.768 0.012
#> SRR1415567 1 0.6214 0.6505 0.584 0.000 0.008 0.188 0.220
#> SRR1331900 2 0.2020 0.7242 0.100 0.900 0.000 0.000 0.000
#> SRR1452099 4 0.2569 0.5895 0.068 0.032 0.004 0.896 0.000
#> SRR1352346 5 0.2339 0.6525 0.000 0.100 0.004 0.004 0.892
#> SRR1364034 4 0.4014 0.7455 0.000 0.256 0.000 0.728 0.016
#> SRR1086046 1 0.3289 0.4997 0.844 0.108 0.000 0.048 0.000
#> SRR1407226 4 0.5976 -0.1878 0.116 0.000 0.000 0.508 0.376
#> SRR1319363 4 0.2890 0.3820 0.160 0.000 0.000 0.836 0.004
#> SRR1446961 2 0.2293 0.7199 0.000 0.900 0.084 0.000 0.016
#> SRR1486650 5 0.5949 -0.2530 0.376 0.000 0.008 0.088 0.528
#> SRR1470152 5 0.1704 0.6683 0.004 0.000 0.068 0.000 0.928
#> SRR1454785 3 0.0880 0.8812 0.000 0.032 0.968 0.000 0.000
#> SRR1092329 2 0.1764 0.7275 0.064 0.928 0.000 0.008 0.000
#> SRR1091476 3 0.0290 0.8888 0.000 0.008 0.992 0.000 0.000
#> SRR1073775 2 0.3816 0.6192 0.304 0.696 0.000 0.000 0.000
#> SRR1366873 2 0.3508 0.6591 0.252 0.748 0.000 0.000 0.000
#> SRR1398114 4 0.4938 0.6823 0.000 0.312 0.000 0.640 0.048
#> SRR1089950 1 0.4582 0.3967 0.572 0.012 0.000 0.000 0.416
#> SRR1433272 4 0.6061 0.6319 0.000 0.212 0.000 0.576 0.212
#> SRR1075314 1 0.1836 0.5835 0.932 0.032 0.000 0.036 0.000
#> SRR1085590 4 0.6704 0.3118 0.004 0.204 0.376 0.416 0.000
#> SRR1100752 3 0.0404 0.8896 0.000 0.012 0.988 0.000 0.000
#> SRR1391494 2 0.2629 0.6677 0.004 0.860 0.000 0.136 0.000
#> SRR1333263 4 0.3143 0.7643 0.000 0.204 0.000 0.796 0.000
#> SRR1310231 2 0.2504 0.6959 0.000 0.896 0.000 0.064 0.040
#> SRR1094144 4 0.3264 0.7519 0.016 0.164 0.000 0.820 0.000
#> SRR1092160 5 0.5562 0.1424 0.000 0.408 0.000 0.072 0.520
#> SRR1320300 2 0.2471 0.7139 0.136 0.864 0.000 0.000 0.000
#> SRR1322747 2 0.1981 0.7039 0.000 0.920 0.000 0.064 0.016
#> SRR1432719 3 0.0290 0.8888 0.000 0.008 0.992 0.000 0.000
#> SRR1100728 4 0.3053 0.7535 0.008 0.164 0.000 0.828 0.000
#> SRR1087511 2 0.4192 0.5091 0.404 0.596 0.000 0.000 0.000
#> SRR1470336 1 0.2171 0.6195 0.912 0.024 0.000 0.000 0.064
#> SRR1322536 1 0.1750 0.5871 0.936 0.036 0.000 0.028 0.000
#> SRR1100824 5 0.4915 0.4177 0.064 0.000 0.004 0.236 0.696
#> SRR1085951 3 0.2136 0.8318 0.008 0.000 0.904 0.088 0.000
#> SRR1322046 2 0.3779 0.5086 0.000 0.752 0.000 0.236 0.012
#> SRR1316420 5 0.2377 0.5802 0.128 0.000 0.000 0.000 0.872
#> SRR1070913 2 0.3534 0.6573 0.256 0.744 0.000 0.000 0.000
#> SRR1345806 3 0.1121 0.8684 0.000 0.044 0.956 0.000 0.000
#> SRR1313872 2 0.6671 -0.1846 0.000 0.412 0.000 0.236 0.352
#> SRR1337666 2 0.4464 0.5300 0.000 0.676 0.008 0.012 0.304
#> SRR1076823 1 0.4752 0.6469 0.684 0.000 0.004 0.272 0.040
#> SRR1093954 4 0.4675 0.5993 0.000 0.380 0.000 0.600 0.020
#> SRR1451921 1 0.4310 0.4816 0.604 0.004 0.000 0.392 0.000
#> SRR1491257 5 0.1124 0.6752 0.036 0.000 0.004 0.000 0.960
#> SRR1416979 4 0.4582 0.5101 0.012 0.416 0.000 0.572 0.000
#> SRR1419015 4 0.2052 0.5264 0.080 0.004 0.004 0.912 0.000
#> SRR817649 5 0.4468 0.5242 0.000 0.228 0.004 0.040 0.728
#> SRR1466376 2 0.2344 0.6994 0.000 0.904 0.000 0.064 0.032
#> SRR1392055 2 0.0955 0.7210 0.000 0.968 0.000 0.028 0.004
#> SRR1120913 2 0.3291 0.6524 0.000 0.840 0.000 0.120 0.040
#> SRR1120869 4 0.4054 0.7509 0.000 0.248 0.000 0.732 0.020
#> SRR1319419 3 0.0703 0.8843 0.000 0.024 0.976 0.000 0.000
#> SRR816495 3 0.4249 0.0990 0.000 0.432 0.568 0.000 0.000
#> SRR818694 2 0.4060 0.5648 0.360 0.640 0.000 0.000 0.000
#> SRR1465653 5 0.1646 0.6911 0.000 0.032 0.020 0.004 0.944
#> SRR1475952 1 0.3222 0.6648 0.852 0.000 0.004 0.036 0.108
#> SRR1465040 2 0.4949 0.5165 0.056 0.656 0.288 0.000 0.000
#> SRR1088461 2 0.5121 -0.2898 0.004 0.500 0.000 0.468 0.028
#> SRR810129 4 0.5505 0.6724 0.000 0.304 0.000 0.604 0.092
#> SRR1400141 3 0.3691 0.7378 0.000 0.040 0.804 0.156 0.000
#> SRR1349585 5 0.2517 0.6058 0.104 0.000 0.008 0.004 0.884
#> SRR1437576 2 0.1041 0.7200 0.004 0.964 0.000 0.032 0.000
#> SRR814407 1 0.5466 0.6705 0.676 0.000 0.012 0.208 0.104
#> SRR1332403 2 0.4779 0.0342 0.000 0.588 0.000 0.388 0.024
#> SRR1099598 2 0.4045 0.5693 0.356 0.644 0.000 0.000 0.000
#> SRR1327723 2 0.1281 0.7180 0.000 0.956 0.000 0.032 0.012
#> SRR1392525 4 0.4049 0.7411 0.040 0.164 0.008 0.788 0.000
#> SRR1320536 1 0.6398 0.4668 0.460 0.000 0.008 0.132 0.400
#> SRR1083824 2 0.2661 0.6961 0.000 0.888 0.000 0.056 0.056
#> SRR1351390 1 0.3582 0.6132 0.768 0.008 0.000 0.000 0.224
#> SRR1309141 4 0.4995 0.7277 0.000 0.264 0.000 0.668 0.068
#> SRR1452803 2 0.6388 0.0799 0.000 0.508 0.000 0.208 0.284
#> SRR811631 2 0.2280 0.7188 0.120 0.880 0.000 0.000 0.000
#> SRR1485563 4 0.5834 0.6002 0.136 0.276 0.000 0.588 0.000
#> SRR1311531 2 0.4300 0.1698 0.000 0.524 0.476 0.000 0.000
#> SRR1353076 2 0.2992 0.7150 0.068 0.868 0.000 0.064 0.000
#> SRR1480831 2 0.4757 0.5687 0.080 0.716 0.000 0.204 0.000
#> SRR1083892 5 0.1026 0.6908 0.004 0.004 0.000 0.024 0.968
#> SRR809873 4 0.2329 0.4559 0.124 0.000 0.000 0.876 0.000
#> SRR1341854 4 0.4380 0.6125 0.000 0.376 0.000 0.616 0.008
#> SRR1399335 4 0.6685 0.4646 0.000 0.340 0.000 0.416 0.244
#> SRR1464209 5 0.0671 0.6858 0.016 0.000 0.000 0.004 0.980
#> SRR1389886 2 0.2416 0.6822 0.000 0.888 0.000 0.100 0.012
#> SRR1400730 3 0.0404 0.8810 0.000 0.000 0.988 0.000 0.012
#> SRR1448008 2 0.2583 0.7173 0.132 0.864 0.000 0.004 0.000
#> SRR1087606 5 0.1121 0.6691 0.044 0.000 0.000 0.000 0.956
#> SRR1445111 1 0.6051 0.6012 0.576 0.000 0.020 0.088 0.316
#> SRR816865 4 0.3439 0.7622 0.004 0.188 0.000 0.800 0.008
#> SRR1323360 3 0.0510 0.8890 0.000 0.016 0.984 0.000 0.000
#> SRR1417364 2 0.5225 0.3205 0.000 0.564 0.392 0.004 0.040
#> SRR1480329 2 0.3796 0.6223 0.300 0.700 0.000 0.000 0.000
#> SRR1403322 1 0.4620 0.5769 0.612 0.000 0.004 0.372 0.012
#> SRR1093625 1 0.6333 0.6334 0.560 0.000 0.008 0.180 0.252
#> SRR1479977 2 0.0566 0.7278 0.012 0.984 0.000 0.004 0.000
#> SRR1082035 5 0.6339 0.3117 0.224 0.164 0.000 0.020 0.592
#> SRR1393046 2 0.1331 0.7156 0.000 0.952 0.000 0.040 0.008
#> SRR1466663 4 0.6049 0.6553 0.000 0.272 0.000 0.564 0.164
#> SRR1384456 1 0.6545 0.5415 0.484 0.000 0.008 0.164 0.344
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.2471 0.78365 0.000 0.896 0.000 0.044 0.020 0.040
#> SRR808862 3 0.2013 0.82015 0.008 0.000 0.908 0.008 0.000 0.076
#> SRR1500382 2 0.1908 0.78836 0.000 0.924 0.000 0.012 0.020 0.044
#> SRR1322683 2 0.3782 0.39978 0.000 0.588 0.000 0.000 0.000 0.412
#> SRR1329811 5 0.0713 0.80650 0.028 0.000 0.000 0.000 0.972 0.000
#> SRR1087297 2 0.0458 0.79979 0.000 0.984 0.000 0.000 0.016 0.000
#> SRR1072626 6 0.5930 0.26673 0.000 0.292 0.000 0.248 0.000 0.460
#> SRR1407428 1 0.0713 0.81852 0.972 0.000 0.000 0.000 0.000 0.028
#> SRR1321029 2 0.2585 0.77167 0.000 0.880 0.000 0.012 0.024 0.084
#> SRR1500282 1 0.2100 0.80287 0.884 0.000 0.004 0.000 0.112 0.000
#> SRR1100496 4 0.1889 0.73572 0.020 0.000 0.056 0.920 0.000 0.004
#> SRR1308778 2 0.4300 0.68706 0.000 0.748 0.000 0.088 0.152 0.012
#> SRR1445304 2 0.3053 0.76317 0.000 0.856 0.000 0.080 0.048 0.016
#> SRR1099378 5 0.3887 0.57634 0.020 0.008 0.000 0.248 0.724 0.000
#> SRR1347412 1 0.1471 0.82329 0.932 0.000 0.004 0.000 0.064 0.000
#> SRR1099694 2 0.5642 0.23012 0.000 0.472 0.000 0.088 0.420 0.020
#> SRR1088365 4 0.1168 0.75734 0.000 0.028 0.000 0.956 0.016 0.000
#> SRR1325752 4 0.4774 0.20803 0.428 0.020 0.000 0.532 0.020 0.000
#> SRR1416713 2 0.1536 0.79920 0.000 0.940 0.000 0.016 0.040 0.004
#> SRR1074474 1 0.0692 0.82787 0.976 0.000 0.000 0.004 0.020 0.000
#> SRR1469369 6 0.3482 0.45910 0.000 0.316 0.000 0.000 0.000 0.684
#> SRR1400507 2 0.1714 0.78357 0.000 0.908 0.000 0.000 0.000 0.092
#> SRR1378179 4 0.4694 0.56851 0.000 0.268 0.000 0.656 0.072 0.004
#> SRR1377905 2 0.4044 0.71060 0.000 0.744 0.000 0.076 0.180 0.000
#> SRR1089479 1 0.0692 0.82398 0.976 0.000 0.000 0.000 0.004 0.020
#> SRR1073365 2 0.3340 0.75804 0.000 0.832 0.000 0.112 0.028 0.028
#> SRR1500306 6 0.1910 0.71153 0.108 0.000 0.000 0.000 0.000 0.892
#> SRR1101566 6 0.3464 0.48589 0.000 0.312 0.000 0.000 0.000 0.688
#> SRR1350503 2 0.1151 0.79605 0.000 0.956 0.032 0.000 0.000 0.012
#> SRR1446007 2 0.4386 0.56641 0.000 0.652 0.300 0.000 0.000 0.048
#> SRR1102875 2 0.4635 -0.00624 0.000 0.488 0.000 0.480 0.008 0.024
#> SRR1380293 5 0.2147 0.76170 0.000 0.044 0.000 0.032 0.912 0.012
#> SRR1331198 2 0.3565 0.73990 0.000 0.796 0.000 0.008 0.156 0.040
#> SRR1092686 3 0.3189 0.63933 0.000 0.000 0.760 0.236 0.004 0.000
#> SRR1069421 4 0.0870 0.76003 0.004 0.012 0.000 0.972 0.012 0.000
#> SRR1341650 4 0.1333 0.74975 0.048 0.008 0.000 0.944 0.000 0.000
#> SRR1357276 2 0.2030 0.78482 0.000 0.908 0.000 0.000 0.064 0.028
#> SRR1498374 2 0.1493 0.79248 0.000 0.936 0.000 0.004 0.004 0.056
#> SRR1093721 2 0.4095 0.14560 0.000 0.512 0.000 0.000 0.008 0.480
#> SRR1464660 5 0.1390 0.80290 0.032 0.000 0.016 0.000 0.948 0.004
#> SRR1402051 6 0.2609 0.72471 0.096 0.036 0.000 0.000 0.000 0.868
#> SRR1488734 2 0.0935 0.79811 0.000 0.964 0.000 0.032 0.004 0.000
#> SRR1082616 4 0.2146 0.73121 0.044 0.000 0.004 0.908 0.000 0.044
#> SRR1099427 2 0.2883 0.68877 0.000 0.788 0.000 0.000 0.000 0.212
#> SRR1453093 6 0.2680 0.71945 0.004 0.124 0.000 0.016 0.000 0.856
#> SRR1357064 5 0.1866 0.78163 0.084 0.000 0.000 0.008 0.908 0.000
#> SRR811237 4 0.0777 0.76203 0.000 0.024 0.000 0.972 0.000 0.004
#> SRR1100848 2 0.6746 0.21710 0.000 0.444 0.000 0.052 0.244 0.260
#> SRR1346755 2 0.3371 0.61982 0.000 0.708 0.000 0.000 0.000 0.292
#> SRR1472529 2 0.1327 0.79061 0.000 0.936 0.000 0.000 0.000 0.064
#> SRR1398905 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1082733 2 0.2114 0.78587 0.000 0.904 0.000 0.076 0.008 0.012
#> SRR1308035 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1466445 3 0.0632 0.86359 0.000 0.024 0.976 0.000 0.000 0.000
#> SRR1359080 2 0.1237 0.79776 0.000 0.956 0.000 0.004 0.020 0.020
#> SRR1455825 2 0.2118 0.77716 0.000 0.888 0.000 0.000 0.008 0.104
#> SRR1389300 2 0.0865 0.79660 0.000 0.964 0.000 0.000 0.000 0.036
#> SRR812246 3 0.0935 0.85974 0.000 0.004 0.964 0.000 0.000 0.032
#> SRR1076632 4 0.0862 0.76052 0.004 0.016 0.000 0.972 0.008 0.000
#> SRR1415567 1 0.0508 0.82262 0.984 0.000 0.000 0.004 0.000 0.012
#> SRR1331900 2 0.0547 0.79734 0.000 0.980 0.000 0.000 0.000 0.020
#> SRR1452099 4 0.1461 0.74664 0.044 0.000 0.000 0.940 0.000 0.016
#> SRR1352346 5 0.2296 0.78126 0.020 0.008 0.000 0.012 0.908 0.052
#> SRR1364034 4 0.2651 0.72741 0.000 0.112 0.000 0.860 0.028 0.000
#> SRR1086046 6 0.2706 0.72502 0.068 0.028 0.000 0.024 0.000 0.880
#> SRR1407226 1 0.4516 0.54997 0.668 0.000 0.000 0.260 0.072 0.000
#> SRR1319363 4 0.2980 0.62301 0.192 0.000 0.000 0.800 0.000 0.008
#> SRR1446961 2 0.0508 0.79825 0.000 0.984 0.012 0.000 0.000 0.004
#> SRR1486650 1 0.2003 0.79581 0.884 0.000 0.000 0.000 0.116 0.000
#> SRR1470152 5 0.1794 0.79715 0.028 0.000 0.016 0.000 0.932 0.024
#> SRR1454785 3 0.3482 0.50333 0.000 0.316 0.684 0.000 0.000 0.000
#> SRR1092329 2 0.2442 0.75755 0.000 0.852 0.000 0.004 0.000 0.144
#> SRR1091476 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1073775 2 0.3607 0.50417 0.000 0.652 0.000 0.000 0.000 0.348
#> SRR1366873 2 0.2146 0.76722 0.000 0.880 0.000 0.004 0.000 0.116
#> SRR1398114 4 0.4278 0.46837 0.000 0.336 0.000 0.632 0.032 0.000
#> SRR1089950 6 0.6245 0.01252 0.216 0.012 0.000 0.000 0.384 0.388
#> SRR1433272 4 0.4015 0.37937 0.000 0.012 0.000 0.616 0.372 0.000
#> SRR1075314 6 0.2311 0.71018 0.104 0.000 0.000 0.016 0.000 0.880
#> SRR1085590 4 0.6645 0.18352 0.000 0.332 0.280 0.364 0.004 0.020
#> SRR1100752 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1391494 2 0.5040 0.06042 0.000 0.488 0.000 0.456 0.016 0.040
#> SRR1333263 4 0.0922 0.76095 0.004 0.024 0.000 0.968 0.004 0.000
#> SRR1310231 2 0.0622 0.79878 0.000 0.980 0.000 0.012 0.008 0.000
#> SRR1094144 4 0.1007 0.75791 0.016 0.008 0.000 0.968 0.004 0.004
#> SRR1092160 5 0.5007 0.28373 0.000 0.328 0.000 0.044 0.604 0.024
#> SRR1320300 2 0.0790 0.79724 0.000 0.968 0.000 0.000 0.000 0.032
#> SRR1322747 2 0.0291 0.79807 0.000 0.992 0.000 0.000 0.004 0.004
#> SRR1432719 3 0.3047 0.79044 0.000 0.052 0.872 0.028 0.036 0.012
#> SRR1100728 4 0.0870 0.75972 0.012 0.012 0.000 0.972 0.004 0.000
#> SRR1087511 6 0.1779 0.73347 0.016 0.064 0.000 0.000 0.000 0.920
#> SRR1470336 6 0.2278 0.70022 0.128 0.000 0.000 0.000 0.004 0.868
#> SRR1322536 6 0.2624 0.69603 0.124 0.000 0.000 0.020 0.000 0.856
#> SRR1100824 5 0.6001 0.02575 0.348 0.000 0.000 0.240 0.412 0.000
#> SRR1085951 3 0.0363 0.86850 0.000 0.000 0.988 0.012 0.000 0.000
#> SRR1322046 2 0.4454 0.60899 0.000 0.704 0.000 0.236 0.032 0.028
#> SRR1316420 5 0.3851 -0.00549 0.460 0.000 0.000 0.000 0.540 0.000
#> SRR1070913 2 0.3464 0.58576 0.000 0.688 0.000 0.000 0.000 0.312
#> SRR1345806 3 0.0363 0.86934 0.000 0.012 0.988 0.000 0.000 0.000
#> SRR1313872 2 0.4874 0.60058 0.000 0.640 0.000 0.108 0.252 0.000
#> SRR1337666 2 0.2879 0.74505 0.004 0.816 0.000 0.000 0.176 0.004
#> SRR1076823 1 0.1780 0.79604 0.924 0.000 0.000 0.028 0.000 0.048
#> SRR1093954 4 0.3819 0.57983 0.000 0.280 0.000 0.700 0.020 0.000
#> SRR1451921 6 0.5291 0.40008 0.120 0.000 0.000 0.328 0.000 0.552
#> SRR1491257 1 0.2793 0.71973 0.800 0.000 0.000 0.000 0.200 0.000
#> SRR1416979 4 0.4626 0.34834 0.000 0.372 0.000 0.588 0.008 0.032
#> SRR1419015 4 0.3052 0.59496 0.216 0.000 0.000 0.780 0.000 0.004
#> SRR817649 5 0.1338 0.78713 0.004 0.032 0.000 0.004 0.952 0.008
#> SRR1466376 2 0.0767 0.79899 0.000 0.976 0.000 0.008 0.012 0.004
#> SRR1392055 2 0.0993 0.79591 0.000 0.964 0.000 0.000 0.012 0.024
#> SRR1120913 2 0.2078 0.79370 0.000 0.916 0.000 0.040 0.032 0.012
#> SRR1120869 4 0.2121 0.74198 0.000 0.096 0.000 0.892 0.012 0.000
#> SRR1319419 3 0.2631 0.69847 0.000 0.180 0.820 0.000 0.000 0.000
#> SRR816495 2 0.3371 0.60603 0.000 0.708 0.292 0.000 0.000 0.000
#> SRR818694 6 0.2664 0.68769 0.000 0.184 0.000 0.000 0.000 0.816
#> SRR1465653 5 0.0713 0.80650 0.028 0.000 0.000 0.000 0.972 0.000
#> SRR1475952 6 0.3851 0.14300 0.460 0.000 0.000 0.000 0.000 0.540
#> SRR1465040 2 0.2941 0.68145 0.000 0.780 0.220 0.000 0.000 0.000
#> SRR1088461 2 0.5048 0.19656 0.000 0.552 0.000 0.388 0.036 0.024
#> SRR810129 4 0.4253 0.61665 0.000 0.232 0.000 0.704 0.064 0.000
#> SRR1400141 3 0.1501 0.83089 0.000 0.000 0.924 0.076 0.000 0.000
#> SRR1349585 1 0.2697 0.73184 0.812 0.000 0.000 0.000 0.188 0.000
#> SRR1437576 2 0.0146 0.79806 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR814407 1 0.4716 0.59029 0.708 0.000 0.084 0.020 0.000 0.188
#> SRR1332403 2 0.3011 0.70057 0.000 0.800 0.000 0.192 0.004 0.004
#> SRR1099598 6 0.1765 0.73065 0.000 0.096 0.000 0.000 0.000 0.904
#> SRR1327723 2 0.2828 0.78343 0.000 0.872 0.000 0.020 0.036 0.072
#> SRR1392525 4 0.1705 0.75765 0.016 0.024 0.008 0.940 0.000 0.012
#> SRR1320536 1 0.1588 0.82240 0.924 0.000 0.000 0.004 0.072 0.000
#> SRR1083824 2 0.0508 0.79984 0.000 0.984 0.004 0.000 0.012 0.000
#> SRR1351390 6 0.4549 0.49842 0.232 0.000 0.000 0.000 0.088 0.680
#> SRR1309141 2 0.4589 0.38339 0.004 0.612 0.004 0.348 0.032 0.000
#> SRR1452803 2 0.4403 0.68079 0.000 0.708 0.000 0.096 0.196 0.000
#> SRR811631 2 0.2092 0.76735 0.000 0.876 0.000 0.000 0.000 0.124
#> SRR1485563 4 0.4398 0.61448 0.032 0.068 0.000 0.764 0.004 0.132
#> SRR1311531 3 0.3728 0.40330 0.000 0.344 0.652 0.000 0.000 0.004
#> SRR1353076 2 0.2750 0.78340 0.000 0.868 0.000 0.080 0.004 0.048
#> SRR1480831 2 0.5798 0.31438 0.000 0.516 0.000 0.288 0.004 0.192
#> SRR1083892 5 0.1225 0.80427 0.036 0.000 0.000 0.012 0.952 0.000
#> SRR809873 4 0.2282 0.71538 0.088 0.000 0.000 0.888 0.000 0.024
#> SRR1341854 4 0.5169 0.00707 0.000 0.460 0.000 0.476 0.044 0.020
#> SRR1399335 2 0.6006 0.22358 0.000 0.508 0.000 0.156 0.316 0.020
#> SRR1464209 5 0.1663 0.78388 0.088 0.000 0.000 0.000 0.912 0.000
#> SRR1389886 2 0.0717 0.80062 0.000 0.976 0.000 0.016 0.008 0.000
#> SRR1400730 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1448008 2 0.3410 0.69740 0.000 0.768 0.000 0.008 0.008 0.216
#> SRR1087606 5 0.1082 0.80458 0.040 0.000 0.000 0.000 0.956 0.004
#> SRR1445111 1 0.2186 0.82268 0.908 0.000 0.000 0.008 0.048 0.036
#> SRR816865 4 0.0862 0.76052 0.004 0.016 0.000 0.972 0.008 0.000
#> SRR1323360 3 0.0000 0.87099 0.000 0.000 1.000 0.000 0.000 0.000
#> SRR1417364 2 0.2969 0.68035 0.000 0.776 0.224 0.000 0.000 0.000
#> SRR1480329 6 0.2212 0.72238 0.000 0.112 0.000 0.000 0.008 0.880
#> SRR1403322 1 0.5934 0.09938 0.444 0.000 0.000 0.228 0.000 0.328
#> SRR1093625 1 0.0436 0.82546 0.988 0.000 0.000 0.004 0.004 0.004
#> SRR1479977 2 0.0260 0.79730 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1082035 1 0.6765 0.17706 0.476 0.080 0.000 0.028 0.344 0.072
#> SRR1393046 2 0.1138 0.79741 0.000 0.960 0.000 0.012 0.004 0.024
#> SRR1466663 4 0.7318 0.30730 0.176 0.256 0.000 0.428 0.136 0.004
#> SRR1384456 1 0.1327 0.82368 0.936 0.000 0.000 0.000 0.064 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "hclust"]
# you can also extract it by
# res = res_list["ATC:hclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 0.955 0.941 0.973 0.2895 0.716 0.716
#> 3 3 0.756 0.844 0.889 0.4447 0.811 0.738
#> 4 4 0.510 0.718 0.841 0.2111 0.970 0.945
#> 5 5 0.482 0.691 0.829 0.0921 0.973 0.948
#> 6 6 0.525 0.638 0.801 0.0756 0.938 0.876
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
#> SRR810713 2 0.0000 0.978 0.000 1.000
#> SRR808862 2 0.1414 0.965 0.020 0.980
#> SRR1500382 2 0.3274 0.934 0.060 0.940
#> SRR1322683 2 0.0000 0.978 0.000 1.000
#> SRR1329811 2 0.6973 0.772 0.188 0.812
#> SRR1087297 2 0.2948 0.941 0.052 0.948
#> SRR1072626 2 0.0000 0.978 0.000 1.000
#> SRR1407428 1 0.0000 0.933 1.000 0.000
#> SRR1321029 2 0.0000 0.978 0.000 1.000
#> SRR1500282 1 0.0000 0.933 1.000 0.000
#> SRR1100496 2 0.0000 0.978 0.000 1.000
#> SRR1308778 2 0.2603 0.947 0.044 0.956
#> SRR1445304 2 0.0000 0.978 0.000 1.000
#> SRR1099378 2 0.4562 0.897 0.096 0.904
#> SRR1347412 1 0.0000 0.933 1.000 0.000
#> SRR1099694 2 0.0000 0.978 0.000 1.000
#> SRR1088365 2 0.0000 0.978 0.000 1.000
#> SRR1325752 2 0.3584 0.926 0.068 0.932
#> SRR1416713 2 0.0000 0.978 0.000 1.000
#> SRR1074474 1 0.0000 0.933 1.000 0.000
#> SRR1469369 2 0.0000 0.978 0.000 1.000
#> SRR1400507 2 0.0000 0.978 0.000 1.000
#> SRR1378179 2 0.2603 0.947 0.044 0.956
#> SRR1377905 2 0.0000 0.978 0.000 1.000
#> SRR1089479 1 0.1414 0.931 0.980 0.020
#> SRR1073365 2 0.0000 0.978 0.000 1.000
#> SRR1500306 2 0.4562 0.895 0.096 0.904
#> SRR1101566 2 0.0938 0.971 0.012 0.988
#> SRR1350503 2 0.0000 0.978 0.000 1.000
#> SRR1446007 2 0.0000 0.978 0.000 1.000
#> SRR1102875 2 0.0000 0.978 0.000 1.000
#> SRR1380293 2 0.3584 0.926 0.068 0.932
#> SRR1331198 2 0.0000 0.978 0.000 1.000
#> SRR1092686 2 0.0000 0.978 0.000 1.000
#> SRR1069421 2 0.0000 0.978 0.000 1.000
#> SRR1341650 2 0.0000 0.978 0.000 1.000
#> SRR1357276 2 0.3584 0.926 0.068 0.932
#> SRR1498374 2 0.0000 0.978 0.000 1.000
#> SRR1093721 2 0.0376 0.976 0.004 0.996
#> SRR1464660 1 0.1843 0.928 0.972 0.028
#> SRR1402051 2 0.0000 0.978 0.000 1.000
#> SRR1488734 2 0.2603 0.947 0.044 0.956
#> SRR1082616 2 0.0000 0.978 0.000 1.000
#> SRR1099427 2 0.3431 0.930 0.064 0.936
#> SRR1453093 2 0.0000 0.978 0.000 1.000
#> SRR1357064 1 0.1184 0.932 0.984 0.016
#> SRR811237 2 0.0000 0.978 0.000 1.000
#> SRR1100848 2 0.0000 0.978 0.000 1.000
#> SRR1346755 2 0.0000 0.978 0.000 1.000
#> SRR1472529 2 0.0000 0.978 0.000 1.000
#> SRR1398905 2 0.9833 0.231 0.424 0.576
#> SRR1082733 2 0.0000 0.978 0.000 1.000
#> SRR1308035 2 0.0000 0.978 0.000 1.000
#> SRR1466445 2 0.0000 0.978 0.000 1.000
#> SRR1359080 2 0.0000 0.978 0.000 1.000
#> SRR1455825 2 0.0000 0.978 0.000 1.000
#> SRR1389300 2 0.0000 0.978 0.000 1.000
#> SRR812246 2 0.0000 0.978 0.000 1.000
#> SRR1076632 2 0.0000 0.978 0.000 1.000
#> SRR1415567 1 0.0000 0.933 1.000 0.000
#> SRR1331900 2 0.0000 0.978 0.000 1.000
#> SRR1452099 2 0.0000 0.978 0.000 1.000
#> SRR1352346 1 0.0000 0.933 1.000 0.000
#> SRR1364034 2 0.0000 0.978 0.000 1.000
#> SRR1086046 2 0.0000 0.978 0.000 1.000
#> SRR1407226 1 0.9460 0.478 0.636 0.364
#> SRR1319363 2 0.1843 0.960 0.028 0.972
#> SRR1446961 2 0.0000 0.978 0.000 1.000
#> SRR1486650 1 0.0000 0.933 1.000 0.000
#> SRR1470152 1 0.0000 0.933 1.000 0.000
#> SRR1454785 2 0.0000 0.978 0.000 1.000
#> SRR1092329 2 0.0000 0.978 0.000 1.000
#> SRR1091476 2 0.1414 0.965 0.020 0.980
#> SRR1073775 2 0.0000 0.978 0.000 1.000
#> SRR1366873 2 0.0000 0.978 0.000 1.000
#> SRR1398114 2 0.0000 0.978 0.000 1.000
#> SRR1089950 2 0.5946 0.838 0.144 0.856
#> SRR1433272 2 0.0000 0.978 0.000 1.000
#> SRR1075314 2 0.0000 0.978 0.000 1.000
#> SRR1085590 2 0.0000 0.978 0.000 1.000
#> SRR1100752 2 0.0000 0.978 0.000 1.000
#> SRR1391494 2 0.0000 0.978 0.000 1.000
#> SRR1333263 2 0.0000 0.978 0.000 1.000
#> SRR1310231 2 0.2603 0.947 0.044 0.956
#> SRR1094144 2 0.0000 0.978 0.000 1.000
#> SRR1092160 2 0.0000 0.978 0.000 1.000
#> SRR1320300 2 0.0000 0.978 0.000 1.000
#> SRR1322747 2 0.0000 0.978 0.000 1.000
#> SRR1432719 2 0.0000 0.978 0.000 1.000
#> SRR1100728 2 0.0000 0.978 0.000 1.000
#> SRR1087511 2 0.0938 0.971 0.012 0.988
#> SRR1470336 1 0.3431 0.905 0.936 0.064
#> SRR1322536 2 0.0000 0.978 0.000 1.000
#> SRR1100824 2 0.6531 0.804 0.168 0.832
#> SRR1085951 2 0.0000 0.978 0.000 1.000
#> SRR1322046 2 0.0000 0.978 0.000 1.000
#> SRR1316420 1 0.5629 0.846 0.868 0.132
#> SRR1070913 2 0.0000 0.978 0.000 1.000
#> SRR1345806 2 0.0000 0.978 0.000 1.000
#> SRR1313872 2 0.0000 0.978 0.000 1.000
#> SRR1337666 2 0.0672 0.974 0.008 0.992
#> SRR1076823 2 0.2948 0.941 0.052 0.948
#> SRR1093954 2 0.0000 0.978 0.000 1.000
#> SRR1451921 2 0.0000 0.978 0.000 1.000
#> SRR1491257 1 0.9460 0.479 0.636 0.364
#> SRR1416979 2 0.0000 0.978 0.000 1.000
#> SRR1419015 2 0.2948 0.941 0.052 0.948
#> SRR817649 2 0.3584 0.926 0.068 0.932
#> SRR1466376 2 0.0000 0.978 0.000 1.000
#> SRR1392055 2 0.0000 0.978 0.000 1.000
#> SRR1120913 2 0.0000 0.978 0.000 1.000
#> SRR1120869 2 0.0000 0.978 0.000 1.000
#> SRR1319419 2 0.0000 0.978 0.000 1.000
#> SRR816495 2 0.0000 0.978 0.000 1.000
#> SRR818694 2 0.0000 0.978 0.000 1.000
#> SRR1465653 1 0.1184 0.932 0.984 0.016
#> SRR1475952 1 0.0376 0.933 0.996 0.004
#> SRR1465040 2 0.0000 0.978 0.000 1.000
#> SRR1088461 2 0.0000 0.978 0.000 1.000
#> SRR810129 2 0.0000 0.978 0.000 1.000
#> SRR1400141 2 0.0000 0.978 0.000 1.000
#> SRR1349585 1 0.0938 0.933 0.988 0.012
#> SRR1437576 2 0.0000 0.978 0.000 1.000
#> SRR814407 2 0.9833 0.231 0.424 0.576
#> SRR1332403 2 0.0000 0.978 0.000 1.000
#> SRR1099598 2 0.0938 0.971 0.012 0.988
#> SRR1327723 2 0.0000 0.978 0.000 1.000
#> SRR1392525 2 0.0000 0.978 0.000 1.000
#> SRR1320536 1 0.0000 0.933 1.000 0.000
#> SRR1083824 2 0.0000 0.978 0.000 1.000
#> SRR1351390 2 0.4431 0.900 0.092 0.908
#> SRR1309141 2 0.0000 0.978 0.000 1.000
#> SRR1452803 2 0.0000 0.978 0.000 1.000
#> SRR811631 2 0.0000 0.978 0.000 1.000
#> SRR1485563 2 0.0000 0.978 0.000 1.000
#> SRR1311531 2 0.0000 0.978 0.000 1.000
#> SRR1353076 2 0.0376 0.976 0.004 0.996
#> SRR1480831 2 0.0000 0.978 0.000 1.000
#> SRR1083892 1 0.1843 0.928 0.972 0.028
#> SRR809873 2 0.1843 0.960 0.028 0.972
#> SRR1341854 2 0.0000 0.978 0.000 1.000
#> SRR1399335 2 0.0000 0.978 0.000 1.000
#> SRR1464209 1 0.9323 0.514 0.652 0.348
#> SRR1389886 2 0.0000 0.978 0.000 1.000
#> SRR1400730 1 0.4431 0.884 0.908 0.092
#> SRR1448008 2 0.0000 0.978 0.000 1.000
#> SRR1087606 1 0.1843 0.928 0.972 0.028
#> SRR1445111 1 0.0000 0.933 1.000 0.000
#> SRR816865 2 0.0000 0.978 0.000 1.000
#> SRR1323360 2 0.0000 0.978 0.000 1.000
#> SRR1417364 2 0.0000 0.978 0.000 1.000
#> SRR1480329 2 0.3584 0.926 0.068 0.932
#> SRR1403322 2 0.5178 0.869 0.116 0.884
#> SRR1093625 1 0.0000 0.933 1.000 0.000
#> SRR1479977 2 0.0000 0.978 0.000 1.000
#> SRR1082035 1 0.5946 0.834 0.856 0.144
#> SRR1393046 2 0.0000 0.978 0.000 1.000
#> SRR1466663 2 0.0000 0.978 0.000 1.000
#> SRR1384456 1 0.0000 0.933 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.1289 0.9415 0.000 0.968 0.032
#> SRR808862 2 0.5760 0.1249 0.000 0.672 0.328
#> SRR1500382 3 0.6291 0.6817 0.000 0.468 0.532
#> SRR1322683 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1329811 3 0.5760 0.7050 0.000 0.328 0.672
#> SRR1087297 2 0.6192 -0.3473 0.000 0.580 0.420
#> SRR1072626 2 0.0237 0.9577 0.000 0.996 0.004
#> SRR1407428 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1321029 2 0.0747 0.9521 0.000 0.984 0.016
#> SRR1500282 1 0.4974 0.8503 0.764 0.000 0.236
#> SRR1100496 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1308778 2 0.4654 0.5993 0.000 0.792 0.208
#> SRR1445304 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1099378 3 0.6154 0.7441 0.000 0.408 0.592
#> SRR1347412 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1099694 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1325752 3 0.6260 0.7140 0.000 0.448 0.552
#> SRR1416713 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1469369 2 0.1163 0.9445 0.000 0.972 0.028
#> SRR1400507 2 0.0237 0.9577 0.000 0.996 0.004
#> SRR1378179 2 0.3879 0.7410 0.000 0.848 0.152
#> SRR1377905 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1089479 1 0.5621 0.8426 0.692 0.000 0.308
#> SRR1073365 2 0.0424 0.9564 0.000 0.992 0.008
#> SRR1500306 3 0.6192 0.7354 0.000 0.420 0.580
#> SRR1101566 2 0.1753 0.9248 0.000 0.952 0.048
#> SRR1350503 2 0.1753 0.9242 0.000 0.952 0.048
#> SRR1446007 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1102875 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1380293 3 0.6299 0.6635 0.000 0.476 0.524
#> SRR1331198 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1092686 2 0.1163 0.9445 0.000 0.972 0.028
#> SRR1069421 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1341650 2 0.0892 0.9498 0.000 0.980 0.020
#> SRR1357276 3 0.6260 0.7140 0.000 0.448 0.552
#> SRR1498374 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1093721 2 0.1860 0.9196 0.000 0.948 0.052
#> SRR1464660 1 0.5988 0.8223 0.632 0.000 0.368
#> SRR1402051 2 0.0424 0.9531 0.000 0.992 0.008
#> SRR1488734 2 0.3879 0.7410 0.000 0.848 0.152
#> SRR1082616 2 0.0424 0.9531 0.000 0.992 0.008
#> SRR1099427 3 0.6286 0.6890 0.000 0.464 0.536
#> SRR1453093 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1357064 1 0.5529 0.8437 0.704 0.000 0.296
#> SRR811237 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1100848 2 0.0424 0.9564 0.000 0.992 0.008
#> SRR1346755 2 0.0892 0.9501 0.000 0.980 0.020
#> SRR1472529 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1398905 3 0.1337 0.0373 0.012 0.016 0.972
#> SRR1082733 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1308035 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1466445 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1359080 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR812246 2 0.1411 0.9366 0.000 0.964 0.036
#> SRR1076632 2 0.1289 0.9419 0.000 0.968 0.032
#> SRR1415567 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1452099 2 0.0892 0.9498 0.000 0.980 0.020
#> SRR1352346 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1364034 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1086046 2 0.1031 0.9370 0.000 0.976 0.024
#> SRR1407226 3 0.6264 -0.3145 0.244 0.032 0.724
#> SRR1319363 3 0.6204 0.7154 0.000 0.424 0.576
#> SRR1446961 2 0.0892 0.9498 0.000 0.980 0.020
#> SRR1486650 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1470152 1 0.2625 0.8492 0.916 0.000 0.084
#> SRR1454785 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1092329 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1091476 2 0.5760 0.1249 0.000 0.672 0.328
#> SRR1073775 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1089950 3 0.5948 0.7487 0.000 0.360 0.640
#> SRR1433272 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1075314 2 0.1163 0.9328 0.000 0.972 0.028
#> SRR1085590 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1100752 2 0.0747 0.9521 0.000 0.984 0.016
#> SRR1391494 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1333263 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1310231 2 0.4654 0.5993 0.000 0.792 0.208
#> SRR1094144 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1092160 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1322747 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1432719 2 0.0892 0.9498 0.000 0.980 0.020
#> SRR1100728 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1087511 2 0.1753 0.9248 0.000 0.952 0.048
#> SRR1470336 1 0.6140 0.8101 0.596 0.000 0.404
#> SRR1322536 2 0.1163 0.9328 0.000 0.972 0.028
#> SRR1100824 3 0.6818 0.7265 0.024 0.348 0.628
#> SRR1085951 2 0.0592 0.9494 0.000 0.988 0.012
#> SRR1322046 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1316420 1 0.6308 0.7249 0.508 0.000 0.492
#> SRR1070913 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1345806 2 0.1163 0.9442 0.000 0.972 0.028
#> SRR1313872 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1337666 2 0.2165 0.9025 0.000 0.936 0.064
#> SRR1076823 3 0.6111 0.7368 0.000 0.396 0.604
#> SRR1093954 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1451921 2 0.1643 0.9128 0.000 0.956 0.044
#> SRR1491257 3 0.7157 -0.3026 0.276 0.056 0.668
#> SRR1416979 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1419015 3 0.6215 0.7311 0.000 0.428 0.572
#> SRR817649 3 0.6274 0.7022 0.000 0.456 0.544
#> SRR1466376 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1392055 2 0.1411 0.9373 0.000 0.964 0.036
#> SRR1120913 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1120869 2 0.1411 0.9381 0.000 0.964 0.036
#> SRR1319419 2 0.1289 0.9418 0.000 0.968 0.032
#> SRR816495 2 0.1411 0.9373 0.000 0.964 0.036
#> SRR818694 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1465653 1 0.5926 0.8276 0.644 0.000 0.356
#> SRR1475952 1 0.5621 0.8438 0.692 0.000 0.308
#> SRR1465040 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1088461 2 0.0424 0.9563 0.000 0.992 0.008
#> SRR810129 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1400141 2 0.1163 0.9445 0.000 0.972 0.028
#> SRR1349585 1 0.5465 0.8448 0.712 0.000 0.288
#> SRR1437576 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR814407 3 0.1337 0.0373 0.012 0.016 0.972
#> SRR1332403 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1099598 2 0.1753 0.9248 0.000 0.952 0.048
#> SRR1327723 2 0.1031 0.9479 0.000 0.976 0.024
#> SRR1392525 2 0.0592 0.9549 0.000 0.988 0.012
#> SRR1320536 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1083824 2 0.0237 0.9575 0.000 0.996 0.004
#> SRR1351390 3 0.6225 0.7267 0.000 0.432 0.568
#> SRR1309141 2 0.1411 0.9381 0.000 0.964 0.036
#> SRR1452803 2 0.1411 0.9373 0.000 0.964 0.036
#> SRR811631 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1485563 2 0.1031 0.9468 0.000 0.976 0.024
#> SRR1311531 2 0.1163 0.9442 0.000 0.972 0.028
#> SRR1353076 2 0.1529 0.9339 0.000 0.960 0.040
#> SRR1480831 2 0.0592 0.9549 0.000 0.988 0.012
#> SRR1083892 1 0.5988 0.8223 0.632 0.000 0.368
#> SRR809873 3 0.6204 0.7154 0.000 0.424 0.576
#> SRR1341854 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1399335 2 0.1411 0.9381 0.000 0.964 0.036
#> SRR1464209 3 0.5977 -0.3531 0.252 0.020 0.728
#> SRR1389886 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1400730 1 0.6286 0.7554 0.536 0.000 0.464
#> SRR1448008 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1087606 1 0.5988 0.8223 0.632 0.000 0.368
#> SRR1445111 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR816865 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1323360 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1417364 2 0.0892 0.9498 0.000 0.980 0.020
#> SRR1480329 3 0.6260 0.7140 0.000 0.448 0.552
#> SRR1403322 3 0.6033 0.7054 0.004 0.336 0.660
#> SRR1093625 1 0.0000 0.8436 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1082035 1 0.7138 0.7264 0.540 0.024 0.436
#> SRR1393046 2 0.0000 0.9590 0.000 1.000 0.000
#> SRR1466663 2 0.1031 0.9468 0.000 0.976 0.024
#> SRR1384456 1 0.0000 0.8436 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.3024 0.8153 0.000 0.852 0.000 0.148
#> SRR808862 2 0.5167 -0.1806 0.000 0.508 0.004 0.488
#> SRR1500382 4 0.4722 0.7480 0.000 0.300 0.008 0.692
#> SRR1322683 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1329811 4 0.6883 0.6282 0.000 0.192 0.212 0.596
#> SRR1087297 4 0.5050 0.5232 0.000 0.408 0.004 0.588
#> SRR1072626 2 0.1716 0.8615 0.000 0.936 0.000 0.064
#> SRR1407428 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1321029 2 0.2149 0.8510 0.000 0.912 0.000 0.088
#> SRR1500282 1 0.4040 0.5265 0.752 0.000 0.248 0.000
#> SRR1100496 2 0.1902 0.8342 0.000 0.932 0.004 0.064
#> SRR1308778 2 0.4790 0.3532 0.000 0.620 0.000 0.380
#> SRR1445304 2 0.0188 0.8696 0.000 0.996 0.000 0.004
#> SRR1099378 4 0.5500 0.7401 0.000 0.224 0.068 0.708
#> SRR1347412 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1099694 2 0.0707 0.8713 0.000 0.980 0.000 0.020
#> SRR1088365 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1325752 4 0.4567 0.7600 0.000 0.276 0.008 0.716
#> SRR1416713 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1074474 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1469369 2 0.3123 0.8087 0.000 0.844 0.000 0.156
#> SRR1400507 2 0.1389 0.8651 0.000 0.952 0.000 0.048
#> SRR1378179 2 0.4543 0.5254 0.000 0.676 0.000 0.324
#> SRR1377905 2 0.0188 0.8696 0.000 0.996 0.000 0.004
#> SRR1089479 1 0.5244 0.1938 0.600 0.000 0.388 0.012
#> SRR1073365 2 0.2589 0.8374 0.000 0.884 0.000 0.116
#> SRR1500306 4 0.5839 0.6493 0.000 0.200 0.104 0.696
#> SRR1101566 2 0.3528 0.7729 0.000 0.808 0.000 0.192
#> SRR1350503 2 0.3688 0.7518 0.000 0.792 0.000 0.208
#> SRR1446007 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1380293 4 0.4746 0.7427 0.000 0.304 0.008 0.688
#> SRR1331198 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1092686 2 0.3266 0.7961 0.000 0.832 0.000 0.168
#> SRR1069421 2 0.2197 0.8093 0.000 0.916 0.004 0.080
#> SRR1341650 2 0.3172 0.8033 0.000 0.840 0.000 0.160
#> SRR1357276 4 0.4567 0.7600 0.000 0.276 0.008 0.716
#> SRR1498374 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1093721 2 0.3649 0.7570 0.000 0.796 0.000 0.204
#> SRR1464660 3 0.5503 0.2340 0.468 0.000 0.516 0.016
#> SRR1402051 2 0.2976 0.7583 0.000 0.872 0.008 0.120
#> SRR1488734 2 0.4543 0.5254 0.000 0.676 0.000 0.324
#> SRR1082616 2 0.2675 0.7889 0.000 0.892 0.008 0.100
#> SRR1099427 4 0.4509 0.7550 0.000 0.288 0.004 0.708
#> SRR1453093 2 0.0817 0.8587 0.000 0.976 0.000 0.024
#> SRR1357064 1 0.5231 0.1924 0.604 0.000 0.384 0.012
#> SRR811237 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1100848 2 0.1792 0.8608 0.000 0.932 0.000 0.068
#> SRR1346755 2 0.2530 0.8390 0.000 0.888 0.000 0.112
#> SRR1472529 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1398905 3 0.4103 0.3617 0.000 0.000 0.744 0.256
#> SRR1082733 2 0.0188 0.8715 0.000 0.996 0.000 0.004
#> SRR1308035 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1466445 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.0469 0.8718 0.000 0.988 0.000 0.012
#> SRR1455825 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1389300 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR812246 2 0.4137 0.6740 0.000 0.780 0.012 0.208
#> SRR1076632 2 0.3356 0.7897 0.000 0.824 0.000 0.176
#> SRR1415567 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1331900 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1452099 2 0.3306 0.8169 0.000 0.840 0.004 0.156
#> SRR1352346 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1364034 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1086046 2 0.4079 0.6608 0.000 0.800 0.020 0.180
#> SRR1407226 3 0.6806 0.4796 0.112 0.000 0.544 0.344
#> SRR1319363 4 0.5798 0.3959 0.000 0.096 0.208 0.696
#> SRR1446961 2 0.2345 0.8455 0.000 0.900 0.000 0.100
#> SRR1486650 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.3610 0.5920 0.800 0.000 0.200 0.000
