Date: 2019-12-25 22:11:55 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 46361 rows and 139 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, anno = anno)
Dimension of the input matrix:
mat = get_matrix(res_list)
dim(mat)
#> [1] 46361 139
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, top_annotation = HeatmapAnnotation(df = get_anno(res_list),
col = get_anno_col(res_list)), 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:kmeans | 2 | 1.000 | 1.000 | 1.000 | ** | |
| SD:skmeans | 3 | 1.000 | 0.962 | 0.984 | ** | 2 |
| SD:pam | 3 | 1.000 | 0.987 | 0.994 | ** | 2 |
| SD:mclust | 2 | 1.000 | 1.000 | 1.000 | ** | |
| SD:NMF | 2 | 1.000 | 1.000 | 1.000 | ** | |
| CV:kmeans | 2 | 1.000 | 1.000 | 1.000 | ** | |
| CV:pam | 3 | 1.000 | 0.983 | 0.993 | ** | 2 |
| CV:mclust | 2 | 1.000 | 1.000 | 1.000 | ** | |
| CV:NMF | 2 | 1.000 | 1.000 | 1.000 | ** | |
| MAD:hclust | 3 | 1.000 | 0.972 | 0.988 | ** | 2 |
| MAD:kmeans | 2 | 1.000 | 1.000 | 1.000 | ** | |
| MAD:skmeans | 4 | 1.000 | 0.960 | 0.974 | ** | 2,3 |
| MAD:pam | 2 | 1.000 | 0.997 | 0.999 | ** | |
| MAD:mclust | 2 | 1.000 | 1.000 | 1.000 | ** | |
| MAD:NMF | 2 | 1.000 | 1.000 | 1.000 | ** | |
| ATC:kmeans | 2 | 1.000 | 1.000 | 1.000 | ** | |
| ATC:skmeans | 3 | 1.000 | 0.986 | 0.977 | ** | 2 |
| ATC:pam | 4 | 1.000 | 0.989 | 0.996 | ** | 2,3 |
| ATC:mclust | 2 | 1.000 | 1.000 | 1.000 | ** | |
| ATC:hclust | 3 | 0.967 | 0.974 | 0.987 | ** | 2 |
| CV:hclust | 4 | 0.963 | 0.918 | 0.922 | ** | 2,3 |
| SD:hclust | 4 | 0.958 | 0.917 | 0.929 | ** | 2,3 |
| CV:skmeans | 3 | 0.941 | 0.948 | 0.972 | * | 2 |
| ATC:NMF | 3 | 0.931 | 0.947 | 0.928 | * | 2 |
**: 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 1 1.000 1.000 0.479 0.521 0.521
#> CV:NMF 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:NMF 2 1 1.000 1.000 0.479 0.521 0.521
#> ATC:NMF 2 1 1.000 1.000 0.479 0.521 0.521
#> SD:skmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> CV:skmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:skmeans 2 1 0.994 0.997 0.480 0.521 0.521
#> ATC:skmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> SD:mclust 2 1 1.000 1.000 0.479 0.521 0.521
#> CV:mclust 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:mclust 2 1 1.000 1.000 0.479 0.521 0.521
#> ATC:mclust 2 1 1.000 1.000 0.479 0.521 0.521
#> SD:kmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> CV:kmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:kmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> ATC:kmeans 2 1 1.000 1.000 0.479 0.521 0.521
#> SD:pam 2 1 1.000 1.000 0.479 0.521 0.521
#> CV:pam 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:pam 2 1 0.997 0.999 0.480 0.521 0.521
#> ATC:pam 2 1 1.000 1.000 0.479 0.521 0.521
#> SD:hclust 2 1 1.000 1.000 0.479 0.521 0.521
#> CV:hclust 2 1 1.000 1.000 0.479 0.521 0.521
#> MAD:hclust 2 1 1.000 1.000 0.479 0.521 0.521
#> ATC:hclust 2 1 1.000 1.000 0.479 0.521 0.521
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.784 0.842 0.867 0.1113 0.991 0.983
#> CV:NMF 3 0.852 0.937 0.923 0.1006 1.000 1.000
#> MAD:NMF 3 1.000 0.960 0.980 0.0487 0.984 0.969
#> ATC:NMF 3 0.931 0.947 0.928 0.1159 0.926 0.857
#> SD:skmeans 3 1.000 0.962 0.984 0.3834 0.815 0.645
#> CV:skmeans 3 0.941 0.948 0.972 0.3849 0.815 0.645
#> MAD:skmeans 3 1.000 0.991 0.997 0.3819 0.815 0.645
#> ATC:skmeans 3 1.000 0.986 0.977 0.1637 0.926 0.857
#> SD:mclust 3 0.707 0.832 0.874 0.3258 0.823 0.661
#> CV:mclust 3 0.727 0.849 0.890 0.3296 0.823 0.661
#> MAD:mclust 3 0.751 0.917 0.906 0.3354 0.818 0.650
#> ATC:mclust 3 0.591 0.840 0.786 0.2677 1.000 1.000
#> SD:kmeans 3 0.746 0.863 0.812 0.2844 0.821 0.657
#> CV:kmeans 3 0.714 0.702 0.690 0.2813 0.815 0.645
#> MAD:kmeans 3 0.731 0.941 0.826 0.2945 0.815 0.645
#> ATC:kmeans 3 0.619 0.826 0.785 0.2814 1.000 1.000
#> SD:pam 3 1.000 0.987 0.994 0.1528 0.927 0.859
#> CV:pam 3 1.000 0.983 0.993 0.1527 0.928 0.861
#> MAD:pam 3 0.713 0.806 0.846 0.2924 0.834 0.681
#> ATC:pam 3 1.000 0.990 0.997 0.1519 0.927 0.859
#> SD:hclust 3 1.000 0.975 0.990 0.1477 0.931 0.867
#> CV:hclust 3 1.000 0.977 0.991 0.1480 0.931 0.867
#> MAD:hclust 3 1.000 0.972 0.988 0.1533 0.927 0.859
#> ATC:hclust 3 0.967 0.974 0.987 0.1485 0.928 0.861
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.582 0.464 0.806 0.1638 0.994 0.989
#> CV:NMF 4 0.583 0.639 0.811 0.1650 0.966 0.935
#> MAD:NMF 4 0.617 0.693 0.821 0.2400 0.918 0.840
#> ATC:NMF 4 0.929 0.930 0.944 0.0321 0.994 0.988
#> SD:skmeans 4 0.824 0.911 0.916 0.1093 0.924 0.774
#> CV:skmeans 4 0.800 0.912 0.894 0.1083 0.924 0.774
#> MAD:skmeans 4 1.000 0.960 0.974 0.1117 0.925 0.777
#> ATC:skmeans 4 0.665 0.889 0.850 0.1691 1.000 1.000
#> SD:mclust 4 0.551 0.514 0.718 0.0905 0.944 0.843
#> CV:mclust 4 0.553 0.680 0.721 0.0878 0.902 0.724
#> MAD:mclust 4 0.627 0.598 0.788 0.1263 0.906 0.737
#> ATC:mclust 4 0.611 0.469 0.739 0.1278 0.830 0.674
#> SD:kmeans 4 0.620 0.871 0.808 0.1412 0.892 0.697
#> CV:kmeans 4 0.608 0.870 0.798 0.1437 0.834 0.567
#> MAD:kmeans 4 0.605 0.850 0.761 0.1272 0.924 0.774
#> ATC:kmeans 4 0.558 0.487 0.533 0.1322 0.740 0.503
#> SD:pam 4 0.813 0.904 0.946 0.3273 0.816 0.589
#> CV:pam 4 0.787 0.889 0.910 0.3263 0.816 0.591
#> MAD:pam 4 0.858 0.885 0.949 0.1699 0.882 0.686
#> ATC:pam 4 1.000 0.989 0.996 0.0390 0.976 0.947
#> SD:hclust 4 0.958 0.917 0.929 0.0409 0.972 0.939
#> CV:hclust 4 0.963 0.918 0.922 0.0414 0.972 0.939
#> MAD:hclust 4 0.777 0.787 0.897 0.2236 0.840 0.643
#> ATC:hclust 4 1.000 0.978 0.991 0.0421 0.979 0.954
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.531 0.603 0.768 0.1029 0.812 0.631
#> CV:NMF 5 0.533 0.609 0.763 0.1162 0.789 0.585
#> MAD:NMF 5 0.622 0.655 0.825 0.1571 0.786 0.530
#> ATC:NMF 5 0.890 0.917 0.936 0.0241 0.994 0.988
#> SD:skmeans 5 0.805 0.835 0.871 0.0605 0.953 0.824
#> CV:skmeans 5 0.792 0.811 0.828 0.0592 0.958 0.843
#> MAD:skmeans 5 0.842 0.790 0.860 0.0658 0.924 0.725
#> ATC:skmeans 5 0.629 0.599 0.768 0.0780 0.834 0.629
#> SD:mclust 5 0.541 0.645 0.747 0.0609 0.915 0.744
#> CV:mclust 5 0.553 0.566 0.769 0.0815 0.922 0.748
#> MAD:mclust 5 0.648 0.496 0.738 0.0707 0.831 0.500
#> ATC:mclust 5 0.616 0.518 0.720 0.0910 0.784 0.482
#> SD:kmeans 5 0.659 0.612 0.766 0.0726 0.995 0.981
#> CV:kmeans 5 0.546 0.780 0.751 0.0675 0.991 0.967
#> MAD:kmeans 5 0.714 0.768 0.765 0.0837 0.984 0.941
#> ATC:kmeans 5 0.544 0.569 0.652 0.0732 0.797 0.397
#> SD:pam 5 0.763 0.824 0.903 0.0363 0.961 0.856
#> CV:pam 5 0.742 0.813 0.894 0.0390 0.959 0.848
#> MAD:pam 5 0.839 0.880 0.929 0.0501 0.961 0.860
#> ATC:pam 5 0.829 0.926 0.949 0.0548 0.992 0.981
#> SD:hclust 5 0.796 0.796 0.876 0.0804 0.984 0.962
#> CV:hclust 5 0.760 0.794 0.865 0.0859 0.993 0.983
#> MAD:hclust 5 0.716 0.674 0.803 0.0590 0.963 0.873
#> ATC:hclust 5 0.997 0.967 0.985 0.0121 0.991 0.978
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.511 0.560 0.723 0.06682 0.878 0.651
#> CV:NMF 6 0.499 0.531 0.693 0.06018 0.898 0.701
#> MAD:NMF 6 0.543 0.483 0.664 0.03258 0.876 0.597
#> ATC:NMF 6 0.876 0.911 0.928 0.02629 0.994 0.988
#> SD:skmeans 6 0.762 0.758 0.830 0.04171 0.957 0.815
#> CV:skmeans 6 0.777 0.775 0.825 0.04278 0.955 0.806
#> MAD:skmeans 6 0.809 0.714 0.845 0.04405 0.941 0.735
#> ATC:skmeans 6 0.616 0.581 0.748 0.04875 0.840 0.544
#> SD:mclust 6 0.538 0.610 0.648 0.03872 0.932 0.766
#> CV:mclust 6 0.531 0.602 0.670 0.02429 0.960 0.856
#> MAD:mclust 6 0.688 0.667 0.776 0.04479 0.906 0.635
#> ATC:mclust 6 0.659 0.580 0.730 0.06435 0.845 0.491
#> SD:kmeans 6 0.656 0.622 0.701 0.05320 0.905 0.644
#> CV:kmeans 6 0.658 0.688 0.742 0.05951 0.915 0.684
#> MAD:kmeans 6 0.690 0.659 0.733 0.05053 0.906 0.652
#> ATC:kmeans 6 0.608 0.538 0.692 0.06102 0.919 0.660
#> SD:pam 6 0.752 0.757 0.828 0.03505 0.968 0.874
#> CV:pam 6 0.737 0.741 0.822 0.03751 0.968 0.874
#> MAD:pam 6 0.784 0.676 0.828 0.05850 0.907 0.643
#> ATC:pam 6 0.651 0.538 0.806 0.14872 0.913 0.794
#> SD:hclust 6 0.733 0.766 0.869 0.08949 0.927 0.825
#> CV:hclust 6 0.785 0.746 0.853 0.06920 0.931 0.835
#> MAD:hclust 6 0.663 0.678 0.771 0.03759 0.909 0.683
#> ATC:hclust 6 0.986 0.948 0.977 0.00601 0.999 0.998
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res_list, k = 2)
#> n disease.state(p) gender(p) k
#> SD:NMF 139 0.0773 1 2
#> CV:NMF 139 0.0773 1 2
#> MAD:NMF 139 0.0773 1 2
#> ATC:NMF 139 0.0773 1 2
#> SD:skmeans 139 0.0773 1 2
#> CV:skmeans 139 0.0773 1 2
#> MAD:skmeans 139 0.0773 1 2
#> ATC:skmeans 139 0.0773 1 2
#> SD:mclust 139 0.0773 1 2
#> CV:mclust 139 0.0773 1 2
#> MAD:mclust 139 0.0773 1 2
#> ATC:mclust 139 0.0773 1 2
#> SD:kmeans 139 0.0773 1 2
#> CV:kmeans 139 0.0773 1 2
#> MAD:kmeans 139 0.0773 1 2
#> ATC:kmeans 139 0.0773 1 2
#> SD:pam 139 0.0773 1 2
#> CV:pam 139 0.0773 1 2
#> MAD:pam 139 0.0773 1 2
#> ATC:pam 139 0.0773 1 2
#> SD:hclust 139 0.0773 1 2
#> CV:hclust 139 0.0773 1 2
#> MAD:hclust 139 0.0773 1 2
#> ATC:hclust 139 0.0773 1 2
test_to_known_factors(res_list, k = 3)
#> n disease.state(p) gender(p) k
#> SD:NMF 134 1.29e-01 1.0000 3
#> CV:NMF 139 7.73e-02 1.0000 3
#> MAD:NMF 137 7.12e-02 0.8683 3
#> ATC:NMF 136 1.29e-01 0.9639 3
#> SD:skmeans 136 7.03e-07 0.4420 3
#> CV:skmeans 137 5.59e-07 0.4251 3
#> MAD:skmeans 138 4.45e-07 0.4087 3
#> ATC:skmeans 139 8.43e-02 0.9486 3
#> SD:mclust 131 1.42e-04 0.2978 3
#> CV:mclust 134 1.92e-04 0.1616 3
#> MAD:mclust 137 5.66e-07 0.0787 3
#> ATC:mclust 139 7.73e-02 1.0000 3
#> SD:kmeans 135 8.84e-07 0.4594 3
#> CV:kmeans 126 1.08e-06 0.4220 3
#> MAD:kmeans 139 3.55e-07 0.3929 3
#> ATC:kmeans 139 7.73e-02 1.0000 3
#> SD:pam 139 1.28e-01 0.9215 3
#> CV:pam 138 1.37e-01 0.8986 3
#> MAD:pam 129 8.83e-04 0.5377 3
#> ATC:pam 138 6.46e-02 0.8986 3
#> SD:hclust 137 1.35e-01 0.8292 3
#> CV:hclust 137 1.35e-01 0.8292 3
#> MAD:hclust 137 1.27e-01 0.7921 3
#> ATC:hclust 139 1.21e-01 0.8885 3
test_to_known_factors(res_list, k = 4)
#> n disease.state(p) gender(p) k
#> SD:NMF 96 4.74e-01 0.752 4
#> CV:NMF 112 3.10e-02 0.784 4
#> MAD:NMF 123 2.44e-01 1.000 4
#> ATC:NMF 137 7.43e-02 0.908 4
#> SD:skmeans 135 3.08e-06 0.450 4
#> CV:skmeans 138 1.63e-06 0.409 4
#> MAD:skmeans 138 1.23e-06 0.482 4
#> ATC:skmeans 139 8.43e-02 0.949 4
#> SD:mclust 84 2.13e-04 0.175 4
#> CV:mclust 114 1.24e-04 0.367 4
#> MAD:mclust 101 6.79e-06 0.123 4
#> ATC:mclust 65 2.05e-01 0.477 4
#> SD:kmeans 137 1.49e-06 0.613 4
#> CV:kmeans 136 2.82e-06 0.597 4
#> MAD:kmeans 137 1.90e-06 0.419 4
#> ATC:kmeans 90 2.65e-01 0.547 4
#> SD:pam 136 3.74e-04 0.649 4
#> CV:pam 135 2.50e-04 0.610 4
#> MAD:pam 137 7.05e-03 0.650 4
#> ATC:pam 138 1.72e-01 0.793 4
#> SD:hclust 134 1.45e-01 0.769 4
#> CV:hclust 134 1.45e-01 0.769 4
#> MAD:hclust 122 2.10e-05 0.441 4
#> ATC:hclust 136 1.82e-01 0.793 4
test_to_known_factors(res_list, k = 5)
#> n disease.state(p) gender(p) k
#> SD:NMF 117 3.48e-07 0.0899 5
#> CV:NMF 111 5.13e-08 0.1484 5
#> MAD:NMF 116 4.88e-05 0.0337 5
#> ATC:NMF 137 7.43e-02 0.9077 5
#> SD:skmeans 134 9.58e-07 0.5560 5
#> CV:skmeans 133 3.42e-06 0.5431 5
#> MAD:skmeans 125 4.48e-11 0.2003 5
#> ATC:skmeans 88 2.20e-01 0.8380 5
#> SD:mclust 107 3.22e-04 0.3107 5
#> CV:mclust 93 2.72e-04 0.1649 5
#> MAD:mclust 84 1.90e-07 0.1267 5
#> ATC:mclust 53 5.58e-01 0.5230 5
#> SD:kmeans 114 5.22e-04 0.8065 5
#> CV:kmeans 134 1.16e-06 0.5644 5
#> MAD:kmeans 135 5.20e-07 0.4207 5
#> ATC:kmeans 92 2.47e-04 0.2219 5
#> SD:pam 126 1.43e-03 0.6853 5
#> CV:pam 126 8.94e-04 0.6587 5
#> MAD:pam 137 1.41e-02 0.7749 5
#> ATC:pam 137 1.86e-01 0.7766 5
#> SD:hclust 126 1.37e-01 0.8168 5
#> CV:hclust 131 2.32e-01 0.7344 5
#> MAD:hclust 103 1.57e-05 0.2272 5
#> ATC:hclust 137 1.37e-01 0.7766 5
test_to_known_factors(res_list, k = 6)
#> n disease.state(p) gender(p) k
#> SD:NMF 109 7.31e-07 0.121 6
#> CV:NMF 101 1.54e-06 0.274 6
#> MAD:NMF 80 7.16e-05 0.164 6
#> ATC:NMF 137 7.43e-02 0.908 6
#> SD:skmeans 128 3.76e-09 0.804 6
#> CV:skmeans 131 2.63e-09 0.589 6
#> MAD:skmeans 107 5.23e-08 0.561 6
#> ATC:skmeans 89 5.86e-01 0.594 6
#> SD:mclust 118 4.82e-05 0.423 6
#> CV:mclust 110 8.31e-05 0.308 6
#> MAD:mclust 125 7.87e-08 0.261 6
#> ATC:mclust 79 4.36e-02 0.610 6
#> SD:kmeans 107 6.46e-06 0.775 6
#> CV:kmeans 122 4.08e-09 0.768 6
#> MAD:kmeans 117 3.51e-11 0.315 6
#> ATC:kmeans 93 6.97e-11 0.133 6
#> SD:pam 127 6.29e-04 0.607 6
#> CV:pam 124 8.70e-04 0.523 6
#> MAD:pam 108 1.55e-01 0.968 6
#> ATC:pam 104 9.67e-02 0.818 6
#> SD:hclust 127 1.71e-01 0.873 6
#> CV:hclust 118 4.81e-02 0.840 6
#> MAD:hclust 127 1.73e-05 0.544 6
#> ATC:hclust 134 2.03e-01 0.826 6
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 46361 rows and 139 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 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.975 0.990 0.1477 0.931 0.867
#> 4 4 0.958 0.917 0.929 0.0409 0.972 0.939
#> 5 5 0.796 0.796 0.876 0.0804 0.984 0.962
#> 6 6 0.733 0.766 0.869 0.0895 0.927 0.825
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.6295 0.158 0.528 0 0.472
#> GSM1182187 3 0.0592 0.991 0.012 0 0.988
#> GSM1182188 3 0.0000 0.994 0.000 0 1.000
#> GSM1182189 1 0.0000 0.961 1.000 0 0.000
#> GSM1182190 1 0.0000 0.961 1.000 0 0.000
#> GSM1182191 1 0.6295 0.158 0.528 0 0.472
#> GSM1182192 1 0.0000 0.961 1.000 0 0.000
#> GSM1182193 1 0.0000 0.961 1.000 0 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000
#> GSM1182202 3 0.0592 0.991 0.012 0 0.988
#> GSM1182203 3 0.0592 0.991 0.012 0 0.988
#> GSM1182204 3 0.0592 0.991 0.012 0 0.988
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000
#> GSM1182207 1 0.0000 0.961 1.000 0 0.000
#> GSM1182208 1 0.0000 0.961 1.000 0 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000
#> GSM1182217 3 0.0892 0.984 0.020 0 0.980
#> GSM1182218 1 0.0000 0.961 1.000 0 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000
#> GSM1182227 1 0.0000 0.961 1.000 0 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000
#> GSM1182232 1 0.0000 0.961 1.000 0 0.000
#> GSM1182233 1 0.0000 0.961 1.000 0 0.000
#> GSM1182234 1 0.0000 0.961 1.000 0 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000
#> GSM1182236 1 0.0000 0.961 1.000 0 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000
#> GSM1182245 1 0.0000 0.961 1.000 0 0.000
#> GSM1182246 3 0.0000 0.994 0.000 0 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000
#> GSM1182251 1 0.0592 0.954 0.988 0 0.012
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000
#> GSM1182255 3 0.0000 0.994 0.000 0 1.000
#> GSM1182256 3 0.0000 0.994 0.000 0 1.000
#> GSM1182257 3 0.0237 0.994 0.004 0 0.996
#> GSM1182258 3 0.0000 0.994 0.000 0 1.000
#> GSM1182259 3 0.0000 0.994 0.000 0 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000
#> GSM1182263 1 0.0424 0.957 0.992 0 0.008
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000
#> GSM1182267 1 0.0000 0.961 1.000 0 0.000
#> GSM1182268 1 0.0000 0.961 1.000 0 0.000
#> GSM1182269 1 0.0000 0.961 1.000 0 0.000
#> GSM1182270 1 0.0000 0.961 1.000 0 0.000
#> GSM1182271 3 0.0000 0.994 0.000 0 1.000
#> GSM1182272 3 0.0000 0.994 0.000 0 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000
#> GSM1182277 1 0.0000 0.961 1.000 0 0.000
#> GSM1182278 1 0.0000 0.961 1.000 0 0.000
#> GSM1182279 1 0.0747 0.952 0.984 0 0.016
#> GSM1182280 1 0.0747 0.952 0.984 0 0.016
#> GSM1182281 1 0.3116 0.863 0.892 0 0.108
#> GSM1182282 1 0.0000 0.961 1.000 0 0.000
#> GSM1182283 1 0.0000 0.961 1.000 0 0.000
#> GSM1182284 1 0.0000 0.961 1.000 0 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000
#> GSM1182289 1 0.0592 0.954 0.988 0 0.012
#> GSM1182290 1 0.0000 0.961 1.000 0 0.000
#> GSM1182291 3 0.0000 0.994 0.000 0 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000
#> GSM1182304 1 0.0747 0.952 0.984 0 0.016
#> GSM1182305 1 0.4235 0.783 0.824 0 0.176
#> GSM1182306 3 0.0592 0.991 0.012 0 0.988
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000
#> GSM1182314 3 0.0000 0.994 0.000 0 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000
#> GSM1182302 3 0.0592 0.991 0.012 0 0.988
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000
#> GSM1182311 1 0.0000 0.961 1.000 0 0.000
#> GSM1182313 3 0.0000 0.994 0.000 0 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000
#> GSM1182323 1 0.0000 0.961 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.4713 0.236 0.640 0 0.000 0.360
#> GSM1182187 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182188 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182189 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182190 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182191 1 0.4713 0.236 0.640 0 0.000 0.360
#> GSM1182192 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182193 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182202 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182203 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182204 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182207 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182208 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182217 4 0.2814 0.926 0.132 0 0.000 0.868
#> GSM1182218 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182227 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182232 1 0.4830 0.708 0.608 0 0.392 0.000
#> GSM1182233 1 0.4830 0.708 0.608 0 0.392 0.000
#> GSM1182234 3 0.4477 0.316 0.312 0 0.688 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182236 1 0.4624 0.764 0.660 0 0.340 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182245 3 0.0336 0.779 0.008 0 0.992 0.000
#> GSM1182246 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182251 1 0.2714 0.668 0.884 0 0.112 0.004
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182255 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182256 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182257 4 0.2216 0.939 0.092 0 0.000 0.908
#> GSM1182258 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182259 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182263 1 0.2944 0.675 0.868 0 0.128 0.004
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182267 1 0.4898 0.667 0.584 0 0.416 0.000
#> GSM1182268 1 0.4830 0.708 0.608 0 0.392 0.000
#> GSM1182269 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182270 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182271 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182272 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182277 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182278 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182279 1 0.2345 0.662 0.900 0 0.100 0.000
#> GSM1182280 1 0.2345 0.662 0.900 0 0.100 0.000
#> GSM1182281 3 0.5998 0.469 0.212 0 0.680 0.108
#> GSM1182282 3 0.0336 0.779 0.008 0 0.992 0.000
#> GSM1182283 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182284 3 0.2408 0.856 0.104 0 0.896 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182289 1 0.2714 0.668 0.884 0 0.112 0.004
#> GSM1182290 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182291 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182304 1 0.2345 0.662 0.900 0 0.100 0.000
#> GSM1182305 1 0.4050 0.466 0.808 0 0.024 0.168
#> GSM1182306 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182314 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182302 4 0.2704 0.931 0.124 0 0.000 0.876
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182311 1 0.4605 0.767 0.664 0 0.336 0.000
#> GSM1182313 4 0.0000 0.953 0.000 0 0.000 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182323 1 0.4605 0.767 0.664 0 0.336 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 5 0.4774 -0.0247 0.444 0.000 0.012 0.004 0.540
#> GSM1182187 4 0.4307 -0.3609 0.000 0.000 0.000 0.504 0.496
#> GSM1182188 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 5 0.4774 -0.0247 0.444 0.000 0.012 0.004 0.540
#> GSM1182192 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182193 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182194 2 0.5639 0.5492 0.000 0.568 0.092 0.000 0.340
#> GSM1182195 2 0.5639 0.5492 0.000 0.568 0.092 0.000 0.340
#> GSM1182196 2 0.0290 0.9348 0.000 0.992 0.000 0.000 0.008
#> GSM1182197 2 0.0963 0.9284 0.000 0.964 0.000 0.000 0.036
#> GSM1182198 2 0.5639 0.5492 0.000 0.568 0.092 0.000 0.340
#> GSM1182199 2 0.5639 0.5492 0.000 0.568 0.092 0.000 0.340
#> GSM1182200 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182201 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182202 5 0.4227 0.4794 0.000 0.000 0.000 0.420 0.580
#> GSM1182203 5 0.4249 0.4634 0.000 0.000 0.000 0.432 0.568
#> GSM1182204 5 0.4249 0.4634 0.000 0.000 0.000 0.432 0.568
#> GSM1182205 2 0.2983 0.8861 0.000 0.864 0.040 0.000 0.096
#> GSM1182206 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182207 1 0.1638 0.7712 0.932 0.000 0.004 0.000 0.064
#> GSM1182208 1 0.1638 0.7712 0.932 0.000 0.004 0.000 0.064
#> GSM1182209 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182210 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182211 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182212 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182215 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182216 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182217 5 0.4359 0.4793 0.004 0.000 0.000 0.412 0.584
#> GSM1182218 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182220 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182221 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182222 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182223 2 0.1965 0.9070 0.000 0.904 0.000 0.000 0.096
#> GSM1182224 2 0.5309 0.6598 0.000 0.644 0.092 0.000 0.264
#> GSM1182225 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182226 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182227 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182228 2 0.2740 0.8939 0.000 0.876 0.028 0.000 0.096
#> GSM1182229 2 0.2653 0.8963 0.000 0.880 0.024 0.000 0.096
#> GSM1182230 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182231 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182232 1 0.1341 0.7295 0.944 0.000 0.056 0.000 0.000
#> GSM1182233 1 0.1341 0.7295 0.944 0.000 0.056 0.000 0.000
#> GSM1182234 1 0.4074 -0.3333 0.636 0.000 0.364 0.000 0.000
#> GSM1182235 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182236 1 0.0162 0.7763 0.996 0.000 0.004 0.000 0.000
#> GSM1182237 2 0.2464 0.8997 0.000 0.888 0.016 0.000 0.096
#> GSM1182238 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182239 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182240 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182241 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182242 2 0.2740 0.8939 0.000 0.876 0.028 0.000 0.096
#> GSM1182243 2 0.1774 0.9191 0.000 0.932 0.016 0.000 0.052
#> GSM1182244 2 0.5309 0.6598 0.000 0.644 0.092 0.000 0.264
#> GSM1182245 3 0.3857 0.8188 0.312 0.000 0.688 0.000 0.000
#> GSM1182246 4 0.0162 0.8405 0.000 0.000 0.000 0.996 0.004
#> GSM1182247 2 0.2824 0.8911 0.000 0.872 0.032 0.000 0.096
#> GSM1182248 2 0.2824 0.8911 0.000 0.872 0.032 0.000 0.096
#> GSM1182249 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182250 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182251 1 0.4964 0.6620 0.700 0.000 0.204 0.000 0.096
#> GSM1182252 2 0.2740 0.8939 0.000 0.876 0.028 0.000 0.096
#> GSM1182253 2 0.2769 0.8940 0.000 0.876 0.032 0.000 0.092
#> GSM1182254 2 0.1914 0.9161 0.000 0.924 0.016 0.000 0.060
#> GSM1182255 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.4161 0.0271 0.000 0.000 0.000 0.608 0.392
#> GSM1182258 4 0.0609 0.8292 0.000 0.000 0.000 0.980 0.020
#> GSM1182259 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182261 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182262 2 0.2561 0.8979 0.000 0.884 0.020 0.000 0.096
#> GSM1182263 1 0.4701 0.6714 0.720 0.000 0.204 0.000 0.076
#> GSM1182264 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182265 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182266 2 0.1364 0.9257 0.000 0.952 0.012 0.000 0.036
#> GSM1182267 1 0.1732 0.6936 0.920 0.000 0.080 0.000 0.000
#> GSM1182268 1 0.1341 0.7295 0.944 0.000 0.056 0.000 0.000
#> GSM1182269 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0162 0.8409 0.000 0.000 0.000 0.996 0.004
#> GSM1182272 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 2 0.1469 0.9245 0.000 0.948 0.016 0.000 0.036
#> GSM1182275 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182276 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182277 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182278 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182279 1 0.5004 0.6562 0.692 0.000 0.216 0.000 0.092
#> GSM1182280 1 0.5004 0.6562 0.692 0.000 0.216 0.000 0.092
#> GSM1182281 3 0.2127 0.4367 0.000 0.000 0.892 0.108 0.000
#> GSM1182282 3 0.3857 0.8188 0.312 0.000 0.688 0.000 0.000
#> GSM1182283 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182284 3 0.4235 0.8887 0.424 0.000 0.576 0.000 0.000
#> GSM1182285 2 0.5309 0.6598 0.000 0.644 0.092 0.000 0.264
#> GSM1182286 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182287 2 0.1965 0.9070 0.000 0.904 0.000 0.000 0.096
#> GSM1182288 2 0.2905 0.8887 0.000 0.868 0.036 0.000 0.096
#> GSM1182289 1 0.4964 0.6620 0.700 0.000 0.204 0.000 0.096
#> GSM1182290 1 0.1638 0.7712 0.932 0.000 0.004 0.000 0.064
#> GSM1182291 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.1469 0.9245 0.000 0.948 0.016 0.000 0.036
#> GSM1182292 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182293 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182294 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182295 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182296 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182298 2 0.5639 0.5492 0.000 0.568 0.092 0.000 0.340
#> GSM1182299 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182300 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182301 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182303 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182304 1 0.5004 0.6562 0.692 0.000 0.216 0.000 0.092
#> GSM1182305 1 0.7517 0.4255 0.508 0.000 0.228 0.104 0.160
#> GSM1182306 4 0.4297 -0.2799 0.000 0.000 0.000 0.528 0.472
#> GSM1182307 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182309 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182312 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182314 4 0.0290 0.8392 0.000 0.000 0.000 0.992 0.008
#> GSM1182316 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182318 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182319 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182320 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182321 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182322 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182324 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182297 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182302 5 0.4227 0.4794 0.000 0.000 0.000 0.420 0.580
#> GSM1182308 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182310 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182311 1 0.0000 0.7789 1.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.8431 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182317 2 0.0000 0.9364 0.000 1.000 0.000 0.000 0.000
#> GSM1182323 1 0.0000 0.7789 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
#> GSM1182186 6 0.5423 -0.0961 0.012 0.000 0.080 0.000 0.440 0.468
#> GSM1182187 6 0.1663 0.7661 0.000 0.000 0.000 0.088 0.000 0.912
#> GSM1182188 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 5 0.0865 0.7854 0.036 0.000 0.000 0.000 0.964 0.000
#> GSM1182190 5 0.0458 0.7901 0.016 0.000 0.000 0.000 0.984 0.000
#> GSM1182191 6 0.5423 -0.0961 0.012 0.000 0.080 0.000 0.440 0.468
#> GSM1182192 1 0.2996 0.8861 0.772 0.000 0.000 0.000 0.228 0.000
#> GSM1182193 1 0.2996 0.8861 0.772 0.000 0.000 0.000 0.228 0.000
#> GSM1182194 3 0.2793 0.9018 0.000 0.200 0.800 0.000 0.000 0.000
#> GSM1182195 3 0.2793 0.9018 0.000 0.200 0.800 0.000 0.000 0.000
#> GSM1182196 2 0.0363 0.8511 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182197 2 0.1444 0.8196 0.000 0.928 0.072 0.000 0.000 0.000
#> GSM1182198 3 0.2793 0.9018 0.000 0.200 0.800 0.000 0.000 0.000
#> GSM1182199 3 0.2793 0.9018 0.000 0.200 0.800 0.000 0.000 0.000
#> GSM1182200 2 0.0146 0.8518 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182201 2 0.0790 0.8445 0.000 0.968 0.032 0.000 0.000 0.000
#> GSM1182202 6 0.0146 0.8002 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM1182203 6 0.0458 0.8019 0.000 0.000 0.000 0.016 0.000 0.984
#> GSM1182204 6 0.0458 0.8019 0.000 0.000 0.000 0.016 0.000 0.984
#> GSM1182205 2 0.3634 0.4167 0.000 0.644 0.356 0.000 0.000 0.000
#> GSM1182206 2 0.3446 0.5313 0.000 0.692 0.308 0.000 0.000 0.000
#> GSM1182207 5 0.2852 0.7804 0.064 0.000 0.080 0.000 0.856 0.000
#> GSM1182208 5 0.2852 0.7804 0.064 0.000 0.080 0.000 0.856 0.000
#> GSM1182209 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182210 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.0260 0.8520 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182212 2 0.0260 0.8520 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182215 2 0.3428 0.5462 0.000 0.696 0.304 0.000 0.000 0.000
#> GSM1182216 2 0.0458 0.8508 0.000 0.984 0.016 0.000 0.000 0.000
#> GSM1182217 6 0.0291 0.7983 0.000 0.000 0.004 0.000 0.004 0.992
#> GSM1182218 5 0.0458 0.7901 0.016 0.000 0.000 0.000 0.984 0.000
#> GSM1182219 2 0.0146 0.8518 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182220 2 0.0146 0.8518 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182221 2 0.0260 0.8517 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182222 2 0.0547 0.8498 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1182223 2 0.3309 0.5915 0.000 0.720 0.280 0.000 0.000 0.000
#> GSM1182224 3 0.3446 0.8319 0.000 0.308 0.692 0.000 0.000 0.000
#> GSM1182225 2 0.0547 0.8498 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1182226 2 0.0547 0.8498 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1182227 1 0.2996 0.8861 0.772 0.000 0.000 0.000 0.228 0.000
#> GSM1182228 2 0.3244 0.6015 0.000 0.732 0.268 0.000 0.000 0.000
#> GSM1182229 2 0.3620 0.4370 0.000 0.648 0.352 0.000 0.000 0.000
#> GSM1182230 2 0.3409 0.5515 0.000 0.700 0.300 0.000 0.000 0.000
#> GSM1182231 2 0.3330 0.5783 0.000 0.716 0.284 0.000 0.000 0.000
#> GSM1182232 5 0.2491 0.6618 0.164 0.000 0.000 0.000 0.836 0.000
#> GSM1182233 5 0.2491 0.6618 0.164 0.000 0.000 0.000 0.836 0.000
#> GSM1182234 1 0.3828 0.4797 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182235 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182236 5 0.1075 0.7799 0.048 0.000 0.000 0.000 0.952 0.000
#> GSM1182237 2 0.3076 0.6389 0.000 0.760 0.240 0.000 0.000 0.000
#> GSM1182238 2 0.0260 0.8517 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182239 2 0.0146 0.8510 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182240 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182241 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182242 2 0.3659 0.4024 0.000 0.636 0.364 0.000 0.000 0.000
#> GSM1182243 2 0.3050 0.6676 0.000 0.764 0.236 0.000 0.000 0.000
#> GSM1182244 3 0.3647 0.7582 0.000 0.360 0.640 0.000 0.000 0.000
#> GSM1182245 1 0.2048 0.8231 0.880 0.000 0.000 0.000 0.120 0.000
#> GSM1182246 4 0.0146 0.9940 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182247 2 0.3684 0.3786 0.000 0.628 0.372 0.000 0.000 0.000
#> GSM1182248 2 0.3684 0.3786 0.000 0.628 0.372 0.000 0.000 0.000
#> GSM1182249 2 0.2527 0.7471 0.000 0.832 0.168 0.000 0.000 0.000
#> GSM1182250 2 0.2562 0.7443 0.000 0.828 0.172 0.000 0.000 0.000
#> GSM1182251 5 0.4954 0.7033 0.100 0.000 0.196 0.000 0.684 0.020
#> GSM1182252 2 0.3634 0.4259 0.000 0.644 0.356 0.000 0.000 0.000
#> GSM1182253 2 0.3634 0.4192 0.000 0.644 0.356 0.000 0.000 0.000
#> GSM1182254 2 0.3101 0.6558 0.000 0.756 0.244 0.000 0.000 0.000
#> GSM1182255 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 6 0.2854 0.6412 0.000 0.000 0.000 0.208 0.000 0.792
#> GSM1182258 4 0.0547 0.9815 0.000 0.000 0.000 0.980 0.000 0.020
#> GSM1182259 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 2 0.2260 0.7704 0.000 0.860 0.140 0.000 0.000 0.000
#> GSM1182261 2 0.3371 0.5651 0.000 0.708 0.292 0.000 0.000 0.000
#> GSM1182262 2 0.3371 0.5651 0.000 0.708 0.292 0.000 0.000 0.000
#> GSM1182263 5 0.4650 0.7182 0.104 0.000 0.172 0.000 0.712 0.012
#> GSM1182264 2 0.2378 0.7615 0.000 0.848 0.152 0.000 0.000 0.000
#> GSM1182265 2 0.2378 0.7609 0.000 0.848 0.152 0.000 0.000 0.000
#> GSM1182266 2 0.2416 0.7582 0.000 0.844 0.156 0.000 0.000 0.000
#> GSM1182267 5 0.3175 0.5378 0.256 0.000 0.000 0.000 0.744 0.000
#> GSM1182268 5 0.2697 0.6377 0.188 0.000 0.000 0.000 0.812 0.000
#> GSM1182269 5 0.0458 0.7901 0.016 0.000 0.000 0.000 0.984 0.000
#> GSM1182270 5 0.0458 0.7901 0.016 0.000 0.000 0.000 0.984 0.000
#> GSM1182271 4 0.0146 0.9939 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182272 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 2 0.2823 0.7108 0.000 0.796 0.204 0.000 0.000 0.000
#> GSM1182275 2 0.0713 0.8467 0.000 0.972 0.028 0.000 0.000 0.000
#> GSM1182276 2 0.0547 0.8499 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1182277 1 0.3076 0.8819 0.760 0.000 0.000 0.000 0.240 0.000
#> GSM1182278 1 0.3076 0.8819 0.760 0.000 0.000 0.000 0.240 0.000
#> GSM1182279 5 0.4938 0.6948 0.112 0.000 0.200 0.000 0.676 0.012
#> GSM1182280 5 0.4938 0.6948 0.112 0.000 0.200 0.000 0.676 0.012
#> GSM1182281 1 0.3657 0.4900 0.792 0.000 0.100 0.108 0.000 0.000
#> GSM1182282 1 0.2416 0.8161 0.844 0.000 0.000 0.000 0.156 0.000
#> GSM1182283 1 0.3076 0.8822 0.760 0.000 0.000 0.000 0.240 0.000
#> GSM1182284 1 0.2996 0.8861 0.772 0.000 0.000 0.000 0.228 0.000
#> GSM1182285 3 0.3464 0.8258 0.000 0.312 0.688 0.000 0.000 0.000
#> GSM1182286 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182287 2 0.3309 0.5915 0.000 0.720 0.280 0.000 0.000 0.000
#> GSM1182288 2 0.3684 0.3775 0.000 0.628 0.372 0.000 0.000 0.000
#> GSM1182289 5 0.4954 0.7033 0.100 0.000 0.196 0.000 0.684 0.020
#> GSM1182290 5 0.2794 0.7811 0.060 0.000 0.080 0.000 0.860 0.000
#> GSM1182291 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 2 0.2823 0.7108 0.000 0.796 0.204 0.000 0.000 0.000
#> GSM1182292 2 0.0146 0.8510 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182293 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182294 2 0.0146 0.8516 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182295 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182296 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182298 3 0.2793 0.9018 0.000 0.200 0.800 0.000 0.000 0.000
#> GSM1182299 2 0.0260 0.8520 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182300 2 0.0146 0.8510 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182301 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182303 2 0.0146 0.8518 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182304 5 0.4938 0.6948 0.112 0.000 0.200 0.000 0.676 0.012
#> GSM1182305 5 0.7640 0.5182 0.128 0.000 0.196 0.104 0.492 0.080
#> GSM1182306 6 0.1957 0.7484 0.000 0.000 0.000 0.112 0.000 0.888
#> GSM1182307 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182309 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182312 2 0.0260 0.8517 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182314 4 0.0260 0.9924 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM1182316 2 0.0363 0.8516 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182318 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182319 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182320 2 0.0260 0.8517 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182321 2 0.0713 0.8441 0.000 0.972 0.028 0.000 0.000 0.000
#> GSM1182322 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182324 2 0.0713 0.8470 0.000 0.972 0.028 0.000 0.000 0.000
#> GSM1182297 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182302 6 0.0146 0.8002 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM1182308 2 0.0363 0.8517 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182310 2 0.0260 0.8517 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1182311 5 0.0458 0.7901 0.016 0.000 0.000 0.000 0.984 0.000
#> GSM1182313 4 0.0000 0.9964 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.0000 0.8511 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182317 2 0.0146 0.8518 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182323 5 0.0363 0.7900 0.012 0.000 0.000 0.000 0.988 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:hclust 139 0.0773 1.000 2
#> SD:hclust 137 0.1355 0.829 3
#> SD:hclust 134 0.1447 0.769 4
#> SD:hclust 126 0.1371 0.817 5
#> SD:hclust 127 0.1711 0.873 6
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 46361 rows and 139 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 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.746 0.863 0.812 0.2844 0.821 0.657
#> 4 4 0.620 0.871 0.808 0.1412 0.892 0.697
#> 5 5 0.659 0.612 0.766 0.0726 0.995 0.981
#> 6 6 0.656 0.622 0.701 0.0532 0.905 0.644
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182187 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182188 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182189 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182190 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182191 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182192 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182193 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182194 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182195 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182196 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182197 2 0.0424 0.9237 0.000 0.992 0.008
#> GSM1182198 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182199 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182200 2 0.0592 0.9192 0.000 0.988 0.012
#> GSM1182201 2 0.5397 0.0923 0.000 0.720 0.280
#> GSM1182202 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182203 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182204 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182205 3 0.6235 0.9902 0.000 0.436 0.564
#> GSM1182206 3 0.6260 0.9702 0.000 0.448 0.552
#> GSM1182207 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182208 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182209 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182210 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182211 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182212 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182213 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182214 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182215 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182216 2 0.0592 0.9218 0.000 0.988 0.012
#> GSM1182217 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182218 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182219 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182220 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182221 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182222 2 0.1411 0.8885 0.000 0.964 0.036
#> GSM1182223 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182224 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182225 2 0.0592 0.9222 0.000 0.988 0.012
#> GSM1182226 2 0.0592 0.9218 0.000 0.988 0.012
#> GSM1182227 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182228 3 0.6244 0.9886 0.000 0.440 0.560
#> GSM1182229 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182230 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182231 2 0.2537 0.8110 0.000 0.920 0.080
#> GSM1182232 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182235 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182236 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182237 2 0.6299 -0.8094 0.000 0.524 0.476