#> SRR1454785 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1092329 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1091476 2 0.5167 -0.1806 0.000 0.508 0.004 0.488
#> SRR1073775 2 0.0188 0.8694 0.000 0.996 0.000 0.004
#> SRR1366873 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1398114 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1089950 4 0.6534 0.7042 0.000 0.220 0.148 0.632
#> SRR1433272 2 0.2125 0.8242 0.000 0.920 0.004 0.076
#> SRR1075314 2 0.4868 0.4935 0.000 0.720 0.024 0.256
#> SRR1085590 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1100752 2 0.2081 0.8527 0.000 0.916 0.000 0.084
#> SRR1391494 2 0.0592 0.8720 0.000 0.984 0.000 0.016
#> SRR1333263 2 0.2125 0.8242 0.000 0.920 0.004 0.076
#> SRR1310231 2 0.4790 0.3532 0.000 0.620 0.000 0.380
#> SRR1094144 2 0.2197 0.8194 0.000 0.916 0.004 0.080
#> SRR1092160 2 0.0817 0.8706 0.000 0.976 0.000 0.024
#> SRR1320300 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1322747 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1432719 2 0.2408 0.8435 0.000 0.896 0.000 0.104
#> SRR1100728 2 0.2197 0.8194 0.000 0.916 0.004 0.080
#> SRR1087511 2 0.3528 0.7729 0.000 0.808 0.000 0.192
#> SRR1470336 1 0.5805 0.1837 0.576 0.000 0.388 0.036
#> SRR1322536 2 0.4868 0.4935 0.000 0.720 0.024 0.256
#> SRR1100824 4 0.6399 0.6758 0.012 0.180 0.128 0.680
#> SRR1085951 2 0.3498 0.7008 0.000 0.832 0.008 0.160
#> SRR1322046 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1316420 3 0.6851 0.4301 0.344 0.000 0.540 0.116
#> SRR1070913 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1345806 2 0.3219 0.8011 0.000 0.836 0.000 0.164
#> SRR1313872 2 0.0592 0.8718 0.000 0.984 0.000 0.016
#> SRR1337666 2 0.3649 0.7576 0.000 0.796 0.000 0.204
#> SRR1076823 4 0.5681 0.3964 0.000 0.088 0.208 0.704
#> SRR1093954 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1451921 2 0.5227 0.4802 0.000 0.704 0.040 0.256
#> SRR1491257 3 0.7540 0.4743 0.112 0.032 0.552 0.304
#> SRR1416979 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1419015 4 0.5528 0.7334 0.000 0.236 0.064 0.700
#> SRR817649 4 0.4621 0.7575 0.000 0.284 0.008 0.708
#> SRR1466376 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1392055 2 0.3444 0.7809 0.000 0.816 0.000 0.184
#> SRR1120913 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1120869 2 0.3400 0.7856 0.000 0.820 0.000 0.180
#> SRR1319419 2 0.3266 0.7962 0.000 0.832 0.000 0.168
#> SRR816495 2 0.3400 0.7858 0.000 0.820 0.000 0.180
#> SRR818694 2 0.0817 0.8587 0.000 0.976 0.000 0.024
#> SRR1465653 3 0.5510 0.1932 0.480 0.000 0.504 0.016
#> SRR1475952 1 0.4677 0.4234 0.680 0.000 0.316 0.004
#> SRR1465040 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1088461 2 0.2704 0.8313 0.000 0.876 0.000 0.124
#> SRR810129 2 0.0188 0.8696 0.000 0.996 0.000 0.004
#> SRR1400141 2 0.3266 0.7961 0.000 0.832 0.000 0.168
#> SRR1349585 1 0.5070 0.2442 0.620 0.000 0.372 0.008
#> SRR1437576 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR814407 3 0.4103 0.3617 0.000 0.000 0.744 0.256
#> SRR1332403 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1099598 2 0.3528 0.7729 0.000 0.808 0.000 0.192
#> SRR1327723 2 0.3074 0.8105 0.000 0.848 0.000 0.152
#> SRR1392525 2 0.2469 0.8415 0.000 0.892 0.000 0.108
#> SRR1320536 1 0.0469 0.7617 0.988 0.000 0.012 0.000
#> SRR1083824 2 0.1792 0.8606 0.000 0.932 0.000 0.068
#> SRR1351390 4 0.5705 0.6619 0.000 0.204 0.092 0.704
#> SRR1309141 2 0.3400 0.7856 0.000 0.820 0.000 0.180
#> SRR1452803 2 0.3444 0.7809 0.000 0.816 0.000 0.184
#> SRR811631 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1485563 2 0.3219 0.7994 0.000 0.836 0.000 0.164
#> SRR1311531 2 0.3266 0.7977 0.000 0.832 0.000 0.168
#> SRR1353076 2 0.3311 0.7930 0.000 0.828 0.000 0.172
#> SRR1480831 2 0.2469 0.8415 0.000 0.892 0.000 0.108
#> SRR1083892 3 0.5503 0.2340 0.468 0.000 0.516 0.016
#> SRR809873 4 0.5798 0.3959 0.000 0.096 0.208 0.696
#> SRR1341854 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1399335 2 0.3400 0.7856 0.000 0.820 0.000 0.180
#> SRR1464209 3 0.6898 0.4964 0.124 0.004 0.580 0.292
#> SRR1389886 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1400730 3 0.5984 0.3783 0.372 0.000 0.580 0.048
#> SRR1448008 2 0.0817 0.8587 0.000 0.976 0.000 0.024
#> SRR1087606 3 0.5503 0.2340 0.468 0.000 0.516 0.016
#> SRR1445111 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR816865 2 0.2197 0.8093 0.000 0.916 0.004 0.080
#> SRR1323360 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1417364 2 0.2345 0.8455 0.000 0.900 0.000 0.100
#> SRR1480329 4 0.4567 0.7600 0.000 0.276 0.008 0.716
#> SRR1403322 4 0.6552 0.0462 0.000 0.076 0.440 0.484
#> SRR1093625 1 0.0000 0.7683 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.0336 0.8719 0.000 0.992 0.000 0.008
#> SRR1082035 3 0.7307 0.3892 0.376 0.000 0.468 0.156
#> SRR1393046 2 0.0000 0.8710 0.000 1.000 0.000 0.000
#> SRR1466663 2 0.3219 0.7994 0.000 0.836 0.000 0.164
#> SRR1384456 1 0.0000 0.7683 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.3003 0.7714 0.000 0.812 0.188 0.000 0.000
#> SRR808862 3 0.4426 0.4730 0.000 0.380 0.612 0.004 0.004
#> SRR1500382 3 0.3795 0.7353 0.000 0.192 0.780 0.000 0.028
#> SRR1322683 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1329811 3 0.6146 0.4530 0.000 0.108 0.548 0.012 0.332
#> SRR1087297 3 0.4630 0.6238 0.000 0.300 0.672 0.008 0.020
#> SRR1072626 2 0.2068 0.8237 0.000 0.904 0.092 0.004 0.000
#> SRR1407428 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.2377 0.8078 0.000 0.872 0.128 0.000 0.000
#> SRR1500282 1 0.3707 0.4657 0.716 0.000 0.000 0.000 0.284
#> SRR1100496 2 0.2800 0.7801 0.000 0.892 0.040 0.052 0.016
#> SRR1308778 2 0.4452 0.0203 0.000 0.500 0.496 0.000 0.004
#> SRR1445304 2 0.0324 0.8355 0.000 0.992 0.004 0.000 0.004
#> SRR1099378 3 0.5171 0.6686 0.000 0.120 0.740 0.036 0.104
#> SRR1347412 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.0880 0.8391 0.000 0.968 0.032 0.000 0.000
#> SRR1088365 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1325752 3 0.3774 0.7370 0.000 0.160 0.804 0.008 0.028
#> SRR1416713 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1074474 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 2 0.3551 0.7410 0.000 0.772 0.220 0.000 0.008
#> SRR1400507 2 0.1608 0.8289 0.000 0.928 0.072 0.000 0.000
#> SRR1378179 2 0.4268 0.2655 0.000 0.556 0.444 0.000 0.000
#> SRR1377905 2 0.0324 0.8355 0.000 0.992 0.004 0.000 0.004
#> SRR1089479 1 0.4594 -0.1221 0.508 0.000 0.004 0.004 0.484
#> SRR1073365 2 0.2929 0.7774 0.000 0.820 0.180 0.000 0.000
#> SRR1500306 3 0.7179 0.4341 0.000 0.120 0.560 0.120 0.200
#> SRR1101566 2 0.3707 0.6630 0.000 0.716 0.284 0.000 0.000
#> SRR1350503 2 0.3707 0.6631 0.000 0.716 0.284 0.000 0.000
#> SRR1446007 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1102875 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1380293 3 0.3724 0.7375 0.000 0.184 0.788 0.000 0.028
#> SRR1331198 2 0.0794 0.8384 0.000 0.972 0.028 0.000 0.000
#> SRR1092686 2 0.3366 0.7291 0.000 0.768 0.232 0.000 0.000
#> SRR1069421 2 0.3022 0.7514 0.000 0.880 0.036 0.064 0.020
#> SRR1341650 2 0.3274 0.7405 0.000 0.780 0.220 0.000 0.000
#> SRR1357276 3 0.3774 0.7370 0.000 0.160 0.804 0.008 0.028
#> SRR1498374 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1093721 2 0.3684 0.6708 0.000 0.720 0.280 0.000 0.000
#> SRR1464660 5 0.4084 0.6045 0.328 0.000 0.004 0.000 0.668
#> SRR1402051 2 0.3967 0.6650 0.000 0.808 0.040 0.136 0.016
#> SRR1488734 2 0.4268 0.2655 0.000 0.556 0.444 0.000 0.000
#> SRR1082616 2 0.3442 0.7254 0.000 0.852 0.044 0.088 0.016
#> SRR1099427 3 0.3754 0.7406 0.000 0.176 0.796 0.008 0.020
#> SRR1453093 2 0.1059 0.8235 0.000 0.968 0.020 0.008 0.004
#> SRR1357064 1 0.4452 -0.1657 0.500 0.000 0.004 0.000 0.496
#> SRR811237 2 0.0290 0.8358 0.000 0.992 0.000 0.000 0.008
#> SRR1100848 2 0.2233 0.8198 0.000 0.892 0.104 0.004 0.000
#> SRR1346755 2 0.2732 0.7911 0.000 0.840 0.160 0.000 0.000
#> SRR1472529 2 0.0794 0.8384 0.000 0.972 0.028 0.000 0.000
#> SRR1398905 4 0.5513 0.4157 0.000 0.000 0.116 0.632 0.252
#> SRR1082733 2 0.0290 0.8381 0.000 0.992 0.008 0.000 0.000
#> SRR1308035 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1466445 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1359080 2 0.0404 0.8390 0.000 0.988 0.012 0.000 0.000
#> SRR1455825 2 0.0794 0.8385 0.000 0.972 0.028 0.000 0.000
#> SRR1389300 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR812246 2 0.5453 0.5538 0.000 0.692 0.088 0.196 0.024
#> SRR1076632 2 0.3452 0.7183 0.000 0.756 0.244 0.000 0.000
#> SRR1415567 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0794 0.8385 0.000 0.972 0.028 0.000 0.000
#> SRR1452099 2 0.3670 0.7700 0.000 0.796 0.180 0.020 0.004
#> SRR1352346 1 0.0693 0.7416 0.980 0.000 0.008 0.000 0.012
#> SRR1364034 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1086046 2 0.5109 0.5434 0.000 0.712 0.052 0.208 0.028
#> SRR1407226 5 0.4244 0.4602 0.012 0.000 0.248 0.012 0.728
#> SRR1319363 4 0.4799 0.6458 0.000 0.016 0.312 0.656 0.016
#> SRR1446961 2 0.2732 0.7916 0.000 0.840 0.160 0.000 0.000
#> SRR1486650 1 0.0693 0.7416 0.980 0.000 0.008 0.000 0.012
#> SRR1470152 1 0.4067 0.4266 0.692 0.000 0.008 0.000 0.300
#> SRR1454785 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1092329 2 0.0290 0.8358 0.000 0.992 0.000 0.000 0.008
#> SRR1091476 3 0.4426 0.4730 0.000 0.380 0.612 0.004 0.004
#> SRR1073775 2 0.0324 0.8354 0.000 0.992 0.000 0.004 0.004
#> SRR1366873 2 0.0794 0.8385 0.000 0.972 0.028 0.000 0.000
#> SRR1398114 2 0.0510 0.8392 0.000 0.984 0.016 0.000 0.000
#> SRR1089950 3 0.6209 0.5714 0.000 0.120 0.600 0.024 0.256
#> SRR1433272 2 0.3003 0.7610 0.000 0.880 0.040 0.064 0.016
#> SRR1075314 2 0.5854 0.3208 0.000 0.604 0.044 0.308 0.044
#> SRR1085590 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1100752 2 0.2179 0.8146 0.000 0.888 0.112 0.000 0.000
#> SRR1391494 2 0.0510 0.8397 0.000 0.984 0.016 0.000 0.000
#> SRR1333263 2 0.3003 0.7610 0.000 0.880 0.040 0.064 0.016
#> SRR1310231 2 0.4452 0.0203 0.000 0.500 0.496 0.000 0.004
#> SRR1094144 2 0.3152 0.7605 0.000 0.872 0.048 0.064 0.016
#> SRR1092160 2 0.0963 0.8384 0.000 0.964 0.036 0.000 0.000
#> SRR1320300 2 0.0794 0.8385 0.000 0.972 0.028 0.000 0.000
#> SRR1322747 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1432719 2 0.2773 0.7893 0.000 0.836 0.164 0.000 0.000
#> SRR1100728 2 0.3152 0.7605 0.000 0.872 0.048 0.064 0.016
#> SRR1087511 2 0.3707 0.6630 0.000 0.716 0.284 0.000 0.000
#> SRR1470336 1 0.6649 0.2552 0.544 0.000 0.124 0.036 0.296
#> SRR1322536 2 0.5854 0.3208 0.000 0.604 0.044 0.308 0.044
#> SRR1100824 3 0.5624 0.5849 0.000 0.096 0.692 0.036 0.176
#> SRR1085951 2 0.4443 0.6006 0.000 0.764 0.044 0.176 0.016
#> SRR1322046 2 0.0703 0.8385 0.000 0.976 0.024 0.000 0.000
#> SRR1316420 5 0.4944 0.6657 0.208 0.000 0.092 0.000 0.700
#> SRR1070913 2 0.0609 0.8387 0.000 0.980 0.020 0.000 0.000
#> SRR1345806 2 0.3366 0.7315 0.000 0.768 0.232 0.000 0.000
#> SRR1313872 2 0.0510 0.8396 0.000 0.984 0.016 0.000 0.000
#> SRR1337666 2 0.3707 0.6631 0.000 0.716 0.284 0.000 0.000
#> SRR1076823 4 0.4661 0.6229 0.000 0.004 0.356 0.624 0.016
#> SRR1093954 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1451921 2 0.5408 0.2795 0.000 0.584 0.020 0.364 0.032
#> SRR1491257 5 0.4025 0.4603 0.008 0.000 0.232 0.012 0.748
#> SRR1416979 2 0.0290 0.8358 0.000 0.992 0.000 0.000 0.008
#> SRR1419015 3 0.5729 0.5616 0.000 0.140 0.664 0.180 0.016
#> SRR817649 3 0.3852 0.7413 0.000 0.168 0.796 0.008 0.028
#> SRR1466376 2 0.0794 0.8384 0.000 0.972 0.028 0.000 0.000
#> SRR1392055 2 0.3480 0.7113 0.000 0.752 0.248 0.000 0.000
#> SRR1120913 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1120869 2 0.3452 0.7166 0.000 0.756 0.244 0.000 0.000
#> SRR1319419 2 0.3210 0.7472 0.000 0.788 0.212 0.000 0.000
#> SRR816495 2 0.3480 0.7133 0.000 0.752 0.248 0.000 0.000
#> SRR818694 2 0.1059 0.8235 0.000 0.968 0.020 0.008 0.004
#> SRR1465653 5 0.4135 0.5787 0.340 0.000 0.004 0.000 0.656
#> SRR1475952 1 0.5684 0.4340 0.648 0.000 0.096 0.016 0.240
#> SRR1465040 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1088461 2 0.2966 0.7724 0.000 0.816 0.184 0.000 0.000
#> SRR810129 2 0.0324 0.8355 0.000 0.992 0.004 0.000 0.004
#> SRR1400141 2 0.3366 0.7291 0.000 0.768 0.232 0.000 0.000
#> SRR1349585 1 0.4446 -0.0910 0.520 0.000 0.004 0.000 0.476
#> SRR1437576 2 0.0671 0.8393 0.000 0.980 0.016 0.000 0.004
#> SRR814407 4 0.5513 0.4157 0.000 0.000 0.116 0.632 0.252
#> SRR1332403 2 0.0404 0.8383 0.000 0.988 0.012 0.000 0.000
#> SRR1099598 2 0.3707 0.6630 0.000 0.716 0.284 0.000 0.000
#> SRR1327723 2 0.3074 0.7616 0.000 0.804 0.196 0.000 0.000
#> SRR1392525 2 0.3289 0.7797 0.000 0.816 0.172 0.004 0.008
#> SRR1320536 1 0.0609 0.7415 0.980 0.000 0.000 0.000 0.020
#> SRR1083824 2 0.1851 0.8252 0.000 0.912 0.088 0.000 0.000
#> SRR1351390 3 0.7074 0.4608 0.000 0.120 0.572 0.112 0.196
#> SRR1309141 2 0.3452 0.7166 0.000 0.756 0.244 0.000 0.000
#> SRR1452803 2 0.3480 0.7113 0.000 0.752 0.248 0.000 0.000
#> SRR811631 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1485563 2 0.3305 0.7365 0.000 0.776 0.224 0.000 0.000
#> SRR1311531 2 0.3395 0.7272 0.000 0.764 0.236 0.000 0.000
#> SRR1353076 2 0.3242 0.7445 0.000 0.784 0.216 0.000 0.000
#> SRR1480831 2 0.3289 0.7797 0.000 0.816 0.172 0.004 0.008
#> SRR1083892 5 0.4084 0.6045 0.328 0.000 0.004 0.000 0.668
#> SRR809873 4 0.4799 0.6458 0.000 0.016 0.312 0.656 0.016
#> SRR1341854 2 0.0703 0.8385 0.000 0.976 0.024 0.000 0.000
#> SRR1399335 2 0.3452 0.7166 0.000 0.756 0.244 0.000 0.000
#> SRR1464209 5 0.3521 0.5144 0.012 0.000 0.172 0.008 0.808
#> SRR1389886 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1400730 5 0.3676 0.6428 0.232 0.000 0.004 0.004 0.760
#> SRR1448008 2 0.1059 0.8235 0.000 0.968 0.020 0.008 0.004
#> SRR1087606 5 0.4084 0.6045 0.328 0.000 0.004 0.000 0.668
#> SRR1445111 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR816865 2 0.3022 0.7514 0.000 0.880 0.036 0.064 0.020
#> SRR1323360 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1417364 2 0.2732 0.7916 0.000 0.840 0.160 0.000 0.000
#> SRR1480329 3 0.3813 0.7386 0.000 0.164 0.800 0.008 0.028
#> SRR1403322 4 0.0693 0.5870 0.000 0.000 0.012 0.980 0.008
#> SRR1093625 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.0794 0.8384 0.000 0.972 0.028 0.000 0.000
#> SRR1082035 5 0.5898 0.6193 0.252 0.000 0.140 0.004 0.604
#> SRR1393046 2 0.0162 0.8366 0.000 0.996 0.000 0.000 0.004
#> SRR1466663 2 0.3305 0.7365 0.000 0.776 0.224 0.000 0.000
#> SRR1384456 1 0.0000 0.7508 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.3284 0.73479 0.000 0.784 0.196 0.000 0.000 0.020
#> SRR808862 3 0.4009 0.48903 0.000 0.288 0.684 0.000 0.000 0.028
#> SRR1500382 3 0.3002 0.55288 0.000 0.136 0.836 0.000 0.008 0.020
#> SRR1322683 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1329811 3 0.6011 0.06793 0.000 0.016 0.512 0.000 0.292 0.180
#> SRR1087297 3 0.3791 0.54169 0.000 0.224 0.748 0.008 0.004 0.016
#> SRR1072626 2 0.2301 0.79765 0.000 0.884 0.096 0.000 0.000 0.020
#> SRR1407428 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.2531 0.78050 0.000 0.856 0.132 0.000 0.000 0.012
#> SRR1500282 1 0.3390 0.36357 0.704 0.000 0.000 0.000 0.296 0.000
#> SRR1100496 2 0.4022 0.62351 0.000 0.768 0.024 0.040 0.000 0.168
#> SRR1308778 3 0.4136 0.20655 0.000 0.428 0.560 0.000 0.000 0.012
#> SRR1445304 2 0.0790 0.80725 0.000 0.968 0.000 0.000 0.000 0.032
#> SRR1099378 3 0.4408 0.41647 0.000 0.040 0.784 0.032 0.108 0.036
#> SRR1347412 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.0790 0.81872 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1088365 2 0.0632 0.81005 0.000 0.976 0.000 0.000 0.000 0.024
#> SRR1325752 3 0.2657 0.53750 0.000 0.084 0.880 0.008 0.008 0.020
#> SRR1416713 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1074474 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 2 0.3791 0.68856 0.000 0.732 0.236 0.000 0.000 0.032
#> SRR1400507 2 0.1812 0.80392 0.000 0.912 0.080 0.000 0.000 0.008
#> SRR1378179 3 0.4183 -0.00947 0.000 0.480 0.508 0.000 0.000 0.012
#> SRR1377905 2 0.0937 0.80495 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1089479 5 0.4421 0.45956 0.424 0.000 0.000 0.004 0.552 0.020
#> SRR1073365 2 0.3136 0.74321 0.000 0.796 0.188 0.000 0.000 0.016
#> SRR1500306 3 0.6998 -0.00932 0.000 0.020 0.524 0.092 0.160 0.204
#> SRR1101566 2 0.4002 0.56217 0.000 0.660 0.320 0.000 0.000 0.020
#> SRR1350503 2 0.3916 0.60549 0.000 0.680 0.300 0.000 0.000 0.020
#> SRR1446007 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1102875 2 0.0632 0.81005 0.000 0.976 0.000 0.000 0.000 0.024
#> SRR1380293 3 0.2699 0.55492 0.000 0.108 0.864 0.000 0.008 0.020
#> SRR1331198 2 0.0865 0.81611 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1092686 2 0.3617 0.68370 0.000 0.736 0.244 0.000 0.000 0.020
#> SRR1069421 2 0.3817 0.61364 0.000 0.784 0.012 0.052 0.000 0.152
#> SRR1341650 2 0.3566 0.69246 0.000 0.744 0.236 0.000 0.000 0.020
#> SRR1357276 3 0.2657 0.53750 0.000 0.084 0.880 0.008 0.008 0.020
#> SRR1498374 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1093721 2 0.3934 0.59933 0.000 0.676 0.304 0.000 0.000 0.020
#> SRR1464660 5 0.3163 0.71280 0.232 0.000 0.004 0.000 0.764 0.000
#> SRR1402051 2 0.4621 0.48188 0.000 0.724 0.016 0.112 0.000 0.148
#> SRR1488734 3 0.4183 -0.00947 0.000 0.480 0.508 0.000 0.000 0.012
#> SRR1082616 2 0.4492 0.51033 0.000 0.720 0.016 0.068 0.000 0.196
#> SRR1099427 3 0.2679 0.54955 0.000 0.100 0.872 0.008 0.008 0.012
#> SRR1453093 2 0.1524 0.78530 0.000 0.932 0.008 0.000 0.000 0.060
#> SRR1357064 5 0.3944 0.47344 0.428 0.000 0.004 0.000 0.568 0.000
#> SRR811237 2 0.0937 0.80414 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1100848 2 0.2445 0.79423 0.000 0.872 0.108 0.000 0.000 0.020
#> SRR1346755 2 0.3318 0.74969 0.000 0.796 0.172 0.000 0.000 0.032
#> SRR1472529 2 0.0865 0.81611 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1398905 4 0.5142 0.53710 0.000 0.000 0.028 0.632 0.064 0.276
#> SRR1082733 2 0.0725 0.81507 0.000 0.976 0.012 0.000 0.000 0.012
#> SRR1308035 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1466445 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1359080 2 0.0363 0.81637 0.000 0.988 0.012 0.000 0.000 0.000
#> SRR1455825 2 0.0790 0.81686 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1389300 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR812246 2 0.6522 0.04930 0.000 0.536 0.084 0.160 0.000 0.220
#> SRR1076632 2 0.3688 0.67127 0.000 0.724 0.256 0.000 0.000 0.020
#> SRR1415567 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0790 0.81686 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1452099 2 0.4007 0.72797 0.000 0.760 0.184 0.020 0.000 0.036
#> SRR1352346 1 0.1320 0.83700 0.948 0.000 0.000 0.000 0.016 0.036
#> SRR1364034 2 0.0632 0.81005 0.000 0.976 0.000 0.000 0.000 0.024
#> SRR1086046 2 0.6307 -0.13840 0.000 0.520 0.044 0.168 0.000 0.268
#> SRR1407226 5 0.4390 0.45368 0.004 0.000 0.232 0.000 0.700 0.064
#> SRR1319363 4 0.4061 0.64692 0.000 0.012 0.316 0.664 0.008 0.000
#> SRR1446961 2 0.2877 0.76019 0.000 0.820 0.168 0.000 0.000 0.012
#> SRR1486650 1 0.1320 0.83700 0.948 0.000 0.000 0.000 0.016 0.036
#> SRR1470152 1 0.4333 0.15046 0.596 0.000 0.000 0.000 0.376 0.028
#> SRR1454785 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1092329 2 0.0937 0.80414 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1091476 3 0.4009 0.48903 0.000 0.288 0.684 0.000 0.000 0.028
#> SRR1073775 2 0.0790 0.80720 0.000 0.968 0.000 0.000 0.000 0.032
#> SRR1366873 2 0.0790 0.81686 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1398114 2 0.0909 0.81687 0.000 0.968 0.020 0.000 0.000 0.012
#> SRR1089950 3 0.5612 0.29918 0.000 0.040 0.640 0.008 0.220 0.092
#> SRR1433272 2 0.3771 0.62677 0.000 0.792 0.016 0.048 0.000 0.144
#> SRR1075314 6 0.6605 0.40823 0.000 0.312 0.028 0.268 0.000 0.392
#> SRR1085590 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1100752 2 0.2357 0.78827 0.000 0.872 0.116 0.000 0.000 0.012
#> SRR1391494 2 0.0914 0.81691 0.000 0.968 0.016 0.000 0.000 0.016
#> SRR1333263 2 0.3771 0.62677 0.000 0.792 0.016 0.048 0.000 0.144
#> SRR1310231 3 0.4136 0.20655 0.000 0.428 0.560 0.000 0.000 0.012
#> SRR1094144 2 0.4291 0.58667 0.000 0.748 0.028 0.048 0.000 0.176
#> SRR1092160 2 0.0865 0.81825 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1320300 2 0.0790 0.81686 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1322747 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1432719 2 0.3003 0.75577 0.000 0.812 0.172 0.000 0.000 0.016
#> SRR1100728 2 0.4291 0.58667 0.000 0.748 0.028 0.048 0.000 0.176
#> SRR1087511 2 0.4002 0.56217 0.000 0.660 0.320 0.000 0.000 0.020
#> SRR1470336 6 0.6934 -0.52876 0.356 0.000 0.028 0.032 0.168 0.416
#> SRR1322536 6 0.6605 0.40823 0.000 0.312 0.028 0.268 0.000 0.392
#> SRR1100824 3 0.4731 0.36356 0.000 0.036 0.736 0.032 0.172 0.024
#> SRR1085951 2 0.5285 0.32546 0.000 0.664 0.028 0.140 0.000 0.168
#> SRR1322046 2 0.0790 0.81653 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1316420 5 0.3897 0.70588 0.136 0.000 0.084 0.000 0.776 0.004
#> SRR1070913 2 0.0547 0.81669 0.000 0.980 0.020 0.000 0.000 0.000
#> SRR1345806 2 0.3420 0.69793 0.000 0.748 0.240 0.000 0.000 0.012
#> SRR1313872 2 0.1003 0.81633 0.000 0.964 0.016 0.000 0.000 0.020
#> SRR1337666 2 0.4146 0.60138 0.000 0.676 0.288 0.000 0.000 0.036
#> SRR1076823 4 0.4046 0.63716 0.000 0.000 0.368 0.620 0.008 0.004
#> SRR1093954 2 0.0632 0.81005 0.000 0.976 0.000 0.000 0.000 0.024
#> SRR1451921 2 0.6065 -0.57480 0.000 0.384 0.000 0.352 0.000 0.264
#> SRR1491257 5 0.4365 0.45965 0.000 0.000 0.228 0.004 0.704 0.064
#> SRR1416979 2 0.0937 0.80414 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1419015 3 0.4409 0.30582 0.000 0.072 0.732 0.184 0.008 0.004
#> SRR817649 3 0.2760 0.54651 0.000 0.092 0.872 0.008 0.008 0.020
#> SRR1466376 2 0.1010 0.81679 0.000 0.960 0.036 0.000 0.000 0.004
#> SRR1392055 2 0.3688 0.67019 0.000 0.724 0.256 0.000 0.000 0.020
#> SRR1120913 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1120869 2 0.3711 0.66487 0.000 0.720 0.260 0.000 0.000 0.020
#> SRR1319419 2 0.3376 0.71543 0.000 0.764 0.220 0.000 0.000 0.016
#> SRR816495 2 0.3688 0.67185 0.000 0.724 0.256 0.000 0.000 0.020
#> SRR818694 2 0.1524 0.78530 0.000 0.932 0.008 0.000 0.000 0.060
#> SRR1465653 5 0.3240 0.70368 0.244 0.000 0.004 0.000 0.752 0.000
#> SRR1475952 1 0.6230 0.20020 0.464 0.000 0.008 0.020 0.140 0.368
#> SRR1465040 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1088461 2 0.3200 0.73488 0.000 0.788 0.196 0.000 0.000 0.016
#> SRR810129 2 0.0937 0.80495 0.000 0.960 0.000 0.000 0.000 0.040
#> SRR1400141 2 0.3617 0.68370 0.000 0.736 0.244 0.000 0.000 0.020
#> SRR1349585 5 0.3986 0.39717 0.464 0.000 0.004 0.000 0.532 0.000
#> SRR1437576 2 0.1003 0.81674 0.000 0.964 0.020 0.000 0.000 0.016
#> SRR814407 4 0.5142 0.53710 0.000 0.000 0.028 0.632 0.064 0.276
#> SRR1332403 2 0.0914 0.81547 0.000 0.968 0.016 0.000 0.000 0.016
#> SRR1099598 2 0.4002 0.56217 0.000 0.660 0.320 0.000 0.000 0.020
#> SRR1327723 2 0.3171 0.73337 0.000 0.784 0.204 0.000 0.000 0.012
#> SRR1392525 2 0.4002 0.71060 0.000 0.744 0.188 0.000 0.000 0.068
#> SRR1320536 1 0.0547 0.84758 0.980 0.000 0.000 0.000 0.020 0.000
#> SRR1083824 2 0.2121 0.79884 0.000 0.892 0.096 0.000 0.000 0.012
#> SRR1351390 3 0.6891 0.02749 0.000 0.020 0.536 0.084 0.156 0.204
#> SRR1309141 2 0.3711 0.66487 0.000 0.720 0.260 0.000 0.000 0.020
#> SRR1452803 2 0.3688 0.67019 0.000 0.724 0.256 0.000 0.000 0.020
#> SRR811631 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1485563 2 0.3592 0.68780 0.000 0.740 0.240 0.000 0.000 0.020
#> SRR1311531 2 0.3534 0.69024 0.000 0.740 0.244 0.000 0.000 0.016
#> SRR1353076 2 0.3404 0.71266 0.000 0.760 0.224 0.000 0.000 0.016
#> SRR1480831 2 0.3892 0.71764 0.000 0.752 0.188 0.000 0.000 0.060
#> SRR1083892 5 0.3163 0.71280 0.232 0.000 0.004 0.000 0.764 0.000
#> SRR809873 4 0.4061 0.64692 0.000 0.012 0.316 0.664 0.008 0.000
#> SRR1341854 2 0.0790 0.81653 0.000 0.968 0.032 0.000 0.000 0.000
#> SRR1399335 2 0.3711 0.66487 0.000 0.720 0.260 0.000 0.000 0.020
#> SRR1464209 5 0.3905 0.51425 0.008 0.000 0.136 0.000 0.780 0.076
#> SRR1389886 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1400730 5 0.2504 0.70081 0.136 0.000 0.004 0.000 0.856 0.004
#> SRR1448008 2 0.1524 0.78530 0.000 0.932 0.008 0.000 0.000 0.060
#> SRR1087606 5 0.3163 0.71280 0.232 0.000 0.004 0.000 0.764 0.000
#> SRR1445111 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR816865 2 0.3817 0.61364 0.000 0.784 0.012 0.052 0.000 0.152
#> SRR1323360 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1417364 2 0.2877 0.76019 0.000 0.820 0.168 0.000 0.000 0.012
#> SRR1480329 3 0.2709 0.54008 0.000 0.088 0.876 0.008 0.008 0.020
#> SRR1403322 4 0.0146 0.58352 0.000 0.000 0.000 0.996 0.000 0.004
#> SRR1093625 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.0865 0.81611 0.000 0.964 0.036 0.000 0.000 0.000
#> SRR1082035 5 0.4799 0.67257 0.172 0.000 0.140 0.000 0.684 0.004
#> SRR1393046 2 0.0713 0.80893 0.000 0.972 0.000 0.000 0.000 0.028
#> SRR1466663 2 0.3592 0.68780 0.000 0.740 0.240 0.000 0.000 0.020
#> SRR1384456 1 0.0000 0.86086 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "kmeans"]
# you can also extract it by
# res = res_list["ATC:kmeans"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 0.982 0.993 0.3260 0.676 0.676
#> 3 3 0.652 0.770 0.903 0.7472 0.710 0.584
#> 4 4 0.719 0.754 0.875 0.1987 0.785 0.549
#> 5 5 0.798 0.778 0.881 0.0749 0.925 0.774
#> 6 6 0.682 0.636 0.809 0.0625 0.933 0.767
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
#> SRR810713 2 0.000 0.995 0.000 1.000
#> SRR808862 2 0.000 0.995 0.000 1.000
#> SRR1500382 2 0.000 0.995 0.000 1.000
#> SRR1322683 2 0.000 0.995 0.000 1.000
#> SRR1329811 2 0.969 0.335 0.396 0.604
#> SRR1087297 2 0.000 0.995 0.000 1.000
#> SRR1072626 2 0.000 0.995 0.000 1.000
#> SRR1407428 1 0.000 0.986 1.000 0.000
#> SRR1321029 2 0.000 0.995 0.000 1.000
#> SRR1500282 1 0.000 0.986 1.000 0.000
#> SRR1100496 2 0.000 0.995 0.000 1.000
#> SRR1308778 2 0.000 0.995 0.000 1.000
#> SRR1445304 2 0.000 0.995 0.000 1.000
#> SRR1099378 2 0.000 0.995 0.000 1.000
#> SRR1347412 1 0.000 0.986 1.000 0.000
#> SRR1099694 2 0.000 0.995 0.000 1.000
#> SRR1088365 2 0.000 0.995 0.000 1.000
#> SRR1325752 2 0.000 0.995 0.000 1.000
#> SRR1416713 2 0.000 0.995 0.000 1.000
#> SRR1074474 1 0.000 0.986 1.000 0.000
#> SRR1469369 2 0.000 0.995 0.000 1.000
#> SRR1400507 2 0.000 0.995 0.000 1.000
#> SRR1378179 2 0.000 0.995 0.000 1.000
#> SRR1377905 2 0.000 0.995 0.000 1.000
#> SRR1089479 1 0.000 0.986 1.000 0.000
#> SRR1073365 2 0.000 0.995 0.000 1.000
#> SRR1500306 2 0.706 0.759 0.192 0.808
#> SRR1101566 2 0.000 0.995 0.000 1.000
#> SRR1350503 2 0.000 0.995 0.000 1.000
#> SRR1446007 2 0.000 0.995 0.000 1.000
#> SRR1102875 2 0.000 0.995 0.000 1.000
#> SRR1380293 2 0.000 0.995 0.000 1.000
#> SRR1331198 2 0.000 0.995 0.000 1.000
#> SRR1092686 2 0.000 0.995 0.000 1.000
#> SRR1069421 2 0.000 0.995 0.000 1.000
#> SRR1341650 2 0.000 0.995 0.000 1.000
#> SRR1357276 1 0.980 0.277 0.584 0.416
#> SRR1498374 2 0.000 0.995 0.000 1.000
#> SRR1093721 2 0.000 0.995 0.000 1.000
#> SRR1464660 1 0.000 0.986 1.000 0.000
#> SRR1402051 2 0.000 0.995 0.000 1.000
#> SRR1488734 2 0.000 0.995 0.000 1.000
#> SRR1082616 2 0.000 0.995 0.000 1.000
#> SRR1099427 2 0.000 0.995 0.000 1.000
#> SRR1453093 2 0.000 0.995 0.000 1.000
#> SRR1357064 1 0.000 0.986 1.000 0.000
#> SRR811237 2 0.000 0.995 0.000 1.000
#> SRR1100848 2 0.000 0.995 0.000 1.000
#> SRR1346755 2 0.000 0.995 0.000 1.000
#> SRR1472529 2 0.000 0.995 0.000 1.000
#> SRR1398905 1 0.000 0.986 1.000 0.000
#> SRR1082733 2 0.000 0.995 0.000 1.000
#> SRR1308035 2 0.000 0.995 0.000 1.000
#> SRR1466445 2 0.000 0.995 0.000 1.000
#> SRR1359080 2 0.000 0.995 0.000 1.000
#> SRR1455825 2 0.000 0.995 0.000 1.000
#> SRR1389300 2 0.000 0.995 0.000 1.000
#> SRR812246 2 0.000 0.995 0.000 1.000
#> SRR1076632 2 0.000 0.995 0.000 1.000
#> SRR1415567 1 0.000 0.986 1.000 0.000
#> SRR1331900 2 0.000 0.995 0.000 1.000
#> SRR1452099 2 0.000 0.995 0.000 1.000
#> SRR1352346 1 0.000 0.986 1.000 0.000
#> SRR1364034 2 0.000 0.995 0.000 1.000
#> SRR1086046 2 0.000 0.995 0.000 1.000
#> SRR1407226 1 0.000 0.986 1.000 0.000
#> SRR1319363 2 0.000 0.995 0.000 1.000
#> SRR1446961 2 0.000 0.995 0.000 1.000
#> SRR1486650 1 0.000 0.986 1.000 0.000
#> SRR1470152 1 0.000 0.986 1.000 0.000
#> SRR1454785 2 0.000 0.995 0.000 1.000
#> SRR1092329 2 0.000 0.995 0.000 1.000
#> SRR1091476 2 0.000 0.995 0.000 1.000
#> SRR1073775 2 0.000 0.995 0.000 1.000
#> SRR1366873 2 0.000 0.995 0.000 1.000
#> SRR1398114 2 0.000 0.995 0.000 1.000
#> SRR1089950 1 0.000 0.986 1.000 0.000
#> SRR1433272 2 0.000 0.995 0.000 1.000
#> SRR1075314 2 0.000 0.995 0.000 1.000
#> SRR1085590 2 0.000 0.995 0.000 1.000
#> SRR1100752 2 0.000 0.995 0.000 1.000
#> SRR1391494 2 0.000 0.995 0.000 1.000
#> SRR1333263 2 0.000 0.995 0.000 1.000
#> SRR1310231 2 0.000 0.995 0.000 1.000
#> SRR1094144 2 0.000 0.995 0.000 1.000
#> SRR1092160 2 0.000 0.995 0.000 1.000
#> SRR1320300 2 0.000 0.995 0.000 1.000
#> SRR1322747 2 0.000 0.995 0.000 1.000
#> SRR1432719 2 0.000 0.995 0.000 1.000
#> SRR1100728 2 0.000 0.995 0.000 1.000
#> SRR1087511 2 0.000 0.995 0.000 1.000
#> SRR1470336 1 0.000 0.986 1.000 0.000
#> SRR1322536 2 0.000 0.995 0.000 1.000
#> SRR1100824 1 0.000 0.986 1.000 0.000
#> SRR1085951 2 0.000 0.995 0.000 1.000
#> SRR1322046 2 0.000 0.995 0.000 1.000
#> SRR1316420 1 0.000 0.986 1.000 0.000
#> SRR1070913 2 0.000 0.995 0.000 1.000
#> SRR1345806 2 0.000 0.995 0.000 1.000
#> SRR1313872 2 0.000 0.995 0.000 1.000
#> SRR1337666 2 0.000 0.995 0.000 1.000
#> SRR1076823 2 0.000 0.995 0.000 1.000
#> SRR1093954 2 0.000 0.995 0.000 1.000
#> SRR1451921 2 0.000 0.995 0.000 1.000
#> SRR1491257 1 0.000 0.986 1.000 0.000
#> SRR1416979 2 0.000 0.995 0.000 1.000
#> SRR1419015 2 0.000 0.995 0.000 1.000
#> SRR817649 2 0.000 0.995 0.000 1.000
#> SRR1466376 2 0.000 0.995 0.000 1.000
#> SRR1392055 2 0.000 0.995 0.000 1.000
#> SRR1120913 2 0.000 0.995 0.000 1.000
#> SRR1120869 2 0.000 0.995 0.000 1.000
#> SRR1319419 2 0.000 0.995 0.000 1.000
#> SRR816495 2 0.000 0.995 0.000 1.000
#> SRR818694 2 0.000 0.995 0.000 1.000
#> SRR1465653 1 0.000 0.986 1.000 0.000
#> SRR1475952 1 0.000 0.986 1.000 0.000
#> SRR1465040 2 0.000 0.995 0.000 1.000
#> SRR1088461 2 0.000 0.995 0.000 1.000
#> SRR810129 2 0.000 0.995 0.000 1.000
#> SRR1400141 2 0.000 0.995 0.000 1.000
#> SRR1349585 1 0.000 0.986 1.000 0.000
#> SRR1437576 2 0.000 0.995 0.000 1.000
#> SRR814407 1 0.000 0.986 1.000 0.000
#> SRR1332403 2 0.000 0.995 0.000 1.000
#> SRR1099598 2 0.000 0.995 0.000 1.000
#> SRR1327723 2 0.000 0.995 0.000 1.000
#> SRR1392525 2 0.000 0.995 0.000 1.000
#> SRR1320536 1 0.000 0.986 1.000 0.000
#> SRR1083824 2 0.000 0.995 0.000 1.000
#> SRR1351390 2 0.000 0.995 0.000 1.000
#> SRR1309141 2 0.000 0.995 0.000 1.000
#> SRR1452803 2 0.000 0.995 0.000 1.000
#> SRR811631 2 0.000 0.995 0.000 1.000
#> SRR1485563 2 0.000 0.995 0.000 1.000
#> SRR1311531 2 0.000 0.995 0.000 1.000
#> SRR1353076 2 0.000 0.995 0.000 1.000
#> SRR1480831 2 0.000 0.995 0.000 1.000
#> SRR1083892 1 0.000 0.986 1.000 0.000
#> SRR809873 2 0.000 0.995 0.000 1.000
#> SRR1341854 2 0.000 0.995 0.000 1.000
#> SRR1399335 2 0.000 0.995 0.000 1.000
#> SRR1464209 1 0.000 0.986 1.000 0.000
#> SRR1389886 2 0.000 0.995 0.000 1.000
#> SRR1400730 1 0.000 0.986 1.000 0.000
#> SRR1448008 2 0.000 0.995 0.000 1.000
#> SRR1087606 1 0.000 0.986 1.000 0.000
#> SRR1445111 1 0.000 0.986 1.000 0.000
#> SRR816865 2 0.000 0.995 0.000 1.000
#> SRR1323360 2 0.000 0.995 0.000 1.000
#> SRR1417364 2 0.000 0.995 0.000 1.000
#> SRR1480329 2 0.000 0.995 0.000 1.000
#> SRR1403322 2 0.430 0.900 0.088 0.912
#> SRR1093625 1 0.000 0.986 1.000 0.000
#> SRR1479977 2 0.000 0.995 0.000 1.000
#> SRR1082035 1 0.000 0.986 1.000 0.000
#> SRR1393046 2 0.000 0.995 0.000 1.000
#> SRR1466663 2 0.000 0.995 0.000 1.000
#> SRR1384456 1 0.000 0.986 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.4931 0.6359 0.000 0.768 0.232
#> SRR808862 3 0.2448 0.7682 0.000 0.076 0.924
#> SRR1500382 3 0.4235 0.7598 0.000 0.176 0.824
#> SRR1322683 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1329811 3 0.0475 0.7471 0.004 0.004 0.992
#> SRR1087297 3 0.3267 0.7729 0.000 0.116 0.884
#> SRR1072626 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1407428 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1321029 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1500282 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1100496 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1308778 3 0.3267 0.7729 0.000 0.116 0.884
#> SRR1445304 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1099378 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1347412 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1099694 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1088365 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1325752 3 0.0424 0.7495 0.000 0.008 0.992
#> SRR1416713 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1469369 3 0.6126 0.4461 0.000 0.400 0.600
#> SRR1400507 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1378179 3 0.6111 0.4558 0.000 0.396 0.604
#> SRR1377905 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1089479 1 0.0237 0.9665 0.996 0.000 0.004
#> SRR1073365 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1500306 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1101566 3 0.6168 0.4076 0.000 0.412 0.588
#> SRR1350503 3 0.6095 0.4646 0.000 0.392 0.608
#> SRR1446007 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1102875 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1380293 3 0.3551 0.7713 0.000 0.132 0.868
#> SRR1331198 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1092686 2 0.6168 0.2234 0.000 0.588 0.412
#> SRR1069421 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1341650 3 0.6154 0.3874 0.000 0.408 0.592
#> SRR1357276 3 0.1753 0.7607 0.000 0.048 0.952
#> SRR1498374 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1093721 3 0.6111 0.4558 0.000 0.396 0.604
#> SRR1464660 1 0.2878 0.9307 0.904 0.000 0.096
#> SRR1402051 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1488734 3 0.4750 0.7337 0.000 0.216 0.784
#> SRR1082616 2 0.2066 0.8504 0.000 0.940 0.060
#> SRR1099427 3 0.3619 0.7713 0.000 0.136 0.864
#> SRR1453093 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1357064 1 0.0237 0.9665 0.996 0.000 0.004
#> SRR811237 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1100848 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1346755 2 0.1031 0.8828 0.000 0.976 0.024
#> SRR1472529 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1398905 3 0.5621 0.2719 0.308 0.000 0.692
#> SRR1082733 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1308035 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1466445 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1359080 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR812246 3 0.3038 0.7699 0.000 0.104 0.896
#> SRR1076632 3 0.3879 0.7677 0.000 0.152 0.848
#> SRR1415567 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1452099 2 0.3267 0.8057 0.000 0.884 0.116
#> SRR1352346 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1364034 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1086046 2 0.5650 0.5314 0.000 0.688 0.312
#> SRR1407226 3 0.5905 0.1833 0.352 0.000 0.648
#> SRR1319363 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1446961 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1486650 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1454785 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1092329 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1091476 3 0.0592 0.7517 0.000 0.012 0.988
#> SRR1073775 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1398114 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1089950 3 0.0424 0.7438 0.008 0.000 0.992
#> SRR1433272 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1075314 2 0.2066 0.8504 0.000 0.940 0.060
#> SRR1085590 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1100752 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1391494 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1333263 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1310231 3 0.4702 0.7377 0.000 0.212 0.788
#> SRR1094144 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1092160 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1320300 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1322747 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1432719 2 0.5591 0.5118 0.000 0.696 0.304
#> SRR1100728 2 0.1031 0.8879 0.000 0.976 0.024
#> SRR1087511 2 0.6305 -0.0534 0.000 0.516 0.484
#> SRR1470336 1 0.3038 0.9249 0.896 0.000 0.104
#> SRR1322536 2 0.5760 0.4944 0.000 0.672 0.328
#> SRR1100824 3 0.0424 0.7438 0.008 0.000 0.992
#> SRR1085951 2 0.2066 0.8504 0.000 0.940 0.060
#> SRR1322046 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1316420 1 0.2878 0.9307 0.904 0.000 0.096
#> SRR1070913 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1345806 2 0.5529 0.5278 0.000 0.704 0.296
#> SRR1313872 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1337666 3 0.6154 0.4304 0.000 0.408 0.592
#> SRR1076823 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1093954 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1451921 2 0.5431 0.5815 0.000 0.716 0.284
#> SRR1491257 3 0.6045 0.1253 0.380 0.000 0.620
#> SRR1416979 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1419015 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR817649 3 0.1753 0.7607 0.000 0.048 0.952
#> SRR1466376 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1392055 2 0.5650 0.4946 0.000 0.688 0.312
#> SRR1120913 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1120869 2 0.6252 0.1073 0.000 0.556 0.444
#> SRR1319419 2 0.6260 0.0917 0.000 0.552 0.448
#> SRR816495 2 0.5560 0.5197 0.000 0.700 0.300
#> SRR818694 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1465653 1 0.0237 0.9665 0.996 0.000 0.004
#> SRR1475952 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1465040 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1088461 2 0.5760 0.4604 0.000 0.672 0.328
#> SRR810129 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1400141 3 0.4605 0.7434 0.000 0.204 0.796
#> SRR1349585 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1437576 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR814407 1 0.4504 0.8382 0.804 0.000 0.196
#> SRR1332403 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1099598 2 0.6291 0.0187 0.000 0.532 0.468
#> SRR1327723 2 0.2959 0.8093 0.000 0.900 0.100
#> SRR1392525 2 0.6168 0.2352 0.000 0.588 0.412
#> SRR1320536 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1083824 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1351390 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1309141 3 0.5859 0.5574 0.000 0.344 0.656
#> SRR1452803 2 0.5733 0.4674 0.000 0.676 0.324
#> SRR811631 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1485563 3 0.4750 0.7322 0.000 0.216 0.784
#> SRR1311531 2 0.5591 0.5118 0.000 0.696 0.304
#> SRR1353076 2 0.6307 -0.0833 0.000 0.512 0.488
#> SRR1480831 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1083892 1 0.2796 0.9328 0.908 0.000 0.092
#> SRR809873 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1341854 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1399335 3 0.6192 0.3919 0.000 0.420 0.580
#> SRR1464209 3 0.5988 0.1388 0.368 0.000 0.632
#> SRR1389886 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1400730 1 0.2878 0.9307 0.904 0.000 0.096
#> SRR1448008 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1087606 1 0.2796 0.9328 0.908 0.000 0.092
#> SRR1445111 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR816865 2 0.0424 0.8958 0.000 0.992 0.008
#> SRR1323360 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1417364 2 0.5529 0.5276 0.000 0.704 0.296
#> SRR1480329 3 0.0424 0.7495 0.000 0.008 0.992
#> SRR1403322 3 0.0000 0.7471 0.000 0.000 1.000
#> SRR1093625 1 0.0000 0.9672 1.000 0.000 0.000
#> SRR1479977 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1082035 1 0.2878 0.9307 0.904 0.000 0.096
#> SRR1393046 2 0.0000 0.8997 0.000 1.000 0.000
#> SRR1466663 3 0.4399 0.7560 0.000 0.188 0.812
#> SRR1384456 1 0.0000 0.9672 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 3 0.2011 0.8472 0.000 0.080 0.920 0.000
#> SRR808862 3 0.5766 0.1183 0.000 0.032 0.564 0.404
#> SRR1500382 3 0.3342 0.7748 0.000 0.032 0.868 0.100
#> SRR1322683 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1329811 4 0.3172 0.6996 0.000 0.000 0.160 0.840
#> SRR1087297 3 0.1833 0.8428 0.000 0.032 0.944 0.024
#> SRR1072626 2 0.4372 0.6598 0.000 0.728 0.268 0.004
#> SRR1407428 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1321029 3 0.4713 0.4096 0.000 0.360 0.640 0.000
#> SRR1500282 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1100496 2 0.0895 0.8801 0.000 0.976 0.004 0.020
#> SRR1308778 3 0.3523 0.7612 0.000 0.032 0.856 0.112
#> SRR1445304 2 0.0921 0.9010 0.000 0.972 0.028 0.000
#> SRR1099378 4 0.4222 0.6744 0.000 0.000 0.272 0.728
#> SRR1347412 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1099694 2 0.0921 0.9010 0.000 0.972 0.028 0.000
#> SRR1088365 2 0.0707 0.8993 0.000 0.980 0.020 0.000
#> SRR1325752 3 0.4866 0.0665 0.000 0.000 0.596 0.404
#> SRR1416713 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1074474 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1469369 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1400507 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1378179 3 0.1489 0.8640 0.000 0.044 0.952 0.004
#> SRR1377905 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1089479 1 0.3688 0.7607 0.792 0.000 0.000 0.208
#> SRR1073365 2 0.3801 0.7435 0.000 0.780 0.220 0.000
#> SRR1500306 4 0.1474 0.6842 0.000 0.000 0.052 0.948
#> SRR1101566 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1350503 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1446007 2 0.0921 0.9010 0.000 0.972 0.028 0.000
#> SRR1102875 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1380293 3 0.3958 0.7193 0.000 0.032 0.824 0.144
#> SRR1331198 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1092686 3 0.1474 0.8632 0.000 0.052 0.948 0.000
#> SRR1069421 2 0.0779 0.8824 0.000 0.980 0.004 0.016
#> SRR1341650 3 0.2300 0.8468 0.000 0.048 0.924 0.028
#> SRR1357276 3 0.4941 0.0174 0.000 0.000 0.564 0.436
#> SRR1498374 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1093721 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1464660 1 0.5143 0.6015 0.628 0.000 0.012 0.360
#> SRR1402051 2 0.0779 0.8824 0.000 0.980 0.004 0.016
#> SRR1488734 3 0.1489 0.8640 0.000 0.044 0.952 0.004
#> SRR1082616 2 0.4500 0.6684 0.000 0.776 0.032 0.192
#> SRR1099427 3 0.2021 0.8507 0.000 0.040 0.936 0.024
#> SRR1453093 2 0.0779 0.8824 0.000 0.980 0.004 0.016
#> SRR1357064 1 0.3937 0.7676 0.800 0.000 0.012 0.188
#> SRR811237 2 0.0779 0.8824 0.000 0.980 0.004 0.016
#> SRR1100848 2 0.4509 0.5859 0.000 0.708 0.288 0.004
#> SRR1346755 2 0.4981 0.2069 0.000 0.536 0.464 0.000
#> SRR1472529 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1398905 4 0.1576 0.6825 0.004 0.000 0.048 0.948
#> SRR1082733 2 0.2149 0.8781 0.000 0.912 0.088 0.000
#> SRR1308035 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1466445 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1455825 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1389300 2 0.0921 0.9010 0.000 0.972 0.028 0.000
#> SRR812246 3 0.1510 0.8275 0.000 0.016 0.956 0.028
#> SRR1076632 3 0.2021 0.8507 0.000 0.040 0.936 0.024
#> SRR1415567 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1331900 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1452099 2 0.5564 0.1722 0.000 0.544 0.436 0.020
#> SRR1352346 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1364034 2 0.1022 0.9012 0.000 0.968 0.032 0.000
#> SRR1086046 3 0.7558 0.1468 0.000 0.256 0.488 0.256
#> SRR1407226 4 0.4578 0.5778 0.160 0.000 0.052 0.788
#> SRR1319363 4 0.3764 0.6865 0.000 0.000 0.216 0.784
#> SRR1446961 3 0.3610 0.6958 0.000 0.200 0.800 0.000
#> SRR1486650 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.0592 0.8496 0.984 0.000 0.000 0.016
#> SRR1454785 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1092329 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1091476 3 0.1624 0.8232 0.000 0.020 0.952 0.028
#> SRR1073775 2 0.0921 0.9010 0.000 0.972 0.028 0.000
#> SRR1366873 2 0.2345 0.8669 0.000 0.900 0.100 0.000
#> SRR1398114 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1089950 4 0.3024 0.7018 0.000 0.000 0.148 0.852
#> SRR1433272 2 0.1059 0.8848 0.000 0.972 0.012 0.016
#> SRR1075314 2 0.5055 0.5670 0.000 0.712 0.032 0.256
#> SRR1085590 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1100752 2 0.4661 0.5274 0.000 0.652 0.348 0.000
#> SRR1391494 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1333263 2 0.0469 0.8872 0.000 0.988 0.000 0.012
#> SRR1310231 3 0.1888 0.8588 0.000 0.044 0.940 0.016
#> SRR1094144 2 0.5173 0.4976 0.000 0.660 0.320 0.020
#> SRR1092160 2 0.4790 0.4514 0.000 0.620 0.380 0.000
#> SRR1320300 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1322747 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1432719 3 0.1792 0.8556 0.000 0.068 0.932 0.000
#> SRR1100728 2 0.5581 0.1179 0.000 0.532 0.448 0.020
#> SRR1087511 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1470336 4 0.5407 -0.3160 0.484 0.000 0.012 0.504
#> SRR1322536 4 0.7769 0.2347 0.000 0.272 0.296 0.432
#> SRR1100824 4 0.3123 0.6995 0.000 0.000 0.156 0.844
#> SRR1085951 2 0.4500 0.6684 0.000 0.776 0.032 0.192
#> SRR1322046 2 0.2973 0.8307 0.000 0.856 0.144 0.000
#> SRR1316420 1 0.5143 0.6015 0.628 0.000 0.012 0.360
#> SRR1070913 2 0.1022 0.9012 0.000 0.968 0.032 0.000
#> SRR1345806 3 0.1867 0.8528 0.000 0.072 0.928 0.000
#> SRR1313872 2 0.1211 0.9009 0.000 0.960 0.040 0.000
#> SRR1337666 3 0.1557 0.8616 0.000 0.056 0.944 0.000
#> SRR1076823 4 0.3726 0.6884 0.000 0.000 0.212 0.788
#> SRR1093954 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1451921 3 0.7726 0.0722 0.000 0.296 0.444 0.260
#> SRR1491257 4 0.5109 0.4995 0.212 0.000 0.052 0.736
#> SRR1416979 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1419015 4 0.4996 0.3074 0.000 0.000 0.484 0.516
#> SRR817649 3 0.3743 0.6886 0.000 0.016 0.824 0.160
#> SRR1466376 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1392055 3 0.1637 0.8598 0.000 0.060 0.940 0.000
#> SRR1120913 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1120869 3 0.1576 0.8641 0.000 0.048 0.948 0.004
#> SRR1319419 3 0.1474 0.8632 0.000 0.052 0.948 0.000
#> SRR816495 3 0.1792 0.8556 0.000 0.068 0.932 0.000
#> SRR818694 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1465653 1 0.3625 0.7839 0.828 0.000 0.012 0.160
#> SRR1475952 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1465040 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1088461 3 0.1940 0.8496 0.000 0.076 0.924 0.000
#> SRR810129 2 0.0000 0.8921 0.000 1.000 0.000 0.000
#> SRR1400141 3 0.1767 0.8609 0.000 0.044 0.944 0.012
#> SRR1349585 1 0.0188 0.8531 0.996 0.000 0.000 0.004
#> SRR1437576 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR814407 4 0.3958 0.5399 0.160 0.000 0.024 0.816
#> SRR1332403 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1099598 3 0.1389 0.8640 0.000 0.048 0.952 0.000
#> SRR1327723 3 0.2530 0.8141 0.000 0.112 0.888 0.000
#> SRR1392525 3 0.2197 0.8553 0.000 0.048 0.928 0.024
#> SRR1320536 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1083824 3 0.4543 0.5027 0.000 0.324 0.676 0.000
#> SRR1351390 4 0.1557 0.6858 0.000 0.000 0.056 0.944
#> SRR1309141 3 0.1489 0.8640 0.000 0.044 0.952 0.004
#> SRR1452803 3 0.1716 0.8579 0.000 0.064 0.936 0.000
#> SRR811631 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1485563 3 0.1798 0.8566 0.000 0.040 0.944 0.016
#> SRR1311531 3 0.1792 0.8556 0.000 0.068 0.932 0.000
#> SRR1353076 3 0.1489 0.8640 0.000 0.044 0.952 0.004
#> SRR1480831 2 0.4608 0.6104 0.000 0.692 0.304 0.004
#> SRR1083892 1 0.5143 0.6015 0.628 0.000 0.012 0.360
#> SRR809873 4 0.4382 0.5833 0.000 0.000 0.296 0.704
#> SRR1341854 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1399335 3 0.1302 0.8642 0.000 0.044 0.956 0.000
#> SRR1464209 4 0.4552 0.5615 0.172 0.000 0.044 0.784
#> SRR1389886 2 0.0817 0.9002 0.000 0.976 0.024 0.000
#> SRR1400730 1 0.5143 0.6015 0.628 0.000 0.012 0.360
#> SRR1448008 2 0.0524 0.8866 0.000 0.988 0.004 0.008
#> SRR1087606 1 0.5143 0.6015 0.628 0.000 0.012 0.360
#> SRR1445111 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR816865 2 0.0779 0.8824 0.000 0.980 0.004 0.016
#> SRR1323360 2 0.1474 0.8996 0.000 0.948 0.052 0.000
#> SRR1417364 3 0.2149 0.8384 0.000 0.088 0.912 0.000
#> SRR1480329 3 0.4888 0.0385 0.000 0.000 0.588 0.412
#> SRR1403322 4 0.3356 0.6954 0.000 0.000 0.176 0.824
#> SRR1093625 1 0.0000 0.8540 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.4008 0.7145 0.000 0.756 0.244 0.000
#> SRR1082035 1 0.5189 0.5800 0.616 0.000 0.012 0.372
#> SRR1393046 2 0.1022 0.9012 0.000 0.968 0.032 0.000
#> SRR1466663 3 0.2002 0.8564 0.000 0.044 0.936 0.020
#> SRR1384456 1 0.0000 0.8540 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 3 0.2036 0.8601 0.000 0.056 0.920 0.024 0.000
#> SRR808862 4 0.2536 0.6047 0.000 0.000 0.128 0.868 0.004
#> SRR1500382 3 0.2819 0.8335 0.000 0.004 0.884 0.052 0.060
#> SRR1322683 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR1329811 5 0.2139 0.7128 0.000 0.000 0.032 0.052 0.916
#> SRR1087297 3 0.0671 0.8884 0.000 0.000 0.980 0.016 0.004
#> SRR1072626 2 0.4883 0.7012 0.000 0.752 0.100 0.128 0.020
#> SRR1407428 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.4292 0.5026 0.000 0.272 0.704 0.024 0.000
#> SRR1500282 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1100496 2 0.4973 0.2881 0.000 0.592 0.004 0.376 0.028
#> SRR1308778 3 0.2729 0.8265 0.000 0.000 0.884 0.060 0.056
#> SRR1445304 2 0.0162 0.9153 0.000 0.996 0.000 0.000 0.004
#> SRR1099378 5 0.6160 0.1492 0.000 0.000 0.132 0.420 0.448
#> SRR1347412 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.0451 0.9162 0.000 0.988 0.000 0.008 0.004
#> SRR1088365 2 0.1082 0.9079 0.000 0.964 0.000 0.008 0.028
#> SRR1325752 3 0.4734 0.6563 0.000 0.000 0.728 0.096 0.176
#> SRR1416713 2 0.0000 0.9156 0.000 1.000 0.000 0.000 0.000
#> SRR1074474 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.0960 0.8912 0.000 0.008 0.972 0.016 0.004
#> SRR1400507 2 0.0992 0.9078 0.000 0.968 0.008 0.024 0.000
#> SRR1378179 3 0.0727 0.8922 0.000 0.004 0.980 0.004 0.012
#> SRR1377905 2 0.0898 0.9077 0.000 0.972 0.000 0.008 0.020
#> SRR1089479 5 0.3452 0.6595 0.244 0.000 0.000 0.000 0.756
#> SRR1073365 2 0.2521 0.8517 0.000 0.900 0.068 0.024 0.008
#> SRR1500306 5 0.4497 0.3716 0.000 0.000 0.008 0.424 0.568
#> SRR1101566 3 0.0162 0.8919 0.000 0.000 0.996 0.004 0.000
#> SRR1350503 3 0.0932 0.8908 0.000 0.004 0.972 0.020 0.004
#> SRR1446007 2 0.0162 0.9156 0.000 0.996 0.000 0.004 0.000
#> SRR1102875 2 0.0000 0.9156 0.000 1.000 0.000 0.000 0.000
#> SRR1380293 3 0.3268 0.8091 0.000 0.004 0.856 0.060 0.080
#> SRR1331198 2 0.0771 0.9108 0.000 0.976 0.004 0.020 0.000
#> SRR1092686 3 0.0613 0.8915 0.000 0.004 0.984 0.004 0.008
#> SRR1069421 2 0.3789 0.7006 0.000 0.768 0.000 0.212 0.020
#> SRR1341650 3 0.4522 0.1580 0.000 0.000 0.552 0.440 0.008
#> SRR1357276 3 0.4806 0.6066 0.000 0.000 0.688 0.060 0.252
#> SRR1498374 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR1093721 3 0.0566 0.8923 0.000 0.004 0.984 0.012 0.000
#> SRR1464660 5 0.3143 0.7050 0.204 0.000 0.000 0.000 0.796
#> SRR1402051 2 0.3586 0.7360 0.000 0.792 0.000 0.188 0.020
#> SRR1488734 3 0.0727 0.8911 0.000 0.004 0.980 0.012 0.004
#> SRR1082616 4 0.3880 0.5881 0.000 0.204 0.004 0.772 0.020
#> SRR1099427 3 0.0671 0.8895 0.000 0.000 0.980 0.016 0.004
#> SRR1453093 2 0.1800 0.8834 0.000 0.932 0.000 0.048 0.020
#> SRR1357064 5 0.3452 0.6595 0.244 0.000 0.000 0.000 0.756
#> SRR811237 2 0.1800 0.8834 0.000 0.932 0.000 0.048 0.020
#> SRR1100848 2 0.5814 0.5890 0.000 0.672 0.140 0.160 0.028
#> SRR1346755 2 0.5009 0.1972 0.000 0.540 0.428 0.032 0.000
#> SRR1472529 2 0.0771 0.9108 0.000 0.976 0.004 0.020 0.000
#> SRR1398905 5 0.4390 0.3748 0.000 0.000 0.004 0.428 0.568
#> SRR1082733 2 0.1306 0.9042 0.000 0.960 0.016 0.016 0.008
#> SRR1308035 2 0.0162 0.9156 0.000 0.996 0.000 0.004 0.000
#> SRR1466445 2 0.1310 0.9018 0.000 0.956 0.000 0.024 0.020
#> SRR1359080 2 0.0771 0.9108 0.000 0.976 0.004 0.020 0.000
#> SRR1455825 2 0.0671 0.9121 0.000 0.980 0.004 0.016 0.000
#> SRR1389300 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR812246 3 0.0290 0.8911 0.000 0.000 0.992 0.008 0.000
#> SRR1076632 3 0.0798 0.8901 0.000 0.000 0.976 0.016 0.008
#> SRR1415567 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0671 0.9121 0.000 0.980 0.004 0.016 0.000
#> SRR1452099 4 0.6914 0.4817 0.000 0.296 0.176 0.500 0.028
#> SRR1352346 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1364034 2 0.0404 0.9153 0.000 0.988 0.000 0.000 0.012
#> SRR1086046 4 0.2771 0.6133 0.000 0.012 0.128 0.860 0.000
#> SRR1407226 5 0.2067 0.7248 0.032 0.000 0.000 0.048 0.920
#> SRR1319363 4 0.3988 0.4563 0.000 0.000 0.036 0.768 0.196
#> SRR1446961 3 0.2104 0.8563 0.000 0.060 0.916 0.024 0.000
#> SRR1486650 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 1 0.4045 0.4080 0.644 0.000 0.000 0.000 0.356
#> SRR1454785 2 0.0162 0.9156 0.000 0.996 0.004 0.000 0.000
#> SRR1092329 2 0.1399 0.8964 0.000 0.952 0.000 0.028 0.020
#> SRR1091476 3 0.0404 0.8905 0.000 0.000 0.988 0.012 0.000
#> SRR1073775 2 0.0000 0.9156 0.000 1.000 0.000 0.000 0.000
#> SRR1366873 2 0.1012 0.9069 0.000 0.968 0.012 0.020 0.000
#> SRR1398114 2 0.0854 0.9126 0.000 0.976 0.004 0.012 0.008
#> SRR1089950 5 0.2628 0.7011 0.000 0.000 0.028 0.088 0.884
#> SRR1433272 2 0.3964 0.7601 0.000 0.788 0.016 0.176 0.020
#> SRR1075314 4 0.2516 0.6074 0.000 0.140 0.000 0.860 0.000
#> SRR1085590 2 0.0898 0.9082 0.000 0.972 0.000 0.008 0.020
#> SRR1100752 2 0.4141 0.5883 0.000 0.728 0.248 0.024 0.000
#> SRR1391494 2 0.0771 0.9117 0.000 0.976 0.004 0.020 0.000
#> SRR1333263 2 0.2773 0.8286 0.000 0.868 0.000 0.112 0.020
#> SRR1310231 3 0.0833 0.8900 0.000 0.004 0.976 0.016 0.004
#> SRR1094144 4 0.6884 0.3561 0.000 0.364 0.148 0.460 0.028
#> SRR1092160 2 0.4315 0.5365 0.000 0.700 0.276 0.024 0.000
#> SRR1320300 2 0.0324 0.9152 0.000 0.992 0.004 0.004 0.000
#> SRR1322747 2 0.0000 0.9156 0.000 1.000 0.000 0.000 0.000
#> SRR1432719 3 0.1661 0.8747 0.000 0.036 0.940 0.024 0.000
#> SRR1100728 4 0.6947 0.3794 0.000 0.352 0.160 0.460 0.028
#> SRR1087511 3 0.0451 0.8911 0.000 0.000 0.988 0.004 0.008
#> SRR1470336 5 0.3086 0.7144 0.180 0.000 0.000 0.004 0.816
#> SRR1322536 4 0.2228 0.6139 0.000 0.004 0.076 0.908 0.012
#> SRR1100824 5 0.3035 0.6866 0.000 0.000 0.032 0.112 0.856
#> SRR1085951 4 0.4585 0.4631 0.000 0.352 0.000 0.628 0.020
#> SRR1322046 2 0.2321 0.8619 0.000 0.912 0.056 0.024 0.008
#> SRR1316420 5 0.3039 0.7114 0.192 0.000 0.000 0.000 0.808
#> SRR1070913 2 0.0451 0.9144 0.000 0.988 0.004 0.008 0.000
#> SRR1345806 3 0.1661 0.8747 0.000 0.036 0.940 0.024 0.000
#> SRR1313872 2 0.0771 0.9117 0.000 0.976 0.004 0.020 0.000
#> SRR1337666 3 0.1828 0.8785 0.000 0.032 0.936 0.028 0.004
#> SRR1076823 4 0.3988 0.4563 0.000 0.000 0.036 0.768 0.196
#> SRR1093954 2 0.0290 0.9156 0.000 0.992 0.000 0.000 0.008
#> SRR1451921 4 0.2470 0.6213 0.000 0.012 0.104 0.884 0.000
#> SRR1491257 5 0.2067 0.7248 0.032 0.000 0.000 0.048 0.920
#> SRR1416979 2 0.1485 0.8936 0.000 0.948 0.000 0.032 0.020
#> SRR1419015 3 0.6588 -0.0873 0.000 0.000 0.400 0.392 0.208
#> SRR817649 3 0.3110 0.8066 0.000 0.000 0.860 0.060 0.080
#> SRR1466376 2 0.0671 0.9121 0.000 0.980 0.004 0.016 0.000
#> SRR1392055 3 0.1911 0.8770 0.000 0.036 0.932 0.028 0.004
#> SRR1120913 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR1120869 3 0.0613 0.8915 0.000 0.004 0.984 0.004 0.008
#> SRR1319419 3 0.0613 0.8915 0.000 0.004 0.984 0.004 0.008
#> SRR816495 3 0.1818 0.8697 0.000 0.044 0.932 0.024 0.000
#> SRR818694 2 0.1399 0.8964 0.000 0.952 0.000 0.028 0.020
#> SRR1465653 5 0.3612 0.6275 0.268 0.000 0.000 0.000 0.732
#> SRR1475952 1 0.0162 0.9325 0.996 0.000 0.000 0.004 0.000
#> SRR1465040 2 0.0451 0.9138 0.000 0.988 0.000 0.008 0.004
#> SRR1088461 3 0.0740 0.8908 0.000 0.004 0.980 0.008 0.008
#> SRR810129 2 0.1012 0.9062 0.000 0.968 0.000 0.012 0.020
#> SRR1400141 3 0.0451 0.8910 0.000 0.000 0.988 0.008 0.004
#> SRR1349585 1 0.3949 0.4647 0.668 0.000 0.000 0.000 0.332
#> SRR1437576 2 0.0324 0.9152 0.000 0.992 0.004 0.004 0.000
#> SRR814407 5 0.5218 0.5369 0.068 0.000 0.000 0.308 0.624
#> SRR1332403 2 0.0162 0.9156 0.000 0.996 0.004 0.000 0.000
#> SRR1099598 3 0.0451 0.8911 0.000 0.000 0.988 0.004 0.008
#> SRR1327723 3 0.2502 0.8568 0.000 0.060 0.904 0.024 0.012
#> SRR1392525 3 0.4517 0.3540 0.000 0.004 0.616 0.372 0.008
#> SRR1320536 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 3 0.3639 0.6816 0.000 0.184 0.792 0.024 0.000
#> SRR1351390 5 0.4497 0.3716 0.000 0.000 0.008 0.424 0.568
#> SRR1309141 3 0.0451 0.8925 0.000 0.004 0.988 0.008 0.000
#> SRR1452803 3 0.1911 0.8770 0.000 0.036 0.932 0.028 0.004
#> SRR811631 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR1485563 3 0.0451 0.8910 0.000 0.000 0.988 0.008 0.004
#> SRR1311531 3 0.1661 0.8747 0.000 0.036 0.940 0.024 0.000
#> SRR1353076 3 0.0727 0.8922 0.000 0.004 0.980 0.004 0.012
#> SRR1480831 2 0.4824 0.6694 0.000 0.744 0.124 0.124 0.008
#> SRR1083892 5 0.3143 0.7050 0.204 0.000 0.000 0.000 0.796
#> SRR809873 4 0.3375 0.5344 0.000 0.000 0.056 0.840 0.104
#> SRR1341854 2 0.0771 0.9108 0.000 0.976 0.004 0.020 0.000
#> SRR1399335 3 0.0451 0.8925 0.000 0.004 0.988 0.008 0.000
#> SRR1464209 5 0.0880 0.7290 0.032 0.000 0.000 0.000 0.968
#> SRR1389886 2 0.0324 0.9150 0.000 0.992 0.000 0.004 0.004
#> SRR1400730 5 0.3143 0.7050 0.204 0.000 0.000 0.000 0.796
#> SRR1448008 2 0.1568 0.8911 0.000 0.944 0.000 0.036 0.020
#> SRR1087606 5 0.3143 0.7050 0.204 0.000 0.000 0.000 0.796
#> SRR1445111 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR816865 2 0.2331 0.8593 0.000 0.900 0.000 0.080 0.020
#> SRR1323360 2 0.0162 0.9156 0.000 0.996 0.004 0.000 0.000
#> SRR1417364 3 0.2036 0.8601 0.000 0.056 0.920 0.024 0.000
#> SRR1480329 3 0.4683 0.6610 0.000 0.000 0.732 0.092 0.176
#> SRR1403322 4 0.3655 0.4803 0.000 0.000 0.036 0.804 0.160
#> SRR1093625 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.2964 0.7890 0.000 0.856 0.120 0.024 0.000
#> SRR1082035 5 0.3003 0.7121 0.188 0.000 0.000 0.000 0.812
#> SRR1393046 2 0.0000 0.9156 0.000 1.000 0.000 0.000 0.000
#> SRR1466663 3 0.0404 0.8907 0.000 0.000 0.988 0.012 0.000
#> SRR1384456 1 0.0000 0.9362 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 3 0.3359 0.72541 0.000 0.192 0.788 0.012 0.004 0.004
#> SRR808862 6 0.5045 0.18262 0.000 0.000 0.056 0.412 0.008 0.524
#> SRR1500382 3 0.2908 0.73923 0.000 0.004 0.864 0.012 0.028 0.092
#> SRR1322683 2 0.3201 0.71396 0.000 0.780 0.000 0.208 0.012 0.000
#> SRR1329811 5 0.3373 0.62066 0.000 0.000 0.008 0.000 0.744 0.248
#> SRR1087297 3 0.1483 0.79139 0.000 0.000 0.944 0.012 0.008 0.036
#> SRR1072626 2 0.5881 0.03673 0.000 0.528 0.100 0.344 0.016 0.012
#> SRR1407428 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.4195 0.35619 0.000 0.440 0.548 0.008 0.000 0.004
#> SRR1500282 1 0.0146 0.99369 0.996 0.000 0.000 0.000 0.004 0.000
#> SRR1100496 4 0.4008 0.52682 0.000 0.184 0.008 0.760 0.004 0.044
#> SRR1308778 3 0.2880 0.72452 0.000 0.000 0.856 0.012 0.024 0.108
#> SRR1445304 2 0.3078 0.72486 0.000 0.796 0.000 0.192 0.012 0.000
#> SRR1099378 6 0.5069 0.51715 0.000 0.000 0.204 0.036 0.080 0.680
#> SRR1347412 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.3048 0.74845 0.000 0.824 0.004 0.152 0.020 0.000
#> SRR1088365 2 0.4713 0.50167 0.000 0.580 0.004 0.380 0.028 0.008
#> SRR1325752 3 0.4464 0.46033 0.000 0.000 0.668 0.012 0.036 0.284
#> SRR1416713 2 0.1584 0.76436 0.000 0.928 0.000 0.064 0.008 0.000
#> SRR1074474 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.2302 0.77755 0.000 0.120 0.872 0.000 0.000 0.008
#> SRR1400507 2 0.0717 0.74083 0.000 0.976 0.016 0.008 0.000 0.000
#> SRR1378179 3 0.2063 0.79612 0.000 0.000 0.912 0.060 0.008 0.020
#> SRR1377905 2 0.3835 0.59547 0.000 0.668 0.000 0.320 0.012 0.000
#> SRR1089479 5 0.1757 0.80753 0.076 0.000 0.000 0.000 0.916 0.008
#> SRR1073365 2 0.3762 0.59365 0.000 0.816 0.088 0.072 0.016 0.008
#> SRR1500306 6 0.3364 0.57575 0.000 0.000 0.000 0.024 0.196 0.780
#> SRR1101566 3 0.0622 0.80827 0.000 0.000 0.980 0.008 0.000 0.012
#> SRR1350503 3 0.0696 0.80596 0.000 0.004 0.980 0.008 0.004 0.004
#> SRR1446007 2 0.3299 0.74289 0.000 0.808 0.004 0.164 0.020 0.004
#> SRR1102875 2 0.3010 0.74966 0.000 0.828 0.004 0.148 0.020 0.000
#> SRR1380293 3 0.3659 0.63873 0.000 0.000 0.780 0.012 0.028 0.180
#> SRR1331198 2 0.0260 0.75085 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1092686 3 0.2136 0.79373 0.000 0.000 0.908 0.064 0.012 0.016
#> SRR1069421 4 0.3288 0.41511 0.000 0.276 0.000 0.724 0.000 0.000
#> SRR1341650 4 0.5799 0.04953 0.000 0.000 0.408 0.460 0.016 0.116
#> SRR1357276 3 0.4910 0.48994 0.000 0.000 0.676 0.012 0.104 0.208
#> SRR1498374 2 0.3110 0.72191 0.000 0.792 0.000 0.196 0.012 0.000
#> SRR1093721 3 0.0146 0.80737 0.000 0.000 0.996 0.000 0.000 0.004
#> SRR1464660 5 0.1387 0.81118 0.068 0.000 0.000 0.000 0.932 0.000
#> SRR1402051 4 0.3499 0.35040 0.000 0.320 0.000 0.680 0.000 0.000
#> SRR1488734 3 0.0912 0.80429 0.000 0.004 0.972 0.012 0.008 0.004
#> SRR1082616 4 0.3672 0.36360 0.000 0.036 0.000 0.780 0.008 0.176
#> SRR1099427 3 0.1555 0.79899 0.000 0.000 0.940 0.012 0.008 0.040
#> SRR1453093 2 0.4185 0.17438 0.000 0.496 0.000 0.492 0.012 0.000
#> SRR1357064 5 0.1501 0.80796 0.076 0.000 0.000 0.000 0.924 0.000
#> SRR811237 4 0.4177 -0.14076 0.000 0.468 0.000 0.520 0.012 0.000
#> SRR1100848 4 0.6136 0.33729 0.000 0.336 0.144 0.496 0.012 0.012
#> SRR1346755 2 0.5736 -0.05106 0.000 0.488 0.400 0.092 0.008 0.012
#> SRR1472529 2 0.0260 0.75379 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1398905 6 0.3440 0.57483 0.000 0.000 0.000 0.028 0.196 0.776
#> SRR1082733 2 0.2812 0.67152 0.000 0.876 0.032 0.072 0.016 0.004
#> SRR1308035 2 0.2100 0.76259 0.000 0.884 0.000 0.112 0.004 0.000
#> SRR1466445 2 0.4074 0.59817 0.000 0.656 0.000 0.324 0.016 0.004
#> SRR1359080 2 0.0458 0.75246 0.000 0.984 0.000 0.016 0.000 0.000
#> SRR1455825 2 0.0000 0.75424 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1389300 2 0.3369 0.73848 0.000 0.800 0.004 0.172 0.020 0.004
#> SRR812246 3 0.0717 0.80762 0.000 0.000 0.976 0.008 0.000 0.016
#> SRR1076632 3 0.2513 0.79232 0.000 0.000 0.888 0.060 0.008 0.044
#> SRR1415567 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0000 0.75424 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1452099 4 0.5490 0.38925 0.000 0.048 0.164 0.668 0.004 0.116
#> SRR1352346 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1364034 2 0.3517 0.72800 0.000 0.780 0.004 0.188 0.028 0.000
#> SRR1086046 4 0.5188 -0.00846 0.000 0.004 0.060 0.540 0.008 0.388
#> SRR1407226 5 0.3133 0.65797 0.008 0.000 0.000 0.000 0.780 0.212
#> SRR1319363 6 0.2804 0.67604 0.000 0.000 0.016 0.108 0.016 0.860
#> SRR1446961 3 0.4100 0.45511 0.000 0.388 0.600 0.008 0.000 0.004
#> SRR1486650 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.3409 0.57987 0.300 0.000 0.000 0.000 0.700 0.000
#> SRR1454785 2 0.1588 0.76380 0.000 0.924 0.000 0.072 0.004 0.000
#> SRR1092329 2 0.3835 0.59292 0.000 0.668 0.000 0.320 0.012 0.000
#> SRR1091476 3 0.0767 0.80454 0.000 0.000 0.976 0.008 0.004 0.012
#> SRR1073775 2 0.2218 0.75859 0.000 0.884 0.000 0.104 0.012 0.000
#> SRR1366873 2 0.1116 0.72966 0.000 0.960 0.028 0.008 0.000 0.004
#> SRR1398114 2 0.1686 0.71599 0.000 0.924 0.000 0.064 0.012 0.000
#> SRR1089950 5 0.4095 0.16391 0.000 0.000 0.008 0.000 0.512 0.480
#> SRR1433272 4 0.3934 0.37215 0.000 0.376 0.008 0.616 0.000 0.000
#> SRR1075314 4 0.4688 0.13823 0.000 0.036 0.000 0.612 0.012 0.340
#> SRR1085590 2 0.3710 0.62991 0.000 0.696 0.000 0.292 0.012 0.000
#> SRR1100752 2 0.3977 0.35973 0.000 0.692 0.284 0.020 0.000 0.004
#> SRR1391494 2 0.0632 0.75092 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1333263 4 0.3765 0.25272 0.000 0.404 0.000 0.596 0.000 0.000
#> SRR1310231 3 0.1251 0.79651 0.000 0.000 0.956 0.012 0.008 0.024
#> SRR1094144 4 0.5680 0.44730 0.000 0.080 0.148 0.676 0.016 0.080
#> SRR1092160 2 0.4613 0.33118 0.000 0.664 0.280 0.044 0.008 0.004
#> SRR1320300 2 0.0547 0.75954 0.000 0.980 0.000 0.020 0.000 0.000
#> SRR1322747 2 0.2218 0.75859 0.000 0.884 0.000 0.104 0.012 0.000
#> SRR1432719 3 0.3214 0.74634 0.000 0.164 0.812 0.016 0.004 0.004
#> SRR1100728 4 0.6104 0.40982 0.000 0.076 0.164 0.632 0.016 0.112
#> SRR1087511 3 0.2252 0.78892 0.000 0.000 0.900 0.072 0.012 0.016
#> SRR1470336 5 0.3707 0.71980 0.056 0.000 0.000 0.004 0.784 0.156
#> SRR1322536 4 0.4541 -0.11126 0.000 0.000 0.016 0.544 0.012 0.428
#> SRR1100824 5 0.4093 0.17352 0.000 0.000 0.008 0.000 0.516 0.476
#> SRR1085951 4 0.4022 0.42708 0.000 0.088 0.000 0.764 0.004 0.144
#> SRR1322046 2 0.3059 0.64521 0.000 0.860 0.052 0.072 0.012 0.004
#> SRR1316420 5 0.1524 0.80878 0.060 0.000 0.000 0.000 0.932 0.008
#> SRR1070913 2 0.0260 0.75552 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1345806 3 0.3369 0.73975 0.000 0.172 0.800 0.020 0.004 0.004
#> SRR1313872 2 0.0632 0.75197 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1337666 3 0.2757 0.76981 0.000 0.136 0.848 0.008 0.004 0.004
#> SRR1076823 6 0.3003 0.67864 0.000 0.000 0.028 0.104 0.016 0.852
#> SRR1093954 2 0.3485 0.73085 0.000 0.784 0.004 0.184 0.028 0.000
#> SRR1451921 4 0.4688 -0.03822 0.000 0.000 0.032 0.560 0.008 0.400
#> SRR1491257 5 0.3043 0.67158 0.008 0.000 0.000 0.000 0.792 0.200
#> SRR1416979 2 0.3883 0.57414 0.000 0.656 0.000 0.332 0.012 0.000
#> SRR1419015 6 0.5677 0.24317 0.000 0.000 0.364 0.108 0.016 0.512
#> SRR817649 3 0.3692 0.63328 0.000 0.000 0.776 0.012 0.028 0.184
#> SRR1466376 2 0.0146 0.75569 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR1392055 3 0.2504 0.76950 0.000 0.136 0.856 0.004 0.000 0.004
#> SRR1120913 2 0.3201 0.71396 0.000 0.780 0.000 0.208 0.012 0.000
#> SRR1120869 3 0.2252 0.79133 0.000 0.000 0.900 0.072 0.012 0.016
#> SRR1319419 3 0.1952 0.79946 0.000 0.000 0.920 0.052 0.012 0.016
#> SRR816495 3 0.2703 0.74727 0.000 0.172 0.824 0.000 0.000 0.004
#> SRR818694 2 0.3819 0.59822 0.000 0.672 0.000 0.316 0.012 0.000
#> SRR1465653 5 0.1714 0.79945 0.092 0.000 0.000 0.000 0.908 0.000
#> SRR1475952 1 0.0713 0.97354 0.972 0.000 0.000 0.000 0.000 0.028
#> SRR1465040 2 0.3201 0.71396 0.000 0.780 0.000 0.208 0.012 0.000
#> SRR1088461 3 0.3352 0.77802 0.000 0.048 0.848 0.076 0.012 0.016
#> SRR810129 2 0.3835 0.59682 0.000 0.668 0.000 0.320 0.012 0.000
#> SRR1400141 3 0.0820 0.80722 0.000 0.000 0.972 0.012 0.000 0.016
#> SRR1349585 5 0.3607 0.49425 0.348 0.000 0.000 0.000 0.652 0.000
#> SRR1437576 2 0.0146 0.75275 0.000 0.996 0.000 0.004 0.000 0.000
#> SRR814407 6 0.4572 0.19712 0.020 0.000 0.000 0.012 0.400 0.568
#> SRR1332403 2 0.1411 0.76388 0.000 0.936 0.000 0.060 0.004 0.000
#> SRR1099598 3 0.2308 0.78830 0.000 0.000 0.896 0.076 0.012 0.016
#> SRR1327723 3 0.4769 0.65136 0.000 0.244 0.684 0.048 0.016 0.008
#> SRR1392525 3 0.5933 0.20830 0.000 0.008 0.504 0.360 0.016 0.112
#> SRR1320536 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 3 0.4755 0.31293 0.000 0.452 0.512 0.024 0.008 0.004
#> SRR1351390 6 0.3364 0.57575 0.000 0.000 0.000 0.024 0.196 0.780
#> SRR1309141 3 0.0405 0.80700 0.000 0.004 0.988 0.008 0.000 0.000
#> SRR1452803 3 0.2544 0.76877 0.000 0.140 0.852 0.004 0.000 0.004
#> SRR811631 2 0.3201 0.71396 0.000 0.780 0.000 0.208 0.012 0.000
#> SRR1485563 3 0.1856 0.79983 0.000 0.000 0.920 0.048 0.000 0.032
#> SRR1311531 3 0.2920 0.74517 0.000 0.168 0.820 0.008 0.000 0.004
#> SRR1353076 3 0.2426 0.79058 0.000 0.004 0.896 0.068 0.012 0.020
#> SRR1480831 2 0.5755 0.16771 0.000 0.592 0.116 0.264 0.016 0.012
#> SRR1083892 5 0.1387 0.81118 0.068 0.000 0.000 0.000 0.932 0.000
#> SRR809873 6 0.2848 0.63517 0.000 0.000 0.008 0.176 0.000 0.816
#> SRR1341854 2 0.0260 0.75085 0.000 0.992 0.000 0.008 0.000 0.000
#> SRR1399335 3 0.0405 0.80700 0.000 0.004 0.988 0.008 0.000 0.000
#> SRR1464209 5 0.2212 0.74751 0.008 0.000 0.000 0.000 0.880 0.112
#> SRR1389886 2 0.3046 0.72526 0.000 0.800 0.000 0.188 0.012 0.000
#> SRR1400730 5 0.1387 0.81118 0.068 0.000 0.000 0.000 0.932 0.000
#> SRR1448008 2 0.4116 0.39497 0.000 0.572 0.000 0.416 0.012 0.000
#> SRR1087606 5 0.1387 0.81118 0.068 0.000 0.000 0.000 0.932 0.000
#> SRR1445111 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR816865 4 0.4123 0.03866 0.000 0.420 0.000 0.568 0.012 0.000
#> SRR1323360 2 0.0865 0.76078 0.000 0.964 0.000 0.036 0.000 0.000
#> SRR1417364 3 0.3672 0.63004 0.000 0.276 0.712 0.008 0.000 0.004
#> SRR1480329 3 0.4404 0.47758 0.000 0.000 0.680 0.012 0.036 0.272
#> SRR1403322 6 0.2912 0.64661 0.000 0.000 0.000 0.172 0.012 0.816
#> SRR1093625 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.2695 0.59064 0.000 0.844 0.144 0.008 0.000 0.004
#> SRR1082035 5 0.1327 0.81057 0.064 0.000 0.000 0.000 0.936 0.000
#> SRR1393046 2 0.2266 0.75831 0.000 0.880 0.000 0.108 0.012 0.000
#> SRR1466663 3 0.1257 0.80587 0.000 0.000 0.952 0.028 0.000 0.020
#> SRR1384456 1 0.0000 0.99722 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "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 17467 rows and 159 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.984 0.994 0.4433 0.561 0.561
#> 3 3 0.651 0.668 0.842 0.4095 0.811 0.665
#> 4 4 0.909 0.889 0.953 0.1344 0.863 0.658
#> 5 5 0.714 0.683 0.834 0.0525 0.960 0.867
#> 6 6 0.690 0.589 0.782 0.0499 0.965 0.877
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2
There is also optional best \(k\) = 2 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> SRR810713 2 0.0000 0.991 0.000 1.000
#> SRR808862 2 0.9944 0.170 0.456 0.544
#> SRR1500382 1 0.0000 1.000 1.000 0.000
#> SRR1322683 2 0.0000 0.991 0.000 1.000
#> SRR1329811 1 0.0000 1.000 1.000 0.000
#> SRR1087297 1 0.0000 1.000 1.000 0.000
#> SRR1072626 2 0.0000 0.991 0.000 1.000
#> SRR1407428 1 0.0000 1.000 1.000 0.000
#> SRR1321029 2 0.0000 0.991 0.000 1.000
#> SRR1500282 1 0.0000 1.000 1.000 0.000
#> SRR1100496 2 0.0000 0.991 0.000 1.000
#> SRR1308778 1 0.0000 1.000 1.000 0.000
#> SRR1445304 2 0.0000 0.991 0.000 1.000
#> SRR1099378 1 0.0000 1.000 1.000 0.000
#> SRR1347412 1 0.0000 1.000 1.000 0.000
#> SRR1099694 2 0.0000 0.991 0.000 1.000
#> SRR1088365 2 0.0000 0.991 0.000 1.000
#> SRR1325752 1 0.0000 1.000 1.000 0.000
#> SRR1416713 2 0.0000 0.991 0.000 1.000
#> SRR1074474 1 0.0000 1.000 1.000 0.000
#> SRR1469369 2 0.0000 0.991 0.000 1.000
#> SRR1400507 2 0.0000 0.991 0.000 1.000
#> SRR1378179 2 0.0000 0.991 0.000 1.000
#> SRR1377905 2 0.0000 0.991 0.000 1.000
#> SRR1089479 1 0.0000 1.000 1.000 0.000
#> SRR1073365 2 0.0000 0.991 0.000 1.000
#> SRR1500306 1 0.0000 1.000 1.000 0.000
#> SRR1101566 2 0.0000 0.991 0.000 1.000
#> SRR1350503 2 0.0000 0.991 0.000 1.000
#> SRR1446007 2 0.0000 0.991 0.000 1.000
#> SRR1102875 2 0.0000 0.991 0.000 1.000