#> GSM1182238 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182239 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182240 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182241 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182242 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182243 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182244 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182245 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182246 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182247 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182248 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182249 2 0.6111 -0.5270 0.000 0.604 0.396
#> GSM1182250 3 0.6235 0.9902 0.000 0.436 0.564
#> GSM1182251 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182252 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182253 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182254 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182255 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182256 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182257 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182258 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182259 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182260 3 0.6252 0.9826 0.000 0.444 0.556
#> GSM1182261 3 0.6235 0.9902 0.000 0.436 0.564
#> GSM1182262 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182263 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182264 3 0.6252 0.9826 0.000 0.444 0.556
#> GSM1182265 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182266 3 0.6244 0.9886 0.000 0.440 0.560
#> GSM1182267 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182270 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182271 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182272 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182273 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182275 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182276 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182277 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182279 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182280 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182281 1 0.5810 0.8026 0.664 0.000 0.336
#> GSM1182282 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182284 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182285 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182286 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182287 2 0.5327 0.1644 0.000 0.728 0.272
#> GSM1182288 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182289 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182290 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182291 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182274 3 0.6225 0.9938 0.000 0.432 0.568
#> GSM1182292 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182293 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182294 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182295 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182296 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182298 3 0.6235 0.9929 0.000 0.436 0.564
#> GSM1182299 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182300 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182301 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182303 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182304 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182305 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182306 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182307 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182309 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182312 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182314 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182316 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182318 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182319 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182320 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182321 2 0.4062 0.6016 0.000 0.836 0.164
#> GSM1182322 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182324 2 0.4178 0.5898 0.000 0.828 0.172
#> GSM1182297 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182302 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182308 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182310 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182311 1 0.0000 0.8515 1.000 0.000 0.000
#> GSM1182313 1 0.6225 0.7890 0.568 0.000 0.432
#> GSM1182315 2 0.0237 0.9295 0.000 0.996 0.004
#> GSM1182317 2 0.0000 0.9313 0.000 1.000 0.000
#> GSM1182323 1 0.0000 0.8515 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.2813 0.8875 0.024 0.080 0.000 0.896
#> GSM1182187 4 0.1389 0.9346 0.000 0.048 0.000 0.952
#> GSM1182188 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182190 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182191 4 0.3205 0.8644 0.024 0.104 0.000 0.872
#> GSM1182192 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182193 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182194 3 0.3266 0.8327 0.168 0.000 0.832 0.000
#> GSM1182195 3 0.3311 0.8330 0.172 0.000 0.828 0.000
#> GSM1182196 2 0.5657 0.8809 0.120 0.720 0.160 0.000
#> GSM1182197 2 0.5990 0.6843 0.056 0.608 0.336 0.000
#> GSM1182198 3 0.3448 0.8316 0.168 0.004 0.828 0.000
#> GSM1182199 3 0.3448 0.8316 0.168 0.004 0.828 0.000
#> GSM1182200 2 0.4638 0.8895 0.044 0.776 0.180 0.000
#> GSM1182201 3 0.5997 0.0918 0.048 0.376 0.576 0.000
#> GSM1182202 4 0.1389 0.9346 0.000 0.048 0.000 0.952
#> GSM1182203 4 0.1389 0.9346 0.000 0.048 0.000 0.952
#> GSM1182204 4 0.1389 0.9346 0.000 0.048 0.000 0.952
#> GSM1182205 3 0.1807 0.8862 0.052 0.008 0.940 0.000
#> GSM1182206 3 0.3286 0.8392 0.080 0.044 0.876 0.000
#> GSM1182207 1 0.5746 0.9298 0.572 0.032 0.000 0.396
#> GSM1182208 1 0.5827 0.9294 0.568 0.036 0.000 0.396
#> GSM1182209 2 0.4405 0.8967 0.048 0.800 0.152 0.000
#> GSM1182210 2 0.4285 0.8982 0.040 0.804 0.156 0.000
#> GSM1182211 2 0.4197 0.8977 0.036 0.808 0.156 0.000
#> GSM1182212 2 0.4285 0.8969 0.040 0.804 0.156 0.000
#> GSM1182213 2 0.4285 0.8970 0.040 0.804 0.156 0.000
#> GSM1182214 2 0.4105 0.9010 0.032 0.812 0.156 0.000
#> GSM1182215 3 0.1890 0.8766 0.056 0.008 0.936 0.000
#> GSM1182216 2 0.5376 0.8807 0.088 0.736 0.176 0.000
#> GSM1182217 4 0.2813 0.8875 0.024 0.080 0.000 0.896
#> GSM1182218 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182219 2 0.4452 0.8968 0.048 0.796 0.156 0.000
#> GSM1182220 2 0.4452 0.8968 0.048 0.796 0.156 0.000
#> GSM1182221 2 0.6243 0.8543 0.160 0.668 0.172 0.000
#> GSM1182222 2 0.5572 0.8679 0.088 0.716 0.196 0.000
#> GSM1182223 3 0.2578 0.8561 0.036 0.052 0.912 0.000
#> GSM1182224 3 0.3311 0.8330 0.172 0.000 0.828 0.000
#> GSM1182225 2 0.5417 0.8781 0.088 0.732 0.180 0.000
#> GSM1182226 2 0.5495 0.8795 0.096 0.728 0.176 0.000
#> GSM1182227 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182228 3 0.3323 0.8386 0.060 0.064 0.876 0.000
#> GSM1182229 3 0.0188 0.8891 0.004 0.000 0.996 0.000
#> GSM1182230 3 0.0188 0.8891 0.004 0.000 0.996 0.000
#> GSM1182231 2 0.6672 0.5023 0.088 0.504 0.408 0.000
#> GSM1182232 1 0.4843 0.9442 0.604 0.000 0.000 0.396
#> GSM1182233 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182234 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182235 2 0.4609 0.8998 0.056 0.788 0.156 0.000
#> GSM1182236 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182237 3 0.4944 0.7033 0.072 0.160 0.768 0.000
#> GSM1182238 2 0.5248 0.8890 0.088 0.748 0.164 0.000
#> GSM1182239 2 0.4405 0.9004 0.048 0.800 0.152 0.000
#> GSM1182240 2 0.5050 0.8966 0.084 0.764 0.152 0.000
#> GSM1182241 2 0.4711 0.8936 0.064 0.784 0.152 0.000
#> GSM1182242 3 0.0937 0.8880 0.012 0.012 0.976 0.000
#> GSM1182243 3 0.1042 0.8868 0.020 0.008 0.972 0.000
#> GSM1182244 3 0.3881 0.8258 0.172 0.016 0.812 0.000
#> GSM1182245 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182246 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0469 0.8883 0.012 0.000 0.988 0.000
#> GSM1182248 3 0.0592 0.8887 0.016 0.000 0.984 0.000
#> GSM1182249 3 0.6078 0.5529 0.152 0.164 0.684 0.000
#> GSM1182250 3 0.2021 0.8754 0.056 0.012 0.932 0.000
#> GSM1182251 1 0.6844 0.8620 0.500 0.104 0.000 0.396
#> GSM1182252 3 0.0469 0.8883 0.012 0.000 0.988 0.000
#> GSM1182253 3 0.0592 0.8887 0.016 0.000 0.984 0.000
#> GSM1182254 3 0.0469 0.8888 0.012 0.000 0.988 0.000
#> GSM1182255 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0188 0.9474 0.000 0.004 0.000 0.996
#> GSM1182258 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.1733 0.8825 0.028 0.024 0.948 0.000
#> GSM1182261 3 0.2984 0.8508 0.084 0.028 0.888 0.000
#> GSM1182262 3 0.1389 0.8822 0.048 0.000 0.952 0.000
#> GSM1182263 1 0.6491 0.8949 0.528 0.076 0.000 0.396
#> GSM1182264 3 0.1629 0.8811 0.024 0.024 0.952 0.000
#> GSM1182265 3 0.3392 0.8225 0.124 0.020 0.856 0.000
#> GSM1182266 3 0.1059 0.8867 0.016 0.012 0.972 0.000
#> GSM1182267 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182268 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182269 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182270 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182271 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0336 0.8891 0.008 0.000 0.992 0.000
#> GSM1182275 3 0.0804 0.8893 0.012 0.008 0.980 0.000
#> GSM1182276 2 0.4285 0.8969 0.040 0.804 0.156 0.000
#> GSM1182277 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182278 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182279 1 0.6798 0.8673 0.504 0.100 0.000 0.396
#> GSM1182280 1 0.6491 0.8949 0.528 0.076 0.000 0.396
#> GSM1182281 4 0.4318 0.6351 0.116 0.068 0.000 0.816
#> GSM1182282 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182283 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182284 1 0.5980 0.9352 0.560 0.044 0.000 0.396
#> GSM1182285 3 0.3266 0.8327 0.168 0.000 0.832 0.000
#> GSM1182286 2 0.4237 0.9013 0.040 0.808 0.152 0.000
#> GSM1182287 3 0.6302 0.0644 0.068 0.368 0.564 0.000
#> GSM1182288 3 0.0657 0.8880 0.012 0.004 0.984 0.000
#> GSM1182289 1 0.6798 0.8673 0.504 0.100 0.000 0.396
#> GSM1182290 1 0.5980 0.9215 0.560 0.044 0.000 0.396
#> GSM1182291 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0927 0.8873 0.016 0.008 0.976 0.000
#> GSM1182292 2 0.4562 0.8951 0.056 0.792 0.152 0.000
#> GSM1182293 2 0.5657 0.8734 0.120 0.720 0.160 0.000
#> GSM1182294 2 0.5742 0.8709 0.120 0.712 0.168 0.000
#> GSM1182295 2 0.4010 0.9024 0.028 0.816 0.156 0.000
#> GSM1182296 2 0.4562 0.8951 0.056 0.792 0.152 0.000
#> GSM1182298 3 0.3448 0.8316 0.168 0.004 0.828 0.000
#> GSM1182299 2 0.4010 0.9024 0.028 0.816 0.156 0.000
#> GSM1182300 2 0.4485 0.8999 0.052 0.796 0.152 0.000
#> GSM1182301 2 0.4405 0.8967 0.048 0.800 0.152 0.000
#> GSM1182303 2 0.4285 0.8969 0.040 0.804 0.156 0.000
#> GSM1182304 1 0.6844 0.8668 0.500 0.104 0.000 0.396
#> GSM1182305 4 0.3307 0.8597 0.028 0.104 0.000 0.868
#> GSM1182306 4 0.0336 0.9467 0.000 0.008 0.000 0.992
#> GSM1182307 2 0.4405 0.8978 0.048 0.800 0.152 0.000
#> GSM1182309 2 0.5763 0.8720 0.132 0.712 0.156 0.000
#> GSM1182312 2 0.6204 0.8576 0.164 0.672 0.164 0.000
#> GSM1182314 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.6162 0.8561 0.156 0.676 0.168 0.000
#> GSM1182318 2 0.4285 0.9014 0.040 0.804 0.156 0.000
#> GSM1182319 2 0.5902 0.8671 0.140 0.700 0.160 0.000
#> GSM1182320 2 0.6162 0.8561 0.156 0.676 0.168 0.000
#> GSM1182321 2 0.7179 0.5181 0.140 0.480 0.380 0.000
#> GSM1182322 2 0.5944 0.8658 0.140 0.696 0.164 0.000
#> GSM1182324 2 0.7338 0.5078 0.160 0.464 0.376 0.000
#> GSM1182297 2 0.4322 0.9010 0.044 0.804 0.152 0.000
#> GSM1182302 4 0.1389 0.9346 0.000 0.048 0.000 0.952
#> GSM1182308 2 0.5056 0.8897 0.076 0.760 0.164 0.000
#> GSM1182310 2 0.6323 0.8497 0.164 0.660 0.176 0.000
#> GSM1182311 1 0.5016 0.9446 0.600 0.004 0.000 0.396
#> GSM1182313 4 0.0000 0.9480 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.5560 0.8879 0.116 0.728 0.156 0.000
#> GSM1182317 2 0.5551 0.8752 0.112 0.728 0.160 0.000
#> GSM1182323 1 0.5016 0.9446 0.600 0.004 0.000 0.396
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 4 0.6854 0.7817 0.340 0.000 0.020 0.468 0.172
#> GSM1182187 4 0.6323 0.8769 0.292 0.000 0.032 0.576 0.100
#> GSM1182188 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182189 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 4 0.6949 0.7516 0.340 0.000 0.016 0.440 0.204
#> GSM1182192 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182193 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182194 3 0.7024 0.6097 0.000 0.076 0.568 0.192 0.164
#> GSM1182195 3 0.7216 0.6087 0.000 0.080 0.544 0.196 0.180
#> GSM1182196 2 0.5505 0.1147 0.000 0.636 0.020 0.056 0.288
#> GSM1182197 2 0.6107 -0.1369 0.000 0.568 0.332 0.036 0.064
#> GSM1182198 3 0.7077 0.6078 0.000 0.076 0.560 0.200 0.164
#> GSM1182199 3 0.7077 0.6078 0.000 0.076 0.560 0.200 0.164
#> GSM1182200 2 0.2390 0.5314 0.000 0.908 0.060 0.008 0.024
#> GSM1182201 3 0.5190 0.2800 0.000 0.404 0.560 0.016 0.020
#> GSM1182202 4 0.6366 0.8750 0.292 0.000 0.032 0.572 0.104
#> GSM1182203 4 0.6249 0.8780 0.292 0.000 0.028 0.580 0.100
#> GSM1182204 4 0.6292 0.8764 0.292 0.000 0.028 0.576 0.104
#> GSM1182205 3 0.4893 0.7382 0.000 0.080 0.740 0.016 0.164
#> GSM1182206 3 0.5937 0.6553 0.000 0.096 0.644 0.032 0.228
#> GSM1182207 1 0.1732 0.8593 0.920 0.000 0.000 0.000 0.080
#> GSM1182208 1 0.1732 0.8593 0.920 0.000 0.000 0.000 0.080
#> GSM1182209 2 0.1372 0.5985 0.000 0.956 0.004 0.024 0.016
#> GSM1182210 2 0.0798 0.6006 0.000 0.976 0.000 0.008 0.016
#> GSM1182211 2 0.0451 0.5983 0.000 0.988 0.000 0.004 0.008
#> GSM1182212 2 0.0740 0.5943 0.000 0.980 0.004 0.008 0.008
#> GSM1182213 2 0.0451 0.6008 0.000 0.988 0.000 0.008 0.004
#> GSM1182214 2 0.0693 0.6023 0.000 0.980 0.000 0.008 0.012
#> GSM1182215 3 0.5346 0.7061 0.000 0.084 0.696 0.020 0.200
#> GSM1182216 2 0.4452 0.2771 0.000 0.696 0.000 0.032 0.272
#> GSM1182217 4 0.6993 0.7878 0.340 0.000 0.032 0.468 0.160
#> GSM1182218 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.1251 0.5963 0.000 0.956 0.000 0.008 0.036
#> GSM1182220 2 0.1059 0.5959 0.000 0.968 0.004 0.008 0.020
#> GSM1182221 2 0.4637 -0.4016 0.000 0.536 0.000 0.012 0.452
#> GSM1182222 2 0.4605 0.2641 0.000 0.692 0.004 0.032 0.272
#> GSM1182223 3 0.4052 0.7237 0.000 0.176 0.784 0.024 0.016
#> GSM1182224 3 0.7217 0.6119 0.000 0.080 0.544 0.184 0.192
#> GSM1182225 2 0.4452 0.2771 0.000 0.696 0.000 0.032 0.272
#> GSM1182226 2 0.4498 0.2559 0.000 0.688 0.000 0.032 0.280
#> GSM1182227 1 0.2694 0.8686 0.884 0.000 0.040 0.000 0.076
#> GSM1182228 3 0.4985 0.7080 0.000 0.164 0.740 0.068 0.028
#> GSM1182229 3 0.2331 0.7832 0.000 0.080 0.900 0.020 0.000
#> GSM1182230 3 0.3566 0.7841 0.000 0.080 0.848 0.020 0.052
#> GSM1182231 2 0.7390 -0.3465 0.000 0.388 0.332 0.032 0.248
#> GSM1182232 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182234 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182235 2 0.3854 0.5528 0.000 0.816 0.004 0.080 0.100
#> GSM1182236 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.6751 0.5595 0.000 0.172 0.608 0.088 0.132
#> GSM1182238 2 0.4451 0.3209 0.000 0.712 0.000 0.040 0.248
#> GSM1182239 2 0.3142 0.5837 0.000 0.864 0.004 0.056 0.076
#> GSM1182240 2 0.2813 0.5501 0.000 0.868 0.000 0.024 0.108
#> GSM1182241 2 0.2967 0.5706 0.000 0.884 0.024 0.060 0.032
#> GSM1182242 3 0.2116 0.7828 0.000 0.076 0.912 0.008 0.004
#> GSM1182243 3 0.3782 0.7736 0.000 0.084 0.836 0.024 0.056
#> GSM1182244 3 0.7247 0.5993 0.000 0.092 0.548 0.184 0.176
#> GSM1182245 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182246 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182247 3 0.2172 0.7831 0.000 0.076 0.908 0.000 0.016
#> GSM1182248 3 0.3093 0.7832 0.000 0.080 0.872 0.016 0.032
#> GSM1182249 3 0.6543 0.3900 0.000 0.156 0.548 0.020 0.276
#> GSM1182250 3 0.5183 0.7071 0.000 0.084 0.716 0.020 0.180
#> GSM1182251 1 0.3274 0.7322 0.780 0.000 0.000 0.000 0.220
#> GSM1182252 3 0.2429 0.7832 0.000 0.076 0.900 0.004 0.020
#> GSM1182253 3 0.2733 0.7844 0.000 0.080 0.888 0.016 0.016
#> GSM1182254 3 0.3426 0.7805 0.000 0.084 0.856 0.028 0.032
#> GSM1182255 4 0.3906 0.9028 0.292 0.000 0.004 0.704 0.000
#> GSM1182256 4 0.3906 0.9028 0.292 0.000 0.004 0.704 0.000
#> GSM1182257 4 0.5196 0.8968 0.292 0.000 0.036 0.652 0.020
#> GSM1182258 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182259 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182260 3 0.4056 0.7704 0.000 0.080 0.824 0.044 0.052
#> GSM1182261 3 0.5937 0.6462 0.000 0.096 0.644 0.032 0.228
#> GSM1182262 3 0.5250 0.7158 0.000 0.084 0.708 0.020 0.188
#> GSM1182263 1 0.3132 0.7862 0.820 0.000 0.008 0.000 0.172
#> GSM1182264 3 0.3844 0.7634 0.000 0.104 0.828 0.044 0.024
#> GSM1182265 3 0.5375 0.6003 0.000 0.080 0.640 0.004 0.276
#> GSM1182266 3 0.2647 0.7824 0.000 0.076 0.892 0.024 0.008
#> GSM1182267 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182268 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.3906 0.9028 0.292 0.000 0.004 0.704 0.000
#> GSM1182272 4 0.3906 0.9028 0.292 0.000 0.004 0.704 0.000
#> GSM1182273 3 0.2990 0.7851 0.000 0.080 0.876 0.012 0.032
#> GSM1182275 3 0.2116 0.7822 0.000 0.076 0.912 0.004 0.008
#> GSM1182276 2 0.1087 0.5917 0.000 0.968 0.016 0.008 0.008
#> GSM1182277 1 0.2694 0.8686 0.884 0.000 0.040 0.000 0.076
#> GSM1182278 1 0.2694 0.8686 0.884 0.000 0.040 0.000 0.076
#> GSM1182279 1 0.3109 0.7563 0.800 0.000 0.000 0.000 0.200
#> GSM1182280 1 0.2852 0.7850 0.828 0.000 0.000 0.000 0.172
#> GSM1182281 4 0.6888 0.6475 0.364 0.000 0.044 0.476 0.116
#> GSM1182282 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182283 1 0.2676 0.8687 0.884 0.000 0.036 0.000 0.080
#> GSM1182284 1 0.2694 0.8686 0.884 0.000 0.040 0.000 0.076
#> GSM1182285 3 0.7059 0.6118 0.000 0.076 0.564 0.184 0.176
#> GSM1182286 2 0.3384 0.5769 0.000 0.848 0.004 0.060 0.088
#> GSM1182287 3 0.6008 0.2595 0.000 0.380 0.528 0.016 0.076
#> GSM1182288 3 0.2861 0.7835 0.000 0.076 0.884 0.016 0.024
#> GSM1182289 1 0.3143 0.7531 0.796 0.000 0.000 0.000 0.204
#> GSM1182290 1 0.2074 0.8426 0.896 0.000 0.000 0.000 0.104
#> GSM1182291 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182274 3 0.3730 0.7757 0.000 0.084 0.840 0.028 0.048
#> GSM1182292 2 0.1808 0.5938 0.000 0.936 0.004 0.040 0.020
#> GSM1182293 2 0.4084 0.0248 0.000 0.668 0.000 0.004 0.328
#> GSM1182294 2 0.4313 -0.0617 0.000 0.636 0.000 0.008 0.356
#> GSM1182295 2 0.2304 0.5777 0.000 0.892 0.000 0.008 0.100
#> GSM1182296 2 0.1808 0.5944 0.000 0.936 0.004 0.040 0.020
#> GSM1182298 3 0.7077 0.6078 0.000 0.076 0.560 0.200 0.164
#> GSM1182299 2 0.1757 0.6014 0.000 0.936 0.004 0.012 0.048
#> GSM1182300 2 0.3322 0.5618 0.000 0.848 0.004 0.044 0.104
#> GSM1182301 2 0.1728 0.5971 0.000 0.940 0.004 0.036 0.020
#> GSM1182303 2 0.0854 0.5937 0.000 0.976 0.004 0.008 0.012
#> GSM1182304 1 0.3039 0.7621 0.808 0.000 0.000 0.000 0.192
#> GSM1182305 4 0.6593 0.7431 0.340 0.000 0.000 0.440 0.220
#> GSM1182306 4 0.5363 0.8952 0.292 0.000 0.032 0.644 0.032
#> GSM1182307 2 0.1978 0.5941 0.000 0.928 0.004 0.044 0.024
#> GSM1182309 2 0.4709 0.0533 0.000 0.648 0.004 0.024 0.324
#> GSM1182312 2 0.4440 -0.4250 0.000 0.528 0.000 0.004 0.468
#> GSM1182314 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182316 2 0.4283 -0.4062 0.000 0.544 0.000 0.000 0.456
#> GSM1182318 2 0.2389 0.5501 0.000 0.880 0.000 0.004 0.116
#> GSM1182319 2 0.5278 -0.0269 0.000 0.600 0.004 0.052 0.344
#> GSM1182320 2 0.4278 -0.3909 0.000 0.548 0.000 0.000 0.452
#> GSM1182321 2 0.7323 -0.6195 0.000 0.440 0.164 0.052 0.344
#> GSM1182322 2 0.5278 -0.0269 0.000 0.600 0.004 0.052 0.344
#> GSM1182324 5 0.5995 0.0000 0.000 0.420 0.112 0.000 0.468
#> GSM1182297 2 0.3629 0.5665 0.000 0.832 0.004 0.072 0.092
#> GSM1182302 4 0.6366 0.8750 0.292 0.000 0.032 0.572 0.104
#> GSM1182308 2 0.2329 0.5071 0.000 0.876 0.000 0.000 0.124
#> GSM1182310 2 0.4430 -0.4147 0.000 0.540 0.000 0.004 0.456
#> GSM1182311 1 0.0000 0.8907 1.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.3752 0.9030 0.292 0.000 0.000 0.708 0.000
#> GSM1182315 2 0.4562 0.2607 0.000 0.676 0.000 0.032 0.292
#> GSM1182317 2 0.4029 0.0658 0.000 0.680 0.000 0.004 0.316
#> GSM1182323 1 0.0000 0.8907 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
#> GSM1182186 4 0.583 0.6623 0.040 0.000 0.008 0.612 0.104 0.236
#> GSM1182187 4 0.397 0.8023 0.000 0.000 0.020 0.772 0.044 0.164
#> GSM1182188 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182190 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182191 4 0.602 0.5740 0.040 0.000 0.004 0.540 0.100 0.316
#> GSM1182192 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182193 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182194 6 0.443 0.9703 0.000 0.028 0.424 0.000 0.000 0.548
#> GSM1182195 6 0.456 0.9561 0.000 0.028 0.424 0.000 0.004 0.544
#> GSM1182196 2 0.576 0.3947 0.048 0.676 0.108 0.000 0.136 0.032
#> GSM1182197 3 0.735 0.0668 0.080 0.240 0.424 0.000 0.240 0.016
#> GSM1182198 6 0.443 0.9703 0.000 0.028 0.424 0.000 0.000 0.548
#> GSM1182199 6 0.443 0.9703 0.000 0.028 0.424 0.000 0.000 0.548
#> GSM1182200 5 0.460 0.7662 0.000 0.348 0.024 0.000 0.612 0.016
#> GSM1182201 3 0.603 0.4069 0.032 0.116 0.604 0.000 0.228 0.020
#> GSM1182202 4 0.412 0.7989 0.000 0.000 0.024 0.764 0.048 0.164
#> GSM1182203 4 0.395 0.8036 0.000 0.000 0.024 0.776 0.040 0.160
#> GSM1182204 4 0.412 0.7989 0.000 0.000 0.024 0.764 0.048 0.164
#> GSM1182205 3 0.532 0.4876 0.032 0.112 0.696 0.000 0.016 0.144
#> GSM1182206 3 0.580 0.5087 0.092 0.196 0.648 0.000 0.036 0.028
#> GSM1182207 1 0.579 0.7590 0.628 0.000 0.004 0.216 0.076 0.076
#> GSM1182208 1 0.560 0.7612 0.636 0.000 0.000 0.216 0.076 0.072
#> GSM1182209 5 0.383 0.7972 0.000 0.376 0.000 0.000 0.620 0.004
#> GSM1182210 5 0.383 0.7767 0.000 0.444 0.000 0.000 0.556 0.000
#> GSM1182211 5 0.388 0.7934 0.000 0.396 0.000 0.000 0.600 0.004
#> GSM1182212 5 0.401 0.7930 0.000 0.372 0.000 0.000 0.616 0.012
#> GSM1182213 5 0.402 0.7995 0.004 0.400 0.000 0.000 0.592 0.004
#> GSM1182214 5 0.467 0.7661 0.028 0.428 0.000 0.000 0.536 0.008
#> GSM1182215 3 0.523 0.5438 0.092 0.140 0.712 0.000 0.028 0.028
#> GSM1182216 2 0.677 0.2223 0.152 0.552 0.056 0.000 0.208 0.032
#> GSM1182217 4 0.595 0.6764 0.040 0.000 0.020 0.620 0.100 0.220
#> GSM1182218 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182219 5 0.580 0.5114 0.120 0.420 0.004 0.000 0.448 0.008
#> GSM1182220 5 0.417 0.7905 0.008 0.376 0.000 0.000 0.608 0.008
#> GSM1182221 2 0.377 0.4857 0.108 0.812 0.004 0.000 0.052 0.024
#> GSM1182222 2 0.692 0.2328 0.156 0.540 0.068 0.000 0.204 0.032
#> GSM1182223 3 0.309 0.6154 0.000 0.044 0.852 0.000 0.088 0.016
#> GSM1182224 6 0.479 0.9526 0.008 0.028 0.424 0.000 0.004 0.536
#> GSM1182225 2 0.663 0.1880 0.152 0.552 0.040 0.000 0.224 0.032
#> GSM1182226 2 0.673 0.2441 0.156 0.560 0.056 0.000 0.196 0.032
#> GSM1182227 1 0.607 0.7812 0.572 0.000 0.000 0.216 0.168 0.044
#> GSM1182228 3 0.416 0.5937 0.004 0.052 0.788 0.000 0.112 0.044
#> GSM1182229 3 0.130 0.6204 0.000 0.032 0.952 0.000 0.004 0.012
#> GSM1182230 3 0.300 0.5974 0.036 0.040 0.876 0.000 0.012 0.036
#> GSM1182231 3 0.745 0.1246 0.148 0.344 0.392 0.000 0.084 0.032
#> GSM1182232 1 0.305 0.8130 0.780 0.000 0.004 0.216 0.000 0.000
#> GSM1182233 1 0.333 0.8125 0.772 0.000 0.004 0.216 0.004 0.004
#> GSM1182234 1 0.607 0.7812 0.572 0.000 0.000 0.216 0.168 0.044
#> GSM1182235 2 0.713 -0.2463 0.136 0.420 0.048 0.000 0.356 0.040
#> GSM1182236 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182237 3 0.714 0.3852 0.148 0.168 0.540 0.000 0.104 0.040
#> GSM1182238 2 0.618 0.2099 0.140 0.596 0.048 0.000 0.204 0.012
#> GSM1182239 5 0.692 0.3554 0.116 0.388 0.040 0.000 0.416 0.040
#> GSM1182240 5 0.458 0.6700 0.012 0.476 0.000 0.000 0.496 0.016
#> GSM1182241 5 0.612 0.6694 0.056 0.348 0.036 0.000 0.528 0.032
#> GSM1182242 3 0.246 0.5557 0.000 0.028 0.888 0.000 0.008 0.076
#> GSM1182243 3 0.293 0.6385 0.048 0.060 0.872 0.000 0.012 0.008
#> GSM1182244 6 0.531 0.8736 0.008 0.028 0.368 0.000 0.036 0.560
#> GSM1182245 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182246 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 3 0.276 0.5533 0.008 0.028 0.876 0.000 0.008 0.080
#> GSM1182248 3 0.276 0.5499 0.008 0.028 0.872 0.000 0.004 0.088
#> GSM1182249 3 0.527 0.4779 0.052 0.300 0.616 0.000 0.020 0.012
#> GSM1182250 3 0.440 0.6077 0.056 0.152 0.760 0.000 0.012 0.020
#> GSM1182251 1 0.734 0.4681 0.360 0.000 0.000 0.216 0.120 0.304
#> GSM1182252 3 0.262 0.5391 0.008 0.028 0.876 0.000 0.000 0.088
#> GSM1182253 3 0.240 0.5523 0.000 0.028 0.888 0.000 0.004 0.080
#> GSM1182254 3 0.244 0.6329 0.032 0.036 0.904 0.000 0.020 0.008
#> GSM1182255 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.264 0.8284 0.000 0.000 0.024 0.876 0.012 0.088
#> GSM1182258 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 3 0.364 0.6278 0.044 0.072 0.836 0.000 0.032 0.016
#> GSM1182261 3 0.615 0.4783 0.120 0.196 0.616 0.000 0.036 0.032
#> GSM1182262 3 0.511 0.5489 0.088 0.132 0.724 0.000 0.028 0.028
#> GSM1182263 1 0.712 0.6400 0.468 0.000 0.004 0.216 0.112 0.200
#> GSM1182264 3 0.408 0.6063 0.040 0.040 0.816 0.000 0.048 0.056
#> GSM1182265 3 0.461 0.5115 0.048 0.248 0.688 0.000 0.008 0.008
#> GSM1182266 3 0.319 0.6148 0.040 0.036 0.868 0.000 0.024 0.032
#> GSM1182267 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182268 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182269 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182270 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182271 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 3 0.274 0.6107 0.040 0.040 0.888 0.000 0.008 0.024
#> GSM1182275 3 0.320 0.6101 0.032 0.032 0.868 0.000 0.032 0.036
#> GSM1182276 5 0.419 0.7873 0.000 0.356 0.004 0.000 0.624 0.016
#> GSM1182277 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182278 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182279 1 0.717 0.5741 0.432 0.000 0.000 0.216 0.116 0.236
#> GSM1182280 1 0.688 0.6536 0.504 0.000 0.004 0.216 0.096 0.180
#> GSM1182281 4 0.592 0.4219 0.076 0.000 0.000 0.620 0.176 0.128
#> GSM1182282 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182283 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182284 1 0.610 0.7808 0.568 0.000 0.000 0.216 0.172 0.044
#> GSM1182285 6 0.466 0.9660 0.008 0.028 0.424 0.000 0.000 0.540
#> GSM1182286 5 0.668 0.3718 0.124 0.404 0.020 0.000 0.412 0.040
#> GSM1182287 3 0.581 0.3969 0.004 0.152 0.596 0.000 0.224 0.024
#> GSM1182288 3 0.271 0.5480 0.008 0.028 0.876 0.000 0.004 0.084
#> GSM1182289 1 0.718 0.5751 0.432 0.000 0.000 0.216 0.120 0.232
#> GSM1182290 1 0.597 0.7473 0.612 0.000 0.004 0.216 0.080 0.088
#> GSM1182291 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.251 0.6321 0.044 0.060 0.888 0.000 0.008 0.000
#> GSM1182292 5 0.460 0.7745 0.004 0.376 0.000 0.000 0.584 0.036
#> GSM1182293 2 0.214 0.4657 0.000 0.872 0.000 0.000 0.128 0.000
#> GSM1182294 2 0.201 0.5159 0.004 0.916 0.016 0.000 0.060 0.004
#> GSM1182295 2 0.408 -0.3816 0.008 0.608 0.000 0.000 0.380 0.004
#> GSM1182296 5 0.455 0.7698 0.004 0.384 0.000 0.000 0.580 0.032
#> GSM1182298 6 0.443 0.9703 0.000 0.028 0.424 0.000 0.000 0.548
#> GSM1182299 5 0.551 0.7014 0.048 0.372 0.036 0.000 0.540 0.004
#> GSM1182300 2 0.469 -0.3595 0.008 0.560 0.000 0.000 0.400 0.032
#> GSM1182301 5 0.394 0.7943 0.000 0.380 0.000 0.000 0.612 0.008
#> GSM1182303 5 0.415 0.7869 0.000 0.372 0.004 0.000 0.612 0.012
#> GSM1182304 1 0.722 0.5985 0.452 0.000 0.004 0.216 0.120 0.208
#> GSM1182305 4 0.614 0.5360 0.048 0.000 0.000 0.528 0.120 0.304
#> GSM1182306 4 0.282 0.8273 0.000 0.000 0.024 0.868 0.020 0.088
#> GSM1182307 5 0.477 0.7605 0.012 0.396 0.000 0.000 0.560 0.032
#> GSM1182309 2 0.272 0.4723 0.004 0.860 0.000 0.000 0.112 0.024
#> GSM1182312 2 0.226 0.5202 0.068 0.900 0.000 0.000 0.024 0.008
#> GSM1182314 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 2 0.171 0.5249 0.008 0.940 0.012 0.000 0.020 0.020
#> GSM1182318 2 0.387 -0.3223 0.004 0.604 0.000 0.000 0.392 0.000
#> GSM1182319 2 0.372 0.4842 0.016 0.824 0.028 0.000 0.100 0.032
#> GSM1182320 2 0.134 0.5260 0.008 0.956 0.012 0.000 0.016 0.008
#> GSM1182321 2 0.508 0.4200 0.016 0.716 0.160 0.000 0.068 0.040
#> GSM1182322 2 0.362 0.4892 0.016 0.832 0.028 0.000 0.092 0.032
#> GSM1182324 2 0.369 0.4483 0.024 0.808 0.136 0.000 0.008 0.024
#> GSM1182297 2 0.677 -0.3281 0.128 0.428 0.024 0.000 0.380 0.040
#> GSM1182302 4 0.412 0.7989 0.000 0.000 0.024 0.764 0.048 0.164
#> GSM1182308 5 0.478 0.6387 0.012 0.460 0.004 0.000 0.504 0.020
#> GSM1182310 2 0.143 0.5289 0.016 0.948 0.028 0.000 0.000 0.008
#> GSM1182311 1 0.319 0.8128 0.776 0.000 0.000 0.216 0.004 0.004
#> GSM1182313 4 0.000 0.8436 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.429 0.3655 0.084 0.748 0.000 0.000 0.156 0.012
#> GSM1182317 2 0.249 0.4324 0.000 0.836 0.000 0.000 0.164 0.000
#> GSM1182323 1 0.333 0.8125 0.772 0.000 0.004 0.216 0.004 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:kmeans 139 7.73e-02 1.000 2
#> SD:kmeans 135 8.84e-07 0.459 3
#> SD:kmeans 137 1.49e-06 0.613 4
#> SD:kmeans 114 5.22e-04 0.807 5
#> SD:kmeans 107 6.46e-06 0.775 6
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 46361 rows and 139 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 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.962 0.984 0.3834 0.815 0.645
#> 4 4 0.824 0.911 0.916 0.1093 0.924 0.774
#> 5 5 0.805 0.835 0.871 0.0605 0.953 0.824
#> 6 6 0.762 0.758 0.830 0.0417 0.957 0.815
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 1.000 1 0.000 0.000
#> GSM1182187 1 0.0000 1.000 1 0.000 0.000
#> GSM1182188 1 0.0000 1.000 1 0.000 0.000
#> GSM1182189 1 0.0000 1.000 1 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1 0.000 0.000
#> GSM1182191 1 0.0000 1.000 1 0.000 0.000
#> GSM1182192 1 0.0000 1.000 1 0.000 0.000
#> GSM1182193 1 0.0000 1.000 1 0.000 0.000
#> GSM1182194 3 0.0000 0.957 0 0.000 1.000
#> GSM1182195 3 0.0000 0.957 0 0.000 1.000
#> GSM1182196 2 0.0000 0.984 0 1.000 0.000
#> GSM1182197 2 0.0592 0.976 0 0.988 0.012
#> GSM1182198 3 0.0000 0.957 0 0.000 1.000
#> GSM1182199 3 0.0000 0.957 0 0.000 1.000
#> GSM1182200 2 0.0747 0.974 0 0.984 0.016
#> GSM1182201 3 0.6140 0.341 0 0.404 0.596
#> GSM1182202 1 0.0000 1.000 1 0.000 0.000
#> GSM1182203 1 0.0000 1.000 1 0.000 0.000
#> GSM1182204 1 0.0000 1.000 1 0.000 0.000
#> GSM1182205 3 0.0237 0.955 0 0.004 0.996
#> GSM1182206 3 0.1163 0.937 0 0.028 0.972
#> GSM1182207 1 0.0000 1.000 1 0.000 0.000
#> GSM1182208 1 0.0000 1.000 1 0.000 0.000
#> GSM1182209 2 0.0000 0.984 0 1.000 0.000
#> GSM1182210 2 0.0000 0.984 0 1.000 0.000
#> GSM1182211 2 0.0000 0.984 0 1.000 0.000
#> GSM1182212 2 0.0000 0.984 0 1.000 0.000
#> GSM1182213 2 0.0000 0.984 0 1.000 0.000
#> GSM1182214 2 0.0000 0.984 0 1.000 0.000
#> GSM1182215 3 0.0000 0.957 0 0.000 1.000
#> GSM1182216 2 0.1031 0.967 0 0.976 0.024
#> GSM1182217 1 0.0000 1.000 1 0.000 0.000
#> GSM1182218 1 0.0000 1.000 1 0.000 0.000
#> GSM1182219 2 0.0000 0.984 0 1.000 0.000
#> GSM1182220 2 0.0000 0.984 0 1.000 0.000
#> GSM1182221 2 0.0237 0.982 0 0.996 0.004
#> GSM1182222 2 0.2261 0.925 0 0.932 0.068
#> GSM1182223 3 0.0000 0.957 0 0.000 1.000
#> GSM1182224 3 0.0000 0.957 0 0.000 1.000
#> GSM1182225 2 0.1031 0.967 0 0.976 0.024
#> GSM1182226 2 0.0892 0.971 0 0.980 0.020
#> GSM1182227 1 0.0000 1.000 1 0.000 0.000
#> GSM1182228 3 0.0237 0.955 0 0.004 0.996
#> GSM1182229 3 0.0000 0.957 0 0.000 1.000
#> GSM1182230 3 0.0000 0.957 0 0.000 1.000
#> GSM1182231 2 0.3941 0.821 0 0.844 0.156
#> GSM1182232 1 0.0000 1.000 1 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1 0.000 0.000
#> GSM1182235 2 0.0000 0.984 0 1.000 0.000
#> GSM1182236 1 0.0000 1.000 1 0.000 0.000
#> GSM1182237 3 0.4062 0.798 0 0.164 0.836
#> GSM1182238 2 0.0000 0.984 0 1.000 0.000
#> GSM1182239 2 0.0000 0.984 0 1.000 0.000
#> GSM1182240 2 0.0000 0.984 0 1.000 0.000
#> GSM1182241 2 0.0000 0.984 0 1.000 0.000
#> GSM1182242 3 0.0237 0.955 0 0.004 0.996
#> GSM1182243 3 0.0000 0.957 0 0.000 1.000
#> GSM1182244 3 0.0424 0.953 0 0.008 0.992
#> GSM1182245 1 0.0000 1.000 1 0.000 0.000
#> GSM1182246 1 0.0000 1.000 1 0.000 0.000
#> GSM1182247 3 0.0000 0.957 0 0.000 1.000
#> GSM1182248 3 0.0000 0.957 0 0.000 1.000
#> GSM1182249 3 0.6286 0.149 0 0.464 0.536
#> GSM1182250 3 0.0237 0.955 0 0.004 0.996
#> GSM1182251 1 0.0000 1.000 1 0.000 0.000
#> GSM1182252 3 0.0000 0.957 0 0.000 1.000
#> GSM1182253 3 0.0000 0.957 0 0.000 1.000
#> GSM1182254 3 0.0000 0.957 0 0.000 1.000
#> GSM1182255 1 0.0000 1.000 1 0.000 0.000
#> GSM1182256 1 0.0000 1.000 1 0.000 0.000
#> GSM1182257 1 0.0000 1.000 1 0.000 0.000
#> GSM1182258 1 0.0000 1.000 1 0.000 0.000
#> GSM1182259 1 0.0000 1.000 1 0.000 0.000
#> GSM1182260 3 0.0892 0.944 0 0.020 0.980
#> GSM1182261 3 0.0424 0.953 0 0.008 0.992
#> GSM1182262 3 0.0000 0.957 0 0.000 1.000
#> GSM1182263 1 0.0000 1.000 1 0.000 0.000
#> GSM1182264 3 0.1031 0.941 0 0.024 0.976
#> GSM1182265 3 0.0000 0.957 0 0.000 1.000
#> GSM1182266 3 0.0237 0.955 0 0.004 0.996
#> GSM1182267 1 0.0000 1.000 1 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1 0.000 0.000
#> GSM1182271 1 0.0000 1.000 1 0.000 0.000
#> GSM1182272 1 0.0000 1.000 1 0.000 0.000
#> GSM1182273 3 0.0000 0.957 0 0.000 1.000
#> GSM1182275 3 0.0000 0.957 0 0.000 1.000
#> GSM1182276 2 0.0000 0.984 0 1.000 0.000
#> GSM1182277 1 0.0000 1.000 1 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1 0.000 0.000
#> GSM1182279 1 0.0000 1.000 1 0.000 0.000
#> GSM1182280 1 0.0000 1.000 1 0.000 0.000
#> GSM1182281 1 0.0000 1.000 1 0.000 0.000
#> GSM1182282 1 0.0000 1.000 1 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1 0.000 0.000
#> GSM1182285 3 0.0000 0.957 0 0.000 1.000
#> GSM1182286 2 0.0000 0.984 0 1.000 0.000
#> GSM1182287 3 0.5968 0.434 0 0.364 0.636
#> GSM1182288 3 0.0000 0.957 0 0.000 1.000
#> GSM1182289 1 0.0000 1.000 1 0.000 0.000
#> GSM1182290 1 0.0000 1.000 1 0.000 0.000
#> GSM1182291 1 0.0000 1.000 1 0.000 0.000
#> GSM1182274 3 0.0000 0.957 0 0.000 1.000
#> GSM1182292 2 0.0000 0.984 0 1.000 0.000
#> GSM1182293 2 0.0000 0.984 0 1.000 0.000
#> GSM1182294 2 0.0000 0.984 0 1.000 0.000
#> GSM1182295 2 0.0000 0.984 0 1.000 0.000
#> GSM1182296 2 0.0000 0.984 0 1.000 0.000
#> GSM1182298 3 0.0000 0.957 0 0.000 1.000
#> GSM1182299 2 0.0000 0.984 0 1.000 0.000
#> GSM1182300 2 0.0000 0.984 0 1.000 0.000
#> GSM1182301 2 0.0000 0.984 0 1.000 0.000
#> GSM1182303 2 0.0000 0.984 0 1.000 0.000
#> GSM1182304 1 0.0000 1.000 1 0.000 0.000
#> GSM1182305 1 0.0000 1.000 1 0.000 0.000
#> GSM1182306 1 0.0000 1.000 1 0.000 0.000
#> GSM1182307 2 0.0000 0.984 0 1.000 0.000
#> GSM1182309 2 0.0000 0.984 0 1.000 0.000
#> GSM1182312 2 0.0237 0.982 0 0.996 0.004
#> GSM1182314 1 0.0000 1.000 1 0.000 0.000
#> GSM1182316 2 0.0237 0.982 0 0.996 0.004
#> GSM1182318 2 0.0000 0.984 0 1.000 0.000
#> GSM1182319 2 0.0000 0.984 0 1.000 0.000
#> GSM1182320 2 0.0237 0.982 0 0.996 0.004
#> GSM1182321 2 0.4002 0.812 0 0.840 0.160
#> GSM1182322 2 0.0000 0.984 0 1.000 0.000
#> GSM1182324 2 0.4702 0.739 0 0.788 0.212
#> GSM1182297 2 0.0000 0.984 0 1.000 0.000
#> GSM1182302 1 0.0000 1.000 1 0.000 0.000
#> GSM1182308 2 0.0237 0.982 0 0.996 0.004
#> GSM1182310 2 0.0237 0.982 0 0.996 0.004
#> GSM1182311 1 0.0000 1.000 1 0.000 0.000
#> GSM1182313 1 0.0000 1.000 1 0.000 0.000
#> GSM1182315 2 0.0000 0.984 0 1.000 0.000
#> GSM1182317 2 0.0000 0.984 0 1.000 0.000
#> GSM1182323 1 0.0000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182187 4 0.3907 0.6218 0.232 0.000 0.000 0.768
#> GSM1182188 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182190 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182191 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182192 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182193 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182194 3 0.0707 0.9226 0.020 0.000 0.980 0.000
#> GSM1182195 3 0.0921 0.9232 0.028 0.000 0.972 0.000
#> GSM1182196 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182197 2 0.1022 0.9403 0.000 0.968 0.032 0.000
#> GSM1182198 3 0.0707 0.9226 0.020 0.000 0.980 0.000
#> GSM1182199 3 0.0707 0.9226 0.020 0.000 0.980 0.000
#> GSM1182200 2 0.1004 0.9464 0.004 0.972 0.024 0.000
#> GSM1182201 3 0.4817 0.3554 0.000 0.388 0.612 0.000
#> GSM1182202 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182203 4 0.4746 0.2410 0.368 0.000 0.000 0.632
#> GSM1182204 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182205 3 0.3024 0.8698 0.148 0.000 0.852 0.000
#> GSM1182206 3 0.3447 0.8619 0.128 0.020 0.852 0.000
#> GSM1182207 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182208 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182209 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182210 2 0.0188 0.9524 0.004 0.996 0.000 0.000
#> GSM1182211 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182212 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182213 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182214 2 0.0188 0.9524 0.004 0.996 0.000 0.000
#> GSM1182215 3 0.2760 0.8734 0.128 0.000 0.872 0.000
#> GSM1182216 2 0.2760 0.9115 0.128 0.872 0.000 0.000
#> GSM1182217 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182218 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182219 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182220 2 0.0188 0.9522 0.004 0.996 0.000 0.000
#> GSM1182221 2 0.2814 0.9104 0.132 0.868 0.000 0.000
#> GSM1182222 2 0.3088 0.9067 0.128 0.864 0.008 0.000
#> GSM1182223 3 0.0188 0.9251 0.000 0.004 0.996 0.000
#> GSM1182224 3 0.0921 0.9232 0.028 0.000 0.972 0.000
#> GSM1182225 2 0.2760 0.9115 0.128 0.872 0.000 0.000
#> GSM1182226 2 0.2760 0.9115 0.128 0.872 0.000 0.000
#> GSM1182227 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182228 3 0.1174 0.9178 0.020 0.012 0.968 0.000
#> GSM1182229 3 0.0000 0.9248 0.000 0.000 1.000 0.000
#> GSM1182230 3 0.0336 0.9253 0.008 0.000 0.992 0.000
#> GSM1182231 2 0.4259 0.8687 0.128 0.816 0.056 0.000
#> GSM1182232 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182233 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182234 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182235 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182236 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182237 3 0.3962 0.8098 0.028 0.152 0.820 0.000
#> GSM1182238 2 0.2530 0.9184 0.112 0.888 0.000 0.000
#> GSM1182239 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182240 2 0.2814 0.9190 0.132 0.868 0.000 0.000
#> GSM1182241 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182242 3 0.0000 0.9248 0.000 0.000 1.000 0.000
#> GSM1182243 3 0.0469 0.9251 0.012 0.000 0.988 0.000
#> GSM1182244 3 0.1733 0.9135 0.028 0.024 0.948 0.000
#> GSM1182245 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182246 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0000 0.9248 0.000 0.000 1.000 0.000
#> GSM1182248 3 0.0469 0.9251 0.012 0.000 0.988 0.000
#> GSM1182249 3 0.6707 0.0435 0.088 0.444 0.468 0.000
#> GSM1182250 3 0.2760 0.8734 0.128 0.000 0.872 0.000
#> GSM1182251 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182252 3 0.0000 0.9248 0.000 0.000 1.000 0.000
#> GSM1182253 3 0.0592 0.9245 0.016 0.000 0.984 0.000
#> GSM1182254 3 0.0469 0.9251 0.012 0.000 0.988 0.000
#> GSM1182255 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.1389 0.9075 0.048 0.000 0.000 0.952
#> GSM1182258 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.0927 0.9205 0.016 0.008 0.976 0.000
#> GSM1182261 3 0.3217 0.8670 0.128 0.012 0.860 0.000
#> GSM1182262 3 0.2760 0.8734 0.128 0.000 0.872 0.000
#> GSM1182263 1 0.4916 0.5574 0.576 0.000 0.000 0.424
#> GSM1182264 3 0.1624 0.9095 0.020 0.028 0.952 0.000
#> GSM1182265 3 0.1302 0.9163 0.044 0.000 0.956 0.000
#> GSM1182266 3 0.0469 0.9234 0.012 0.000 0.988 0.000
#> GSM1182267 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182268 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182269 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182270 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182271 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0469 0.9251 0.012 0.000 0.988 0.000