#> SRR1380293 1 0.0000 1.000 1.000 0.000
#> SRR1331198 2 0.0000 0.991 0.000 1.000
#> SRR1092686 2 0.0000 0.991 0.000 1.000
#> SRR1069421 2 0.0000 0.991 0.000 1.000
#> SRR1341650 2 0.0000 0.991 0.000 1.000
#> SRR1357276 1 0.0000 1.000 1.000 0.000
#> SRR1498374 2 0.0000 0.991 0.000 1.000
#> SRR1093721 2 0.0000 0.991 0.000 1.000
#> SRR1464660 1 0.0000 1.000 1.000 0.000
#> SRR1402051 2 0.0000 0.991 0.000 1.000
#> SRR1488734 2 0.4298 0.898 0.088 0.912
#> SRR1082616 2 0.0000 0.991 0.000 1.000
#> SRR1099427 1 0.0000 1.000 1.000 0.000
#> SRR1453093 2 0.0000 0.991 0.000 1.000
#> SRR1357064 1 0.0000 1.000 1.000 0.000
#> SRR811237 2 0.0000 0.991 0.000 1.000
#> SRR1100848 2 0.0000 0.991 0.000 1.000
#> SRR1346755 2 0.0000 0.991 0.000 1.000
#> SRR1472529 2 0.0000 0.991 0.000 1.000
#> SRR1398905 1 0.0000 1.000 1.000 0.000
#> SRR1082733 2 0.0000 0.991 0.000 1.000
#> SRR1308035 2 0.0000 0.991 0.000 1.000
#> SRR1466445 2 0.0000 0.991 0.000 1.000
#> SRR1359080 2 0.0000 0.991 0.000 1.000
#> SRR1455825 2 0.0000 0.991 0.000 1.000
#> SRR1389300 2 0.0000 0.991 0.000 1.000
#> SRR812246 2 0.0000 0.991 0.000 1.000
#> SRR1076632 2 0.9775 0.306 0.412 0.588
#> SRR1415567 1 0.0000 1.000 1.000 0.000
#> SRR1331900 2 0.0000 0.991 0.000 1.000
#> SRR1452099 2 0.0000 0.991 0.000 1.000
#> SRR1352346 1 0.0000 1.000 1.000 0.000
#> SRR1364034 2 0.0000 0.991 0.000 1.000
#> SRR1086046 2 0.0000 0.991 0.000 1.000
#> SRR1407226 1 0.0000 1.000 1.000 0.000
#> SRR1319363 1 0.0000 1.000 1.000 0.000
#> SRR1446961 2 0.0000 0.991 0.000 1.000
#> SRR1486650 1 0.0000 1.000 1.000 0.000
#> SRR1470152 1 0.0000 1.000 1.000 0.000
#> SRR1454785 2 0.0000 0.991 0.000 1.000
#> SRR1092329 2 0.0000 0.991 0.000 1.000
#> SRR1091476 1 0.0000 1.000 1.000 0.000
#> SRR1073775 2 0.0000 0.991 0.000 1.000
#> SRR1366873 2 0.0000 0.991 0.000 1.000
#> SRR1398114 2 0.0000 0.991 0.000 1.000
#> SRR1089950 1 0.0000 1.000 1.000 0.000
#> SRR1433272 2 0.0000 0.991 0.000 1.000
#> SRR1075314 2 0.0000 0.991 0.000 1.000
#> SRR1085590 2 0.0000 0.991 0.000 1.000
#> SRR1100752 2 0.0000 0.991 0.000 1.000
#> SRR1391494 2 0.0000 0.991 0.000 1.000
#> SRR1333263 2 0.0000 0.991 0.000 1.000
#> SRR1310231 1 0.0000 1.000 1.000 0.000
#> SRR1094144 2 0.0000 0.991 0.000 1.000
#> SRR1092160 2 0.0000 0.991 0.000 1.000
#> SRR1320300 2 0.0000 0.991 0.000 1.000
#> SRR1322747 2 0.0000 0.991 0.000 1.000
#> SRR1432719 2 0.0000 0.991 0.000 1.000
#> SRR1100728 2 0.0000 0.991 0.000 1.000
#> SRR1087511 2 0.0000 0.991 0.000 1.000
#> SRR1470336 1 0.0000 1.000 1.000 0.000
#> SRR1322536 2 0.0000 0.991 0.000 1.000
#> SRR1100824 1 0.0000 1.000 1.000 0.000
#> SRR1085951 2 0.0000 0.991 0.000 1.000
#> SRR1322046 2 0.0000 0.991 0.000 1.000
#> SRR1316420 1 0.0000 1.000 1.000 0.000
#> SRR1070913 2 0.0000 0.991 0.000 1.000
#> SRR1345806 2 0.0000 0.991 0.000 1.000
#> SRR1313872 2 0.0000 0.991 0.000 1.000
#> SRR1337666 2 0.0000 0.991 0.000 1.000
#> SRR1076823 1 0.0000 1.000 1.000 0.000
#> SRR1093954 2 0.0000 0.991 0.000 1.000
#> SRR1451921 2 0.0000 0.991 0.000 1.000
#> SRR1491257 1 0.0000 1.000 1.000 0.000
#> SRR1416979 2 0.0000 0.991 0.000 1.000
#> SRR1419015 1 0.0000 1.000 1.000 0.000
#> SRR817649 1 0.0000 1.000 1.000 0.000
#> SRR1466376 2 0.0000 0.991 0.000 1.000
#> SRR1392055 2 0.0000 0.991 0.000 1.000
#> SRR1120913 2 0.0000 0.991 0.000 1.000
#> SRR1120869 2 0.0000 0.991 0.000 1.000
#> SRR1319419 2 0.0000 0.991 0.000 1.000
#> SRR816495 2 0.0000 0.991 0.000 1.000
#> SRR818694 2 0.0000 0.991 0.000 1.000
#> SRR1465653 1 0.0000 1.000 1.000 0.000
#> SRR1475952 1 0.0000 1.000 1.000 0.000
#> SRR1465040 2 0.0000 0.991 0.000 1.000
#> SRR1088461 2 0.0000 0.991 0.000 1.000
#> SRR810129 2 0.0000 0.991 0.000 1.000
#> SRR1400141 2 0.0000 0.991 0.000 1.000
#> SRR1349585 1 0.0000 1.000 1.000 0.000
#> SRR1437576 2 0.0000 0.991 0.000 1.000
#> SRR814407 1 0.0000 1.000 1.000 0.000
#> SRR1332403 2 0.0000 0.991 0.000 1.000
#> SRR1099598 2 0.0000 0.991 0.000 1.000
#> SRR1327723 2 0.0000 0.991 0.000 1.000
#> SRR1392525 2 0.0000 0.991 0.000 1.000
#> SRR1320536 1 0.0000 1.000 1.000 0.000
#> SRR1083824 2 0.0000 0.991 0.000 1.000
#> SRR1351390 1 0.0000 1.000 1.000 0.000
#> SRR1309141 2 0.0000 0.991 0.000 1.000
#> SRR1452803 2 0.0000 0.991 0.000 1.000
#> SRR811631 2 0.0000 0.991 0.000 1.000
#> SRR1485563 2 0.0000 0.991 0.000 1.000
#> SRR1311531 2 0.0000 0.991 0.000 1.000
#> SRR1353076 2 0.0000 0.991 0.000 1.000
#> SRR1480831 2 0.0000 0.991 0.000 1.000
#> SRR1083892 1 0.0000 1.000 1.000 0.000
#> SRR809873 1 0.0000 1.000 1.000 0.000
#> SRR1341854 2 0.0000 0.991 0.000 1.000
#> SRR1399335 2 0.0000 0.991 0.000 1.000
#> SRR1464209 1 0.0000 1.000 1.000 0.000
#> SRR1389886 2 0.0000 0.991 0.000 1.000
#> SRR1400730 1 0.0000 1.000 1.000 0.000
#> SRR1448008 2 0.0000 0.991 0.000 1.000
#> SRR1087606 1 0.0000 1.000 1.000 0.000
#> SRR1445111 1 0.0000 1.000 1.000 0.000
#> SRR816865 2 0.0000 0.991 0.000 1.000
#> SRR1323360 2 0.0000 0.991 0.000 1.000
#> SRR1417364 2 0.0000 0.991 0.000 1.000
#> SRR1480329 1 0.0000 1.000 1.000 0.000
#> SRR1403322 1 0.0000 1.000 1.000 0.000
#> SRR1093625 1 0.0000 1.000 1.000 0.000
#> SRR1479977 2 0.0000 0.991 0.000 1.000
#> SRR1082035 1 0.0000 1.000 1.000 0.000
#> SRR1393046 2 0.0000 0.991 0.000 1.000
#> SRR1466663 2 0.0938 0.979 0.012 0.988
#> SRR1384456 1 0.0000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.3941 0.65395 0.000 0.844 0.156
#> SRR808862 3 0.8379 0.55713 0.208 0.168 0.624
#> SRR1500382 1 0.9282 0.30620 0.468 0.164 0.368
#> SRR1322683 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1329811 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1087297 1 0.6026 0.57835 0.624 0.000 0.376
#> SRR1072626 3 0.6111 0.65420 0.000 0.396 0.604
#> SRR1407428 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1321029 2 0.0237 0.77786 0.000 0.996 0.004
#> SRR1500282 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1100496 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1308778 1 0.5968 0.59320 0.636 0.000 0.364
#> SRR1445304 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1099378 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1347412 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1099694 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1088365 3 0.6045 0.67681 0.000 0.380 0.620
#> SRR1325752 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1416713 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1469369 2 0.1964 0.75001 0.000 0.944 0.056
#> SRR1400507 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1378179 3 0.5465 0.24620 0.000 0.288 0.712
#> SRR1377905 2 0.4605 0.48777 0.000 0.796 0.204
#> SRR1089479 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1073365 2 0.2711 0.72513 0.000 0.912 0.088
#> SRR1500306 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1101566 2 0.6295 0.14973 0.000 0.528 0.472
#> SRR1350503 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1446007 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1102875 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1380293 1 0.3619 0.83326 0.864 0.000 0.136
#> SRR1331198 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1092686 3 0.6180 0.00551 0.000 0.416 0.584
#> SRR1069421 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1341650 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1357276 1 0.3941 0.81548 0.844 0.000 0.156
#> SRR1498374 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1093721 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1464660 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1402051 2 0.6204 -0.22160 0.000 0.576 0.424
#> SRR1488734 2 0.7279 0.33780 0.036 0.588 0.376
#> SRR1082616 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1099427 1 0.6307 0.41618 0.512 0.000 0.488
#> SRR1453093 2 0.6180 -0.19608 0.000 0.584 0.416
#> SRR1357064 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR811237 2 0.6204 -0.22160 0.000 0.576 0.424
#> SRR1100848 2 0.6045 -0.06733 0.000 0.620 0.380
#> SRR1346755 2 0.4654 0.47974 0.000 0.792 0.208
#> SRR1472529 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1398905 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1082733 2 0.2711 0.72513 0.000 0.912 0.088
#> SRR1308035 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1466445 2 0.4654 0.47974 0.000 0.792 0.208
#> SRR1359080 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1455825 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1389300 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR812246 3 0.0592 0.50527 0.000 0.012 0.988
#> SRR1076632 3 0.0000 0.49821 0.000 0.000 1.000
#> SRR1415567 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1331900 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1452099 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1352346 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1364034 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1086046 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1407226 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1319363 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1446961 2 0.1860 0.75247 0.000 0.948 0.052
#> SRR1486650 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1454785 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1092329 2 0.4654 0.47974 0.000 0.792 0.208
#> SRR1091476 1 0.0747 0.93007 0.984 0.000 0.016
#> SRR1073775 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1366873 2 0.1860 0.75247 0.000 0.948 0.052
#> SRR1398114 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1089950 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1433272 2 0.6204 -0.22160 0.000 0.576 0.424
#> SRR1075314 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1085590 2 0.2796 0.67411 0.000 0.908 0.092
#> SRR1100752 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1391494 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1333263 2 0.6204 -0.22160 0.000 0.576 0.424
#> SRR1310231 1 0.9616 0.20904 0.420 0.204 0.376
#> SRR1094144 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1092160 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1320300 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1322747 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1432719 2 0.2537 0.73158 0.000 0.920 0.080
#> SRR1100728 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1087511 3 0.5859 0.66992 0.000 0.344 0.656
#> SRR1470336 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1322536 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1100824 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1085951 3 0.6302 0.48544 0.000 0.480 0.520
#> SRR1322046 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1316420 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1070913 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1345806 2 0.2796 0.72155 0.000 0.908 0.092
#> SRR1313872 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1337666 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1076823 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1093954 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1451921 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1491257 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1416979 2 0.4931 0.42461 0.000 0.768 0.232
#> SRR1419015 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR817649 1 0.5465 0.68244 0.712 0.000 0.288
#> SRR1466376 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1392055 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1120913 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1120869 3 0.6168 0.01438 0.000 0.412 0.588
#> SRR1319419 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR816495 2 0.5882 0.42363 0.000 0.652 0.348
#> SRR818694 2 0.4654 0.47974 0.000 0.792 0.208
#> SRR1465653 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1465040 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1088461 3 0.4504 0.42296 0.000 0.196 0.804
#> SRR810129 2 0.4605 0.48777 0.000 0.796 0.204
#> SRR1400141 3 0.5926 0.13220 0.000 0.356 0.644
#> SRR1349585 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1437576 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR814407 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1332403 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1099598 3 0.3752 0.57825 0.000 0.144 0.856
#> SRR1327723 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1392525 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1320536 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1083824 2 0.2711 0.72513 0.000 0.912 0.088
#> SRR1351390 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1309141 2 0.5988 0.40035 0.000 0.632 0.368
#> SRR1452803 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR811631 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1485563 3 0.6026 0.68155 0.000 0.376 0.624
#> SRR1311531 2 0.3038 0.71019 0.000 0.896 0.104
#> SRR1353076 3 0.6215 -0.02448 0.000 0.428 0.572
#> SRR1480831 2 0.6026 -0.12997 0.000 0.624 0.376
#> SRR1083892 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR809873 3 0.6026 0.21069 0.376 0.000 0.624
#> SRR1341854 2 0.0237 0.77831 0.000 0.996 0.004
#> SRR1399335 2 0.6026 0.39120 0.000 0.624 0.376
#> SRR1464209 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1389886 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1400730 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1448008 2 0.5254 0.34101 0.000 0.736 0.264
#> SRR1087606 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR816865 3 0.6302 0.48544 0.000 0.480 0.520
#> SRR1323360 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1417364 2 0.1860 0.75247 0.000 0.948 0.052
#> SRR1480329 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1403322 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1479977 2 0.1860 0.75247 0.000 0.948 0.052
#> SRR1082035 1 0.0000 0.94139 1.000 0.000 0.000
#> SRR1393046 2 0.0000 0.77838 0.000 1.000 0.000
#> SRR1466663 3 0.5497 0.64966 0.000 0.292 0.708
#> SRR1384456 1 0.0000 0.94139 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.1022 0.9421 0.000 0.968 0.032 0.000
#> SRR808862 4 0.0000 0.8750 0.000 0.000 0.000 1.000
#> SRR1500382 3 0.3569 0.7403 0.196 0.000 0.804 0.000
#> SRR1322683 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1329811 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1087297 3 0.0376 0.8741 0.004 0.000 0.992 0.004
#> SRR1072626 4 0.4730 0.5078 0.000 0.364 0.000 0.636
#> SRR1407428 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1321029 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1500282 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1100496 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1308778 3 0.3569 0.7403 0.196 0.000 0.804 0.000
#> SRR1445304 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1099378 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1347412 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1099694 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1088365 4 0.4585 0.5681 0.000 0.332 0.000 0.668
#> SRR1325752 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1416713 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1074474 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1469369 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1400507 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1378179 3 0.0469 0.8730 0.000 0.000 0.988 0.012
#> SRR1377905 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1089479 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1073365 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1500306 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1101566 2 0.5062 0.5246 0.000 0.680 0.300 0.020
#> SRR1350503 3 0.0000 0.8742 0.000 0.000 1.000 0.000
#> SRR1446007 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1102875 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1380293 1 0.4967 0.1070 0.548 0.000 0.452 0.000
#> SRR1331198 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1092686 3 0.0524 0.8741 0.000 0.004 0.988 0.008
#> SRR1069421 4 0.0469 0.8759 0.000 0.012 0.000 0.988
#> SRR1341650 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1357276 1 0.4989 0.0331 0.528 0.000 0.472 0.000
#> SRR1498374 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1093721 3 0.0469 0.8724 0.000 0.012 0.988 0.000
#> SRR1464660 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1402051 4 0.1940 0.8443 0.000 0.076 0.000 0.924
#> SRR1488734 3 0.0188 0.8744 0.000 0.000 0.996 0.004
#> SRR1082616 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1099427 3 0.0188 0.8744 0.000 0.000 0.996 0.004
#> SRR1453093 4 0.4804 0.4627 0.000 0.384 0.000 0.616
#> SRR1357064 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR811237 4 0.3837 0.6950 0.000 0.224 0.000 0.776
#> SRR1100848 2 0.4992 -0.0596 0.000 0.524 0.000 0.476
#> SRR1346755 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1472529 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1398905 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1082733 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1308035 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1466445 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1359080 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1455825 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1389300 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR812246 4 0.4304 0.6139 0.000 0.000 0.284 0.716
#> SRR1076632 3 0.0469 0.8730 0.000 0.000 0.988 0.012
#> SRR1415567 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1331900 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1452099 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1352346 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1364034 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1086046 4 0.0000 0.8750 0.000 0.000 0.000 1.000
#> SRR1407226 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1319363 1 0.0592 0.9611 0.984 0.000 0.000 0.016
#> SRR1446961 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1486650 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1470152 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1454785 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1092329 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1091476 1 0.0469 0.9650 0.988 0.000 0.012 0.000
#> SRR1073775 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1366873 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1398114 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1089950 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1433272 4 0.2011 0.8416 0.000 0.080 0.000 0.920
#> SRR1075314 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1085590 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1100752 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1391494 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1333263 4 0.2011 0.8416 0.000 0.080 0.000 0.920
#> SRR1310231 3 0.0592 0.8707 0.016 0.000 0.984 0.000
#> SRR1094144 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1092160 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1320300 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1322747 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1432719 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1100728 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1087511 4 0.6267 0.6312 0.000 0.148 0.188 0.664
#> SRR1470336 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1322536 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1100824 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1085951 4 0.0469 0.8757 0.000 0.012 0.000 0.988
#> SRR1322046 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1316420 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1070913 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1345806 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1313872 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1337666 3 0.3172 0.7765 0.000 0.160 0.840 0.000
#> SRR1076823 1 0.0188 0.9719 0.996 0.000 0.000 0.004
#> SRR1093954 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1451921 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1491257 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1416979 2 0.0188 0.9693 0.000 0.996 0.000 0.004
#> SRR1419015 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR817649 3 0.4817 0.3829 0.388 0.000 0.612 0.000
#> SRR1466376 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1392055 3 0.3123 0.7811 0.000 0.156 0.844 0.000
#> SRR1120913 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1120869 3 0.2565 0.8452 0.000 0.056 0.912 0.032
#> SRR1319419 3 0.0188 0.8744 0.000 0.000 0.996 0.004
#> SRR816495 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR818694 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1465653 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1475952 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1465040 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1088461 3 0.6827 0.3732 0.000 0.128 0.568 0.304
#> SRR810129 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1400141 3 0.0336 0.8741 0.000 0.000 0.992 0.008
#> SRR1349585 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1437576 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR814407 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1332403 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1099598 4 0.5182 0.5999 0.000 0.028 0.288 0.684
#> SRR1327723 3 0.0707 0.8712 0.000 0.020 0.980 0.000
#> SRR1392525 4 0.0188 0.8777 0.000 0.004 0.000 0.996
#> SRR1320536 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1083824 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1351390 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1309141 3 0.3528 0.7397 0.000 0.192 0.808 0.000
#> SRR1452803 3 0.3074 0.7852 0.000 0.152 0.848 0.000
#> SRR811631 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1485563 4 0.0000 0.8750 0.000 0.000 0.000 1.000
#> SRR1311531 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1353076 3 0.0336 0.8741 0.000 0.000 0.992 0.008
#> SRR1480831 2 0.4250 0.5762 0.000 0.724 0.000 0.276
#> SRR1083892 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR809873 4 0.0000 0.8750 0.000 0.000 0.000 1.000
#> SRR1341854 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1399335 3 0.2814 0.8043 0.000 0.132 0.868 0.000
#> SRR1464209 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1389886 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1400730 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1448008 2 0.4790 0.2934 0.000 0.620 0.000 0.380
#> SRR1087606 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1445111 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR816865 4 0.1867 0.8468 0.000 0.072 0.000 0.928
#> SRR1323360 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1417364 2 0.0336 0.9676 0.000 0.992 0.008 0.000
#> SRR1480329 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1403322 1 0.0707 0.9572 0.980 0.000 0.000 0.020
#> SRR1093625 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1479977 2 0.0188 0.9701 0.000 0.996 0.004 0.000
#> SRR1082035 1 0.0000 0.9754 1.000 0.000 0.000 0.000
#> SRR1393046 2 0.0000 0.9724 0.000 1.000 0.000 0.000
#> SRR1466663 4 0.1576 0.8446 0.000 0.004 0.048 0.948
#> SRR1384456 1 0.0000 0.9754 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 2 0.1764 0.84645 0.000 0.928 0.008 0.000 0.064
#> SRR808862 4 0.3837 0.57285 0.000 0.000 0.308 0.692 0.000
#> SRR1500382 5 0.2471 0.49760 0.136 0.000 0.000 0.000 0.864
#> SRR1322683 2 0.0992 0.85968 0.000 0.968 0.008 0.024 0.000
#> SRR1329811 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1087297 5 0.2230 0.45919 0.000 0.000 0.116 0.000 0.884
#> SRR1072626 2 0.6199 0.05546 0.000 0.468 0.140 0.392 0.000
#> SRR1407428 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 2 0.4617 0.68403 0.000 0.744 0.148 0.000 0.108
#> SRR1500282 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1100496 4 0.0566 0.73116 0.000 0.004 0.012 0.984 0.000
#> SRR1308778 5 0.3280 0.46740 0.176 0.000 0.012 0.000 0.812
#> SRR1445304 2 0.0451 0.86395 0.000 0.988 0.004 0.008 0.000
#> SRR1099378 1 0.1121 0.89472 0.956 0.000 0.044 0.000 0.000
#> SRR1347412 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.1281 0.85711 0.000 0.956 0.012 0.032 0.000
#> SRR1088365 4 0.6603 0.09717 0.000 0.392 0.212 0.396 0.000
#> SRR1325752 1 0.2470 0.82699 0.884 0.000 0.012 0.000 0.104
#> SRR1416713 2 0.0000 0.86415 0.000 1.000 0.000 0.000 0.000
#> SRR1074474 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 2 0.4671 0.68012 0.000 0.740 0.144 0.000 0.116
#> SRR1400507 2 0.0290 0.86344 0.000 0.992 0.008 0.000 0.000
#> SRR1378179 5 0.4639 -0.00811 0.000 0.000 0.368 0.020 0.612
#> SRR1377905 2 0.2660 0.80256 0.000 0.864 0.008 0.128 0.000
#> SRR1089479 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1073365 2 0.3210 0.73007 0.000 0.788 0.212 0.000 0.000
#> SRR1500306 1 0.3513 0.76707 0.800 0.000 0.180 0.020 0.000
#> SRR1101566 3 0.5086 0.31434 0.000 0.228 0.688 0.004 0.080
#> SRR1350503 5 0.2690 0.43518 0.000 0.000 0.156 0.000 0.844
#> SRR1446007 2 0.1877 0.84777 0.000 0.924 0.064 0.012 0.000
#> SRR1102875 2 0.3011 0.78824 0.000 0.844 0.140 0.016 0.000
#> SRR1380293 1 0.4262 0.16067 0.560 0.000 0.000 0.000 0.440
#> SRR1331198 2 0.1918 0.84005 0.000 0.928 0.036 0.000 0.036
#> SRR1092686 3 0.5070 0.36163 0.000 0.024 0.568 0.008 0.400
#> SRR1069421 4 0.2390 0.69290 0.000 0.084 0.020 0.896 0.000
#> SRR1341650 4 0.1478 0.72676 0.000 0.000 0.064 0.936 0.000
#> SRR1357276 5 0.4273 0.16210 0.448 0.000 0.000 0.000 0.552
#> SRR1498374 2 0.0324 0.86416 0.000 0.992 0.004 0.004 0.000
#> SRR1093721 3 0.4604 0.24724 0.000 0.012 0.560 0.000 0.428
#> SRR1464660 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1402051 4 0.3551 0.58725 0.000 0.220 0.008 0.772 0.000
#> SRR1488734 5 0.2127 0.46490 0.000 0.000 0.108 0.000 0.892
#> SRR1082616 4 0.0609 0.73192 0.000 0.000 0.020 0.980 0.000
#> SRR1099427 5 0.4256 -0.00847 0.000 0.000 0.436 0.000 0.564
#> SRR1453093 2 0.4656 0.06447 0.000 0.508 0.012 0.480 0.000
#> SRR1357064 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR811237 4 0.4430 0.39383 0.000 0.360 0.012 0.628 0.000
#> SRR1100848 2 0.4482 0.39711 0.000 0.612 0.012 0.376 0.000
#> SRR1346755 2 0.2707 0.80058 0.000 0.860 0.008 0.132 0.000
#> SRR1472529 2 0.0000 0.86415 0.000 1.000 0.000 0.000 0.000
#> SRR1398905 1 0.3093 0.78981 0.824 0.000 0.168 0.008 0.000
#> SRR1082733 2 0.3074 0.73123 0.000 0.804 0.196 0.000 0.000
#> SRR1308035 2 0.0290 0.86344 0.000 0.992 0.008 0.000 0.000
#> SRR1466445 2 0.2953 0.78623 0.000 0.844 0.012 0.144 0.000
#> SRR1359080 2 0.0162 0.86391 0.000 0.996 0.004 0.000 0.000
#> SRR1455825 2 0.1408 0.84975 0.000 0.948 0.044 0.000 0.008
#> SRR1389300 2 0.2423 0.83301 0.000 0.896 0.080 0.024 0.000
#> SRR812246 3 0.4400 0.32156 0.000 0.000 0.736 0.212 0.052
#> SRR1076632 3 0.4552 0.27854 0.000 0.000 0.524 0.008 0.468
#> SRR1415567 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.1082 0.85638 0.000 0.964 0.028 0.000 0.008
#> SRR1452099 4 0.0290 0.73263 0.000 0.000 0.008 0.992 0.000
#> SRR1352346 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1364034 2 0.4238 0.74007 0.000 0.776 0.088 0.136 0.000
#> SRR1086046 4 0.3039 0.65887 0.000 0.000 0.192 0.808 0.000
#> SRR1407226 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1319363 1 0.5952 0.47501 0.560 0.000 0.304 0.136 0.000
#> SRR1446961 2 0.4617 0.68403 0.000 0.744 0.148 0.000 0.108
#> SRR1486650 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1454785 2 0.0404 0.86318 0.000 0.988 0.012 0.000 0.000
#> SRR1092329 2 0.2753 0.79533 0.000 0.856 0.008 0.136 0.000
#> SRR1091476 1 0.6593 0.11817 0.464 0.000 0.284 0.000 0.252
#> SRR1073775 2 0.0324 0.86416 0.000 0.992 0.004 0.004 0.000
#> SRR1366873 2 0.2659 0.81568 0.000 0.888 0.052 0.000 0.060
#> SRR1398114 2 0.1571 0.84880 0.000 0.936 0.060 0.004 0.000
#> SRR1089950 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1433272 4 0.3582 0.58476 0.000 0.224 0.008 0.768 0.000
#> SRR1075314 4 0.2852 0.66954 0.000 0.000 0.172 0.828 0.000
#> SRR1085590 2 0.1894 0.84103 0.000 0.920 0.008 0.072 0.000
#> SRR1100752 2 0.3994 0.73608 0.000 0.792 0.140 0.000 0.068
#> SRR1391494 2 0.0798 0.86160 0.000 0.976 0.008 0.016 0.000
#> SRR1333263 4 0.3756 0.55428 0.000 0.248 0.008 0.744 0.000
#> SRR1310231 5 0.1579 0.51563 0.032 0.000 0.024 0.000 0.944
#> SRR1094144 4 0.0963 0.72467 0.000 0.000 0.036 0.964 0.000
#> SRR1092160 2 0.1830 0.84323 0.000 0.924 0.008 0.068 0.000
#> SRR1320300 2 0.0404 0.86314 0.000 0.988 0.012 0.000 0.000
#> SRR1322747 2 0.0162 0.86391 0.000 0.996 0.004 0.000 0.000
#> SRR1432719 2 0.3800 0.75661 0.000 0.812 0.108 0.000 0.080
#> SRR1100728 4 0.1341 0.71712 0.000 0.000 0.056 0.944 0.000
#> SRR1087511 3 0.5744 0.44567 0.000 0.040 0.636 0.272 0.052
#> SRR1470336 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1322536 4 0.3143 0.64839 0.000 0.000 0.204 0.796 0.000
#> SRR1100824 1 0.0290 0.91334 0.992 0.000 0.008 0.000 0.000
#> SRR1085951 4 0.0992 0.73490 0.000 0.008 0.024 0.968 0.000
#> SRR1322046 2 0.0963 0.86029 0.000 0.964 0.036 0.000 0.000
#> SRR1316420 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1070913 2 0.0000 0.86415 0.000 1.000 0.000 0.000 0.000
#> SRR1345806 2 0.4781 0.66884 0.000 0.728 0.160 0.000 0.112
#> SRR1313872 2 0.0324 0.86429 0.000 0.992 0.004 0.004 0.000
#> SRR1337666 5 0.4519 0.37641 0.000 0.100 0.148 0.000 0.752
#> SRR1076823 1 0.5188 0.55455 0.612 0.000 0.328 0.060 0.000
#> SRR1093954 2 0.3845 0.70334 0.000 0.768 0.208 0.024 0.000
#> SRR1451921 4 0.2852 0.67294 0.000 0.000 0.172 0.828 0.000
#> SRR1491257 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1416979 2 0.3421 0.72100 0.000 0.788 0.008 0.204 0.000
#> SRR1419015 1 0.2573 0.83416 0.880 0.000 0.104 0.016 0.000
#> SRR817649 5 0.3816 0.36527 0.304 0.000 0.000 0.000 0.696
#> SRR1466376 2 0.0290 0.86344 0.000 0.992 0.008 0.000 0.000
#> SRR1392055 5 0.3749 0.44939 0.000 0.080 0.104 0.000 0.816
#> SRR1120913 2 0.0798 0.86160 0.000 0.976 0.008 0.016 0.000
#> SRR1120869 5 0.6261 -0.26650 0.000 0.048 0.424 0.048 0.480
#> SRR1319419 3 0.4359 0.31536 0.000 0.004 0.584 0.000 0.412
#> SRR816495 2 0.4887 0.65436 0.000 0.720 0.148 0.000 0.132
#> SRR818694 2 0.2818 0.79689 0.000 0.856 0.012 0.132 0.000
#> SRR1465653 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1475952 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 2 0.0579 0.86319 0.000 0.984 0.008 0.008 0.000
#> SRR1088461 3 0.8063 0.36599 0.000 0.168 0.440 0.176 0.216
#> SRR810129 2 0.2753 0.79625 0.000 0.856 0.008 0.136 0.000
#> SRR1400141 3 0.4446 0.27242 0.000 0.000 0.520 0.004 0.476
#> SRR1349585 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1437576 2 0.0290 0.86344 0.000 0.992 0.008 0.000 0.000
#> SRR814407 1 0.2179 0.84423 0.888 0.000 0.112 0.000 0.000
#> SRR1332403 2 0.0290 0.86344 0.000 0.992 0.008 0.000 0.000
#> SRR1099598 3 0.6749 0.43954 0.000 0.068 0.556 0.284 0.092
#> SRR1327723 5 0.5555 -0.26818 0.000 0.068 0.452 0.000 0.480
#> SRR1392525 4 0.2020 0.70208 0.000 0.000 0.100 0.900 0.000
#> SRR1320536 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.2962 0.80234 0.000 0.868 0.084 0.000 0.048
#> SRR1351390 1 0.3513 0.76707 0.800 0.000 0.180 0.020 0.000
#> SRR1309141 5 0.2907 0.46851 0.000 0.116 0.008 0.012 0.864
#> SRR1452803 5 0.3090 0.47879 0.000 0.088 0.052 0.000 0.860
#> SRR811631 2 0.0579 0.86319 0.000 0.984 0.008 0.008 0.000
#> SRR1485563 4 0.2848 0.68542 0.000 0.000 0.156 0.840 0.004
#> SRR1311531 2 0.4711 0.67477 0.000 0.736 0.148 0.000 0.116
#> SRR1353076 5 0.4440 -0.27704 0.000 0.000 0.468 0.004 0.528
#> SRR1480831 2 0.5488 0.41199 0.000 0.608 0.092 0.300 0.000
#> SRR1083892 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR809873 4 0.3966 0.54935 0.000 0.000 0.336 0.664 0.000
#> SRR1341854 2 0.0000 0.86415 0.000 1.000 0.000 0.000 0.000
#> SRR1399335 5 0.3218 0.48256 0.000 0.096 0.032 0.012 0.860
#> SRR1464209 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1389886 2 0.0798 0.86160 0.000 0.976 0.008 0.016 0.000
#> SRR1400730 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1448008 2 0.4251 0.53683 0.000 0.672 0.012 0.316 0.000
#> SRR1087606 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1445111 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR816865 4 0.3789 0.58927 0.000 0.212 0.020 0.768 0.000
#> SRR1323360 2 0.0609 0.86232 0.000 0.980 0.020 0.000 0.000
#> SRR1417364 2 0.4617 0.68403 0.000 0.744 0.148 0.000 0.108
#> SRR1480329 1 0.2067 0.86137 0.920 0.000 0.032 0.000 0.048
#> SRR1403322 1 0.6399 0.35707 0.492 0.000 0.316 0.192 0.000
#> SRR1093625 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.2592 0.81831 0.000 0.892 0.052 0.000 0.056
#> SRR1082035 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
#> SRR1393046 2 0.0000 0.86415 0.000 1.000 0.000 0.000 0.000
#> SRR1466663 4 0.4465 0.60568 0.000 0.004 0.084 0.764 0.148
#> SRR1384456 1 0.0000 0.91766 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.4079 0.68787 0.096 0.788 0.032 0.000 0.000 0.084
#> SRR808862 1 0.4246 0.44519 0.532 0.000 0.016 0.452 0.000 0.000
#> SRR1500382 6 0.1531 0.60840 0.000 0.000 0.004 0.000 0.068 0.928
#> SRR1322683 2 0.1075 0.72837 0.000 0.952 0.000 0.048 0.000 0.000
#> SRR1329811 5 0.0291 0.90430 0.004 0.000 0.004 0.000 0.992 0.000
#> SRR1087297 6 0.2048 0.55014 0.000 0.000 0.120 0.000 0.000 0.880
#> SRR1072626 2 0.5978 -0.11774 0.004 0.416 0.192 0.388 0.000 0.000
#> SRR1407428 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1321029 2 0.6794 0.31602 0.308 0.480 0.116 0.008 0.000 0.088
#> SRR1500282 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1100496 4 0.2371 0.55577 0.016 0.052 0.032 0.900 0.000 0.000
#> SRR1308778 6 0.2250 0.59428 0.000 0.000 0.020 0.000 0.092 0.888
#> SRR1445304 2 0.0458 0.73795 0.000 0.984 0.000 0.016 0.000 0.000
#> SRR1099378 5 0.2100 0.81003 0.112 0.000 0.004 0.000 0.884 0.000
#> SRR1347412 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1099694 2 0.2378 0.66741 0.000 0.848 0.000 0.152 0.000 0.000
#> SRR1088365 3 0.6044 0.02689 0.000 0.308 0.416 0.276 0.000 0.000
#> SRR1325752 5 0.4192 0.24414 0.016 0.000 0.000 0.000 0.572 0.412
#> SRR1416713 2 0.0458 0.74077 0.016 0.984 0.000 0.000 0.000 0.000
#> SRR1074474 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1469369 2 0.6323 0.37781 0.316 0.508 0.104 0.000 0.000 0.072
#> SRR1400507 2 0.1391 0.73993 0.040 0.944 0.016 0.000 0.000 0.000
#> SRR1378179 3 0.4312 0.35143 0.012 0.000 0.584 0.008 0.000 0.396
#> SRR1377905 2 0.3126 0.57767 0.000 0.752 0.000 0.248 0.000 0.000
#> SRR1089479 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1073365 2 0.5160 0.40462 0.104 0.564 0.332 0.000 0.000 0.000
#> SRR1500306 5 0.4607 0.49025 0.244 0.000 0.020 0.048 0.688 0.000
#> SRR1101566 3 0.3455 0.57540 0.132 0.036 0.816 0.000 0.000 0.016
#> SRR1350503 6 0.5455 0.43636 0.296 0.008 0.124 0.000 0.000 0.572
#> SRR1446007 2 0.3485 0.65130 0.004 0.784 0.184 0.028 0.000 0.000
#> SRR1102875 2 0.4152 0.50530 0.000 0.664 0.304 0.032 0.000 0.000
#> SRR1380293 6 0.3862 0.08377 0.000 0.000 0.000 0.000 0.476 0.524
#> SRR1331198 2 0.4105 0.63987 0.188 0.752 0.040 0.000 0.000 0.020
#> SRR1092686 3 0.2095 0.69734 0.000 0.016 0.904 0.004 0.000 0.076
#> SRR1069421 4 0.2980 0.55844 0.000 0.192 0.008 0.800 0.000 0.000
#> SRR1341650 4 0.4662 0.30451 0.236 0.000 0.096 0.668 0.000 0.000
#> SRR1357276 6 0.3290 0.48014 0.000 0.000 0.004 0.000 0.252 0.744
#> SRR1498374 2 0.0363 0.73829 0.000 0.988 0.000 0.012 0.000 0.000
#> SRR1093721 3 0.5196 0.42343 0.192 0.016 0.656 0.000 0.000 0.136
#> SRR1464660 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1402051 4 0.3351 0.53654 0.000 0.288 0.000 0.712 0.000 0.000
#> SRR1488734 6 0.1908 0.56524 0.004 0.000 0.096 0.000 0.000 0.900
#> SRR1082616 4 0.1245 0.49100 0.032 0.000 0.016 0.952 0.000 0.000
#> SRR1099427 6 0.5255 0.28259 0.124 0.000 0.272 0.004 0.000 0.600
#> SRR1453093 4 0.4103 0.16216 0.004 0.448 0.004 0.544 0.000 0.000
#> SRR1357064 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR811237 4 0.3634 0.42748 0.000 0.356 0.000 0.644 0.000 0.000
#> SRR1100848 2 0.4103 0.13882 0.004 0.544 0.004 0.448 0.000 0.000
#> SRR1346755 2 0.3265 0.57060 0.000 0.748 0.004 0.248 0.000 0.000
#> SRR1472529 2 0.0692 0.74070 0.020 0.976 0.004 0.000 0.000 0.000
#> SRR1398905 5 0.3539 0.63729 0.208 0.000 0.008 0.016 0.768 0.000
#> SRR1082733 2 0.4229 0.27353 0.016 0.548 0.436 0.000 0.000 0.000
#> SRR1308035 2 0.1297 0.74101 0.040 0.948 0.012 0.000 0.000 0.000
#> SRR1466445 2 0.3390 0.50661 0.000 0.704 0.000 0.296 0.000 0.000
#> SRR1359080 2 0.0806 0.74276 0.020 0.972 0.000 0.008 0.000 0.000
#> SRR1455825 2 0.3671 0.66565 0.168 0.784 0.040 0.000 0.000 0.008
#> SRR1389300 2 0.3424 0.66028 0.004 0.796 0.168 0.032 0.000 0.000
#> SRR812246 3 0.5919 0.06833 0.296 0.000 0.516 0.176 0.000 0.012
#> SRR1076632 3 0.2454 0.67198 0.000 0.000 0.840 0.000 0.000 0.160
#> SRR1415567 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1331900 2 0.3423 0.68310 0.148 0.808 0.036 0.000 0.000 0.008
#> SRR1452099 4 0.1793 0.53159 0.036 0.032 0.004 0.928 0.000 0.000
#> SRR1352346 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1364034 2 0.4002 0.62112 0.000 0.744 0.188 0.068 0.000 0.000
#> SRR1086046 4 0.3929 0.08514 0.272 0.000 0.028 0.700 0.000 0.000
#> SRR1407226 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1319363 1 0.4955 0.71132 0.644 0.000 0.000 0.136 0.220 0.000
#> SRR1446961 2 0.6525 0.33578 0.316 0.488 0.104 0.000 0.000 0.092
#> SRR1486650 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1470152 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1454785 2 0.1838 0.73174 0.068 0.916 0.016 0.000 0.000 0.000
#> SRR1092329 2 0.3266 0.54433 0.000 0.728 0.000 0.272 0.000 0.000
#> SRR1091476 5 0.7639 -0.18481 0.332 0.000 0.156 0.016 0.352 0.144
#> SRR1073775 2 0.0508 0.74131 0.012 0.984 0.004 0.000 0.000 0.000
#> SRR1366873 2 0.4613 0.59539 0.232 0.696 0.048 0.000 0.000 0.024
#> SRR1398114 2 0.2592 0.71341 0.016 0.864 0.116 0.004 0.000 0.000
#> SRR1089950 5 0.0291 0.90430 0.004 0.000 0.004 0.000 0.992 0.000
#> SRR1433272 4 0.3371 0.53520 0.000 0.292 0.000 0.708 0.000 0.000
#> SRR1075314 4 0.3431 0.19750 0.228 0.000 0.016 0.756 0.000 0.000
#> SRR1085590 2 0.2631 0.64503 0.000 0.820 0.000 0.180 0.000 0.000
#> SRR1100752 2 0.6263 0.42187 0.288 0.548 0.092 0.008 0.000 0.064
#> SRR1391494 2 0.0937 0.73128 0.000 0.960 0.000 0.040 0.000 0.000
#> SRR1333263 4 0.3390 0.53242 0.000 0.296 0.000 0.704 0.000 0.000
#> SRR1310231 6 0.1265 0.59271 0.000 0.000 0.044 0.000 0.008 0.948
#> SRR1094144 4 0.2446 0.53502 0.000 0.012 0.124 0.864 0.000 0.000
#> SRR1092160 2 0.2562 0.65218 0.000 0.828 0.000 0.172 0.000 0.000
#> SRR1320300 2 0.1983 0.73019 0.072 0.908 0.020 0.000 0.000 0.000
#> SRR1322747 2 0.0790 0.74059 0.032 0.968 0.000 0.000 0.000 0.000
#> SRR1432719 2 0.5624 0.52044 0.248 0.616 0.080 0.000 0.000 0.056
#> SRR1100728 4 0.3543 0.46929 0.032 0.000 0.200 0.768 0.000 0.000
#> SRR1087511 3 0.3026 0.68388 0.020 0.036 0.864 0.076 0.000 0.004
#> SRR1470336 5 0.0146 0.90565 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1322536 4 0.3969 -0.08477 0.332 0.000 0.016 0.652 0.000 0.000
#> SRR1100824 5 0.0458 0.89596 0.016 0.000 0.000 0.000 0.984 0.000
#> SRR1085951 4 0.2007 0.52794 0.032 0.036 0.012 0.920 0.000 0.000
#> SRR1322046 2 0.2350 0.73145 0.036 0.888 0.076 0.000 0.000 0.000
#> SRR1316420 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1070913 2 0.0291 0.73982 0.000 0.992 0.004 0.004 0.000 0.000
#> SRR1345806 2 0.6643 0.30473 0.328 0.464 0.120 0.000 0.000 0.088
#> SRR1313872 2 0.1411 0.72795 0.000 0.936 0.004 0.060 0.000 0.000
#> SRR1337666 6 0.6000 0.41595 0.300 0.044 0.112 0.000 0.000 0.544
#> SRR1076823 1 0.4725 0.66502 0.648 0.000 0.000 0.088 0.264 0.000
#> SRR1093954 2 0.4475 0.29650 0.000 0.556 0.412 0.032 0.000 0.000
#> SRR1451921 4 0.3531 0.00255 0.328 0.000 0.000 0.672 0.000 0.000
#> SRR1491257 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1416979 2 0.3607 0.41223 0.000 0.652 0.000 0.348 0.000 0.000
#> SRR1419015 5 0.4004 0.25636 0.368 0.000 0.000 0.012 0.620 0.000
#> SRR817649 6 0.2631 0.56886 0.000 0.000 0.008 0.000 0.152 0.840
#> SRR1466376 2 0.0865 0.74045 0.036 0.964 0.000 0.000 0.000 0.000
#> SRR1392055 6 0.5886 0.44646 0.280 0.052 0.096 0.000 0.000 0.572
#> SRR1120913 2 0.1007 0.72978 0.000 0.956 0.000 0.044 0.000 0.000
#> SRR1120869 3 0.4343 0.63893 0.008 0.024 0.736 0.028 0.000 0.204
#> SRR1319419 3 0.2765 0.66807 0.064 0.008 0.872 0.000 0.000 0.056
#> SRR816495 2 0.6728 0.27351 0.332 0.452 0.112 0.000 0.000 0.104
#> SRR818694 2 0.3240 0.57641 0.000 0.752 0.004 0.244 0.000 0.000
#> SRR1465653 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1475952 5 0.0146 0.90565 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1465040 2 0.0632 0.73577 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1088461 3 0.4006 0.66098 0.008 0.100 0.804 0.052 0.000 0.036
#> SRR810129 2 0.3126 0.57682 0.000 0.752 0.000 0.248 0.000 0.000
#> SRR1400141 3 0.2340 0.67625 0.000 0.000 0.852 0.000 0.000 0.148
#> SRR1349585 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1437576 2 0.1225 0.73959 0.036 0.952 0.012 0.000 0.000 0.000
#> SRR814407 5 0.2442 0.76161 0.144 0.000 0.004 0.000 0.852 0.000
#> SRR1332403 2 0.0935 0.74063 0.032 0.964 0.004 0.000 0.000 0.000
#> SRR1099598 3 0.2762 0.68784 0.004 0.040 0.876 0.072 0.000 0.008
#> SRR1327723 3 0.6487 0.43025 0.124 0.132 0.560 0.000 0.000 0.184
#> SRR1392525 4 0.4808 0.33317 0.092 0.000 0.272 0.636 0.000 0.000
#> SRR1320536 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1083824 2 0.4961 0.57379 0.236 0.672 0.056 0.000 0.000 0.036
#> SRR1351390 5 0.4607 0.49025 0.244 0.000 0.020 0.048 0.688 0.000
#> SRR1309141 6 0.6045 0.47190 0.144 0.108 0.096 0.012 0.000 0.640
#> SRR1452803 6 0.5583 0.49007 0.224 0.056 0.088 0.000 0.000 0.632
#> SRR811631 2 0.0632 0.73577 0.000 0.976 0.000 0.024 0.000 0.000
#> SRR1485563 4 0.4985 -0.06478 0.400 0.000 0.072 0.528 0.000 0.000
#> SRR1311531 2 0.6744 0.28337 0.328 0.452 0.124 0.000 0.000 0.096
#> SRR1353076 3 0.2948 0.66306 0.000 0.008 0.804 0.000 0.000 0.188
#> SRR1480831 2 0.6201 0.12321 0.016 0.476 0.220 0.288 0.000 0.000
#> SRR1083892 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR809873 1 0.3607 0.56523 0.652 0.000 0.000 0.348 0.000 0.000
#> SRR1341854 2 0.0858 0.74047 0.028 0.968 0.004 0.000 0.000 0.000
#> SRR1399335 6 0.5912 0.44657 0.108 0.060 0.196 0.008 0.000 0.628
#> SRR1464209 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1389886 2 0.0937 0.73107 0.000 0.960 0.000 0.040 0.000 0.000
#> SRR1400730 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1448008 2 0.3727 0.32884 0.000 0.612 0.000 0.388 0.000 0.000
#> SRR1087606 5 0.0146 0.90594 0.004 0.000 0.000 0.000 0.996 0.000
#> SRR1445111 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR816865 4 0.3426 0.54143 0.000 0.276 0.004 0.720 0.000 0.000
#> SRR1323360 2 0.2747 0.72098 0.096 0.868 0.020 0.000 0.000 0.016
#> SRR1417364 2 0.6539 0.34215 0.308 0.492 0.108 0.000 0.000 0.092
#> SRR1480329 5 0.4302 0.49465 0.004 0.000 0.036 0.000 0.668 0.292
#> SRR1403322 1 0.4931 0.72343 0.652 0.000 0.000 0.200 0.148 0.000
#> SRR1093625 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1479977 2 0.4501 0.60654 0.224 0.708 0.044 0.000 0.000 0.024
#> SRR1082035 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1393046 2 0.0000 0.73976 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1466663 4 0.6670 0.09054 0.280 0.004 0.084 0.504 0.000 0.128
#> SRR1384456 5 0.0000 0.90719 0.000 0.000 0.000 0.000 1.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "pam"]
# you can also extract it by
# res = res_list["ATC:pam"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 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 0.993 0.997 0.2717 0.733 0.733
#> 3 3 0.531 0.695 0.867 1.1796 0.651 0.524
#> 4 4 0.548 0.461 0.742 0.1586 0.776 0.508
#> 5 5 0.664 0.615 0.832 0.0629 0.816 0.528
#> 6 6 0.711 0.779 0.855 0.0736 0.879 0.625
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
#> SRR810713 2 0.0000 0.996 0.000 1.000
#> SRR808862 2 0.0000 0.996 0.000 1.000
#> SRR1500382 2 0.0000 0.996 0.000 1.000
#> SRR1322683 2 0.0000 0.996 0.000 1.000
#> SRR1329811 2 0.0000 0.996 0.000 1.000
#> SRR1087297 2 0.0000 0.996 0.000 1.000
#> SRR1072626 2 0.0000 0.996 0.000 1.000
#> SRR1407428 1 0.0000 1.000 1.000 0.000
#> SRR1321029 2 0.0000 0.996 0.000 1.000
#> SRR1500282 1 0.0000 1.000 1.000 0.000
#> SRR1100496 2 0.0000 0.996 0.000 1.000
#> SRR1308778 2 0.0000 0.996 0.000 1.000
#> SRR1445304 2 0.0000 0.996 0.000 1.000
#> SRR1099378 2 0.0000 0.996 0.000 1.000
#> SRR1347412 1 0.0000 1.000 1.000 0.000
#> SRR1099694 2 0.0000 0.996 0.000 1.000
#> SRR1088365 2 0.0000 0.996 0.000 1.000
#> SRR1325752 2 0.0000 0.996 0.000 1.000
#> SRR1416713 2 0.0000 0.996 0.000 1.000
#> SRR1074474 1 0.0000 1.000 1.000 0.000
#> SRR1469369 2 0.0000 0.996 0.000 1.000
#> SRR1400507 2 0.0000 0.996 0.000 1.000
#> SRR1378179 2 0.0000 0.996 0.000 1.000
#> SRR1377905 2 0.0000 0.996 0.000 1.000
#> SRR1089479 1 0.0000 1.000 1.000 0.000
#> SRR1073365 2 0.0000 0.996 0.000 1.000
#> SRR1500306 2 0.0000 0.996 0.000 1.000
#> SRR1101566 2 0.0000 0.996 0.000 1.000
#> SRR1350503 2 0.0000 0.996 0.000 1.000
#> SRR1446007 2 0.0000 0.996 0.000 1.000
#> SRR1102875 2 0.0000 0.996 0.000 1.000
#> SRR1380293 2 0.0000 0.996 0.000 1.000
#> SRR1331198 2 0.0000 0.996 0.000 1.000
#> SRR1092686 2 0.0000 0.996 0.000 1.000
#> SRR1069421 2 0.0000 0.996 0.000 1.000
#> SRR1341650 2 0.0000 0.996 0.000 1.000
#> SRR1357276 2 0.0000 0.996 0.000 1.000
#> SRR1498374 2 0.0000 0.996 0.000 1.000
#> SRR1093721 2 0.0000 0.996 0.000 1.000
#> SRR1464660 1 0.0000 1.000 1.000 0.000
#> SRR1402051 2 0.0000 0.996 0.000 1.000
#> SRR1488734 2 0.0000 0.996 0.000 1.000
#> SRR1082616 2 0.0000 0.996 0.000 1.000
#> SRR1099427 2 0.0000 0.996 0.000 1.000
#> SRR1453093 2 0.0000 0.996 0.000 1.000
#> SRR1357064 1 0.0000 1.000 1.000 0.000
#> SRR811237 2 0.0000 0.996 0.000 1.000
#> SRR1100848 2 0.0000 0.996 0.000 1.000
#> SRR1346755 2 0.0000 0.996 0.000 1.000
#> SRR1472529 2 0.0000 0.996 0.000 1.000
#> SRR1398905 2 0.8499 0.621 0.276 0.724
#> SRR1082733 2 0.0000 0.996 0.000 1.000
#> SRR1308035 2 0.0000 0.996 0.000 1.000
#> SRR1466445 2 0.0000 0.996 0.000 1.000
#> SRR1359080 2 0.0000 0.996 0.000 1.000
#> SRR1455825 2 0.0000 0.996 0.000 1.000
#> SRR1389300 2 0.0000 0.996 0.000 1.000
#> SRR812246 2 0.0000 0.996 0.000 1.000
#> SRR1076632 2 0.0000 0.996 0.000 1.000
#> SRR1415567 1 0.0000 1.000 1.000 0.000
#> SRR1331900 2 0.0000 0.996 0.000 1.000
#> SRR1452099 2 0.0000 0.996 0.000 1.000
#> SRR1352346 1 0.0000 1.000 1.000 0.000
#> SRR1364034 2 0.0000 0.996 0.000 1.000
#> SRR1086046 2 0.0000 0.996 0.000 1.000
#> SRR1407226 2 0.0938 0.985 0.012 0.988
#> SRR1319363 2 0.0000 0.996 0.000 1.000
#> SRR1446961 2 0.0000 0.996 0.000 1.000
#> SRR1486650 1 0.0000 1.000 1.000 0.000
#> SRR1470152 1 0.0000 1.000 1.000 0.000
#> SRR1454785 2 0.0000 0.996 0.000 1.000
#> SRR1092329 2 0.0000 0.996 0.000 1.000
#> SRR1091476 2 0.0000 0.996 0.000 1.000
#> SRR1073775 2 0.0000 0.996 0.000 1.000
#> SRR1366873 2 0.0000 0.996 0.000 1.000
#> SRR1398114 2 0.0000 0.996 0.000 1.000
#> SRR1089950 2 0.0000 0.996 0.000 1.000
#> SRR1433272 2 0.0000 0.996 0.000 1.000
#> SRR1075314 2 0.0000 0.996 0.000 1.000
#> SRR1085590 2 0.0000 0.996 0.000 1.000
#> SRR1100752 2 0.0000 0.996 0.000 1.000
#> SRR1391494 2 0.0000 0.996 0.000 1.000
#> SRR1333263 2 0.0000 0.996 0.000 1.000
#> SRR1310231 2 0.0000 0.996 0.000 1.000
#> SRR1094144 2 0.0000 0.996 0.000 1.000
#> SRR1092160 2 0.0000 0.996 0.000 1.000
#> SRR1320300 2 0.0000 0.996 0.000 1.000
#> SRR1322747 2 0.0000 0.996 0.000 1.000
#> SRR1432719 2 0.0000 0.996 0.000 1.000
#> SRR1100728 2 0.0000 0.996 0.000 1.000
#> SRR1087511 2 0.0000 0.996 0.000 1.000
#> SRR1470336 1 0.0000 1.000 1.000 0.000
#> SRR1322536 2 0.0000 0.996 0.000 1.000
#> SRR1100824 2 0.0000 0.996 0.000 1.000
#> SRR1085951 2 0.0000 0.996 0.000 1.000
#> SRR1322046 2 0.0000 0.996 0.000 1.000
#> SRR1316420 1 0.0000 1.000 1.000 0.000
#> SRR1070913 2 0.0000 0.996 0.000 1.000
#> SRR1345806 2 0.0000 0.996 0.000 1.000
#> SRR1313872 2 0.0000 0.996 0.000 1.000
#> SRR1337666 2 0.0000 0.996 0.000 1.000
#> SRR1076823 2 0.0000 0.996 0.000 1.000
#> SRR1093954 2 0.0000 0.996 0.000 1.000
#> SRR1451921 2 0.0000 0.996 0.000 1.000
#> SRR1491257 2 0.0938 0.985 0.012 0.988
#> SRR1416979 2 0.0000 0.996 0.000 1.000
#> SRR1419015 2 0.0000 0.996 0.000 1.000
#> SRR817649 2 0.0000 0.996 0.000 1.000
#> SRR1466376 2 0.0000 0.996 0.000 1.000
#> SRR1392055 2 0.0000 0.996 0.000 1.000
#> SRR1120913 2 0.0000 0.996 0.000 1.000
#> SRR1120869 2 0.0000 0.996 0.000 1.000
#> SRR1319419 2 0.0000 0.996 0.000 1.000
#> SRR816495 2 0.0000 0.996 0.000 1.000
#> SRR818694 2 0.0000 0.996 0.000 1.000
#> SRR1465653 1 0.0000 1.000 1.000 0.000
#> SRR1475952 1 0.0000 1.000 1.000 0.000
#> SRR1465040 2 0.0000 0.996 0.000 1.000
#> SRR1088461 2 0.0000 0.996 0.000 1.000
#> SRR810129 2 0.0000 0.996 0.000 1.000
#> SRR1400141 2 0.0000 0.996 0.000 1.000
#> SRR1349585 1 0.0000 1.000 1.000 0.000
#> SRR1437576 2 0.0000 0.996 0.000 1.000
#> SRR814407 1 0.0000 1.000 1.000 0.000
#> SRR1332403 2 0.0000 0.996 0.000 1.000
#> SRR1099598 2 0.0000 0.996 0.000 1.000
#> SRR1327723 2 0.0000 0.996 0.000 1.000
#> SRR1392525 2 0.0000 0.996 0.000 1.000
#> SRR1320536 1 0.0000 1.000 1.000 0.000
#> SRR1083824 2 0.0000 0.996 0.000 1.000
#> SRR1351390 2 0.0000 0.996 0.000 1.000
#> SRR1309141 2 0.0000 0.996 0.000 1.000
#> SRR1452803 2 0.0000 0.996 0.000 1.000
#> SRR811631 2 0.0000 0.996 0.000 1.000
#> SRR1485563 2 0.0000 0.996 0.000 1.000
#> SRR1311531 2 0.0000 0.996 0.000 1.000
#> SRR1353076 2 0.0000 0.996 0.000 1.000
#> SRR1480831 2 0.0000 0.996 0.000 1.000
#> SRR1083892 1 0.0000 1.000 1.000 0.000
#> SRR809873 2 0.0000 0.996 0.000 1.000
#> SRR1341854 2 0.0000 0.996 0.000 1.000
#> SRR1399335 2 0.0000 0.996 0.000 1.000
#> SRR1464209 2 0.7139 0.758 0.196 0.804
#> SRR1389886 2 0.0000 0.996 0.000 1.000
#> SRR1400730 1 0.0000 1.000 1.000 0.000
#> SRR1448008 2 0.0000 0.996 0.000 1.000
#> SRR1087606 1 0.0000 1.000 1.000 0.000
#> SRR1445111 1 0.0000 1.000 1.000 0.000
#> SRR816865 2 0.0000 0.996 0.000 1.000
#> SRR1323360 2 0.0000 0.996 0.000 1.000
#> SRR1417364 2 0.0000 0.996 0.000 1.000
#> SRR1480329 2 0.0000 0.996 0.000 1.000
#> SRR1403322 2 0.0000 0.996 0.000 1.000
#> SRR1093625 1 0.0000 1.000 1.000 0.000
#> SRR1479977 2 0.0000 0.996 0.000 1.000
#> SRR1082035 1 0.0000 1.000 1.000 0.000
#> SRR1393046 2 0.0000 0.996 0.000 1.000
#> SRR1466663 2 0.0000 0.996 0.000 1.000
#> SRR1384456 1 0.0000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 2 0.4178 0.7231 0.000 0.828 0.172
#> SRR808862 3 0.2711 0.7788 0.000 0.088 0.912
#> SRR1500382 3 0.4931 0.5797 0.000 0.232 0.768
#> SRR1322683 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1329811 3 0.2339 0.7704 0.012 0.048 0.940
#> SRR1087297 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1072626 2 0.6302 0.0849 0.000 0.520 0.480
#> SRR1407428 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1321029 2 0.5098 0.6500 0.000 0.752 0.248
#> SRR1500282 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1100496 3 0.6274 0.1503 0.000 0.456 0.544
#> SRR1308778 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1445304 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1099378 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1347412 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1099694 2 0.5760 0.4610 0.000 0.672 0.328
#> SRR1088365 2 0.5882 0.4108 0.000 0.652 0.348
#> SRR1325752 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1416713 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1074474 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1469369 2 0.6008 0.4585 0.000 0.628 0.372
#> SRR1400507 2 0.3412 0.7538 0.000 0.876 0.124
#> SRR1378179 3 0.1411 0.8005 0.000 0.036 0.964
#> SRR1377905 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1089479 1 0.0892 0.9823 0.980 0.000 0.020
#> SRR1073365 3 0.6235 0.2185 0.000 0.436 0.564
#> SRR1500306 3 0.2356 0.7839 0.000 0.072 0.928
#> SRR1101566 3 0.6302 0.0518 0.000 0.480 0.520
#> SRR1350503 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1446007 2 0.4605 0.6262 0.000 0.796 0.204
#> SRR1102875 2 0.5621 0.4970 0.000 0.692 0.308
#> SRR1380293 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1331198 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1092686 3 0.5016 0.6382 0.000 0.240 0.760
#> SRR1069421 2 0.5733 0.4974 0.000 0.676 0.324
#> SRR1341650 3 0.5560 0.5477 0.000 0.300 0.700
#> SRR1357276 3 0.0000 0.7821 0.000 0.000 1.000
#> SRR1498374 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1093721 3 0.3551 0.7518 0.000 0.132 0.868
#> SRR1464660 1 0.1289 0.9796 0.968 0.000 0.032
#> SRR1402051 2 0.0237 0.8009 0.000 0.996 0.004
#> SRR1488734 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1082616 3 0.6286 0.1157 0.000 0.464 0.536
#> SRR1099427 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1453093 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1357064 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR811237 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1100848 2 0.6244 0.2483 0.000 0.560 0.440
#> SRR1346755 2 0.3412 0.7538 0.000 0.876 0.124
#> SRR1472529 2 0.3412 0.7538 0.000 0.876 0.124
#> SRR1398905 3 0.0000 0.7821 0.000 0.000 1.000
#> SRR1082733 2 0.6260 0.1144 0.000 0.552 0.448
#> SRR1308035 2 0.3412 0.7466 0.000 0.876 0.124
#> SRR1466445 2 0.2261 0.7822 0.000 0.932 0.068
#> SRR1359080 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1455825 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1389300 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR812246 3 0.1643 0.7981 0.000 0.044 0.956
#> SRR1076632 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1415567 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1331900 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1452099 2 0.6026 0.4262 0.000 0.624 0.376
#> SRR1352346 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1364034 2 0.6168 0.2429 0.000 0.588 0.412
#> SRR1086046 3 0.6079 0.3524 0.000 0.388 0.612
#> SRR1407226 3 0.0747 0.7742 0.016 0.000 0.984
#> SRR1319363 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1446961 2 0.5098 0.6500 0.000 0.752 0.248
#> SRR1486650 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1470152 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR1454785 2 0.1411 0.7922 0.000 0.964 0.036
#> SRR1092329 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1091476 3 0.1411 0.8000 0.000 0.036 0.964
#> SRR1073775 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1366873 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1398114 2 0.5560 0.5724 0.000 0.700 0.300
#> SRR1089950 3 0.0000 0.7821 0.000 0.000 1.000
#> SRR1433272 2 0.5098 0.6500 0.000 0.752 0.248
#> SRR1075314 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1085590 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1100752 2 0.6267 0.1974 0.000 0.548 0.452
#> SRR1391494 2 0.3412 0.7538 0.000 0.876 0.124
#> SRR1333263 2 0.3412 0.7538 0.000 0.876 0.124
#> SRR1310231 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1094144 3 0.6192 0.2589 0.000 0.420 0.580
#> SRR1092160 2 0.5098 0.6500 0.000 0.752 0.248
#> SRR1320300 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1322747 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1432719 3 0.6062 0.3616 0.000 0.384 0.616
#> SRR1100728 3 0.6062 0.3616 0.000 0.384 0.616
#> SRR1087511 3 0.6305 0.0366 0.000 0.484 0.516
#> SRR1470336 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR1322536 2 0.3686 0.7435 0.000 0.860 0.140
#> SRR1100824 3 0.0000 0.7821 0.000 0.000 1.000
#> SRR1085951 2 0.2796 0.7715 0.000 0.908 0.092
#> SRR1322046 2 0.5988 0.4464 0.000 0.632 0.368
#> SRR1316420 1 0.1289 0.9796 0.968 0.000 0.032
#> SRR1070913 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1345806 3 0.6291 0.0965 0.000 0.468 0.532
#> SRR1313872 2 0.4842 0.6774 0.000 0.776 0.224
#> SRR1337666 3 0.6154 0.2624 0.000 0.408 0.592
#> SRR1076823 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1093954 2 0.4842 0.5994 0.000 0.776 0.224
#> SRR1451921 2 0.6302 0.1060 0.000 0.520 0.480
#> SRR1491257 3 0.0747 0.7742 0.016 0.000 0.984
#> SRR1416979 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1419015 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR817649 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1466376 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1392055 2 0.5591 0.5833 0.000 0.696 0.304
#> SRR1120913 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1120869 3 0.4121 0.7162 0.000 0.168 0.832
#> SRR1319419 3 0.5397 0.5801 0.000 0.280 0.720
#> SRR816495 2 0.6286 0.1605 0.000 0.536 0.464
#> SRR818694 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1465653 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR1475952 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1465040 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1088461 3 0.5785 0.4927 0.000 0.332 0.668
#> SRR810129 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1400141 3 0.1289 0.8014 0.000 0.032 0.968
#> SRR1349585 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1437576 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR814407 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR1332403 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1099598 3 0.5621 0.5335 0.000 0.308 0.692
#> SRR1327723 2 0.6295 0.0336 0.000 0.528 0.472
#> SRR1392525 3 0.5733 0.4957 0.000 0.324 0.676
#> SRR1320536 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1083824 2 0.6267 0.1974 0.000 0.548 0.452
#> SRR1351390 3 0.5497 0.5277 0.000 0.292 0.708
#> SRR1309141 3 0.1289 0.8014 0.000 0.032 0.968
#> SRR1452803 3 0.5327 0.6004 0.000 0.272 0.728
#> SRR811631 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1485563 2 0.6307 0.0640 0.000 0.512 0.488
#> SRR1311531 2 0.5291 0.6245 0.000 0.732 0.268
#> SRR1353076 3 0.1289 0.8014 0.000 0.032 0.968
#> SRR1480831 2 0.5098 0.6364 0.000 0.752 0.248
#> SRR1083892 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR809873 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1341854 2 0.0424 0.7984 0.000 0.992 0.008
#> SRR1399335 3 0.3412 0.7539 0.000 0.124 0.876
#> SRR1464209 3 0.5098 0.4591 0.248 0.000 0.752
#> SRR1389886 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1400730 1 0.1163 0.9813 0.972 0.000 0.028
#> SRR1448008 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1087606 1 0.1289 0.9796 0.968 0.000 0.032
#> SRR1445111 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR816865 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1323360 2 0.3482 0.7445 0.000 0.872 0.128
#> SRR1417364 2 0.5327 0.6196 0.000 0.728 0.272
#> SRR1480329 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1403322 3 0.1163 0.8017 0.000 0.028 0.972
#> SRR1093625 1 0.0000 0.9835 1.000 0.000 0.000
#> SRR1479977 2 0.1411 0.7933 0.000 0.964 0.036
#> SRR1082035 1 0.4796 0.7805 0.780 0.000 0.220
#> SRR1393046 2 0.0000 0.8016 0.000 1.000 0.000
#> SRR1466663 3 0.3941 0.7140 0.000 0.156 0.844
#> SRR1384456 1 0.0000 0.9835 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 1 0.7609 -0.179 0.404 0.396 0.200 0.000
#> SRR808862 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1500382 3 0.2281 0.498 0.000 0.096 0.904 0.000
#> SRR1322683 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1329811 1 0.4605 0.189 0.664 0.000 0.336 0.000
#> SRR1087297 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1072626 3 0.7065 0.518 0.404 0.124 0.472 0.000
#> SRR1407428 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1321029 1 0.7712 -0.370 0.404 0.224 0.372 0.000
#> SRR1500282 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1100496 3 0.5592 0.619 0.404 0.024 0.572 0.000
#> SRR1308778 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1445304 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1099378 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1347412 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1099694 1 0.7854 -0.323 0.400 0.296 0.304 0.000
#> SRR1088365 2 0.4356 0.471 0.000 0.708 0.292 0.000
#> SRR1325752 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1416713 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1074474 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1469369 1 0.7647 -0.394 0.404 0.208 0.388 0.000
#> SRR1400507 2 0.7419 0.127 0.396 0.436 0.168 0.000
#> SRR1378179 3 0.4122 0.627 0.236 0.004 0.760 0.000
#> SRR1377905 2 0.4817 0.475 0.388 0.612 0.000 0.000
#> SRR1089479 4 0.4103 0.690 0.256 0.000 0.000 0.744
#> SRR1073365 3 0.6570 0.602 0.320 0.100 0.580 0.000
#> SRR1500306 1 0.4720 0.186 0.672 0.004 0.324 0.000
#> SRR1101566 3 0.7026 0.518 0.404 0.120 0.476 0.000
#> SRR1350503 3 0.0469 0.568 0.012 0.000 0.988 0.000
#> SRR1446007 2 0.2345 0.679 0.000 0.900 0.100 0.000
#> SRR1102875 2 0.3975 0.549 0.000 0.760 0.240 0.000
#> SRR1380293 3 0.0592 0.561 0.000 0.016 0.984 0.000
#> SRR1331198 2 0.1305 0.744 0.036 0.960 0.004 0.000
#> SRR1092686 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1069421 1 0.7824 -0.244 0.400 0.336 0.264 0.000
#> SRR1341650 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1357276 3 0.1792 0.478 0.068 0.000 0.932 0.000
#> SRR1498374 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1093721 3 0.5398 0.623 0.404 0.016 0.580 0.000
#> SRR1464660 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1402051 2 0.5016 0.461 0.396 0.600 0.004 0.000
#> SRR1488734 3 0.0188 0.562 0.000 0.004 0.996 0.000
#> SRR1082616 3 0.6499 0.577 0.400 0.076 0.524 0.000
#> SRR1099427 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1453093 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1357064 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR811237 2 0.2530 0.705 0.112 0.888 0.000 0.000
#> SRR1100848 3 0.6562 0.571 0.404 0.080 0.516 0.000
#> SRR1346755 2 0.7396 0.109 0.404 0.432 0.164 0.000
#> SRR1472529 2 0.7419 0.127 0.396 0.436 0.168 0.000
#> SRR1398905 1 0.4866 0.171 0.596 0.000 0.404 0.000
#> SRR1082733 2 0.5865 0.156 0.036 0.552 0.412 0.000
#> SRR1308035 2 0.3688 0.582 0.000 0.792 0.208 0.000
#> SRR1466445 2 0.6499 0.333 0.400 0.524 0.076 0.000
#> SRR1359080 2 0.5016 0.466 0.396 0.600 0.004 0.000
#> SRR1455825 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1389300 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR812246 3 0.3311 0.606 0.172 0.000 0.828 0.000
#> SRR1076632 3 0.0188 0.562 0.000 0.004 0.996 0.000
#> SRR1415567 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1331900 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1452099 3 0.7307 0.472 0.404 0.152 0.444 0.000
#> SRR1352346 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1364034 2 0.4888 0.219 0.000 0.588 0.412 0.000
#> SRR1086046 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1407226 1 0.4989 0.167 0.528 0.000 0.472 0.000
#> SRR1319363 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1446961 1 0.7712 -0.370 0.404 0.224 0.372 0.000
#> SRR1486650 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1470152 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1454785 2 0.1389 0.733 0.000 0.952 0.048 0.000
#> SRR1092329 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1091476 3 0.0895 0.559 0.004 0.020 0.976 0.000
#> SRR1073775 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1366873 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1398114 3 0.7732 0.414 0.268 0.288 0.444 0.000
#> SRR1089950 1 0.4866 0.171 0.596 0.000 0.404 0.000
#> SRR1433272 1 0.7743 -0.367 0.400 0.232 0.368 0.000
#> SRR1075314 2 0.4843 0.466 0.396 0.604 0.000 0.000
#> SRR1085590 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1100752 3 0.7065 0.513 0.404 0.124 0.472 0.000
#> SRR1391494 2 0.7391 0.127 0.396 0.440 0.164 0.000
#> SRR1333263 2 0.7391 0.127 0.396 0.440 0.164 0.000
#> SRR1310231 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1094144 3 0.5161 0.628 0.400 0.008 0.592 0.000
#> SRR1092160 1 0.7743 -0.367 0.400 0.232 0.368 0.000
#> SRR1320300 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1322747 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1432719 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1100728 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1087511 3 0.7065 0.517 0.404 0.124 0.472 0.000
#> SRR1470336 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1322536 2 0.7343 0.111 0.416 0.428 0.156 0.000
#> SRR1100824 3 0.4999 -0.255 0.492 0.000 0.508 0.000
#> SRR1085951 2 0.7003 0.282 0.368 0.508 0.124 0.000
#> SRR1322046 3 0.6851 0.539 0.400 0.104 0.496 0.000
#> SRR1316420 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1070913 2 0.2999 0.694 0.132 0.864 0.004 0.000
#> SRR1345806 3 0.6857 0.536 0.404 0.104 0.492 0.000
#> SRR1313872 1 0.7862 -0.289 0.396 0.296 0.308 0.000
#> SRR1337666 3 0.7597 0.413 0.356 0.204 0.440 0.000
#> SRR1076823 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1093954 2 0.2345 0.679 0.000 0.900 0.100 0.000
#> SRR1451921 3 0.5950 0.607 0.416 0.040 0.544 0.000
#> SRR1491257 1 0.4866 0.171 0.596 0.000 0.404 0.000
#> SRR1416979 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1419015 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR817649 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1466376 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1392055 3 0.6879 0.454 0.188 0.216 0.596 0.000
#> SRR1120913 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1120869 3 0.4720 0.633 0.324 0.004 0.672 0.000
#> SRR1319419 3 0.4866 0.628 0.404 0.000 0.596 0.000
#> SRR816495 3 0.7065 0.513 0.404 0.124 0.472 0.000
#> SRR818694 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1465653 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1475952 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1465040 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1088461 3 0.5290 0.623 0.404 0.012 0.584 0.000
#> SRR810129 2 0.3649 0.643 0.204 0.796 0.000 0.000
#> SRR1400141 3 0.1716 0.586 0.064 0.000 0.936 0.000
#> SRR1349585 4 0.1211 0.942 0.040 0.000 0.000 0.960
#> SRR1437576 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR814407 1 0.4866 -0.192 0.596 0.000 0.000 0.404
#> SRR1332403 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1099598 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1327723 3 0.7393 0.171 0.164 0.400 0.436 0.000
#> SRR1392525 3 0.5039 0.628 0.404 0.004 0.592 0.000
#> SRR1320536 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1083824 3 0.7065 0.513 0.404 0.124 0.472 0.000
#> SRR1351390 3 0.6014 0.118 0.360 0.052 0.588 0.000
#> SRR1309141 3 0.4008 0.628 0.244 0.000 0.756 0.000
#> SRR1452803 3 0.4978 0.633 0.324 0.012 0.664 0.000
#> SRR811631 2 0.0188 0.755 0.000 0.996 0.004 0.000
#> SRR1485563 3 0.6951 0.267 0.132 0.324 0.544 0.000
#> SRR1311531 1 0.7697 -0.375 0.404 0.220 0.376 0.000
#> SRR1353076 3 0.2921 0.608 0.140 0.000 0.860 0.000
#> SRR1480831 1 0.7844 -0.257 0.404 0.308 0.288 0.000
#> SRR1083892 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR809873 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1341854 2 0.5150 0.460 0.396 0.596 0.008 0.000
#> SRR1399335 3 0.4866 0.628 0.404 0.000 0.596 0.000
#> SRR1464209 1 0.4866 0.171 0.596 0.000 0.404 0.000
#> SRR1389886 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1400730 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1448008 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1087606 1 0.4898 -0.199 0.584 0.000 0.000 0.416
#> SRR1445111 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR816865 2 0.1474 0.736 0.052 0.948 0.000 0.000
#> SRR1323360 2 0.3688 0.582 0.000 0.792 0.208 0.000
#> SRR1417364 1 0.7697 -0.375 0.404 0.220 0.376 0.000
#> SRR1480329 3 0.0000 0.562 0.000 0.000 1.000 0.000
#> SRR1403322 3 0.0657 0.555 0.012 0.004 0.984 0.000
#> SRR1093625 4 0.0000 0.976 0.000 0.000 0.000 1.000
#> SRR1479977 2 0.5592 0.513 0.300 0.656 0.044 0.000
#> SRR1082035 1 0.6969 0.019 0.584 0.000 0.224 0.192
#> SRR1393046 2 0.0000 0.755 0.000 1.000 0.000 0.000
#> SRR1466663 3 0.5582 0.620 0.400 0.024 0.576 0.000
#> SRR1384456 4 0.0000 0.976 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
#> SRR810713 3 0.4015 0.3105 0.000 0.348 0.652 0.000 0.000
#> SRR808862 3 0.3395 0.5202 0.000 0.000 0.764 0.236 0.000
#> SRR1500382 3 0.4894 0.1701 0.000 0.024 0.520 0.456 0.000
#> SRR1322683 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR1329811 5 0.1197 0.8397 0.000 0.000 0.048 0.000 0.952
#> SRR1087297 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1072626 3 0.4617 0.5158 0.000 0.224 0.716 0.060 0.000
#> SRR1407428 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.0794 0.6962 0.000 0.028 0.972 0.000 0.000
#> SRR1500282 1 0.1197 0.9323 0.952 0.000 0.000 0.000 0.048
#> SRR1100496 3 0.1568 0.6874 0.000 0.020 0.944 0.036 0.000
#> SRR1308778 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1445304 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1099378 4 0.0290 0.7659 0.000 0.000 0.008 0.992 0.000
#> SRR1347412 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1099694 3 0.2561 0.6165 0.000 0.144 0.856 0.000 0.000
#> SRR1088365 2 0.3579 0.5832 0.000 0.756 0.240 0.004 0.000
#> SRR1325752 4 0.1965 0.7049 0.000 0.000 0.096 0.904 0.000
#> SRR1416713 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1074474 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.0955 0.6970 0.000 0.028 0.968 0.004 0.000
#> SRR1400507 3 0.4161 0.2107 0.000 0.392 0.608 0.000 0.000
#> SRR1378179 3 0.3366 0.5545 0.000 0.000 0.768 0.232 0.000
#> SRR1377905 2 0.4262 0.2381 0.000 0.560 0.440 0.000 0.000
#> SRR1089479 5 0.3932 0.4631 0.328 0.000 0.000 0.000 0.672
#> SRR1073365 3 0.2179 0.6545 0.000 0.112 0.888 0.000 0.000
#> SRR1500306 4 0.3012 0.6724 0.000 0.000 0.104 0.860 0.036
#> SRR1101566 3 0.0162 0.6991 0.000 0.000 0.996 0.004 0.000
#> SRR1350503 3 0.4268 0.2025 0.000 0.000 0.556 0.444 0.000
#> SRR1446007 2 0.0794 0.8055 0.000 0.972 0.028 0.000 0.000
#> SRR1102875 2 0.3177 0.6336 0.000 0.792 0.208 0.000 0.000
#> SRR1380293 3 0.4297 0.1722 0.000 0.000 0.528 0.472 0.000
#> SRR1331198 2 0.1341 0.8085 0.000 0.944 0.056 0.000 0.000
#> SRR1092686 3 0.0703 0.6967 0.000 0.000 0.976 0.024 0.000
#> SRR1069421 3 0.4851 0.3110 0.000 0.340 0.624 0.036 0.000
#> SRR1341650 3 0.1410 0.6900 0.000 0.000 0.940 0.060 0.000
#> SRR1357276 3 0.5238 0.0725 0.000 0.000 0.480 0.476 0.044
#> SRR1498374 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1093721 3 0.0000 0.6991 0.000 0.000 1.000 0.000 0.000
#> SRR1464660 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1402051 2 0.5103 0.1481 0.000 0.512 0.452 0.036 0.000
#> SRR1488734 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1082616 3 0.4338 0.4078 0.000 0.024 0.696 0.280 0.000
#> SRR1099427 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1453093 2 0.0451 0.8189 0.000 0.988 0.008 0.004 0.000
#> SRR1357064 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR811237 2 0.2843 0.7287 0.000 0.848 0.144 0.008 0.000
#> SRR1100848 3 0.0693 0.7005 0.000 0.012 0.980 0.008 0.000
#> SRR1346755 3 0.4403 0.2264 0.000 0.384 0.608 0.008 0.000
#> SRR1472529 3 0.4182 0.1904 0.000 0.400 0.600 0.000 0.000
#> SRR1398905 5 0.4305 0.2887 0.000 0.000 0.000 0.488 0.512
#> SRR1082733 2 0.4767 0.1927 0.000 0.560 0.420 0.020 0.000
#> SRR1308035 2 0.4114 0.3289 0.000 0.624 0.376 0.000 0.000