#> GSM1182275 3 0.0000 0.9248 0.000 0.000 1.000 0.000
#> GSM1182276 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182277 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182278 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182279 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182280 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182281 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182282 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182283 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182284 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182285 3 0.0707 0.9226 0.020 0.000 0.980 0.000
#> GSM1182286 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182287 3 0.5855 0.3932 0.044 0.356 0.600 0.000
#> GSM1182288 3 0.0188 0.9252 0.004 0.000 0.996 0.000
#> GSM1182289 1 0.3356 0.9718 0.824 0.000 0.000 0.176
#> GSM1182290 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182291 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0188 0.9253 0.004 0.000 0.996 0.000
#> GSM1182292 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182293 2 0.0188 0.9522 0.004 0.996 0.000 0.000
#> GSM1182294 2 0.0592 0.9515 0.016 0.984 0.000 0.000
#> GSM1182295 2 0.0336 0.9522 0.008 0.992 0.000 0.000
#> GSM1182296 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182298 3 0.0707 0.9226 0.020 0.000 0.980 0.000
#> GSM1182299 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182300 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182301 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182303 2 0.0469 0.9516 0.012 0.988 0.000 0.000
#> GSM1182304 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182305 1 0.4855 0.6083 0.600 0.000 0.000 0.400
#> GSM1182306 4 0.3873 0.6298 0.228 0.000 0.000 0.772
#> GSM1182307 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182309 2 0.0817 0.9504 0.024 0.976 0.000 0.000
#> GSM1182312 2 0.2760 0.9125 0.128 0.872 0.000 0.000
#> GSM1182314 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.2814 0.9104 0.132 0.868 0.000 0.000
#> GSM1182318 2 0.0000 0.9521 0.000 1.000 0.000 0.000
#> GSM1182319 2 0.0817 0.9504 0.024 0.976 0.000 0.000
#> GSM1182320 2 0.2760 0.9125 0.128 0.872 0.000 0.000
#> GSM1182321 2 0.3711 0.8447 0.024 0.836 0.140 0.000
#> GSM1182322 2 0.0817 0.9504 0.024 0.976 0.000 0.000
#> GSM1182324 2 0.4740 0.8416 0.132 0.788 0.080 0.000
#> GSM1182297 2 0.0707 0.9508 0.020 0.980 0.000 0.000
#> GSM1182302 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182308 2 0.2704 0.9133 0.124 0.876 0.000 0.000
#> GSM1182310 2 0.2760 0.9125 0.128 0.872 0.000 0.000
#> GSM1182311 1 0.3311 0.9762 0.828 0.000 0.000 0.172
#> GSM1182313 4 0.0000 0.9578 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.2868 0.9182 0.136 0.864 0.000 0.000
#> GSM1182317 2 0.0188 0.9522 0.004 0.996 0.000 0.000
#> GSM1182323 1 0.3311 0.9762 0.828 0.000 0.000 0.172
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182187 4 0.4161 0.4010 0.392 0.000 0.000 0.608 0.000
#> GSM1182188 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182189 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182192 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182193 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182194 5 0.4171 0.9368 0.000 0.000 0.396 0.000 0.604
#> GSM1182195 5 0.4161 0.9312 0.000 0.000 0.392 0.000 0.608
#> GSM1182196 2 0.3283 0.8601 0.000 0.832 0.000 0.028 0.140
#> GSM1182197 3 0.4940 0.3149 0.000 0.436 0.540 0.004 0.020
#> GSM1182198 5 0.4161 0.9358 0.000 0.000 0.392 0.000 0.608
#> GSM1182199 5 0.4171 0.9368 0.000 0.000 0.396 0.000 0.604
#> GSM1182200 2 0.1644 0.8602 0.000 0.940 0.048 0.008 0.004
#> GSM1182201 3 0.3996 0.5829 0.000 0.228 0.752 0.008 0.012
#> GSM1182202 1 0.0404 0.9451 0.988 0.000 0.000 0.012 0.000
#> GSM1182203 1 0.4306 -0.0826 0.508 0.000 0.000 0.492 0.000
#> GSM1182204 1 0.0404 0.9451 0.988 0.000 0.000 0.012 0.000
#> GSM1182205 5 0.4321 0.5641 0.000 0.004 0.396 0.000 0.600
#> GSM1182206 3 0.3883 0.6685 0.000 0.036 0.780 0.000 0.184
#> GSM1182207 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182208 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182209 2 0.1364 0.8702 0.000 0.952 0.000 0.012 0.036
#> GSM1182210 2 0.1205 0.8774 0.000 0.956 0.000 0.004 0.040
#> GSM1182211 2 0.0579 0.8721 0.000 0.984 0.000 0.008 0.008
#> GSM1182212 2 0.0613 0.8716 0.000 0.984 0.004 0.008 0.004
#> GSM1182213 2 0.0566 0.8744 0.000 0.984 0.000 0.004 0.012
#> GSM1182214 2 0.0955 0.8773 0.000 0.968 0.000 0.004 0.028
#> GSM1182215 3 0.2970 0.7084 0.000 0.004 0.828 0.000 0.168
#> GSM1182216 2 0.3596 0.8300 0.000 0.784 0.016 0.000 0.200
#> GSM1182217 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182218 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.0451 0.8739 0.000 0.988 0.000 0.004 0.008
#> GSM1182220 2 0.0740 0.8717 0.000 0.980 0.004 0.008 0.008
#> GSM1182221 2 0.3876 0.7917 0.000 0.684 0.000 0.000 0.316
#> GSM1182222 2 0.3596 0.8300 0.000 0.784 0.016 0.000 0.200
#> GSM1182223 3 0.2361 0.7254 0.000 0.096 0.892 0.000 0.012
#> GSM1182224 5 0.4161 0.9312 0.000 0.000 0.392 0.000 0.608
#> GSM1182225 2 0.3596 0.8300 0.000 0.784 0.016 0.000 0.200
#> GSM1182226 2 0.3727 0.8272 0.000 0.768 0.016 0.000 0.216
#> GSM1182227 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182228 3 0.4430 0.6459 0.000 0.136 0.784 0.024 0.056
#> GSM1182229 3 0.0290 0.7690 0.000 0.000 0.992 0.000 0.008
#> GSM1182230 3 0.0963 0.7593 0.000 0.000 0.964 0.000 0.036
#> GSM1182231 3 0.6098 0.4245 0.000 0.236 0.568 0.000 0.196
#> GSM1182232 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182233 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182234 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182235 2 0.2734 0.8714 0.000 0.888 0.008 0.028 0.076
#> GSM1182236 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.4816 0.6483 0.000 0.092 0.764 0.028 0.116
#> GSM1182238 2 0.3402 0.8411 0.000 0.804 0.008 0.004 0.184
#> GSM1182239 2 0.2178 0.8667 0.000 0.920 0.008 0.024 0.048
#> GSM1182240 2 0.2971 0.8572 0.000 0.836 0.000 0.008 0.156
#> GSM1182241 2 0.2483 0.8617 0.000 0.908 0.016 0.028 0.048
#> GSM1182242 3 0.0609 0.7630 0.000 0.000 0.980 0.000 0.020
#> GSM1182243 3 0.0404 0.7748 0.000 0.000 0.988 0.000 0.012
#> GSM1182244 5 0.4993 0.8673 0.000 0.024 0.340 0.012 0.624
#> GSM1182245 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182246 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182247 3 0.0703 0.7610 0.000 0.000 0.976 0.000 0.024
#> GSM1182248 3 0.0794 0.7643 0.000 0.000 0.972 0.000 0.028
#> GSM1182249 3 0.4441 0.5970 0.000 0.044 0.720 0.000 0.236
#> GSM1182250 3 0.2929 0.7097 0.000 0.008 0.840 0.000 0.152
#> GSM1182251 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182252 3 0.0880 0.7561 0.000 0.000 0.968 0.000 0.032
#> GSM1182253 3 0.1121 0.7622 0.000 0.000 0.956 0.000 0.044
#> GSM1182254 3 0.0290 0.7725 0.000 0.000 0.992 0.000 0.008
#> GSM1182255 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182256 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182257 4 0.2690 0.8329 0.156 0.000 0.000 0.844 0.000
#> GSM1182258 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182259 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182260 3 0.1989 0.7568 0.000 0.020 0.932 0.016 0.032
#> GSM1182261 3 0.3527 0.6844 0.000 0.024 0.804 0.000 0.172
#> GSM1182262 3 0.2732 0.7147 0.000 0.000 0.840 0.000 0.160
#> GSM1182263 1 0.3895 0.5062 0.680 0.000 0.000 0.320 0.000
#> GSM1182264 3 0.2758 0.7373 0.000 0.032 0.896 0.024 0.048
#> GSM1182265 3 0.2966 0.6793 0.000 0.000 0.816 0.000 0.184
#> GSM1182266 3 0.1507 0.7652 0.000 0.012 0.952 0.012 0.024
#> GSM1182267 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182268 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182272 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182273 3 0.0703 0.7718 0.000 0.000 0.976 0.000 0.024
#> GSM1182275 3 0.1018 0.7687 0.000 0.016 0.968 0.000 0.016
#> GSM1182276 2 0.0854 0.8710 0.000 0.976 0.004 0.008 0.012
#> GSM1182277 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182278 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182279 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182280 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182281 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182282 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182283 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182284 4 0.1364 0.9553 0.036 0.000 0.000 0.952 0.012
#> GSM1182285 5 0.4171 0.9368 0.000 0.000 0.396 0.000 0.604
#> GSM1182286 2 0.2124 0.8697 0.000 0.916 0.000 0.028 0.056
#> GSM1182287 3 0.4136 0.6160 0.000 0.188 0.764 0.000 0.048
#> GSM1182288 3 0.0794 0.7643 0.000 0.000 0.972 0.000 0.028
#> GSM1182289 1 0.0290 0.9486 0.992 0.000 0.000 0.008 0.000
#> GSM1182290 1 0.0162 0.9511 0.996 0.000 0.000 0.004 0.000
#> GSM1182291 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182274 3 0.0162 0.7721 0.000 0.000 0.996 0.000 0.004
#> GSM1182292 2 0.1893 0.8645 0.000 0.928 0.000 0.024 0.048
#> GSM1182293 2 0.3231 0.8362 0.000 0.800 0.000 0.004 0.196
#> GSM1182294 2 0.3491 0.8298 0.000 0.768 0.000 0.004 0.228
#> GSM1182295 2 0.2068 0.8772 0.000 0.904 0.000 0.004 0.092
#> GSM1182296 2 0.1893 0.8645 0.000 0.928 0.000 0.024 0.048
#> GSM1182298 5 0.4171 0.9368 0.000 0.000 0.396 0.000 0.604
#> GSM1182299 2 0.1405 0.8689 0.000 0.956 0.016 0.008 0.020
#> GSM1182300 2 0.2482 0.8713 0.000 0.892 0.000 0.024 0.084
#> GSM1182301 2 0.1907 0.8697 0.000 0.928 0.000 0.028 0.044
#> GSM1182303 2 0.0960 0.8728 0.000 0.972 0.004 0.008 0.016
#> GSM1182304 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182305 1 0.3424 0.6563 0.760 0.000 0.000 0.240 0.000
#> GSM1182306 4 0.4138 0.4213 0.384 0.000 0.000 0.616 0.000
#> GSM1182307 2 0.2236 0.8695 0.000 0.908 0.000 0.024 0.068
#> GSM1182309 2 0.3789 0.8291 0.000 0.760 0.000 0.016 0.224
#> GSM1182312 2 0.4066 0.7855 0.000 0.672 0.000 0.004 0.324
#> GSM1182314 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182316 2 0.3966 0.7796 0.000 0.664 0.000 0.000 0.336
#> GSM1182318 2 0.1671 0.8749 0.000 0.924 0.000 0.000 0.076
#> GSM1182319 2 0.4238 0.8234 0.000 0.740 0.004 0.028 0.228
#> GSM1182320 2 0.3932 0.7845 0.000 0.672 0.000 0.000 0.328
#> GSM1182321 2 0.6436 0.6704 0.000 0.584 0.160 0.024 0.232
#> GSM1182322 2 0.4238 0.8234 0.000 0.740 0.004 0.028 0.228
#> GSM1182324 2 0.5852 0.6557 0.000 0.556 0.116 0.000 0.328
#> GSM1182297 2 0.2484 0.8711 0.000 0.900 0.004 0.028 0.068
#> GSM1182302 1 0.0404 0.9451 0.988 0.000 0.000 0.012 0.000
#> GSM1182308 2 0.2377 0.8485 0.000 0.872 0.000 0.000 0.128
#> GSM1182310 2 0.4218 0.7831 0.000 0.668 0.004 0.004 0.324
#> GSM1182311 1 0.0000 0.9515 1.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.0963 0.9551 0.036 0.000 0.000 0.964 0.000
#> GSM1182315 2 0.3814 0.8314 0.000 0.720 0.000 0.004 0.276
#> GSM1182317 2 0.3209 0.8387 0.000 0.812 0.000 0.008 0.180
#> GSM1182323 1 0.0000 0.9515 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
#> GSM1182186 5 0.1858 0.8817 0.052 0.000 0.000 0.012 0.924 0.012
#> GSM1182187 4 0.5702 0.2476 0.096 0.000 0.000 0.480 0.404 0.020
#> GSM1182188 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182189 5 0.2106 0.8595 0.064 0.000 0.000 0.000 0.904 0.032
#> GSM1182190 5 0.2448 0.8493 0.064 0.000 0.000 0.000 0.884 0.052
#> GSM1182191 5 0.2102 0.8797 0.068 0.000 0.000 0.012 0.908 0.012
#> GSM1182192 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182193 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182194 6 0.2697 0.9304 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1182195 6 0.2854 0.9215 0.000 0.000 0.208 0.000 0.000 0.792
#> GSM1182196 2 0.4833 0.0175 0.316 0.620 0.004 0.004 0.000 0.056
#> GSM1182197 3 0.5212 0.4765 0.048 0.312 0.608 0.004 0.000 0.028
#> GSM1182198 6 0.2697 0.9304 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1182199 6 0.2664 0.9304 0.000 0.000 0.184 0.000 0.000 0.816
#> GSM1182200 2 0.2290 0.7296 0.032 0.908 0.044 0.004 0.000 0.012
#> GSM1182201 3 0.3697 0.7373 0.024 0.148 0.800 0.004 0.000 0.024
#> GSM1182202 5 0.2362 0.8411 0.080 0.000 0.000 0.012 0.892 0.016
#> GSM1182203 5 0.5694 0.0183 0.096 0.000 0.000 0.396 0.488 0.020
#> GSM1182204 5 0.2916 0.8163 0.096 0.000 0.000 0.024 0.860 0.020
#> GSM1182205 6 0.5426 0.4584 0.152 0.000 0.292 0.000 0.000 0.556
#> GSM1182206 3 0.3883 0.7338 0.200 0.004 0.752 0.000 0.000 0.044
#> GSM1182207 5 0.2195 0.8789 0.068 0.000 0.000 0.012 0.904 0.016
#> GSM1182208 5 0.2195 0.8789 0.068 0.000 0.000 0.012 0.904 0.016
#> GSM1182209 2 0.1059 0.7618 0.016 0.964 0.000 0.004 0.000 0.016
#> GSM1182210 2 0.2264 0.7422 0.096 0.888 0.004 0.000 0.000 0.012
#> GSM1182211 2 0.1138 0.7589 0.024 0.960 0.000 0.004 0.000 0.012
#> GSM1182212 2 0.1672 0.7529 0.028 0.940 0.016 0.004 0.000 0.012
#> GSM1182213 2 0.0972 0.7655 0.028 0.964 0.000 0.000 0.000 0.008
#> GSM1182214 2 0.1686 0.7606 0.064 0.924 0.000 0.000 0.000 0.012
#> GSM1182215 3 0.3771 0.7450 0.180 0.000 0.764 0.000 0.000 0.056
#> GSM1182216 2 0.4469 0.5050 0.272 0.676 0.040 0.000 0.000 0.012
#> GSM1182217 5 0.0622 0.8812 0.008 0.000 0.000 0.012 0.980 0.000
#> GSM1182218 5 0.2173 0.8633 0.064 0.000 0.000 0.004 0.904 0.028
#> GSM1182219 2 0.1820 0.7625 0.056 0.924 0.008 0.000 0.000 0.012
#> GSM1182220 2 0.1592 0.7577 0.024 0.944 0.016 0.004 0.000 0.012
#> GSM1182221 1 0.4101 0.6869 0.632 0.352 0.008 0.000 0.000 0.008
#> GSM1182222 2 0.4550 0.4906 0.276 0.668 0.044 0.000 0.000 0.012
#> GSM1182223 3 0.1873 0.8147 0.008 0.048 0.924 0.000 0.000 0.020
#> GSM1182224 6 0.2854 0.9215 0.000 0.000 0.208 0.000 0.000 0.792
#> GSM1182225 2 0.4273 0.5378 0.260 0.696 0.032 0.000 0.000 0.012
#> GSM1182226 2 0.4741 0.3803 0.320 0.624 0.044 0.000 0.000 0.012
#> GSM1182227 4 0.0665 0.8952 0.004 0.000 0.000 0.980 0.008 0.008
#> GSM1182228 3 0.3524 0.7730 0.020 0.080 0.832 0.004 0.000 0.064
#> GSM1182229 3 0.0632 0.8192 0.000 0.000 0.976 0.000 0.000 0.024
#> GSM1182230 3 0.2145 0.8053 0.028 0.000 0.900 0.000 0.000 0.072
#> GSM1182231 3 0.5052 0.6146 0.224 0.108 0.656 0.000 0.000 0.012
#> GSM1182232 5 0.0725 0.8813 0.012 0.000 0.000 0.012 0.976 0.000
#> GSM1182233 5 0.0909 0.8810 0.020 0.000 0.000 0.012 0.968 0.000
#> GSM1182234 4 0.0665 0.8952 0.004 0.000 0.000 0.980 0.008 0.008
#> GSM1182235 2 0.3517 0.7179 0.084 0.832 0.020 0.004 0.000 0.060
#> GSM1182236 5 0.1829 0.8688 0.064 0.000 0.000 0.004 0.920 0.012
#> GSM1182237 3 0.5253 0.6950 0.096 0.100 0.708 0.004 0.000 0.092
#> GSM1182238 2 0.4141 0.4975 0.296 0.676 0.020 0.000 0.000 0.008
#> GSM1182239 2 0.2527 0.7476 0.040 0.892 0.008 0.004 0.000 0.056
#> GSM1182240 2 0.3014 0.7056 0.132 0.832 0.000 0.000 0.000 0.036
#> GSM1182241 2 0.2138 0.7443 0.036 0.908 0.000 0.004 0.000 0.052
#> GSM1182242 3 0.1531 0.8079 0.004 0.000 0.928 0.000 0.000 0.068
#> GSM1182243 3 0.0363 0.8242 0.012 0.000 0.988 0.000 0.000 0.000
#> GSM1182244 6 0.3163 0.8757 0.008 0.012 0.172 0.000 0.000 0.808
#> GSM1182245 4 0.0405 0.8966 0.004 0.000 0.000 0.988 0.008 0.000
#> GSM1182246 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182247 3 0.1556 0.8033 0.000 0.000 0.920 0.000 0.000 0.080
#> GSM1182248 3 0.1765 0.7906 0.000 0.000 0.904 0.000 0.000 0.096
#> GSM1182249 3 0.3970 0.6886 0.260 0.016 0.712 0.000 0.000 0.012
#> GSM1182250 3 0.2884 0.7693 0.164 0.004 0.824 0.000 0.000 0.008
#> GSM1182251 5 0.2102 0.8797 0.068 0.000 0.000 0.012 0.908 0.012
#> GSM1182252 3 0.1765 0.7954 0.000 0.000 0.904 0.000 0.000 0.096
#> GSM1182253 3 0.1866 0.8015 0.008 0.000 0.908 0.000 0.000 0.084
#> GSM1182254 3 0.0622 0.8241 0.012 0.000 0.980 0.000 0.000 0.008
#> GSM1182255 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182256 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182257 4 0.4600 0.7590 0.096 0.000 0.000 0.728 0.156 0.020
#> GSM1182258 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182259 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182260 3 0.2226 0.8129 0.028 0.008 0.904 0.000 0.000 0.060
#> GSM1182261 3 0.3219 0.7443 0.192 0.004 0.792 0.000 0.000 0.012
#> GSM1182262 3 0.3578 0.7570 0.164 0.000 0.784 0.000 0.000 0.052
#> GSM1182263 5 0.5038 0.5428 0.068 0.000 0.000 0.292 0.624 0.016
#> GSM1182264 3 0.2976 0.8000 0.024 0.028 0.860 0.000 0.000 0.088
#> GSM1182265 3 0.3756 0.6574 0.268 0.000 0.712 0.000 0.000 0.020
#> GSM1182266 3 0.2069 0.8128 0.020 0.004 0.908 0.000 0.000 0.068
#> GSM1182267 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182268 5 0.1625 0.8751 0.060 0.000 0.000 0.012 0.928 0.000
#> GSM1182269 5 0.2448 0.8493 0.064 0.000 0.000 0.000 0.884 0.052
#> GSM1182270 5 0.2448 0.8493 0.064 0.000 0.000 0.000 0.884 0.052
#> GSM1182271 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182272 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182273 3 0.1720 0.8203 0.032 0.000 0.928 0.000 0.000 0.040
#> GSM1182275 3 0.1767 0.8132 0.012 0.020 0.932 0.000 0.000 0.036
#> GSM1182276 2 0.1592 0.7503 0.016 0.944 0.024 0.004 0.000 0.012
#> GSM1182277 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182278 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182279 5 0.2094 0.8788 0.068 0.000 0.000 0.008 0.908 0.016
#> GSM1182280 5 0.2195 0.8789 0.068 0.000 0.000 0.012 0.904 0.016
#> GSM1182281 4 0.0405 0.8969 0.000 0.000 0.000 0.988 0.008 0.004
#> GSM1182282 4 0.0551 0.8964 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182283 4 0.0551 0.8961 0.004 0.000 0.000 0.984 0.008 0.004
#> GSM1182284 4 0.0665 0.8952 0.004 0.000 0.000 0.980 0.008 0.008
#> GSM1182285 6 0.2697 0.9304 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1182286 2 0.2845 0.7416 0.064 0.872 0.008 0.004 0.000 0.052
#> GSM1182287 3 0.3352 0.7648 0.056 0.120 0.820 0.000 0.000 0.004
#> GSM1182288 3 0.1814 0.7908 0.000 0.000 0.900 0.000 0.000 0.100
#> GSM1182289 5 0.2375 0.8766 0.068 0.000 0.000 0.020 0.896 0.016
#> GSM1182290 5 0.2195 0.8789 0.068 0.000 0.000 0.012 0.904 0.016
#> GSM1182291 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182274 3 0.0806 0.8239 0.020 0.000 0.972 0.000 0.000 0.008
#> GSM1182292 2 0.1693 0.7498 0.020 0.932 0.000 0.004 0.000 0.044
#> GSM1182293 1 0.4211 0.7000 0.532 0.456 0.004 0.000 0.000 0.008
#> GSM1182294 1 0.4032 0.7398 0.572 0.420 0.000 0.000 0.000 0.008
#> GSM1182295 2 0.2838 0.6550 0.188 0.808 0.000 0.000 0.000 0.004
#> GSM1182296 2 0.1605 0.7504 0.016 0.936 0.000 0.004 0.000 0.044
#> GSM1182298 6 0.2664 0.9304 0.000 0.000 0.184 0.000 0.000 0.816
#> GSM1182299 2 0.1440 0.7534 0.032 0.948 0.004 0.004 0.000 0.012
#> GSM1182300 2 0.3159 0.6921 0.108 0.836 0.000 0.004 0.000 0.052
#> GSM1182301 2 0.1788 0.7589 0.028 0.928 0.000 0.004 0.000 0.040
#> GSM1182303 2 0.1749 0.7526 0.032 0.936 0.016 0.004 0.000 0.012
#> GSM1182304 5 0.1982 0.8782 0.068 0.000 0.000 0.004 0.912 0.016
#> GSM1182305 5 0.4719 0.6270 0.060 0.000 0.000 0.248 0.676 0.016
#> GSM1182306 4 0.5651 0.3534 0.096 0.000 0.000 0.516 0.368 0.020
#> GSM1182307 2 0.2591 0.7346 0.064 0.880 0.000 0.004 0.000 0.052
#> GSM1182309 1 0.4513 0.7119 0.532 0.440 0.000 0.004 0.000 0.024
#> GSM1182312 1 0.3426 0.7824 0.720 0.276 0.000 0.000 0.000 0.004
#> GSM1182314 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182316 1 0.3690 0.7853 0.684 0.308 0.000 0.000 0.000 0.008
#> GSM1182318 2 0.2778 0.6127 0.168 0.824 0.000 0.000 0.000 0.008
#> GSM1182319 1 0.4868 0.7199 0.548 0.396 0.000 0.004 0.000 0.052
#> GSM1182320 1 0.3390 0.7937 0.704 0.296 0.000 0.000 0.000 0.000
#> GSM1182321 1 0.6032 0.7067 0.536 0.328 0.064 0.004 0.000 0.068
#> GSM1182322 1 0.4897 0.7295 0.556 0.384 0.000 0.004 0.000 0.056
#> GSM1182324 1 0.4470 0.7497 0.684 0.256 0.052 0.000 0.000 0.008
#> GSM1182297 2 0.3081 0.7355 0.072 0.856 0.008 0.004 0.000 0.060
#> GSM1182302 5 0.2362 0.8411 0.080 0.000 0.000 0.012 0.892 0.016
#> GSM1182308 2 0.2794 0.6868 0.144 0.840 0.000 0.004 0.000 0.012
#> GSM1182310 1 0.3489 0.7935 0.708 0.288 0.000 0.000 0.000 0.004
#> GSM1182311 5 0.2094 0.8674 0.064 0.000 0.000 0.004 0.908 0.024
#> GSM1182313 4 0.2555 0.8986 0.096 0.000 0.000 0.876 0.008 0.020
#> GSM1182315 2 0.4276 0.0124 0.416 0.564 0.000 0.000 0.000 0.020
#> GSM1182317 2 0.4315 -0.6580 0.488 0.496 0.000 0.004 0.000 0.012
#> GSM1182323 5 0.1471 0.8718 0.064 0.000 0.000 0.004 0.932 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:skmeans 139 7.73e-02 1.000 2
#> SD:skmeans 136 7.03e-07 0.442 3
#> SD:skmeans 135 3.08e-06 0.450 4
#> SD:skmeans 134 9.58e-07 0.556 5
#> SD:skmeans 128 3.76e-09 0.804 6
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 46361 rows and 139 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 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 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.987 0.994 0.1528 0.927 0.859
#> 4 4 0.813 0.904 0.946 0.3273 0.816 0.589
#> 5 5 0.763 0.824 0.903 0.0363 0.961 0.856
#> 6 6 0.752 0.757 0.828 0.0350 0.968 0.874
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.175 0.944 0.048 0 0.952
#> GSM1182187 3 0.000 0.980 0.000 0 1.000
#> GSM1182188 3 0.000 0.980 0.000 0 1.000
#> GSM1182189 1 0.000 0.986 1.000 0 0.000
#> GSM1182190 1 0.000 0.986 1.000 0 0.000
#> GSM1182191 3 0.186 0.940 0.052 0 0.948
#> GSM1182192 1 0.000 0.986 1.000 0 0.000
#> GSM1182193 1 0.000 0.986 1.000 0 0.000
#> GSM1182194 2 0.000 1.000 0.000 1 0.000
#> GSM1182195 2 0.000 1.000 0.000 1 0.000
#> GSM1182196 2 0.000 1.000 0.000 1 0.000
#> GSM1182197 2 0.000 1.000 0.000 1 0.000
#> GSM1182198 2 0.000 1.000 0.000 1 0.000
#> GSM1182199 2 0.000 1.000 0.000 1 0.000
#> GSM1182200 2 0.000 1.000 0.000 1 0.000
#> GSM1182201 2 0.000 1.000 0.000 1 0.000
#> GSM1182202 3 0.000 0.980 0.000 0 1.000
#> GSM1182203 3 0.000 0.980 0.000 0 1.000
#> GSM1182204 3 0.000 0.980 0.000 0 1.000
#> GSM1182205 2 0.000 1.000 0.000 1 0.000
#> GSM1182206 2 0.000 1.000 0.000 1 0.000
#> GSM1182207 1 0.000 0.986 1.000 0 0.000
#> GSM1182208 1 0.000 0.986 1.000 0 0.000
#> GSM1182209 2 0.000 1.000 0.000 1 0.000
#> GSM1182210 2 0.000 1.000 0.000 1 0.000
#> GSM1182211 2 0.000 1.000 0.000 1 0.000
#> GSM1182212 2 0.000 1.000 0.000 1 0.000
#> GSM1182213 2 0.000 1.000 0.000 1 0.000
#> GSM1182214 2 0.000 1.000 0.000 1 0.000
#> GSM1182215 2 0.000 1.000 0.000 1 0.000
#> GSM1182216 2 0.000 1.000 0.000 1 0.000
#> GSM1182217 3 0.186 0.941 0.052 0 0.948
#> GSM1182218 1 0.000 0.986 1.000 0 0.000
#> GSM1182219 2 0.000 1.000 0.000 1 0.000
#> GSM1182220 2 0.000 1.000 0.000 1 0.000
#> GSM1182221 2 0.000 1.000 0.000 1 0.000
#> GSM1182222 2 0.000 1.000 0.000 1 0.000
#> GSM1182223 2 0.000 1.000 0.000 1 0.000
#> GSM1182224 2 0.000 1.000 0.000 1 0.000
#> GSM1182225 2 0.000 1.000 0.000 1 0.000
#> GSM1182226 2 0.000 1.000 0.000 1 0.000
#> GSM1182227 1 0.000 0.986 1.000 0 0.000
#> GSM1182228 2 0.000 1.000 0.000 1 0.000
#> GSM1182229 2 0.000 1.000 0.000 1 0.000
#> GSM1182230 2 0.000 1.000 0.000 1 0.000
#> GSM1182231 2 0.000 1.000 0.000 1 0.000
#> GSM1182232 1 0.000 0.986 1.000 0 0.000
#> GSM1182233 1 0.000 0.986 1.000 0 0.000
#> GSM1182234 1 0.000 0.986 1.000 0 0.000
#> GSM1182235 2 0.000 1.000 0.000 1 0.000
#> GSM1182236 1 0.000 0.986 1.000 0 0.000
#> GSM1182237 2 0.000 1.000 0.000 1 0.000
#> GSM1182238 2 0.000 1.000 0.000 1 0.000
#> GSM1182239 2 0.000 1.000 0.000 1 0.000
#> GSM1182240 2 0.000 1.000 0.000 1 0.000
#> GSM1182241 2 0.000 1.000 0.000 1 0.000
#> GSM1182242 2 0.000 1.000 0.000 1 0.000
#> GSM1182243 2 0.000 1.000 0.000 1 0.000
#> GSM1182244 2 0.000 1.000 0.000 1 0.000
#> GSM1182245 1 0.000 0.986 1.000 0 0.000
#> GSM1182246 3 0.000 0.980 0.000 0 1.000
#> GSM1182247 2 0.000 1.000 0.000 1 0.000
#> GSM1182248 2 0.000 1.000 0.000 1 0.000
#> GSM1182249 2 0.000 1.000 0.000 1 0.000
#> GSM1182250 2 0.000 1.000 0.000 1 0.000
#> GSM1182251 1 0.406 0.802 0.836 0 0.164
#> GSM1182252 2 0.000 1.000 0.000 1 0.000
#> GSM1182253 2 0.000 1.000 0.000 1 0.000
#> GSM1182254 2 0.000 1.000 0.000 1 0.000
#> GSM1182255 3 0.000 0.980 0.000 0 1.000
#> GSM1182256 3 0.000 0.980 0.000 0 1.000
#> GSM1182257 3 0.000 0.980 0.000 0 1.000
#> GSM1182258 3 0.000 0.980 0.000 0 1.000
#> GSM1182259 3 0.000 0.980 0.000 0 1.000
#> GSM1182260 2 0.000 1.000 0.000 1 0.000
#> GSM1182261 2 0.000 1.000 0.000 1 0.000
#> GSM1182262 2 0.000 1.000 0.000 1 0.000
#> GSM1182263 1 0.000 0.986 1.000 0 0.000
#> GSM1182264 2 0.000 1.000 0.000 1 0.000
#> GSM1182265 2 0.000 1.000 0.000 1 0.000
#> GSM1182266 2 0.000 1.000 0.000 1 0.000
#> GSM1182267 1 0.000 0.986 1.000 0 0.000
#> GSM1182268 1 0.000 0.986 1.000 0 0.000
#> GSM1182269 1 0.000 0.986 1.000 0 0.000
#> GSM1182270 1 0.000 0.986 1.000 0 0.000
#> GSM1182271 3 0.000 0.980 0.000 0 1.000
#> GSM1182272 3 0.000 0.980 0.000 0 1.000
#> GSM1182273 2 0.000 1.000 0.000 1 0.000
#> GSM1182275 2 0.000 1.000 0.000 1 0.000
#> GSM1182276 2 0.000 1.000 0.000 1 0.000
#> GSM1182277 1 0.000 0.986 1.000 0 0.000
#> GSM1182278 1 0.000 0.986 1.000 0 0.000
#> GSM1182279 1 0.000 0.986 1.000 0 0.000
#> GSM1182280 1 0.000 0.986 1.000 0 0.000
#> GSM1182281 3 0.525 0.643 0.264 0 0.736
#> GSM1182282 1 0.000 0.986 1.000 0 0.000
#> GSM1182283 1 0.000 0.986 1.000 0 0.000
#> GSM1182284 1 0.000 0.986 1.000 0 0.000
#> GSM1182285 2 0.000 1.000 0.000 1 0.000
#> GSM1182286 2 0.000 1.000 0.000 1 0.000
#> GSM1182287 2 0.000 1.000 0.000 1 0.000
#> GSM1182288 2 0.000 1.000 0.000 1 0.000
#> GSM1182289 1 0.000 0.986 1.000 0 0.000
#> GSM1182290 1 0.000 0.986 1.000 0 0.000
#> GSM1182291 3 0.000 0.980 0.000 0 1.000
#> GSM1182274 2 0.000 1.000 0.000 1 0.000
#> GSM1182292 2 0.000 1.000 0.000 1 0.000
#> GSM1182293 2 0.000 1.000 0.000 1 0.000
#> GSM1182294 2 0.000 1.000 0.000 1 0.000
#> GSM1182295 2 0.000 1.000 0.000 1 0.000
#> GSM1182296 2 0.000 1.000 0.000 1 0.000
#> GSM1182298 2 0.000 1.000 0.000 1 0.000
#> GSM1182299 2 0.000 1.000 0.000 1 0.000
#> GSM1182300 2 0.000 1.000 0.000 1 0.000
#> GSM1182301 2 0.000 1.000 0.000 1 0.000
#> GSM1182303 2 0.000 1.000 0.000 1 0.000
#> GSM1182304 1 0.000 0.986 1.000 0 0.000
#> GSM1182305 1 0.510 0.672 0.752 0 0.248
#> GSM1182306 3 0.000 0.980 0.000 0 1.000
#> GSM1182307 2 0.000 1.000 0.000 1 0.000
#> GSM1182309 2 0.000 1.000 0.000 1 0.000
#> GSM1182312 2 0.000 1.000 0.000 1 0.000
#> GSM1182314 3 0.000 0.980 0.000 0 1.000
#> GSM1182316 2 0.000 1.000 0.000 1 0.000
#> GSM1182318 2 0.000 1.000 0.000 1 0.000
#> GSM1182319 2 0.000 1.000 0.000 1 0.000
#> GSM1182320 2 0.000 1.000 0.000 1 0.000
#> GSM1182321 2 0.000 1.000 0.000 1 0.000
#> GSM1182322 2 0.000 1.000 0.000 1 0.000
#> GSM1182324 2 0.000 1.000 0.000 1 0.000
#> GSM1182297 2 0.000 1.000 0.000 1 0.000
#> GSM1182302 3 0.000 0.980 0.000 0 1.000
#> GSM1182308 2 0.000 1.000 0.000 1 0.000
#> GSM1182310 2 0.000 1.000 0.000 1 0.000
#> GSM1182311 1 0.000 0.986 1.000 0 0.000
#> GSM1182313 3 0.000 0.980 0.000 0 1.000
#> GSM1182315 2 0.000 1.000 0.000 1 0.000
#> GSM1182317 2 0.000 1.000 0.000 1 0.000
#> GSM1182323 1 0.000 0.986 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.1389 0.9438 0.048 0.000 0.000 0.952
#> GSM1182187 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182188 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182191 4 0.1474 0.9404 0.052 0.000 0.000 0.948
#> GSM1182192 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182194 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182195 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182196 2 0.2081 0.8832 0.000 0.916 0.084 0.000
#> GSM1182197 2 0.4500 0.6928 0.000 0.684 0.316 0.000
#> GSM1182198 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182199 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182200 2 0.3907 0.8057 0.000 0.768 0.232 0.000
#> GSM1182201 3 0.2469 0.8462 0.000 0.108 0.892 0.000
#> GSM1182202 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182203 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182204 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182205 3 0.1302 0.9008 0.000 0.044 0.956 0.000
#> GSM1182206 3 0.3172 0.8066 0.000 0.160 0.840 0.000
#> GSM1182207 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182209 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182210 2 0.2469 0.9020 0.000 0.892 0.108 0.000
#> GSM1182211 2 0.0188 0.9075 0.000 0.996 0.004 0.000
#> GSM1182212 2 0.1940 0.9041 0.000 0.924 0.076 0.000
#> GSM1182213 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182214 2 0.0188 0.9075 0.000 0.996 0.004 0.000
#> GSM1182215 3 0.4961 0.0668 0.000 0.448 0.552 0.000
#> GSM1182216 2 0.2760 0.8888 0.000 0.872 0.128 0.000
#> GSM1182217 4 0.1474 0.9405 0.052 0.000 0.000 0.948
#> GSM1182218 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182219 2 0.1637 0.9122 0.000 0.940 0.060 0.000
#> GSM1182220 2 0.2081 0.9038 0.000 0.916 0.084 0.000
#> GSM1182221 2 0.2589 0.8951 0.000 0.884 0.116 0.000
#> GSM1182222 2 0.3266 0.8634 0.000 0.832 0.168 0.000
#> GSM1182223 3 0.4933 0.1426 0.000 0.432 0.568 0.000
#> GSM1182224 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182225 2 0.2814 0.8861 0.000 0.868 0.132 0.000
#> GSM1182226 2 0.2589 0.8956 0.000 0.884 0.116 0.000
#> GSM1182227 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182228 3 0.2921 0.8308 0.000 0.140 0.860 0.000
#> GSM1182229 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182230 3 0.1211 0.9035 0.000 0.040 0.960 0.000
#> GSM1182231 2 0.3266 0.8610 0.000 0.832 0.168 0.000
#> GSM1182232 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182235 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182236 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182237 2 0.3444 0.8353 0.000 0.816 0.184 0.000
#> GSM1182238 2 0.2011 0.9094 0.000 0.920 0.080 0.000
#> GSM1182239 2 0.1637 0.9033 0.000 0.940 0.060 0.000
#> GSM1182240 2 0.0469 0.9100 0.000 0.988 0.012 0.000
#> GSM1182241 2 0.2149 0.8821 0.000 0.912 0.088 0.000
#> GSM1182242 3 0.0188 0.9206 0.000 0.004 0.996 0.000
#> GSM1182243 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182244 3 0.1792 0.8836 0.000 0.068 0.932 0.000
#> GSM1182245 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182248 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182249 2 0.4454 0.6902 0.000 0.692 0.308 0.000
#> GSM1182250 3 0.1211 0.9031 0.000 0.040 0.960 0.000
#> GSM1182251 1 0.3219 0.8018 0.836 0.000 0.000 0.164
#> GSM1182252 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182253 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182254 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182255 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182258 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.0921 0.9133 0.000 0.028 0.972 0.000
#> GSM1182261 2 0.4406 0.6833 0.000 0.700 0.300 0.000
#> GSM1182262 3 0.4761 0.3539 0.000 0.372 0.628 0.000
#> GSM1182263 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182264 3 0.1637 0.8840 0.000 0.060 0.940 0.000
#> GSM1182265 3 0.0188 0.9215 0.000 0.004 0.996 0.000
#> GSM1182266 3 0.0469 0.9176 0.000 0.012 0.988 0.000
#> GSM1182267 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182275 3 0.0188 0.9215 0.000 0.004 0.996 0.000
#> GSM1182276 2 0.1940 0.9010 0.000 0.924 0.076 0.000
#> GSM1182277 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182279 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182280 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182281 4 0.4164 0.6430 0.264 0.000 0.000 0.736
#> GSM1182282 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182285 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182286 2 0.0336 0.9091 0.000 0.992 0.008 0.000
#> GSM1182287 3 0.2814 0.8311 0.000 0.132 0.868 0.000
#> GSM1182288 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182289 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182290 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182292 2 0.0188 0.9075 0.000 0.996 0.004 0.000
#> GSM1182293 2 0.2081 0.9094 0.000 0.916 0.084 0.000
#> GSM1182294 2 0.1118 0.9127 0.000 0.964 0.036 0.000
#> GSM1182295 2 0.1940 0.9097 0.000 0.924 0.076 0.000
#> GSM1182296 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182298 3 0.0000 0.9223 0.000 0.000 1.000 0.000
#> GSM1182299 2 0.2814 0.8647 0.000 0.868 0.132 0.000
#> GSM1182300 2 0.1211 0.9072 0.000 0.960 0.040 0.000
#> GSM1182301 2 0.1022 0.9096 0.000 0.968 0.032 0.000
#> GSM1182303 2 0.2530 0.8990 0.000 0.888 0.112 0.000
#> GSM1182304 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182305 1 0.4040 0.6723 0.752 0.000 0.000 0.248
#> GSM1182306 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182307 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182309 2 0.0592 0.9105 0.000 0.984 0.016 0.000
#> GSM1182312 2 0.2530 0.8976 0.000 0.888 0.112 0.000
#> GSM1182314 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.2814 0.8911 0.000 0.868 0.132 0.000
#> GSM1182318 2 0.0188 0.9077 0.000 0.996 0.004 0.000
#> GSM1182319 2 0.2704 0.8721 0.000 0.876 0.124 0.000
#> GSM1182320 2 0.2469 0.8996 0.000 0.892 0.108 0.000
#> GSM1182321 3 0.2408 0.8623 0.000 0.104 0.896 0.000
#> GSM1182322 2 0.2011 0.8822 0.000 0.920 0.080 0.000
#> GSM1182324 3 0.3024 0.8031 0.000 0.148 0.852 0.000
#> GSM1182297 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182302 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182308 2 0.3400 0.8562 0.000 0.820 0.180 0.000
#> GSM1182310 2 0.2704 0.8925 0.000 0.876 0.124 0.000
#> GSM1182311 1 0.0000 0.9864 1.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.9797 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.0188 0.9075 0.000 0.996 0.004 0.000
#> GSM1182317 2 0.0000 0.9066 0.000 1.000 0.000 0.000
#> GSM1182323 1 0.0000 0.9864 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
#> GSM1182186 5 0.2329 0.6380 0.000 0.000 0.000 0.124 0.876
#> GSM1182187 5 0.4219 0.2666 0.000 0.000 0.000 0.416 0.584
#> GSM1182188 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0162 0.9654 0.996 0.000 0.000 0.000 0.004
#> GSM1182191 5 0.1908 0.6499 0.000 0.000 0.000 0.092 0.908
#> GSM1182192 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182195 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182196 2 0.2676 0.8808 0.000 0.884 0.080 0.000 0.036
#> GSM1182197 2 0.4290 0.6932 0.000 0.680 0.304 0.000 0.016
#> GSM1182198 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182199 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182200 2 0.3461 0.8050 0.000 0.772 0.224 0.000 0.004
#> GSM1182201 3 0.2230 0.8306 0.000 0.116 0.884 0.000 0.000
#> GSM1182202 5 0.4182 0.3038 0.000 0.000 0.000 0.400 0.600
#> GSM1182203 4 0.4182 0.2100 0.000 0.000 0.000 0.600 0.400
#> GSM1182204 5 0.4278 0.2283 0.000 0.000 0.000 0.452 0.548
#> GSM1182205 3 0.1836 0.8771 0.000 0.036 0.932 0.000 0.032
#> GSM1182206 3 0.3183 0.7926 0.000 0.156 0.828 0.000 0.016
#> GSM1182207 1 0.4307 -0.2432 0.500 0.000 0.000 0.000 0.500
#> GSM1182208 5 0.4297 0.2316 0.472 0.000 0.000 0.000 0.528
#> GSM1182209 2 0.0609 0.8996 0.000 0.980 0.000 0.000 0.020
#> GSM1182210 2 0.2653 0.9001 0.000 0.880 0.096 0.000 0.024
#> GSM1182211 2 0.0671 0.9005 0.000 0.980 0.004 0.000 0.016
#> GSM1182212 2 0.1774 0.9038 0.000 0.932 0.052 0.000 0.016
#> GSM1182213 2 0.0794 0.9028 0.000 0.972 0.000 0.000 0.028
#> GSM1182214 2 0.1121 0.9022 0.000 0.956 0.000 0.000 0.044
#> GSM1182215 3 0.4420 0.0699 0.000 0.448 0.548 0.000 0.004
#> GSM1182216 2 0.3237 0.8881 0.000 0.848 0.104 0.000 0.048
#> GSM1182217 5 0.2561 0.6260 0.000 0.000 0.000 0.144 0.856
#> GSM1182218 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.2304 0.9069 0.000 0.908 0.044 0.000 0.048
#> GSM1182220 2 0.1845 0.9050 0.000 0.928 0.056 0.000 0.016
#> GSM1182221 2 0.3090 0.8941 0.000 0.860 0.088 0.000 0.052
#> GSM1182222 2 0.3409 0.8682 0.000 0.824 0.144 0.000 0.032
#> GSM1182223 3 0.4256 0.1416 0.000 0.436 0.564 0.000 0.000
#> GSM1182224 3 0.0162 0.9092 0.000 0.000 0.996 0.000 0.004
#> GSM1182225 2 0.3237 0.8872 0.000 0.848 0.104 0.000 0.048
#> GSM1182226 2 0.3090 0.8947 0.000 0.860 0.088 0.000 0.052
#> GSM1182227 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182228 3 0.2629 0.8226 0.000 0.136 0.860 0.000 0.004
#> GSM1182229 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182230 3 0.1205 0.8898 0.000 0.040 0.956 0.000 0.004
#> GSM1182231 2 0.3595 0.8657 0.000 0.816 0.140 0.000 0.044
#> GSM1182232 1 0.0162 0.9654 0.996 0.000 0.000 0.000 0.004
#> GSM1182233 1 0.0510 0.9566 0.984 0.000 0.000 0.000 0.016
#> GSM1182234 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.0880 0.9012 0.000 0.968 0.000 0.000 0.032
#> GSM1182236 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 2 0.3944 0.8365 0.000 0.788 0.160 0.000 0.052
#> GSM1182238 2 0.2592 0.9045 0.000 0.892 0.056 0.000 0.052
#> GSM1182239 2 0.1836 0.9032 0.000 0.932 0.036 0.000 0.032
#> GSM1182240 2 0.1364 0.9071 0.000 0.952 0.012 0.000 0.036
#> GSM1182241 2 0.2390 0.8730 0.000 0.896 0.084 0.000 0.020
#> GSM1182242 3 0.0162 0.9095 0.000 0.004 0.996 0.000 0.000
#> GSM1182243 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182244 3 0.1768 0.8700 0.000 0.072 0.924 0.000 0.004
#> GSM1182245 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182248 3 0.0162 0.9092 0.000 0.000 0.996 0.000 0.004
#> GSM1182249 2 0.4708 0.6898 0.000 0.668 0.292 0.000 0.040
#> GSM1182250 3 0.1750 0.8815 0.000 0.036 0.936 0.000 0.028
#> GSM1182251 5 0.2450 0.6772 0.048 0.000 0.000 0.052 0.900
#> GSM1182252 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182253 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182254 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182255 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.1043 0.9094 0.000 0.000 0.000 0.960 0.040
#> GSM1182258 4 0.0162 0.9331 0.000 0.000 0.000 0.996 0.004
#> GSM1182259 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.0992 0.9011 0.000 0.024 0.968 0.000 0.008
#> GSM1182261 2 0.4315 0.7004 0.000 0.700 0.276 0.000 0.024
#> GSM1182262 3 0.4367 0.3506 0.000 0.372 0.620 0.000 0.008
#> GSM1182263 5 0.4201 0.3674 0.408 0.000 0.000 0.000 0.592
#> GSM1182264 3 0.2104 0.8612 0.000 0.060 0.916 0.000 0.024
#> GSM1182265 3 0.0451 0.9089 0.000 0.008 0.988 0.000 0.004
#> GSM1182266 3 0.0451 0.9068 0.000 0.008 0.988 0.000 0.004
#> GSM1182267 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0703 0.9492 0.976 0.000 0.000 0.000 0.024
#> GSM1182271 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182275 3 0.0324 0.9096 0.000 0.004 0.992 0.000 0.004
#> GSM1182276 2 0.1701 0.9019 0.000 0.936 0.048 0.000 0.016
#> GSM1182277 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.2471 0.6846 0.136 0.000 0.000 0.000 0.864
#> GSM1182280 5 0.4219 0.3521 0.416 0.000 0.000 0.000 0.584
#> GSM1182281 4 0.4280 0.6358 0.140 0.000 0.000 0.772 0.088
#> GSM1182282 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9679 1.000 0.000 0.000 0.000 0.000
#> GSM1182285 3 0.0000 0.9099 0.000 0.000 1.000 0.000 0.000
#> GSM1182286 2 0.1041 0.9029 0.000 0.964 0.004 0.000 0.032
#> GSM1182287 3 0.2377 0.8257 0.000 0.128 0.872 0.000 0.000
#> GSM1182288 3 0.0162 0.9092 0.000 0.000 0.996 0.000 0.004
#> GSM1182289 5 0.2424 0.6849 0.132 0.000 0.000 0.000 0.868
#> GSM1182290 5 0.4278 0.2859 0.452 0.000 0.000 0.000 0.548
#> GSM1182291 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182292 2 0.0771 0.9001 0.000 0.976 0.004 0.000 0.020
#> GSM1182293 2 0.2473 0.9055 0.000 0.896 0.072 0.000 0.032
#> GSM1182294 2 0.1965 0.9057 0.000 0.924 0.024 0.000 0.052
#> GSM1182295 2 0.2359 0.9067 0.000 0.904 0.060 0.000 0.036
#> GSM1182296 2 0.0609 0.8996 0.000 0.980 0.000 0.000 0.020
#> GSM1182298 3 0.0162 0.9098 0.000 0.000 0.996 0.000 0.004
#> GSM1182299 2 0.2573 0.8710 0.000 0.880 0.104 0.000 0.016
#> GSM1182300 2 0.1216 0.9010 0.000 0.960 0.020 0.000 0.020
#> GSM1182301 2 0.1310 0.9020 0.000 0.956 0.024 0.000 0.020
#> GSM1182303 2 0.2304 0.9002 0.000 0.892 0.100 0.000 0.008
#> GSM1182304 5 0.2516 0.6842 0.140 0.000 0.000 0.000 0.860
#> GSM1182305 5 0.2370 0.6747 0.040 0.000 0.000 0.056 0.904
#> GSM1182306 4 0.1608 0.8815 0.000 0.000 0.000 0.928 0.072
#> GSM1182307 2 0.0609 0.8996 0.000 0.980 0.000 0.000 0.020
#> GSM1182309 2 0.0798 0.9035 0.000 0.976 0.008 0.000 0.016
#> GSM1182312 2 0.3033 0.8964 0.000 0.864 0.084 0.000 0.052
#> GSM1182314 4 0.0162 0.9331 0.000 0.000 0.000 0.996 0.004
#> GSM1182316 2 0.3255 0.8922 0.000 0.848 0.100 0.000 0.052
#> GSM1182318 2 0.0451 0.9041 0.000 0.988 0.004 0.000 0.008
#> GSM1182319 2 0.2915 0.8721 0.000 0.860 0.116 0.000 0.024