#> SRR1466445 3 0.5096 0.0529 0.000 0.444 0.520 0.036 0.000
#> SRR1359080 2 0.4294 0.2042 0.000 0.532 0.468 0.000 0.000
#> SRR1455825 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1389300 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR812246 3 0.3508 0.4944 0.000 0.000 0.748 0.252 0.000
#> SRR1076632 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1415567 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1452099 3 0.2054 0.6899 0.000 0.028 0.920 0.052 0.000
#> SRR1352346 1 0.1197 0.9323 0.952 0.000 0.000 0.000 0.048
#> SRR1364034 2 0.4686 0.2688 0.000 0.596 0.384 0.020 0.000
#> SRR1086046 3 0.1568 0.6874 0.000 0.020 0.944 0.036 0.000
#> SRR1407226 4 0.2179 0.6903 0.000 0.000 0.000 0.888 0.112
#> SRR1319363 4 0.0162 0.7671 0.000 0.000 0.004 0.996 0.000
#> SRR1446961 3 0.0794 0.6962 0.000 0.028 0.972 0.000 0.000
#> SRR1486650 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1454785 2 0.1671 0.7891 0.000 0.924 0.076 0.000 0.000
#> SRR1092329 2 0.0451 0.8189 0.000 0.988 0.008 0.004 0.000
#> SRR1091476 3 0.4268 0.1948 0.000 0.000 0.556 0.444 0.000
#> SRR1073775 2 0.0162 0.8204 0.000 0.996 0.004 0.000 0.000
#> SRR1366873 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1398114 3 0.3999 0.5661 0.000 0.240 0.740 0.020 0.000
#> SRR1089950 4 0.1478 0.7248 0.000 0.000 0.000 0.936 0.064
#> SRR1433272 3 0.1753 0.6879 0.000 0.032 0.936 0.032 0.000
#> SRR1075314 2 0.5165 0.1546 0.000 0.512 0.448 0.040 0.000
#> SRR1085590 2 0.0324 0.8194 0.000 0.992 0.004 0.004 0.000
#> SRR1100752 3 0.0000 0.6991 0.000 0.000 1.000 0.000 0.000
#> SRR1391494 3 0.4161 0.2107 0.000 0.392 0.608 0.000 0.000
#> SRR1333263 3 0.5052 0.1554 0.000 0.412 0.552 0.036 0.000
#> SRR1310231 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1094144 3 0.1502 0.6898 0.000 0.004 0.940 0.056 0.000
#> SRR1092160 3 0.0880 0.6957 0.000 0.032 0.968 0.000 0.000
#> SRR1320300 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1322747 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1432719 3 0.0000 0.6991 0.000 0.000 1.000 0.000 0.000
#> SRR1100728 3 0.1341 0.6902 0.000 0.000 0.944 0.056 0.000
#> SRR1087511 3 0.0671 0.6996 0.000 0.004 0.980 0.016 0.000
#> SRR1470336 5 0.1197 0.8654 0.048 0.000 0.000 0.000 0.952
#> SRR1322536 4 0.4815 0.1129 0.000 0.020 0.456 0.524 0.000
#> SRR1100824 4 0.1410 0.7283 0.000 0.000 0.000 0.940 0.060
#> SRR1085951 3 0.5114 -0.0302 0.000 0.472 0.492 0.036 0.000
#> SRR1322046 3 0.1493 0.6994 0.000 0.028 0.948 0.024 0.000
#> SRR1316420 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1070913 2 0.2966 0.7088 0.000 0.816 0.184 0.000 0.000
#> SRR1345806 3 0.0162 0.6991 0.000 0.000 0.996 0.004 0.000
#> SRR1313872 3 0.3109 0.5742 0.000 0.200 0.800 0.000 0.000
#> SRR1337666 3 0.2054 0.6877 0.000 0.028 0.920 0.052 0.000
#> SRR1076823 4 0.0162 0.7671 0.000 0.000 0.004 0.996 0.000
#> SRR1093954 2 0.1399 0.7999 0.000 0.952 0.028 0.020 0.000
#> SRR1451921 4 0.4538 0.1160 0.000 0.008 0.452 0.540 0.000
#> SRR1491257 5 0.0794 0.8761 0.000 0.000 0.000 0.028 0.972
#> SRR1416979 2 0.0324 0.8191 0.000 0.992 0.004 0.004 0.000
#> SRR1419015 4 0.0162 0.7671 0.000 0.000 0.004 0.996 0.000
#> SRR817649 3 0.4300 0.1692 0.000 0.000 0.524 0.476 0.000
#> SRR1466376 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1392055 3 0.4326 0.5041 0.000 0.028 0.708 0.264 0.000
#> SRR1120913 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR1120869 3 0.2230 0.6534 0.000 0.000 0.884 0.116 0.000
#> SRR1319419 3 0.0794 0.6963 0.000 0.000 0.972 0.028 0.000
#> SRR816495 3 0.0000 0.6991 0.000 0.000 1.000 0.000 0.000
#> SRR818694 2 0.0162 0.8189 0.000 0.996 0.000 0.004 0.000
#> SRR1465653 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1475952 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR1088461 3 0.0794 0.6963 0.000 0.000 0.972 0.028 0.000
#> SRR810129 2 0.3662 0.5987 0.000 0.744 0.252 0.004 0.000
#> SRR1400141 3 0.4210 0.2932 0.000 0.000 0.588 0.412 0.000
#> SRR1349585 1 0.3752 0.5798 0.708 0.000 0.000 0.000 0.292
#> SRR1437576 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR814407 5 0.4256 0.3934 0.000 0.000 0.000 0.436 0.564
#> SRR1332403 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1099598 3 0.0794 0.6963 0.000 0.000 0.972 0.028 0.000
#> SRR1327723 3 0.4848 0.1837 0.000 0.420 0.556 0.024 0.000
#> SRR1392525 3 0.0794 0.6963 0.000 0.000 0.972 0.028 0.000
#> SRR1320536 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 3 0.0000 0.6991 0.000 0.000 1.000 0.000 0.000
#> SRR1351390 4 0.2377 0.6828 0.000 0.000 0.128 0.872 0.000
#> SRR1309141 3 0.3177 0.5784 0.000 0.000 0.792 0.208 0.000
#> SRR1452803 3 0.1965 0.6588 0.000 0.000 0.904 0.096 0.000
#> SRR811631 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR1485563 3 0.6696 0.1377 0.000 0.240 0.388 0.372 0.000
#> SRR1311531 3 0.0955 0.6971 0.000 0.028 0.968 0.004 0.000
#> SRR1353076 3 0.3949 0.4269 0.000 0.000 0.668 0.332 0.000
#> SRR1480831 3 0.4768 0.2400 0.000 0.384 0.592 0.024 0.000
#> SRR1083892 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR809873 4 0.0162 0.7671 0.000 0.000 0.004 0.996 0.000
#> SRR1341854 2 0.4542 0.2088 0.000 0.536 0.456 0.008 0.000
#> SRR1399335 3 0.0703 0.6973 0.000 0.000 0.976 0.024 0.000
#> SRR1464209 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1389886 2 0.0000 0.8195 0.000 1.000 0.000 0.000 0.000
#> SRR1400730 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1448008 2 0.0162 0.8189 0.000 0.996 0.000 0.004 0.000
#> SRR1087606 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1445111 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR816865 2 0.1638 0.7909 0.000 0.932 0.064 0.004 0.000
#> SRR1323360 2 0.4114 0.3289 0.000 0.624 0.376 0.000 0.000
#> SRR1417364 3 0.0794 0.6962 0.000 0.028 0.972 0.000 0.000
#> SRR1480329 4 0.4300 -0.1086 0.000 0.000 0.476 0.524 0.000
#> SRR1403322 4 0.0162 0.7671 0.000 0.000 0.004 0.996 0.000
#> SRR1093625 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.4114 0.3837 0.000 0.624 0.376 0.000 0.000
#> SRR1082035 5 0.0000 0.8977 0.000 0.000 0.000 0.000 1.000
#> SRR1393046 2 0.0609 0.8219 0.000 0.980 0.020 0.000 0.000
#> SRR1466663 3 0.0703 0.6972 0.000 0.000 0.976 0.024 0.000
#> SRR1384456 1 0.0000 0.9656 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 3 0.0622 0.820 0.000 0.008 0.980 0.000 0.000 0.012
#> SRR808862 3 0.5037 0.370 0.000 0.000 0.540 0.380 0.000 0.080
#> SRR1500382 3 0.5318 0.643 0.000 0.008 0.620 0.224 0.000 0.148
#> SRR1322683 2 0.1714 0.800 0.000 0.908 0.000 0.000 0.000 0.092
#> SRR1329811 5 0.1644 0.832 0.000 0.000 0.076 0.000 0.920 0.004
#> SRR1087297 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1072626 6 0.4354 0.653 0.000 0.008 0.268 0.040 0.000 0.684
#> SRR1407428 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1500282 1 0.1501 0.903 0.924 0.000 0.000 0.000 0.076 0.000
#> SRR1100496 6 0.2704 0.782 0.000 0.016 0.140 0.000 0.000 0.844
#> SRR1308778 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1445304 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1099378 4 0.0000 0.858 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1347412 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.3398 0.612 0.000 0.740 0.252 0.000 0.000 0.008
#> SRR1088365 6 0.2996 0.749 0.000 0.228 0.000 0.000 0.000 0.772
#> SRR1325752 4 0.3602 0.677 0.000 0.000 0.072 0.792 0.000 0.136
#> SRR1416713 2 0.0146 0.856 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1074474 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.0622 0.822 0.000 0.008 0.980 0.000 0.000 0.012
#> SRR1400507 3 0.1320 0.813 0.000 0.036 0.948 0.000 0.000 0.016
#> SRR1378179 3 0.3997 0.776 0.000 0.000 0.760 0.108 0.000 0.132
#> SRR1377905 2 0.6019 -0.201 0.000 0.400 0.244 0.000 0.000 0.356
#> SRR1089479 5 0.3409 0.539 0.300 0.000 0.000 0.000 0.700 0.000
#> SRR1073365 3 0.1524 0.814 0.000 0.060 0.932 0.000 0.000 0.008
#> SRR1500306 4 0.1297 0.857 0.000 0.000 0.000 0.948 0.040 0.012
#> SRR1101566 3 0.0520 0.823 0.000 0.008 0.984 0.000 0.000 0.008
#> SRR1350503 3 0.4284 0.733 0.000 0.008 0.748 0.108 0.000 0.136
#> SRR1446007 2 0.0458 0.850 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1102875 2 0.1563 0.822 0.000 0.932 0.056 0.000 0.000 0.012
#> SRR1380293 3 0.5314 0.630 0.000 0.000 0.584 0.264 0.000 0.152
#> SRR1331198 2 0.2431 0.781 0.000 0.860 0.132 0.000 0.000 0.008
#> SRR1092686 3 0.1391 0.825 0.000 0.000 0.944 0.040 0.000 0.016
#> SRR1069421 6 0.2768 0.776 0.000 0.012 0.156 0.000 0.000 0.832
#> SRR1341650 3 0.2420 0.806 0.000 0.000 0.884 0.040 0.000 0.076
#> SRR1357276 3 0.5977 0.589 0.000 0.000 0.556 0.264 0.032 0.148
#> SRR1498374 2 0.0260 0.854 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1093721 3 0.0520 0.822 0.000 0.008 0.984 0.000 0.000 0.008
#> SRR1464660 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1402051 6 0.2482 0.776 0.000 0.004 0.148 0.000 0.000 0.848
#> SRR1488734 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1082616 6 0.2260 0.774 0.000 0.000 0.140 0.000 0.000 0.860
#> SRR1099427 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1453093 6 0.2969 0.753 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1357064 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR811237 6 0.3450 0.772 0.000 0.188 0.032 0.000 0.000 0.780
#> SRR1100848 3 0.1410 0.821 0.000 0.004 0.944 0.008 0.000 0.044
#> SRR1346755 3 0.2062 0.811 0.000 0.008 0.900 0.004 0.000 0.088
#> SRR1472529 3 0.3110 0.640 0.000 0.196 0.792 0.000 0.000 0.012
#> SRR1398905 4 0.3390 0.541 0.000 0.000 0.000 0.704 0.296 0.000
#> SRR1082733 2 0.0937 0.845 0.000 0.960 0.040 0.000 0.000 0.000
#> SRR1308035 2 0.2219 0.740 0.000 0.864 0.136 0.000 0.000 0.000
#> SRR1466445 6 0.4989 0.665 0.000 0.140 0.220 0.000 0.000 0.640
#> SRR1359080 2 0.4088 0.495 0.000 0.616 0.368 0.000 0.000 0.016
#> SRR1455825 2 0.0260 0.855 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1389300 2 0.0260 0.853 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR812246 3 0.2904 0.797 0.000 0.008 0.852 0.112 0.000 0.028
#> SRR1076632 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1415567 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1331900 2 0.1471 0.827 0.000 0.932 0.064 0.000 0.000 0.004
#> SRR1452099 3 0.2527 0.805 0.000 0.000 0.876 0.040 0.000 0.084
#> SRR1352346 1 0.1556 0.900 0.920 0.000 0.000 0.000 0.080 0.000
#> SRR1364034 2 0.0260 0.853 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1086046 6 0.3563 0.607 0.000 0.000 0.336 0.000 0.000 0.664
#> SRR1407226 4 0.2003 0.815 0.000 0.000 0.000 0.884 0.116 0.000
#> SRR1319363 4 0.0790 0.860 0.000 0.000 0.000 0.968 0.000 0.032
#> SRR1446961 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1486650 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1454785 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1092329 6 0.2969 0.753 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1091476 3 0.4358 0.731 0.000 0.008 0.740 0.108 0.000 0.144
#> SRR1073775 2 0.0260 0.854 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1366873 2 0.2257 0.790 0.000 0.876 0.116 0.000 0.000 0.008
#> SRR1398114 2 0.4172 0.313 0.000 0.564 0.424 0.004 0.000 0.008
#> SRR1089950 4 0.1391 0.854 0.000 0.000 0.000 0.944 0.040 0.016
#> SRR1433272 3 0.1951 0.809 0.000 0.016 0.908 0.000 0.000 0.076
#> SRR1075314 6 0.2664 0.782 0.000 0.016 0.136 0.000 0.000 0.848
#> SRR1085590 6 0.2996 0.751 0.000 0.228 0.000 0.000 0.000 0.772
#> SRR1100752 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1391494 3 0.1434 0.815 0.000 0.048 0.940 0.000 0.000 0.012
#> SRR1333263 6 0.3202 0.763 0.000 0.024 0.176 0.000 0.000 0.800
#> SRR1310231 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1094144 6 0.4316 0.605 0.000 0.000 0.312 0.040 0.000 0.648
#> SRR1092160 3 0.0725 0.820 0.000 0.012 0.976 0.000 0.000 0.012
#> SRR1320300 2 0.0146 0.856 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1322747 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1432719 3 0.0520 0.822 0.000 0.008 0.984 0.000 0.000 0.008
#> SRR1100728 3 0.2420 0.806 0.000 0.000 0.884 0.040 0.000 0.076
#> SRR1087511 3 0.1866 0.812 0.000 0.008 0.908 0.000 0.000 0.084
#> SRR1470336 5 0.1556 0.887 0.080 0.000 0.000 0.000 0.920 0.000
#> SRR1322536 6 0.2750 0.691 0.000 0.000 0.020 0.136 0.000 0.844
#> SRR1100824 4 0.0937 0.856 0.000 0.000 0.000 0.960 0.040 0.000
#> SRR1085951 6 0.2790 0.784 0.000 0.024 0.132 0.000 0.000 0.844
#> SRR1322046 3 0.1555 0.826 0.000 0.008 0.940 0.040 0.000 0.012
#> SRR1316420 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1070913 2 0.2389 0.784 0.000 0.864 0.128 0.000 0.000 0.008
#> SRR1345806 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1313872 3 0.2730 0.700 0.000 0.152 0.836 0.000 0.000 0.012
#> SRR1337666 3 0.2961 0.803 0.000 0.008 0.840 0.020 0.000 0.132
#> SRR1076823 4 0.1267 0.850 0.000 0.000 0.000 0.940 0.000 0.060
#> SRR1093954 2 0.0260 0.853 0.000 0.992 0.008 0.000 0.000 0.000
#> SRR1451921 6 0.4462 0.645 0.000 0.000 0.136 0.152 0.000 0.712
#> SRR1491257 5 0.0363 0.944 0.000 0.000 0.000 0.012 0.988 0.000
#> SRR1416979 6 0.2996 0.749 0.000 0.228 0.000 0.000 0.000 0.772
#> SRR1419015 4 0.0363 0.854 0.000 0.000 0.012 0.988 0.000 0.000
#> SRR817649 3 0.5283 0.628 0.000 0.000 0.588 0.264 0.000 0.148
#> SRR1466376 2 0.0146 0.856 0.000 0.996 0.000 0.000 0.000 0.004
#> SRR1392055 3 0.2389 0.805 0.000 0.008 0.864 0.000 0.000 0.128
#> SRR1120913 2 0.0458 0.850 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1120869 3 0.3819 0.785 0.000 0.000 0.764 0.064 0.000 0.172
#> SRR1319419 3 0.1934 0.829 0.000 0.000 0.916 0.040 0.000 0.044
#> SRR816495 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR818694 6 0.2996 0.749 0.000 0.228 0.000 0.000 0.000 0.772
#> SRR1465653 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1475952 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1465040 2 0.2003 0.760 0.000 0.884 0.000 0.000 0.000 0.116
#> SRR1088461 3 0.1442 0.826 0.000 0.004 0.944 0.040 0.000 0.012
#> SRR810129 6 0.3782 0.785 0.000 0.124 0.096 0.000 0.000 0.780
#> SRR1400141 3 0.4465 0.742 0.000 0.000 0.712 0.144 0.000 0.144
#> SRR1349585 1 0.3515 0.527 0.676 0.000 0.000 0.000 0.324 0.000
#> SRR1437576 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR814407 4 0.3860 0.129 0.000 0.000 0.000 0.528 0.472 0.000
#> SRR1332403 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1099598 3 0.2250 0.812 0.000 0.000 0.896 0.040 0.000 0.064
#> SRR1327723 2 0.3447 0.721 0.000 0.800 0.164 0.024 0.000 0.012
#> SRR1392525 3 0.2420 0.806 0.000 0.000 0.884 0.040 0.000 0.076
#> SRR1320536 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 3 0.1297 0.808 0.000 0.040 0.948 0.000 0.000 0.012
#> SRR1351390 4 0.1682 0.836 0.000 0.000 0.052 0.928 0.000 0.020
#> SRR1309141 3 0.3083 0.800 0.000 0.000 0.828 0.040 0.000 0.132
#> SRR1452803 3 0.2389 0.807 0.000 0.008 0.864 0.000 0.000 0.128
#> SRR811631 2 0.0458 0.850 0.000 0.984 0.000 0.000 0.000 0.016
#> SRR1485563 3 0.4166 0.770 0.000 0.000 0.728 0.076 0.000 0.196
#> SRR1311531 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1353076 3 0.4462 0.746 0.000 0.000 0.712 0.152 0.000 0.136
#> SRR1480831 3 0.4019 0.733 0.000 0.112 0.792 0.040 0.000 0.056
#> SRR1083892 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR809873 4 0.1327 0.848 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1341854 2 0.3373 0.621 0.000 0.744 0.248 0.000 0.000 0.008
#> SRR1399335 3 0.3266 0.803 0.000 0.008 0.824 0.036 0.000 0.132
#> SRR1464209 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1389886 2 0.0260 0.853 0.000 0.992 0.000 0.000 0.000 0.008
#> SRR1400730 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1448008 6 0.3390 0.675 0.000 0.296 0.000 0.000 0.000 0.704
#> SRR1087606 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1445111 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR816865 6 0.2969 0.753 0.000 0.224 0.000 0.000 0.000 0.776
#> SRR1323360 2 0.3288 0.598 0.000 0.724 0.276 0.000 0.000 0.000
#> SRR1417364 3 0.0717 0.821 0.000 0.008 0.976 0.000 0.000 0.016
#> SRR1480329 3 0.5425 0.575 0.000 0.000 0.552 0.300 0.000 0.148
#> SRR1403322 4 0.1327 0.848 0.000 0.000 0.000 0.936 0.000 0.064
#> SRR1093625 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.4066 0.468 0.000 0.596 0.392 0.000 0.000 0.012
#> SRR1082035 5 0.0000 0.955 0.000 0.000 0.000 0.000 1.000 0.000
#> SRR1393046 2 0.0000 0.856 0.000 1.000 0.000 0.000 0.000 0.000
#> SRR1466663 3 0.2776 0.811 0.000 0.000 0.860 0.088 0.000 0.052
#> SRR1384456 1 0.0000 0.958 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "mclust"]
# you can also extract it by
# res = res_list["ATC:mclust"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17467 rows and 159 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 0.998 0.999 0.4256 0.576 0.576
#> 3 3 0.607 0.645 0.821 0.4916 0.755 0.574
#> 4 4 0.474 0.532 0.739 0.1145 0.767 0.462
#> 5 5 0.476 0.534 0.698 0.0382 0.866 0.609
#> 6 6 0.502 0.501 0.707 0.0395 0.925 0.725
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
#> SRR810713 2 0.0000 0.998 0.000 1.000
#> SRR808862 1 0.0000 1.000 1.000 0.000
#> SRR1500382 2 0.0000 0.998 0.000 1.000
#> SRR1322683 2 0.0000 0.998 0.000 1.000
#> SRR1329811 1 0.0000 1.000 1.000 0.000
#> SRR1087297 2 0.0000 0.998 0.000 1.000
#> SRR1072626 2 0.0000 0.998 0.000 1.000
#> SRR1407428 1 0.0000 1.000 1.000 0.000
#> SRR1321029 2 0.0000 0.998 0.000 1.000
#> SRR1500282 1 0.0000 1.000 1.000 0.000
#> SRR1100496 2 0.0000 0.998 0.000 1.000
#> SRR1308778 2 0.0000 0.998 0.000 1.000
#> SRR1445304 2 0.0000 0.998 0.000 1.000
#> SRR1099378 1 0.0000 1.000 1.000 0.000
#> SRR1347412 1 0.0000 1.000 1.000 0.000
#> SRR1099694 2 0.0000 0.998 0.000 1.000
#> SRR1088365 2 0.0000 0.998 0.000 1.000
#> SRR1325752 2 0.0000 0.998 0.000 1.000
#> SRR1416713 2 0.0000 0.998 0.000 1.000
#> SRR1074474 1 0.0000 1.000 1.000 0.000
#> SRR1469369 2 0.0000 0.998 0.000 1.000
#> SRR1400507 2 0.0000 0.998 0.000 1.000
#> SRR1378179 2 0.0000 0.998 0.000 1.000
#> SRR1377905 2 0.0000 0.998 0.000 1.000
#> SRR1089479 1 0.0000 1.000 1.000 0.000
#> SRR1073365 2 0.0000 0.998 0.000 1.000
#> SRR1500306 1 0.0000 1.000 1.000 0.000
#> SRR1101566 2 0.0000 0.998 0.000 1.000
#> SRR1350503 2 0.0000 0.998 0.000 1.000
#> SRR1446007 2 0.0000 0.998 0.000 1.000
#> SRR1102875 2 0.0000 0.998 0.000 1.000
#> SRR1380293 2 0.0000 0.998 0.000 1.000
#> SRR1331198 2 0.0000 0.998 0.000 1.000
#> SRR1092686 2 0.0000 0.998 0.000 1.000
#> SRR1069421 2 0.0000 0.998 0.000 1.000
#> SRR1341650 2 0.0000 0.998 0.000 1.000
#> SRR1357276 2 0.5178 0.870 0.116 0.884
#> SRR1498374 2 0.0000 0.998 0.000 1.000
#> SRR1093721 2 0.0000 0.998 0.000 1.000
#> SRR1464660 1 0.0000 1.000 1.000 0.000
#> SRR1402051 2 0.0000 0.998 0.000 1.000
#> SRR1488734 2 0.0000 0.998 0.000 1.000
#> SRR1082616 1 0.0000 1.000 1.000 0.000
#> SRR1099427 2 0.0000 0.998 0.000 1.000
#> SRR1453093 2 0.0000 0.998 0.000 1.000
#> SRR1357064 1 0.0000 1.000 1.000 0.000
#> SRR811237 2 0.0000 0.998 0.000 1.000
#> SRR1100848 2 0.0000 0.998 0.000 1.000
#> SRR1346755 2 0.0000 0.998 0.000 1.000
#> SRR1472529 2 0.0000 0.998 0.000 1.000
#> SRR1398905 1 0.0000 1.000 1.000 0.000
#> SRR1082733 2 0.0000 0.998 0.000 1.000
#> SRR1308035 2 0.0000 0.998 0.000 1.000
#> SRR1466445 2 0.0000 0.998 0.000 1.000
#> SRR1359080 2 0.0000 0.998 0.000 1.000
#> SRR1455825 2 0.0000 0.998 0.000 1.000
#> SRR1389300 2 0.0000 0.998 0.000 1.000
#> SRR812246 2 0.0000 0.998 0.000 1.000
#> SRR1076632 2 0.0000 0.998 0.000 1.000
#> SRR1415567 1 0.0000 1.000 1.000 0.000
#> SRR1331900 2 0.0000 0.998 0.000 1.000
#> SRR1452099 2 0.0000 0.998 0.000 1.000
#> SRR1352346 1 0.0000 1.000 1.000 0.000
#> SRR1364034 2 0.0000 0.998 0.000 1.000
#> SRR1086046 1 0.0000 1.000 1.000 0.000
#> SRR1407226 1 0.0000 1.000 1.000 0.000
#> SRR1319363 1 0.0000 1.000 1.000 0.000
#> SRR1446961 2 0.0000 0.998 0.000 1.000
#> SRR1486650 1 0.0000 1.000 1.000 0.000
#> SRR1470152 1 0.0000 1.000 1.000 0.000
#> SRR1454785 2 0.0000 0.998 0.000 1.000
#> SRR1092329 2 0.0000 0.998 0.000 1.000
#> SRR1091476 1 0.0000 1.000 1.000 0.000
#> SRR1073775 2 0.0000 0.998 0.000 1.000
#> SRR1366873 2 0.0000 0.998 0.000 1.000
#> SRR1398114 2 0.0000 0.998 0.000 1.000
#> SRR1089950 1 0.0000 1.000 1.000 0.000
#> SRR1433272 2 0.0000 0.998 0.000 1.000
#> SRR1075314 1 0.0000 1.000 1.000 0.000
#> SRR1085590 2 0.0000 0.998 0.000 1.000
#> SRR1100752 2 0.0000 0.998 0.000 1.000
#> SRR1391494 2 0.0000 0.998 0.000 1.000
#> SRR1333263 2 0.0000 0.998 0.000 1.000
#> SRR1310231 2 0.0000 0.998 0.000 1.000
#> SRR1094144 2 0.0000 0.998 0.000 1.000
#> SRR1092160 2 0.0000 0.998 0.000 1.000
#> SRR1320300 2 0.0000 0.998 0.000 1.000
#> SRR1322747 2 0.0000 0.998 0.000 1.000
#> SRR1432719 2 0.0000 0.998 0.000 1.000
#> SRR1100728 2 0.0000 0.998 0.000 1.000
#> SRR1087511 2 0.0000 0.998 0.000 1.000
#> SRR1470336 1 0.0000 1.000 1.000 0.000
#> SRR1322536 1 0.0000 1.000 1.000 0.000
#> SRR1100824 1 0.0000 1.000 1.000 0.000
#> SRR1085951 1 0.0000 1.000 1.000 0.000
#> SRR1322046 2 0.0000 0.998 0.000 1.000
#> SRR1316420 1 0.0000 1.000 1.000 0.000
#> SRR1070913 2 0.0000 0.998 0.000 1.000
#> SRR1345806 2 0.0000 0.998 0.000 1.000
#> SRR1313872 2 0.0000 0.998 0.000 1.000
#> SRR1337666 2 0.3114 0.941 0.056 0.944
#> SRR1076823 1 0.0000 1.000 1.000 0.000
#> SRR1093954 2 0.0000 0.998 0.000 1.000
#> SRR1451921 1 0.0000 1.000 1.000 0.000
#> SRR1491257 1 0.0000 1.000 1.000 0.000
#> SRR1416979 2 0.0000 0.998 0.000 1.000
#> SRR1419015 1 0.0000 1.000 1.000 0.000
#> SRR817649 2 0.0000 0.998 0.000 1.000
#> SRR1466376 2 0.0000 0.998 0.000 1.000
#> SRR1392055 2 0.0000 0.998 0.000 1.000
#> SRR1120913 2 0.0000 0.998 0.000 1.000
#> SRR1120869 2 0.0000 0.998 0.000 1.000
#> SRR1319419 2 0.0000 0.998 0.000 1.000
#> SRR816495 2 0.0000 0.998 0.000 1.000
#> SRR818694 2 0.0000 0.998 0.000 1.000
#> SRR1465653 1 0.0000 1.000 1.000 0.000
#> SRR1475952 1 0.0000 1.000 1.000 0.000
#> SRR1465040 2 0.0000 0.998 0.000 1.000
#> SRR1088461 2 0.0000 0.998 0.000 1.000
#> SRR810129 2 0.0000 0.998 0.000 1.000
#> SRR1400141 2 0.0000 0.998 0.000 1.000
#> SRR1349585 1 0.0000 1.000 1.000 0.000
#> SRR1437576 2 0.0000 0.998 0.000 1.000
#> SRR814407 1 0.0000 1.000 1.000 0.000
#> SRR1332403 2 0.0000 0.998 0.000 1.000
#> SRR1099598 2 0.0000 0.998 0.000 1.000
#> SRR1327723 2 0.0000 0.998 0.000 1.000
#> SRR1392525 2 0.0000 0.998 0.000 1.000
#> SRR1320536 1 0.0000 1.000 1.000 0.000
#> SRR1083824 2 0.0000 0.998 0.000 1.000
#> SRR1351390 1 0.0000 1.000 1.000 0.000
#> SRR1309141 2 0.0000 0.998 0.000 1.000
#> SRR1452803 2 0.0000 0.998 0.000 1.000
#> SRR811631 2 0.0000 0.998 0.000 1.000
#> SRR1485563 2 0.0000 0.998 0.000 1.000
#> SRR1311531 2 0.0000 0.998 0.000 1.000
#> SRR1353076 2 0.0000 0.998 0.000 1.000
#> SRR1480831 2 0.0000 0.998 0.000 1.000
#> SRR1083892 1 0.0000 1.000 1.000 0.000
#> SRR809873 1 0.0000 1.000 1.000 0.000
#> SRR1341854 2 0.0000 0.998 0.000 1.000
#> SRR1399335 2 0.0000 0.998 0.000 1.000
#> SRR1464209 1 0.0000 1.000 1.000 0.000
#> SRR1389886 2 0.0000 0.998 0.000 1.000
#> SRR1400730 1 0.0000 1.000 1.000 0.000
#> SRR1448008 2 0.0000 0.998 0.000 1.000
#> SRR1087606 1 0.0000 1.000 1.000 0.000
#> SRR1445111 1 0.0000 1.000 1.000 0.000
#> SRR816865 2 0.0000 0.998 0.000 1.000
#> SRR1323360 2 0.0000 0.998 0.000 1.000
#> SRR1417364 2 0.0000 0.998 0.000 1.000
#> SRR1480329 2 0.0376 0.995 0.004 0.996
#> SRR1403322 1 0.0000 1.000 1.000 0.000
#> SRR1093625 1 0.0000 1.000 1.000 0.000
#> SRR1479977 2 0.0000 0.998 0.000 1.000
#> SRR1082035 1 0.0000 1.000 1.000 0.000
#> SRR1393046 2 0.0000 0.998 0.000 1.000
#> SRR1466663 2 0.0000 0.998 0.000 1.000
#> SRR1384456 1 0.0000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 3 0.5760 0.5283 0.000 0.328 0.672
#> SRR808862 1 0.2165 0.9394 0.936 0.064 0.000
#> SRR1500382 2 0.6180 0.5092 0.008 0.660 0.332
#> SRR1322683 3 0.5291 0.6474 0.000 0.268 0.732
#> SRR1329811 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1087297 2 0.5678 0.5386 0.000 0.684 0.316
#> SRR1072626 2 0.2448 0.6542 0.000 0.924 0.076
#> SRR1407428 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1321029 3 0.6111 0.4840 0.000 0.396 0.604
#> SRR1500282 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1100496 2 0.1163 0.6316 0.000 0.972 0.028
#> SRR1308778 2 0.5650 0.5440 0.000 0.688 0.312
#> SRR1445304 3 0.5098 0.6557 0.000 0.248 0.752
#> SRR1099378 1 0.2625 0.9250 0.916 0.084 0.000
#> SRR1347412 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1099694 3 0.5988 0.5326 0.000 0.368 0.632
#> SRR1088365 2 0.5706 0.5411 0.000 0.680 0.320
#> SRR1325752 2 0.3045 0.6491 0.020 0.916 0.064
#> SRR1416713 3 0.2066 0.6376 0.000 0.060 0.940
#> SRR1074474 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1469369 2 0.5397 0.4530 0.000 0.720 0.280
#> SRR1400507 3 0.3551 0.6423 0.000 0.132 0.868
#> SRR1378179 2 0.5650 0.5440 0.000 0.688 0.312
#> SRR1377905 3 0.6291 0.3231 0.000 0.468 0.532
#> SRR1089479 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1073365 3 0.5431 0.2359 0.000 0.284 0.716
#> SRR1500306 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1101566 2 0.2165 0.6534 0.000 0.936 0.064
#> SRR1350503 3 0.5254 0.6270 0.000 0.264 0.736
#> SRR1446007 2 0.5926 0.4950 0.000 0.644 0.356
#> SRR1102875 3 0.5988 0.0197 0.000 0.368 0.632
#> SRR1380293 2 0.5465 0.5689 0.000 0.712 0.288
#> SRR1331198 3 0.5327 0.6445 0.000 0.272 0.728
#> SRR1092686 2 0.5706 0.5380 0.000 0.680 0.320
#> SRR1069421 2 0.1411 0.6271 0.000 0.964 0.036
#> SRR1341650 2 0.1529 0.6452 0.000 0.960 0.040
#> SRR1357276 2 0.5621 0.5485 0.000 0.692 0.308
#> SRR1498374 3 0.5785 0.5857 0.000 0.332 0.668
#> SRR1093721 2 0.6305 -0.2060 0.000 0.516 0.484
#> SRR1464660 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1402051 2 0.5024 0.4361 0.004 0.776 0.220
#> SRR1488734 2 0.5760 0.5201 0.000 0.672 0.328
#> SRR1082616 1 0.2711 0.9210 0.912 0.088 0.000
#> SRR1099427 2 0.2625 0.6532 0.000 0.916 0.084
#> SRR1453093 2 0.4346 0.4946 0.000 0.816 0.184
#> SRR1357064 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR811237 2 0.1529 0.6283 0.000 0.960 0.040
#> SRR1100848 2 0.4121 0.5163 0.000 0.832 0.168
#> SRR1346755 2 0.3752 0.5485 0.000 0.856 0.144
#> SRR1472529 3 0.5327 0.6445 0.000 0.272 0.728
#> SRR1398905 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1082733 3 0.6299 -0.2110 0.000 0.476 0.524
#> SRR1308035 3 0.5216 0.6521 0.000 0.260 0.740
#> SRR1466445 2 0.4974 0.4077 0.000 0.764 0.236
#> SRR1359080 3 0.5621 0.6136 0.000 0.308 0.692
#> SRR1455825 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1389300 2 0.6215 0.3706 0.000 0.572 0.428
#> SRR812246 2 0.1289 0.6294 0.000 0.968 0.032
#> SRR1076632 2 0.2711 0.6535 0.000 0.912 0.088
#> SRR1415567 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1331900 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1452099 2 0.1163 0.6316 0.000 0.972 0.028
#> SRR1352346 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1364034 3 0.6308 -0.2325 0.000 0.492 0.508
#> SRR1086046 1 0.4235 0.8148 0.824 0.176 0.000
#> SRR1407226 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR1319363 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR1446961 3 0.5327 0.6445 0.000 0.272 0.728
#> SRR1486650 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1470152 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1454785 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1092329 2 0.6215 -0.1163 0.000 0.572 0.428
#> SRR1091476 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1073775 3 0.2066 0.6247 0.000 0.060 0.940
#> SRR1366873 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1398114 3 0.6180 -0.1089 0.000 0.416 0.584
#> SRR1089950 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1433272 2 0.6345 0.0218 0.004 0.596 0.400
#> SRR1075314 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1085590 3 0.5291 0.6474 0.000 0.268 0.732
#> SRR1100752 3 0.6244 0.3907 0.000 0.440 0.560
#> SRR1391494 3 0.5327 0.6380 0.000 0.272 0.728
#> SRR1333263 2 0.5098 0.4074 0.000 0.752 0.248
#> SRR1310231 2 0.5760 0.5201 0.000 0.672 0.328
#> SRR1094144 2 0.0424 0.6398 0.000 0.992 0.008
#> SRR1092160 3 0.6154 0.4604 0.000 0.408 0.592
#> SRR1320300 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1322747 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1432719 3 0.5785 0.5283 0.000 0.332 0.668
#> SRR1100728 2 0.1643 0.6450 0.000 0.956 0.044
#> SRR1087511 2 0.0424 0.6398 0.000 0.992 0.008
#> SRR1470336 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1322536 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1100824 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR1085951 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1322046 2 0.6180 0.3808 0.000 0.584 0.416
#> SRR1316420 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1070913 3 0.5327 0.6445 0.000 0.272 0.728
#> SRR1345806 3 0.5465 0.5987 0.000 0.288 0.712
#> SRR1313872 3 0.5882 0.5639 0.000 0.348 0.652
#> SRR1337666 3 0.9379 0.3701 0.216 0.276 0.508
#> SRR1076823 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR1093954 3 0.6204 -0.1231 0.000 0.424 0.576
#> SRR1451921 1 0.2356 0.9343 0.928 0.072 0.000
#> SRR1491257 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR1416979 2 0.6154 -0.0406 0.000 0.592 0.408
#> SRR1419015 1 0.2537 0.9286 0.920 0.080 0.000
#> SRR817649 2 0.4974 0.5977 0.000 0.764 0.236
#> SRR1466376 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1392055 3 0.5254 0.6270 0.000 0.264 0.736
#> SRR1120913 3 0.3941 0.6551 0.000 0.156 0.844
#> SRR1120869 2 0.5760 0.5296 0.000 0.672 0.328
#> SRR1319419 2 0.5760 0.5296 0.000 0.672 0.328
#> SRR816495 3 0.5327 0.6439 0.000 0.272 0.728
#> SRR818694 2 0.6140 -0.0363 0.000 0.596 0.404
#> SRR1465653 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1475952 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1465040 3 0.6126 0.4766 0.000 0.400 0.600
#> SRR1088461 2 0.5497 0.5655 0.000 0.708 0.292
#> SRR810129 3 0.5621 0.6149 0.000 0.308 0.692
#> SRR1400141 2 0.5431 0.5721 0.000 0.716 0.284
#> SRR1349585 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1437576 3 0.5431 0.2201 0.000 0.284 0.716
#> SRR814407 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1332403 3 0.1163 0.6073 0.000 0.028 0.972
#> SRR1099598 2 0.2537 0.6544 0.000 0.920 0.080
#> SRR1327723 2 0.5785 0.5158 0.000 0.668 0.332
#> SRR1392525 2 0.1950 0.6436 0.008 0.952 0.040
#> SRR1320536 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1083824 3 0.5397 0.6445 0.000 0.280 0.720
#> SRR1351390 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1309141 2 0.5948 0.4820 0.000 0.640 0.360
#> SRR1452803 3 0.5363 0.6164 0.000 0.276 0.724
#> SRR811631 3 0.2711 0.6351 0.000 0.088 0.912
#> SRR1485563 2 0.1860 0.6516 0.000 0.948 0.052
#> SRR1311531 3 0.5291 0.6237 0.000 0.268 0.732
#> SRR1353076 2 0.5650 0.5440 0.000 0.688 0.312
#> SRR1480831 2 0.5591 0.5558 0.000 0.696 0.304
#> SRR1083892 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR809873 1 0.2448 0.9315 0.924 0.076 0.000
#> SRR1341854 3 0.2711 0.6216 0.000 0.088 0.912
#> SRR1399335 2 0.6111 0.3886 0.000 0.604 0.396
#> SRR1464209 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1389886 3 0.2261 0.6316 0.000 0.068 0.932
#> SRR1400730 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1448008 2 0.4931 0.4155 0.000 0.768 0.232
#> SRR1087606 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1445111 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR816865 2 0.1411 0.6271 0.000 0.964 0.036
#> SRR1323360 3 0.5216 0.6519 0.000 0.260 0.740
#> SRR1417364 3 0.5859 0.5697 0.000 0.344 0.656
#> SRR1480329 2 0.3112 0.6328 0.056 0.916 0.028
#> SRR1403322 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1479977 3 0.2448 0.6317 0.000 0.076 0.924
#> SRR1082035 1 0.0000 0.9770 1.000 0.000 0.000
#> SRR1393046 3 0.1964 0.6247 0.000 0.056 0.944
#> SRR1466663 2 0.2066 0.6544 0.000 0.940 0.060
#> SRR1384456 1 0.0000 0.9770 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 3 0.4599 0.6374 0.000 0.248 0.736 0.016
#> SRR808862 4 0.4941 0.7819 0.436 0.000 0.000 0.564
#> SRR1500382 3 0.5624 0.6742 0.060 0.120 0.768 0.052
#> SRR1322683 2 0.2623 0.7162 0.000 0.908 0.064 0.028
#> SRR1329811 1 0.4964 -0.2926 0.616 0.000 0.004 0.380
#> SRR1087297 3 0.1722 0.7258 0.000 0.048 0.944 0.008
#> SRR1072626 2 0.7354 0.2959 0.000 0.452 0.388 0.160
#> SRR1407428 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1321029 2 0.5008 0.6216 0.000 0.732 0.228 0.040
#> SRR1500282 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1100496 2 0.7704 0.3628 0.000 0.432 0.232 0.336
#> SRR1308778 3 0.2282 0.7270 0.000 0.052 0.924 0.024
#> SRR1445304 2 0.3105 0.6896 0.000 0.856 0.140 0.004
#> SRR1099378 4 0.5597 0.7631 0.464 0.000 0.020 0.516
#> SRR1347412 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1099694 2 0.4839 0.6632 0.000 0.764 0.184 0.052
#> SRR1088365 2 0.6192 0.3003 0.000 0.512 0.436 0.052
#> SRR1325752 3 0.6782 0.0632 0.056 0.016 0.468 0.460
#> SRR1416713 2 0.1174 0.7111 0.000 0.968 0.020 0.012
#> SRR1074474 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1469369 3 0.4913 0.6913 0.020 0.152 0.788 0.040
#> SRR1400507 2 0.2124 0.7099 0.000 0.924 0.068 0.008
#> SRR1378179 3 0.2216 0.7196 0.000 0.092 0.908 0.000
#> SRR1377905 2 0.5267 0.6493 0.000 0.740 0.184 0.076
#> SRR1089479 1 0.0469 0.6729 0.988 0.000 0.012 0.000
#> SRR1073365 2 0.5231 0.4910 0.000 0.676 0.296 0.028
#> SRR1500306 1 0.5217 -0.2836 0.608 0.000 0.012 0.380
#> SRR1101566 3 0.4352 0.6988 0.000 0.104 0.816 0.080
#> SRR1350503 3 0.4831 0.5774 0.000 0.280 0.704 0.016
#> SRR1446007 2 0.5352 0.4102 0.000 0.596 0.388 0.016
#> SRR1102875 2 0.5343 0.4580 0.000 0.656 0.316 0.028
#> SRR1380293 3 0.2060 0.7292 0.000 0.052 0.932 0.016
#> SRR1331198 2 0.3528 0.6540 0.000 0.808 0.192 0.000
#> SRR1092686 3 0.2918 0.7212 0.000 0.116 0.876 0.008
#> SRR1069421 2 0.7575 0.4069 0.000 0.444 0.200 0.356
#> SRR1341650 3 0.5911 0.6101 0.000 0.112 0.692 0.196
#> SRR1357276 4 0.8566 0.2661 0.188 0.048 0.328 0.436
#> SRR1498374 2 0.5035 0.6413 0.000 0.744 0.204 0.052
#> SRR1093721 3 0.5203 0.6110 0.000 0.232 0.720 0.048
#> SRR1464660 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR1402051 2 0.6882 0.5321 0.024 0.532 0.056 0.388
#> SRR1488734 3 0.1716 0.7250 0.000 0.064 0.936 0.000
#> SRR1082616 4 0.5217 0.7427 0.380 0.000 0.012 0.608
#> SRR1099427 3 0.2830 0.7234 0.000 0.040 0.900 0.060
#> SRR1453093 2 0.5865 0.5932 0.000 0.612 0.048 0.340
#> SRR1357064 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR811237 2 0.6894 0.5232 0.000 0.536 0.120 0.344
#> SRR1100848 2 0.7289 0.5054 0.000 0.536 0.212 0.252
#> SRR1346755 3 0.7373 0.2793 0.000 0.316 0.500 0.184
#> SRR1472529 2 0.3105 0.6904 0.000 0.856 0.140 0.004
#> SRR1398905 1 0.5217 -0.2836 0.608 0.000 0.012 0.380
#> SRR1082733 2 0.5339 0.4066 0.000 0.624 0.356 0.020
#> SRR1308035 2 0.2489 0.7155 0.000 0.912 0.068 0.020
#> SRR1466445 2 0.5546 0.6371 0.000 0.680 0.052 0.268
#> SRR1359080 2 0.4877 0.6487 0.000 0.752 0.204 0.044
#> SRR1455825 2 0.1356 0.7064 0.000 0.960 0.008 0.032
#> SRR1389300 2 0.5040 0.4039 0.000 0.628 0.364 0.008
#> SRR812246 3 0.6265 0.5688 0.000 0.072 0.588 0.340
#> SRR1076632 3 0.4188 0.7199 0.000 0.064 0.824 0.112
#> SRR1415567 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1331900 2 0.1488 0.7062 0.000 0.956 0.012 0.032
#> SRR1452099 3 0.7717 0.2622 0.000 0.232 0.424 0.344
#> SRR1352346 1 0.0000 0.6737 1.000 0.000 0.000 0.000
#> SRR1364034 2 0.5478 0.4215 0.000 0.628 0.344 0.028
#> SRR1086046 4 0.6249 0.6444 0.336 0.000 0.072 0.592
#> SRR1407226 1 0.5488 -0.6221 0.532 0.000 0.016 0.452
#> SRR1319363 4 0.5372 0.7912 0.444 0.000 0.012 0.544
#> SRR1446961 3 0.4948 0.3173 0.000 0.440 0.560 0.000
#> SRR1486650 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1470152 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR1454785 2 0.1489 0.7031 0.000 0.952 0.004 0.044
#> SRR1092329 2 0.4635 0.6716 0.000 0.756 0.028 0.216
#> SRR1091476 1 0.5741 -0.5760 0.536 0.004 0.020 0.440
#> SRR1073775 2 0.2408 0.7056 0.000 0.920 0.044 0.036
#> SRR1366873 2 0.3550 0.6856 0.000 0.860 0.096 0.044
#> SRR1398114 2 0.5478 0.4141 0.000 0.628 0.344 0.028
#> SRR1089950 1 0.4964 -0.2926 0.616 0.000 0.004 0.380
#> SRR1433272 2 0.5665 0.6474 0.000 0.716 0.176 0.108
#> SRR1075314 1 0.5000 -0.6507 0.504 0.000 0.000 0.496
#> SRR1085590 2 0.2908 0.7181 0.000 0.896 0.064 0.040
#> SRR1100752 2 0.5072 0.6379 0.000 0.740 0.208 0.052
#> SRR1391494 2 0.3958 0.6873 0.000 0.824 0.144 0.032
#> SRR1333263 2 0.5471 0.6429 0.000 0.684 0.048 0.268
#> SRR1310231 3 0.2124 0.7287 0.000 0.068 0.924 0.008
#> SRR1094144 2 0.7768 0.3099 0.000 0.428 0.312 0.260
#> SRR1092160 2 0.5203 0.6174 0.000 0.720 0.232 0.048
#> SRR1320300 2 0.2675 0.6995 0.000 0.908 0.048 0.044
#> SRR1322747 2 0.1489 0.7031 0.000 0.952 0.004 0.044
#> SRR1432719 3 0.4535 0.6466 0.000 0.240 0.744 0.016
#> SRR1100728 3 0.7520 0.2435 0.000 0.280 0.492 0.228
#> SRR1087511 3 0.6224 0.5806 0.000 0.144 0.668 0.188
#> SRR1470336 1 0.0937 0.6693 0.976 0.000 0.012 0.012
#> SRR1322536 1 0.5000 -0.6507 0.504 0.000 0.000 0.496
#> SRR1100824 4 0.5506 0.7499 0.472 0.000 0.016 0.512
#> SRR1085951 4 0.5000 0.6172 0.500 0.000 0.000 0.500
#> SRR1322046 2 0.5110 0.4755 0.000 0.656 0.328 0.016
#> SRR1316420 1 0.0804 0.6650 0.980 0.000 0.008 0.012
#> SRR1070913 2 0.3217 0.6952 0.000 0.860 0.128 0.012
#> SRR1345806 3 0.5237 0.4985 0.000 0.356 0.628 0.016
#> SRR1313872 2 0.4267 0.6619 0.000 0.788 0.188 0.024
#> SRR1337666 3 0.7992 0.4469 0.212 0.132 0.580 0.076
#> SRR1076823 4 0.5372 0.7912 0.444 0.000 0.012 0.544
#> SRR1093954 2 0.5478 0.4215 0.000 0.628 0.344 0.028
#> SRR1451921 4 0.5105 0.7901 0.432 0.000 0.004 0.564
#> SRR1491257 1 0.5790 -0.3016 0.608 0.016 0.016 0.360
#> SRR1416979 2 0.5472 0.6407 0.000 0.676 0.044 0.280
#> SRR1419015 4 0.5472 0.7921 0.440 0.000 0.016 0.544
#> SRR817649 3 0.2845 0.7198 0.000 0.028 0.896 0.076
#> SRR1466376 2 0.1489 0.7051 0.000 0.952 0.004 0.044
#> SRR1392055 3 0.4831 0.5774 0.000 0.280 0.704 0.016
#> SRR1120913 2 0.0937 0.7143 0.000 0.976 0.012 0.012
#> SRR1120869 3 0.2149 0.7208 0.000 0.088 0.912 0.000
#> SRR1319419 3 0.2216 0.7207 0.000 0.092 0.908 0.000
#> SRR816495 3 0.4855 0.4049 0.000 0.400 0.600 0.000
#> SRR818694 2 0.5279 0.6555 0.000 0.704 0.044 0.252
#> SRR1465653 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR1475952 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1465040 2 0.4784 0.6907 0.000 0.788 0.100 0.112
#> SRR1088461 3 0.4964 0.5504 0.000 0.244 0.724 0.032
#> SRR810129 2 0.4070 0.6935 0.000 0.824 0.132 0.044
#> SRR1400141 3 0.1716 0.7278 0.000 0.064 0.936 0.000
#> SRR1349585 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR1437576 2 0.4755 0.5996 0.000 0.760 0.200 0.040
#> SRR814407 1 0.5217 -0.2836 0.608 0.000 0.012 0.380
#> SRR1332403 2 0.2759 0.6983 0.000 0.904 0.052 0.044
#> SRR1099598 3 0.5321 0.6282 0.000 0.140 0.748 0.112
#> SRR1327723 3 0.2868 0.6980 0.000 0.136 0.864 0.000
#> SRR1392525 3 0.6226 0.5656 0.004 0.064 0.612 0.320
#> SRR1320536 1 0.1677 0.6678 0.948 0.000 0.012 0.040
#> SRR1083824 2 0.4661 0.5999 0.000 0.728 0.256 0.016
#> SRR1351390 1 0.5099 -0.2902 0.612 0.000 0.008 0.380
#> SRR1309141 3 0.2676 0.7263 0.000 0.092 0.896 0.012
#> SRR1452803 3 0.4720 0.5980 0.000 0.264 0.720 0.016
#> SRR811631 2 0.0524 0.7131 0.000 0.988 0.008 0.004
#> SRR1485563 3 0.4907 0.6736 0.000 0.060 0.764 0.176
#> SRR1311531 3 0.4679 0.5004 0.000 0.352 0.648 0.000
#> SRR1353076 3 0.2737 0.7135 0.000 0.104 0.888 0.008
#> SRR1480831 3 0.5837 0.1012 0.000 0.400 0.564 0.036
#> SRR1083892 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR809873 4 0.5337 0.7920 0.424 0.000 0.012 0.564
#> SRR1341854 2 0.3399 0.6860 0.000 0.868 0.092 0.040
#> SRR1399335 3 0.3032 0.7152 0.000 0.124 0.868 0.008
#> SRR1464209 1 0.4819 -0.1744 0.652 0.000 0.004 0.344
#> SRR1389886 2 0.1284 0.7116 0.000 0.964 0.012 0.024
#> SRR1400730 1 0.1109 0.6526 0.968 0.000 0.004 0.028
#> SRR1448008 2 0.5658 0.6079 0.000 0.632 0.040 0.328
#> SRR1087606 1 0.0188 0.6735 0.996 0.000 0.004 0.000
#> SRR1445111 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR816865 2 0.7449 0.4269 0.000 0.464 0.180 0.356
#> SRR1323360 2 0.3105 0.6899 0.000 0.856 0.140 0.004
#> SRR1417364 3 0.5766 0.3402 0.000 0.404 0.564 0.032
#> SRR1480329 3 0.6031 0.4412 0.016 0.028 0.608 0.348
#> SRR1403322 1 0.4992 -0.6055 0.524 0.000 0.000 0.476
#> SRR1093625 1 0.2021 0.6636 0.932 0.000 0.012 0.056
#> SRR1479977 2 0.3335 0.6649 0.000 0.856 0.128 0.016
#> SRR1082035 1 0.2048 0.6148 0.928 0.000 0.008 0.064
#> SRR1393046 2 0.0804 0.7111 0.000 0.980 0.008 0.012
#> SRR1466663 3 0.3312 0.7221 0.000 0.052 0.876 0.072
#> SRR1384456 1 0.2021 0.6636 0.932 0.000 0.012 0.056
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> SRR810713 3 0.3366 0.7251 0.000 0.116 0.844 0.008 0.032
#> SRR808862 4 0.4808 0.7486 0.132 0.004 0.004 0.748 0.112
#> SRR1500382 3 0.6384 0.4790 0.000 0.016 0.568 0.156 0.260
#> SRR1322683 2 0.4746 0.3688 0.000 0.744 0.120 0.004 0.132
#> SRR1329811 4 0.4597 0.6812 0.260 0.000 0.000 0.696 0.044
#> SRR1087297 3 0.3662 0.6153 0.000 0.000 0.744 0.004 0.252
#> SRR1072626 3 0.6225 -0.0340 0.000 0.200 0.544 0.000 0.256
#> SRR1407428 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR1321029 3 0.5428 0.4887 0.000 0.248 0.668 0.024 0.060
#> SRR1500282 1 0.1106 0.8398 0.964 0.000 0.000 0.024 0.012
#> SRR1100496 5 0.7168 0.6678 0.000 0.352 0.236 0.020 0.392
#> SRR1308778 3 0.3809 0.6158 0.000 0.008 0.736 0.000 0.256
#> SRR1445304 2 0.5258 0.4014 0.000 0.704 0.176 0.012 0.108
#> SRR1099378 4 0.4669 0.7566 0.184 0.004 0.016 0.752 0.044
#> SRR1347412 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR1099694 2 0.6250 0.2814 0.000 0.592 0.264 0.024 0.120
#> SRR1088365 2 0.6688 -0.2964 0.000 0.460 0.316 0.004 0.220
#> SRR1325752 4 0.6372 0.1512 0.004 0.000 0.392 0.460 0.144
#> SRR1416713 2 0.2408 0.4875 0.000 0.892 0.096 0.008 0.004
#> SRR1074474 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR1469369 3 0.3457 0.7287 0.000 0.084 0.852 0.016 0.048
#> SRR1400507 2 0.4394 0.4057 0.000 0.716 0.256 0.012 0.016
#> SRR1378179 3 0.2060 0.7289 0.000 0.016 0.924 0.008 0.052
#> SRR1377905 2 0.6452 0.2097 0.000 0.572 0.260 0.024 0.144
#> SRR1089479 1 0.2852 0.8161 0.828 0.000 0.000 0.172 0.000
#> SRR1073365 2 0.5246 0.1405 0.000 0.512 0.452 0.024 0.012
#> SRR1500306 4 0.4860 0.6918 0.292 0.028 0.000 0.668 0.012
#> SRR1101566 3 0.1728 0.7394 0.000 0.036 0.940 0.004 0.020
#> SRR1350503 3 0.4246 0.7154 0.000 0.096 0.808 0.032 0.064
#> SRR1446007 2 0.6978 -0.1130 0.000 0.508 0.296 0.040 0.156
#> SRR1102875 2 0.4752 0.2771 0.000 0.700 0.256 0.028 0.016
#> SRR1380293 3 0.3861 0.6120 0.000 0.008 0.728 0.000 0.264
#> SRR1331198 2 0.3944 0.4284 0.000 0.720 0.272 0.004 0.004
#> SRR1092686 3 0.1525 0.7383 0.000 0.036 0.948 0.004 0.012
#> SRR1069421 5 0.6832 0.6925 0.000 0.364 0.240 0.004 0.392
#> SRR1341650 3 0.3967 0.6448 0.000 0.020 0.772 0.008 0.200
#> SRR1357276 4 0.6700 0.3693 0.036 0.000 0.300 0.536 0.128
#> SRR1498374 2 0.6417 0.2185 0.000 0.576 0.260 0.024 0.140
#> SRR1093721 3 0.3018 0.7249 0.000 0.084 0.872 0.008 0.036
#> SRR1464660 1 0.4269 0.7888 0.756 0.000 0.000 0.188 0.056
#> SRR1402051 5 0.7173 0.6530 0.000 0.392 0.104 0.072 0.432
#> SRR1488734 3 0.4169 0.6204 0.000 0.000 0.732 0.028 0.240
#> SRR1082616 4 0.5800 0.7123 0.128 0.004 0.024 0.680 0.164
#> SRR1099427 3 0.1894 0.7308 0.000 0.000 0.920 0.008 0.072
#> SRR1453093 5 0.6129 0.6921 0.000 0.420 0.128 0.000 0.452
#> SRR1357064 1 0.4028 0.8003 0.776 0.000 0.000 0.176 0.048
#> SRR811237 5 0.6381 0.7487 0.000 0.384 0.168 0.000 0.448
#> SRR1100848 3 0.5917 0.2911 0.000 0.132 0.564 0.000 0.304
#> SRR1346755 3 0.4059 0.6740 0.000 0.052 0.776 0.000 0.172
#> SRR1472529 2 0.3845 0.4636 0.000 0.760 0.224 0.004 0.012
#> SRR1398905 4 0.4657 0.6936 0.296 0.036 0.000 0.668 0.000
#> SRR1082733 2 0.5679 0.1823 0.000 0.556 0.376 0.052 0.016
#> SRR1308035 2 0.4277 0.4412 0.000 0.784 0.112 0.004 0.100
#> SRR1466445 2 0.5951 -0.4327 0.000 0.520 0.116 0.000 0.364
#> SRR1359080 2 0.5940 0.3282 0.000 0.616 0.272 0.024 0.088
#> SRR1455825 2 0.2824 0.4808 0.000 0.880 0.088 0.024 0.008
#> SRR1389300 2 0.6640 0.0226 0.000 0.548 0.296 0.040 0.116
#> SRR812246 3 0.3896 0.7194 0.012 0.024 0.824 0.016 0.124
#> SRR1076632 3 0.2177 0.7308 0.000 0.004 0.908 0.008 0.080
#> SRR1415567 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR1331900 2 0.3870 0.4632 0.000 0.808 0.148 0.024 0.020
#> SRR1452099 3 0.5821 0.4848 0.000 0.028 0.620 0.068 0.284
#> SRR1352346 1 0.3400 0.8340 0.840 0.004 0.000 0.116 0.040
#> SRR1364034 2 0.4336 0.2656 0.000 0.700 0.280 0.008 0.012
#> SRR1086046 4 0.6393 0.6807 0.128 0.004 0.092 0.660 0.116
#> SRR1407226 4 0.4783 0.7296 0.224 0.004 0.008 0.720 0.044
#> SRR1319363 4 0.4498 0.7659 0.128 0.028 0.008 0.792 0.044
#> SRR1446961 3 0.4483 0.5982 0.000 0.216 0.740 0.020 0.024
#> SRR1486650 1 0.1356 0.8402 0.956 0.004 0.000 0.028 0.012
#> SRR1470152 1 0.3237 0.8279 0.848 0.000 0.000 0.104 0.048
#> SRR1454785 2 0.2819 0.4731 0.000 0.884 0.080 0.024 0.012
#> SRR1092329 2 0.5944 -0.5433 0.000 0.488 0.108 0.000 0.404
#> SRR1091476 4 0.6081 0.7162 0.196 0.004 0.072 0.664 0.064
#> SRR1073775 2 0.3584 0.4735 0.000 0.840 0.104 0.016 0.040
#> SRR1366873 2 0.5204 0.2549 0.000 0.608 0.348 0.024 0.020
#> SRR1398114 2 0.5195 0.2233 0.000 0.608 0.348 0.028 0.016
#> SRR1089950 4 0.4597 0.6812 0.260 0.000 0.000 0.696 0.044
#> SRR1433272 2 0.6839 0.0778 0.000 0.492 0.304 0.020 0.184
#> SRR1075314 4 0.5529 0.7479 0.148 0.032 0.000 0.704 0.116
#> SRR1085590 2 0.5379 0.1910 0.000 0.672 0.116 0.004 0.208
#> SRR1100752 2 0.6476 0.2264 0.000 0.544 0.308 0.024 0.124
#> SRR1391494 2 0.4356 0.4569 0.000 0.748 0.204 0.004 0.044
#> SRR1333263 2 0.6058 -0.4138 0.000 0.508 0.128 0.000 0.364
#> SRR1310231 3 0.4404 0.6065 0.000 0.004 0.716 0.028 0.252
#> SRR1094144 3 0.6233 0.0899 0.000 0.124 0.524 0.008 0.344
#> SRR1092160 3 0.5081 0.5111 0.000 0.256 0.684 0.024 0.036
#> SRR1320300 2 0.3150 0.4775 0.000 0.864 0.096 0.024 0.016
#> SRR1322747 2 0.2878 0.4738 0.000 0.880 0.084 0.024 0.012
#> SRR1432719 3 0.2492 0.7340 0.000 0.072 0.900 0.008 0.020
#> SRR1100728 3 0.4631 0.5571 0.000 0.040 0.704 0.004 0.252
#> SRR1087511 3 0.3321 0.6937 0.000 0.032 0.832 0.000 0.136
#> SRR1470336 1 0.3480 0.7257 0.752 0.000 0.000 0.248 0.000
#> SRR1322536 4 0.5677 0.7468 0.148 0.040 0.000 0.696 0.116
#> SRR1100824 4 0.4532 0.7566 0.184 0.004 0.008 0.756 0.048
#> SRR1085951 4 0.5002 0.7432 0.144 0.004 0.000 0.720 0.132
#> SRR1322046 3 0.5677 0.4229 0.000 0.284 0.632 0.044 0.040
#> SRR1316420 1 0.4509 0.7742 0.728 0.004 0.000 0.224 0.044
#> SRR1070913 2 0.4540 0.4489 0.000 0.748 0.180 0.004 0.068
#> SRR1345806 3 0.3477 0.6906 0.000 0.140 0.828 0.008 0.024
#> SRR1313872 2 0.6017 0.3183 0.000 0.604 0.276 0.020 0.100
#> SRR1337666 3 0.5846 0.5357 0.016 0.024 0.648 0.260 0.052
#> SRR1076823 4 0.4543 0.7662 0.132 0.028 0.008 0.788 0.044
#> SRR1093954 2 0.4657 0.2722 0.000 0.696 0.268 0.020 0.016
#> SRR1451921 4 0.4857 0.7460 0.128 0.004 0.004 0.744 0.120
#> SRR1491257 4 0.6792 0.4901 0.320 0.004 0.096 0.532 0.048
#> SRR1416979 2 0.5964 -0.6108 0.000 0.464 0.108 0.000 0.428
#> SRR1419015 4 0.4652 0.7670 0.132 0.028 0.012 0.784 0.044
#> SRR817649 3 0.5037 0.5561 0.000 0.004 0.664 0.056 0.276
#> SRR1466376 2 0.3038 0.4774 0.000 0.872 0.088 0.024 0.016
#> SRR1392055 3 0.4144 0.7085 0.000 0.108 0.812 0.040 0.040
#> SRR1120913 2 0.4250 0.3875 0.000 0.784 0.084 0.004 0.128
#> SRR1120869 3 0.1364 0.7355 0.000 0.012 0.952 0.000 0.036
#> SRR1319419 3 0.1485 0.7354 0.000 0.020 0.948 0.000 0.032
#> SRR816495 3 0.4010 0.6531 0.000 0.176 0.784 0.008 0.032
#> SRR818694 2 0.5889 -0.6067 0.000 0.472 0.100 0.000 0.428
#> SRR1465653 1 0.4028 0.8003 0.776 0.000 0.000 0.176 0.048
#> SRR1475952 1 0.1281 0.8412 0.956 0.000 0.000 0.032 0.012
#> SRR1465040 2 0.5986 -0.2670 0.000 0.556 0.116 0.004 0.324
#> SRR1088461 3 0.1990 0.7329 0.000 0.028 0.928 0.004 0.040
#> SRR810129 2 0.6013 0.2220 0.000 0.632 0.176 0.016 0.176
#> SRR1400141 3 0.0566 0.7368 0.000 0.004 0.984 0.000 0.012
#> SRR1349585 1 0.3722 0.8289 0.812 0.004 0.000 0.144 0.040
#> SRR1437576 2 0.5067 0.3940 0.000 0.712 0.208 0.060 0.020
#> SRR814407 4 0.4677 0.6910 0.300 0.036 0.000 0.664 0.000
#> SRR1332403 2 0.3400 0.4718 0.000 0.852 0.096 0.036 0.016
#> SRR1099598 3 0.3241 0.6810 0.000 0.024 0.832 0.000 0.144
#> SRR1327723 3 0.4341 0.6568 0.000 0.112 0.800 0.044 0.044
#> SRR1392525 3 0.4548 0.6299 0.000 0.016 0.756 0.048 0.180
#> SRR1320536 1 0.1357 0.8421 0.948 0.000 0.000 0.048 0.004
#> SRR1083824 3 0.5031 0.5401 0.000 0.248 0.692 0.036 0.024
#> SRR1351390 4 0.4622 0.6816 0.264 0.000 0.000 0.692 0.044
#> SRR1309141 3 0.1403 0.7384 0.000 0.024 0.952 0.000 0.024
#> SRR1452803 3 0.4026 0.7206 0.000 0.088 0.824 0.040 0.048
#> SRR811631 2 0.4295 0.3821 0.000 0.780 0.084 0.004 0.132
#> SRR1485563 3 0.2723 0.7042 0.000 0.012 0.864 0.000 0.124
#> SRR1311531 3 0.3394 0.6757 0.000 0.152 0.824 0.004 0.020
#> SRR1353076 3 0.3954 0.6820 0.000 0.040 0.828 0.044 0.088
#> SRR1480831 3 0.4330 0.6618 0.000 0.064 0.796 0.024 0.116
#> SRR1083892 1 0.4199 0.7962 0.764 0.000 0.000 0.180 0.056
#> SRR809873 4 0.4769 0.7633 0.128 0.028 0.008 0.776 0.060
#> SRR1341854 2 0.4557 0.4287 0.000 0.736 0.204 0.056 0.004
#> SRR1399335 3 0.1780 0.7393 0.000 0.028 0.940 0.008 0.024
#> SRR1464209 4 0.4756 0.6616 0.288 0.000 0.000 0.668 0.044
#> SRR1389886 2 0.4525 0.3844 0.000 0.772 0.084 0.012 0.132
#> SRR1400730 1 0.4639 0.7292 0.708 0.000 0.000 0.236 0.056
#> SRR1448008 5 0.5895 0.6026 0.000 0.444 0.100 0.000 0.456
#> SRR1087606 1 0.4199 0.7962 0.764 0.000 0.000 0.180 0.056
#> SRR1445111 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR816865 5 0.6615 0.7270 0.000 0.356 0.220 0.000 0.424
#> SRR1323360 2 0.4650 0.4360 0.000 0.724 0.216 0.004 0.056
#> SRR1417364 3 0.4640 0.6061 0.000 0.204 0.740 0.024 0.032
#> SRR1480329 3 0.6597 -0.0421 0.020 0.000 0.456 0.400 0.124
#> SRR1403322 4 0.4275 0.7675 0.152 0.068 0.000 0.776 0.004
#> SRR1093625 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
#> SRR1479977 3 0.5157 0.0985 0.000 0.468 0.500 0.024 0.008
#> SRR1082035 1 0.4858 0.7278 0.688 0.004 0.000 0.256 0.052
#> SRR1393046 2 0.2112 0.4823 0.000 0.908 0.084 0.004 0.004
#> SRR1466663 3 0.1179 0.7385 0.000 0.016 0.964 0.004 0.016
#> SRR1384456 1 0.1211 0.8387 0.960 0.000 0.000 0.024 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 3 0.2793 0.6176 0.000 0.080 0.872 0.024 0.000 0.024
#> SRR808862 5 0.2573 0.7089 0.000 0.000 0.008 0.044 0.884 0.064
#> SRR1500382 6 0.5494 0.8508 0.008 0.008 0.376 0.000 0.080 0.528
#> SRR1322683 2 0.5070 0.0895 0.000 0.576 0.096 0.328 0.000 0.000
#> SRR1329811 5 0.4884 0.5511 0.204 0.004 0.000 0.008 0.684 0.100
#> SRR1087297 3 0.4199 -0.6695 0.000 0.004 0.544 0.000 0.008 0.444
#> SRR1072626 3 0.4078 0.4896 0.000 0.068 0.748 0.180 0.000 0.004
#> SRR1407428 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1321029 3 0.4744 0.5115 0.020 0.176 0.736 0.024 0.004 0.040
#> SRR1500282 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1100496 4 0.6849 0.5357 0.000 0.120 0.264 0.524 0.040 0.052
#> SRR1308778 3 0.4227 -0.8039 0.000 0.004 0.500 0.000 0.008 0.488
#> SRR1445304 2 0.5230 0.1640 0.000 0.592 0.112 0.292 0.000 0.004
#> SRR1099378 5 0.3983 0.7048 0.068 0.008 0.012 0.000 0.792 0.120
#> SRR1347412 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1099694 2 0.5911 -0.0990 0.000 0.464 0.296 0.240 0.000 0.000
#> SRR1088365 4 0.6719 0.2343 0.000 0.324 0.292 0.356 0.004 0.024
#> SRR1325752 5 0.6314 0.2108 0.004 0.000 0.180 0.028 0.508 0.280
#> SRR1416713 2 0.2527 0.5774 0.000 0.876 0.084 0.040 0.000 0.000
#> SRR1074474 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1469369 3 0.3947 0.6111 0.000 0.080 0.812 0.068 0.012 0.028
#> SRR1400507 2 0.3404 0.5492 0.000 0.760 0.224 0.016 0.000 0.000
#> SRR1378179 3 0.1398 0.6238 0.000 0.008 0.940 0.052 0.000 0.000
#> SRR1377905 4 0.6674 0.3406 0.020 0.320 0.316 0.340 0.004 0.000
#> SRR1089479 1 0.3573 0.7771 0.796 0.000 0.000 0.004 0.148 0.052
#> SRR1073365 2 0.4395 0.4471 0.004 0.644 0.324 0.008 0.000 0.020
#> SRR1500306 5 0.4877 0.5801 0.220 0.004 0.000 0.052 0.692 0.032
#> SRR1101566 3 0.2171 0.6355 0.000 0.040 0.912 0.032 0.000 0.016
#> SRR1350503 3 0.4778 0.1668 0.000 0.068 0.676 0.016 0.000 0.240
#> SRR1446007 2 0.6867 -0.0673 0.000 0.376 0.296 0.280 0.000 0.048
#> SRR1102875 2 0.4516 0.4926 0.004 0.696 0.240 0.008 0.000 0.052
#> SRR1380293 6 0.4312 0.7845 0.000 0.004 0.476 0.000 0.012 0.508
#> SRR1331198 2 0.4641 0.3161 0.000 0.592 0.372 0.020 0.004 0.012
#> SRR1092686 3 0.1226 0.6298 0.000 0.040 0.952 0.004 0.000 0.004
#> SRR1069421 4 0.6176 0.5147 0.000 0.124 0.352 0.492 0.012 0.020
#> SRR1341650 3 0.3087 0.5929 0.000 0.008 0.844 0.120 0.008 0.020
#> SRR1357276 5 0.6377 -0.0825 0.012 0.004 0.236 0.000 0.432 0.316
#> SRR1498374 4 0.6638 0.3340 0.020 0.344 0.272 0.360 0.004 0.000
#> SRR1093721 3 0.2797 0.6021 0.000 0.076 0.872 0.016 0.000 0.036
#> SRR1464660 1 0.6067 0.7006 0.572 0.000 0.000 0.052 0.136 0.240
#> SRR1402051 4 0.6826 0.5897 0.000 0.152 0.156 0.556 0.120 0.016
#> SRR1488734 3 0.3996 -0.5077 0.000 0.004 0.604 0.004 0.000 0.388
#> SRR1082616 5 0.3728 0.6598 0.000 0.000 0.004 0.140 0.788 0.068
#> SRR1099427 3 0.2002 0.6131 0.000 0.004 0.908 0.076 0.000 0.012
#> SRR1453093 4 0.4528 0.6189 0.000 0.152 0.080 0.740 0.000 0.028
#> SRR1357064 1 0.5311 0.7406 0.628 0.000 0.000 0.012 0.136 0.224
#> SRR811237 4 0.4646 0.6260 0.000 0.144 0.096 0.732 0.000 0.028
#> SRR1100848 3 0.3996 0.5873 0.000 0.080 0.752 0.168 0.000 0.000
#> SRR1346755 3 0.2897 0.6380 0.000 0.060 0.852 0.088 0.000 0.000
#> SRR1472529 2 0.3841 0.4676 0.000 0.716 0.256 0.028 0.000 0.000
#> SRR1398905 5 0.4825 0.5742 0.236 0.000 0.000 0.056 0.680 0.028
#> SRR1082733 2 0.4717 0.4456 0.000 0.632 0.308 0.008 0.000 0.052
#> SRR1308035 2 0.4792 0.3114 0.000 0.644 0.096 0.260 0.000 0.000
#> SRR1466445 4 0.5636 0.5636 0.000 0.300 0.180 0.520 0.000 0.000
#> SRR1359080 2 0.5474 0.0821 0.000 0.488 0.384 0.128 0.000 0.000
#> SRR1455825 2 0.2558 0.5927 0.004 0.884 0.084 0.016 0.000 0.012
#> SRR1389300 2 0.6688 0.1045 0.000 0.436 0.280 0.240 0.000 0.044
#> SRR812246 3 0.3547 0.5780 0.000 0.016 0.840 0.060 0.064 0.020
#> SRR1076632 3 0.3181 0.5921 0.000 0.008 0.848 0.084 0.004 0.056
#> SRR1415567 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1331900 2 0.2163 0.5969 0.004 0.892 0.096 0.000 0.000 0.008
#> SRR1452099 3 0.4689 0.4664 0.000 0.008 0.728 0.172 0.072 0.020
#> SRR1352346 1 0.4259 0.7648 0.756 0.012 0.000 0.000 0.128 0.104
#> SRR1364034 2 0.4757 0.4760 0.000 0.660 0.272 0.020 0.000 0.048
#> SRR1086046 5 0.4438 0.6371 0.000 0.000 0.068 0.088 0.768 0.076
#> SRR1407226 5 0.4583 0.6760 0.104 0.012 0.008 0.000 0.740 0.136
#> SRR1319363 5 0.1493 0.7266 0.004 0.000 0.004 0.000 0.936 0.056
#> SRR1446961 3 0.4213 0.5210 0.000 0.184 0.752 0.020 0.004 0.040
#> SRR1486650 1 0.2717 0.7864 0.880 0.012 0.000 0.012 0.080 0.016
#> SRR1470152 1 0.4898 0.7631 0.680 0.000 0.000 0.012 0.108 0.200
#> SRR1454785 2 0.2295 0.5898 0.004 0.900 0.072 0.008 0.000 0.016
#> SRR1092329 4 0.5013 0.6475 0.000 0.224 0.140 0.636 0.000 0.000
#> SRR1091476 5 0.5169 0.6818 0.036 0.004 0.076 0.008 0.704 0.172
#> SRR1073775 2 0.3650 0.5789 0.000 0.812 0.112 0.056 0.000 0.020
#> SRR1366873 2 0.4335 0.4390 0.004 0.672 0.292 0.008 0.000 0.024
#> SRR1398114 2 0.4650 0.4828 0.004 0.672 0.264 0.008 0.000 0.052
#> SRR1089950 5 0.4738 0.5566 0.200 0.000 0.000 0.004 0.684 0.112
#> SRR1433272 3 0.6886 -0.3973 0.020 0.264 0.396 0.304 0.004 0.012
#> SRR1075314 5 0.3458 0.7039 0.008 0.000 0.000 0.104 0.820 0.068
#> SRR1085590 4 0.5233 0.3715 0.000 0.404 0.096 0.500 0.000 0.000
#> SRR1100752 3 0.5378 0.3398 0.020 0.300 0.616 0.044 0.004 0.016
#> SRR1391494 2 0.4332 0.4052 0.000 0.644 0.316 0.040 0.000 0.000
#> SRR1333263 4 0.5958 0.4797 0.000 0.304 0.248 0.448 0.000 0.000
#> SRR1310231 3 0.4032 -0.5872 0.000 0.008 0.572 0.000 0.000 0.420
#> SRR1094144 3 0.4521 0.4602 0.000 0.024 0.692 0.256 0.008 0.020
#> SRR1092160 3 0.3799 0.5303 0.000 0.208 0.756 0.012 0.000 0.024
#> SRR1320300 2 0.2627 0.5930 0.004 0.880 0.084 0.008 0.000 0.024
#> SRR1322747 2 0.2602 0.5871 0.000 0.884 0.072 0.024 0.000 0.020
#> SRR1432719 3 0.2108 0.6229 0.000 0.056 0.912 0.016 0.000 0.016
#> SRR1100728 3 0.3998 0.4990 0.000 0.016 0.756 0.200 0.008 0.020
#> SRR1087511 3 0.2474 0.6287 0.000 0.032 0.884 0.080 0.000 0.004
#> SRR1470336 1 0.4506 0.5970 0.652 0.000 0.000 0.008 0.300 0.040
#> SRR1322536 5 0.3690 0.7014 0.012 0.000 0.000 0.116 0.804 0.068
#> SRR1100824 5 0.4074 0.6963 0.076 0.008 0.008 0.000 0.780 0.128
#> SRR1085951 5 0.3109 0.7024 0.008 0.000 0.000 0.076 0.848 0.068
#> SRR1322046 3 0.4809 0.3440 0.000 0.276 0.656 0.036 0.000 0.032
#> SRR1316420 1 0.5703 0.6999 0.596 0.008 0.000 0.008 0.200 0.188
#> SRR1070913 2 0.4737 0.4274 0.000 0.676 0.192 0.132 0.000 0.000
#> SRR1345806 3 0.3390 0.5853 0.000 0.140 0.816 0.016 0.000 0.028
#> SRR1313872 3 0.5013 0.0159 0.000 0.428 0.508 0.060 0.000 0.004
#> SRR1337666 3 0.6321 -0.3240 0.016 0.008 0.556 0.012 0.196 0.212
#> SRR1076823 5 0.1493 0.7266 0.004 0.000 0.004 0.000 0.936 0.056
#> SRR1093954 2 0.4504 0.4832 0.004 0.692 0.248 0.008 0.000 0.048
#> SRR1451921 5 0.2585 0.7069 0.000 0.000 0.004 0.048 0.880 0.068
#> SRR1491257 5 0.6460 0.5082 0.160 0.012 0.072 0.000 0.580 0.176
#> SRR1416979 4 0.4797 0.6473 0.000 0.212 0.124 0.664 0.000 0.000
#> SRR1419015 5 0.2179 0.7264 0.004 0.000 0.016 0.008 0.908 0.064
#> SRR817649 6 0.4795 0.8686 0.000 0.000 0.400 0.000 0.056 0.544
#> SRR1466376 2 0.2466 0.5941 0.004 0.888 0.084 0.012 0.000 0.012
#> SRR1392055 3 0.3613 0.5448 0.000 0.076 0.816 0.016 0.000 0.092
#> SRR1120913 2 0.5027 0.0668 0.000 0.580 0.076 0.340 0.000 0.004
#> SRR1120869 3 0.1268 0.6258 0.000 0.008 0.952 0.036 0.000 0.004
#> SRR1319419 3 0.1036 0.6263 0.000 0.008 0.964 0.024 0.000 0.004
#> SRR816495 3 0.4214 0.5212 0.000 0.176 0.756 0.020 0.004 0.044
#> SRR818694 4 0.4895 0.6313 0.000 0.228 0.124 0.648 0.000 0.000
#> SRR1465653 1 0.5311 0.7406 0.628 0.000 0.000 0.012 0.136 0.224
#> SRR1475952 1 0.2969 0.7912 0.860 0.000 0.000 0.020 0.088 0.032
#> SRR1465040 4 0.5264 0.4483 0.000 0.376 0.104 0.520 0.000 0.000
#> SRR1088461 3 0.1864 0.6346 0.000 0.032 0.924 0.040 0.000 0.004
#> SRR810129 2 0.5284 -0.1346 0.000 0.508 0.104 0.388 0.000 0.000
#> SRR1400141 3 0.0972 0.6274 0.000 0.028 0.964 0.008 0.000 0.000
#> SRR1349585 1 0.5031 0.7389 0.680 0.012 0.000 0.004 0.188 0.116
#> SRR1437576 2 0.4199 0.5323 0.000 0.728 0.212 0.008 0.000 0.052
#> SRR814407 5 0.5192 0.4865 0.296 0.000 0.000 0.056 0.616 0.032
#> SRR1332403 2 0.2706 0.5906 0.004 0.876 0.084 0.008 0.000 0.028
#> SRR1099598 3 0.2163 0.6167 0.000 0.016 0.892 0.092 0.000 0.000
#> SRR1327723 3 0.3916 0.4260 0.000 0.192 0.760 0.032 0.000 0.016
#> SRR1392525 3 0.4871 0.4004 0.000 0.008 0.704 0.196 0.072 0.020
#> SRR1320536 1 0.1700 0.7929 0.928 0.000 0.000 0.000 0.048 0.024
#> SRR1083824 3 0.4232 0.4988 0.000 0.236 0.716 0.020 0.000 0.028
#> SRR1351390 5 0.4823 0.5555 0.208 0.004 0.000 0.008 0.688 0.092
#> SRR1309141 3 0.1851 0.6149 0.000 0.036 0.928 0.012 0.000 0.024
#> SRR1452803 3 0.3301 0.5086 0.000 0.032 0.828 0.016 0.000 0.124
#> SRR811631 2 0.4881 0.0832 0.000 0.588 0.076 0.336 0.000 0.000
#> SRR1485563 3 0.2661 0.6076 0.000 0.004 0.876 0.092 0.016 0.012
#> SRR1311531 3 0.3428 0.5628 0.000 0.152 0.808 0.016 0.000 0.024
#> SRR1353076 3 0.3300 0.5324 0.000 0.020 0.816 0.152 0.004 0.008
#> SRR1480831 3 0.3402 0.5366 0.000 0.020 0.800 0.168 0.000 0.012
#> SRR1083892 1 0.6001 0.7075 0.580 0.000 0.000 0.052 0.128 0.240
#> SRR809873 5 0.1888 0.7250 0.000 0.000 0.004 0.012 0.916 0.068
#> SRR1341854 2 0.3816 0.5725 0.000 0.760 0.200 0.012 0.000 0.028
#> SRR1399335 3 0.2002 0.6103 0.000 0.040 0.920 0.012 0.000 0.028
#> SRR1464209 5 0.5349 0.4586 0.216 0.000 0.000 0.004 0.608 0.172
#> SRR1389886 2 0.5330 0.1322 0.000 0.588 0.088 0.308 0.000 0.016
#> SRR1400730 1 0.6656 0.6131 0.504 0.004 0.000 0.056 0.208 0.228
#> SRR1448008 4 0.4686 0.6363 0.000 0.168 0.088 0.720 0.000 0.024
#> SRR1087606 1 0.6001 0.7075 0.580 0.000 0.000 0.052 0.128 0.240
#> SRR1445111 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR816865 4 0.5568 0.6094 0.000 0.124 0.172 0.656 0.004 0.044
#> SRR1323360 2 0.4136 0.4989 0.000 0.732 0.192 0.076 0.000 0.000
#> SRR1417364 3 0.4181 0.5247 0.000 0.180 0.756 0.020 0.004 0.040
#> SRR1480329 5 0.6088 0.0911 0.000 0.000 0.192 0.012 0.468 0.328
#> SRR1403322 5 0.2076 0.7223 0.016 0.000 0.000 0.060 0.912 0.012
#> SRR1093625 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
#> SRR1479977 3 0.4747 0.3952 0.004 0.352 0.604 0.020 0.000 0.020
#> SRR1082035 1 0.5866 0.5778 0.548 0.012 0.000 0.004 0.280 0.156
#> SRR1393046 2 0.2365 0.5760 0.000 0.888 0.072 0.040 0.000 0.000
#> SRR1466663 3 0.2176 0.6260 0.000 0.024 0.916 0.036 0.004 0.020
#> SRR1384456 1 0.1838 0.7838 0.928 0.000 0.000 0.020 0.040 0.012
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["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 17467 rows and 159 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 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 0.999 0.965 0.984 0.2744 0.716 0.716
#> 3 3 0.499 0.717 0.864 1.1133 0.623 0.490
#> 4 4 0.468 0.759 0.824 0.0905 0.639 0.373
#> 5 5 0.614 0.681 0.809 0.1676 0.809 0.542
#> 6 6 0.569 0.452 0.688 0.0622 0.880 0.586
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
#> SRR810713 2 0.0000 0.994 0.000 1.000
#> SRR808862 2 0.0000 0.994 0.000 1.000
#> SRR1500382 2 0.0000 0.994 0.000 1.000
#> SRR1322683 2 0.0000 0.994 0.000 1.000
#> SRR1329811 2 0.1414 0.974 0.020 0.980
#> SRR1087297 2 0.0000 0.994 0.000 1.000
#> SRR1072626 2 0.0000 0.994 0.000 1.000
#> SRR1407428 1 0.0000 0.930 1.000 0.000
#> SRR1321029 2 0.0000 0.994 0.000 1.000
#> SRR1500282 1 0.0000 0.930 1.000 0.000
#> SRR1100496 2 0.0000 0.994 0.000 1.000
#> SRR1308778 2 0.0000 0.994 0.000 1.000
#> SRR1445304 2 0.0000 0.994 0.000 1.000
#> SRR1099378 2 0.0000 0.994 0.000 1.000
#> SRR1347412 1 0.0000 0.930 1.000 0.000
#> SRR1099694 2 0.0000 0.994 0.000 1.000
#> SRR1088365 2 0.0000 0.994 0.000 1.000
#> SRR1325752 2 0.0000 0.994 0.000 1.000
#> SRR1416713 2 0.0000 0.994 0.000 1.000
#> SRR1074474 1 0.0000 0.930 1.000 0.000
#> SRR1469369 2 0.0000 0.994 0.000 1.000
#> SRR1400507 2 0.0000 0.994 0.000 1.000
#> SRR1378179 2 0.0000 0.994 0.000 1.000
#> SRR1377905 2 0.0000 0.994 0.000 1.000
#> SRR1089479 1 0.0000 0.930 1.000 0.000
#> SRR1073365 2 0.0000 0.994 0.000 1.000
#> SRR1500306 1 0.9996 0.140 0.512 0.488
#> SRR1101566 2 0.0000 0.994 0.000 1.000
#> SRR1350503 2 0.0000 0.994 0.000 1.000
#> SRR1446007 2 0.0000 0.994 0.000 1.000
#> SRR1102875 2 0.0000 0.994 0.000 1.000
#> SRR1380293 2 0.0000 0.994 0.000 1.000
#> SRR1331198 2 0.0000 0.994 0.000 1.000
#> SRR1092686 2 0.0000 0.994 0.000 1.000
#> SRR1069421 2 0.0000 0.994 0.000 1.000
#> SRR1341650 2 0.0000 0.994 0.000 1.000
#> SRR1357276 2 0.0000 0.994 0.000 1.000
#> SRR1498374 2 0.0000 0.994 0.000 1.000
#> SRR1093721 2 0.0000 0.994 0.000 1.000
#> SRR1464660 1 0.6801 0.795 0.820 0.180
#> SRR1402051 2 0.0000 0.994 0.000 1.000
#> SRR1488734 2 0.0000 0.994 0.000 1.000
#> SRR1082616 2 0.0000 0.994 0.000 1.000
#> SRR1099427 2 0.0000 0.994 0.000 1.000
#> SRR1453093 2 0.0000 0.994 0.000 1.000
#> SRR1357064 1 0.0376 0.929 0.996 0.004
#> SRR811237 2 0.0000 0.994 0.000 1.000
#> SRR1100848 2 0.0000 0.994 0.000 1.000
#> SRR1346755 2 0.0000 0.994 0.000 1.000
#> SRR1472529 2 0.0000 0.994 0.000 1.000
#> SRR1398905 1 0.7219 0.771 0.800 0.200
#> SRR1082733 2 0.0000 0.994 0.000 1.000
#> SRR1308035 2 0.0000 0.994 0.000 1.000
#> SRR1466445 2 0.0000 0.994 0.000 1.000
#> SRR1359080 2 0.0000 0.994 0.000 1.000
#> SRR1455825 2 0.0000 0.994 0.000 1.000
#> SRR1389300 2 0.0000 0.994 0.000 1.000
#> SRR812246 2 0.0000 0.994 0.000 1.000
#> SRR1076632 2 0.0000 0.994 0.000 1.000
#> SRR1415567 1 0.0000 0.930 1.000 0.000
#> SRR1331900 2 0.0000 0.994 0.000 1.000
#> SRR1452099 2 0.0000 0.994 0.000 1.000
#> SRR1352346 1 0.1843 0.917 0.972 0.028
#> SRR1364034 2 0.0000 0.994 0.000 1.000
#> SRR1086046 2 0.0000 0.994 0.000 1.000
#> SRR1407226 2 0.8267 0.616 0.260 0.740
#> SRR1319363 2 0.0000 0.994 0.000 1.000
#> SRR1446961 2 0.0000 0.994 0.000 1.000
#> SRR1486650 1 0.0000 0.930 1.000 0.000
#> SRR1470152 1 0.0000 0.930 1.000 0.000
#> SRR1454785 2 0.0000 0.994 0.000 1.000
#> SRR1092329 2 0.0000 0.994 0.000 1.000
#> SRR1091476 2 0.0000 0.994 0.000 1.000
#> SRR1073775 2 0.0000 0.994 0.000 1.000
#> SRR1366873 2 0.0000 0.994 0.000 1.000
#> SRR1398114 2 0.0000 0.994 0.000 1.000
#> SRR1089950 2 0.3879 0.910 0.076 0.924
#> SRR1433272 2 0.0000 0.994 0.000 1.000
#> SRR1075314 2 0.0000 0.994 0.000 1.000
#> SRR1085590 2 0.0000 0.994 0.000 1.000
#> SRR1100752 2 0.0000 0.994 0.000 1.000
#> SRR1391494 2 0.0000 0.994 0.000 1.000
#> SRR1333263 2 0.0000 0.994 0.000 1.000
#> SRR1310231 2 0.0000 0.994 0.000 1.000
#> SRR1094144 2 0.0000 0.994 0.000 1.000
#> SRR1092160 2 0.0000 0.994 0.000 1.000
#> SRR1320300 2 0.0000 0.994 0.000 1.000
#> SRR1322747 2 0.0000 0.994 0.000 1.000
#> SRR1432719 2 0.0000 0.994 0.000 1.000
#> SRR1100728 2 0.0000 0.994 0.000 1.000
#> SRR1087511 2 0.0000 0.994 0.000 1.000
#> SRR1470336 1 0.0000 0.930 1.000 0.000
#> SRR1322536 2 0.0000 0.994 0.000 1.000
#> SRR1100824 2 0.1184 0.978 0.016 0.984
#> SRR1085951 2 0.0000 0.994 0.000 1.000
#> SRR1322046 2 0.0000 0.994 0.000 1.000
#> SRR1316420 1 0.5519 0.846 0.872 0.128
#> SRR1070913 2 0.0000 0.994 0.000 1.000
#> SRR1345806 2 0.0000 0.994 0.000 1.000
#> SRR1313872 2 0.0000 0.994 0.000 1.000
#> SRR1337666 2 0.0000 0.994 0.000 1.000
#> SRR1076823 2 0.0000 0.994 0.000 1.000
#> SRR1093954 2 0.0000 0.994 0.000 1.000
#> SRR1451921 2 0.0000 0.994 0.000 1.000
#> SRR1491257 2 0.0938 0.982 0.012 0.988
#> SRR1416979 2 0.0000 0.994 0.000 1.000
#> SRR1419015 2 0.0000 0.994 0.000 1.000
#> SRR817649 2 0.0000 0.994 0.000 1.000
#> SRR1466376 2 0.0000 0.994 0.000 1.000
#> SRR1392055 2 0.0000 0.994 0.000 1.000
#> SRR1120913 2 0.0000 0.994 0.000 1.000
#> SRR1120869 2 0.0000 0.994 0.000 1.000
#> SRR1319419 2 0.0000 0.994 0.000 1.000
#> SRR816495 2 0.0000 0.994 0.000 1.000
#> SRR818694 2 0.0000 0.994 0.000 1.000
#> SRR1465653 1 0.0000 0.930 1.000 0.000
#> SRR1475952 1 0.0000 0.930 1.000 0.000
#> SRR1465040 2 0.0000 0.994 0.000 1.000
#> SRR1088461 2 0.0000 0.994 0.000 1.000
#> SRR810129 2 0.0000 0.994 0.000 1.000
#> SRR1400141 2 0.0000 0.994 0.000 1.000
#> SRR1349585 1 0.0000 0.930 1.000 0.000
#> SRR1437576 2 0.0000 0.994 0.000 1.000
#> SRR814407 1 0.0000 0.930 1.000 0.000
#> SRR1332403 2 0.0000 0.994 0.000 1.000
#> SRR1099598 2 0.0000 0.994 0.000 1.000
#> SRR1327723 2 0.0000 0.994 0.000 1.000
#> SRR1392525 2 0.0000 0.994 0.000 1.000
#> SRR1320536 1 0.0000 0.930 1.000 0.000
#> SRR1083824 2 0.0000 0.994 0.000 1.000
#> SRR1351390 2 0.7815 0.671 0.232 0.768
#> SRR1309141 2 0.0000 0.994 0.000 1.000
#> SRR1452803 2 0.0000 0.994 0.000 1.000
#> SRR811631 2 0.0000 0.994 0.000 1.000
#> SRR1485563 2 0.0000 0.994 0.000 1.000
#> SRR1311531 2 0.0000 0.994 0.000 1.000
#> SRR1353076 2 0.0000 0.994 0.000 1.000
#> SRR1480831 2 0.0000 0.994 0.000 1.000
#> SRR1083892 1 0.1633 0.920 0.976 0.024
#> SRR809873 2 0.0000 0.994 0.000 1.000
#> SRR1341854 2 0.0000 0.994 0.000 1.000
#> SRR1399335 2 0.0000 0.994 0.000 1.000
#> SRR1464209 1 0.8909 0.610 0.692 0.308
#> SRR1389886 2 0.0000 0.994 0.000 1.000
#> SRR1400730 1 0.9323 0.532 0.652 0.348
#> SRR1448008 2 0.0000 0.994 0.000 1.000
#> SRR1087606 1 0.4161 0.881 0.916 0.084
#> SRR1445111 1 0.0000 0.930 1.000 0.000
#> SRR816865 2 0.0000 0.994 0.000 1.000
#> SRR1323360 2 0.0000 0.994 0.000 1.000
#> SRR1417364 2 0.0000 0.994 0.000 1.000
#> SRR1480329 2 0.0000 0.994 0.000 1.000
#> SRR1403322 2 0.2043 0.961 0.032 0.968
#> SRR1093625 1 0.0000 0.930 1.000 0.000
#> SRR1479977 2 0.0000 0.994 0.000 1.000
#> SRR1082035 2 0.2948 0.939 0.052 0.948
#> SRR1393046 2 0.0000 0.994 0.000 1.000
#> SRR1466663 2 0.0000 0.994 0.000 1.000
#> SRR1384456 1 0.0000 0.930 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> SRR810713 3 0.5291 0.6861 0.000 0.268 0.732
#> SRR808862 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1500382 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1322683 2 0.1753 0.8725 0.000 0.952 0.048
#> SRR1329811 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1087297 3 0.1031 0.7435 0.000 0.024 0.976
#> SRR1072626 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1407428 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1321029 3 0.1411 0.7494 0.000 0.036 0.964
#> SRR1500282 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1100496 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1308778 3 0.1031 0.7435 0.000 0.024 0.976
#> SRR1445304 3 0.4887 0.7252 0.000 0.228 0.772
#> SRR1099378 2 0.6832 0.4027 0.020 0.604 0.376
#> SRR1347412 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1099694 2 0.6295 0.0512 0.000 0.528 0.472
#> SRR1088365 2 0.1031 0.8775 0.000 0.976 0.024
#> SRR1325752 3 0.6307 0.1139 0.000 0.488 0.512
#> SRR1416713 3 0.4842 0.7303 0.000 0.224 0.776
#> SRR1074474 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1469369 2 0.1529 0.8750 0.000 0.960 0.040
#> SRR1400507 2 0.1860 0.8710 0.000 0.948 0.052
#> SRR1378179 2 0.4121 0.7874 0.000 0.832 0.168
#> SRR1377905 2 0.6045 0.4033 0.000 0.620 0.380
#> SRR1089479 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1073365 3 0.5560 0.6415 0.000 0.300 0.700
#> SRR1500306 1 0.5431 0.5707 0.716 0.284 0.000
#> SRR1101566 2 0.4291 0.7734 0.000 0.820 0.180
#> SRR1350503 3 0.1031 0.7435 0.000 0.024 0.976
#> SRR1446007 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1102875 3 0.5835 0.5727 0.000 0.340 0.660
#> SRR1380293 3 0.0424 0.7294 0.000 0.008 0.992
#> SRR1331198 3 0.3267 0.7608 0.000 0.116 0.884
#> SRR1092686 3 0.4346 0.7540 0.000 0.184 0.816
#> SRR1069421 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1341650 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1357276 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1498374 3 0.4702 0.7358 0.000 0.212 0.788
#> SRR1093721 3 0.3038 0.7597 0.000 0.104 0.896
#> SRR1464660 3 0.5098 0.2987 0.248 0.000 0.752
#> SRR1402051 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1488734 3 0.1529 0.7505 0.000 0.040 0.960
#> SRR1082616 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1099427 2 0.1031 0.8775 0.000 0.976 0.024
#> SRR1453093 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1357064 1 0.6267 0.4795 0.548 0.000 0.452
#> SRR811237 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1100848 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1346755 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1472529 2 0.5397 0.6350 0.000 0.720 0.280
#> SRR1398905 1 0.6045 0.3806 0.620 0.380 0.000
#> SRR1082733 2 0.5621 0.5810 0.000 0.692 0.308
#> SRR1308035 2 0.1529 0.8750 0.000 0.960 0.040
#> SRR1466445 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1359080 3 0.5529 0.6453 0.000 0.296 0.704
#> SRR1455825 2 0.5859 0.4964 0.000 0.656 0.344
#> SRR1389300 2 0.1289 0.8766 0.000 0.968 0.032
#> SRR812246 2 0.2537 0.8563 0.000 0.920 0.080
#> SRR1076632 2 0.2448 0.8588 0.000 0.924 0.076
#> SRR1415567 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1331900 3 0.6252 0.2922 0.000 0.444 0.556
#> SRR1452099 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1352346 3 0.1411 0.6755 0.036 0.000 0.964
#> SRR1364034 2 0.3340 0.8308 0.000 0.880 0.120
#> SRR1086046 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1407226 1 0.6008 0.5625 0.628 0.000 0.372
#> SRR1319363 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1446961 3 0.2261 0.7562 0.000 0.068 0.932