#> GSM1182320 2 0.2962 0.8979 0.000 0.868 0.084 0.000 0.048
#> GSM1182321 3 0.2470 0.8419 0.000 0.104 0.884 0.000 0.012
#> GSM1182322 2 0.2511 0.8747 0.000 0.892 0.080 0.000 0.028
#> GSM1182324 3 0.2843 0.7987 0.000 0.144 0.848 0.000 0.008
#> GSM1182297 2 0.0880 0.9012 0.000 0.968 0.000 0.000 0.032
#> GSM1182302 5 0.4249 0.2592 0.000 0.000 0.000 0.432 0.568
#> GSM1182308 2 0.3048 0.8516 0.000 0.820 0.176 0.000 0.004
#> GSM1182310 2 0.3201 0.8918 0.000 0.852 0.096 0.000 0.052
#> GSM1182311 1 0.0510 0.9567 0.984 0.000 0.000 0.000 0.016
#> GSM1182313 4 0.0000 0.9349 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.1341 0.9019 0.000 0.944 0.000 0.000 0.056
#> GSM1182317 2 0.0510 0.8999 0.000 0.984 0.000 0.000 0.016
#> GSM1182323 1 0.0404 0.9594 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
#> GSM1182186 5 0.2712 0.693 0.000 0.000 0.000 0.088 0.864 0.048
#> GSM1182187 4 0.5984 0.438 0.000 0.000 0.000 0.444 0.276 0.280
#> GSM1182188 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 1 0.3629 0.833 0.724 0.000 0.000 0.000 0.016 0.260
#> GSM1182190 1 0.3789 0.830 0.716 0.000 0.000 0.000 0.024 0.260
#> GSM1182191 5 0.2258 0.722 0.000 0.000 0.000 0.060 0.896 0.044
#> GSM1182192 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.3023 0.775 0.000 0.000 0.768 0.000 0.000 0.232
#> GSM1182195 3 0.3050 0.773 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1182196 2 0.4723 0.649 0.000 0.664 0.232 0.000 0.000 0.104
#> GSM1182197 3 0.4535 -0.275 0.000 0.480 0.488 0.000 0.000 0.032
#> GSM1182198 3 0.2996 0.776 0.000 0.000 0.772 0.000 0.000 0.228
#> GSM1182199 3 0.3050 0.773 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1182200 2 0.4493 0.576 0.000 0.612 0.344 0.000 0.000 0.044
#> GSM1182201 3 0.1838 0.794 0.000 0.068 0.916 0.000 0.000 0.016
#> GSM1182202 4 0.6065 0.361 0.000 0.000 0.000 0.404 0.316 0.280
#> GSM1182203 4 0.5546 0.548 0.000 0.000 0.000 0.552 0.192 0.256
#> GSM1182204 4 0.5786 0.491 0.000 0.000 0.000 0.504 0.240 0.256
#> GSM1182205 3 0.4449 0.740 0.000 0.088 0.696 0.000 0.000 0.216
#> GSM1182206 3 0.4408 0.463 0.000 0.356 0.608 0.000 0.000 0.036
#> GSM1182207 5 0.4747 0.561 0.324 0.000 0.000 0.000 0.608 0.068
#> GSM1182208 5 0.4466 0.658 0.260 0.000 0.000 0.000 0.672 0.068
#> GSM1182209 2 0.2416 0.843 0.000 0.844 0.000 0.000 0.000 0.156
#> GSM1182210 2 0.2672 0.848 0.000 0.868 0.080 0.000 0.000 0.052
#> GSM1182211 2 0.2416 0.846 0.000 0.844 0.000 0.000 0.000 0.156
#> GSM1182212 2 0.2750 0.847 0.000 0.844 0.020 0.000 0.000 0.136
#> GSM1182213 2 0.0713 0.855 0.000 0.972 0.000 0.000 0.000 0.028
#> GSM1182214 2 0.1007 0.856 0.000 0.956 0.000 0.000 0.000 0.044
#> GSM1182215 3 0.5443 0.199 0.000 0.384 0.492 0.000 0.000 0.124
#> GSM1182216 2 0.2134 0.839 0.000 0.904 0.052 0.000 0.000 0.044
#> GSM1182217 5 0.5008 0.403 0.000 0.000 0.000 0.108 0.612 0.280
#> GSM1182218 1 0.3711 0.831 0.720 0.000 0.000 0.000 0.020 0.260
#> GSM1182219 2 0.1418 0.850 0.000 0.944 0.024 0.000 0.000 0.032
#> GSM1182220 2 0.3054 0.853 0.000 0.828 0.036 0.000 0.000 0.136
#> GSM1182221 2 0.2365 0.838 0.000 0.888 0.040 0.000 0.000 0.072
#> GSM1182222 2 0.2775 0.828 0.000 0.856 0.104 0.000 0.000 0.040
#> GSM1182223 2 0.3864 0.199 0.000 0.520 0.480 0.000 0.000 0.000
#> GSM1182224 3 0.3101 0.771 0.000 0.000 0.756 0.000 0.000 0.244
#> GSM1182225 2 0.2197 0.839 0.000 0.900 0.056 0.000 0.000 0.044
#> GSM1182226 2 0.2554 0.835 0.000 0.876 0.048 0.000 0.000 0.076
#> GSM1182227 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182228 3 0.3558 0.642 0.000 0.248 0.736 0.000 0.000 0.016
#> GSM1182229 3 0.0146 0.823 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1182230 3 0.2908 0.809 0.000 0.048 0.848 0.000 0.000 0.104
#> GSM1182231 2 0.2842 0.823 0.000 0.852 0.104 0.000 0.000 0.044
#> GSM1182232 1 0.3424 0.839 0.772 0.000 0.000 0.000 0.024 0.204
#> GSM1182233 1 0.4227 0.815 0.692 0.000 0.000 0.000 0.052 0.256
#> GSM1182234 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.2378 0.849 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM1182236 1 0.3629 0.833 0.724 0.000 0.000 0.000 0.016 0.260
#> GSM1182237 2 0.2908 0.813 0.000 0.848 0.104 0.000 0.000 0.048
#> GSM1182238 2 0.1780 0.844 0.000 0.924 0.028 0.000 0.000 0.048
#> GSM1182239 2 0.2669 0.849 0.000 0.836 0.008 0.000 0.000 0.156
#> GSM1182240 2 0.0935 0.856 0.000 0.964 0.004 0.000 0.000 0.032
#> GSM1182241 2 0.5277 0.610 0.000 0.592 0.256 0.000 0.000 0.152
#> GSM1182242 3 0.0291 0.824 0.000 0.004 0.992 0.000 0.000 0.004
#> GSM1182243 3 0.0260 0.823 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182244 3 0.3766 0.766 0.000 0.032 0.736 0.000 0.000 0.232
#> GSM1182245 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182246 4 0.0146 0.815 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182247 3 0.1075 0.824 0.000 0.000 0.952 0.000 0.000 0.048
#> GSM1182248 3 0.2454 0.805 0.000 0.000 0.840 0.000 0.000 0.160
#> GSM1182249 2 0.4587 0.271 0.000 0.508 0.456 0.000 0.000 0.036
#> GSM1182250 3 0.2176 0.789 0.000 0.080 0.896 0.000 0.000 0.024
#> GSM1182251 5 0.1003 0.783 0.020 0.000 0.000 0.016 0.964 0.000
#> GSM1182252 3 0.1267 0.824 0.000 0.000 0.940 0.000 0.000 0.060
#> GSM1182253 3 0.0260 0.824 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182254 3 0.0000 0.823 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1182255 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.1575 0.792 0.000 0.000 0.000 0.936 0.032 0.032
#> GSM1182258 4 0.0146 0.815 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182259 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 3 0.0820 0.820 0.000 0.016 0.972 0.000 0.000 0.012
#> GSM1182261 2 0.4122 0.673 0.000 0.704 0.248 0.000 0.000 0.048
#> GSM1182262 3 0.5071 0.322 0.000 0.376 0.540 0.000 0.000 0.084
#> GSM1182263 5 0.3136 0.743 0.228 0.000 0.000 0.000 0.768 0.004
#> GSM1182264 3 0.2039 0.787 0.000 0.020 0.904 0.000 0.000 0.076
#> GSM1182265 3 0.1196 0.815 0.000 0.008 0.952 0.000 0.000 0.040
#> GSM1182266 3 0.0405 0.822 0.000 0.004 0.988 0.000 0.000 0.008
#> GSM1182267 1 0.0146 0.846 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1182268 1 0.3629 0.833 0.724 0.000 0.000 0.000 0.016 0.260
#> GSM1182269 1 0.3629 0.833 0.724 0.000 0.000 0.000 0.016 0.260
#> GSM1182270 1 0.4249 0.812 0.688 0.000 0.000 0.000 0.052 0.260
#> GSM1182271 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 3 0.0146 0.823 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1182275 3 0.0260 0.822 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182276 2 0.2831 0.847 0.000 0.840 0.024 0.000 0.000 0.136
#> GSM1182277 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.1462 0.803 0.056 0.000 0.000 0.000 0.936 0.008
#> GSM1182280 5 0.3649 0.731 0.196 0.000 0.000 0.000 0.764 0.040
#> GSM1182281 4 0.5286 0.365 0.296 0.000 0.000 0.572 0.132 0.000
#> GSM1182282 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.846 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182285 3 0.3050 0.773 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1182286 2 0.2558 0.849 0.000 0.840 0.004 0.000 0.000 0.156
#> GSM1182287 3 0.3464 0.555 0.000 0.312 0.688 0.000 0.000 0.000
#> GSM1182288 3 0.0937 0.825 0.000 0.000 0.960 0.000 0.000 0.040
#> GSM1182289 5 0.1398 0.802 0.052 0.000 0.000 0.000 0.940 0.008
#> GSM1182290 5 0.3933 0.711 0.248 0.000 0.000 0.000 0.716 0.036
#> GSM1182291 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.0260 0.823 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182292 2 0.2378 0.843 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM1182293 2 0.2263 0.849 0.000 0.896 0.048 0.000 0.000 0.056
#> GSM1182294 2 0.1719 0.848 0.000 0.924 0.016 0.000 0.000 0.060
#> GSM1182295 2 0.1649 0.853 0.000 0.932 0.032 0.000 0.000 0.036
#> GSM1182296 2 0.2378 0.843 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM1182298 3 0.3050 0.776 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1182299 2 0.4693 0.729 0.000 0.684 0.176 0.000 0.000 0.140
#> GSM1182300 2 0.2631 0.843 0.000 0.840 0.008 0.000 0.000 0.152
#> GSM1182301 2 0.3279 0.837 0.000 0.796 0.028 0.000 0.000 0.176
#> GSM1182303 2 0.3375 0.842 0.000 0.816 0.088 0.000 0.000 0.096
#> GSM1182304 5 0.1524 0.804 0.060 0.000 0.000 0.000 0.932 0.008
#> GSM1182305 5 0.0914 0.780 0.016 0.000 0.000 0.016 0.968 0.000
#> GSM1182306 4 0.4040 0.673 0.000 0.000 0.000 0.688 0.032 0.280
#> GSM1182307 2 0.2340 0.844 0.000 0.852 0.000 0.000 0.000 0.148
#> GSM1182309 2 0.2631 0.848 0.000 0.840 0.008 0.000 0.000 0.152
#> GSM1182312 2 0.2420 0.838 0.000 0.884 0.040 0.000 0.000 0.076
#> GSM1182314 4 0.0260 0.814 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182316 2 0.2629 0.835 0.000 0.872 0.068 0.000 0.000 0.060
#> GSM1182318 2 0.2006 0.856 0.000 0.892 0.004 0.000 0.000 0.104
#> GSM1182319 2 0.4545 0.713 0.000 0.696 0.192 0.000 0.000 0.112
#> GSM1182320 2 0.2250 0.842 0.000 0.896 0.040 0.000 0.000 0.064
#> GSM1182321 3 0.2985 0.748 0.000 0.056 0.844 0.000 0.000 0.100
#> GSM1182322 2 0.5488 0.575 0.000 0.556 0.272 0.000 0.000 0.172
#> GSM1182324 3 0.2740 0.773 0.000 0.076 0.864 0.000 0.000 0.060
#> GSM1182297 2 0.2416 0.848 0.000 0.844 0.000 0.000 0.000 0.156
#> GSM1182302 4 0.5899 0.463 0.000 0.000 0.000 0.472 0.252 0.276
#> GSM1182308 2 0.3354 0.793 0.000 0.796 0.168 0.000 0.000 0.036
#> GSM1182310 2 0.3020 0.823 0.000 0.844 0.076 0.000 0.000 0.080
#> GSM1182311 1 0.3841 0.829 0.716 0.000 0.000 0.000 0.028 0.256
#> GSM1182313 4 0.0000 0.816 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.1141 0.851 0.000 0.948 0.000 0.000 0.000 0.052
#> GSM1182317 2 0.2340 0.850 0.000 0.852 0.000 0.000 0.000 0.148
#> GSM1182323 1 0.4002 0.824 0.704 0.000 0.000 0.000 0.036 0.260
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:pam 139 0.077250 1.000 2
#> SD:pam 139 0.127535 0.921 3
#> SD:pam 136 0.000374 0.649 4
#> SD:pam 126 0.001431 0.685 5
#> SD:pam 127 0.000629 0.607 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.707 0.832 0.874 0.3258 0.823 0.661
#> 4 4 0.551 0.514 0.718 0.0905 0.944 0.843
#> 5 5 0.541 0.645 0.747 0.0609 0.915 0.744
#> 6 6 0.538 0.610 0.648 0.0387 0.932 0.766
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182187 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182188 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182189 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182190 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182191 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182192 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182193 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182194 2 0.1753 0.8192 0.000 0.952 0.048
#> GSM1182195 2 0.1643 0.8186 0.000 0.956 0.044
#> GSM1182196 2 0.5178 0.7204 0.000 0.744 0.256
#> GSM1182197 2 0.2625 0.8190 0.000 0.916 0.084
#> GSM1182198 2 0.2537 0.8092 0.000 0.920 0.080
#> GSM1182199 2 0.2711 0.8062 0.000 0.912 0.088
#> GSM1182200 2 0.2537 0.8221 0.000 0.920 0.080
#> GSM1182201 2 0.1753 0.8332 0.000 0.952 0.048
#> GSM1182202 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182203 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182204 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182205 2 0.3267 0.8216 0.000 0.884 0.116
#> GSM1182206 2 0.3686 0.7572 0.000 0.860 0.140
#> GSM1182207 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182208 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182209 3 0.6308 0.2226 0.000 0.492 0.508
#> GSM1182210 3 0.4750 0.8564 0.000 0.216 0.784
#> GSM1182211 3 0.4842 0.8569 0.000 0.224 0.776
#> GSM1182212 2 0.4750 0.6704 0.000 0.784 0.216
#> GSM1182213 3 0.4796 0.8572 0.000 0.220 0.780
#> GSM1182214 3 0.4796 0.8569 0.000 0.220 0.780
#> GSM1182215 2 0.3038 0.7971 0.000 0.896 0.104
#> GSM1182216 3 0.5621 0.8247 0.000 0.308 0.692
#> GSM1182217 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182218 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182219 3 0.4931 0.8564 0.000 0.232 0.768
#> GSM1182220 3 0.5016 0.8545 0.000 0.240 0.760
#> GSM1182221 3 0.5529 0.8317 0.000 0.296 0.704
#> GSM1182222 3 0.5621 0.8247 0.000 0.308 0.692
#> GSM1182223 2 0.0592 0.8368 0.000 0.988 0.012
#> GSM1182224 2 0.0237 0.8348 0.000 0.996 0.004
#> GSM1182225 3 0.5621 0.8247 0.000 0.308 0.692
#> GSM1182226 3 0.6180 0.6778 0.000 0.416 0.584
#> GSM1182227 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182228 2 0.3116 0.8109 0.000 0.892 0.108
#> GSM1182229 2 0.0747 0.8378 0.000 0.984 0.016
#> GSM1182230 2 0.3192 0.7861 0.000 0.888 0.112
#> GSM1182231 2 0.4062 0.7329 0.000 0.836 0.164
#> GSM1182232 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182233 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182234 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182235 3 0.3879 0.8276 0.000 0.152 0.848
#> GSM1182236 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182237 2 0.5016 0.7412 0.000 0.760 0.240
#> GSM1182238 3 0.5497 0.8336 0.000 0.292 0.708
#> GSM1182239 2 0.5529 0.6661 0.000 0.704 0.296
#> GSM1182240 2 0.6215 0.1563 0.000 0.572 0.428
#> GSM1182241 2 0.4399 0.7570 0.000 0.812 0.188
#> GSM1182242 2 0.2959 0.8142 0.000 0.900 0.100
#> GSM1182243 2 0.2711 0.8060 0.000 0.912 0.088
#> GSM1182244 2 0.3551 0.7971 0.000 0.868 0.132
#> GSM1182245 1 0.2625 0.9500 0.916 0.000 0.084
#> GSM1182246 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182247 2 0.0424 0.8359 0.000 0.992 0.008
#> GSM1182248 2 0.0424 0.8359 0.000 0.992 0.008
#> GSM1182249 2 0.3482 0.7864 0.000 0.872 0.128
#> GSM1182250 2 0.2165 0.8251 0.000 0.936 0.064
#> GSM1182251 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182252 2 0.0747 0.8368 0.000 0.984 0.016
#> GSM1182253 2 0.0000 0.8336 0.000 1.000 0.000
#> GSM1182254 2 0.0000 0.8336 0.000 1.000 0.000
#> GSM1182255 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182256 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182257 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182258 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182259 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182260 2 0.3116 0.8107 0.000 0.892 0.108
#> GSM1182261 2 0.3412 0.7743 0.000 0.876 0.124
#> GSM1182262 2 0.0000 0.8336 0.000 1.000 0.000
#> GSM1182263 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182264 2 0.3267 0.8047 0.000 0.884 0.116
#> GSM1182265 2 0.2878 0.8076 0.000 0.904 0.096
#> GSM1182266 2 0.3116 0.8107 0.000 0.892 0.108
#> GSM1182267 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182268 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182269 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182270 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182271 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182272 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182273 2 0.0237 0.8348 0.000 0.996 0.004
#> GSM1182275 2 0.0592 0.8365 0.000 0.988 0.012
#> GSM1182276 3 0.5650 0.7798 0.000 0.312 0.688
#> GSM1182277 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182278 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182279 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182280 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182281 1 0.0747 0.9771 0.984 0.000 0.016
#> GSM1182282 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182283 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182284 1 0.2796 0.9459 0.908 0.000 0.092
#> GSM1182285 2 0.0747 0.8368 0.000 0.984 0.016
#> GSM1182286 3 0.3752 0.8231 0.000 0.144 0.856
#> GSM1182287 2 0.3551 0.7236 0.000 0.868 0.132
#> GSM1182288 2 0.1163 0.8340 0.000 0.972 0.028
#> GSM1182289 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182290 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182291 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182274 2 0.0424 0.8359 0.000 0.992 0.008
#> GSM1182292 3 0.3752 0.8231 0.000 0.144 0.856
#> GSM1182293 3 0.4750 0.8564 0.000 0.216 0.784
#> GSM1182294 3 0.5968 0.7116 0.000 0.364 0.636
#> GSM1182295 3 0.4750 0.8564 0.000 0.216 0.784
#> GSM1182296 3 0.3752 0.8231 0.000 0.144 0.856
#> GSM1182298 2 0.3038 0.8001 0.000 0.896 0.104
#> GSM1182299 2 0.3551 0.7879 0.000 0.868 0.132
#> GSM1182300 3 0.5591 0.6830 0.000 0.304 0.696
#> GSM1182301 3 0.4555 0.8535 0.000 0.200 0.800
#> GSM1182303 3 0.6225 0.6259 0.000 0.432 0.568
#> GSM1182304 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182305 1 0.0747 0.9752 0.984 0.000 0.016
#> GSM1182306 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182307 3 0.3816 0.8237 0.000 0.148 0.852
#> GSM1182309 3 0.4702 0.8528 0.000 0.212 0.788
#> GSM1182312 3 0.5465 0.8361 0.000 0.288 0.712
#> GSM1182314 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182316 2 0.5431 0.4788 0.000 0.716 0.284
#> GSM1182318 2 0.6274 -0.1012 0.000 0.544 0.456
#> GSM1182319 2 0.5706 0.6283 0.000 0.680 0.320
#> GSM1182320 2 0.6244 -0.2200 0.000 0.560 0.440
#> GSM1182321 2 0.5016 0.7398 0.000 0.760 0.240
#> GSM1182322 3 0.6308 0.0255 0.000 0.492 0.508
#> GSM1182324 2 0.3482 0.7744 0.000 0.872 0.128
#> GSM1182297 3 0.3752 0.8231 0.000 0.144 0.856
#> GSM1182302 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182308 3 0.5465 0.8363 0.000 0.288 0.712
#> GSM1182310 2 0.5397 0.4993 0.000 0.720 0.280
#> GSM1182311 1 0.1031 0.9756 0.976 0.000 0.024
#> GSM1182313 1 0.0000 0.9788 1.000 0.000 0.000
#> GSM1182315 3 0.4796 0.8464 0.000 0.220 0.780
#> GSM1182317 3 0.6291 0.4072 0.000 0.468 0.532
#> GSM1182323 1 0.1031 0.9756 0.976 0.000 0.024
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.6814 0.5399 0.276 0.140 0.000 0.584
#> GSM1182187 1 0.4916 -0.0740 0.576 0.000 0.000 0.424
#> GSM1182188 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182189 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182190 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182191 4 0.6814 0.5399 0.276 0.140 0.000 0.584
#> GSM1182192 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182194 3 0.1489 0.8278 0.000 0.004 0.952 0.044
#> GSM1182195 3 0.0336 0.8271 0.000 0.000 0.992 0.008
#> GSM1182196 3 0.6231 0.5843 0.000 0.184 0.668 0.148
#> GSM1182197 3 0.2060 0.8252 0.000 0.016 0.932 0.052
#> GSM1182198 3 0.1940 0.8237 0.000 0.000 0.924 0.076
#> GSM1182199 3 0.2593 0.8110 0.000 0.004 0.892 0.104
#> GSM1182200 3 0.3552 0.7469 0.000 0.128 0.848 0.024
#> GSM1182201 3 0.1584 0.8297 0.000 0.012 0.952 0.036
#> GSM1182202 4 0.4643 0.7362 0.344 0.000 0.000 0.656
#> GSM1182203 1 0.4916 -0.0740 0.576 0.000 0.000 0.424
#> GSM1182204 4 0.4679 0.7192 0.352 0.000 0.000 0.648
#> GSM1182205 3 0.1970 0.8225 0.000 0.008 0.932 0.060
#> GSM1182206 3 0.4755 0.5555 0.000 0.200 0.760 0.040
#> GSM1182207 1 0.7206 -0.1468 0.460 0.140 0.000 0.400
#> GSM1182208 1 0.7206 -0.1468 0.460 0.140 0.000 0.400
#> GSM1182209 2 0.5453 0.8245 0.000 0.660 0.304 0.036
#> GSM1182210 2 0.4155 0.8744 0.000 0.756 0.240 0.004
#> GSM1182211 2 0.4295 0.8755 0.000 0.752 0.240 0.008
#> GSM1182212 3 0.4980 0.4684 0.000 0.304 0.680 0.016
#> GSM1182213 2 0.4436 0.8670 0.000 0.764 0.216 0.020
#> GSM1182214 2 0.4086 0.8669 0.000 0.776 0.216 0.008
#> GSM1182215 3 0.1488 0.8188 0.000 0.032 0.956 0.012
#> GSM1182216 2 0.5512 0.8409 0.000 0.660 0.300 0.040
#> GSM1182217 4 0.5289 0.7296 0.344 0.020 0.000 0.636
#> GSM1182218 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182219 2 0.4053 0.8692 0.000 0.768 0.228 0.004
#> GSM1182220 2 0.4188 0.8719 0.000 0.752 0.244 0.004
#> GSM1182221 2 0.5497 0.8509 0.000 0.672 0.284 0.044
#> GSM1182222 2 0.5790 0.8080 0.000 0.616 0.340 0.044
#> GSM1182223 3 0.0336 0.8281 0.000 0.008 0.992 0.000
#> GSM1182224 3 0.0188 0.8267 0.000 0.004 0.996 0.000
#> GSM1182225 2 0.5535 0.8388 0.000 0.656 0.304 0.040
#> GSM1182226 2 0.6060 0.6570 0.000 0.516 0.440 0.044
#> GSM1182227 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182228 3 0.3280 0.7945 0.000 0.016 0.860 0.124
#> GSM1182229 3 0.0188 0.8267 0.000 0.004 0.996 0.000
#> GSM1182230 3 0.1637 0.8053 0.000 0.060 0.940 0.000
#> GSM1182231 3 0.4857 0.3313 0.000 0.284 0.700 0.016
#> GSM1182232 1 0.3278 0.2331 0.864 0.020 0.000 0.116
#> GSM1182233 1 0.5173 0.0706 0.660 0.020 0.000 0.320
#> GSM1182234 1 0.0188 0.3406 0.996 0.000 0.000 0.004
#> GSM1182235 2 0.5184 0.8656 0.000 0.732 0.212 0.056
#> GSM1182236 1 0.5173 0.0706 0.660 0.020 0.000 0.320
#> GSM1182237 3 0.6308 0.5386 0.000 0.208 0.656 0.136
#> GSM1182238 2 0.5085 0.8650 0.000 0.708 0.260 0.032
#> GSM1182239 3 0.7077 0.1292 0.000 0.316 0.536 0.148
#> GSM1182240 2 0.6446 0.7957 0.000 0.584 0.328 0.088
#> GSM1182241 3 0.4841 0.7353 0.000 0.080 0.780 0.140
#> GSM1182242 3 0.3161 0.7964 0.000 0.012 0.864 0.124
#> GSM1182243 3 0.1389 0.8135 0.000 0.048 0.952 0.000
#> GSM1182244 3 0.2928 0.8022 0.000 0.012 0.880 0.108
#> GSM1182245 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182246 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182247 3 0.1356 0.8290 0.000 0.008 0.960 0.032
#> GSM1182248 3 0.0188 0.8267 0.000 0.004 0.996 0.000
#> GSM1182249 3 0.2760 0.7281 0.000 0.128 0.872 0.000
#> GSM1182250 3 0.0000 0.8273 0.000 0.000 1.000 0.000
#> GSM1182251 1 0.7221 -0.2130 0.432 0.140 0.000 0.428
#> GSM1182252 3 0.1452 0.8285 0.000 0.008 0.956 0.036
#> GSM1182253 3 0.0000 0.8273 0.000 0.000 1.000 0.000
#> GSM1182254 3 0.0000 0.8273 0.000 0.000 1.000 0.000
#> GSM1182255 1 0.6337 0.0478 0.552 0.068 0.000 0.380
#> GSM1182256 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182257 1 0.4916 -0.0740 0.576 0.000 0.000 0.424
#> GSM1182258 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182259 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182260 3 0.3161 0.7937 0.000 0.012 0.864 0.124
#> GSM1182261 3 0.3176 0.7632 0.000 0.084 0.880 0.036
#> GSM1182262 3 0.0376 0.8263 0.000 0.004 0.992 0.004
#> GSM1182263 1 0.6386 -0.0128 0.648 0.140 0.000 0.212
#> GSM1182264 3 0.3161 0.7937 0.000 0.012 0.864 0.124
#> GSM1182265 3 0.1389 0.8124 0.000 0.048 0.952 0.000
#> GSM1182266 3 0.3161 0.7937 0.000 0.012 0.864 0.124
#> GSM1182267 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182268 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182269 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182270 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182271 1 0.6337 0.0478 0.552 0.068 0.000 0.380
#> GSM1182272 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182273 3 0.0000 0.8273 0.000 0.000 1.000 0.000
#> GSM1182275 3 0.1256 0.8308 0.000 0.008 0.964 0.028
#> GSM1182276 2 0.4776 0.8548 0.000 0.712 0.272 0.016
#> GSM1182277 1 0.0188 0.3406 0.996 0.000 0.000 0.004
#> GSM1182278 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182279 1 0.7220 -0.1924 0.440 0.140 0.000 0.420
#> GSM1182280 1 0.7206 -0.1468 0.460 0.140 0.000 0.400
#> GSM1182281 1 0.0469 0.3362 0.988 0.000 0.000 0.012
#> GSM1182282 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.3424 1.000 0.000 0.000 0.000
#> GSM1182285 3 0.1452 0.8285 0.000 0.008 0.956 0.036
#> GSM1182286 2 0.5221 0.8614 0.000 0.732 0.208 0.060
#> GSM1182287 3 0.2480 0.7750 0.000 0.088 0.904 0.008
#> GSM1182288 3 0.1109 0.8306 0.000 0.004 0.968 0.028
#> GSM1182289 1 0.7220 -0.1924 0.440 0.140 0.000 0.420
#> GSM1182290 1 0.7206 -0.1468 0.460 0.140 0.000 0.400
#> GSM1182291 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182274 3 0.0000 0.8273 0.000 0.000 1.000 0.000
#> GSM1182292 2 0.5599 0.8605 0.000 0.700 0.228 0.072
#> GSM1182293 2 0.4155 0.8752 0.000 0.756 0.240 0.004
#> GSM1182294 2 0.5024 0.7703 0.000 0.632 0.360 0.008
#> GSM1182295 2 0.4018 0.8691 0.000 0.772 0.224 0.004
#> GSM1182296 2 0.5221 0.8614 0.000 0.732 0.208 0.060
#> GSM1182298 3 0.2888 0.8007 0.000 0.004 0.872 0.124
#> GSM1182299 3 0.4361 0.6651 0.000 0.208 0.772 0.020
#> GSM1182300 2 0.6980 0.6826 0.000 0.536 0.332 0.132
#> GSM1182301 2 0.4671 0.8701 0.000 0.752 0.220 0.028
#> GSM1182303 2 0.5650 0.6427 0.000 0.544 0.432 0.024
#> GSM1182304 1 0.7206 -0.1468 0.460 0.140 0.000 0.400
#> GSM1182305 1 0.7179 -0.3285 0.480 0.140 0.000 0.380
#> GSM1182306 1 0.4907 -0.0649 0.580 0.000 0.000 0.420
#> GSM1182307 2 0.5394 0.8623 0.000 0.712 0.228 0.060
#> GSM1182309 2 0.5546 0.8540 0.000 0.680 0.268 0.052
#> GSM1182312 2 0.5343 0.8447 0.000 0.656 0.316 0.028
#> GSM1182314 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182316 3 0.5888 -0.3314 0.000 0.424 0.540 0.036
#> GSM1182318 2 0.5250 0.8161 0.000 0.660 0.316 0.024
#> GSM1182319 3 0.6993 0.2145 0.000 0.296 0.556 0.148
#> GSM1182320 2 0.5987 0.6353 0.000 0.520 0.440 0.040
#> GSM1182321 3 0.6341 0.5232 0.000 0.212 0.652 0.136
#> GSM1182322 2 0.6840 0.4703 0.000 0.468 0.432 0.100
#> GSM1182324 3 0.3852 0.6317 0.000 0.180 0.808 0.012
#> GSM1182297 2 0.5257 0.8624 0.000 0.728 0.212 0.060
#> GSM1182302 4 0.4643 0.7362 0.344 0.000 0.000 0.656
#> GSM1182308 2 0.5195 0.8643 0.000 0.692 0.276 0.032
#> GSM1182310 3 0.5420 0.0474 0.000 0.352 0.624 0.024
#> GSM1182311 1 0.5193 0.0706 0.656 0.020 0.000 0.324
#> GSM1182313 1 0.6347 0.0491 0.548 0.068 0.000 0.384
#> GSM1182315 2 0.5386 0.8710 0.000 0.708 0.236 0.056
#> GSM1182317 2 0.4770 0.8470 0.000 0.700 0.288 0.012
#> GSM1182323 1 0.5193 0.0706 0.656 0.020 0.000 0.324
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.6098 0.1524 0.568 0.000 0.000 0.236 NA
#> GSM1182187 4 0.5302 0.5684 0.344 0.000 0.000 0.592 NA
#> GSM1182188 4 0.1671 0.7677 0.076 0.000 0.000 0.924 NA
#> GSM1182189 1 0.0404 0.6061 0.988 0.000 0.000 0.012 NA
#> GSM1182190 1 0.0404 0.6061 0.988 0.000 0.000 0.012 NA
#> GSM1182191 1 0.6080 0.2260 0.568 0.000 0.000 0.184 NA
#> GSM1182192 1 0.6579 0.4446 0.580 0.000 0.032 0.220 NA
#> GSM1182193 1 0.6800 0.4131 0.540 0.000 0.032 0.256 NA
#> GSM1182194 3 0.5322 0.7724 0.000 0.140 0.672 0.000 NA
#> GSM1182195 3 0.5043 0.7635 0.000 0.136 0.704 0.000 NA
#> GSM1182196 3 0.6292 0.6636 0.000 0.268 0.560 0.008 NA
#> GSM1182197 3 0.5379 0.7901 0.000 0.168 0.668 0.000 NA
#> GSM1182198 3 0.5414 0.7563 0.000 0.140 0.660 0.000 NA
#> GSM1182199 3 0.5668 0.7491 0.000 0.144 0.624 0.000 NA
#> GSM1182200 3 0.6227 0.6234 0.000 0.296 0.568 0.016 NA
#> GSM1182201 3 0.4732 0.8218 0.000 0.144 0.744 0.004 NA
#> GSM1182202 4 0.5488 0.4416 0.428 0.000 0.000 0.508 NA
#> GSM1182203 4 0.5289 0.5725 0.340 0.000 0.000 0.596 NA
#> GSM1182204 4 0.5483 0.4458 0.424 0.000 0.000 0.512 NA
#> GSM1182205 3 0.4151 0.8345 0.000 0.156 0.788 0.012 NA
#> GSM1182206 3 0.5356 0.7439 0.000 0.252 0.672 0.044 NA
#> GSM1182207 1 0.3074 0.5369 0.804 0.000 0.000 0.000 NA
#> GSM1182208 1 0.3074 0.5369 0.804 0.000 0.000 0.000 NA
#> GSM1182209 2 0.3617 0.7515 0.000 0.824 0.128 0.004 NA
#> GSM1182210 2 0.0833 0.8188 0.000 0.976 0.016 0.004 NA
#> GSM1182211 2 0.0740 0.8202 0.000 0.980 0.008 0.004 NA
#> GSM1182212 2 0.6155 -0.2163 0.000 0.488 0.400 0.008 NA
#> GSM1182213 2 0.1329 0.8192 0.000 0.956 0.008 0.004 NA
#> GSM1182214 2 0.0486 0.8175 0.000 0.988 0.004 0.004 NA
#> GSM1182215 3 0.3684 0.8185 0.000 0.192 0.788 0.004 NA
#> GSM1182216 2 0.3795 0.7955 0.000 0.840 0.064 0.060 NA
#> GSM1182217 1 0.5423 -0.1747 0.548 0.000 0.000 0.388 NA
#> GSM1182218 1 0.0404 0.6061 0.988 0.000 0.000 0.012 NA
#> GSM1182219 2 0.1471 0.8210 0.000 0.952 0.020 0.004 NA
#> GSM1182220 2 0.1865 0.8216 0.000 0.936 0.024 0.008 NA
#> GSM1182221 2 0.3432 0.8019 0.000 0.860 0.052 0.060 NA
#> GSM1182222 2 0.4204 0.7751 0.000 0.808 0.104 0.060 NA
#> GSM1182223 3 0.3734 0.8289 0.000 0.168 0.796 0.000 NA
#> GSM1182224 3 0.4781 0.7957 0.000 0.160 0.728 0.000 NA
#> GSM1182225 2 0.3849 0.7909 0.000 0.832 0.084 0.060 NA
#> GSM1182226 2 0.5371 0.5300 0.000 0.656 0.268 0.060 NA
#> GSM1182227 1 0.6800 0.4149 0.540 0.000 0.032 0.256 NA
#> GSM1182228 3 0.5478 0.7951 0.000 0.164 0.656 0.000 NA
#> GSM1182229 3 0.3304 0.8258 0.000 0.168 0.816 0.000 NA
#> GSM1182230 3 0.3527 0.8217 0.000 0.192 0.792 0.000 NA
#> GSM1182231 3 0.4970 0.4971 0.000 0.392 0.580 0.008 NA
#> GSM1182232 1 0.2519 0.5620 0.884 0.000 0.000 0.100 NA
#> GSM1182233 1 0.0404 0.6063 0.988 0.000 0.000 0.012 NA
#> GSM1182234 1 0.6649 0.4372 0.568 0.000 0.032 0.232 NA
#> GSM1182235 2 0.2136 0.8143 0.000 0.904 0.000 0.008 NA
#> GSM1182236 1 0.0290 0.6065 0.992 0.000 0.000 0.008 NA
#> GSM1182237 3 0.6547 0.6086 0.000 0.308 0.516 0.012 NA
#> GSM1182238 2 0.2747 0.8139 0.000 0.896 0.048 0.036 NA
#> GSM1182239 2 0.6916 -0.0235 0.000 0.440 0.328 0.012 NA
#> GSM1182240 2 0.5457 0.5942 0.000 0.680 0.228 0.032 NA
#> GSM1182241 3 0.6343 0.7068 0.000 0.176 0.572 0.012 NA
#> GSM1182242 3 0.5446 0.7985 0.000 0.164 0.660 0.000 NA
#> GSM1182243 3 0.3304 0.8250 0.000 0.168 0.816 0.000 NA
#> GSM1182244 3 0.5048 0.8081 0.000 0.152 0.704 0.000 NA
#> GSM1182245 1 0.6790 0.4113 0.540 0.000 0.032 0.260 NA
#> GSM1182246 4 0.1792 0.7689 0.084 0.000 0.000 0.916 NA
#> GSM1182247 3 0.4138 0.8300 0.000 0.160 0.776 0.000 NA
#> GSM1182248 3 0.3691 0.8283 0.000 0.156 0.804 0.000 NA
#> GSM1182249 3 0.3807 0.7790 0.000 0.240 0.748 0.000 NA
#> GSM1182250 3 0.3011 0.8275 0.000 0.140 0.844 0.000 NA
#> GSM1182251 1 0.4763 0.4229 0.632 0.000 0.000 0.032 NA
#> GSM1182252 3 0.4317 0.8295 0.000 0.160 0.764 0.000 NA
#> GSM1182253 3 0.2843 0.8287 0.000 0.144 0.848 0.000 NA
#> GSM1182254 3 0.3506 0.8292 0.000 0.132 0.824 0.000 NA
#> GSM1182255 4 0.1965 0.7631 0.096 0.000 0.000 0.904 NA
#> GSM1182256 4 0.1671 0.7677 0.076 0.000 0.000 0.924 NA
#> GSM1182257 4 0.5302 0.5684 0.344 0.000 0.000 0.592 NA
#> GSM1182258 4 0.1792 0.7689 0.084 0.000 0.000 0.916 NA
#> GSM1182259 4 0.1732 0.7672 0.080 0.000 0.000 0.920 NA
#> GSM1182260 3 0.5155 0.7921 0.000 0.140 0.692 0.000 NA
#> GSM1182261 3 0.4495 0.8101 0.000 0.196 0.752 0.028 NA
#> GSM1182262 3 0.3360 0.8239 0.000 0.168 0.816 0.004 NA
#> GSM1182263 1 0.5580 0.4269 0.576 0.000 0.000 0.088 NA
#> GSM1182264 3 0.5190 0.7920 0.000 0.140 0.688 0.000 NA
#> GSM1182265 3 0.3081 0.8289 0.000 0.156 0.832 0.000 NA
#> GSM1182266 3 0.5224 0.7910 0.000 0.140 0.684 0.000 NA
#> GSM1182267 1 0.6555 0.4471 0.584 0.000 0.032 0.216 NA
#> GSM1182268 1 0.0290 0.6065 0.992 0.000 0.000 0.008 NA
#> GSM1182269 1 0.0404 0.6061 0.988 0.000 0.000 0.012 NA
#> GSM1182270 1 0.0510 0.6057 0.984 0.000 0.000 0.016 NA
#> GSM1182271 4 0.2732 0.7272 0.160 0.000 0.000 0.840 NA
#> GSM1182272 4 0.1732 0.7672 0.080 0.000 0.000 0.920 NA
#> GSM1182273 3 0.2920 0.8285 0.000 0.132 0.852 0.000 NA
#> GSM1182275 3 0.3595 0.8296 0.000 0.140 0.816 0.000 NA
#> GSM1182276 2 0.1743 0.8189 0.000 0.940 0.028 0.004 NA
#> GSM1182277 1 0.6579 0.4446 0.580 0.000 0.032 0.220 NA
#> GSM1182278 1 0.6752 0.4196 0.548 0.000 0.032 0.252 NA
#> GSM1182279 1 0.4836 0.4193 0.628 0.000 0.000 0.036 NA
#> GSM1182280 1 0.4118 0.4558 0.660 0.000 0.000 0.004 NA
#> GSM1182281 1 0.7405 0.3032 0.396 0.000 0.032 0.268 NA
#> GSM1182282 1 0.6800 0.4150 0.540 0.000 0.032 0.256 NA
#> GSM1182283 1 0.6772 0.4161 0.544 0.000 0.032 0.256 NA
#> GSM1182284 1 0.6808 0.4084 0.536 0.000 0.032 0.264 NA
#> GSM1182285 3 0.5237 0.7940 0.000 0.160 0.684 0.000 NA
#> GSM1182286 2 0.2304 0.8111 0.000 0.892 0.000 0.008 NA
#> GSM1182287 3 0.4052 0.8141 0.000 0.204 0.764 0.004 NA
#> GSM1182288 3 0.3810 0.8320 0.000 0.168 0.792 0.000 NA
#> GSM1182289 1 0.4836 0.4224 0.628 0.000 0.000 0.036 NA
#> GSM1182290 1 0.3074 0.5369 0.804 0.000 0.000 0.000 NA
#> GSM1182291 4 0.1732 0.7672 0.080 0.000 0.000 0.920 NA
#> GSM1182274 3 0.3400 0.8297 0.000 0.136 0.828 0.000 NA
#> GSM1182292 2 0.3056 0.8056 0.000 0.860 0.020 0.008 NA
#> GSM1182293 2 0.1173 0.8226 0.000 0.964 0.012 0.004 NA
#> GSM1182294 2 0.3732 0.6242 0.000 0.776 0.208 0.008 NA
#> GSM1182295 2 0.0324 0.8172 0.000 0.992 0.004 0.004 NA
#> GSM1182296 2 0.2136 0.8116 0.000 0.904 0.000 0.008 NA
#> GSM1182298 3 0.5806 0.7363 0.000 0.144 0.600 0.000 NA
#> GSM1182299 3 0.6147 0.5967 0.000 0.328 0.536 0.004 NA
#> GSM1182300 2 0.5967 0.5035 0.000 0.628 0.200 0.012 NA
#> GSM1182301 2 0.1978 0.8194 0.000 0.928 0.024 0.004 NA
#> GSM1182303 2 0.3839 0.7849 0.000 0.828 0.092 0.016 NA
#> GSM1182304 1 0.4524 0.4478 0.644 0.000 0.000 0.020 NA
#> GSM1182305 1 0.6767 0.0211 0.388 0.000 0.000 0.336 NA
#> GSM1182306 4 0.5302 0.5684 0.344 0.000 0.000 0.592 NA
#> GSM1182307 2 0.2354 0.8121 0.000 0.904 0.012 0.008 NA
#> GSM1182309 2 0.3248 0.8005 0.000 0.856 0.052 0.004 NA
#> GSM1182312 2 0.3216 0.8092 0.000 0.868 0.068 0.048 NA
#> GSM1182314 4 0.1792 0.7689 0.084 0.000 0.000 0.916 NA
#> GSM1182316 3 0.5843 0.3592 0.000 0.420 0.508 0.052 NA
#> GSM1182318 2 0.4359 0.6694 0.000 0.756 0.188 0.004 NA
#> GSM1182319 3 0.6657 0.4638 0.000 0.352 0.472 0.012 NA
#> GSM1182320 2 0.5579 0.5106 0.000 0.640 0.280 0.048 NA
#> GSM1182321 3 0.6178 0.6341 0.000 0.296 0.536 0.000 NA
#> GSM1182322 2 0.6658 -0.1611 0.000 0.452 0.388 0.016 NA
#> GSM1182324 3 0.4161 0.7246 0.000 0.280 0.704 0.000 NA
#> GSM1182297 2 0.2295 0.8131 0.000 0.900 0.004 0.008 NA
#> GSM1182302 4 0.5492 0.4363 0.432 0.000 0.000 0.504 NA
#> GSM1182308 2 0.3170 0.8133 0.000 0.876 0.048 0.036 NA
#> GSM1182310 3 0.5140 0.3316 0.000 0.444 0.524 0.008 NA
#> GSM1182311 1 0.0404 0.6056 0.988 0.000 0.000 0.012 NA
#> GSM1182313 4 0.1671 0.7677 0.076 0.000 0.000 0.924 NA
#> GSM1182315 2 0.2532 0.8227 0.000 0.908 0.028 0.028 NA
#> GSM1182317 2 0.3566 0.7146 0.000 0.812 0.160 0.004 NA
#> GSM1182323 1 0.0290 0.6065 0.992 0.000 0.000 0.008 NA
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.3547 0.213 0.004 0.000 0.000 0.300 0.696 NA
#> GSM1182187 4 0.4945 0.617 0.004 0.008 0.000 0.632 0.292 NA
#> GSM1182188 4 0.0363 0.755 0.000 0.000 0.000 0.988 0.012 NA
#> GSM1182189 5 0.6045 0.541 0.224 0.012 0.000 0.004 0.532 NA
#> GSM1182190 5 0.6045 0.540 0.228 0.012 0.000 0.004 0.532 NA
#> GSM1182191 5 0.3383 0.274 0.004 0.000 0.000 0.268 0.728 NA
#> GSM1182192 1 0.5408 0.841 0.552 0.000 0.000 0.144 0.304 NA
#> GSM1182193 1 0.5461 0.882 0.572 0.000 0.000 0.200 0.228 NA
#> GSM1182194 3 0.4559 0.580 0.020 0.012 0.620 0.004 0.000 NA
#> GSM1182195 3 0.5008 0.570 0.072 0.012 0.648 0.004 0.000 NA
#> GSM1182196 3 0.5879 0.381 0.044 0.172 0.604 0.000 0.000 NA
#> GSM1182197 3 0.4990 0.597 0.084 0.056 0.712 0.000 0.000 NA
#> GSM1182198 3 0.5114 0.561 0.076 0.012 0.632 0.004 0.000 NA
#> GSM1182199 3 0.5307 0.552 0.080 0.012 0.592 0.004 0.000 NA
#> GSM1182200 3 0.6180 0.406 0.164 0.172 0.588 0.000 0.000 NA
#> GSM1182201 3 0.3975 0.639 0.044 0.036 0.788 0.000 0.000 NA
#> GSM1182202 4 0.5145 0.559 0.004 0.008 0.000 0.588 0.332 NA
#> GSM1182203 4 0.4772 0.649 0.004 0.008 0.000 0.668 0.256 NA
#> GSM1182204 4 0.5011 0.591 0.004 0.008 0.000 0.616 0.308 NA
#> GSM1182205 3 0.4025 0.645 0.048 0.000 0.720 0.000 0.000 NA
#> GSM1182206 3 0.6154 0.509 0.088 0.100 0.576 0.000 0.000 NA
#> GSM1182207 5 0.2378 0.551 0.152 0.000 0.000 0.000 0.848 NA
#> GSM1182208 5 0.2378 0.551 0.152 0.000 0.000 0.000 0.848 NA
#> GSM1182209 2 0.5057 0.646 0.040 0.592 0.340 0.000 0.000 NA
#> GSM1182210 2 0.2783 0.794 0.016 0.836 0.148 0.000 0.000 NA
#> GSM1182211 2 0.3784 0.797 0.024 0.736 0.236 0.000 0.000 NA
#> GSM1182212 3 0.6353 -0.191 0.136 0.384 0.436 0.000 0.000 NA
#> GSM1182213 2 0.4354 0.793 0.052 0.704 0.236 0.000 0.000 NA
#> GSM1182214 2 0.3221 0.801 0.004 0.772 0.220 0.000 0.000 NA
#> GSM1182215 3 0.4661 0.594 0.028 0.048 0.696 0.000 0.000 NA
#> GSM1182216 2 0.5203 0.770 0.140 0.656 0.188 0.000 0.000 NA
#> GSM1182217 4 0.5490 0.318 0.004 0.008 0.000 0.488 0.416 NA
#> GSM1182218 5 0.6045 0.540 0.228 0.012 0.000 0.004 0.532 NA
#> GSM1182219 2 0.3425 0.798 0.028 0.800 0.164 0.000 0.000 NA
#> GSM1182220 2 0.4044 0.803 0.060 0.756 0.176 0.000 0.000 NA
#> GSM1182221 2 0.5232 0.773 0.132 0.664 0.180 0.000 0.000 NA
#> GSM1182222 2 0.5444 0.743 0.120 0.604 0.260 0.000 0.000 NA
#> GSM1182223 3 0.3509 0.655 0.028 0.040 0.824 0.000 0.000 NA
#> GSM1182224 3 0.4172 0.621 0.016 0.012 0.672 0.000 0.000 NA
#> GSM1182225 2 0.5284 0.763 0.140 0.644 0.200 0.000 0.000 NA
#> GSM1182226 2 0.5518 0.705 0.116 0.564 0.308 0.000 0.000 NA
#> GSM1182227 1 0.5501 0.891 0.564 0.000 0.000 0.200 0.236 NA
#> GSM1182228 3 0.4310 0.637 0.024 0.028 0.712 0.000 0.000 NA
#> GSM1182229 3 0.2868 0.655 0.000 0.028 0.840 0.000 0.000 NA
#> GSM1182230 3 0.4133 0.612 0.020 0.024 0.724 0.000 0.000 NA
#> GSM1182231 3 0.5637 0.459 0.032 0.172 0.624 0.000 0.000 NA
#> GSM1182232 5 0.6715 0.421 0.248 0.012 0.000 0.040 0.492 NA
#> GSM1182233 5 0.5913 0.543 0.228 0.012 0.000 0.000 0.536 NA
#> GSM1182234 1 0.5408 0.840 0.552 0.000 0.000 0.144 0.304 NA
#> GSM1182235 2 0.4764 0.794 0.044 0.732 0.156 0.004 0.000 NA
#> GSM1182236 5 0.5913 0.543 0.228 0.012 0.000 0.000 0.536 NA
#> GSM1182237 3 0.6203 0.491 0.056 0.088 0.500 0.004 0.000 NA
#> GSM1182238 2 0.3964 0.801 0.048 0.764 0.176 0.000 0.000 NA
#> GSM1182239 3 0.6904 0.193 0.136 0.196 0.516 0.004 0.000 NA
#> GSM1182240 2 0.6061 0.575 0.104 0.472 0.384 0.000 0.000 NA
#> GSM1182241 3 0.5959 0.498 0.108 0.072 0.620 0.004 0.000 NA
#> GSM1182242 3 0.4161 0.636 0.004 0.012 0.608 0.000 0.000 NA
#> GSM1182243 3 0.3622 0.640 0.020 0.024 0.792 0.000 0.000 NA
#> GSM1182244 3 0.4507 0.631 0.020 0.012 0.596 0.000 0.000 NA
#> GSM1182245 1 0.5643 0.877 0.536 0.000 0.000 0.216 0.248 NA
#> GSM1182246 4 0.1418 0.754 0.024 0.000 0.000 0.944 0.032 NA
#> GSM1182247 3 0.3790 0.653 0.004 0.016 0.716 0.000 0.000 NA
#> GSM1182248 3 0.3198 0.644 0.000 0.000 0.740 0.000 0.000 NA
#> GSM1182249 3 0.4111 0.563 0.024 0.112 0.780 0.000 0.000 NA
#> GSM1182250 3 0.2492 0.659 0.020 0.004 0.876 0.000 0.000 NA
#> GSM1182251 5 0.1075 0.531 0.000 0.000 0.000 0.048 0.952 NA
#> GSM1182252 3 0.3684 0.643 0.004 0.004 0.692 0.000 0.000 NA
#> GSM1182253 3 0.2838 0.660 0.000 0.004 0.808 0.000 0.000 NA
#> GSM1182254 3 0.3373 0.654 0.012 0.032 0.816 0.000 0.000 NA
#> GSM1182255 4 0.1003 0.757 0.004 0.000 0.000 0.964 0.028 NA
#> GSM1182256 4 0.0458 0.757 0.000 0.000 0.000 0.984 0.016 NA
#> GSM1182257 4 0.4758 0.620 0.000 0.008 0.000 0.640 0.292 NA
#> GSM1182258 4 0.1168 0.754 0.016 0.000 0.000 0.956 0.028 NA
#> GSM1182259 4 0.0363 0.755 0.000 0.000 0.000 0.988 0.012 NA
#> GSM1182260 3 0.4260 0.618 0.016 0.024 0.692 0.000 0.000 NA
#> GSM1182261 3 0.5568 0.566 0.060 0.076 0.628 0.000 0.000 NA
#> GSM1182262 3 0.3942 0.626 0.020 0.024 0.752 0.000 0.000 NA
#> GSM1182263 5 0.1007 0.506 0.000 0.000 0.000 0.044 0.956 NA
#> GSM1182264 3 0.3790 0.625 0.016 0.004 0.716 0.000 0.000 NA
#> GSM1182265 3 0.3344 0.656 0.020 0.032 0.828 0.000 0.000 NA
#> GSM1182266 3 0.3767 0.623 0.016 0.004 0.720 0.000 0.000 NA
#> GSM1182267 1 0.5373 0.828 0.552 0.000 0.000 0.136 0.312 NA
#> GSM1182268 5 0.5913 0.543 0.228 0.012 0.000 0.000 0.536 NA
#> GSM1182269 5 0.6045 0.540 0.228 0.012 0.000 0.004 0.532 NA
#> GSM1182270 5 0.6045 0.543 0.228 0.012 0.000 0.004 0.532 NA
#> GSM1182271 4 0.2257 0.735 0.000 0.008 0.000 0.876 0.116 NA
#> GSM1182272 4 0.0363 0.755 0.000 0.000 0.000 0.988 0.012 NA
#> GSM1182273 3 0.2378 0.655 0.000 0.000 0.848 0.000 0.000 NA
#> GSM1182275 3 0.2573 0.666 0.012 0.012 0.872 0.000 0.000 NA
#> GSM1182276 2 0.5250 0.719 0.116 0.612 0.264 0.000 0.000 NA
#> GSM1182277 1 0.5391 0.832 0.552 0.000 0.000 0.140 0.308 NA
#> GSM1182278 1 0.5543 0.892 0.556 0.000 0.000 0.204 0.240 NA
#> GSM1182279 5 0.0547 0.544 0.000 0.000 0.000 0.020 0.980 NA
#> GSM1182280 5 0.0146 0.546 0.000 0.000 0.000 0.004 0.996 NA
#> GSM1182281 1 0.5958 0.611 0.392 0.000 0.000 0.220 0.388 NA
#> GSM1182282 1 0.5480 0.889 0.564 0.000 0.000 0.184 0.252 NA
#> GSM1182283 1 0.5546 0.889 0.556 0.000 0.000 0.208 0.236 NA
#> GSM1182284 1 0.5551 0.882 0.556 0.000 0.000 0.220 0.224 NA
#> GSM1182285 3 0.4497 0.602 0.020 0.012 0.600 0.000 0.000 NA
#> GSM1182286 2 0.4754 0.793 0.040 0.732 0.156 0.004 0.000 NA
#> GSM1182287 3 0.4104 0.614 0.048 0.108 0.788 0.000 0.000 NA
#> GSM1182288 3 0.3354 0.654 0.004 0.004 0.752 0.000 0.000 NA
#> GSM1182289 5 0.0632 0.541 0.000 0.000 0.000 0.024 0.976 NA
#> GSM1182290 5 0.2520 0.550 0.152 0.000 0.000 0.004 0.844 NA
#> GSM1182291 4 0.0363 0.755 0.000 0.000 0.000 0.988 0.012 NA
#> GSM1182274 3 0.3299 0.655 0.012 0.028 0.820 0.000 0.000 NA
#> GSM1182292 2 0.5860 0.739 0.060 0.592 0.268 0.004 0.000 NA
#> GSM1182293 2 0.3799 0.808 0.024 0.764 0.196 0.000 0.000 NA
#> GSM1182294 2 0.5583 0.620 0.024 0.580 0.292 0.000 0.000 NA
#> GSM1182295 2 0.2814 0.804 0.008 0.820 0.172 0.000 0.000 NA
#> GSM1182296 2 0.5009 0.796 0.040 0.700 0.188 0.004 0.000 NA
#> GSM1182298 3 0.5374 0.544 0.080 0.012 0.572 0.004 0.000 NA
#> GSM1182299 3 0.6241 0.348 0.116 0.216 0.576 0.000 0.000 NA
#> GSM1182300 2 0.6643 0.456 0.056 0.424 0.376 0.004 0.000 NA
#> GSM1182301 2 0.4584 0.790 0.040 0.688 0.248 0.000 0.000 NA
#> GSM1182303 2 0.5838 0.673 0.152 0.568 0.256 0.000 0.000 NA
#> GSM1182304 5 0.0146 0.546 0.000 0.000 0.000 0.004 0.996 NA
#> GSM1182305 5 0.3728 0.139 0.004 0.000 0.000 0.344 0.652 NA
#> GSM1182306 4 0.4758 0.620 0.000 0.008 0.000 0.640 0.292 NA
#> GSM1182307 2 0.4952 0.784 0.024 0.684 0.220 0.004 0.000 NA
#> GSM1182309 2 0.5398 0.704 0.020 0.600 0.284 0.000 0.000 NA
#> GSM1182312 2 0.5011 0.762 0.084 0.672 0.220 0.000 0.000 NA
#> GSM1182314 4 0.1245 0.755 0.016 0.000 0.000 0.952 0.032 NA
#> GSM1182316 3 0.5901 -0.140 0.108 0.340 0.520 0.000 0.000 NA
#> GSM1182318 2 0.5126 0.581 0.052 0.544 0.388 0.000 0.000 NA
#> GSM1182319 3 0.6255 0.125 0.036 0.264 0.536 0.004 0.000 NA
#> GSM1182320 3 0.6005 -0.433 0.108 0.416 0.444 0.000 0.000 NA
#> GSM1182321 3 0.5760 0.392 0.020 0.180 0.584 0.000 0.000 NA
#> GSM1182322 3 0.6278 -0.108 0.044 0.328 0.504 0.004 0.000 NA
#> GSM1182324 3 0.4355 0.474 0.012 0.176 0.736 0.000 0.000 NA
#> GSM1182297 2 0.4782 0.796 0.048 0.728 0.164 0.004 0.000 NA
#> GSM1182302 4 0.5090 0.584 0.004 0.008 0.000 0.604 0.316 NA
#> GSM1182308 2 0.4681 0.799 0.088 0.708 0.188 0.000 0.000 NA
#> GSM1182310 3 0.4601 0.182 0.020 0.308 0.644 0.000 0.000 NA
#> GSM1182311 5 0.6045 0.543 0.228 0.012 0.000 0.004 0.532 NA
#> GSM1182313 4 0.0622 0.756 0.008 0.000 0.000 0.980 0.012 NA
#> GSM1182315 2 0.4647 0.810 0.056 0.724 0.180 0.000 0.000 NA
#> GSM1182317 2 0.4651 0.615 0.012 0.588 0.372 0.000 0.000 NA
#> GSM1182323 5 0.5913 0.543 0.228 0.012 0.000 0.000 0.536 NA
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:mclust 139 7.73e-02 1.000 2
#> SD:mclust 131 1.42e-04 0.298 3
#> SD:mclust 84 2.13e-04 0.175 4
#> SD:mclust 107 3.22e-04 0.311 5
#> SD:mclust 118 4.82e-05 0.423 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.784 0.842 0.867 0.1113 0.991 0.983
#> 4 4 0.582 0.464 0.806 0.1638 0.994 0.989
#> 5 5 0.531 0.603 0.768 0.1029 0.812 0.631
#> 6 6 0.511 0.560 0.723 0.0668 0.878 0.651
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182187 1 0.2625 0.942 0.916 0.000 0.084
#> GSM1182188 1 0.0424 0.935 0.992 0.000 0.008
#> GSM1182189 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182190 1 0.3482 0.939 0.872 0.000 0.128
#> GSM1182191 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182192 1 0.1411 0.940 0.964 0.000 0.036
#> GSM1182193 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182194 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182195 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182196 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182197 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182198 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182199 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182200 2 0.4121 0.566 0.000 0.832 0.168
#> GSM1182201 2 0.1031 0.848 0.000 0.976 0.024
#> GSM1182202 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182203 1 0.2878 0.942 0.904 0.000 0.096
#> GSM1182204 1 0.2878 0.942 0.904 0.000 0.096
#> GSM1182205 2 0.2711 0.840 0.000 0.912 0.088
#> GSM1182206 2 0.2796 0.838 0.000 0.908 0.092
#> GSM1182207 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182208 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182209 3 0.6307 0.000 0.000 0.488 0.512
#> GSM1182210 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182211 2 0.4235 0.538 0.000 0.824 0.176
#> GSM1182212 2 0.5760 -0.336 0.000 0.672 0.328
#> GSM1182213 2 0.4002 0.589 0.000 0.840 0.160
#> GSM1182214 2 0.2356 0.788 0.000 0.928 0.072
#> GSM1182215 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182216 2 0.1643 0.855 0.000 0.956 0.044
#> GSM1182217 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182218 1 0.3551 0.939 0.868 0.000 0.132
#> GSM1182219 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182220 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182221 2 0.0237 0.854 0.000 0.996 0.004
#> GSM1182222 2 0.1643 0.854 0.000 0.956 0.044
#> GSM1182223 2 0.2796 0.838 0.000 0.908 0.092
#> GSM1182224 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182225 2 0.0892 0.856 0.000 0.980 0.020
#> GSM1182226 2 0.1753 0.854 0.000 0.952 0.048
#> GSM1182227 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182228 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182229 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182230 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182231 2 0.2066 0.850 0.000 0.940 0.060
#> GSM1182232 1 0.3412 0.940 0.876 0.000 0.124
#> GSM1182233 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182234 1 0.0237 0.936 0.996 0.000 0.004
#> GSM1182235 2 0.2165 0.798 0.000 0.936 0.064
#> GSM1182236 1 0.3619 0.938 0.864 0.000 0.136
#> GSM1182237 2 0.0592 0.855 0.000 0.988 0.012
#> GSM1182238 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182239 2 0.2711 0.760 0.000 0.912 0.088
#> GSM1182240 2 0.0747 0.848 0.000 0.984 0.016
#> GSM1182241 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182242 2 0.2261 0.848 0.000 0.932 0.068
#> GSM1182243 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182244 2 0.1163 0.857 0.000 0.972 0.028
#> GSM1182245 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182246 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182247 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182248 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182249 2 0.2625 0.842 0.000 0.916 0.084
#> GSM1182250 2 0.3038 0.830 0.000 0.896 0.104
#> GSM1182251 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182252 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182253 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182254 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182255 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182256 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182257 1 0.0892 0.939 0.980 0.000 0.020
#> GSM1182258 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182259 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182260 2 0.0747 0.856 0.000 0.984 0.016
#> GSM1182261 2 0.2959 0.832 0.000 0.900 0.100
#> GSM1182262 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182263 1 0.2796 0.943 0.908 0.000 0.092
#> GSM1182264 2 0.0592 0.852 0.000 0.988 0.012
#> GSM1182265 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182266 2 0.0747 0.855 0.000 0.984 0.016
#> GSM1182267 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182268 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182269 1 0.3267 0.940 0.884 0.000 0.116
#> GSM1182270 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182271 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182272 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182273 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182275 2 0.2448 0.849 0.000 0.924 0.076
#> GSM1182276 2 0.2878 0.745 0.000 0.904 0.096
#> GSM1182277 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182278 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182279 1 0.3686 0.938 0.860 0.000 0.140
#> GSM1182280 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182281 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182282 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182283 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182284 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182285 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182286 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182287 2 0.2711 0.840 0.000 0.912 0.088
#> GSM1182288 2 0.2878 0.835 0.000 0.904 0.096
#> GSM1182289 1 0.3686 0.937 0.860 0.000 0.140
#> GSM1182290 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182291 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182274 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182292 2 0.4555 0.447 0.000 0.800 0.200
#> GSM1182293 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182294 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182295 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182296 2 0.1163 0.840 0.000 0.972 0.028
#> GSM1182298 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182299 2 0.3192 0.713 0.000 0.888 0.112
#> GSM1182300 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182301 2 0.1031 0.843 0.000 0.976 0.024
#> GSM1182303 2 0.3267 0.706 0.000 0.884 0.116
#> GSM1182304 1 0.3752 0.936 0.856 0.000 0.144
#> GSM1182305 1 0.1411 0.940 0.964 0.000 0.036
#> GSM1182306 1 0.2165 0.942 0.936 0.000 0.064
#> GSM1182307 2 0.5098 0.203 0.000 0.752 0.248
#> GSM1182309 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182312 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182314 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182316 2 0.0592 0.855 0.000 0.988 0.012
#> GSM1182318 2 0.4702 0.395 0.000 0.788 0.212
#> GSM1182319 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182320 2 0.0424 0.853 0.000 0.992 0.008
#> GSM1182321 2 0.1411 0.856 0.000 0.964 0.036
#> GSM1182322 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182324 2 0.3116 0.827 0.000 0.892 0.108
#> GSM1182297 2 0.3267 0.704 0.000 0.884 0.116
#> GSM1182302 1 0.3619 0.938 0.864 0.000 0.136
#> GSM1182308 2 0.2066 0.804 0.000 0.940 0.060
#> GSM1182310 2 0.1753 0.854 0.000 0.952 0.048
#> GSM1182311 1 0.3686 0.939 0.860 0.000 0.140
#> GSM1182313 1 0.0592 0.935 0.988 0.000 0.012
#> GSM1182315 2 0.0892 0.846 0.000 0.980 0.020
#> GSM1182317 2 0.2448 0.781 0.000 0.924 0.076
#> GSM1182323 1 0.3752 0.936 0.856 0.000 0.144
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.4841 0.6942 0.780 0.000 0.140 0.080
#> GSM1182187 1 0.3051 0.7727 0.884 0.000 0.088 0.028
#> GSM1182188 1 0.1610 0.7685 0.952 0.000 0.032 0.016
#> GSM1182189 1 0.4300 0.7189 0.820 0.000 0.092 0.088
#> GSM1182190 1 0.2473 0.7810 0.908 0.000 0.080 0.012
#> GSM1182191 1 0.5293 0.6394 0.748 0.000 0.152 0.100
#> GSM1182192 1 0.3674 0.7525 0.852 0.000 0.104 0.044
#> GSM1182193 1 0.5209 0.6475 0.756 0.000 0.104 0.140
#> GSM1182194 2 0.5004 0.3974 0.000 0.604 0.004 0.392
#> GSM1182195 2 0.4961 0.3362 0.000 0.552 0.000 0.448
#> GSM1182196 2 0.0921 0.5764 0.000 0.972 0.028 0.000
#> GSM1182197 2 0.2216 0.5264 0.000 0.908 0.092 0.000
#> GSM1182198 2 0.5000 0.2762 0.000 0.504 0.000 0.496
#> GSM1182199 2 0.4999 0.2825 0.000 0.508 0.000 0.492
#> GSM1182200 2 0.4103 0.1513 0.000 0.744 0.256 0.000
#> GSM1182201 2 0.2329 0.5729 0.000 0.916 0.072 0.012
#> GSM1182202 1 0.3278 0.7641 0.864 0.000 0.116 0.020
#> GSM1182203 1 0.1284 0.7719 0.964 0.000 0.024 0.012
#> GSM1182204 1 0.1510 0.7704 0.956 0.000 0.028 0.016
#> GSM1182205 2 0.3764 0.5711 0.000 0.784 0.000 0.216
#> GSM1182206 2 0.2773 0.6117 0.000 0.880 0.004 0.116
#> GSM1182207 1 0.7332 -0.5836 0.480 0.000 0.164 0.356
#> GSM1182208 4 0.7693 0.0000 0.352 0.000 0.224 0.424
#> GSM1182209 3 0.4992 0.0000 0.000 0.476 0.524 0.000
#> GSM1182210 2 0.3444 0.3423 0.000 0.816 0.184 0.000
#> GSM1182211 2 0.4972 -0.8039 0.000 0.544 0.456 0.000
#> GSM1182212 2 0.4972 -0.7876 0.000 0.544 0.456 0.000
#> GSM1182213 2 0.4898 -0.6675 0.000 0.584 0.416 0.000
#> GSM1182214 2 0.4948 -0.7564 0.000 0.560 0.440 0.000
#> GSM1182215 2 0.3539 0.5926 0.000 0.820 0.004 0.176
#> GSM1182216 2 0.5384 0.4004 0.000 0.728 0.196 0.076
#> GSM1182217 1 0.3325 0.7601 0.864 0.000 0.112 0.024
#> GSM1182218 1 0.1398 0.7859 0.956 0.000 0.040 0.004
#> GSM1182219 2 0.3311 0.3737 0.000 0.828 0.172 0.000
#> GSM1182220 2 0.4222 0.0265 0.000 0.728 0.272 0.000
#> GSM1182221 2 0.1576 0.5657 0.000 0.948 0.048 0.004
#> GSM1182222 2 0.3354 0.6039 0.000 0.872 0.044 0.084
#> GSM1182223 2 0.3706 0.6088 0.000 0.848 0.040 0.112
#> GSM1182224 2 0.4730 0.4346 0.000 0.636 0.000 0.364
#> GSM1182225 2 0.3638 0.5141 0.000 0.848 0.120 0.032
#> GSM1182226 2 0.1792 0.6136 0.000 0.932 0.000 0.068
#> GSM1182227 1 0.1004 0.7751 0.972 0.000 0.024 0.004
#> GSM1182228 2 0.1576 0.5641 0.000 0.948 0.048 0.004
#> GSM1182229 2 0.2973 0.6064 0.000 0.856 0.000 0.144
#> GSM1182230 2 0.3400 0.5932 0.000 0.820 0.000 0.180
#> GSM1182231 2 0.2216 0.6143 0.000 0.908 0.000 0.092
#> GSM1182232 1 0.3674 0.7528 0.852 0.000 0.104 0.044
#> GSM1182233 1 0.4982 0.6743 0.772 0.000 0.136 0.092
#> GSM1182234 1 0.2565 0.7764 0.912 0.000 0.032 0.056
#> GSM1182235 2 0.4222 0.0117 0.000 0.728 0.272 0.000
#> GSM1182236 1 0.3166 0.7586 0.868 0.000 0.116 0.016
#> GSM1182237 2 0.0937 0.5904 0.000 0.976 0.012 0.012
#> GSM1182238 2 0.3610 0.2974 0.000 0.800 0.200 0.000
#> GSM1182239 2 0.3801 0.2378 0.000 0.780 0.220 0.000
#> GSM1182240 2 0.4155 0.1686 0.000 0.756 0.240 0.004
#> GSM1182241 2 0.1661 0.5609 0.000 0.944 0.052 0.004
#> GSM1182242 2 0.2216 0.6169 0.000 0.908 0.000 0.092
#> GSM1182243 2 0.3208 0.6038 0.000 0.848 0.004 0.148
#> GSM1182244 2 0.2469 0.6050 0.000 0.892 0.000 0.108
#> GSM1182245 1 0.3004 0.7765 0.892 0.000 0.048 0.060
#> GSM1182246 1 0.1913 0.7663 0.940 0.000 0.040 0.020
#> GSM1182247 2 0.3790 0.5934 0.000 0.820 0.016 0.164
#> GSM1182248 2 0.4262 0.5515 0.000 0.756 0.008 0.236
#> GSM1182249 2 0.2345 0.6146 0.000 0.900 0.000 0.100
#> GSM1182250 2 0.3356 0.5975 0.000 0.824 0.000 0.176
#> GSM1182251 1 0.4869 0.6834 0.780 0.000 0.132 0.088
#> GSM1182252 2 0.3907 0.5612 0.000 0.768 0.000 0.232
#> GSM1182253 2 0.4720 0.4731 0.000 0.672 0.004 0.324
#> GSM1182254 2 0.3718 0.5930 0.000 0.820 0.012 0.168
#> GSM1182255 1 0.1677 0.7637 0.948 0.000 0.040 0.012
#> GSM1182256 1 0.1798 0.7646 0.944 0.000 0.040 0.016
#> GSM1182257 1 0.1151 0.7770 0.968 0.000 0.024 0.008
#> GSM1182258 1 0.1174 0.7797 0.968 0.000 0.020 0.012
#> GSM1182259 1 0.1584 0.7645 0.952 0.000 0.036 0.012
#> GSM1182260 2 0.2271 0.6003 0.000 0.916 0.008 0.076
#> GSM1182261 2 0.2814 0.6091 0.000 0.868 0.000 0.132
#> GSM1182262 2 0.3123 0.6020 0.000 0.844 0.000 0.156
#> GSM1182263 1 0.5171 0.6613 0.760 0.000 0.112 0.128
#> GSM1182264 2 0.4175 0.4725 0.000 0.776 0.012 0.212
#> GSM1182265 2 0.4477 0.4880 0.000 0.688 0.000 0.312
#> GSM1182266 2 0.3032 0.5744 0.000 0.868 0.008 0.124
#> GSM1182267 1 0.3312 0.7619 0.876 0.000 0.052 0.072
#> GSM1182268 1 0.4969 0.6701 0.772 0.000 0.140 0.088
#> GSM1182269 1 0.4646 0.7039 0.796 0.000 0.120 0.084
#> GSM1182270 1 0.4609 0.7169 0.788 0.000 0.156 0.056
#> GSM1182271 1 0.1584 0.7651 0.952 0.000 0.036 0.012
#> GSM1182272 1 0.1584 0.7645 0.952 0.000 0.036 0.012
#> GSM1182273 2 0.4916 0.3654 0.000 0.576 0.000 0.424
#> GSM1182275 2 0.2924 0.6151 0.000 0.884 0.016 0.100
#> GSM1182276 2 0.4624 -0.3162 0.000 0.660 0.340 0.000
#> GSM1182277 1 0.1109 0.7855 0.968 0.000 0.028 0.004
#> GSM1182278 1 0.1406 0.7786 0.960 0.000 0.024 0.016
#> GSM1182279 1 0.5674 0.5808 0.720 0.000 0.148 0.132
#> GSM1182280 1 0.6457 0.3256 0.644 0.000 0.156 0.200
#> GSM1182281 1 0.1624 0.7791 0.952 0.000 0.028 0.020
#> GSM1182282 1 0.2675 0.7809 0.908 0.000 0.048 0.044
#> GSM1182283 1 0.2500 0.7841 0.916 0.000 0.040 0.044
#> GSM1182284 1 0.1209 0.7740 0.964 0.000 0.032 0.004
#> GSM1182285 2 0.4406 0.5021 0.000 0.700 0.000 0.300
#> GSM1182286 2 0.3569 0.3117 0.000 0.804 0.196 0.000
#> GSM1182287 2 0.3899 0.6061 0.000 0.840 0.052 0.108
#> GSM1182288 2 0.3610 0.5829 0.000 0.800 0.000 0.200
#> GSM1182289 1 0.5375 0.6312 0.744 0.000 0.140 0.116
#> GSM1182290 1 0.7304 -0.5487 0.492 0.000 0.164 0.344
#> GSM1182291 1 0.1677 0.7637 0.948 0.000 0.040 0.012
#> GSM1182274 2 0.3942 0.5582 0.000 0.764 0.000 0.236
#> GSM1182292 2 0.4955 -0.7626 0.000 0.556 0.444 0.000
#> GSM1182293 2 0.2345 0.5041 0.000 0.900 0.100 0.000
#> GSM1182294 2 0.1022 0.5736 0.000 0.968 0.032 0.000
#> GSM1182295 2 0.3024 0.4230 0.000 0.852 0.148 0.000
#> GSM1182296 2 0.3837 0.2294 0.000 0.776 0.224 0.000
#> GSM1182298 2 0.4996 0.2901 0.000 0.516 0.000 0.484
#> GSM1182299 2 0.3400 0.3793 0.000 0.820 0.180 0.000
#> GSM1182300 2 0.2408 0.4986 0.000 0.896 0.104 0.000
#> GSM1182301 2 0.4193 0.0354 0.000 0.732 0.268 0.000
#> GSM1182303 2 0.4624 -0.3158 0.000 0.660 0.340 0.000
#> GSM1182304 1 0.6025 0.5072 0.688 0.000 0.172 0.140
#> GSM1182305 1 0.4599 0.7113 0.800 0.000 0.112 0.088
#> GSM1182306 1 0.2060 0.7835 0.932 0.000 0.052 0.016
#> GSM1182307 2 0.4999 -0.9123 0.000 0.508 0.492 0.000
#> GSM1182309 2 0.2216 0.5213 0.000 0.908 0.092 0.000
#> GSM1182312 2 0.1302 0.5666 0.000 0.956 0.044 0.000
#> GSM1182314 1 0.1929 0.7689 0.940 0.000 0.036 0.024
#> GSM1182316 2 0.0672 0.5973 0.000 0.984 0.008 0.008
#> GSM1182318 2 0.4843 -0.5477 0.000 0.604 0.396 0.000
#> GSM1182319 2 0.1733 0.5878 0.000 0.948 0.024 0.028
#> GSM1182320 2 0.1211 0.6077 0.000 0.960 0.000 0.040
#> GSM1182321 2 0.2124 0.6061 0.000 0.924 0.008 0.068
#> GSM1182322 2 0.2635 0.5747 0.000 0.904 0.020 0.076
#> GSM1182324 2 0.3494 0.5962 0.000 0.824 0.004 0.172
#> GSM1182297 2 0.4679 -0.3998 0.000 0.648 0.352 0.000
#> GSM1182302 1 0.1938 0.7815 0.936 0.000 0.052 0.012
#> GSM1182308 2 0.4431 -0.1678 0.000 0.696 0.304 0.000
#> GSM1182310 2 0.2589 0.6022 0.000 0.884 0.000 0.116
#> GSM1182311 1 0.5102 0.6664 0.764 0.000 0.136 0.100
#> GSM1182313 1 0.1798 0.7646 0.944 0.000 0.040 0.016
#> GSM1182315 2 0.3539 0.3683 0.000 0.820 0.176 0.004
#> GSM1182317 2 0.4250 0.0453 0.000 0.724 0.276 0.000
#> GSM1182323 1 0.3856 0.7344 0.832 0.000 0.136 0.032
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.3969 0.6451 0.692 0.004 0.000 0.304 0.000
#> GSM1182187 1 0.2813 0.7334 0.832 0.000 0.000 0.168 0.000
#> GSM1182188 1 0.1502 0.7338 0.940 0.000 0.000 0.056 0.004
#> GSM1182189 1 0.4540 0.5961 0.640 0.000 0.000 0.340 0.020
#> GSM1182190 1 0.4212 0.7031 0.736 0.004 0.000 0.236 0.024
#> GSM1182191 1 0.4438 0.5484 0.608 0.004 0.000 0.384 0.004
#> GSM1182192 1 0.3167 0.7447 0.820 0.004 0.000 0.172 0.004
#> GSM1182193 1 0.4323 0.7107 0.744 0.012 0.000 0.220 0.024
#> GSM1182194 3 0.2574 0.6213 0.000 0.012 0.876 0.000 0.112
#> GSM1182195 3 0.2179 0.5989 0.000 0.000 0.896 0.004 0.100
#> GSM1182196 3 0.4297 0.5148 0.000 0.288 0.692 0.000 0.020
#> GSM1182197 3 0.4602 0.6031 0.000 0.240 0.708 0.000 0.052
#> GSM1182198 3 0.3160 0.4569 0.000 0.000 0.808 0.004 0.188
#> GSM1182199 3 0.3047 0.5084 0.000 0.004 0.832 0.004 0.160
#> GSM1182200 3 0.5538 0.3999 0.000 0.312 0.596 0.000 0.092
#> GSM1182201 3 0.4791 0.6748 0.000 0.132 0.740 0.004 0.124
#> GSM1182202 1 0.3300 0.7048 0.792 0.004 0.000 0.204 0.000
#> GSM1182203 1 0.2424 0.7296 0.868 0.000 0.000 0.132 0.000
#> GSM1182204 1 0.2561 0.7284 0.856 0.000 0.000 0.144 0.000
#> GSM1182205 3 0.1830 0.6994 0.000 0.028 0.932 0.000 0.040
#> GSM1182206 3 0.2570 0.7240 0.000 0.108 0.880 0.004 0.008
#> GSM1182207 4 0.4157 0.8669 0.264 0.000 0.000 0.716 0.020
#> GSM1182208 4 0.4230 0.8140 0.168 0.008 0.000 0.776 0.048
#> GSM1182209 2 0.1704 0.4907 0.000 0.928 0.068 0.000 0.004
#> GSM1182210 2 0.4227 0.5028 0.000 0.580 0.420 0.000 0.000
#> GSM1182211 2 0.2249 0.5319 0.000 0.896 0.096 0.000 0.008
#> GSM1182212 2 0.5044 0.2295 0.000 0.504 0.464 0.000 0.032
#> GSM1182213 2 0.4161 0.5230 0.000 0.608 0.392 0.000 0.000
#> GSM1182214 2 0.1965 0.5375 0.000 0.904 0.096 0.000 0.000
#> GSM1182215 3 0.2359 0.7195 0.000 0.060 0.904 0.000 0.036
#> GSM1182216 2 0.4118 0.5019 0.000 0.660 0.336 0.000 0.004
#> GSM1182217 1 0.3010 0.7298 0.824 0.000 0.000 0.172 0.004
#> GSM1182218 1 0.3621 0.7310 0.788 0.000 0.000 0.192 0.020
#> GSM1182219 3 0.4242 0.1181 0.000 0.428 0.572 0.000 0.000
#> GSM1182220 3 0.4653 -0.1144 0.000 0.472 0.516 0.000 0.012
#> GSM1182221 2 0.3861 0.5512 0.000 0.712 0.284 0.000 0.004
#> GSM1182222 3 0.3611 0.6423 0.000 0.208 0.780 0.004 0.008
#> GSM1182223 3 0.3558 0.7234 0.000 0.108 0.828 0.000 0.064
#> GSM1182224 3 0.1864 0.6499 0.000 0.004 0.924 0.004 0.068
#> GSM1182225 3 0.4196 0.3060 0.000 0.356 0.640 0.000 0.004
#> GSM1182226 3 0.4564 0.2107 0.000 0.372 0.612 0.000 0.016
#> GSM1182227 1 0.3653 0.7207 0.828 0.012 0.000 0.124 0.036
#> GSM1182228 3 0.3675 0.6788 0.000 0.188 0.788 0.000 0.024
#> GSM1182229 3 0.2233 0.7297 0.000 0.080 0.904 0.000 0.016
#> GSM1182230 3 0.2171 0.7247 0.000 0.064 0.912 0.000 0.024
#> GSM1182231 3 0.2629 0.7119 0.000 0.136 0.860 0.000 0.004
#> GSM1182232 1 0.3662 0.7153 0.744 0.000 0.000 0.252 0.004
#> GSM1182233 1 0.4182 0.5952 0.644 0.000 0.000 0.352 0.004
#> GSM1182234 1 0.4407 0.7067 0.764 0.016 0.000 0.180 0.040
#> GSM1182235 2 0.3730 0.6331 0.000 0.712 0.288 0.000 0.000
#> GSM1182236 1 0.3967 0.7003 0.724 0.000 0.000 0.264 0.012
#> GSM1182237 3 0.3805 0.6749 0.000 0.184 0.784 0.000 0.032
#> GSM1182238 2 0.3398 0.6183 0.000 0.780 0.216 0.000 0.004
#> GSM1182239 2 0.4451 0.2212 0.000 0.504 0.492 0.000 0.004
#> GSM1182240 3 0.4659 -0.2463 0.000 0.492 0.496 0.000 0.012
#> GSM1182241 3 0.3961 0.6083 0.000 0.248 0.736 0.000 0.016
#> GSM1182242 3 0.2813 0.7173 0.000 0.048 0.884 0.004 0.064
#> GSM1182243 3 0.2623 0.7297 0.000 0.096 0.884 0.004 0.016
#> GSM1182244 3 0.3090 0.7231 0.000 0.104 0.856 0.000 0.040
#> GSM1182245 1 0.3541 0.7516 0.824 0.012 0.000 0.144 0.020
#> GSM1182246 1 0.1331 0.7195 0.952 0.000 0.000 0.040 0.008
#> GSM1182247 3 0.3413 0.6666 0.000 0.044 0.832 0.000 0.124
#> GSM1182248 3 0.2233 0.6390 0.000 0.000 0.892 0.004 0.104
#> GSM1182249 3 0.3060 0.7117 0.000 0.128 0.848 0.000 0.024
#> GSM1182250 3 0.1831 0.7274 0.000 0.076 0.920 0.000 0.004
#> GSM1182251 1 0.4387 0.5909 0.640 0.000 0.000 0.348 0.012
#> GSM1182252 3 0.1915 0.7135 0.000 0.032 0.928 0.000 0.040
#> GSM1182253 3 0.1740 0.6739 0.000 0.012 0.932 0.000 0.056
#> GSM1182254 3 0.2608 0.6741 0.000 0.020 0.888 0.004 0.088
#> GSM1182255 1 0.0955 0.7205 0.968 0.000 0.000 0.028 0.004
#> GSM1182256 1 0.1357 0.7123 0.948 0.000 0.000 0.048 0.004
#> GSM1182257 1 0.0794 0.7283 0.972 0.000 0.000 0.028 0.000
#> GSM1182258 1 0.1282 0.7320 0.952 0.000 0.000 0.044 0.004
#> GSM1182259 1 0.1894 0.7004 0.920 0.000 0.000 0.072 0.008
#> GSM1182260 3 0.2645 0.7141 0.000 0.068 0.888 0.000 0.044
#> GSM1182261 3 0.2077 0.7276 0.000 0.084 0.908 0.000 0.008
#> GSM1182262 3 0.1990 0.7281 0.000 0.068 0.920 0.004 0.008
#> GSM1182263 1 0.4348 0.6388 0.668 0.000 0.000 0.316 0.016
#> GSM1182264 3 0.3334 0.6939 0.000 0.080 0.852 0.004 0.064
#> GSM1182265 3 0.3169 0.6911 0.000 0.060 0.856 0.000 0.084
#> GSM1182266 3 0.3333 0.6959 0.000 0.060 0.856 0.008 0.076
#> GSM1182267 1 0.3495 0.7318 0.812 0.000 0.000 0.160 0.028
#> GSM1182268 1 0.4726 0.6296 0.644 0.004 0.000 0.328 0.024
#> GSM1182269 1 0.4674 0.6469 0.676 0.008 0.000 0.292 0.024
#> GSM1182270 1 0.4251 0.6401 0.672 0.000 0.000 0.316 0.012
#> GSM1182271 1 0.1124 0.7220 0.960 0.000 0.000 0.036 0.004
#> GSM1182272 1 0.1830 0.7004 0.924 0.000 0.000 0.068 0.008
#> GSM1182273 3 0.1952 0.6326 0.000 0.000 0.912 0.004 0.084
#> GSM1182275 3 0.3532 0.7225 0.000 0.092 0.832 0.000 0.076
#> GSM1182276 3 0.4904 -0.1306 0.000 0.472 0.504 0.000 0.024
#> GSM1182277 1 0.2720 0.7325 0.880 0.004 0.000 0.096 0.020
#> GSM1182278 1 0.2886 0.7351 0.864 0.004 0.000 0.116 0.016
#> GSM1182279 1 0.4928 0.5185 0.596 0.008 0.000 0.376 0.020
#> GSM1182280 1 0.4383 0.4473 0.572 0.000 0.000 0.424 0.004
#> GSM1182281 1 0.2069 0.7131 0.912 0.000 0.000 0.076 0.012
#> GSM1182282 1 0.3692 0.7339 0.812 0.008 0.000 0.152 0.028
#> GSM1182283 1 0.3194 0.7502 0.832 0.000 0.000 0.148 0.020
#> GSM1182284 1 0.3241 0.7209 0.856 0.008 0.000 0.100 0.036
#> GSM1182285 3 0.1197 0.6668 0.000 0.000 0.952 0.000 0.048
#> GSM1182286 2 0.4171 0.5575 0.000 0.604 0.396 0.000 0.000
#> GSM1182287 3 0.3291 0.7230 0.000 0.120 0.840 0.000 0.040
#> GSM1182288 3 0.1710 0.6934 0.000 0.016 0.940 0.004 0.040
#> GSM1182289 1 0.4564 0.5374 0.600 0.004 0.000 0.388 0.008
#> GSM1182290 4 0.4169 0.8771 0.256 0.004 0.000 0.724 0.016
#> GSM1182291 1 0.0955 0.7205 0.968 0.000 0.000 0.028 0.004
#> GSM1182274 3 0.2756 0.6995 0.000 0.036 0.892 0.012 0.060
#> GSM1182292 2 0.3861 0.6086 0.000 0.712 0.284 0.000 0.004
#> GSM1182293 2 0.3906 0.6208 0.000 0.704 0.292 0.000 0.004
#> GSM1182294 3 0.4902 0.0894 0.000 0.408 0.564 0.000 0.028
#> GSM1182295 2 0.4150 0.5800 0.000 0.612 0.388 0.000 0.000
#> GSM1182296 2 0.4171 0.5524 0.000 0.604 0.396 0.000 0.000
#> GSM1182298 3 0.3715 0.2570 0.000 0.004 0.736 0.000 0.260
#> GSM1182299 3 0.4985 0.2039 0.000 0.392 0.580 0.012 0.016
#> GSM1182300 3 0.4415 0.0141 0.000 0.444 0.552 0.000 0.004
#> GSM1182301 2 0.4464 0.4954 0.000 0.584 0.408 0.000 0.008
#> GSM1182303 3 0.5009 0.0745 0.000 0.428 0.540 0.000 0.032
#> GSM1182304 1 0.4359 0.4806 0.584 0.000 0.000 0.412 0.004
#> GSM1182305 1 0.4295 0.6894 0.724 0.004 0.000 0.248 0.024
#> GSM1182306 1 0.2230 0.7391 0.884 0.000 0.000 0.116 0.000
#> GSM1182307 2 0.1768 0.4986 0.000 0.924 0.072 0.000 0.004
#> GSM1182309 2 0.3988 0.5599 0.000 0.768 0.196 0.000 0.036
#> GSM1182312 2 0.3663 0.5309 0.000 0.776 0.208 0.000 0.016
#> GSM1182314 1 0.1205 0.7293 0.956 0.000 0.000 0.040 0.004
#> GSM1182316 2 0.5263 0.4025 0.000 0.576 0.368 0.000 0.056
#> GSM1182318 2 0.2193 0.5247 0.000 0.900 0.092 0.000 0.008
#> GSM1182319 5 0.6500 0.7987 0.000 0.236 0.276 0.000 0.488
#> GSM1182320 2 0.4969 0.3721 0.000 0.652 0.292 0.000 0.056
#> GSM1182321 3 0.4872 0.5631 0.000 0.120 0.720 0.000 0.160
#> GSM1182322 5 0.6287 0.8226 0.000 0.240 0.224 0.000 0.536
#> GSM1182324 3 0.2953 0.7205 0.000 0.100 0.868 0.004 0.028
#> GSM1182297 2 0.2516 0.5792 0.000 0.860 0.140 0.000 0.000
#> GSM1182302 1 0.2280 0.7303 0.880 0.000 0.000 0.120 0.000
#> GSM1182308 2 0.4416 0.5943 0.000 0.632 0.356 0.000 0.012
#> GSM1182310 5 0.6021 0.8098 0.000 0.144 0.304 0.000 0.552
#> GSM1182311 1 0.4492 0.6664 0.680 0.004 0.000 0.296 0.020
#> GSM1182313 1 0.2006 0.7084 0.916 0.000 0.000 0.072 0.012
#> GSM1182315 2 0.2848 0.5538 0.000 0.840 0.156 0.000 0.004
#> GSM1182317 2 0.2068 0.5213 0.000 0.904 0.092 0.000 0.004
#> GSM1182323 1 0.3928 0.6631 0.700 0.004 0.000 0.296 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.4199 0.6575 0.000 0.000 0.000 0.380 0.600 NA
#> GSM1182187 4 0.3725 0.3984 0.000 0.000 0.000 0.676 0.316 NA
#> GSM1182188 4 0.2662 0.6106 0.004 0.000 0.000 0.840 0.152 NA
#> GSM1182189 5 0.4376 0.6366 0.012 0.000 0.000 0.384 0.592 NA
#> GSM1182190 5 0.4576 0.5839 0.008 0.000 0.000 0.412 0.556 NA
#> GSM1182191 5 0.3912 0.7114 0.000 0.000 0.000 0.340 0.648 NA
#> GSM1182192 4 0.4242 -0.3106 0.000 0.000 0.000 0.536 0.448 NA
#> GSM1182193 5 0.4712 0.5131 0.004 0.000 0.000 0.448 0.512 NA
#> GSM1182194 3 0.3254 0.6907 0.052 0.004 0.836 0.000 0.004 NA
#> GSM1182195 3 0.1845 0.6802 0.052 0.000 0.920 0.000 0.000 NA
#> GSM1182196 3 0.5120 0.0797 0.052 0.408 0.528 0.000 0.004 NA
#> GSM1182197 3 0.5716 0.4921 0.028 0.280 0.576 0.000 0.000 NA
#> GSM1182198 3 0.3516 0.5581 0.164 0.000 0.788 0.000 0.000 NA
#> GSM1182199 3 0.3102 0.6162 0.156 0.000 0.816 0.000 0.000 NA
#> GSM1182200 3 0.6069 0.4201 0.012 0.268 0.520 0.000 0.004 NA
#> GSM1182201 3 0.5183 0.5849 0.000 0.140 0.604 0.000 0.000 NA
#> GSM1182202 4 0.4019 0.3717 0.004 0.000 0.000 0.652 0.332 NA
#> GSM1182203 4 0.3672 0.4853 0.004 0.000 0.000 0.712 0.276 NA
#> GSM1182204 4 0.3452 0.5225 0.004 0.000 0.000 0.736 0.256 NA
#> GSM1182205 3 0.1944 0.7268 0.036 0.024 0.924 0.000 0.000 NA
#> GSM1182206 3 0.2805 0.6927 0.012 0.160 0.828 0.000 0.000 NA
#> GSM1182207 5 0.4079 0.5188 0.000 0.000 0.000 0.136 0.752 NA
#> GSM1182208 5 0.4374 0.3881 0.000 0.000 0.000 0.096 0.712 NA
#> GSM1182209 2 0.1268 0.4957 0.004 0.952 0.008 0.000 0.000 NA
#> GSM1182210 2 0.3380 0.7149 0.004 0.748 0.244 0.000 0.000 NA
#> GSM1182211 2 0.1478 0.5605 0.004 0.944 0.032 0.000 0.000 NA
#> GSM1182212 2 0.4882 0.4386 0.004 0.540 0.404 0.000 0.000 NA
#> GSM1182213 2 0.3606 0.7040 0.004 0.724 0.264 0.000 0.000 NA
#> GSM1182214 2 0.1788 0.6351 0.004 0.916 0.076 0.000 0.000 NA
#> GSM1182215 3 0.2886 0.7221 0.072 0.064 0.860 0.000 0.000 NA
#> GSM1182216 2 0.4867 0.5602 0.012 0.600 0.340 0.000 0.000 NA
#> GSM1182217 4 0.3921 0.4281 0.004 0.000 0.000 0.676 0.308 NA
#> GSM1182218 4 0.4832 -0.1039 0.016 0.000 0.000 0.532 0.424 NA
#> GSM1182219 2 0.4268 0.4203 0.012 0.556 0.428 0.000 0.000 NA
#> GSM1182220 2 0.4310 0.5170 0.000 0.580 0.396 0.000 0.000 NA
#> GSM1182221 2 0.3287 0.6882 0.012 0.768 0.220 0.000 0.000 NA
#> GSM1182222 3 0.4044 0.4208 0.012 0.312 0.668 0.000 0.000 NA
#> GSM1182223 3 0.2954 0.7397 0.004 0.096 0.852 0.000 0.000 NA
#> GSM1182224 3 0.1471 0.7123 0.064 0.004 0.932 0.000 0.000 NA
#> GSM1182225 3 0.4260 -0.2255 0.016 0.472 0.512 0.000 0.000 NA
#> GSM1182226 3 0.5272 -0.2247 0.052 0.460 0.468 0.000 0.000 NA
#> GSM1182227 4 0.5387 -0.0488 0.040 0.000 0.000 0.544 0.372 NA
#> GSM1182228 3 0.4168 0.6703 0.024 0.204 0.740 0.000 0.000 NA
#> GSM1182229 3 0.2122 0.7419 0.000 0.076 0.900 0.000 0.000 NA
#> GSM1182230 3 0.2106 0.7368 0.032 0.064 0.904 0.000 0.000 NA
#> GSM1182231 3 0.3161 0.6368 0.008 0.216 0.776 0.000 0.000 NA
#> GSM1182232 5 0.4419 0.6719 0.000 0.000 0.000 0.384 0.584 NA
#> GSM1182233 5 0.4134 0.7277 0.000 0.000 0.000 0.316 0.656 NA
#> GSM1182234 4 0.5148 0.0676 0.024 0.000 0.000 0.572 0.356 NA
#> GSM1182235 2 0.3860 0.7168 0.008 0.756 0.200 0.000 0.000 NA
#> GSM1182236 5 0.4554 0.6192 0.008 0.000 0.000 0.400 0.568 NA
#> GSM1182237 3 0.4927 0.5698 0.104 0.244 0.648 0.000 0.000 NA
#> GSM1182238 2 0.4289 0.6955 0.016 0.724 0.216 0.000 0.000 NA
#> GSM1182239 2 0.4559 0.5666 0.024 0.600 0.364 0.000 0.000 NA
#> GSM1182240 2 0.4347 0.6583 0.028 0.672 0.288 0.000 0.000 NA
#> GSM1182241 3 0.4671 0.4921 0.060 0.296 0.640 0.000 0.000 NA
#> GSM1182242 3 0.2911 0.7292 0.036 0.032 0.876 0.000 0.004 NA
#> GSM1182243 3 0.2162 0.7403 0.004 0.088 0.896 0.000 0.000 NA
#> GSM1182244 3 0.4143 0.6978 0.120 0.120 0.756 0.000 0.000 NA
#> GSM1182245 4 0.3207 0.6042 0.004 0.000 0.000 0.828 0.124 NA
#> GSM1182246 4 0.0717 0.6543 0.008 0.000 0.000 0.976 0.016 NA
#> GSM1182247 3 0.3205 0.7221 0.052 0.016 0.852 0.000 0.004 NA
#> GSM1182248 3 0.1542 0.7191 0.008 0.004 0.936 0.000 0.000 NA
#> GSM1182249 3 0.4305 0.5984 0.068 0.232 0.700 0.000 0.000 NA
#> GSM1182250 3 0.2687 0.7429 0.024 0.092 0.872 0.000 0.000 NA
#> GSM1182251 5 0.4064 0.7211 0.000 0.000 0.000 0.336 0.644 NA
#> GSM1182252 3 0.2259 0.7409 0.024 0.036 0.912 0.000 0.004 NA
#> GSM1182253 3 0.3119 0.7227 0.036 0.032 0.856 0.000 0.000 NA
#> GSM1182254 3 0.1957 0.7305 0.008 0.024 0.920 0.000 0.000 NA
#> GSM1182255 4 0.0551 0.6557 0.004 0.000 0.000 0.984 0.008 NA
#> GSM1182256 4 0.0622 0.6554 0.012 0.000 0.000 0.980 0.008 NA
#> GSM1182257 4 0.1426 0.6611 0.008 0.000 0.000 0.948 0.028 NA
#> GSM1182258 4 0.0806 0.6608 0.000 0.000 0.000 0.972 0.020 NA
#> GSM1182259 4 0.1275 0.6543 0.016 0.000 0.000 0.956 0.012 NA
#> GSM1182260 3 0.4877 0.7012 0.084 0.104 0.732 0.000 0.000 NA
#> GSM1182261 3 0.2907 0.7357 0.028 0.096 0.860 0.000 0.000 NA
#> GSM1182262 3 0.1461 0.7364 0.016 0.044 0.940 0.000 0.000 NA
#> GSM1182263 5 0.4767 0.5175 0.004 0.000 0.000 0.444 0.512 NA
#> GSM1182264 3 0.5375 0.6511 0.108 0.084 0.696 0.000 0.004 NA
#> GSM1182265 3 0.5950 0.5486 0.212 0.116 0.604 0.000 0.000 NA
#> GSM1182266 3 0.5942 0.5730 0.072 0.096 0.628 0.000 0.008 NA
#> GSM1182267 4 0.4574 0.4521 0.020 0.000 0.000 0.680 0.260 NA
#> GSM1182268 5 0.4883 0.6632 0.016 0.000 0.000 0.356 0.588 NA
#> GSM1182269 4 0.4664 -0.3734 0.004 0.000 0.000 0.488 0.476 NA
#> GSM1182270 5 0.4161 0.6943 0.004 0.000 0.000 0.348 0.632 NA
#> GSM1182271 4 0.0748 0.6590 0.004 0.000 0.000 0.976 0.016 NA
#> GSM1182272 4 0.1059 0.6520 0.016 0.000 0.000 0.964 0.004 NA
#> GSM1182273 3 0.2921 0.6208 0.000 0.008 0.828 0.000 0.008 NA
#> GSM1182275 3 0.4437 0.7170 0.012 0.132 0.748 0.000 0.004 NA
#> GSM1182276 2 0.4716 0.4980 0.004 0.576 0.376 0.000 0.000 NA
#> GSM1182277 4 0.4029 0.5491 0.012 0.000 0.000 0.736 0.220 NA
#> GSM1182278 4 0.3947 0.5692 0.016 0.000 0.000 0.756 0.196 NA
#> GSM1182279 5 0.4115 0.7241 0.004 0.000 0.000 0.268 0.696 NA
#> GSM1182280 5 0.3743 0.7121 0.000 0.000 0.000 0.252 0.724 NA
#> GSM1182281 4 0.1124 0.6598 0.008 0.000 0.000 0.956 0.036 NA
#> GSM1182282 4 0.3124 0.6046 0.008 0.000 0.000 0.828 0.140 NA
#> GSM1182283 4 0.4117 0.4664 0.004 0.000 0.000 0.704 0.256 NA
#> GSM1182284 4 0.3694 0.5942 0.024 0.000 0.000 0.808 0.120 NA
#> GSM1182285 3 0.1434 0.7202 0.024 0.008 0.948 0.000 0.000 NA
#> GSM1182286 2 0.3766 0.7052 0.024 0.720 0.256 0.000 0.000 NA
#> GSM1182287 3 0.2771 0.7297 0.000 0.116 0.852 0.000 0.000 NA
#> GSM1182288 3 0.1434 0.7227 0.020 0.008 0.948 0.000 0.000 NA
#> GSM1182289 4 0.5191 -0.4366 0.000 0.000 0.000 0.456 0.456 NA
#> GSM1182290 5 0.4795 0.4588 0.000 0.000 0.000 0.176 0.672 NA
#> GSM1182291 4 0.0405 0.6539 0.004 0.000 0.000 0.988 0.008 NA
#> GSM1182274 3 0.5411 0.3903 0.016 0.064 0.592 0.000 0.012 NA
#> GSM1182292 2 0.2425 0.6525 0.008 0.880 0.100 0.000 0.000 NA
#> GSM1182293 2 0.3111 0.7082 0.008 0.820 0.156 0.000 0.000 NA
#> GSM1182294 2 0.4947 0.6068 0.088 0.596 0.316 0.000 0.000 NA
#> GSM1182295 2 0.3110 0.7202 0.012 0.792 0.196 0.000 0.000 NA
#> GSM1182296 2 0.2946 0.7158 0.004 0.808 0.184 0.000 0.000 NA
#> GSM1182298 3 0.3630 0.5558 0.212 0.000 0.756 0.000 0.000 NA
#> GSM1182299 2 0.5423 0.0795 0.004 0.456 0.440 0.000 0.000 NA
#> GSM1182300 2 0.4218 0.5825 0.024 0.616 0.360 0.000 0.000 NA
#> GSM1182301 2 0.3534 0.6812 0.008 0.792 0.168 0.000 0.000 NA
#> GSM1182303 3 0.4930 -0.1160 0.004 0.448 0.496 0.000 0.000 NA
#> GSM1182304 5 0.3907 0.7231 0.000 0.000 0.000 0.268 0.704 NA
#> GSM1182305 5 0.4379 0.6103 0.000 0.000 0.000 0.396 0.576 NA
#> GSM1182306 4 0.3827 0.4198 0.004 0.000 0.000 0.680 0.308 NA
#> GSM1182307 2 0.1251 0.5516 0.012 0.956 0.024 0.000 0.000 NA
#> GSM1182309 2 0.3622 0.6486 0.072 0.800 0.124 0.000 0.000 NA
#> GSM1182312 2 0.3473 0.6692 0.048 0.804 0.144 0.000 0.000 NA
#> GSM1182314 4 0.1949 0.6428 0.004 0.000 0.000 0.904 0.088 NA
#> GSM1182316 2 0.3923 0.6185 0.080 0.772 0.144 0.000 0.004 NA
#> GSM1182318 2 0.1668 0.6173 0.004 0.928 0.060 0.000 0.000 NA
#> GSM1182319 1 0.5679 0.6268 0.532 0.316 0.144 0.000 0.000 NA
#> GSM1182320 2 0.3622 0.5351 0.072 0.800 0.124 0.000 0.000 NA
#> GSM1182321 3 0.6760 0.0637 0.300 0.220 0.428 0.000 0.000 NA
#> GSM1182322 1 0.4066 0.7891 0.692 0.272 0.036 0.000 0.000 NA
#> GSM1182324 3 0.4278 0.6078 0.076 0.212 0.712 0.000 0.000 NA
#> GSM1182297 2 0.3633 0.6979 0.024 0.800 0.148 0.000 0.000 NA
#> GSM1182302 4 0.3329 0.5495 0.004 0.000 0.000 0.756 0.236 NA
#> GSM1182308 2 0.3780 0.7163 0.004 0.728 0.248 0.000 0.000 NA
#> GSM1182310 1 0.4582 0.7951 0.684 0.216 0.100 0.000 0.000 NA
#> GSM1182311 5 0.4306 0.7315 0.004 0.000 0.000 0.308 0.656 NA
#> GSM1182313 4 0.2730 0.6152 0.012 0.000 0.000 0.836 0.152 NA
#> GSM1182315 2 0.3047 0.5983 0.060 0.852 0.080 0.000 0.000 NA
#> GSM1182317 2 0.1003 0.5469 0.000 0.964 0.020 0.000 0.000 NA
#> GSM1182323 5 0.4168 0.6561 0.000 0.000 0.000 0.400 0.584 NA
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> SD:NMF 139 7.73e-02 1.0000 2
#> SD:NMF 134 1.29e-01 1.0000 3
#> SD:NMF 96 4.74e-01 0.7516 4
#> SD:NMF 117 3.48e-07 0.0899 5
#> SD:NMF 109 7.31e-07 0.1212 6
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 46361 rows and 139 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 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.977 0.991 0.1480 0.931 0.867
#> 4 4 0.963 0.918 0.922 0.0414 0.972 0.939
#> 5 5 0.760 0.794 0.865 0.0859 0.993 0.983
#> 6 6 0.785 0.746 0.853 0.0692 0.931 0.835
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.6260 0.250 0.552 0 0.448
#> GSM1182187 3 0.0000 0.999 0.000 0 1.000
#> GSM1182188 3 0.0000 0.999 0.000 0 1.000
#> GSM1182189 1 0.0000 0.962 1.000 0 0.000
#> GSM1182190 1 0.0000 0.962 1.000 0 0.000
#> GSM1182191 1 0.6260 0.250 0.552 0 0.448
#> GSM1182192 1 0.0000 0.962 1.000 0 0.000
#> GSM1182193 1 0.0000 0.962 1.000 0 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000
#> GSM1182202 3 0.0000 0.999 0.000 0 1.000
#> GSM1182203 3 0.0000 0.999 0.000 0 1.000
#> GSM1182204 3 0.0000 0.999 0.000 0 1.000
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000
#> GSM1182207 1 0.0000 0.962 1.000 0 0.000
#> GSM1182208 1 0.0000 0.962 1.000 0 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000
#> GSM1182217 3 0.0592 0.987 0.012 0 0.988
#> GSM1182218 1 0.0000 0.962 1.000 0 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000
#> GSM1182227 1 0.0000 0.962 1.000 0 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000
#> GSM1182232 1 0.0000 0.962 1.000 0 0.000
#> GSM1182233 1 0.0000 0.962 1.000 0 0.000
#> GSM1182234 1 0.0000 0.962 1.000 0 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000
#> GSM1182236 1 0.0000 0.962 1.000 0 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000
#> GSM1182245 1 0.0000 0.962 1.000 0 0.000
#> GSM1182246 3 0.0000 0.999 0.000 0 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000
#> GSM1182251 1 0.1031 0.947 0.976 0 0.024
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000
#> GSM1182255 3 0.0000 0.999 0.000 0 1.000
#> GSM1182256 3 0.0000 0.999 0.000 0 1.000
#> GSM1182257 3 0.0000 0.999 0.000 0 1.000
#> GSM1182258 3 0.0000 0.999 0.000 0 1.000
#> GSM1182259 3 0.0000 0.999 0.000 0 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000
#> GSM1182263 1 0.0592 0.955 0.988 0 0.012
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000
#> GSM1182267 1 0.0000 0.962 1.000 0 0.000
#> GSM1182268 1 0.0000 0.962 1.000 0 0.000
#> GSM1182269 1 0.0000 0.962 1.000 0 0.000
#> GSM1182270 1 0.0000 0.962 1.000 0 0.000
#> GSM1182271 3 0.0000 0.999 0.000 0 1.000
#> GSM1182272 3 0.0000 0.999 0.000 0 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000
#> GSM1182277 1 0.0000 0.962 1.000 0 0.000
#> GSM1182278 1 0.0000 0.962 1.000 0 0.000
#> GSM1182279 1 0.0747 0.953 0.984 0 0.016
#> GSM1182280 1 0.0747 0.953 0.984 0 0.016
#> GSM1182281 1 0.3412 0.848 0.876 0 0.124
#> GSM1182282 1 0.0000 0.962 1.000 0 0.000
#> GSM1182283 1 0.0000 0.962 1.000 0 0.000
#> GSM1182284 1 0.0000 0.962 1.000 0 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000
#> GSM1182289 1 0.0892 0.950 0.980 0 0.020
#> GSM1182290 1 0.0000 0.962 1.000 0 0.000
#> GSM1182291 3 0.0000 0.999 0.000 0 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000
#> GSM1182304 1 0.0747 0.953 0.984 0 0.016
#> GSM1182305 1 0.4178 0.794 0.828 0 0.172
#> GSM1182306 3 0.0000 0.999 0.000 0 1.000
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000
#> GSM1182314 3 0.0000 0.999 0.000 0 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000
#> GSM1182302 3 0.0000 0.999 0.000 0 1.000
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000
#> GSM1182311 1 0.0000 0.962 1.000 0 0.000
#> GSM1182313 3 0.0000 0.999 0.000 0 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000
#> GSM1182323 1 0.0000 0.962 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.4477 0.304 0.688 0 0.000 0.312
#> GSM1182187 4 0.2814 0.926 0.132 0 0.000 0.868
#> GSM1182188 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182189 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182190 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182191 1 0.4477 0.304 0.688 0 0.000 0.312
#> GSM1182192 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182193 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182202 4 0.2868 0.924 0.136 0 0.000 0.864
#> GSM1182203 4 0.2868 0.924 0.136 0 0.000 0.864
#> GSM1182204 4 0.2868 0.924 0.136 0 0.000 0.864
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182207 1 0.4679 0.747 0.648 0 0.352 0.000
#> GSM1182208 1 0.4679 0.747 0.648 0 0.352 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182217 4 0.3024 0.916 0.148 0 0.000 0.852
#> GSM1182218 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182227 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182232 1 0.4888 0.734 0.588 0 0.412 0.000
#> GSM1182233 1 0.4888 0.734 0.588 0 0.412 0.000
#> GSM1182234 3 0.3942 0.479 0.236 0 0.764 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182236 1 0.4855 0.745 0.600 0 0.400 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182245 3 0.0817 0.817 0.024 0 0.976 0.000
#> GSM1182246 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182251 1 0.2944 0.647 0.868 0 0.128 0.004
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182255 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182256 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182257 4 0.2469 0.932 0.108 0 0.000 0.892
#> GSM1182258 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182259 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182263 1 0.3208 0.660 0.848 0 0.148 0.004
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182267 1 0.4972 0.663 0.544 0 0.456 0.000
#> GSM1182268 1 0.4898 0.730 0.584 0 0.416 0.000