#> SRR1486650 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1470152 1 0.5465 0.6998 0.712 0.000 0.288
#> SRR1454785 3 0.5948 0.5306 0.000 0.360 0.640
#> SRR1092329 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1091476 3 0.3340 0.7454 0.000 0.120 0.880
#> SRR1073775 2 0.2356 0.8610 0.000 0.928 0.072
#> SRR1366873 3 0.3941 0.7578 0.000 0.156 0.844
#> SRR1398114 2 0.6225 0.2187 0.000 0.568 0.432
#> SRR1089950 3 0.6079 -0.0198 0.388 0.000 0.612
#> SRR1433272 2 0.4702 0.7367 0.000 0.788 0.212
#> SRR1075314 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1085590 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1100752 3 0.5859 0.5518 0.000 0.344 0.656
#> SRR1391494 2 0.3686 0.8122 0.000 0.860 0.140
#> SRR1333263 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1310231 3 0.1289 0.7479 0.000 0.032 0.968
#> SRR1094144 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1092160 3 0.5835 0.5729 0.000 0.340 0.660
#> SRR1320300 3 0.4750 0.7371 0.000 0.216 0.784
#> SRR1322747 3 0.5327 0.6796 0.000 0.272 0.728
#> SRR1432719 3 0.5138 0.7028 0.000 0.252 0.748
#> SRR1100728 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1087511 2 0.1643 0.8740 0.000 0.956 0.044
#> SRR1470336 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1322536 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1100824 1 0.8745 0.3635 0.524 0.120 0.356
#> SRR1085951 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1322046 2 0.1643 0.8739 0.000 0.956 0.044
#> SRR1316420 1 0.5016 0.7307 0.760 0.000 0.240
#> SRR1070913 2 0.5016 0.6989 0.000 0.760 0.240
#> SRR1345806 3 0.6095 0.4528 0.000 0.392 0.608
#> SRR1313872 2 0.4062 0.7899 0.000 0.836 0.164
#> SRR1337666 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1076823 2 0.0237 0.8686 0.004 0.996 0.000
#> SRR1093954 2 0.5178 0.6767 0.000 0.744 0.256
#> SRR1451921 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1491257 3 0.4346 0.5258 0.184 0.000 0.816
#> SRR1416979 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1419015 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR817649 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1466376 3 0.5678 0.6170 0.000 0.316 0.684
#> SRR1392055 3 0.1163 0.7459 0.000 0.028 0.972
#> SRR1120913 3 0.6308 0.0943 0.000 0.492 0.508
#> SRR1120869 2 0.4931 0.7103 0.000 0.768 0.232
#> SRR1319419 3 0.6026 0.4942 0.000 0.376 0.624
#> SRR816495 3 0.1411 0.7494 0.000 0.036 0.964
#> SRR818694 2 0.0592 0.8756 0.000 0.988 0.012
#> SRR1465653 3 0.5810 0.0290 0.336 0.000 0.664
#> SRR1475952 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1465040 2 0.1163 0.8771 0.000 0.972 0.028
#> SRR1088461 2 0.5016 0.6995 0.000 0.760 0.240
#> SRR810129 2 0.1860 0.8710 0.000 0.948 0.052
#> SRR1400141 3 0.5397 0.6711 0.000 0.280 0.720
#> SRR1349585 1 0.0424 0.8293 0.992 0.000 0.008
#> SRR1437576 2 0.3816 0.8055 0.000 0.852 0.148
#> SRR814407 1 0.4346 0.6872 0.816 0.184 0.000
#> SRR1332403 2 0.6026 0.4099 0.000 0.624 0.376
#> SRR1099598 2 0.1411 0.8758 0.000 0.964 0.036
#> SRR1327723 3 0.4346 0.7503 0.000 0.184 0.816
#> SRR1392525 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1320536 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1083824 3 0.1289 0.7479 0.000 0.032 0.968
#> SRR1351390 1 0.5109 0.7399 0.780 0.008 0.212
#> SRR1309141 3 0.4750 0.7362 0.000 0.216 0.784
#> SRR1452803 3 0.1031 0.7435 0.000 0.024 0.976
#> SRR811631 2 0.3340 0.8282 0.000 0.880 0.120
#> SRR1485563 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1311531 2 0.5327 0.6497 0.000 0.728 0.272
#> SRR1353076 2 0.1860 0.8716 0.000 0.948 0.052
#> SRR1480831 2 0.0892 0.8776 0.000 0.980 0.020
#> SRR1083892 1 0.6008 0.6088 0.628 0.000 0.372
#> SRR809873 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1341854 2 0.1753 0.8725 0.000 0.952 0.048
#> SRR1399335 3 0.1163 0.7459 0.000 0.028 0.972
#> SRR1464209 1 0.5529 0.6807 0.704 0.000 0.296
#> SRR1389886 2 0.5254 0.6622 0.000 0.736 0.264
#> SRR1400730 3 0.6045 -0.1006 0.380 0.000 0.620
#> SRR1448008 2 0.0000 0.8716 0.000 1.000 0.000
#> SRR1087606 1 0.6309 0.3964 0.504 0.000 0.496
#> SRR1445111 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR816865 2 0.0424 0.8744 0.000 0.992 0.008
#> SRR1323360 2 0.5678 0.5646 0.000 0.684 0.316
#> SRR1417364 3 0.1031 0.7435 0.000 0.024 0.976
#> SRR1480329 3 0.0424 0.7294 0.000 0.008 0.992
#> SRR1403322 2 0.1163 0.8459 0.028 0.972 0.000
#> SRR1093625 1 0.0000 0.8314 1.000 0.000 0.000
#> SRR1479977 3 0.3686 0.7603 0.000 0.140 0.860
#> SRR1082035 3 0.0000 0.7211 0.000 0.000 1.000
#> SRR1393046 2 0.6225 0.2199 0.000 0.568 0.432
#> SRR1466663 2 0.5706 0.5557 0.000 0.680 0.320
#> SRR1384456 1 0.0000 0.8314 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> SRR810713 2 0.2489 0.8232 0.068 0.912 0.020 0.000
#> SRR808862 3 0.1557 0.8415 0.000 0.056 0.944 0.000
#> SRR1500382 2 0.4175 0.7659 0.212 0.776 0.012 0.000
#> SRR1322683 2 0.2918 0.7875 0.008 0.876 0.116 0.000
#> SRR1329811 1 0.2207 0.8285 0.928 0.056 0.012 0.004
#> SRR1087297 2 0.5442 0.6651 0.288 0.672 0.040 0.000
#> SRR1072626 2 0.5277 0.2654 0.008 0.532 0.460 0.000
#> SRR1407428 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1321029 2 0.5013 0.7215 0.292 0.688 0.020 0.000
#> SRR1500282 4 0.1211 0.9509 0.040 0.000 0.000 0.960
#> SRR1100496 3 0.1576 0.8412 0.004 0.048 0.948 0.000
#> SRR1308778 2 0.4867 0.7294 0.232 0.736 0.032 0.000
#> SRR1445304 2 0.3427 0.8207 0.112 0.860 0.028 0.000
#> SRR1099378 1 0.5783 0.4389 0.636 0.032 0.324 0.008
#> SRR1347412 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1099694 2 0.3907 0.8182 0.120 0.836 0.044 0.000
#> SRR1088365 2 0.5731 0.2785 0.028 0.544 0.428 0.000
#> SRR1325752 2 0.6025 0.7154 0.172 0.688 0.140 0.000
#> SRR1416713 2 0.2699 0.8180 0.068 0.904 0.028 0.000
#> SRR1074474 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1469369 2 0.2915 0.7961 0.028 0.892 0.080 0.000
#> SRR1400507 2 0.3497 0.7713 0.024 0.852 0.124 0.000
#> SRR1378179 2 0.5199 0.7691 0.144 0.756 0.100 0.000
#> SRR1377905 2 0.5820 0.7430 0.108 0.700 0.192 0.000
#> SRR1089479 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1073365 2 0.3757 0.7950 0.152 0.828 0.020 0.000
#> SRR1500306 3 0.5436 0.7163 0.040 0.052 0.772 0.136
#> SRR1101566 2 0.6107 0.6600 0.088 0.648 0.264 0.000
#> SRR1350503 2 0.3351 0.7954 0.148 0.844 0.008 0.000
#> SRR1446007 2 0.2266 0.8113 0.004 0.912 0.084 0.000
#> SRR1102875 2 0.4552 0.7770 0.172 0.784 0.044 0.000
#> SRR1380293 2 0.5007 0.6103 0.356 0.636 0.008 0.000
#> SRR1331198 2 0.3182 0.7996 0.096 0.876 0.028 0.000
#> SRR1092686 2 0.5925 0.6447 0.284 0.648 0.068 0.000
#> SRR1069421 3 0.1722 0.8404 0.008 0.048 0.944 0.000
#> SRR1341650 3 0.2699 0.8268 0.028 0.068 0.904 0.000
#> SRR1357276 2 0.5538 0.6198 0.320 0.644 0.036 0.000
#> SRR1498374 2 0.3758 0.8042 0.104 0.848 0.048 0.000
#> SRR1093721 2 0.3401 0.7977 0.152 0.840 0.008 0.000
#> SRR1464660 1 0.2353 0.8354 0.928 0.040 0.008 0.024
#> SRR1402051 3 0.4961 0.1335 0.000 0.448 0.552 0.000
#> SRR1488734 2 0.4418 0.7666 0.184 0.784 0.032 0.000
#> SRR1082616 3 0.1474 0.8415 0.000 0.052 0.948 0.000
#> SRR1099427 2 0.5052 0.7034 0.036 0.720 0.244 0.000
#> SRR1453093 2 0.5310 0.3260 0.012 0.576 0.412 0.000
#> SRR1357064 1 0.3051 0.8226 0.884 0.028 0.000 0.088
#> SRR811237 3 0.4925 0.1473 0.000 0.428 0.572 0.000
#> SRR1100848 2 0.3942 0.7263 0.000 0.764 0.236 0.000
#> SRR1346755 2 0.3224 0.7831 0.016 0.864 0.120 0.000
#> SRR1472529 2 0.3051 0.7934 0.028 0.884 0.088 0.000
#> SRR1398905 3 0.4875 0.7481 0.008 0.072 0.792 0.128
#> SRR1082733 2 0.4624 0.7776 0.164 0.784 0.052 0.000
#> SRR1308035 2 0.4238 0.7283 0.028 0.796 0.176 0.000
#> SRR1466445 2 0.4086 0.7146 0.008 0.776 0.216 0.000
#> SRR1359080 2 0.3354 0.8227 0.084 0.872 0.044 0.000
#> SRR1455825 2 0.2385 0.8094 0.028 0.920 0.052 0.000
#> SRR1389300 2 0.3486 0.8147 0.044 0.864 0.092 0.000
#> SRR812246 3 0.2623 0.8365 0.028 0.064 0.908 0.000
#> SRR1076632 3 0.5312 0.5533 0.040 0.268 0.692 0.000
#> SRR1415567 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1331900 2 0.2578 0.8086 0.036 0.912 0.052 0.000
#> SRR1452099 3 0.1637 0.8426 0.000 0.060 0.940 0.000
#> SRR1352346 1 0.1661 0.8313 0.944 0.052 0.000 0.004
#> SRR1364034 2 0.4410 0.8002 0.128 0.808 0.064 0.000
#> SRR1086046 3 0.1716 0.8401 0.000 0.064 0.936 0.000
#> SRR1407226 1 0.7335 0.6296 0.640 0.072 0.096 0.192
#> SRR1319363 3 0.1820 0.8289 0.020 0.036 0.944 0.000
#> SRR1446961 2 0.3266 0.7993 0.108 0.868 0.024 0.000
#> SRR1486650 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1470152 1 0.3853 0.7955 0.852 0.040 0.008 0.100
#> SRR1454785 2 0.2227 0.8186 0.036 0.928 0.036 0.000
#> SRR1092329 2 0.4284 0.7075 0.020 0.780 0.200 0.000
#> SRR1091476 1 0.2909 0.8034 0.888 0.092 0.020 0.000
#> SRR1073775 2 0.2450 0.8050 0.016 0.912 0.072 0.000
#> SRR1366873 2 0.2222 0.8145 0.060 0.924 0.016 0.000
#> SRR1398114 2 0.3913 0.7987 0.148 0.824 0.028 0.000
#> SRR1089950 1 0.2456 0.8369 0.924 0.028 0.008 0.040
#> SRR1433272 1 0.7729 -0.0734 0.400 0.228 0.372 0.000
#> SRR1075314 3 0.2197 0.8310 0.004 0.080 0.916 0.000
#> SRR1085590 2 0.3913 0.7534 0.028 0.824 0.148 0.000
#> SRR1100752 2 0.5228 0.7701 0.124 0.756 0.120 0.000
#> SRR1391494 2 0.2675 0.8019 0.008 0.892 0.100 0.000
#> SRR1333263 2 0.4605 0.5545 0.000 0.664 0.336 0.000
#> SRR1310231 2 0.4267 0.7639 0.188 0.788 0.024 0.000
#> SRR1094144 3 0.1722 0.8405 0.008 0.048 0.944 0.000
#> SRR1092160 2 0.3931 0.8169 0.128 0.832 0.040 0.000
#> SRR1320300 2 0.1716 0.8194 0.064 0.936 0.000 0.000
#> SRR1322747 2 0.2413 0.8212 0.064 0.916 0.020 0.000
#> SRR1432719 2 0.3658 0.8081 0.144 0.836 0.020 0.000
#> SRR1100728 3 0.2197 0.8280 0.024 0.048 0.928 0.000
#> SRR1087511 3 0.4379 0.7378 0.036 0.172 0.792 0.000
#> SRR1470336 4 0.0895 0.9597 0.000 0.004 0.020 0.976
#> SRR1322536 3 0.1716 0.8389 0.000 0.064 0.936 0.000
#> SRR1100824 1 0.6348 0.6267 0.676 0.048 0.236 0.040
#> SRR1085951 3 0.2197 0.8309 0.004 0.080 0.916 0.000
#> SRR1322046 2 0.2255 0.8050 0.012 0.920 0.068 0.000
#> SRR1316420 1 0.5085 0.7747 0.796 0.052 0.036 0.116
#> SRR1070913 2 0.3080 0.7871 0.024 0.880 0.096 0.000
#> SRR1345806 2 0.4046 0.8188 0.124 0.828 0.048 0.000
#> SRR1313872 2 0.2799 0.7949 0.008 0.884 0.108 0.000
#> SRR1337666 2 0.3895 0.7573 0.184 0.804 0.012 0.000
#> SRR1076823 3 0.3128 0.7245 0.032 0.076 0.888 0.004
#> SRR1093954 2 0.4893 0.7729 0.168 0.768 0.064 0.000
#> SRR1451921 3 0.1557 0.8414 0.000 0.056 0.944 0.000
#> SRR1491257 2 0.8730 0.0148 0.232 0.388 0.044 0.336
#> SRR1416979 2 0.4567 0.6746 0.016 0.740 0.244 0.000
#> SRR1419015 3 0.2032 0.8207 0.028 0.036 0.936 0.000
#> SRR817649 1 0.2197 0.8185 0.916 0.080 0.004 0.000
#> SRR1466376 2 0.2385 0.8215 0.052 0.920 0.028 0.000
#> SRR1392055 2 0.3933 0.7764 0.200 0.792 0.008 0.000
#> SRR1120913 2 0.3009 0.8213 0.052 0.892 0.056 0.000
#> SRR1120869 2 0.5257 0.7650 0.144 0.752 0.104 0.000
#> SRR1319419 2 0.4842 0.7584 0.192 0.760 0.048 0.000
#> SRR816495 2 0.3972 0.7780 0.204 0.788 0.008 0.000
#> SRR818694 2 0.3925 0.7382 0.016 0.808 0.176 0.000
#> SRR1465653 1 0.2140 0.8315 0.932 0.052 0.008 0.008
#> SRR1475952 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1465040 2 0.4104 0.7370 0.028 0.808 0.164 0.000
#> SRR1088461 2 0.6184 0.6579 0.120 0.664 0.216 0.000
#> SRR810129 2 0.4840 0.7115 0.028 0.732 0.240 0.000
#> SRR1400141 2 0.6508 0.5916 0.296 0.600 0.104 0.000
#> SRR1349585 4 0.2215 0.9182 0.016 0.024 0.024 0.936
#> SRR1437576 2 0.2002 0.8181 0.020 0.936 0.044 0.000
#> SRR814407 3 0.5249 0.5950 0.000 0.044 0.708 0.248
#> SRR1332403 2 0.1888 0.8167 0.016 0.940 0.044 0.000
#> SRR1099598 3 0.5106 0.6080 0.040 0.240 0.720 0.000
#> SRR1327723 2 0.3647 0.8044 0.108 0.852 0.040 0.000
#> SRR1392525 3 0.4991 0.2888 0.004 0.388 0.608 0.000
#> SRR1320536 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1083824 2 0.4136 0.7700 0.196 0.788 0.016 0.000
#> SRR1351390 1 0.4590 0.7347 0.804 0.040 0.012 0.144
#> SRR1309141 2 0.3853 0.7974 0.160 0.820 0.020 0.000
#> SRR1452803 2 0.4019 0.7692 0.196 0.792 0.012 0.000
#> SRR811631 2 0.3367 0.7791 0.028 0.864 0.108 0.000
#> SRR1485563 3 0.3975 0.6600 0.000 0.240 0.760 0.000
#> SRR1311531 2 0.2466 0.8012 0.028 0.916 0.056 0.000
#> SRR1353076 2 0.4669 0.7909 0.100 0.796 0.104 0.000
#> SRR1480831 2 0.4564 0.5981 0.000 0.672 0.328 0.000
#> SRR1083892 1 0.2570 0.8344 0.916 0.028 0.004 0.052
#> SRR809873 3 0.1820 0.8289 0.020 0.036 0.944 0.000
#> SRR1341854 2 0.2363 0.8040 0.024 0.920 0.056 0.000
#> SRR1399335 2 0.4957 0.6785 0.300 0.684 0.016 0.000
#> SRR1464209 1 0.3653 0.7953 0.844 0.028 0.000 0.128
#> SRR1389886 2 0.2227 0.8217 0.036 0.928 0.036 0.000
#> SRR1400730 1 0.3219 0.8211 0.892 0.052 0.012 0.044
#> SRR1448008 2 0.3991 0.7423 0.020 0.808 0.172 0.000
#> SRR1087606 1 0.2218 0.8364 0.932 0.028 0.004 0.036
#> SRR1445111 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR816865 3 0.1902 0.8422 0.004 0.064 0.932 0.000
#> SRR1323360 2 0.3497 0.7688 0.024 0.852 0.124 0.000
#> SRR1417364 2 0.4012 0.7781 0.184 0.800 0.016 0.000
#> SRR1480329 1 0.3486 0.7739 0.864 0.092 0.044 0.000
#> SRR1403322 3 0.1557 0.8415 0.000 0.056 0.944 0.000
#> SRR1093625 4 0.0000 0.9878 0.000 0.000 0.000 1.000
#> SRR1479977 2 0.2984 0.8145 0.084 0.888 0.028 0.000
#> SRR1082035 1 0.3385 0.7942 0.880 0.072 0.040 0.008
#> SRR1393046 2 0.2142 0.8085 0.016 0.928 0.056 0.000
#> SRR1466663 2 0.5897 0.7568 0.136 0.700 0.164 0.000
#> SRR1384456 4 0.0000 0.9878 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
#> SRR810713 3 0.4420 0.18460 0.000 0.448 0.548 0.000 0.004
#> SRR808862 4 0.0162 0.86522 0.000 0.000 0.004 0.996 0.000
#> SRR1500382 2 0.5009 0.26377 0.000 0.540 0.428 0.000 0.032
#> SRR1322683 3 0.2248 0.76841 0.000 0.088 0.900 0.012 0.000
#> SRR1329811 5 0.0613 0.86066 0.004 0.008 0.004 0.000 0.984
#> SRR1087297 2 0.1560 0.68910 0.000 0.948 0.020 0.004 0.028
#> SRR1072626 4 0.5803 -0.09227 0.000 0.420 0.092 0.488 0.000
#> SRR1407428 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1321029 3 0.4768 0.51136 0.000 0.040 0.656 0.000 0.304
#> SRR1500282 1 0.3508 0.63704 0.748 0.000 0.000 0.000 0.252
#> SRR1100496 4 0.1331 0.86628 0.000 0.040 0.008 0.952 0.000
#> SRR1308778 2 0.2674 0.71583 0.000 0.868 0.120 0.000 0.012
#> SRR1445304 3 0.3224 0.74011 0.000 0.160 0.824 0.000 0.016
#> SRR1099378 5 0.4562 0.56482 0.000 0.032 0.000 0.292 0.676
#> SRR1347412 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.4621 0.37531 0.000 0.576 0.412 0.004 0.008
#> SRR1088365 2 0.2563 0.59566 0.000 0.872 0.008 0.120 0.000
#> SRR1325752 2 0.1300 0.68343 0.000 0.956 0.016 0.028 0.000
#> SRR1416713 3 0.2573 0.76273 0.000 0.104 0.880 0.000 0.016
#> SRR1074474 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1469369 3 0.1357 0.76508 0.000 0.048 0.948 0.004 0.000
#> SRR1400507 3 0.1484 0.76559 0.000 0.048 0.944 0.008 0.000
#> SRR1378179 2 0.1671 0.71489 0.000 0.924 0.076 0.000 0.000
#> SRR1377905 3 0.4493 0.72194 0.000 0.080 0.796 0.080 0.044
#> SRR1089479 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1073365 2 0.3814 0.64517 0.000 0.720 0.276 0.000 0.004
#> SRR1500306 4 0.3426 0.76085 0.008 0.012 0.008 0.836 0.136
#> SRR1101566 2 0.5391 0.62973 0.000 0.652 0.232 0.116 0.000
#> SRR1350503 3 0.4555 0.48505 0.000 0.344 0.636 0.000 0.020
#> SRR1446007 2 0.4507 0.55528 0.000 0.644 0.340 0.012 0.004
#> SRR1102875 2 0.3461 0.68477 0.000 0.772 0.224 0.004 0.000
#> SRR1380293 2 0.5572 0.63062 0.000 0.644 0.192 0.000 0.164
#> SRR1331198 3 0.1018 0.75554 0.000 0.016 0.968 0.000 0.016
#> SRR1092686 2 0.1710 0.67700 0.000 0.944 0.012 0.024 0.020
#> SRR1069421 4 0.1282 0.86209 0.000 0.044 0.000 0.952 0.004
#> SRR1341650 4 0.3424 0.74026 0.000 0.240 0.000 0.760 0.000
#> SRR1357276 2 0.1648 0.69734 0.000 0.940 0.040 0.000 0.020
#> SRR1498374 3 0.1597 0.75497 0.000 0.020 0.948 0.008 0.024
#> SRR1093721 2 0.4511 0.51148 0.000 0.628 0.356 0.000 0.016
#> SRR1464660 5 0.0162 0.86285 0.000 0.004 0.000 0.000 0.996
#> SRR1402051 4 0.4747 0.13209 0.000 0.016 0.484 0.500 0.000
#> SRR1488734 2 0.3333 0.69412 0.000 0.788 0.208 0.000 0.004
#> SRR1082616 4 0.0566 0.86598 0.000 0.012 0.004 0.984 0.000
#> SRR1099427 2 0.3037 0.71536 0.000 0.864 0.100 0.032 0.004
#> SRR1453093 3 0.4653 0.00987 0.000 0.012 0.516 0.472 0.000
#> SRR1357064 5 0.1364 0.85410 0.036 0.012 0.000 0.000 0.952
#> SRR811237 4 0.2563 0.78840 0.000 0.008 0.120 0.872 0.000
#> SRR1100848 2 0.6069 0.38606 0.000 0.528 0.352 0.116 0.004
#> SRR1346755 3 0.3359 0.73949 0.000 0.164 0.816 0.020 0.000
#> SRR1472529 3 0.0794 0.75988 0.000 0.028 0.972 0.000 0.000
#> SRR1398905 4 0.2207 0.84448 0.044 0.012 0.012 0.924 0.008
#> SRR1082733 2 0.2929 0.70543 0.000 0.820 0.180 0.000 0.000
#> SRR1308035 3 0.1697 0.71597 0.000 0.008 0.932 0.060 0.000
#> SRR1466445 3 0.3916 0.73524 0.000 0.104 0.804 0.092 0.000
#> SRR1359080 3 0.3863 0.64967 0.000 0.248 0.740 0.000 0.012
#> SRR1455825 3 0.2629 0.75224 0.000 0.136 0.860 0.000 0.004
#> SRR1389300 2 0.3870 0.66022 0.000 0.732 0.260 0.004 0.004
#> SRR812246 4 0.0960 0.86601 0.000 0.016 0.004 0.972 0.008
#> SRR1076632 2 0.2971 0.51856 0.000 0.836 0.000 0.156 0.008
#> SRR1415567 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1331900 3 0.1410 0.76592 0.000 0.060 0.940 0.000 0.000
#> SRR1452099 4 0.1012 0.86447 0.000 0.012 0.020 0.968 0.000
#> SRR1352346 5 0.0932 0.86095 0.004 0.020 0.004 0.000 0.972
#> SRR1364034 2 0.3628 0.68829 0.000 0.772 0.216 0.012 0.000
#> SRR1086046 4 0.0566 0.86620 0.000 0.004 0.012 0.984 0.000
#> SRR1407226 2 0.7438 -0.17995 0.312 0.472 0.000 0.120 0.096
#> SRR1319363 4 0.1544 0.85384 0.000 0.068 0.000 0.932 0.000
#> SRR1446961 3 0.1386 0.76162 0.000 0.032 0.952 0.000 0.016
#> SRR1486650 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0290 0.86209 0.008 0.000 0.000 0.000 0.992
#> SRR1454785 3 0.3282 0.71718 0.000 0.188 0.804 0.000 0.008
#> SRR1092329 3 0.1628 0.71674 0.000 0.008 0.936 0.056 0.000
#> SRR1091476 5 0.1419 0.85018 0.000 0.016 0.016 0.012 0.956
#> SRR1073775 3 0.4211 0.44929 0.000 0.360 0.636 0.004 0.000
#> SRR1366873 3 0.3521 0.67208 0.000 0.232 0.764 0.000 0.004
#> SRR1398114 2 0.4111 0.63162 0.000 0.708 0.280 0.004 0.008
#> SRR1089950 5 0.0867 0.85983 0.008 0.008 0.000 0.008 0.976
#> SRR1433272 5 0.6229 0.46817 0.000 0.012 0.164 0.236 0.588
#> SRR1075314 4 0.1364 0.85252 0.000 0.012 0.036 0.952 0.000
#> SRR1085590 3 0.0865 0.73818 0.000 0.004 0.972 0.024 0.000
#> SRR1100752 3 0.3498 0.67098 0.000 0.016 0.848 0.044 0.092
#> SRR1391494 3 0.3934 0.66091 0.000 0.244 0.740 0.016 0.000
#> SRR1333263 3 0.4298 0.63571 0.000 0.060 0.756 0.184 0.000
#> SRR1310231 2 0.4380 0.59597 0.000 0.676 0.304 0.000 0.020
#> SRR1094144 4 0.1197 0.86233 0.000 0.048 0.000 0.952 0.000
#> SRR1092160 3 0.4881 0.11546 0.000 0.460 0.520 0.004 0.016
#> SRR1320300 3 0.4251 0.42593 0.000 0.372 0.624 0.000 0.004
#> SRR1322747 3 0.4264 0.40355 0.000 0.376 0.620 0.000 0.004
#> SRR1432719 2 0.4743 0.11156 0.000 0.512 0.472 0.000 0.016
#> SRR1100728 4 0.2773 0.80408 0.000 0.164 0.000 0.836 0.000
#> SRR1087511 4 0.4108 0.62486 0.000 0.308 0.008 0.684 0.000
#> SRR1470336 1 0.1731 0.90680 0.932 0.004 0.004 0.060 0.000
#> SRR1322536 4 0.1012 0.85824 0.000 0.012 0.020 0.968 0.000
#> SRR1100824 5 0.6691 0.30710 0.000 0.312 0.000 0.260 0.428
#> SRR1085951 4 0.1626 0.84876 0.000 0.016 0.044 0.940 0.000
#> SRR1322046 3 0.4211 0.45269 0.000 0.360 0.636 0.004 0.000
#> SRR1316420 5 0.5879 0.56669 0.148 0.236 0.000 0.004 0.612
#> SRR1070913 3 0.1357 0.76611 0.000 0.048 0.948 0.004 0.000
#> SRR1345806 3 0.4798 0.32835 0.000 0.396 0.580 0.000 0.024
#> SRR1313872 3 0.3124 0.75776 0.000 0.136 0.844 0.016 0.004
#> SRR1337666 3 0.1701 0.74107 0.000 0.016 0.936 0.000 0.048
#> SRR1076823 4 0.3884 0.67135 0.000 0.288 0.000 0.708 0.004
#> SRR1093954 2 0.1792 0.71572 0.000 0.916 0.084 0.000 0.000
#> SRR1451921 4 0.0451 0.86605 0.000 0.004 0.008 0.988 0.000
#> SRR1491257 2 0.3291 0.63876 0.100 0.856 0.028 0.000 0.016
#> SRR1416979 3 0.3670 0.71463 0.000 0.068 0.820 0.112 0.000
#> SRR1419015 4 0.2929 0.78330 0.000 0.180 0.000 0.820 0.000
#> SRR817649 5 0.2124 0.81602 0.000 0.096 0.004 0.000 0.900
#> SRR1466376 3 0.4084 0.52358 0.000 0.328 0.668 0.000 0.004
#> SRR1392055 3 0.4996 0.24532 0.000 0.420 0.548 0.000 0.032
#> SRR1120913 3 0.3456 0.72251 0.000 0.184 0.800 0.000 0.016
#> SRR1120869 2 0.1485 0.69558 0.000 0.948 0.032 0.020 0.000
#> SRR1319419 2 0.2189 0.71434 0.000 0.904 0.084 0.000 0.012
#> SRR816495 3 0.3924 0.74851 0.000 0.120 0.808 0.004 0.068
#> SRR818694 3 0.1740 0.73297 0.000 0.012 0.932 0.056 0.000
#> SRR1465653 5 0.0324 0.86309 0.004 0.004 0.000 0.000 0.992
#> SRR1475952 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1465040 3 0.1469 0.72362 0.000 0.016 0.948 0.036 0.000
#> SRR1088461 2 0.1469 0.68034 0.000 0.948 0.016 0.036 0.000
#> SRR810129 3 0.4567 0.71048 0.000 0.120 0.760 0.116 0.004
#> SRR1400141 2 0.1885 0.67232 0.000 0.936 0.012 0.032 0.020
#> SRR1349585 1 0.1792 0.86849 0.916 0.084 0.000 0.000 0.000
#> SRR1437576 3 0.4273 0.18023 0.000 0.448 0.552 0.000 0.000
#> SRR814407 4 0.2088 0.83706 0.072 0.004 0.004 0.916 0.004
#> SRR1332403 3 0.3635 0.65006 0.000 0.248 0.748 0.000 0.004
#> SRR1099598 2 0.4288 -0.02140 0.000 0.612 0.000 0.384 0.004
#> SRR1327723 2 0.3715 0.66136 0.000 0.736 0.260 0.000 0.004
#> SRR1392525 4 0.2795 0.81973 0.000 0.100 0.028 0.872 0.000
#> SRR1320536 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1083824 2 0.4592 0.54630 0.000 0.644 0.332 0.000 0.024
#> SRR1351390 5 0.1256 0.85509 0.004 0.012 0.008 0.012 0.964
#> SRR1309141 2 0.4298 0.52081 0.000 0.640 0.352 0.000 0.008
#> SRR1452803 2 0.4734 0.46184 0.000 0.604 0.372 0.000 0.024
#> SRR811631 3 0.0912 0.75068 0.000 0.016 0.972 0.012 0.000
#> SRR1485563 4 0.1877 0.83659 0.000 0.012 0.064 0.924 0.000
#> SRR1311531 3 0.1121 0.76411 0.000 0.044 0.956 0.000 0.000
#> SRR1353076 2 0.1764 0.71004 0.000 0.928 0.064 0.000 0.008
#> SRR1480831 2 0.6363 0.15507 0.000 0.444 0.392 0.164 0.000
#> SRR1083892 5 0.0865 0.86214 0.004 0.024 0.000 0.000 0.972
#> SRR809873 4 0.1608 0.85048 0.000 0.072 0.000 0.928 0.000
#> SRR1341854 3 0.2719 0.74992 0.000 0.144 0.852 0.004 0.000
#> SRR1399335 2 0.4772 0.68245 0.000 0.728 0.164 0.000 0.108
#> SRR1464209 5 0.1106 0.85934 0.024 0.012 0.000 0.000 0.964
#> SRR1389886 3 0.4589 0.05271 0.000 0.472 0.520 0.004 0.004
#> SRR1400730 5 0.0740 0.85951 0.004 0.008 0.008 0.000 0.980
#> SRR1448008 3 0.3359 0.75929 0.000 0.108 0.840 0.052 0.000
#> SRR1087606 5 0.0613 0.86200 0.004 0.008 0.000 0.004 0.984
#> SRR1445111 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR816865 4 0.0880 0.86562 0.000 0.032 0.000 0.968 0.000
#> SRR1323360 3 0.1087 0.73805 0.000 0.008 0.968 0.016 0.008
#> SRR1417364 3 0.2139 0.75223 0.000 0.032 0.916 0.000 0.052
#> SRR1480329 5 0.3366 0.73228 0.000 0.212 0.000 0.004 0.784
#> SRR1403322 4 0.0451 0.86605 0.000 0.004 0.008 0.988 0.000
#> SRR1093625 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
#> SRR1479977 3 0.2625 0.76133 0.000 0.108 0.876 0.000 0.016
#> SRR1082035 5 0.3086 0.76328 0.000 0.180 0.000 0.004 0.816
#> SRR1393046 3 0.1768 0.76664 0.000 0.072 0.924 0.000 0.004
#> SRR1466663 2 0.4737 0.66220 0.000 0.712 0.228 0.056 0.004
#> SRR1384456 1 0.0000 0.96450 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> SRR810713 2 0.4174 0.59970 0.000 0.732 0.184 0.000 0.000 0.084
#> SRR808862 4 0.2100 0.57721 0.000 0.000 0.004 0.884 0.000 0.112
#> SRR1500382 3 0.4531 0.34120 0.000 0.280 0.668 0.000 0.016 0.036
#> SRR1322683 2 0.3558 0.63845 0.000 0.792 0.160 0.004 0.000 0.044
#> SRR1329811 5 0.0146 0.83764 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1087297 3 0.1218 0.48876 0.000 0.012 0.956 0.000 0.004 0.028
#> SRR1072626 3 0.5302 0.18252 0.000 0.040 0.560 0.360 0.000 0.040
#> SRR1407428 1 0.0146 0.93885 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1321029 5 0.7680 -0.19851 0.000 0.240 0.252 0.000 0.304 0.204
#> SRR1500282 1 0.3828 0.18508 0.560 0.000 0.000 0.000 0.440 0.000
#> SRR1100496 4 0.3756 0.45399 0.000 0.004 0.004 0.676 0.000 0.316
#> SRR1308778 3 0.3732 0.42375 0.000 0.076 0.780 0.000 0.000 0.144
#> SRR1445304 2 0.3002 0.60743 0.000 0.848 0.048 0.000 0.004 0.100
#> SRR1099378 5 0.5078 0.44750 0.000 0.000 0.008 0.196 0.656 0.140
#> SRR1347412 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1099694 2 0.4886 0.22944 0.000 0.508 0.432 0.000 0.000 0.060
#> SRR1088365 3 0.5845 -0.34046 0.000 0.008 0.472 0.152 0.000 0.368
#> SRR1325752 3 0.4240 0.09602 0.000 0.016 0.672 0.016 0.000 0.296
#> SRR1416713 2 0.2307 0.62216 0.000 0.896 0.032 0.000 0.004 0.068
#> SRR1074474 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1469369 2 0.5890 0.20574 0.000 0.448 0.340 0.000 0.000 0.212
#> SRR1400507 2 0.4114 0.58950 0.000 0.732 0.196 0.000 0.000 0.072
#> SRR1378179 3 0.5070 0.06752 0.000 0.100 0.584 0.000 0.000 0.316
#> SRR1377905 2 0.3601 0.50478 0.000 0.800 0.004 0.036 0.008 0.152
#> SRR1089479 1 0.0146 0.93885 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1073365 3 0.2730 0.52282 0.000 0.152 0.836 0.000 0.000 0.012
#> SRR1500306 4 0.5713 0.31839 0.004 0.000 0.000 0.504 0.156 0.336
#> SRR1101566 3 0.6033 0.19382 0.000 0.020 0.436 0.120 0.004 0.420
#> SRR1350503 3 0.5707 0.29823 0.000 0.252 0.544 0.000 0.004 0.200
#> SRR1446007 3 0.4392 0.47497 0.000 0.072 0.708 0.004 0.000 0.216
#> SRR1102875 3 0.4273 0.44253 0.000 0.148 0.732 0.000 0.000 0.120
#> SRR1380293 6 0.7708 0.40892 0.000 0.252 0.244 0.000 0.216 0.288
#> SRR1331198 2 0.1934 0.64834 0.000 0.916 0.044 0.000 0.000 0.040
#> SRR1092686 3 0.3837 0.26689 0.000 0.008 0.744 0.008 0.012 0.228
#> SRR1069421 4 0.4601 0.35545 0.000 0.028 0.004 0.588 0.004 0.376
#> SRR1341650 4 0.4936 0.30521 0.000 0.024 0.028 0.552 0.000 0.396
#> SRR1357276 3 0.1738 0.48053 0.000 0.004 0.928 0.000 0.016 0.052
#> SRR1498374 2 0.5561 0.39850 0.000 0.564 0.264 0.000 0.004 0.168
#> SRR1093721 3 0.5117 0.38511 0.000 0.076 0.580 0.000 0.008 0.336
#> SRR1464660 5 0.0405 0.83882 0.000 0.000 0.004 0.000 0.988 0.008
#> SRR1402051 2 0.5221 0.04059 0.000 0.560 0.000 0.328 0.000 0.112
#> SRR1488734 3 0.2230 0.52150 0.000 0.084 0.892 0.000 0.000 0.024
#> SRR1082616 4 0.0458 0.59404 0.000 0.000 0.000 0.984 0.000 0.016
#> SRR1099427 3 0.4425 0.38764 0.000 0.012 0.704 0.052 0.000 0.232
#> SRR1453093 4 0.5349 0.33369 0.000 0.216 0.004 0.608 0.000 0.172
#> SRR1357064 5 0.0837 0.83545 0.020 0.000 0.004 0.000 0.972 0.004
#> SRR811237 4 0.5748 0.05811 0.000 0.308 0.000 0.496 0.000 0.196
#> SRR1100848 3 0.6293 0.38296 0.000 0.208 0.552 0.184 0.000 0.056
#> SRR1346755 2 0.3924 0.61904 0.000 0.740 0.208 0.000 0.000 0.052
#> SRR1472529 2 0.1245 0.63214 0.000 0.952 0.016 0.000 0.000 0.032
#> SRR1398905 4 0.4399 0.49026 0.056 0.000 0.004 0.688 0.000 0.252
#> SRR1082733 3 0.2724 0.50774 0.000 0.084 0.864 0.000 0.000 0.052
#> SRR1308035 2 0.2664 0.62713 0.000 0.888 0.032 0.020 0.004 0.056
#> SRR1466445 2 0.5987 0.53344 0.000 0.612 0.188 0.084 0.000 0.116
#> SRR1359080 2 0.4441 0.46061 0.000 0.620 0.344 0.000 0.004 0.032
#> SRR1455825 3 0.5784 -0.10740 0.000 0.408 0.416 0.000 0.000 0.176
#> SRR1389300 3 0.2942 0.51159 0.000 0.132 0.836 0.000 0.000 0.032
#> SRR812246 4 0.6043 0.30731 0.000 0.008 0.080 0.456 0.036 0.420
#> SRR1076632 3 0.5095 -0.10091 0.000 0.000 0.584 0.104 0.000 0.312
#> SRR1415567 1 0.0146 0.93885 0.996 0.000 0.000 0.004 0.000 0.000
#> SRR1331900 2 0.4203 0.57151 0.000 0.716 0.216 0.000 0.000 0.068
#> SRR1452099 4 0.5103 0.35837 0.000 0.104 0.004 0.612 0.000 0.280
#> SRR1352346 5 0.0622 0.83868 0.000 0.000 0.012 0.000 0.980 0.008
#> SRR1364034 3 0.5991 -0.11432 0.000 0.256 0.436 0.000 0.000 0.308
#> SRR1086046 4 0.3595 0.49336 0.000 0.000 0.008 0.704 0.000 0.288
#> SRR1407226 6 0.8591 0.30583 0.192 0.016 0.196 0.132 0.080 0.384
#> SRR1319363 4 0.3969 0.42814 0.000 0.004 0.008 0.644 0.000 0.344
#> SRR1446961 2 0.5069 0.47222 0.000 0.628 0.256 0.000 0.004 0.112
#> SRR1486650 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1470152 5 0.0146 0.83764 0.000 0.000 0.000 0.000 0.996 0.004
#> SRR1454785 2 0.4065 0.53490 0.000 0.672 0.300 0.000 0.000 0.028
#> SRR1092329 2 0.1625 0.60607 0.000 0.928 0.000 0.012 0.000 0.060
#> SRR1091476 5 0.2530 0.79022 0.000 0.008 0.008 0.008 0.880 0.096
#> SRR1073775 3 0.5336 0.26474 0.000 0.284 0.572 0.000 0.000 0.144
#> SRR1366873 3 0.5551 0.05901 0.000 0.360 0.496 0.000 0.000 0.144
#> SRR1398114 2 0.6106 -0.20077 0.000 0.376 0.324 0.000 0.000 0.300
#> SRR1089950 5 0.1124 0.83178 0.000 0.000 0.008 0.000 0.956 0.036
#> SRR1433272 2 0.6903 -0.33221 0.000 0.376 0.000 0.300 0.052 0.272
#> SRR1075314 4 0.1644 0.58904 0.000 0.004 0.000 0.920 0.000 0.076
#> SRR1085590 2 0.2036 0.59482 0.000 0.912 0.008 0.016 0.000 0.064
#> SRR1100752 2 0.7041 0.36422 0.000 0.520 0.144 0.016 0.120 0.200
#> SRR1391494 2 0.3493 0.63086 0.000 0.800 0.136 0.000 0.000 0.064
#> SRR1333263 2 0.5416 0.08062 0.000 0.580 0.000 0.196 0.000 0.224
#> SRR1310231 3 0.3558 0.47693 0.000 0.212 0.760 0.000 0.000 0.028
#> SRR1094144 4 0.4646 0.34737 0.000 0.032 0.008 0.580 0.000 0.380
#> SRR1092160 2 0.4402 0.54778 0.000 0.716 0.168 0.000 0.000 0.116
#> SRR1320300 3 0.4940 0.00246 0.000 0.400 0.532 0.000 0.000 0.068
#> SRR1322747 2 0.4326 0.37162 0.000 0.572 0.404 0.000 0.000 0.024
#> SRR1432719 2 0.4696 0.41775 0.000 0.588 0.356 0.000 0.000 0.056
#> SRR1100728 4 0.4803 0.30968 0.000 0.040 0.008 0.556 0.000 0.396
#> SRR1087511 4 0.6231 0.16775 0.000 0.000 0.296 0.368 0.004 0.332
#> SRR1470336 4 0.6160 0.15854 0.216 0.000 0.000 0.404 0.008 0.372
#> SRR1322536 4 0.1501 0.58754 0.000 0.000 0.000 0.924 0.000 0.076
#> SRR1100824 6 0.7468 0.20174 0.000 0.000 0.188 0.168 0.280 0.364
#> SRR1085951 4 0.3161 0.55883 0.000 0.080 0.004 0.840 0.000 0.076
#> SRR1322046 2 0.4011 0.53666 0.000 0.672 0.304 0.000 0.000 0.024
#> SRR1316420 5 0.4850 0.63466 0.112 0.000 0.156 0.000 0.708 0.024
#> SRR1070913 2 0.2457 0.65401 0.000 0.880 0.084 0.000 0.000 0.036
#> SRR1345806 3 0.5543 0.19164 0.000 0.312 0.552 0.000 0.008 0.128
#> SRR1313872 2 0.3191 0.55790 0.000 0.832 0.024 0.016 0.000 0.128
#> SRR1337666 2 0.5951 0.41170 0.000 0.592 0.216 0.000 0.048 0.144
#> SRR1076823 4 0.5235 0.30596 0.004 0.000 0.284 0.596 0.000 0.116
#> SRR1093954 3 0.3841 0.39294 0.000 0.068 0.764 0.000 0.000 0.168
#> SRR1451921 4 0.0458 0.59485 0.000 0.000 0.000 0.984 0.000 0.016
#> SRR1491257 3 0.4008 0.24010 0.196 0.000 0.740 0.000 0.000 0.064
#> SRR1416979 2 0.3356 0.52224 0.000 0.824 0.004 0.072 0.000 0.100
#> SRR1419015 4 0.4007 0.49636 0.000 0.000 0.052 0.728 0.000 0.220
#> SRR817649 5 0.2444 0.78784 0.000 0.012 0.068 0.000 0.892 0.028
#> SRR1466376 2 0.4277 0.46302 0.000 0.616 0.356 0.000 0.000 0.028
#> SRR1392055 3 0.5158 -0.07313 0.000 0.436 0.500 0.000 0.020 0.044
#> SRR1120913 2 0.2760 0.62579 0.000 0.868 0.052 0.000 0.004 0.076
#> SRR1120869 3 0.5764 -0.21381 0.000 0.092 0.504 0.028 0.000 0.376
#> SRR1319419 3 0.1895 0.49608 0.000 0.016 0.912 0.000 0.000 0.072
#> SRR816495 2 0.6295 0.09512 0.000 0.412 0.388 0.000 0.024 0.176
#> SRR818694 2 0.5098 0.56060 0.000 0.680 0.172 0.024 0.000 0.124
#> SRR1465653 5 0.0146 0.83838 0.000 0.000 0.004 0.000 0.996 0.000
#> SRR1475952 1 0.2100 0.85641 0.884 0.000 0.000 0.004 0.000 0.112
#> SRR1465040 2 0.2203 0.62192 0.000 0.896 0.016 0.004 0.000 0.084
#> SRR1088461 3 0.4334 0.22753 0.000 0.028 0.708 0.024 0.000 0.240
#> SRR810129 2 0.4974 0.31921 0.000 0.672 0.012 0.088 0.004 0.224
#> SRR1400141 3 0.3632 0.26617 0.000 0.008 0.752 0.008 0.004 0.228
#> SRR1349585 1 0.1858 0.84579 0.904 0.000 0.092 0.000 0.000 0.004
#> SRR1437576 2 0.4332 0.51299 0.000 0.644 0.316 0.000 0.000 0.040
#> SRR814407 4 0.1950 0.58172 0.064 0.000 0.000 0.912 0.000 0.024
#> SRR1332403 2 0.3202 0.64397 0.000 0.816 0.144 0.000 0.000 0.040
#> SRR1099598 3 0.5320 0.11812 0.000 0.000 0.572 0.288 0.000 0.140
#> SRR1327723 3 0.1895 0.52624 0.000 0.072 0.912 0.000 0.000 0.016
#> SRR1392525 4 0.3469 0.55559 0.000 0.020 0.032 0.816 0.000 0.132
#> SRR1320536 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1083824 3 0.3732 0.45168 0.000 0.228 0.744 0.000 0.004 0.024
#> SRR1351390 5 0.1524 0.81859 0.000 0.000 0.000 0.008 0.932 0.060
#> SRR1309141 2 0.5870 0.11860 0.000 0.480 0.244 0.000 0.000 0.276
#> SRR1452803 3 0.5301 -0.16356 0.000 0.444 0.476 0.000 0.012 0.068
#> SRR811631 2 0.1633 0.64132 0.000 0.932 0.024 0.000 0.000 0.044
#> SRR1485563 4 0.5279 0.33026 0.000 0.108 0.008 0.596 0.000 0.288
#> SRR1311531 3 0.6338 0.05603 0.000 0.308 0.384 0.004 0.004 0.300
#> SRR1353076 3 0.1719 0.47561 0.000 0.016 0.924 0.000 0.000 0.060
#> SRR1480831 3 0.6411 -0.17783 0.000 0.408 0.408 0.136 0.000 0.048
#> SRR1083892 5 0.0622 0.83695 0.000 0.000 0.008 0.000 0.980 0.012
#> SRR809873 4 0.3037 0.55657 0.000 0.004 0.016 0.820 0.000 0.160
#> SRR1341854 2 0.1757 0.65996 0.000 0.916 0.076 0.000 0.000 0.008
#> SRR1399335 6 0.7142 0.33976 0.000 0.220 0.320 0.008 0.064 0.388
#> SRR1464209 5 0.1148 0.83341 0.016 0.000 0.004 0.000 0.960 0.020
#> SRR1389886 2 0.4389 0.42707 0.000 0.596 0.372 0.000 0.000 0.032
#> SRR1400730 5 0.0891 0.83352 0.000 0.000 0.008 0.000 0.968 0.024
#> SRR1448008 2 0.5997 0.46919 0.000 0.568 0.272 0.060 0.000 0.100
#> SRR1087606 5 0.0777 0.83814 0.000 0.000 0.004 0.000 0.972 0.024
#> SRR1445111 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR816865 4 0.5458 0.20197 0.000 0.112 0.004 0.512 0.000 0.372
#> SRR1323360 2 0.1950 0.62703 0.000 0.924 0.020 0.004 0.008 0.044
#> SRR1417364 2 0.5057 0.54923 0.000 0.668 0.228 0.000 0.032 0.072
#> SRR1480329 5 0.6711 0.19674 0.000 0.000 0.300 0.032 0.356 0.312
#> SRR1403322 4 0.0000 0.59466 0.000 0.000 0.000 1.000 0.000 0.000
#> SRR1093625 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
#> SRR1479977 2 0.4974 0.42676 0.000 0.588 0.324 0.000 0.000 0.088
#> SRR1082035 5 0.3172 0.71831 0.000 0.000 0.128 0.000 0.824 0.048
#> SRR1393046 2 0.1863 0.63927 0.000 0.920 0.036 0.000 0.000 0.044
#> SRR1466663 6 0.7653 0.37050 0.000 0.316 0.140 0.184 0.012 0.348
#> SRR1384456 1 0.0000 0.93997 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
sessionInfo()
#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: CentOS Linux 7 (Core)
#>
#> Matrix products: default
#> BLAS: /usr/lib64/libblas.so.3.4.2
#> LAPACK: /usr/lib64/liblapack.so.3.4.2
#>
#> locale:
#> [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8
#> [4] LC_COLLATE=en_GB.UTF-8 LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
#> [7] LC_PAPER=en_GB.UTF-8 LC_NAME=C LC_ADDRESS=C
#> [10] LC_TELEPHONE=C LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
#>
#> attached base packages:
#> [1] grid stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] genefilter_1.66.0 ComplexHeatmap_2.3.1 markdown_1.1 knitr_1.26
#> [5] GetoptLong_0.1.7 cola_1.3.2
#>
#> loaded via a namespace (and not attached):
#> [1] circlize_0.4.8 shape_1.4.4 xfun_0.11 slam_0.1-46
#> [5] lattice_0.20-38 splines_3.6.0 colorspace_1.4-1 vctrs_0.2.0
#> [9] stats4_3.6.0 blob_1.2.0 XML_3.98-1.20 survival_2.44-1.1
#> [13] rlang_0.4.2 pillar_1.4.2 DBI_1.0.0 BiocGenerics_0.30.0
#> [17] bit64_0.9-7 RColorBrewer_1.1-2 matrixStats_0.55.0 stringr_1.4.0
#> [21] GlobalOptions_0.1.1 evaluate_0.14 memoise_1.1.0 Biobase_2.44.0
#> [25] IRanges_2.18.3 parallel_3.6.0 AnnotationDbi_1.46.1 highr_0.8
#> [29] Rcpp_1.0.3 xtable_1.8-4 backports_1.1.5 S4Vectors_0.22.1
#> [33] annotate_1.62.0 skmeans_0.2-11 bit_1.1-14 microbenchmark_1.4-7
#> [37] brew_1.0-6 impute_1.58.0 rjson_0.2.20 png_0.1-7
#> [41] digest_0.6.23 stringi_1.4.3 polyclip_1.10-0 clue_0.3-57
#> [45] tools_3.6.0 bitops_1.0-6 magrittr_1.5 eulerr_6.0.0
#> [49] RCurl_1.95-4.12 RSQLite_2.1.4 tibble_2.1.3 cluster_2.1.0
#> [53] crayon_1.3.4 pkgconfig_2.0.3 zeallot_0.1.0 Matrix_1.2-17
#> [57] xml2_1.2.2 httr_1.4.1 R6_2.4.1 mclust_5.4.5
#> [61] compiler_3.6.0