#> GSM1182269 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182270 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182271 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182272 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182277 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182278 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182279 1 0.2814 0.658 0.868 0 0.132 0.000
#> GSM1182280 1 0.2814 0.658 0.868 0 0.132 0.000
#> GSM1182281 3 0.6414 0.449 0.240 0 0.636 0.124
#> GSM1182282 3 0.0817 0.817 0.024 0 0.976 0.000
#> GSM1182283 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182284 3 0.1716 0.875 0.064 0 0.936 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182289 1 0.2999 0.651 0.864 0 0.132 0.004
#> GSM1182290 1 0.4679 0.747 0.648 0 0.352 0.000
#> GSM1182291 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182304 1 0.2814 0.658 0.868 0 0.132 0.000
#> GSM1182305 1 0.3450 0.473 0.836 0 0.008 0.156
#> GSM1182306 4 0.2530 0.931 0.112 0 0.000 0.888
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182314 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182302 4 0.2868 0.924 0.136 0 0.000 0.864
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182311 1 0.4843 0.748 0.604 0 0.396 0.000
#> GSM1182313 4 0.0000 0.950 0.000 0 0.000 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182323 1 0.4843 0.748 0.604 0 0.396 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.4940 0.307 0.540 0.000 0.436 0.020 0.004
#> GSM1182187 4 0.4446 -0.836 0.000 0.000 0.476 0.520 0.004
#> GSM1182188 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182190 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182191 1 0.4940 0.307 0.540 0.000 0.436 0.020 0.004
#> GSM1182192 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182193 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182194 2 0.5315 0.626 0.000 0.600 0.332 0.000 0.068
#> GSM1182195 2 0.5315 0.626 0.000 0.600 0.332 0.000 0.068
#> GSM1182196 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182197 2 0.0290 0.926 0.000 0.992 0.008 0.000 0.000
#> GSM1182198 2 0.5315 0.626 0.000 0.600 0.332 0.000 0.068
#> GSM1182199 2 0.5315 0.626 0.000 0.600 0.332 0.000 0.068
#> GSM1182200 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182201 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182202 3 0.4434 0.946 0.000 0.000 0.536 0.460 0.004
#> GSM1182203 3 0.4449 0.936 0.000 0.000 0.512 0.484 0.004
#> GSM1182204 3 0.4450 0.930 0.000 0.000 0.508 0.488 0.004
#> GSM1182205 2 0.3513 0.837 0.000 0.800 0.180 0.000 0.020
#> GSM1182206 2 0.3209 0.846 0.000 0.812 0.180 0.000 0.008
#> GSM1182207 1 0.3210 0.707 0.788 0.000 0.000 0.000 0.212
#> GSM1182208 1 0.3210 0.707 0.788 0.000 0.000 0.000 0.212
#> GSM1182209 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182210 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182211 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182212 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182215 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182216 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182217 3 0.4390 0.908 0.000 0.000 0.568 0.428 0.004
#> GSM1182218 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182219 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182220 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182221 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182222 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182223 2 0.2813 0.858 0.000 0.832 0.168 0.000 0.000
#> GSM1182224 2 0.4995 0.712 0.000 0.668 0.264 0.000 0.068
#> GSM1182225 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182226 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182227 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182228 2 0.3093 0.853 0.000 0.824 0.168 0.000 0.008
#> GSM1182229 2 0.3093 0.853 0.000 0.824 0.168 0.000 0.008
#> GSM1182230 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182231 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182232 1 0.3949 0.688 0.668 0.000 0.000 0.000 0.332
#> GSM1182233 1 0.3949 0.688 0.668 0.000 0.000 0.000 0.332
#> GSM1182234 5 0.3816 0.490 0.304 0.000 0.000 0.000 0.696
#> GSM1182235 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182236 1 0.3876 0.703 0.684 0.000 0.000 0.000 0.316
#> GSM1182237 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182238 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182239 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182240 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182241 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182242 2 0.3203 0.851 0.000 0.820 0.168 0.000 0.012
#> GSM1182243 2 0.1121 0.915 0.000 0.956 0.044 0.000 0.000
#> GSM1182244 2 0.4995 0.712 0.000 0.668 0.264 0.000 0.068
#> GSM1182245 5 0.3471 0.798 0.092 0.000 0.072 0.000 0.836
#> GSM1182246 4 0.0510 0.788 0.000 0.000 0.016 0.984 0.000
#> GSM1182247 2 0.3343 0.846 0.000 0.812 0.172 0.000 0.016
#> GSM1182248 2 0.3343 0.846 0.000 0.812 0.172 0.000 0.016
#> GSM1182249 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182250 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182251 1 0.1502 0.615 0.940 0.000 0.056 0.000 0.004
#> GSM1182252 2 0.3343 0.846 0.000 0.812 0.172 0.000 0.016
#> GSM1182253 2 0.3123 0.856 0.000 0.828 0.160 0.000 0.012
#> GSM1182254 2 0.1851 0.896 0.000 0.912 0.088 0.000 0.000
#> GSM1182255 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.4126 -0.536 0.000 0.000 0.380 0.620 0.000
#> GSM1182258 4 0.0609 0.786 0.000 0.000 0.020 0.980 0.000
#> GSM1182259 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182261 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182262 2 0.3048 0.851 0.000 0.820 0.176 0.000 0.004
#> GSM1182263 1 0.1774 0.625 0.932 0.000 0.052 0.000 0.016
#> GSM1182264 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182265 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182266 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182267 1 0.4126 0.609 0.620 0.000 0.000 0.000 0.380
#> GSM1182268 1 0.3983 0.679 0.660 0.000 0.000 0.000 0.340
#> GSM1182269 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182270 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182271 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182275 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182276 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182277 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182278 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182279 1 0.1357 0.624 0.948 0.000 0.048 0.000 0.004
#> GSM1182280 1 0.1357 0.624 0.948 0.000 0.048 0.000 0.004
#> GSM1182281 5 0.6635 0.399 0.204 0.000 0.076 0.112 0.608
#> GSM1182282 5 0.3471 0.798 0.092 0.000 0.072 0.000 0.836
#> GSM1182283 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182284 5 0.2424 0.869 0.132 0.000 0.000 0.000 0.868
#> GSM1182285 2 0.4995 0.712 0.000 0.668 0.264 0.000 0.068
#> GSM1182286 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182287 2 0.2813 0.858 0.000 0.832 0.168 0.000 0.000
#> GSM1182288 2 0.3438 0.844 0.000 0.808 0.172 0.000 0.020
#> GSM1182289 1 0.1430 0.617 0.944 0.000 0.052 0.000 0.004
#> GSM1182290 1 0.3210 0.707 0.788 0.000 0.000 0.000 0.212
#> GSM1182291 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182292 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182293 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182294 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182295 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182296 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182298 2 0.5315 0.626 0.000 0.600 0.332 0.000 0.068
#> GSM1182299 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182300 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182301 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182303 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182304 1 0.1357 0.624 0.948 0.000 0.048 0.000 0.004
#> GSM1182305 1 0.4716 0.479 0.772 0.000 0.088 0.112 0.028
#> GSM1182306 4 0.4273 -0.764 0.000 0.000 0.448 0.552 0.000
#> GSM1182307 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182309 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182312 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182314 4 0.0510 0.788 0.000 0.000 0.016 0.984 0.000
#> GSM1182316 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182318 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182319 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182320 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182321 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182322 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182324 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182297 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182302 3 0.4437 0.947 0.000 0.000 0.532 0.464 0.004
#> GSM1182308 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182310 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182311 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
#> GSM1182313 4 0.0000 0.801 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182317 2 0.0000 0.928 0.000 1.000 0.000 0.000 0.000
#> GSM1182323 1 0.3857 0.707 0.688 0.000 0.000 0.000 0.312
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.4504 0.321 0.000 0.000 0.032 0.000 0.536 0.432
#> GSM1182187 6 0.1812 0.922 0.000 0.000 0.008 0.080 0.000 0.912
#> GSM1182188 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 5 0.3330 0.677 0.284 0.000 0.000 0.000 0.716 0.000
#> GSM1182190 5 0.3136 0.689 0.228 0.000 0.004 0.000 0.768 0.000
#> GSM1182191 5 0.4504 0.321 0.000 0.000 0.032 0.000 0.536 0.432
#> GSM1182192 1 0.1387 0.871 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM1182193 1 0.1444 0.870 0.928 0.000 0.000 0.000 0.072 0.000
#> GSM1182194 3 0.3515 0.935 0.000 0.324 0.676 0.000 0.000 0.000
#> GSM1182195 3 0.3499 0.935 0.000 0.320 0.680 0.000 0.000 0.000
#> GSM1182196 2 0.0547 0.839 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1182197 2 0.1141 0.813 0.000 0.948 0.052 0.000 0.000 0.000
#> GSM1182198 3 0.3499 0.935 0.000 0.320 0.680 0.000 0.000 0.000
#> GSM1182199 3 0.3499 0.935 0.000 0.320 0.680 0.000 0.000 0.000
#> GSM1182200 2 0.0146 0.845 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182201 2 0.0363 0.841 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182202 6 0.0363 0.936 0.000 0.000 0.000 0.012 0.000 0.988
#> GSM1182203 6 0.0937 0.941 0.000 0.000 0.000 0.040 0.000 0.960
#> GSM1182204 6 0.1007 0.941 0.000 0.000 0.000 0.044 0.000 0.956
#> GSM1182205 2 0.3634 0.138 0.000 0.644 0.356 0.000 0.000 0.000
#> GSM1182206 2 0.3592 0.207 0.000 0.656 0.344 0.000 0.000 0.000
#> GSM1182207 5 0.2882 0.684 0.180 0.000 0.008 0.000 0.812 0.000
#> GSM1182208 5 0.2882 0.684 0.180 0.000 0.008 0.000 0.812 0.000
#> GSM1182209 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182210 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182212 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182213 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182215 2 0.3428 0.354 0.000 0.696 0.304 0.000 0.000 0.000
#> GSM1182216 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182217 6 0.0547 0.927 0.000 0.000 0.020 0.000 0.000 0.980
#> GSM1182218 5 0.3189 0.690 0.236 0.000 0.004 0.000 0.760 0.000
#> GSM1182219 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182220 2 0.0146 0.845 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182221 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182222 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182223 2 0.3288 0.443 0.000 0.724 0.276 0.000 0.000 0.000
#> GSM1182224 3 0.3737 0.882 0.000 0.392 0.608 0.000 0.000 0.000
#> GSM1182225 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182226 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182227 1 0.1588 0.865 0.924 0.000 0.004 0.000 0.072 0.000
#> GSM1182228 2 0.3309 0.433 0.000 0.720 0.280 0.000 0.000 0.000
#> GSM1182229 2 0.3482 0.325 0.000 0.684 0.316 0.000 0.000 0.000
#> GSM1182230 2 0.3446 0.346 0.000 0.692 0.308 0.000 0.000 0.000
#> GSM1182231 2 0.3446 0.346 0.000 0.692 0.308 0.000 0.000 0.000
#> GSM1182232 5 0.3482 0.657 0.316 0.000 0.000 0.000 0.684 0.000
#> GSM1182233 5 0.3482 0.657 0.316 0.000 0.000 0.000 0.684 0.000
#> GSM1182234 1 0.3076 0.548 0.760 0.000 0.000 0.000 0.240 0.000
#> GSM1182235 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182236 5 0.3584 0.668 0.308 0.000 0.004 0.000 0.688 0.000
#> GSM1182237 2 0.3409 0.376 0.000 0.700 0.300 0.000 0.000 0.000
#> GSM1182238 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182239 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182240 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182241 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182242 2 0.3531 0.278 0.000 0.672 0.328 0.000 0.000 0.000
#> GSM1182243 2 0.2416 0.694 0.000 0.844 0.156 0.000 0.000 0.000
#> GSM1182244 3 0.3774 0.859 0.000 0.408 0.592 0.000 0.000 0.000
#> GSM1182245 1 0.2277 0.804 0.892 0.000 0.076 0.000 0.032 0.000
#> GSM1182246 4 0.0520 0.987 0.000 0.000 0.008 0.984 0.000 0.008
#> GSM1182247 2 0.3620 0.179 0.000 0.648 0.352 0.000 0.000 0.000
#> GSM1182248 2 0.3620 0.179 0.000 0.648 0.352 0.000 0.000 0.000
#> GSM1182249 2 0.1765 0.778 0.000 0.904 0.096 0.000 0.000 0.000
#> GSM1182250 2 0.1714 0.782 0.000 0.908 0.092 0.000 0.000 0.000
#> GSM1182251 5 0.3459 0.640 0.004 0.000 0.212 0.000 0.768 0.016
#> GSM1182252 2 0.3620 0.179 0.000 0.648 0.352 0.000 0.000 0.000
#> GSM1182253 2 0.3547 0.255 0.000 0.668 0.332 0.000 0.000 0.000
#> GSM1182254 2 0.2793 0.618 0.000 0.800 0.200 0.000 0.000 0.000
#> GSM1182255 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 6 0.2597 0.831 0.000 0.000 0.000 0.176 0.000 0.824
#> GSM1182258 4 0.0622 0.984 0.000 0.000 0.008 0.980 0.000 0.012
#> GSM1182259 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 2 0.1610 0.786 0.000 0.916 0.084 0.000 0.000 0.000
#> GSM1182261 2 0.3409 0.363 0.000 0.700 0.300 0.000 0.000 0.000
#> GSM1182262 2 0.3409 0.363 0.000 0.700 0.300 0.000 0.000 0.000
#> GSM1182263 5 0.3636 0.647 0.016 0.000 0.208 0.000 0.764 0.012
#> GSM1182264 2 0.1663 0.782 0.000 0.912 0.088 0.000 0.000 0.000
#> GSM1182265 2 0.1610 0.785 0.000 0.916 0.084 0.000 0.000 0.000
#> GSM1182266 2 0.1714 0.779 0.000 0.908 0.092 0.000 0.000 0.000
#> GSM1182267 5 0.3828 0.513 0.440 0.000 0.000 0.000 0.560 0.000
#> GSM1182268 5 0.3717 0.604 0.384 0.000 0.000 0.000 0.616 0.000
#> GSM1182269 5 0.3163 0.690 0.232 0.000 0.004 0.000 0.764 0.000
#> GSM1182270 5 0.3163 0.690 0.232 0.000 0.004 0.000 0.764 0.000
#> GSM1182271 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 2 0.1765 0.775 0.000 0.904 0.096 0.000 0.000 0.000
#> GSM1182275 2 0.0363 0.841 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182276 2 0.0363 0.841 0.000 0.988 0.012 0.000 0.000 0.000
#> GSM1182277 1 0.1387 0.870 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM1182278 1 0.1387 0.870 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM1182279 5 0.3273 0.647 0.004 0.000 0.212 0.000 0.776 0.008
#> GSM1182280 5 0.3273 0.647 0.004 0.000 0.212 0.000 0.776 0.008
#> GSM1182281 1 0.5749 0.454 0.600 0.000 0.248 0.108 0.044 0.000
#> GSM1182282 1 0.2852 0.792 0.856 0.000 0.080 0.000 0.064 0.000
#> GSM1182283 1 0.1387 0.871 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM1182284 1 0.1327 0.869 0.936 0.000 0.000 0.000 0.064 0.000
#> GSM1182285 3 0.3737 0.882 0.000 0.392 0.608 0.000 0.000 0.000
#> GSM1182286 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182287 2 0.3288 0.443 0.000 0.724 0.276 0.000 0.000 0.000
#> GSM1182288 2 0.3578 0.224 0.000 0.660 0.340 0.000 0.000 0.000
#> GSM1182289 5 0.3370 0.642 0.004 0.000 0.212 0.000 0.772 0.012
#> GSM1182290 5 0.2778 0.686 0.168 0.000 0.008 0.000 0.824 0.000
#> GSM1182291 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 2 0.1765 0.775 0.000 0.904 0.096 0.000 0.000 0.000
#> GSM1182292 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182293 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182294 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182295 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182296 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182298 3 0.3499 0.935 0.000 0.320 0.680 0.000 0.000 0.000
#> GSM1182299 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182300 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182301 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182303 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182304 5 0.3273 0.647 0.004 0.000 0.212 0.000 0.776 0.008
#> GSM1182305 5 0.6189 0.560 0.024 0.000 0.224 0.108 0.600 0.044
#> GSM1182306 6 0.1863 0.907 0.000 0.000 0.000 0.104 0.000 0.896
#> GSM1182307 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182309 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182312 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182314 4 0.0520 0.987 0.000 0.000 0.008 0.984 0.000 0.008
#> GSM1182316 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182318 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182319 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182320 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182321 2 0.0146 0.845 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182322 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182324 2 0.0146 0.845 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182297 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182302 6 0.0458 0.938 0.000 0.000 0.000 0.016 0.000 0.984
#> GSM1182308 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182310 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182311 5 0.3136 0.690 0.228 0.000 0.004 0.000 0.768 0.000
#> GSM1182313 4 0.0000 0.995 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.0146 0.846 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1182317 2 0.0000 0.846 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182323 5 0.3240 0.690 0.244 0.000 0.004 0.000 0.752 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:hclust 139 0.0773 1.000 2
#> CV:hclust 137 0.1355 0.829 3
#> CV:hclust 134 0.1447 0.769 4
#> CV:hclust 131 0.2322 0.734 5
#> CV:hclust 118 0.0481 0.840 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.714 0.702 0.690 0.2813 0.815 0.645
#> 4 4 0.608 0.870 0.798 0.1437 0.834 0.567
#> 5 5 0.546 0.780 0.751 0.0675 0.991 0.967
#> 6 6 0.658 0.688 0.742 0.0595 0.915 0.684
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182187 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182188 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182189 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182190 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182191 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182192 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182193 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182194 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182195 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182196 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182197 3 0.6286 0.96368 0.000 0.464 0.536
#> GSM1182198 2 0.0424 0.74327 0.000 0.992 0.008
#> GSM1182199 2 0.0747 0.74156 0.000 0.984 0.016
#> GSM1182200 3 0.6308 0.90850 0.000 0.492 0.508
#> GSM1182201 2 0.5560 -0.00864 0.000 0.700 0.300
#> GSM1182202 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182203 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182204 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182205 2 0.0592 0.74131 0.000 0.988 0.012
#> GSM1182206 2 0.0424 0.74120 0.000 0.992 0.008
#> GSM1182207 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182208 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182209 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182210 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182211 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182212 3 0.6274 0.97486 0.000 0.456 0.544
#> GSM1182213 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182214 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182215 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182216 2 0.6274 -0.77863 0.000 0.544 0.456
#> GSM1182217 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182218 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182219 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182220 3 0.6286 0.96346 0.000 0.464 0.536
#> GSM1182221 2 0.6308 -0.87773 0.000 0.508 0.492
#> GSM1182222 2 0.6252 -0.74623 0.000 0.556 0.444
#> GSM1182223 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182224 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182225 2 0.6274 -0.77863 0.000 0.544 0.456
#> GSM1182226 2 0.6280 -0.79035 0.000 0.540 0.460
#> GSM1182227 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182228 2 0.2711 0.67447 0.000 0.912 0.088
#> GSM1182229 2 0.0424 0.74417 0.000 0.992 0.008
#> GSM1182230 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182231 2 0.6244 -0.73522 0.000 0.560 0.440
#> GSM1182232 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182235 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182236 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182237 2 0.3267 0.63776 0.000 0.884 0.116
#> GSM1182238 3 0.6291 0.96095 0.000 0.468 0.532
#> GSM1182239 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182240 3 0.6280 0.96847 0.000 0.460 0.540
#> GSM1182241 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182242 2 0.1529 0.72310 0.000 0.960 0.040
#> GSM1182243 2 0.0237 0.74404 0.000 0.996 0.004
#> GSM1182244 2 0.2625 0.67619 0.000 0.916 0.084
#> GSM1182245 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182246 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182247 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182248 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182249 2 0.2261 0.68422 0.000 0.932 0.068
#> GSM1182250 2 0.0424 0.74120 0.000 0.992 0.008
#> GSM1182251 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182252 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182253 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182254 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182255 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182256 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182257 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182258 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182259 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182260 2 0.2537 0.68389 0.000 0.920 0.080
#> GSM1182261 2 0.0424 0.74120 0.000 0.992 0.008
#> GSM1182262 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182263 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182264 2 0.2878 0.66321 0.000 0.904 0.096
#> GSM1182265 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182266 2 0.1753 0.71601 0.000 0.952 0.048
#> GSM1182267 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182270 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182271 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182272 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182273 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182275 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182276 3 0.6280 0.97044 0.000 0.460 0.540
#> GSM1182277 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182279 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182280 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182281 1 0.5905 0.79647 0.648 0.000 0.352
#> GSM1182282 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182284 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182285 2 0.0592 0.74336 0.000 0.988 0.012
#> GSM1182286 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182287 2 0.4842 0.25323 0.000 0.776 0.224
#> GSM1182288 2 0.0424 0.74327 0.000 0.992 0.008
#> GSM1182289 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182290 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182291 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182274 2 0.0000 0.74398 0.000 1.000 0.000
#> GSM1182292 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182293 3 0.6267 0.97758 0.000 0.452 0.548
#> GSM1182294 3 0.6280 0.97247 0.000 0.460 0.540
#> GSM1182295 3 0.6280 0.97247 0.000 0.460 0.540
#> GSM1182296 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182298 2 0.0747 0.74156 0.000 0.984 0.016
#> GSM1182299 3 0.6267 0.97758 0.000 0.452 0.548
#> GSM1182300 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182301 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182303 3 0.6307 0.92006 0.000 0.488 0.512
#> GSM1182304 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182305 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182306 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182307 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182309 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182312 3 0.6309 0.90121 0.000 0.496 0.504
#> GSM1182314 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182316 2 0.6309 -0.89628 0.000 0.500 0.500
#> GSM1182318 3 0.6274 0.97666 0.000 0.456 0.544
#> GSM1182319 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182320 2 0.6309 -0.88781 0.000 0.504 0.496
#> GSM1182321 2 0.6204 -0.59520 0.000 0.576 0.424
#> GSM1182322 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182324 2 0.5835 -0.36246 0.000 0.660 0.340
#> GSM1182297 3 0.6260 0.97798 0.000 0.448 0.552
#> GSM1182302 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182308 2 0.6308 -0.87800 0.000 0.508 0.492
#> GSM1182310 3 0.6308 0.91038 0.000 0.492 0.508
#> GSM1182311 1 0.0000 0.84728 1.000 0.000 0.000
#> GSM1182313 1 0.6260 0.78319 0.552 0.000 0.448
#> GSM1182315 3 0.6286 0.96386 0.000 0.464 0.536
#> GSM1182317 3 0.6267 0.97758 0.000 0.452 0.548
#> GSM1182323 1 0.0000 0.84728 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.6727 0.884 0.384 0.000 0.096 0.520
#> GSM1182187 4 0.6097 0.932 0.364 0.000 0.056 0.580
#> GSM1182188 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182189 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182190 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182191 4 0.7036 0.858 0.384 0.000 0.124 0.492
#> GSM1182192 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182193 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182194 3 0.5842 0.865 0.000 0.168 0.704 0.128
#> GSM1182195 3 0.5985 0.865 0.000 0.168 0.692 0.140
#> GSM1182196 2 0.3108 0.871 0.000 0.872 0.016 0.112
#> GSM1182197 2 0.3647 0.752 0.000 0.832 0.152 0.016
#> GSM1182198 3 0.5849 0.864 0.000 0.164 0.704 0.132
#> GSM1182199 3 0.5800 0.864 0.000 0.164 0.708 0.128
#> GSM1182200 2 0.2670 0.857 0.000 0.904 0.072 0.024
#> GSM1182201 2 0.5858 -0.281 0.000 0.500 0.468 0.032
#> GSM1182202 4 0.6097 0.932 0.364 0.000 0.056 0.580
#> GSM1182203 4 0.6097 0.932 0.364 0.000 0.056 0.580
#> GSM1182204 4 0.6097 0.932 0.364 0.000 0.056 0.580
#> GSM1182205 3 0.5160 0.888 0.000 0.180 0.748 0.072
#> GSM1182206 3 0.5669 0.866 0.000 0.200 0.708 0.092
#> GSM1182207 1 0.1211 0.925 0.960 0.000 0.040 0.000
#> GSM1182208 1 0.1211 0.925 0.960 0.000 0.040 0.000
#> GSM1182209 2 0.1576 0.881 0.000 0.948 0.004 0.048
#> GSM1182210 2 0.0817 0.885 0.000 0.976 0.000 0.024
#> GSM1182211 2 0.0817 0.884 0.000 0.976 0.000 0.024
#> GSM1182212 2 0.0817 0.883 0.000 0.976 0.000 0.024
#> GSM1182213 2 0.0707 0.883 0.000 0.980 0.000 0.020
#> GSM1182214 2 0.0592 0.883 0.000 0.984 0.000 0.016
#> GSM1182215 3 0.5007 0.893 0.000 0.172 0.760 0.068
#> GSM1182216 2 0.3745 0.834 0.000 0.852 0.060 0.088
#> GSM1182217 4 0.6727 0.884 0.384 0.000 0.096 0.520
#> GSM1182218 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182219 2 0.0592 0.883 0.000 0.984 0.000 0.016
#> GSM1182220 2 0.1388 0.882 0.000 0.960 0.012 0.028
#> GSM1182221 2 0.4095 0.831 0.000 0.804 0.024 0.172
#> GSM1182222 2 0.3820 0.831 0.000 0.848 0.064 0.088
#> GSM1182223 3 0.4248 0.882 0.000 0.220 0.768 0.012
#> GSM1182224 3 0.5985 0.865 0.000 0.168 0.692 0.140
#> GSM1182225 2 0.3745 0.834 0.000 0.852 0.060 0.088
#> GSM1182226 2 0.3796 0.835 0.000 0.848 0.056 0.096
#> GSM1182227 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182228 3 0.5623 0.787 0.000 0.292 0.660 0.048
#> GSM1182229 3 0.3266 0.903 0.000 0.168 0.832 0.000
#> GSM1182230 3 0.3836 0.905 0.000 0.168 0.816 0.016
#> GSM1182231 2 0.5867 0.603 0.000 0.688 0.216 0.096
#> GSM1182232 1 0.0000 0.945 1.000 0.000 0.000 0.000
#> GSM1182233 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182234 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182235 2 0.1489 0.883 0.000 0.952 0.004 0.044
#> GSM1182236 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182237 3 0.6079 0.760 0.000 0.300 0.628 0.072
#> GSM1182238 2 0.2011 0.875 0.000 0.920 0.000 0.080
#> GSM1182239 2 0.1398 0.882 0.000 0.956 0.004 0.040
#> GSM1182240 2 0.2401 0.881 0.000 0.904 0.004 0.092
#> GSM1182241 2 0.2021 0.876 0.000 0.932 0.012 0.056
#> GSM1182242 3 0.3836 0.901 0.000 0.168 0.816 0.016
#> GSM1182243 3 0.3946 0.904 0.000 0.168 0.812 0.020
#> GSM1182244 3 0.6868 0.783 0.000 0.264 0.584 0.152
#> GSM1182245 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182246 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182247 3 0.3448 0.903 0.000 0.168 0.828 0.004
#> GSM1182248 3 0.3836 0.904 0.000 0.168 0.816 0.016
#> GSM1182249 3 0.6157 0.815 0.000 0.232 0.660 0.108
#> GSM1182250 3 0.5212 0.883 0.000 0.192 0.740 0.068
#> GSM1182251 1 0.2760 0.843 0.872 0.000 0.128 0.000
#> GSM1182252 3 0.3448 0.903 0.000 0.168 0.828 0.004
#> GSM1182253 3 0.4379 0.902 0.000 0.172 0.792 0.036
#> GSM1182254 3 0.3591 0.904 0.000 0.168 0.824 0.008
#> GSM1182255 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182256 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182257 4 0.4905 0.947 0.364 0.000 0.004 0.632
#> GSM1182258 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182259 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182260 3 0.4974 0.863 0.000 0.224 0.736 0.040
#> GSM1182261 3 0.5572 0.869 0.000 0.196 0.716 0.088
#> GSM1182262 3 0.4937 0.894 0.000 0.172 0.764 0.064
#> GSM1182263 1 0.2530 0.862 0.888 0.000 0.112 0.000
#> GSM1182264 3 0.5227 0.829 0.000 0.256 0.704 0.040
#> GSM1182265 3 0.5728 0.855 0.000 0.188 0.708 0.104
#> GSM1182266 3 0.4375 0.893 0.000 0.180 0.788 0.032
#> GSM1182267 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182268 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182269 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182270 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182271 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182272 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182273 3 0.3718 0.904 0.000 0.168 0.820 0.012
#> GSM1182275 3 0.3266 0.903 0.000 0.168 0.832 0.000
#> GSM1182276 2 0.1833 0.875 0.000 0.944 0.032 0.024
#> GSM1182277 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182278 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182279 1 0.2704 0.848 0.876 0.000 0.124 0.000
#> GSM1182280 1 0.2530 0.862 0.888 0.000 0.112 0.000
#> GSM1182281 4 0.6393 0.736 0.456 0.000 0.064 0.480
#> GSM1182282 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182283 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182284 1 0.1022 0.940 0.968 0.000 0.032 0.000
#> GSM1182285 3 0.5842 0.865 0.000 0.168 0.704 0.128
#> GSM1182286 2 0.1305 0.882 0.000 0.960 0.004 0.036
#> GSM1182287 3 0.5938 0.294 0.000 0.480 0.484 0.036
#> GSM1182288 3 0.3790 0.904 0.000 0.164 0.820 0.016
#> GSM1182289 1 0.2704 0.848 0.876 0.000 0.124 0.000
#> GSM1182290 1 0.1211 0.925 0.960 0.000 0.040 0.000
#> GSM1182291 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182274 3 0.3808 0.903 0.000 0.176 0.812 0.012
#> GSM1182292 2 0.1743 0.877 0.000 0.940 0.004 0.056
#> GSM1182293 2 0.2647 0.860 0.000 0.880 0.000 0.120
#> GSM1182294 2 0.2814 0.858 0.000 0.868 0.000 0.132
#> GSM1182295 2 0.0921 0.887 0.000 0.972 0.000 0.028
#> GSM1182296 2 0.1824 0.880 0.000 0.936 0.004 0.060
#> GSM1182298 3 0.5849 0.863 0.000 0.164 0.704 0.132
#> GSM1182299 2 0.0469 0.886 0.000 0.988 0.000 0.012
#> GSM1182300 2 0.1902 0.882 0.000 0.932 0.004 0.064
#> GSM1182301 2 0.1743 0.881 0.000 0.940 0.004 0.056
#> GSM1182303 2 0.2089 0.876 0.000 0.932 0.020 0.048
#> GSM1182304 1 0.2760 0.847 0.872 0.000 0.128 0.000
#> GSM1182305 4 0.7081 0.849 0.388 0.000 0.128 0.484
#> GSM1182306 4 0.4905 0.947 0.364 0.000 0.004 0.632
#> GSM1182307 2 0.1824 0.880 0.000 0.936 0.004 0.060
#> GSM1182309 2 0.3157 0.857 0.000 0.852 0.004 0.144
#> GSM1182312 2 0.3925 0.834 0.000 0.808 0.016 0.176
#> GSM1182314 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182316 2 0.4035 0.831 0.000 0.804 0.020 0.176
#> GSM1182318 2 0.1474 0.884 0.000 0.948 0.000 0.052
#> GSM1182319 2 0.3306 0.855 0.000 0.840 0.004 0.156
#> GSM1182320 2 0.4035 0.831 0.000 0.804 0.020 0.176
#> GSM1182321 2 0.6457 0.587 0.000 0.644 0.200 0.156
#> GSM1182322 2 0.3306 0.855 0.000 0.840 0.004 0.156
#> GSM1182324 2 0.6950 0.473 0.000 0.584 0.236 0.180
#> GSM1182297 2 0.1398 0.883 0.000 0.956 0.004 0.040
#> GSM1182302 4 0.6097 0.932 0.364 0.000 0.056 0.580
#> GSM1182308 2 0.2563 0.867 0.000 0.908 0.020 0.072
#> GSM1182310 2 0.3636 0.839 0.000 0.820 0.008 0.172
#> GSM1182311 1 0.0188 0.945 0.996 0.000 0.004 0.000
#> GSM1182313 4 0.4730 0.947 0.364 0.000 0.000 0.636
#> GSM1182315 2 0.3157 0.870 0.000 0.852 0.004 0.144
#> GSM1182317 2 0.2530 0.864 0.000 0.888 0.000 0.112
#> GSM1182323 1 0.0188 0.945 0.996 0.000 0.004 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 4 0.6938 0.7642 0.288 0.000 0.028 0.500 NA
#> GSM1182187 4 0.6041 0.8819 0.248 0.000 0.052 0.632 NA
#> GSM1182188 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182189 1 0.0404 0.8713 0.988 0.000 0.000 0.000 NA
#> GSM1182190 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182191 4 0.7233 0.7017 0.288 0.000 0.028 0.440 NA
#> GSM1182192 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182193 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182194 3 0.5739 0.7011 0.000 0.100 0.556 0.000 NA
#> GSM1182195 3 0.5762 0.6998 0.000 0.100 0.548 0.000 NA
#> GSM1182196 2 0.6479 0.6953 0.000 0.636 0.100 0.096 NA
#> GSM1182197 2 0.5729 0.3431 0.000 0.600 0.320 0.056 NA
#> GSM1182198 3 0.5822 0.6976 0.000 0.108 0.548 0.000 NA
#> GSM1182199 3 0.5845 0.6964 0.000 0.108 0.540 0.000 NA
#> GSM1182200 2 0.3289 0.7534 0.000 0.860 0.088 0.036 NA
#> GSM1182201 3 0.5545 0.3587 0.000 0.432 0.516 0.032 NA
#> GSM1182202 4 0.6041 0.8819 0.248 0.000 0.052 0.632 NA
#> GSM1182203 4 0.5856 0.8854 0.248 0.000 0.044 0.644 NA
#> GSM1182204 4 0.5913 0.8839 0.248 0.000 0.044 0.640 NA
#> GSM1182205 3 0.4543 0.8232 0.000 0.120 0.768 0.008 NA
#> GSM1182206 3 0.5195 0.7790 0.000 0.136 0.736 0.036 NA
#> GSM1182207 1 0.2329 0.8197 0.876 0.000 0.000 0.000 NA
#> GSM1182208 1 0.2329 0.8197 0.876 0.000 0.000 0.000 NA
#> GSM1182209 2 0.1830 0.8013 0.000 0.932 0.000 0.028 NA
#> GSM1182210 2 0.1854 0.8112 0.000 0.936 0.008 0.020 NA
#> GSM1182211 2 0.1200 0.8027 0.000 0.964 0.008 0.016 NA
#> GSM1182212 2 0.1518 0.7977 0.000 0.952 0.016 0.020 NA
#> GSM1182213 2 0.1455 0.8026 0.000 0.952 0.008 0.032 NA
#> GSM1182214 2 0.1569 0.8081 0.000 0.948 0.008 0.032 NA
#> GSM1182215 3 0.4244 0.8198 0.000 0.104 0.804 0.024 NA
#> GSM1182216 2 0.5258 0.7474 0.000 0.740 0.076 0.060 NA
#> GSM1182217 4 0.7129 0.7809 0.288 0.000 0.052 0.504 NA
#> GSM1182218 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182219 2 0.1538 0.8046 0.000 0.948 0.008 0.036 NA
#> GSM1182220 2 0.2060 0.7958 0.000 0.928 0.036 0.024 NA
#> GSM1182221 2 0.6802 0.6774 0.000 0.548 0.036 0.168 NA
#> GSM1182222 2 0.5422 0.7386 0.000 0.728 0.088 0.060 NA
#> GSM1182223 3 0.3940 0.7792 0.000 0.208 0.768 0.008 NA
#> GSM1182224 3 0.5909 0.7001 0.000 0.100 0.544 0.004 NA
#> GSM1182225 2 0.5093 0.7511 0.000 0.752 0.072 0.056 NA
#> GSM1182226 2 0.5436 0.7464 0.000 0.728 0.080 0.068 NA
#> GSM1182227 1 0.2782 0.8542 0.880 0.000 0.048 0.000 NA
#> GSM1182228 3 0.5310 0.6845 0.000 0.284 0.652 0.024 NA
#> GSM1182229 3 0.2416 0.8341 0.000 0.100 0.888 0.000 NA
#> GSM1182230 3 0.2914 0.8355 0.000 0.100 0.872 0.012 NA
#> GSM1182231 2 0.6963 0.0572 0.000 0.432 0.404 0.044 NA
#> GSM1182232 1 0.0162 0.8714 0.996 0.000 0.000 0.000 NA
#> GSM1182233 1 0.0404 0.8713 0.988 0.000 0.000 0.000 NA
#> GSM1182234 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182235 2 0.3142 0.8052 0.000 0.868 0.008 0.068 NA
#> GSM1182236 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182237 3 0.6276 0.6682 0.000 0.232 0.624 0.060 NA
#> GSM1182238 2 0.4079 0.7906 0.000 0.812 0.020 0.060 NA
#> GSM1182239 2 0.2381 0.8018 0.000 0.908 0.004 0.052 NA
#> GSM1182240 2 0.2388 0.8052 0.000 0.900 0.000 0.028 NA
#> GSM1182241 2 0.2745 0.7839 0.000 0.896 0.024 0.052 NA
#> GSM1182242 3 0.3192 0.8331 0.000 0.112 0.848 0.000 NA
#> GSM1182243 3 0.3387 0.8346 0.000 0.100 0.852 0.028 NA
#> GSM1182244 3 0.6739 0.6297 0.000 0.176 0.456 0.012 NA
#> GSM1182245 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182246 4 0.3635 0.9026 0.248 0.000 0.004 0.748 NA
#> GSM1182247 3 0.3037 0.8340 0.000 0.100 0.864 0.004 NA
#> GSM1182248 3 0.3195 0.8340 0.000 0.100 0.856 0.004 NA
#> GSM1182249 3 0.6170 0.7104 0.000 0.140 0.652 0.048 NA
#> GSM1182250 3 0.4575 0.8172 0.000 0.116 0.784 0.036 NA
#> GSM1182251 1 0.3661 0.6910 0.724 0.000 0.000 0.000 NA
#> GSM1182252 3 0.3117 0.8339 0.000 0.100 0.860 0.004 NA
#> GSM1182253 3 0.3342 0.8350 0.000 0.100 0.848 0.004 NA
#> GSM1182254 3 0.3204 0.8350 0.000 0.100 0.860 0.016 NA
#> GSM1182255 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182256 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182257 4 0.5129 0.8947 0.248 0.000 0.052 0.684 NA
#> GSM1182258 4 0.3635 0.9026 0.248 0.000 0.004 0.748 NA
#> GSM1182259 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182260 3 0.4411 0.8083 0.000 0.152 0.780 0.036 NA
#> GSM1182261 3 0.5361 0.7792 0.000 0.124 0.728 0.044 NA
#> GSM1182262 3 0.4364 0.8214 0.000 0.104 0.796 0.024 NA
#> GSM1182263 1 0.3635 0.7184 0.748 0.000 0.004 0.000 NA
#> GSM1182264 3 0.5071 0.7711 0.000 0.192 0.724 0.048 NA
#> GSM1182265 3 0.5924 0.7558 0.000 0.104 0.688 0.072 NA
#> GSM1182266 3 0.4025 0.8257 0.000 0.124 0.812 0.036 NA
#> GSM1182267 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182268 1 0.0404 0.8713 0.988 0.000 0.000 0.000 NA
#> GSM1182269 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182270 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182271 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182272 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182273 3 0.3561 0.8346 0.000 0.100 0.844 0.032 NA
#> GSM1182275 3 0.3405 0.8332 0.000 0.108 0.848 0.024 NA
#> GSM1182276 2 0.2047 0.7903 0.000 0.928 0.040 0.020 NA
#> GSM1182277 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182278 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182279 1 0.3561 0.7059 0.740 0.000 0.000 0.000 NA
#> GSM1182280 1 0.3452 0.7205 0.756 0.000 0.000 0.000 NA
#> GSM1182281 4 0.7193 0.5386 0.348 0.000 0.044 0.448 NA
#> GSM1182282 1 0.2782 0.8542 0.880 0.000 0.048 0.000 NA
#> GSM1182283 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182284 1 0.2708 0.8547 0.884 0.000 0.044 0.000 NA
#> GSM1182285 3 0.5898 0.7000 0.000 0.100 0.548 0.004 NA
#> GSM1182286 2 0.2304 0.8053 0.000 0.908 0.000 0.048 NA
#> GSM1182287 3 0.5283 0.4574 0.000 0.384 0.572 0.012 NA
#> GSM1182288 3 0.3299 0.8343 0.000 0.108 0.848 0.004 NA
#> GSM1182289 1 0.3586 0.7030 0.736 0.000 0.000 0.000 NA
#> GSM1182290 1 0.2329 0.8197 0.876 0.000 0.000 0.000 NA
#> GSM1182291 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182274 3 0.3374 0.8340 0.000 0.100 0.852 0.032 NA
#> GSM1182292 2 0.1750 0.7999 0.000 0.936 0.000 0.028 NA
#> GSM1182293 2 0.5753 0.7215 0.000 0.660 0.016 0.136 NA
#> GSM1182294 2 0.5911 0.7150 0.000 0.640 0.016 0.140 NA
#> GSM1182295 2 0.2968 0.8095 0.000 0.872 0.008 0.028 NA
#> GSM1182296 2 0.1907 0.8010 0.000 0.928 0.000 0.028 NA
#> GSM1182298 3 0.5845 0.6964 0.000 0.108 0.540 0.000 NA
#> GSM1182299 2 0.1904 0.8017 0.000 0.936 0.020 0.028 NA
#> GSM1182300 2 0.3012 0.8039 0.000 0.860 0.000 0.036 NA
#> GSM1182301 2 0.1818 0.8015 0.000 0.932 0.000 0.024 NA
#> GSM1182303 2 0.2269 0.7934 0.000 0.920 0.032 0.020 NA
#> GSM1182304 1 0.3586 0.7099 0.736 0.000 0.000 0.000 NA
#> GSM1182305 4 0.6723 0.6554 0.300 0.000 0.000 0.420 NA
#> GSM1182306 4 0.5219 0.8940 0.248 0.000 0.052 0.680 NA
#> GSM1182307 2 0.1893 0.8031 0.000 0.928 0.000 0.024 NA
#> GSM1182309 2 0.5777 0.7185 0.000 0.648 0.012 0.136 NA
#> GSM1182312 2 0.6721 0.6827 0.000 0.556 0.032 0.172 NA
#> GSM1182314 4 0.3635 0.9026 0.248 0.000 0.004 0.748 NA
#> GSM1182316 2 0.6632 0.6812 0.000 0.568 0.036 0.144 NA
#> GSM1182318 2 0.3265 0.8050 0.000 0.856 0.008 0.040 NA
#> GSM1182319 2 0.6150 0.7019 0.000 0.612 0.016 0.164 NA
#> GSM1182320 2 0.6679 0.6809 0.000 0.568 0.040 0.144 NA
#> GSM1182321 2 0.7798 0.5403 0.000 0.480 0.140 0.164 NA
#> GSM1182322 2 0.6056 0.7040 0.000 0.616 0.012 0.164 NA
#> GSM1182324 2 0.8150 0.4472 0.000 0.412 0.188 0.152 NA
#> GSM1182297 2 0.2522 0.8059 0.000 0.896 0.000 0.052 NA
#> GSM1182302 4 0.5978 0.8826 0.248 0.000 0.048 0.636 NA
#> GSM1182308 2 0.3054 0.7838 0.000 0.880 0.032 0.028 NA
#> GSM1182310 2 0.6525 0.6834 0.000 0.576 0.028 0.156 NA
#> GSM1182311 1 0.0566 0.8711 0.984 0.000 0.004 0.000 NA
#> GSM1182313 4 0.3480 0.9028 0.248 0.000 0.000 0.752 NA
#> GSM1182315 2 0.4779 0.7811 0.000 0.716 0.000 0.084 NA
#> GSM1182317 2 0.5553 0.7269 0.000 0.668 0.008 0.136 NA
#> GSM1182323 1 0.0404 0.8713 0.988 0.000 0.000 0.000 NA
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 4 0.7203 0.716 0.240 0.000 0.008 0.468 0.148 0.136
#> GSM1182187 4 0.6335 0.827 0.188 0.000 0.016 0.600 0.124 0.072
#> GSM1182188 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182189 1 0.0653 0.843 0.980 0.000 0.004 0.000 0.012 0.004
#> GSM1182190 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182191 4 0.7401 0.649 0.240 0.000 0.004 0.412 0.132 0.212
#> GSM1182192 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182193 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182194 6 0.4419 0.936 0.000 0.032 0.384 0.000 0.000 0.584
#> GSM1182195 6 0.4845 0.911 0.000 0.032 0.392 0.000 0.016 0.560
#> GSM1182196 2 0.7023 -0.210 0.000 0.464 0.192 0.036 0.276 0.032
#> GSM1182197 3 0.6814 0.360 0.000 0.324 0.492 0.080 0.040 0.064
#> GSM1182198 6 0.4553 0.934 0.000 0.032 0.384 0.000 0.004 0.580
#> GSM1182199 6 0.4400 0.937 0.000 0.032 0.376 0.000 0.000 0.592
#> GSM1182200 2 0.2920 0.642 0.000 0.880 0.040 0.028 0.012 0.040
#> GSM1182201 3 0.5604 0.495 0.000 0.248 0.632 0.056 0.012 0.052
#> GSM1182202 4 0.6498 0.823 0.188 0.000 0.024 0.592 0.120 0.076
#> GSM1182203 4 0.6077 0.837 0.188 0.000 0.020 0.628 0.104 0.060
#> GSM1182204 4 0.6266 0.831 0.188 0.000 0.020 0.612 0.108 0.072
#> GSM1182205 3 0.4936 0.633 0.000 0.036 0.748 0.032 0.104 0.080
#> GSM1182206 3 0.5709 0.588 0.000 0.064 0.676 0.096 0.144 0.020
#> GSM1182207 1 0.2199 0.810 0.892 0.000 0.000 0.000 0.020 0.088
#> GSM1182208 1 0.2199 0.810 0.892 0.000 0.000 0.000 0.020 0.088
#> GSM1182209 2 0.1845 0.671 0.000 0.920 0.000 0.000 0.052 0.028
#> GSM1182210 2 0.1843 0.655 0.000 0.912 0.000 0.004 0.080 0.004
#> GSM1182211 2 0.1572 0.667 0.000 0.936 0.000 0.000 0.036 0.028
#> GSM1182212 2 0.2279 0.662 0.000 0.912 0.012 0.024 0.012 0.040
#> GSM1182213 2 0.1307 0.678 0.000 0.952 0.000 0.008 0.032 0.008
#> GSM1182214 2 0.2001 0.674 0.000 0.920 0.000 0.016 0.044 0.020
#> GSM1182215 3 0.4652 0.639 0.000 0.036 0.752 0.080 0.124 0.008
#> GSM1182216 2 0.6631 0.238 0.000 0.552 0.072 0.116 0.240 0.020
#> GSM1182217 4 0.7271 0.728 0.240 0.000 0.016 0.472 0.156 0.116
#> GSM1182218 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182219 2 0.2749 0.667 0.000 0.884 0.004 0.044 0.048 0.020
#> GSM1182220 2 0.1787 0.673 0.000 0.932 0.020 0.000 0.016 0.032
#> GSM1182221 5 0.5857 0.585 0.000 0.376 0.008 0.092 0.504 0.020
#> GSM1182222 2 0.6737 0.223 0.000 0.540 0.080 0.116 0.244 0.020
#> GSM1182223 3 0.3394 0.668 0.000 0.104 0.832 0.028 0.000 0.036
#> GSM1182224 6 0.5046 0.902 0.000 0.032 0.384 0.000 0.028 0.556
#> GSM1182225 2 0.6592 0.264 0.000 0.560 0.072 0.116 0.232 0.020
#> GSM1182226 2 0.6779 0.172 0.000 0.528 0.076 0.120 0.256 0.020
#> GSM1182227 1 0.3023 0.822 0.836 0.000 0.000 0.000 0.120 0.044
#> GSM1182228 3 0.4889 0.606 0.000 0.152 0.736 0.024 0.040 0.048
#> GSM1182229 3 0.1575 0.691 0.000 0.032 0.936 0.000 0.000 0.032
#> GSM1182230 3 0.3044 0.688 0.000 0.032 0.876 0.024 0.032 0.036
#> GSM1182231 3 0.7420 0.345 0.000 0.212 0.468 0.132 0.168 0.020
#> GSM1182232 1 0.0000 0.844 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0508 0.844 0.984 0.000 0.000 0.000 0.012 0.004
#> GSM1182234 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182235 2 0.5623 0.484 0.000 0.684 0.032 0.080 0.156 0.048
#> GSM1182236 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182237 3 0.7022 0.464 0.000 0.152 0.568 0.100 0.124 0.056
#> GSM1182238 2 0.6017 0.267 0.000 0.592 0.036 0.092 0.260 0.020
#> GSM1182239 2 0.4873 0.585 0.000 0.752 0.032 0.056 0.116 0.044
#> GSM1182240 2 0.2760 0.664 0.000 0.868 0.004 0.016 0.100 0.012
#> GSM1182241 2 0.4075 0.626 0.000 0.816 0.048 0.056 0.044 0.036
#> GSM1182242 3 0.2322 0.671 0.000 0.036 0.896 0.000 0.004 0.064
#> GSM1182243 3 0.2643 0.709 0.000 0.036 0.888 0.036 0.040 0.000
#> GSM1182244 6 0.5253 0.794 0.000 0.084 0.280 0.000 0.020 0.616
#> GSM1182245 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182246 4 0.2838 0.869 0.188 0.000 0.004 0.808 0.000 0.000
#> GSM1182247 3 0.2307 0.666 0.000 0.032 0.896 0.000 0.004 0.068
#> GSM1182248 3 0.2259 0.676 0.000 0.032 0.908 0.000 0.020 0.040
#> GSM1182249 3 0.5689 0.598 0.000 0.076 0.660 0.036 0.196 0.032
#> GSM1182250 3 0.4065 0.685 0.000 0.040 0.784 0.048 0.128 0.000
#> GSM1182251 1 0.4808 0.582 0.636 0.000 0.000 0.000 0.092 0.272
#> GSM1182252 3 0.2249 0.664 0.000 0.032 0.900 0.000 0.004 0.064
#> GSM1182253 3 0.3136 0.694 0.000 0.036 0.868 0.012 0.044 0.040
#> GSM1182254 3 0.1944 0.707 0.000 0.036 0.924 0.024 0.016 0.000
#> GSM1182255 4 0.2838 0.869 0.188 0.000 0.004 0.808 0.000 0.000
#> GSM1182256 4 0.2838 0.869 0.188 0.000 0.004 0.808 0.000 0.000
#> GSM1182257 4 0.4678 0.858 0.188 0.000 0.024 0.720 0.064 0.004
#> GSM1182258 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182259 4 0.2838 0.869 0.188 0.000 0.004 0.808 0.000 0.000
#> GSM1182260 3 0.4199 0.686 0.000 0.060 0.808 0.040 0.052 0.040
#> GSM1182261 3 0.5861 0.567 0.000 0.060 0.660 0.116 0.144 0.020
#> GSM1182262 3 0.4527 0.642 0.000 0.036 0.764 0.080 0.112 0.008
#> GSM1182263 1 0.4455 0.658 0.688 0.000 0.000 0.000 0.080 0.232
#> GSM1182264 3 0.4865 0.643 0.000 0.096 0.756 0.036 0.036 0.076
#> GSM1182265 3 0.5140 0.584 0.000 0.040 0.680 0.040 0.224 0.016
#> GSM1182266 3 0.3624 0.676 0.000 0.048 0.840 0.032 0.020 0.060
#> GSM1182267 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182268 1 0.0653 0.843 0.980 0.000 0.004 0.000 0.012 0.004
#> GSM1182269 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182270 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182271 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182272 4 0.2838 0.869 0.188 0.000 0.004 0.808 0.000 0.000
#> GSM1182273 3 0.2889 0.696 0.000 0.032 0.884 0.032 0.032 0.020
#> GSM1182275 3 0.3140 0.684 0.000 0.040 0.864 0.028 0.008 0.060
#> GSM1182276 2 0.2341 0.659 0.000 0.908 0.024 0.016 0.008 0.044
#> GSM1182277 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182278 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182279 1 0.4680 0.602 0.652 0.000 0.000 0.000 0.084 0.264
#> GSM1182280 1 0.4229 0.665 0.712 0.000 0.000 0.000 0.068 0.220
#> GSM1182281 4 0.7113 0.484 0.280 0.000 0.004 0.448 0.116 0.152
#> GSM1182282 1 0.3023 0.822 0.836 0.000 0.000 0.000 0.120 0.044
#> GSM1182283 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182284 1 0.2979 0.823 0.840 0.000 0.000 0.000 0.116 0.044
#> GSM1182285 6 0.4553 0.936 0.000 0.032 0.384 0.000 0.004 0.580
#> GSM1182286 2 0.4579 0.604 0.000 0.776 0.024 0.060 0.092 0.048
#> GSM1182287 3 0.4755 0.457 0.000 0.288 0.656 0.028 0.020 0.008
#> GSM1182288 3 0.2469 0.673 0.000 0.032 0.900 0.008 0.012 0.048
#> GSM1182289 1 0.4700 0.599 0.648 0.000 0.000 0.000 0.084 0.268
#> GSM1182290 1 0.2510 0.797 0.872 0.000 0.000 0.000 0.028 0.100
#> GSM1182291 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182274 3 0.2925 0.704 0.000 0.036 0.880 0.040 0.032 0.012
#> GSM1182292 2 0.2314 0.659 0.000 0.900 0.000 0.008 0.056 0.036
#> GSM1182293 5 0.4279 0.739 0.000 0.436 0.000 0.004 0.548 0.012
#> GSM1182294 5 0.4018 0.764 0.000 0.412 0.000 0.008 0.580 0.000
#> GSM1182295 2 0.3298 0.462 0.000 0.756 0.000 0.008 0.236 0.000
#> GSM1182296 2 0.2164 0.657 0.000 0.900 0.000 0.000 0.068 0.032
#> GSM1182298 6 0.4400 0.937 0.000 0.032 0.376 0.000 0.000 0.592
#> GSM1182299 2 0.3922 0.649 0.000 0.824 0.032 0.064 0.044 0.036
#> GSM1182300 2 0.3858 0.464 0.000 0.732 0.000 0.004 0.236 0.028
#> GSM1182301 2 0.2189 0.666 0.000 0.904 0.000 0.004 0.060 0.032
#> GSM1182303 2 0.2632 0.657 0.000 0.896 0.020 0.016 0.028 0.040
#> GSM1182304 1 0.4707 0.619 0.660 0.000 0.000 0.000 0.096 0.244
#> GSM1182305 4 0.7182 0.594 0.248 0.000 0.000 0.388 0.092 0.272
#> GSM1182306 4 0.4786 0.858 0.188 0.000 0.024 0.716 0.064 0.008
#> GSM1182307 2 0.1984 0.662 0.000 0.912 0.000 0.000 0.056 0.032
#> GSM1182309 5 0.4338 0.732 0.000 0.420 0.000 0.004 0.560 0.016
#> GSM1182312 5 0.5074 0.702 0.000 0.372 0.004 0.036 0.568 0.020
#> GSM1182314 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182316 5 0.4102 0.757 0.000 0.356 0.004 0.012 0.628 0.000
#> GSM1182318 2 0.3545 0.408 0.000 0.748 0.000 0.008 0.236 0.008
#> GSM1182319 5 0.4388 0.700 0.000 0.400 0.000 0.000 0.572 0.028
#> GSM1182320 5 0.3782 0.764 0.000 0.360 0.004 0.000 0.636 0.000
#> GSM1182321 5 0.5912 0.603 0.000 0.276 0.112 0.000 0.568 0.044
#> GSM1182322 5 0.4388 0.700 0.000 0.400 0.000 0.000 0.572 0.028
#> GSM1182324 5 0.5537 0.583 0.000 0.216 0.140 0.024 0.620 0.000
#> GSM1182297 2 0.5081 0.543 0.000 0.728 0.024 0.060 0.140 0.048
#> GSM1182302 4 0.6416 0.827 0.188 0.000 0.024 0.600 0.116 0.072
#> GSM1182308 2 0.2796 0.636 0.000 0.876 0.016 0.020 0.080 0.008
#> GSM1182310 5 0.3782 0.770 0.000 0.360 0.004 0.000 0.636 0.000
#> GSM1182311 1 0.0748 0.843 0.976 0.000 0.004 0.000 0.016 0.004
#> GSM1182313 4 0.2697 0.870 0.188 0.000 0.000 0.812 0.000 0.000
#> GSM1182315 2 0.5188 -0.102 0.000 0.544 0.008 0.052 0.388 0.008
#> GSM1182317 5 0.4467 0.693 0.000 0.464 0.000 0.000 0.508 0.028
#> GSM1182323 1 0.0653 0.843 0.980 0.000 0.004 0.000 0.012 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:kmeans 139 7.73e-02 1.000 2
#> CV:kmeans 126 1.08e-06 0.422 3
#> CV:kmeans 136 2.82e-06 0.597 4
#> CV:kmeans 134 1.16e-06 0.564 5
#> CV:kmeans 122 4.08e-09 0.768 6
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 46361 rows and 139 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 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.941 0.948 0.972 0.3849 0.815 0.645
#> 4 4 0.800 0.912 0.894 0.1083 0.924 0.774
#> 5 5 0.792 0.811 0.828 0.0592 0.958 0.843
#> 6 6 0.777 0.775 0.825 0.0428 0.955 0.806
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 1.000 1 0.000 0.000
#> GSM1182187 1 0.0000 1.000 1 0.000 0.000
#> GSM1182188 1 0.0000 1.000 1 0.000 0.000
#> GSM1182189 1 0.0000 1.000 1 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1 0.000 0.000
#> GSM1182191 1 0.0000 1.000 1 0.000 0.000
#> GSM1182192 1 0.0000 1.000 1 0.000 0.000
#> GSM1182193 1 0.0000 1.000 1 0.000 0.000
#> GSM1182194 3 0.0000 0.947 0 0.000 1.000
#> GSM1182195 3 0.0000 0.947 0 0.000 1.000
#> GSM1182196 2 0.0000 0.957 0 1.000 0.000
#> GSM1182197 2 0.0592 0.956 0 0.988 0.012
#> GSM1182198 3 0.0237 0.946 0 0.004 0.996
#> GSM1182199 3 0.0237 0.946 0 0.004 0.996
#> GSM1182200 2 0.2356 0.925 0 0.928 0.072
#> GSM1182201 3 0.6267 0.209 0 0.452 0.548
#> GSM1182202 1 0.0000 1.000 1 0.000 0.000
#> GSM1182203 1 0.0000 1.000 1 0.000 0.000
#> GSM1182204 1 0.0000 1.000 1 0.000 0.000
#> GSM1182205 3 0.0424 0.945 0 0.008 0.992
#> GSM1182206 3 0.0237 0.945 0 0.004 0.996
#> GSM1182207 1 0.0000 1.000 1 0.000 0.000
#> GSM1182208 1 0.0000 1.000 1 0.000 0.000
#> GSM1182209 2 0.0000 0.957 0 1.000 0.000
#> GSM1182210 2 0.0237 0.958 0 0.996 0.004
#> GSM1182211 2 0.0237 0.958 0 0.996 0.004
#> GSM1182212 2 0.0424 0.957 0 0.992 0.008
#> GSM1182213 2 0.0237 0.958 0 0.996 0.004
#> GSM1182214 2 0.0237 0.958 0 0.996 0.004
#> GSM1182215 3 0.0000 0.947 0 0.000 1.000
#> GSM1182216 2 0.4121 0.837 0 0.832 0.168
#> GSM1182217 1 0.0000 1.000 1 0.000 0.000
#> GSM1182218 1 0.0000 1.000 1 0.000 0.000
#> GSM1182219 2 0.0237 0.958 0 0.996 0.004
#> GSM1182220 2 0.1031 0.952 0 0.976 0.024
#> GSM1182221 2 0.2356 0.925 0 0.928 0.072
#> GSM1182222 2 0.4452 0.810 0 0.808 0.192
#> GSM1182223 3 0.0424 0.944 0 0.008 0.992
#> GSM1182224 3 0.0000 0.947 0 0.000 1.000
#> GSM1182225 2 0.4121 0.837 0 0.832 0.168
#> GSM1182226 2 0.4062 0.841 0 0.836 0.164
#> GSM1182227 1 0.0000 1.000 1 0.000 0.000
#> GSM1182228 3 0.3267 0.872 0 0.116 0.884
#> GSM1182229 3 0.0000 0.947 0 0.000 1.000
#> GSM1182230 3 0.0000 0.947 0 0.000 1.000
#> GSM1182231 2 0.4504 0.805 0 0.804 0.196
#> GSM1182232 1 0.0000 1.000 1 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1 0.000 0.000
#> GSM1182235 2 0.0000 0.957 0 1.000 0.000
#> GSM1182236 1 0.0000 1.000 1 0.000 0.000
#> GSM1182237 3 0.4504 0.790 0 0.196 0.804
#> GSM1182238 2 0.1031 0.952 0 0.976 0.024
#> GSM1182239 2 0.0000 0.957 0 1.000 0.000
#> GSM1182240 2 0.0747 0.954 0 0.984 0.016
#> GSM1182241 2 0.0000 0.957 0 1.000 0.000
#> GSM1182242 3 0.1753 0.921 0 0.048 0.952
#> GSM1182243 3 0.0000 0.947 0 0.000 1.000
#> GSM1182244 3 0.3412 0.863 0 0.124 0.876
#> GSM1182245 1 0.0000 1.000 1 0.000 0.000
#> GSM1182246 1 0.0000 1.000 1 0.000 0.000
#> GSM1182247 3 0.0000 0.947 0 0.000 1.000
#> GSM1182248 3 0.0000 0.947 0 0.000 1.000
#> GSM1182249 3 0.4399 0.759 0 0.188 0.812
#> GSM1182250 3 0.0000 0.947 0 0.000 1.000
#> GSM1182251 1 0.0000 1.000 1 0.000 0.000
#> GSM1182252 3 0.0000 0.947 0 0.000 1.000
#> GSM1182253 3 0.0000 0.947 0 0.000 1.000
#> GSM1182254 3 0.0000 0.947 0 0.000 1.000
#> GSM1182255 1 0.0000 1.000 1 0.000 0.000
#> GSM1182256 1 0.0000 1.000 1 0.000 0.000
#> GSM1182257 1 0.0000 1.000 1 0.000 0.000
#> GSM1182258 1 0.0000 1.000 1 0.000 0.000
#> GSM1182259 1 0.0000 1.000 1 0.000 0.000
#> GSM1182260 3 0.3551 0.858 0 0.132 0.868
#> GSM1182261 3 0.0000 0.947 0 0.000 1.000
#> GSM1182262 3 0.0000 0.947 0 0.000 1.000
#> GSM1182263 1 0.0000 1.000 1 0.000 0.000
#> GSM1182264 3 0.4062 0.825 0 0.164 0.836
#> GSM1182265 3 0.0000 0.947 0 0.000 1.000
#> GSM1182266 3 0.2066 0.913 0 0.060 0.940
#> GSM1182267 1 0.0000 1.000 1 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1 0.000 0.000
#> GSM1182271 1 0.0000 1.000 1 0.000 0.000
#> GSM1182272 1 0.0000 1.000 1 0.000 0.000
#> GSM1182273 3 0.0000 0.947 0 0.000 1.000
#> GSM1182275 3 0.0000 0.947 0 0.000 1.000
#> GSM1182276 2 0.0424 0.957 0 0.992 0.008
#> GSM1182277 1 0.0000 1.000 1 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1 0.000 0.000
#> GSM1182279 1 0.0000 1.000 1 0.000 0.000
#> GSM1182280 1 0.0000 1.000 1 0.000 0.000
#> GSM1182281 1 0.0000 1.000 1 0.000 0.000
#> GSM1182282 1 0.0000 1.000 1 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1 0.000 0.000
#> GSM1182285 3 0.0000 0.947 0 0.000 1.000
#> GSM1182286 2 0.0000 0.957 0 1.000 0.000
#> GSM1182287 3 0.5733 0.494 0 0.324 0.676
#> GSM1182288 3 0.0237 0.946 0 0.004 0.996
#> GSM1182289 1 0.0000 1.000 1 0.000 0.000
#> GSM1182290 1 0.0000 1.000 1 0.000 0.000
#> GSM1182291 1 0.0000 1.000 1 0.000 0.000
#> GSM1182274 3 0.0000 0.947 0 0.000 1.000
#> GSM1182292 2 0.0000 0.957 0 1.000 0.000
#> GSM1182293 2 0.0237 0.958 0 0.996 0.004
#> GSM1182294 2 0.0237 0.958 0 0.996 0.004
#> GSM1182295 2 0.0237 0.958 0 0.996 0.004
#> GSM1182296 2 0.0000 0.957 0 1.000 0.000
#> GSM1182298 3 0.0237 0.946 0 0.004 0.996
#> GSM1182299 2 0.0237 0.958 0 0.996 0.004
#> GSM1182300 2 0.0000 0.957 0 1.000 0.000
#> GSM1182301 2 0.0000 0.957 0 1.000 0.000
#> GSM1182303 2 0.1753 0.940 0 0.952 0.048
#> GSM1182304 1 0.0000 1.000 1 0.000 0.000
#> GSM1182305 1 0.0000 1.000 1 0.000 0.000
#> GSM1182306 1 0.0000 1.000 1 0.000 0.000
#> GSM1182307 2 0.0000 0.957 0 1.000 0.000
#> GSM1182309 2 0.0237 0.958 0 0.996 0.004
#> GSM1182312 2 0.1753 0.940 0 0.952 0.048
#> GSM1182314 1 0.0000 1.000 1 0.000 0.000
#> GSM1182316 2 0.2356 0.925 0 0.928 0.072
#> GSM1182318 2 0.0237 0.958 0 0.996 0.004
#> GSM1182319 2 0.0000 0.957 0 1.000 0.000
#> GSM1182320 2 0.2356 0.925 0 0.928 0.072
#> GSM1182321 2 0.4002 0.804 0 0.840 0.160
#> GSM1182322 2 0.0000 0.957 0 1.000 0.000
#> GSM1182324 2 0.5327 0.693 0 0.728 0.272
#> GSM1182297 2 0.0000 0.957 0 1.000 0.000
#> GSM1182302 1 0.0000 1.000 1 0.000 0.000
#> GSM1182308 2 0.2711 0.913 0 0.912 0.088
#> GSM1182310 2 0.1411 0.946 0 0.964 0.036
#> GSM1182311 1 0.0000 1.000 1 0.000 0.000
#> GSM1182313 1 0.0000 1.000 1 0.000 0.000
#> GSM1182315 2 0.0747 0.954 0 0.984 0.016
#> GSM1182317 2 0.0237 0.958 0 0.996 0.004
#> GSM1182323 1 0.0000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182187 4 0.3311 0.730 0.172 0.000 0.000 0.828
#> GSM1182188 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182190 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182191 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182192 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182193 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182194 3 0.0592 0.919 0.016 0.000 0.984 0.000
#> GSM1182195 3 0.0921 0.920 0.028 0.000 0.972 0.000
#> GSM1182196 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182197 2 0.1474 0.920 0.000 0.948 0.052 0.000
#> GSM1182198 3 0.0592 0.919 0.016 0.000 0.984 0.000
#> GSM1182199 3 0.0592 0.919 0.016 0.000 0.984 0.000
#> GSM1182200 2 0.1489 0.923 0.004 0.952 0.044 0.000
#> GSM1182201 3 0.4898 0.314 0.000 0.416 0.584 0.000
#> GSM1182202 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182203 4 0.3975 0.585 0.240 0.000 0.000 0.760
#> GSM1182204 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182205 3 0.3355 0.870 0.160 0.004 0.836 0.000
#> GSM1182206 3 0.3856 0.862 0.136 0.032 0.832 0.000
#> GSM1182207 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182208 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182209 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182210 2 0.0336 0.934 0.008 0.992 0.000 0.000
#> GSM1182211 2 0.0000 0.934 0.000 1.000 0.000 0.000
#> GSM1182212 2 0.0000 0.934 0.000 1.000 0.000 0.000
#> GSM1182213 2 0.0188 0.934 0.004 0.996 0.000 0.000
#> GSM1182214 2 0.0336 0.934 0.008 0.992 0.000 0.000
#> GSM1182215 3 0.3324 0.872 0.136 0.012 0.852 0.000
#> GSM1182216 2 0.3760 0.881 0.136 0.836 0.028 0.000
#> GSM1182217 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182218 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182219 2 0.0188 0.934 0.004 0.996 0.000 0.000
#> GSM1182220 2 0.0376 0.934 0.004 0.992 0.004 0.000
#> GSM1182221 2 0.3377 0.888 0.140 0.848 0.012 0.000
#> GSM1182222 2 0.3856 0.880 0.136 0.832 0.032 0.000
#> GSM1182223 3 0.0336 0.921 0.000 0.008 0.992 0.000
#> GSM1182224 3 0.1022 0.920 0.032 0.000 0.968 0.000
#> GSM1182225 2 0.3760 0.881 0.136 0.836 0.028 0.000
#> GSM1182226 2 0.3760 0.881 0.136 0.836 0.028 0.000
#> GSM1182227 4 0.0188 0.966 0.004 0.000 0.000 0.996
#> GSM1182228 3 0.3758 0.854 0.048 0.104 0.848 0.000
#> GSM1182229 3 0.0000 0.920 0.000 0.000 1.000 0.000
#> GSM1182230 3 0.0469 0.921 0.012 0.000 0.988 0.000
#> GSM1182231 2 0.4440 0.863 0.136 0.804 0.060 0.000
#> GSM1182232 1 0.3726 0.970 0.788 0.000 0.000 0.212
#> GSM1182233 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182234 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182235 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182236 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182237 3 0.4436 0.819 0.052 0.148 0.800 0.000
#> GSM1182238 2 0.3032 0.896 0.124 0.868 0.008 0.000
#> GSM1182239 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182240 2 0.3591 0.899 0.168 0.824 0.008 0.000
#> GSM1182241 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182242 3 0.0937 0.914 0.012 0.012 0.976 0.000
#> GSM1182243 3 0.0469 0.921 0.012 0.000 0.988 0.000
#> GSM1182244 3 0.3581 0.860 0.032 0.116 0.852 0.000
#> GSM1182245 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182246 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0000 0.920 0.000 0.000 1.000 0.000
#> GSM1182248 3 0.0469 0.921 0.012 0.000 0.988 0.000
#> GSM1182249 3 0.5609 0.711 0.088 0.200 0.712 0.000
#> GSM1182250 3 0.3554 0.868 0.136 0.020 0.844 0.000
#> GSM1182251 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182252 3 0.0000 0.920 0.000 0.000 1.000 0.000
#> GSM1182253 3 0.1938 0.909 0.052 0.012 0.936 0.000
#> GSM1182254 3 0.0469 0.921 0.012 0.000 0.988 0.000
#> GSM1182255 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182258 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.1733 0.905 0.028 0.024 0.948 0.000
#> GSM1182261 3 0.3554 0.868 0.136 0.020 0.844 0.000
#> GSM1182262 3 0.3271 0.875 0.132 0.012 0.856 0.000
#> GSM1182263 1 0.4933 0.602 0.568 0.000 0.000 0.432
#> GSM1182264 3 0.3934 0.845 0.048 0.116 0.836 0.000
#> GSM1182265 3 0.1975 0.910 0.048 0.016 0.936 0.000
#> GSM1182266 3 0.1182 0.912 0.016 0.016 0.968 0.000
#> GSM1182267 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182268 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182269 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182270 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182271 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0707 0.920 0.020 0.000 0.980 0.000
#> GSM1182275 3 0.0188 0.921 0.000 0.004 0.996 0.000
#> GSM1182276 2 0.0188 0.934 0.000 0.996 0.004 0.000
#> GSM1182277 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182278 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182279 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182280 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182281 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182282 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182283 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182284 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182285 3 0.0592 0.919 0.016 0.000 0.984 0.000
#> GSM1182286 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182287 3 0.5343 0.503 0.028 0.316 0.656 0.000
#> GSM1182288 3 0.0188 0.921 0.004 0.000 0.996 0.000
#> GSM1182289 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182290 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182291 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0000 0.920 0.000 0.000 1.000 0.000
#> GSM1182292 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182293 2 0.0188 0.934 0.004 0.996 0.000 0.000
#> GSM1182294 2 0.1302 0.929 0.044 0.956 0.000 0.000
#> GSM1182295 2 0.0469 0.934 0.012 0.988 0.000 0.000
#> GSM1182296 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182298 3 0.0592 0.919 0.016 0.000 0.984 0.000
#> GSM1182299 2 0.0188 0.934 0.004 0.996 0.000 0.000
#> GSM1182300 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182301 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182303 2 0.1489 0.928 0.044 0.952 0.004 0.000
#> GSM1182304 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182305 1 0.4977 0.530 0.540 0.000 0.000 0.460
#> GSM1182306 4 0.3311 0.730 0.172 0.000 0.000 0.828
#> GSM1182307 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182309 2 0.0817 0.933 0.024 0.976 0.000 0.000
#> GSM1182312 2 0.3324 0.890 0.136 0.852 0.012 0.000
#> GSM1182314 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.3377 0.888 0.140 0.848 0.012 0.000
#> GSM1182318 2 0.0336 0.934 0.008 0.992 0.000 0.000
#> GSM1182319 2 0.1474 0.928 0.052 0.948 0.000 0.000
#> GSM1182320 2 0.3377 0.888 0.140 0.848 0.012 0.000
#> GSM1182321 2 0.4578 0.787 0.052 0.788 0.160 0.000
#> GSM1182322 2 0.1474 0.928 0.052 0.948 0.000 0.000
#> GSM1182324 2 0.5266 0.804 0.140 0.752 0.108 0.000
#> GSM1182297 2 0.1389 0.929 0.048 0.952 0.000 0.000
#> GSM1182302 1 0.3688 0.973 0.792 0.000 0.000 0.208
#> GSM1182308 2 0.3324 0.889 0.136 0.852 0.012 0.000
#> GSM1182310 2 0.3324 0.890 0.136 0.852 0.012 0.000
#> GSM1182311 1 0.3649 0.973 0.796 0.000 0.000 0.204
#> GSM1182313 4 0.0000 0.970 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.3764 0.896 0.172 0.816 0.012 0.000
#> GSM1182317 2 0.0188 0.934 0.004 0.996 0.000 0.000
#> GSM1182323 1 0.3688 0.973 0.792 0.000 0.000 0.208
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182187 4 0.4030 0.610 0.352 0.000 0.000 0.648 0.000
#> GSM1182188 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182189 1 0.0579 0.960 0.984 0.000 0.000 0.008 0.008
#> GSM1182190 1 0.0579 0.960 0.984 0.000 0.000 0.008 0.008
#> GSM1182191 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182192 4 0.2561 0.954 0.096 0.000 0.000 0.884 0.020
#> GSM1182193 4 0.2561 0.954 0.096 0.000 0.000 0.884 0.020
#> GSM1182194 5 0.4300 0.901 0.000 0.000 0.476 0.000 0.524
#> GSM1182195 5 0.4278 0.879 0.000 0.000 0.452 0.000 0.548
#> GSM1182196 2 0.4450 0.831 0.000 0.764 0.004 0.080 0.152
#> GSM1182197 3 0.4906 0.257 0.000 0.480 0.496 0.000 0.024
#> GSM1182198 5 0.4302 0.898 0.000 0.000 0.480 0.000 0.520
#> GSM1182199 5 0.4300 0.901 0.000 0.000 0.476 0.000 0.524
#> GSM1182200 2 0.1710 0.833 0.000 0.940 0.040 0.004 0.016
#> GSM1182201 3 0.4371 0.416 0.000 0.344 0.644 0.000 0.012
#> GSM1182202 1 0.0609 0.954 0.980 0.000 0.000 0.020 0.000
#> GSM1182203 4 0.4045 0.592 0.356 0.000 0.000 0.644 0.000
#> GSM1182204 1 0.1043 0.943 0.960 0.000 0.000 0.040 0.000
#> GSM1182205 5 0.4415 0.515 0.000 0.004 0.444 0.000 0.552
#> GSM1182206 3 0.3656 0.632 0.000 0.020 0.784 0.000 0.196
#> GSM1182207 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182208 1 0.0566 0.962 0.984 0.000 0.000 0.004 0.012
#> GSM1182209 2 0.2291 0.838 0.000 0.908 0.000 0.056 0.036
#> GSM1182210 2 0.1331 0.848 0.000 0.952 0.000 0.008 0.040
#> GSM1182211 2 0.0566 0.843 0.000 0.984 0.000 0.004 0.012
#> GSM1182212 2 0.0324 0.841 0.000 0.992 0.000 0.004 0.004
#> GSM1182213 2 0.0798 0.845 0.000 0.976 0.000 0.008 0.016
#> GSM1182214 2 0.1082 0.848 0.000 0.964 0.000 0.008 0.028
#> GSM1182215 3 0.3053 0.656 0.000 0.008 0.828 0.000 0.164
#> GSM1182216 2 0.4254 0.796 0.000 0.740 0.040 0.000 0.220
#> GSM1182217 1 0.0162 0.963 0.996 0.000 0.000 0.004 0.000
#> GSM1182218 1 0.0579 0.960 0.984 0.000 0.000 0.008 0.008
#> GSM1182219 2 0.0932 0.844 0.000 0.972 0.004 0.004 0.020
#> GSM1182220 2 0.0566 0.842 0.000 0.984 0.000 0.004 0.012
#> GSM1182221 2 0.4299 0.742 0.000 0.608 0.000 0.004 0.388
#> GSM1182222 2 0.4325 0.794 0.000 0.736 0.044 0.000 0.220
#> GSM1182223 3 0.2886 0.606 0.000 0.148 0.844 0.000 0.008
#> GSM1182224 5 0.4278 0.879 0.000 0.000 0.452 0.000 0.548
#> GSM1182225 2 0.4224 0.797 0.000 0.744 0.040 0.000 0.216
#> GSM1182226 2 0.4398 0.792 0.000 0.720 0.040 0.000 0.240
#> GSM1182227 4 0.2448 0.955 0.088 0.000 0.000 0.892 0.020
#> GSM1182228 3 0.5472 0.496 0.000 0.196 0.696 0.072 0.036
#> GSM1182229 3 0.0290 0.678 0.000 0.000 0.992 0.000 0.008
#> GSM1182230 3 0.1270 0.682 0.000 0.000 0.948 0.000 0.052
#> GSM1182231 3 0.6301 0.375 0.000 0.252 0.532 0.000 0.216
#> GSM1182232 1 0.0162 0.963 0.996 0.000 0.000 0.004 0.000
#> GSM1182233 1 0.0000 0.963 1.000 0.000 0.000 0.000 0.000
#> GSM1182234 4 0.2448 0.955 0.088 0.000 0.000 0.892 0.020
#> GSM1182235 2 0.3733 0.837 0.000 0.836 0.016 0.080 0.068
#> GSM1182236 1 0.0290 0.962 0.992 0.000 0.000 0.000 0.008
#> GSM1182237 3 0.5381 0.569 0.000 0.080 0.736 0.084 0.100
#> GSM1182238 2 0.3752 0.817 0.000 0.780 0.016 0.004 0.200
#> GSM1182239 2 0.3174 0.832 0.000 0.868 0.016 0.080 0.036
#> GSM1182240 2 0.3521 0.839 0.000 0.820 0.000 0.040 0.140
#> GSM1182241 2 0.3281 0.828 0.000 0.864 0.024 0.080 0.032
#> GSM1182242 3 0.1124 0.665 0.000 0.004 0.960 0.000 0.036
#> GSM1182243 3 0.1430 0.697 0.000 0.004 0.944 0.000 0.052
#> GSM1182244 5 0.6219 0.755 0.000 0.056 0.364 0.044 0.536
#> GSM1182245 4 0.2448 0.955 0.088 0.000 0.000 0.892 0.020
#> GSM1182246 4 0.1965 0.955 0.096 0.000 0.000 0.904 0.000
#> GSM1182247 3 0.0703 0.664 0.000 0.000 0.976 0.000 0.024
#> GSM1182248 3 0.1341 0.672 0.000 0.000 0.944 0.000 0.056
#> GSM1182249 3 0.4897 0.521 0.000 0.056 0.688 0.004 0.252
#> GSM1182250 3 0.3163 0.655 0.000 0.012 0.824 0.000 0.164
#> GSM1182251 1 0.0566 0.962 0.984 0.000 0.000 0.004 0.012
#> GSM1182252 3 0.0963 0.654 0.000 0.000 0.964 0.000 0.036
#> GSM1182253 3 0.2304 0.677 0.000 0.008 0.892 0.000 0.100
#> GSM1182254 3 0.0963 0.690 0.000 0.000 0.964 0.000 0.036
#> GSM1182255 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182256 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182257 4 0.1965 0.954 0.096 0.000 0.000 0.904 0.000
#> GSM1182258 4 0.1965 0.955 0.096 0.000 0.000 0.904 0.000
#> GSM1182259 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182260 3 0.2689 0.671 0.000 0.024 0.900 0.036 0.040
#> GSM1182261 3 0.3690 0.628 0.000 0.020 0.780 0.000 0.200
#> GSM1182262 3 0.2929 0.659 0.000 0.008 0.840 0.000 0.152
#> GSM1182263 1 0.4251 0.455 0.672 0.000 0.000 0.316 0.012
#> GSM1182264 3 0.3820 0.620 0.000 0.052 0.840 0.060 0.048
#> GSM1182265 3 0.3849 0.569 0.000 0.016 0.752 0.000 0.232
#> GSM1182266 3 0.2122 0.664 0.000 0.008 0.924 0.032 0.036
#> GSM1182267 4 0.2561 0.954 0.096 0.000 0.000 0.884 0.020
#> GSM1182268 1 0.0290 0.962 0.992 0.000 0.000 0.000 0.008
#> GSM1182269 1 0.0579 0.960 0.984 0.000 0.000 0.008 0.008
#> GSM1182270 1 0.0290 0.962 0.992 0.000 0.000 0.000 0.008
#> GSM1182271 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182272 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182273 3 0.1430 0.684 0.000 0.004 0.944 0.000 0.052
#> GSM1182275 3 0.1195 0.669 0.000 0.012 0.960 0.000 0.028
#> GSM1182276 2 0.0486 0.841 0.000 0.988 0.004 0.004 0.004
#> GSM1182277 4 0.2505 0.955 0.092 0.000 0.000 0.888 0.020
#> GSM1182278 4 0.2505 0.955 0.092 0.000 0.000 0.888 0.020
#> GSM1182279 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182280 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182281 4 0.2561 0.954 0.096 0.000 0.000 0.884 0.020
#> GSM1182282 4 0.2448 0.955 0.088 0.000 0.000 0.892 0.020
#> GSM1182283 4 0.2561 0.954 0.096 0.000 0.000 0.884 0.020
#> GSM1182284 4 0.2448 0.955 0.088 0.000 0.000 0.892 0.020
#> GSM1182285 5 0.4300 0.901 0.000 0.000 0.476 0.000 0.524
#> GSM1182286 2 0.3325 0.838 0.000 0.856 0.008 0.080 0.056
#> GSM1182287 3 0.4730 0.482 0.000 0.260 0.688 0.000 0.052
#> GSM1182288 3 0.1270 0.671 0.000 0.000 0.948 0.000 0.052
#> GSM1182289 1 0.0566 0.961 0.984 0.000 0.000 0.004 0.012
#> GSM1182290 1 0.0566 0.962 0.984 0.000 0.000 0.004 0.012
#> GSM1182291 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182274 3 0.0865 0.695 0.000 0.004 0.972 0.000 0.024
#> GSM1182292 2 0.2676 0.834 0.000 0.884 0.000 0.080 0.036
#> GSM1182293 2 0.3662 0.785 0.000 0.744 0.000 0.004 0.252
#> GSM1182294 2 0.4108 0.773 0.000 0.684 0.000 0.008 0.308
#> GSM1182295 2 0.2136 0.853 0.000 0.904 0.000 0.008 0.088
#> GSM1182296 2 0.2754 0.835 0.000 0.880 0.000 0.080 0.040
#> GSM1182298 5 0.4300 0.901 0.000 0.000 0.476 0.000 0.524
#> GSM1182299 2 0.0613 0.841 0.000 0.984 0.008 0.004 0.004
#> GSM1182300 2 0.3301 0.839 0.000 0.848 0.000 0.080 0.072
#> GSM1182301 2 0.2569 0.838 0.000 0.892 0.000 0.068 0.040
#> GSM1182303 2 0.1124 0.842 0.000 0.960 0.000 0.004 0.036
#> GSM1182304 1 0.0404 0.962 0.988 0.000 0.000 0.000 0.012
#> GSM1182305 1 0.3992 0.565 0.720 0.000 0.000 0.268 0.012
#> GSM1182306 4 0.3949 0.649 0.332 0.000 0.000 0.668 0.000
#> GSM1182307 2 0.2830 0.837 0.000 0.876 0.000 0.080 0.044
#> GSM1182309 2 0.4167 0.789 0.000 0.724 0.000 0.024 0.252
#> GSM1182312 2 0.4392 0.745 0.000 0.612 0.000 0.008 0.380
#> GSM1182314 4 0.1965 0.955 0.096 0.000 0.000 0.904 0.000
#> GSM1182316 2 0.4403 0.743 0.000 0.608 0.000 0.008 0.384
#> GSM1182318 2 0.2020 0.841 0.000 0.900 0.000 0.000 0.100
#> GSM1182319 2 0.5245 0.773 0.000 0.640 0.000 0.080 0.280
#> GSM1182320 2 0.4380 0.746 0.000 0.616 0.000 0.008 0.376
#> GSM1182321 2 0.7255 0.637 0.000 0.508 0.136 0.076 0.280
#> GSM1182322 2 0.5245 0.773 0.000 0.640 0.000 0.080 0.280
#> GSM1182324 2 0.6173 0.579 0.000 0.468 0.136 0.000 0.396
#> GSM1182297 2 0.3133 0.839 0.000 0.864 0.004 0.080 0.052
#> GSM1182302 1 0.0794 0.951 0.972 0.000 0.000 0.028 0.000
#> GSM1182308 2 0.2439 0.831 0.000 0.876 0.000 0.004 0.120
#> GSM1182310 2 0.4264 0.747 0.000 0.620 0.000 0.004 0.376
#> GSM1182311 1 0.0290 0.962 0.992 0.000 0.000 0.000 0.008
#> GSM1182313 4 0.1851 0.955 0.088 0.000 0.000 0.912 0.000
#> GSM1182315 2 0.4671 0.794 0.000 0.640 0.000 0.028 0.332
#> GSM1182317 2 0.3579 0.790 0.000 0.756 0.000 0.004 0.240
#> GSM1182323 1 0.0290 0.962 0.992 0.000 0.000 0.000 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.2401 0.8977 0.060 0.000 0.000 0.044 0.892 0.004
#> GSM1182187 4 0.3647 0.4311 0.000 0.000 0.000 0.640 0.360 0.000
#> GSM1182188 4 0.0146 0.9308 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182189 5 0.3092 0.8750 0.088 0.000 0.000 0.044 0.852 0.016
#> GSM1182190 5 0.3435 0.8601 0.096 0.000 0.000 0.044 0.832 0.028
#> GSM1182191 5 0.2575 0.8953 0.072 0.000 0.000 0.044 0.880 0.004
#> GSM1182192 4 0.1857 0.9203 0.044 0.000 0.000 0.924 0.028 0.004
#> GSM1182193 4 0.1523 0.9266 0.044 0.000 0.000 0.940 0.008 0.008
#> GSM1182194 6 0.2416 0.9064 0.000 0.000 0.156 0.000 0.000 0.844
#> GSM1182195 6 0.3023 0.8776 0.004 0.000 0.212 0.000 0.000 0.784
#> GSM1182196 2 0.4411 0.3110 0.232 0.708 0.020 0.000 0.000 0.040
#> GSM1182197 3 0.6015 0.4802 0.052 0.264 0.592 0.000 0.016 0.076
#> GSM1182198 6 0.2527 0.9042 0.000 0.000 0.168 0.000 0.000 0.832
#> GSM1182199 6 0.2416 0.9064 0.000 0.000 0.156 0.000 0.000 0.844
#> GSM1182200 2 0.4060 0.7069 0.064 0.812 0.032 0.000 0.024 0.068
#> GSM1182201 3 0.5048 0.7020 0.028 0.132 0.724 0.000 0.020 0.096
#> GSM1182202 5 0.1700 0.8914 0.000 0.000 0.000 0.080 0.916 0.004
#> GSM1182203 4 0.3601 0.5334 0.000 0.000 0.000 0.684 0.312 0.004
#> GSM1182204 5 0.2302 0.8727 0.000 0.000 0.000 0.120 0.872 0.008
#> GSM1182205 6 0.5554 0.4062 0.124 0.004 0.316 0.000 0.004 0.552
#> GSM1182206 3 0.3900 0.7292 0.184 0.004 0.764 0.000 0.004 0.044
#> GSM1182207 5 0.2687 0.8943 0.072 0.000 0.000 0.044 0.876 0.008
#> GSM1182208 5 0.2719 0.8957 0.072 0.000 0.000 0.040 0.876 0.012
#> GSM1182209 2 0.1760 0.7534 0.020 0.928 0.000 0.000 0.004 0.048
#> GSM1182210 2 0.3339 0.7354 0.120 0.824 0.000 0.000 0.008 0.048
#> GSM1182211 2 0.3101 0.7367 0.056 0.856 0.000 0.000 0.020 0.068
#> GSM1182212 2 0.3182 0.7355 0.056 0.852 0.000 0.000 0.024 0.068
#> GSM1182213 2 0.1745 0.7601 0.068 0.920 0.000 0.000 0.000 0.012
#> GSM1182214 2 0.2333 0.7508 0.092 0.884 0.000 0.000 0.000 0.024
#> GSM1182215 3 0.3946 0.7348 0.164 0.000 0.764 0.000 0.004 0.068
#> GSM1182216 2 0.5040 0.4805 0.252 0.648 0.088 0.000 0.004 0.008
#> GSM1182217 5 0.1075 0.8991 0.000 0.000 0.000 0.048 0.952 0.000
#> GSM1182218 5 0.3142 0.8733 0.092 0.000 0.000 0.044 0.848 0.016
#> GSM1182219 2 0.2933 0.7505 0.096 0.856 0.000 0.000 0.008 0.040
#> GSM1182220 2 0.3182 0.7400 0.056 0.852 0.000 0.000 0.024 0.068
#> GSM1182221 1 0.4538 0.5923 0.600 0.364 0.028 0.000 0.000 0.008
#> GSM1182222 2 0.5040 0.4805 0.252 0.648 0.088 0.000 0.004 0.008
#> GSM1182223 3 0.2856 0.7948 0.004 0.064 0.868 0.000 0.004 0.060
#> GSM1182224 6 0.3023 0.8776 0.004 0.000 0.212 0.000 0.000 0.784
#> GSM1182225 2 0.4879 0.5074 0.248 0.664 0.076 0.000 0.004 0.008
#> GSM1182226 2 0.5158 0.4259 0.276 0.624 0.088 0.000 0.004 0.008
#> GSM1182227 4 0.1410 0.9283 0.044 0.000 0.000 0.944 0.008 0.004
#> GSM1182228 3 0.3992 0.7213 0.008 0.184 0.756 0.000 0.000 0.052
#> GSM1182229 3 0.1444 0.7976 0.000 0.000 0.928 0.000 0.000 0.072
#> GSM1182230 3 0.2436 0.7925 0.032 0.000 0.880 0.000 0.000 0.088
#> GSM1182231 3 0.5272 0.5714 0.216 0.132 0.640 0.000 0.004 0.008
#> GSM1182232 5 0.1333 0.9000 0.008 0.000 0.000 0.048 0.944 0.000
#> GSM1182233 5 0.1713 0.8987 0.028 0.000 0.000 0.044 0.928 0.000
#> GSM1182234 4 0.1410 0.9293 0.044 0.000 0.000 0.944 0.008 0.004
#> GSM1182235 2 0.3201 0.6866 0.088 0.848 0.028 0.000 0.000 0.036
#> GSM1182236 5 0.2790 0.8792 0.088 0.000 0.000 0.032 0.868 0.012
#> GSM1182237 3 0.5010 0.6807 0.072 0.168 0.704 0.000 0.000 0.056
#> GSM1182238 2 0.4220 0.5183 0.304 0.664 0.028 0.000 0.000 0.004
#> GSM1182239 2 0.1829 0.7357 0.028 0.928 0.008 0.000 0.000 0.036
#> GSM1182240 2 0.2308 0.7292 0.108 0.880 0.000 0.000 0.004 0.008
#> GSM1182241 2 0.1922 0.7250 0.024 0.924 0.012 0.000 0.000 0.040
#> GSM1182242 3 0.2234 0.7812 0.000 0.004 0.872 0.000 0.000 0.124
#> GSM1182243 3 0.0146 0.8086 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM1182244 6 0.2506 0.8267 0.000 0.052 0.068 0.000 0.000 0.880
#> GSM1182245 4 0.1265 0.9267 0.044 0.000 0.000 0.948 0.000 0.008
#> GSM1182246 4 0.0260 0.9308 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182247 3 0.2191 0.7823 0.000 0.000 0.876 0.000 0.004 0.120
#> GSM1182248 3 0.1858 0.7793 0.004 0.000 0.904 0.000 0.000 0.092
#> GSM1182249 3 0.4096 0.7311 0.204 0.024 0.744 0.000 0.000 0.028
#> GSM1182250 3 0.2346 0.7726 0.124 0.000 0.868 0.000 0.000 0.008
#> GSM1182251 5 0.2687 0.8964 0.072 0.000 0.000 0.044 0.876 0.008
#> GSM1182252 3 0.2378 0.7656 0.000 0.000 0.848 0.000 0.000 0.152
#> GSM1182253 3 0.3159 0.7801 0.052 0.000 0.836 0.000 0.004 0.108
#> GSM1182254 3 0.0260 0.8090 0.008 0.000 0.992 0.000 0.000 0.000
#> GSM1182255 4 0.0260 0.9309 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182256 4 0.0146 0.9308 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182257 4 0.0865 0.9155 0.000 0.000 0.000 0.964 0.036 0.000
#> GSM1182258 4 0.0363 0.9305 0.000 0.000 0.000 0.988 0.012 0.000
#> GSM1182259 4 0.0260 0.9309 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182260 3 0.2703 0.7968 0.016 0.028 0.876 0.000 0.000 0.080
#> GSM1182261 3 0.3025 0.7470 0.164 0.004 0.820 0.000 0.004 0.008
#> GSM1182262 3 0.3894 0.7411 0.152 0.000 0.772 0.000 0.004 0.072
#> GSM1182263 5 0.4943 0.5750 0.072 0.000 0.000 0.300 0.620 0.008
#> GSM1182264 3 0.4050 0.7558 0.016 0.104 0.780 0.000 0.000 0.100
#> GSM1182265 3 0.4112 0.6895 0.224 0.000 0.724 0.000 0.004 0.048
#> GSM1182266 3 0.2611 0.7947 0.016 0.016 0.876 0.000 0.000 0.092
#> GSM1182267 4 0.1605 0.9280 0.044 0.000 0.000 0.936 0.016 0.004
#> GSM1182268 5 0.2781 0.8847 0.084 0.000 0.000 0.040 0.868 0.008
#> GSM1182269 5 0.3387 0.8623 0.092 0.000 0.000 0.044 0.836 0.028
#> GSM1182270 5 0.3179 0.8667 0.092 0.000 0.000 0.032 0.848 0.028
#> GSM1182271 4 0.0260 0.9309 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182272 4 0.0146 0.9308 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182273 3 0.1341 0.8094 0.028 0.000 0.948 0.000 0.000 0.024
#> GSM1182275 3 0.3018 0.7949 0.012 0.016 0.856 0.000 0.012 0.104
#> GSM1182276 2 0.3177 0.7363 0.052 0.852 0.000 0.000 0.024 0.072
#> GSM1182277 4 0.1410 0.9275 0.044 0.000 0.000 0.944 0.004 0.008
#> GSM1182278 4 0.1410 0.9275 0.044 0.000 0.000 0.944 0.004 0.008
#> GSM1182279 5 0.2549 0.8947 0.072 0.000 0.000 0.036 0.884 0.008
#> GSM1182280 5 0.2619 0.8946 0.072 0.000 0.000 0.040 0.880 0.008
#> GSM1182281 4 0.1340 0.9285 0.040 0.000 0.000 0.948 0.004 0.008
#> GSM1182282 4 0.1523 0.9223 0.044 0.000 0.000 0.940 0.008 0.008
#> GSM1182283 4 0.1410 0.9281 0.044 0.000 0.000 0.944 0.008 0.004
#> GSM1182284 4 0.1296 0.9282 0.044 0.000 0.000 0.948 0.004 0.004
#> GSM1182285 6 0.2416 0.9064 0.000 0.000 0.156 0.000 0.000 0.844
#> GSM1182286 2 0.1977 0.7336 0.040 0.920 0.008 0.000 0.000 0.032
#> GSM1182287 3 0.3195 0.7634 0.036 0.116 0.836 0.000 0.000 0.012
#> GSM1182288 3 0.2053 0.7756 0.004 0.000 0.888 0.000 0.000 0.108
#> GSM1182289 5 0.2817 0.8919 0.072 0.000 0.000 0.052 0.868 0.008
#> GSM1182290 5 0.2687 0.8943 0.072 0.000 0.000 0.044 0.876 0.008
#> GSM1182291 4 0.0146 0.9308 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182274 3 0.1391 0.8045 0.016 0.000 0.944 0.000 0.000 0.040
#> GSM1182292 2 0.1320 0.7357 0.016 0.948 0.000 0.000 0.000 0.036
#> GSM1182293 1 0.4953 0.7039 0.572 0.364 0.000 0.000 0.008 0.056
#> GSM1182294 1 0.4181 0.7367 0.600 0.384 0.004 0.000 0.000 0.012
#> GSM1182295 2 0.2912 0.7051 0.172 0.816 0.000 0.000 0.000 0.012
#> GSM1182296 2 0.1320 0.7366 0.016 0.948 0.000 0.000 0.000 0.036
#> GSM1182298 6 0.2416 0.9064 0.000 0.000 0.156 0.000 0.000 0.844
#> GSM1182299 2 0.3385 0.7304 0.064 0.844 0.004 0.000 0.024 0.064
#> GSM1182300 2 0.2680 0.6698 0.108 0.860 0.000 0.000 0.000 0.032
#> GSM1182301 2 0.1857 0.7485 0.028 0.924 0.000 0.000 0.004 0.044
#> GSM1182303 2 0.3468 0.7348 0.072 0.832 0.000 0.000 0.024 0.072
#> GSM1182304 5 0.2364 0.8952 0.072 0.000 0.000 0.032 0.892 0.004
#> GSM1182305 5 0.4758 0.5923 0.060 0.000 0.000 0.292 0.640 0.008
#> GSM1182306 4 0.3446 0.5591 0.000 0.000 0.000 0.692 0.308 0.000
#> GSM1182307 2 0.1575 0.7338 0.032 0.936 0.000 0.000 0.000 0.032
#> GSM1182309 1 0.4779 0.7267 0.568 0.384 0.000 0.000 0.008 0.040
#> GSM1182312 1 0.3499 0.7641 0.728 0.264 0.004 0.000 0.000 0.004
#> GSM1182314 4 0.0260 0.9308 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182316 1 0.3871 0.7668 0.696 0.288 0.008 0.000 0.004 0.004
#> GSM1182318 2 0.4158 0.5352 0.224 0.724 0.000 0.000 0.008 0.044
#> GSM1182319 1 0.4783 0.6939 0.536 0.420 0.008 0.000 0.000 0.036
#> GSM1182320 1 0.3543 0.7776 0.720 0.272 0.004 0.000 0.000 0.004
#> GSM1182321 1 0.5875 0.6796 0.536 0.336 0.064 0.000 0.000 0.064
#> GSM1182322 1 0.4771 0.7006 0.544 0.412 0.008 0.000 0.000 0.036
#> GSM1182324 1 0.5004 0.6903 0.668 0.216 0.104 0.000 0.004 0.008
#> GSM1182297 2 0.2492 0.7173 0.068 0.888 0.008 0.000 0.000 0.036
#> GSM1182302 5 0.1858 0.8881 0.000 0.000 0.000 0.092 0.904 0.004
#> GSM1182308 2 0.4057 0.7230 0.112 0.796 0.020 0.000 0.012 0.060
#> GSM1182310 1 0.3541 0.7735 0.728 0.260 0.012 0.000 0.000 0.000
#> GSM1182311 5 0.3091 0.8735 0.092 0.000 0.000 0.036 0.852 0.020
#> GSM1182313 4 0.0146 0.9308 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1182315 2 0.3890 -0.0994 0.400 0.596 0.000 0.000 0.000 0.004
#> GSM1182317 1 0.5263 0.6139 0.512 0.412 0.000 0.000 0.016 0.060
#> GSM1182323 5 0.2763 0.8820 0.088 0.000 0.000 0.036 0.868 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:skmeans 139 7.73e-02 1.000 2
#> CV:skmeans 137 5.59e-07 0.425 3
#> CV:skmeans 138 1.63e-06 0.409 4
#> CV:skmeans 133 3.42e-06 0.543 5
#> CV:skmeans 131 2.63e-09 0.589 6
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 46361 rows and 139 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 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 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.983 0.993 0.1527 0.928 0.861
#> 4 4 0.787 0.889 0.910 0.3263 0.816 0.591
#> 5 5 0.742 0.813 0.894 0.0390 0.959 0.848
#> 6 6 0.737 0.741 0.822 0.0375 0.968 0.874
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.0000 1.000 0.000 0 1.000
#> GSM1182187 3 0.0000 1.000 0.000 0 1.000
#> GSM1182188 3 0.0000 1.000 0.000 0 1.000
#> GSM1182189 1 0.0000 0.971 1.000 0 0.000
#> GSM1182190 1 0.0000 0.971 1.000 0 0.000
#> GSM1182191 3 0.0237 0.996 0.004 0 0.996
#> GSM1182192 1 0.0000 0.971 1.000 0 0.000
#> GSM1182193 1 0.0000 0.971 1.000 0 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000
#> GSM1182202 3 0.0000 1.000 0.000 0 1.000
#> GSM1182203 3 0.0000 1.000 0.000 0 1.000
#> GSM1182204 3 0.0000 1.000 0.000 0 1.000
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000
#> GSM1182207 1 0.0000 0.971 1.000 0 0.000
#> GSM1182208 1 0.0000 0.971 1.000 0 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000
#> GSM1182217 3 0.0000 1.000 0.000 0 1.000
#> GSM1182218 1 0.0000 0.971 1.000 0 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000
#> GSM1182227 1 0.0000 0.971 1.000 0 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000
#> GSM1182232 1 0.0000 0.971 1.000 0 0.000
#> GSM1182233 1 0.0000 0.971 1.000 0 0.000
#> GSM1182234 1 0.0000 0.971 1.000 0 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000
#> GSM1182236 1 0.0000 0.971 1.000 0 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000
#> GSM1182245 1 0.0000 0.971 1.000 0 0.000
#> GSM1182246 3 0.0000 1.000 0.000 0 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000
#> GSM1182251 1 0.4346 0.772 0.816 0 0.184
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000
#> GSM1182255 3 0.0000 1.000 0.000 0 1.000
#> GSM1182256 3 0.0000 1.000 0.000 0 1.000
#> GSM1182257 3 0.0000 1.000 0.000 0 1.000
#> GSM1182258 3 0.0000 1.000 0.000 0 1.000
#> GSM1182259 3 0.0000 1.000 0.000 0 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000
#> GSM1182263 1 0.0000 0.971 1.000 0 0.000
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000
#> GSM1182267 1 0.0000 0.971 1.000 0 0.000
#> GSM1182268 1 0.0000 0.971 1.000 0 0.000
#> GSM1182269 1 0.0000 0.971 1.000 0 0.000
#> GSM1182270 1 0.0000 0.971 1.000 0 0.000
#> GSM1182271 3 0.0000 1.000 0.000 0 1.000
#> GSM1182272 3 0.0000 1.000 0.000 0 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000
#> GSM1182277 1 0.0000 0.971 1.000 0 0.000
#> GSM1182278 1 0.0000 0.971 1.000 0 0.000
#> GSM1182279 1 0.0000 0.971 1.000 0 0.000
#> GSM1182280 1 0.0000 0.971 1.000 0 0.000
#> GSM1182281 1 0.6299 0.107 0.524 0 0.476
#> GSM1182282 1 0.0000 0.971 1.000 0 0.000
#> GSM1182283 1 0.0000 0.971 1.000 0 0.000
#> GSM1182284 1 0.0000 0.971 1.000 0 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000
#> GSM1182289 1 0.0237 0.968 0.996 0 0.004
#> GSM1182290 1 0.0000 0.971 1.000 0 0.000
#> GSM1182291 3 0.0000 1.000 0.000 0 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000
#> GSM1182304 1 0.0000 0.971 1.000 0 0.000
#> GSM1182305 1 0.5178 0.666 0.744 0 0.256
#> GSM1182306 3 0.0000 1.000 0.000 0 1.000
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000
#> GSM1182314 3 0.0000 1.000 0.000 0 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000
#> GSM1182302 3 0.0000 1.000 0.000 0 1.000
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000
#> GSM1182311 1 0.0000 0.971 1.000 0 0.000
#> GSM1182313 3 0.0000 1.000 0.000 0 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000
#> GSM1182323 1 0.0000 0.971 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.0469 0.9944 0.000 0.000 0.012 0.988
#> GSM1182187 4 0.0469 0.9944 0.000 0.000 0.012 0.988
#> GSM1182188 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182191 4 0.0657 0.9918 0.004 0.000 0.012 0.984
#> GSM1182192 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182194 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182195 3 0.0707 0.9127 0.000 0.020 0.980 0.000
#> GSM1182196 2 0.2868 0.8402 0.000 0.864 0.136 0.000
#> GSM1182197 2 0.4898 0.4669 0.000 0.584 0.416 0.000
#> GSM1182198 3 0.0707 0.9127 0.000 0.020 0.980 0.000
#> GSM1182199 3 0.0592 0.9133 0.000 0.016 0.984 0.000
#> GSM1182200 2 0.3801 0.8128 0.000 0.780 0.220 0.000
#> GSM1182201 3 0.2011 0.8804 0.000 0.080 0.920 0.000
#> GSM1182202 4 0.0469 0.9944 0.000 0.000 0.012 0.988
#> GSM1182203 4 0.0336 0.9954 0.000 0.000 0.008 0.992
#> GSM1182204 4 0.0336 0.9954 0.000 0.000 0.008 0.992
#> GSM1182205 3 0.2704 0.8479 0.000 0.124 0.876 0.000
#> GSM1182206 3 0.4356 0.6404 0.000 0.292 0.708 0.000
#> GSM1182207 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182209 2 0.0188 0.8929 0.000 0.996 0.004 0.000
#> GSM1182210 2 0.2921 0.8777 0.000 0.860 0.140 0.000
#> GSM1182211 2 0.0188 0.8947 0.000 0.996 0.004 0.000
#> GSM1182212 2 0.2345 0.8814 0.000 0.900 0.100 0.000
#> GSM1182213 2 0.0188 0.8929 0.000 0.996 0.004 0.000
#> GSM1182214 2 0.0592 0.8974 0.000 0.984 0.016 0.000
#> GSM1182215 3 0.4817 0.3322 0.000 0.388 0.612 0.000
#> GSM1182216 2 0.2216 0.8918 0.000 0.908 0.092 0.000
#> GSM1182217 4 0.0469 0.9944 0.000 0.000 0.012 0.988
#> GSM1182218 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182219 2 0.1389 0.9015 0.000 0.952 0.048 0.000
#> GSM1182220 2 0.2814 0.8692 0.000 0.868 0.132 0.000
#> GSM1182221 2 0.2216 0.8918 0.000 0.908 0.092 0.000
#> GSM1182222 2 0.3172 0.8626 0.000 0.840 0.160 0.000
#> GSM1182223 3 0.4916 0.1935 0.000 0.424 0.576 0.000
#> GSM1182224 3 0.0707 0.9127 0.000 0.020 0.980 0.000
#> GSM1182225 2 0.2408 0.8903 0.000 0.896 0.104 0.000
#> GSM1182226 2 0.2149 0.8931 0.000 0.912 0.088 0.000
#> GSM1182227 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182228 3 0.3356 0.8106 0.000 0.176 0.824 0.000
#> GSM1182229 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182230 3 0.1474 0.8984 0.000 0.052 0.948 0.000
#> GSM1182231 2 0.3172 0.8625 0.000 0.840 0.160 0.000
#> GSM1182232 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182235 2 0.0188 0.8929 0.000 0.996 0.004 0.000
#> GSM1182236 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182237 2 0.3486 0.7908 0.000 0.812 0.188 0.000
#> GSM1182238 2 0.1716 0.8979 0.000 0.936 0.064 0.000
#> GSM1182239 2 0.2345 0.8763 0.000 0.900 0.100 0.000
#> GSM1182240 2 0.0469 0.8960 0.000 0.988 0.012 0.000
#> GSM1182241 2 0.2814 0.8455 0.000 0.868 0.132 0.000
#> GSM1182242 3 0.0707 0.9104 0.000 0.020 0.980 0.000
#> GSM1182243 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182244 3 0.1867 0.8892 0.000 0.072 0.928 0.000
#> GSM1182245 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182248 3 0.0707 0.9127 0.000 0.020 0.980 0.000
#> GSM1182249 2 0.4804 0.5047 0.000 0.616 0.384 0.000
#> GSM1182250 3 0.2530 0.8551 0.000 0.112 0.888 0.000
#> GSM1182251 1 0.3852 0.7664 0.808 0.000 0.012 0.180
#> GSM1182252 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182253 3 0.0817 0.9118 0.000 0.024 0.976 0.000
#> GSM1182254 3 0.0592 0.9133 0.000 0.016 0.984 0.000
#> GSM1182255 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0188 0.9961 0.000 0.000 0.004 0.996
#> GSM1182258 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.1867 0.8859 0.000 0.072 0.928 0.000
#> GSM1182261 2 0.4679 0.5627 0.000 0.648 0.352 0.000
#> GSM1182262 3 0.4250 0.6388 0.000 0.276 0.724 0.000
#> GSM1182263 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182264 3 0.2081 0.8717 0.000 0.084 0.916 0.000
#> GSM1182265 3 0.1118 0.9072 0.000 0.036 0.964 0.000
#> GSM1182266 3 0.1022 0.9051 0.000 0.032 0.968 0.000
#> GSM1182267 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0707 0.9127 0.000 0.020 0.980 0.000
#> GSM1182275 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182276 2 0.2647 0.8721 0.000 0.880 0.120 0.000
#> GSM1182277 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182279 1 0.0336 0.9648 0.992 0.000 0.008 0.000
#> GSM1182280 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182281 1 0.4994 0.0944 0.520 0.000 0.000 0.480
#> GSM1182282 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182285 3 0.0592 0.9129 0.000 0.016 0.984 0.000
#> GSM1182286 2 0.0921 0.8970 0.000 0.972 0.028 0.000
#> GSM1182287 3 0.4008 0.6928 0.000 0.244 0.756 0.000
#> GSM1182288 3 0.0592 0.9133 0.000 0.016 0.984 0.000
#> GSM1182289 1 0.0657 0.9593 0.984 0.000 0.012 0.004
#> GSM1182290 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0817 0.9129 0.000 0.024 0.976 0.000
#> GSM1182292 2 0.0707 0.8946 0.000 0.980 0.020 0.000
#> GSM1182293 2 0.2281 0.8976 0.000 0.904 0.096 0.000
#> GSM1182294 2 0.1637 0.8997 0.000 0.940 0.060 0.000
#> GSM1182295 2 0.2011 0.8973 0.000 0.920 0.080 0.000
#> GSM1182296 2 0.0469 0.8941 0.000 0.988 0.012 0.000
#> GSM1182298 3 0.0469 0.9132 0.000 0.012 0.988 0.000
#> GSM1182299 2 0.3528 0.8177 0.000 0.808 0.192 0.000
#> GSM1182300 2 0.1716 0.8913 0.000 0.936 0.064 0.000
#> GSM1182301 2 0.2011 0.8900 0.000 0.920 0.080 0.000
#> GSM1182303 2 0.3024 0.8707 0.000 0.852 0.148 0.000
#> GSM1182304 1 0.0336 0.9648 0.992 0.000 0.008 0.000
#> GSM1182305 1 0.4485 0.6658 0.740 0.000 0.012 0.248
#> GSM1182306 4 0.0188 0.9961 0.000 0.000 0.004 0.996
#> GSM1182307 2 0.0592 0.8950 0.000 0.984 0.016 0.000
#> GSM1182309 2 0.0817 0.8957 0.000 0.976 0.024 0.000
#> GSM1182312 2 0.2216 0.8918 0.000 0.908 0.092 0.000
#> GSM1182314 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.2408 0.8902 0.000 0.896 0.104 0.000
#> GSM1182318 2 0.0469 0.8946 0.000 0.988 0.012 0.000
#> GSM1182319 2 0.2921 0.8375 0.000 0.860 0.140 0.000
#> GSM1182320 2 0.2216 0.8918 0.000 0.908 0.092 0.000
#> GSM1182321 3 0.2760 0.8466 0.000 0.128 0.872 0.000
#> GSM1182322 2 0.2530 0.8526 0.000 0.888 0.112 0.000
#> GSM1182324 3 0.3975 0.6983 0.000 0.240 0.760 0.000
#> GSM1182297 2 0.0188 0.8929 0.000 0.996 0.004 0.000
#> GSM1182302 4 0.0336 0.9954 0.000 0.000 0.008 0.992
#> GSM1182308 2 0.3311 0.8533 0.000 0.828 0.172 0.000
#> GSM1182310 2 0.2530 0.8883 0.000 0.888 0.112 0.000
#> GSM1182311 1 0.0000 0.9698 1.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.9967 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.0817 0.8983 0.000 0.976 0.024 0.000
#> GSM1182317 2 0.0336 0.8924 0.000 0.992 0.008 0.000
#> GSM1182323 1 0.0000 0.9698 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
#> GSM1182186 5 0.2074 0.6046 0.000 0.000 0.000 0.104 0.896
#> GSM1182187 5 0.4307 -0.2485 0.000 0.000 0.000 0.500 0.500
#> GSM1182188 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 5 0.1792 0.6161 0.000 0.000 0.000 0.084 0.916
#> GSM1182192 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.0000 0.8969 0.000 0.000 1.000 0.000 0.000
#> GSM1182195 3 0.0579 0.8963 0.000 0.008 0.984 0.000 0.008
#> GSM1182196 2 0.2629 0.8332 0.000 0.860 0.136 0.000 0.004
#> GSM1182197 2 0.4497 0.4481 0.000 0.568 0.424 0.000 0.008
#> GSM1182198 3 0.0290 0.8968 0.000 0.008 0.992 0.000 0.000
#> GSM1182199 3 0.0162 0.8972 0.000 0.004 0.996 0.000 0.000
#> GSM1182200 2 0.3305 0.8052 0.000 0.776 0.224 0.000 0.000
#> GSM1182201 3 0.1608 0.8675 0.000 0.072 0.928 0.000 0.000
#> GSM1182202 5 0.4242 -0.0445 0.000 0.000 0.000 0.428 0.572
#> GSM1182203 4 0.3508 0.6195 0.000 0.000 0.000 0.748 0.252
#> GSM1182204 4 0.4294 0.1584 0.000 0.000 0.000 0.532 0.468
#> GSM1182205 3 0.2864 0.8276 0.000 0.112 0.864 0.000 0.024
#> GSM1182206 3 0.4594 0.6132 0.000 0.284 0.680 0.000 0.036
#> GSM1182207 5 0.4283 0.4247 0.456 0.000 0.000 0.000 0.544
#> GSM1182208 5 0.4287 0.4148 0.460 0.000 0.000 0.000 0.540
#> GSM1182209 2 0.1124 0.8845 0.000 0.960 0.004 0.000 0.036
#> GSM1182210 2 0.2921 0.8787 0.000 0.856 0.124 0.000 0.020
#> GSM1182211 2 0.1408 0.8935 0.000 0.948 0.008 0.000 0.044
#> GSM1182212 2 0.2712 0.8830 0.000 0.880 0.088 0.000 0.032
#> GSM1182213 2 0.0162 0.8890 0.000 0.996 0.004 0.000 0.000
#> GSM1182214 2 0.1300 0.8937 0.000 0.956 0.016 0.000 0.028
#> GSM1182215 3 0.4663 0.3269 0.000 0.376 0.604 0.000 0.020
#> GSM1182216 2 0.2504 0.8846 0.000 0.896 0.064 0.000 0.040
#> GSM1182217 5 0.2230 0.5949 0.000 0.000 0.000 0.116 0.884
#> GSM1182218 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.1444 0.8965 0.000 0.948 0.040 0.000 0.012
#> GSM1182220 2 0.2723 0.8680 0.000 0.864 0.124 0.000 0.012
#> GSM1182221 2 0.2504 0.8846 0.000 0.896 0.064 0.000 0.040
#> GSM1182222 2 0.3409 0.8585 0.000 0.824 0.144 0.000 0.032
#> GSM1182223 3 0.4210 0.2109 0.000 0.412 0.588 0.000 0.000
#> GSM1182224 3 0.0898 0.8937 0.000 0.008 0.972 0.000 0.020
#> GSM1182225 2 0.2694 0.8845 0.000 0.884 0.076 0.000 0.040
#> GSM1182226 2 0.2504 0.8846 0.000 0.896 0.064 0.000 0.040
#> GSM1182227 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182228 3 0.3278 0.8003 0.000 0.156 0.824 0.000 0.020
#> GSM1182229 3 0.0162 0.8973 0.000 0.000 0.996 0.000 0.004
#> GSM1182230 3 0.1549 0.8819 0.000 0.040 0.944 0.000 0.016
#> GSM1182231 2 0.3432 0.8604 0.000 0.828 0.132 0.000 0.040
#> GSM1182232 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0510 0.9807 0.984 0.000 0.000 0.000 0.016
#> GSM1182234 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.1357 0.8864 0.000 0.948 0.004 0.000 0.048
#> GSM1182236 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 2 0.3562 0.7766 0.000 0.788 0.196 0.000 0.016
#> GSM1182238 2 0.2228 0.8880 0.000 0.912 0.048 0.000 0.040
#> GSM1182239 2 0.2694 0.8752 0.000 0.884 0.076 0.000 0.040
#> GSM1182240 2 0.0693 0.8929 0.000 0.980 0.012 0.000 0.008
#> GSM1182241 2 0.3432 0.8374 0.000 0.828 0.132 0.000 0.040
#> GSM1182242 3 0.0290 0.8942 0.000 0.008 0.992 0.000 0.000
#> GSM1182243 3 0.0162 0.8973 0.000 0.000 0.996 0.000 0.004
#> GSM1182244 3 0.1430 0.8794 0.000 0.052 0.944 0.000 0.004
#> GSM1182245 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.0000 0.8969 0.000 0.000 1.000 0.000 0.000
#> GSM1182248 3 0.0693 0.8956 0.000 0.008 0.980 0.000 0.012
#> GSM1182249 2 0.4494 0.5003 0.000 0.608 0.380 0.000 0.012
#> GSM1182250 3 0.2900 0.8299 0.000 0.108 0.864 0.000 0.028
#> GSM1182251 5 0.2012 0.6373 0.020 0.000 0.000 0.060 0.920
#> GSM1182252 3 0.0162 0.8973 0.000 0.000 0.996 0.000 0.004
#> GSM1182253 3 0.0807 0.8950 0.000 0.012 0.976 0.000 0.012
#> GSM1182254 3 0.0324 0.8977 0.000 0.004 0.992 0.000 0.004
#> GSM1182255 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.1410 0.8413 0.000 0.000 0.000 0.940 0.060
#> GSM1182258 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.2012 0.8626 0.000 0.060 0.920 0.000 0.020
#> GSM1182261 2 0.4638 0.5852 0.000 0.648 0.324 0.000 0.028
#> GSM1182262 3 0.4138 0.6185 0.000 0.276 0.708 0.000 0.016
#> GSM1182263 5 0.4210 0.4894 0.412 0.000 0.000 0.000 0.588
#> GSM1182264 3 0.2569 0.8405 0.000 0.068 0.892 0.000 0.040
#> GSM1182265 3 0.1168 0.8899 0.000 0.032 0.960 0.000 0.008
#> GSM1182266 3 0.0510 0.8906 0.000 0.016 0.984 0.000 0.000
#> GSM1182267 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0162 0.9947 0.996 0.000 0.000 0.000 0.004
#> GSM1182271 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 3 0.0290 0.8968 0.000 0.008 0.992 0.000 0.000
#> GSM1182275 3 0.0000 0.8969 0.000 0.000 1.000 0.000 0.000
#> GSM1182276 2 0.2795 0.8732 0.000 0.872 0.100 0.000 0.028
#> GSM1182277 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.2966 0.6850 0.184 0.000 0.000 0.000 0.816
#> GSM1182280 5 0.4242 0.4671 0.428 0.000 0.000 0.000 0.572
#> GSM1182281 4 0.4735 0.4071 0.284 0.000 0.000 0.672 0.044
#> GSM1182282 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9986 1.000 0.000 0.000 0.000 0.000
#> GSM1182285 3 0.0162 0.8968 0.000 0.004 0.996 0.000 0.000
#> GSM1182286 2 0.1741 0.8881 0.000 0.936 0.024 0.000 0.040
#> GSM1182287 3 0.3612 0.6972 0.000 0.228 0.764 0.000 0.008
#> GSM1182288 3 0.0671 0.8955 0.000 0.004 0.980 0.000 0.016
#> GSM1182289 5 0.2690 0.6829 0.156 0.000 0.000 0.000 0.844
#> GSM1182290 5 0.4268 0.4467 0.444 0.000 0.000 0.000 0.556
#> GSM1182291 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 3 0.0566 0.8979 0.000 0.012 0.984 0.000 0.004
#> GSM1182292 2 0.1469 0.8848 0.000 0.948 0.016 0.000 0.036
#> GSM1182293 2 0.2408 0.8918 0.000 0.892 0.092 0.000 0.016
#> GSM1182294 2 0.2300 0.8894 0.000 0.908 0.052 0.000 0.040
#> GSM1182295 2 0.1764 0.8946 0.000 0.928 0.064 0.000 0.008
#> GSM1182296 2 0.1364 0.8851 0.000 0.952 0.012 0.000 0.036
#> GSM1182298 3 0.0000 0.8969 0.000 0.000 1.000 0.000 0.000
#> GSM1182299 2 0.3694 0.8259 0.000 0.796 0.172 0.000 0.032
#> GSM1182300 2 0.2074 0.8848 0.000 0.920 0.044 0.000 0.036
#> GSM1182301 2 0.2426 0.8823 0.000 0.900 0.064 0.000 0.036
#> GSM1182303 2 0.2763 0.8649 0.000 0.848 0.148 0.000 0.004
#> GSM1182304 5 0.2966 0.6850 0.184 0.000 0.000 0.000 0.816
#> GSM1182305 5 0.2036 0.6399 0.024 0.000 0.000 0.056 0.920
#> GSM1182306 4 0.1410 0.8413 0.000 0.000 0.000 0.940 0.060
#> GSM1182307 2 0.1444 0.8859 0.000 0.948 0.012 0.000 0.040
#> GSM1182309 2 0.1661 0.8860 0.000 0.940 0.024 0.000 0.036
#> GSM1182312 2 0.2504 0.8846 0.000 0.896 0.064 0.000 0.040
#> GSM1182314 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 2 0.2616 0.8846 0.000 0.888 0.076 0.000 0.036
#> GSM1182318 2 0.0404 0.8908 0.000 0.988 0.012 0.000 0.000
#> GSM1182319 2 0.3197 0.8262 0.000 0.836 0.140 0.000 0.024
#> GSM1182320 2 0.2426 0.8854 0.000 0.900 0.064 0.000 0.036
#> GSM1182321 3 0.3267 0.8123 0.000 0.112 0.844 0.000 0.044
#> GSM1182322 2 0.3459 0.8406 0.000 0.832 0.116 0.000 0.052
#> GSM1182324 3 0.4313 0.6753 0.000 0.228 0.732 0.000 0.040
#> GSM1182297 2 0.1205 0.8851 0.000 0.956 0.004 0.000 0.040
#> GSM1182302 4 0.4297 0.1513 0.000 0.000 0.000 0.528 0.472
#> GSM1182308 2 0.3224 0.8525 0.000 0.824 0.160 0.000 0.016
#> GSM1182310 2 0.2813 0.8820 0.000 0.876 0.084 0.000 0.040
#> GSM1182311 1 0.0162 0.9947 0.996 0.000 0.000 0.000 0.004
#> GSM1182313 4 0.0000 0.8766 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.1493 0.8929 0.000 0.948 0.028 0.000 0.024
#> GSM1182317 2 0.0798 0.8894 0.000 0.976 0.008 0.000 0.016
#> GSM1182323 1 0.0000 0.9986 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
#> GSM1182186 5 0.2119 0.6926 0.000 0.000 0.000 0.060 0.904 NA
#> GSM1182187 4 0.5858 0.5113 0.000 0.000 0.000 0.484 0.272 NA
#> GSM1182188 4 0.0146 0.8342 0.000 0.000 0.000 0.996 0.000 NA
#> GSM1182189 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182190 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182191 5 0.1720 0.7105 0.000 0.000 0.000 0.040 0.928 NA
#> GSM1182192 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182193 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182194 3 0.3390 0.6975 0.000 0.000 0.704 0.000 0.000 NA
#> GSM1182195 3 0.3499 0.6948 0.000 0.000 0.680 0.000 0.000 NA
#> GSM1182196 2 0.4330 0.4250 0.000 0.632 0.332 0.000 0.000 NA
#> GSM1182197 3 0.4514 0.1543 0.000 0.372 0.588 0.000 0.000 NA
#> GSM1182198 3 0.3428 0.6984 0.000 0.000 0.696 0.000 0.000 NA
#> GSM1182199 3 0.3428 0.6969 0.000 0.000 0.696 0.000 0.000 NA
#> GSM1182200 2 0.4219 0.4824 0.000 0.592 0.388 0.000 0.000 NA
#> GSM1182201 3 0.1563 0.7708 0.000 0.056 0.932 0.000 0.000 NA
#> GSM1182202 4 0.5961 0.4462 0.000 0.000 0.000 0.444 0.312 NA
#> GSM1182203 4 0.5135 0.6352 0.000 0.000 0.000 0.616 0.144 NA
#> GSM1182204 4 0.5351 0.6091 0.000 0.000 0.000 0.588 0.176 NA
#> GSM1182205 3 0.4968 0.6816 0.000 0.120 0.632 0.000 0.000 NA
#> GSM1182206 3 0.5184 0.1949 0.000 0.432 0.480 0.000 0.000 NA
#> GSM1182207 5 0.3717 0.5946 0.384 0.000 0.000 0.000 0.616 NA
#> GSM1182208 5 0.3727 0.5844 0.388 0.000 0.000 0.000 0.612 NA
#> GSM1182209 2 0.2219 0.8224 0.000 0.864 0.000 0.000 0.000 NA
#> GSM1182210 2 0.2905 0.8267 0.000 0.852 0.084 0.000 0.000 NA
#> GSM1182211 2 0.2482 0.8368 0.000 0.848 0.004 0.000 0.000 NA
#> GSM1182212 2 0.3032 0.8269 0.000 0.840 0.056 0.000 0.000 NA
#> GSM1182213 2 0.0790 0.8394 0.000 0.968 0.000 0.000 0.000 NA
#> GSM1182214 2 0.1753 0.8398 0.000 0.912 0.004 0.000 0.000 NA
#> GSM1182215 3 0.5377 0.3442 0.000 0.348 0.528 0.000 0.000 NA
#> GSM1182216 2 0.2118 0.8212 0.000 0.888 0.008 0.000 0.000 NA
#> GSM1182217 5 0.4428 0.4756 0.000 0.000 0.000 0.072 0.684 NA
#> GSM1182218 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182219 2 0.1563 0.8379 0.000 0.932 0.012 0.000 0.000 NA
#> GSM1182220 2 0.3078 0.8090 0.000 0.836 0.108 0.000 0.000 NA
#> GSM1182221 2 0.2212 0.8202 0.000 0.880 0.008 0.000 0.000 NA
#> GSM1182222 2 0.3514 0.8034 0.000 0.804 0.108 0.000 0.000 NA
#> GSM1182223 2 0.4333 0.1763 0.000 0.512 0.468 0.000 0.000 NA
#> GSM1182224 3 0.4039 0.6783 0.000 0.016 0.632 0.000 0.000 NA
#> GSM1182225 2 0.2358 0.8232 0.000 0.876 0.016 0.000 0.000 NA
#> GSM1182226 2 0.2266 0.8198 0.000 0.880 0.012 0.000 0.000 NA
#> GSM1182227 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182228 3 0.4270 0.5743 0.000 0.264 0.684 0.000 0.000 NA
#> GSM1182229 3 0.0458 0.7784 0.000 0.000 0.984 0.000 0.000 NA
#> GSM1182230 3 0.3657 0.7470 0.000 0.100 0.792 0.000 0.000 NA
#> GSM1182231 2 0.3321 0.8068 0.000 0.820 0.080 0.000 0.000 NA
#> GSM1182232 1 0.1075 0.8886 0.952 0.000 0.000 0.000 0.000 NA
#> GSM1182233 1 0.0865 0.8574 0.964 0.000 0.000 0.000 0.036 NA
#> GSM1182234 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182235 2 0.2558 0.8299 0.000 0.840 0.004 0.000 0.000 NA
#> GSM1182236 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182237 2 0.3860 0.7232 0.000 0.764 0.164 0.000 0.000 NA
#> GSM1182238 2 0.2053 0.8216 0.000 0.888 0.004 0.000 0.000 NA
#> GSM1182239 2 0.2768 0.8263 0.000 0.832 0.012 0.000 0.000 NA
#> GSM1182240 2 0.1082 0.8408 0.000 0.956 0.004 0.000 0.000 NA
#> GSM1182241 2 0.5556 0.4086 0.000 0.512 0.336 0.000 0.000 NA
#> GSM1182242 3 0.0146 0.7795 0.000 0.000 0.996 0.000 0.000 NA
#> GSM1182243 3 0.0632 0.7790 0.000 0.000 0.976 0.000 0.000 NA
#> GSM1182244 3 0.3652 0.7222 0.000 0.016 0.720 0.000 0.000 NA
#> GSM1182245 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182246 4 0.0146 0.8340 0.000 0.000 0.000 0.996 0.004 NA
#> GSM1182247 3 0.1007 0.7803 0.000 0.000 0.956 0.000 0.000 NA
#> GSM1182248 3 0.2805 0.7577 0.000 0.004 0.812 0.000 0.000 NA
#> GSM1182249 3 0.4726 0.0707 0.000 0.424 0.528 0.000 0.000 NA
#> GSM1182250 3 0.3563 0.7087 0.000 0.132 0.796 0.000 0.000 NA
#> GSM1182251 5 0.0146 0.7433 0.004 0.000 0.000 0.000 0.996 NA
#> GSM1182252 3 0.1204 0.7829 0.000 0.000 0.944 0.000 0.000 NA
#> GSM1182253 3 0.0632 0.7822 0.000 0.000 0.976 0.000 0.000 NA
#> GSM1182254 3 0.0260 0.7807 0.000 0.000 0.992 0.000 0.000 NA
#> GSM1182255 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182256 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182257 4 0.1745 0.8009 0.000 0.000 0.000 0.920 0.068 NA
#> GSM1182258 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182259 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182260 3 0.1908 0.7651 0.000 0.028 0.916 0.000 0.000 NA
#> GSM1182261 2 0.4596 0.6114 0.000 0.672 0.240 0.000 0.000 NA
#> GSM1182262 3 0.5193 0.4131 0.000 0.344 0.552 0.000 0.000 NA
#> GSM1182263 5 0.3860 0.7100 0.236 0.000 0.000 0.000 0.728 NA
#> GSM1182264 3 0.2972 0.7181 0.000 0.036 0.836 0.000 0.000 NA
#> GSM1182265 3 0.2070 0.7696 0.000 0.044 0.908 0.000 0.000 NA
#> GSM1182266 3 0.0146 0.7793 0.000 0.000 0.996 0.000 0.000 NA
#> GSM1182267 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182268 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182269 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
#> GSM1182270 1 0.0146 0.8820 0.996 0.000 0.000 0.000 0.004 NA
#> GSM1182271 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182272 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182273 3 0.0363 0.7815 0.000 0.000 0.988 0.000 0.000 NA
#> GSM1182275 3 0.0508 0.7804 0.000 0.004 0.984 0.000 0.000 NA
#> GSM1182276 2 0.3017 0.8233 0.000 0.840 0.052 0.000 0.000 NA
#> GSM1182277 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182278 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182279 5 0.2048 0.7870 0.120 0.000 0.000 0.000 0.880 NA
#> GSM1182280 5 0.3351 0.7004 0.288 0.000 0.000 0.000 0.712 NA
#> GSM1182281 4 0.6606 0.2631 0.184 0.000 0.000 0.532 0.092 NA
#> GSM1182282 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182283 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182284 1 0.2730 0.8926 0.808 0.000 0.000 0.000 0.000 NA
#> GSM1182285 3 0.3428 0.6966 0.000 0.000 0.696 0.000 0.000 NA
#> GSM1182286 2 0.2520 0.8262 0.000 0.844 0.004 0.000 0.000 NA
#> GSM1182287 3 0.4332 0.4158 0.000 0.352 0.616 0.000 0.000 NA
#> GSM1182288 3 0.1588 0.7816 0.000 0.004 0.924 0.000 0.000 NA
#> GSM1182289 5 0.1663 0.7815 0.088 0.000 0.000 0.000 0.912 NA
#> GSM1182290 5 0.3578 0.6524 0.340 0.000 0.000 0.000 0.660 NA
#> GSM1182291 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182274 3 0.0858 0.7792 0.000 0.004 0.968 0.000 0.000 NA
#> GSM1182292 2 0.2402 0.8214 0.000 0.856 0.004 0.000 0.000 NA
#> GSM1182293 2 0.2389 0.8335 0.000 0.888 0.060 0.000 0.000 NA
#> GSM1182294 2 0.2311 0.8228 0.000 0.880 0.016 0.000 0.000 NA
#> GSM1182295 2 0.1151 0.8366 0.000 0.956 0.012 0.000 0.000 NA
#> GSM1182296 2 0.2362 0.8221 0.000 0.860 0.004 0.000 0.000 NA
#> GSM1182298 3 0.3409 0.6982 0.000 0.000 0.700 0.000 0.000 NA
#> GSM1182299 2 0.5029 0.5669 0.000 0.612 0.276 0.000 0.000 NA
#> GSM1182300 2 0.2402 0.8214 0.000 0.856 0.004 0.000 0.000 NA
#> GSM1182301 2 0.2911 0.8183 0.000 0.832 0.024 0.000 0.000 NA
#> GSM1182303 2 0.2901 0.8040 0.000 0.840 0.128 0.000 0.000 NA
#> GSM1182304 5 0.2092 0.7871 0.124 0.000 0.000 0.000 0.876 NA
#> GSM1182305 5 0.0260 0.7385 0.000 0.000 0.000 0.000 0.992 NA
#> GSM1182306 4 0.4229 0.7157 0.000 0.000 0.000 0.712 0.068 NA
#> GSM1182307 2 0.2402 0.8235 0.000 0.856 0.004 0.000 0.000 NA
#> GSM1182309 2 0.2520 0.8219 0.000 0.844 0.004 0.000 0.000 NA
#> GSM1182312 2 0.2346 0.8177 0.000 0.868 0.008 0.000 0.000 NA
#> GSM1182314 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182316 2 0.2398 0.8225 0.000 0.876 0.020 0.000 0.000 NA
#> GSM1182318 2 0.1219 0.8403 0.000 0.948 0.004 0.000 0.000 NA
#> GSM1182319 2 0.5267 0.4411 0.000 0.560 0.320 0.000 0.000 NA
#> GSM1182320 2 0.2118 0.8231 0.000 0.888 0.008 0.000 0.000 NA
#> GSM1182321 3 0.3627 0.6993 0.000 0.080 0.792 0.000 0.000 NA
#> GSM1182322 2 0.5771 0.3903 0.000 0.476 0.336 0.000 0.000 NA
#> GSM1182324 3 0.4036 0.6892 0.000 0.136 0.756 0.000 0.000 NA
#> GSM1182297 2 0.2482 0.8272 0.000 0.848 0.004 0.000 0.000 NA
#> GSM1182302 4 0.5391 0.6031 0.000 0.000 0.000 0.580 0.176 NA
#> GSM1182308 2 0.3149 0.7953 0.000 0.824 0.132 0.000 0.000 NA
#> GSM1182310 2 0.3534 0.7820 0.000 0.800 0.076 0.000 0.000 NA
#> GSM1182311 1 0.0146 0.8820 0.996 0.000 0.000 0.000 0.004 NA
#> GSM1182313 4 0.0000 0.8350 0.000 0.000 0.000 1.000 0.000 NA
#> GSM1182315 2 0.1644 0.8323 0.000 0.920 0.004 0.000 0.000 NA
#> GSM1182317 2 0.1910 0.8387 0.000 0.892 0.000 0.000 0.000 NA
#> GSM1182323 1 0.0000 0.8840 1.000 0.000 0.000 0.000 0.000 NA
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:pam 139 0.077250 1.000 2
#> CV:pam 138 0.136924 0.899 3
#> CV:pam 135 0.000250 0.610 4
#> CV:pam 126 0.000894 0.659 5
#> CV:pam 124 0.000870 0.523 6
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 46361 rows and 139 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 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.727 0.849 0.890 0.3296 0.823 0.661
#> 4 4 0.553 0.680 0.721 0.0878 0.902 0.724
#> 5 5 0.553 0.566 0.769 0.0815 0.922 0.748
#> 6 6 0.531 0.602 0.670 0.0243 0.960 0.856
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182187 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182188 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182189 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182190 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182191 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182192 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182193 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182194 2 0.0892 0.865 0.000 0.980 0.020
#> GSM1182195 2 0.0892 0.864 0.000 0.980 0.020
#> GSM1182196 2 0.4796 0.733 0.000 0.780 0.220
#> GSM1182197 2 0.1529 0.865 0.000 0.960 0.040
#> GSM1182198 2 0.1643 0.857 0.000 0.956 0.044
#> GSM1182199 2 0.1964 0.854 0.000 0.944 0.056
#> GSM1182200 2 0.2356 0.848 0.000 0.928 0.072
#> GSM1182201 2 0.0747 0.872 0.000 0.984 0.016
#> GSM1182202 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182203 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182204 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182205 2 0.2261 0.870 0.000 0.932 0.068
#> GSM1182206 2 0.1964 0.858 0.000 0.944 0.056
#> GSM1182207 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182208 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182209 3 0.6079 0.569 0.000 0.388 0.612
#> GSM1182210 3 0.4555 0.869 0.000 0.200 0.800
#> GSM1182211 3 0.4605 0.869 0.000 0.204 0.796
#> GSM1182212 2 0.5327 0.567 0.000 0.728 0.272
#> GSM1182213 3 0.4555 0.869 0.000 0.200 0.800
#> GSM1182214 3 0.4555 0.869 0.000 0.200 0.800
#> GSM1182215 2 0.1753 0.863 0.000 0.952 0.048
#> GSM1182216 3 0.5650 0.811 0.000 0.312 0.688
#> GSM1182217 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182218 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182219 3 0.4555 0.869 0.000 0.200 0.800
#> GSM1182220 3 0.4887 0.866 0.000 0.228 0.772
#> GSM1182221 3 0.5291 0.848 0.000 0.268 0.732
#> GSM1182222 3 0.5733 0.797 0.000 0.324 0.676
#> GSM1182223 2 0.0747 0.872 0.000 0.984 0.016
#> GSM1182224 2 0.0592 0.871 0.000 0.988 0.012
#> GSM1182225 3 0.5650 0.811 0.000 0.312 0.688
#> GSM1182226 3 0.6225 0.639 0.000 0.432 0.568
#> GSM1182227 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182228 2 0.2356 0.851 0.000 0.928 0.072
#> GSM1182229 2 0.1031 0.872 0.000 0.976 0.024
#> GSM1182230 2 0.1964 0.861 0.000 0.944 0.056
#> GSM1182231 2 0.2261 0.850 0.000 0.932 0.068
#> GSM1182232 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182233 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182234 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182235 3 0.3752 0.847 0.000 0.144 0.856
#> GSM1182236 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182237 2 0.4002 0.811 0.000 0.840 0.160
#> GSM1182238 3 0.4974 0.863 0.000 0.236 0.764
#> GSM1182239 2 0.5016 0.704 0.000 0.760 0.240
#> GSM1182240 3 0.6286 0.379 0.000 0.464 0.536
#> GSM1182241 2 0.4452 0.749 0.000 0.808 0.192
#> GSM1182242 2 0.1964 0.853 0.000 0.944 0.056
#> GSM1182243 2 0.1529 0.867 0.000 0.960 0.040
#> GSM1182244 2 0.2711 0.847 0.000 0.912 0.088
#> GSM1182245 1 0.2796 0.947 0.908 0.000 0.092
#> GSM1182246 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182247 2 0.0237 0.872 0.000 0.996 0.004
#> GSM1182248 2 0.0424 0.871 0.000 0.992 0.008
#> GSM1182249 2 0.1964 0.861 0.000 0.944 0.056
#> GSM1182250 2 0.1163 0.871 0.000 0.972 0.028
#> GSM1182251 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182252 2 0.0237 0.872 0.000 0.996 0.004
#> GSM1182253 2 0.0592 0.871 0.000 0.988 0.012
#> GSM1182254 2 0.0237 0.871 0.000 0.996 0.004
#> GSM1182255 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182256 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182257 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182258 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182259 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182260 2 0.2261 0.849 0.000 0.932 0.068
#> GSM1182261 2 0.1860 0.861 0.000 0.948 0.052
#> GSM1182262 2 0.0747 0.872 0.000 0.984 0.016
#> GSM1182263 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182264 2 0.2625 0.841 0.000 0.916 0.084
#> GSM1182265 2 0.1643 0.868 0.000 0.956 0.044
#> GSM1182266 2 0.1964 0.853 0.000 0.944 0.056
#> GSM1182267 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182268 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182269 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182270 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182271 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182272 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182273 2 0.0237 0.871 0.000 0.996 0.004
#> GSM1182275 2 0.0592 0.873 0.000 0.988 0.012
#> GSM1182276 3 0.6026 0.668 0.000 0.376 0.624
#> GSM1182277 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182278 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182279 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182280 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182281 1 0.0747 0.975 0.984 0.000 0.016
#> GSM1182282 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182283 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182284 1 0.2878 0.940 0.904 0.000 0.096
#> GSM1182285 2 0.0237 0.872 0.000 0.996 0.004
#> GSM1182286 3 0.3816 0.846 0.000 0.148 0.852
#> GSM1182287 2 0.4346 0.665 0.000 0.816 0.184
#> GSM1182288 2 0.1289 0.870 0.000 0.968 0.032
#> GSM1182289 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182290 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182291 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182274 2 0.0237 0.871 0.000 0.996 0.004
#> GSM1182292 3 0.3816 0.846 0.000 0.148 0.852
#> GSM1182293 3 0.4654 0.870 0.000 0.208 0.792
#> GSM1182294 3 0.5926 0.725 0.000 0.356 0.644
#> GSM1182295 3 0.4605 0.869 0.000 0.204 0.796
#> GSM1182296 3 0.3816 0.846 0.000 0.148 0.852
#> GSM1182298 2 0.2165 0.848 0.000 0.936 0.064
#> GSM1182299 2 0.3686 0.780 0.000 0.860 0.140
#> GSM1182300 3 0.5706 0.702 0.000 0.320 0.680
#> GSM1182301 3 0.4235 0.863 0.000 0.176 0.824
#> GSM1182303 3 0.6180 0.643 0.000 0.416 0.584
#> GSM1182304 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182305 1 0.1289 0.969 0.968 0.000 0.032
#> GSM1182306 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182307 3 0.3816 0.846 0.000 0.148 0.852
#> GSM1182309 3 0.4555 0.868 0.000 0.200 0.800
#> GSM1182312 3 0.5363 0.844 0.000 0.276 0.724
#> GSM1182314 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182316 2 0.5327 0.505 0.000 0.728 0.272
#> GSM1182318 2 0.6305 -0.288 0.000 0.516 0.484
#> GSM1182319 2 0.5529 0.604 0.000 0.704 0.296
#> GSM1182320 2 0.6291 -0.340 0.000 0.532 0.468
#> GSM1182321 2 0.3192 0.844 0.000 0.888 0.112
#> GSM1182322 2 0.6286 0.021 0.000 0.536 0.464
#> GSM1182324 2 0.1860 0.861 0.000 0.948 0.052
#> GSM1182297 3 0.3816 0.846 0.000 0.148 0.852
#> GSM1182302 1 0.0000 0.975 1.000 0.000 0.000
#> GSM1182308 3 0.5178 0.854 0.000 0.256 0.744
#> GSM1182310 2 0.5431 0.463 0.000 0.716 0.284
#> GSM1182311 1 0.0892 0.973 0.980 0.000 0.020
#> GSM1182313 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182315 3 0.4555 0.864 0.000 0.200 0.800
#> GSM1182317 3 0.6225 0.545 0.000 0.432 0.568
#> GSM1182323 1 0.0892 0.973 0.980 0.000 0.020
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.4761 0.4967 0.628 0.000 0.000 0.372
#> GSM1182187 4 0.2589 0.5485 0.116 0.000 0.000 0.884
#> GSM1182188 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182190 1 0.6763 0.7003 0.564 0.116 0.000 0.320
#> GSM1182191 1 0.4761 0.4967 0.628 0.000 0.000 0.372
#> GSM1182192 4 0.7168 0.3659 0.236 0.208 0.000 0.556
#> GSM1182193 4 0.7168 0.3659 0.236 0.208 0.000 0.556
#> GSM1182194 3 0.1557 0.8474 0.056 0.000 0.944 0.000
#> GSM1182195 3 0.0707 0.8526 0.020 0.000 0.980 0.000
#> GSM1182196 3 0.5897 0.6454 0.136 0.164 0.700 0.000
#> GSM1182197 3 0.2816 0.8445 0.064 0.036 0.900 0.000
#> GSM1182198 3 0.2675 0.8333 0.100 0.000 0.892 0.008
#> GSM1182199 3 0.2976 0.8247 0.120 0.000 0.872 0.008
#> GSM1182200 3 0.3447 0.7700 0.020 0.128 0.852 0.000
#> GSM1182201 3 0.2124 0.8537 0.040 0.028 0.932 0.000
#> GSM1182202 4 0.4661 0.0225 0.348 0.000 0.000 0.652
#> GSM1182203 4 0.2589 0.5485 0.116 0.000 0.000 0.884
#> GSM1182204 4 0.4624 0.0490 0.340 0.000 0.000 0.660
#> GSM1182205 3 0.1406 0.8531 0.024 0.016 0.960 0.000
#> GSM1182206 3 0.3342 0.7731 0.032 0.100 0.868 0.000
#> GSM1182207 1 0.3801 0.7281 0.780 0.000 0.000 0.220
#> GSM1182208 1 0.3801 0.7281 0.780 0.000 0.000 0.220
#> GSM1182209 2 0.5247 0.8459 0.032 0.684 0.284 0.000
#> GSM1182210 2 0.3726 0.8717 0.000 0.788 0.212 0.000
#> GSM1182211 2 0.4122 0.8779 0.004 0.760 0.236 0.000
#> GSM1182212 3 0.4699 0.4613 0.004 0.320 0.676 0.000
#> GSM1182213 2 0.3870 0.8714 0.004 0.788 0.208 0.000
#> GSM1182214 2 0.3870 0.8714 0.004 0.788 0.208 0.000
#> GSM1182215 3 0.1174 0.8481 0.012 0.020 0.968 0.000
#> GSM1182216 2 0.5311 0.8264 0.024 0.648 0.328 0.000
#> GSM1182217 4 0.4776 -0.0735 0.376 0.000 0.000 0.624
#> GSM1182218 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182219 2 0.3726 0.8724 0.000 0.788 0.212 0.000
#> GSM1182220 2 0.4485 0.8734 0.012 0.740 0.248 0.000
#> GSM1182221 2 0.5206 0.8397 0.024 0.668 0.308 0.000
#> GSM1182222 2 0.5386 0.8118 0.024 0.632 0.344 0.000
#> GSM1182223 3 0.0804 0.8499 0.008 0.012 0.980 0.000
#> GSM1182224 3 0.0804 0.8502 0.008 0.012 0.980 0.000
#> GSM1182225 2 0.5386 0.8118 0.024 0.632 0.344 0.000
#> GSM1182226 2 0.5771 0.6209 0.028 0.512 0.460 0.000
#> GSM1182227 4 0.7193 0.3570 0.240 0.208 0.000 0.552
#> GSM1182228 3 0.3157 0.8168 0.144 0.004 0.852 0.000
#> GSM1182229 3 0.0657 0.8495 0.004 0.012 0.984 0.000
#> GSM1182230 3 0.1356 0.8450 0.008 0.032 0.960 0.000
#> GSM1182231 3 0.4019 0.6201 0.012 0.196 0.792 0.000
#> GSM1182232 4 0.6837 0.1169 0.340 0.116 0.000 0.544
#> GSM1182233 1 0.6779 0.6928 0.560 0.116 0.000 0.324
#> GSM1182234 4 0.7062 0.3751 0.224 0.204 0.000 0.572
#> GSM1182235 2 0.5558 0.8627 0.080 0.712 0.208 0.000
#> GSM1182236 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182237 3 0.5470 0.6778 0.100 0.168 0.732 0.000
#> GSM1182238 2 0.4422 0.8715 0.008 0.736 0.256 0.000
#> GSM1182239 3 0.6463 0.5389 0.160 0.196 0.644 0.000
#> GSM1182240 2 0.5577 0.8270 0.036 0.636 0.328 0.000
#> GSM1182241 3 0.5416 0.7049 0.148 0.112 0.740 0.000
#> GSM1182242 3 0.3052 0.8223 0.136 0.004 0.860 0.000
#> GSM1182243 3 0.1151 0.8477 0.008 0.024 0.968 0.000
#> GSM1182244 3 0.2976 0.8239 0.120 0.008 0.872 0.000
#> GSM1182245 4 0.7239 0.3399 0.248 0.208 0.000 0.544
#> GSM1182246 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.1743 0.8486 0.056 0.004 0.940 0.000
#> GSM1182248 3 0.0376 0.8506 0.004 0.004 0.992 0.000
#> GSM1182249 3 0.1305 0.8437 0.004 0.036 0.960 0.000
#> GSM1182250 3 0.0376 0.8520 0.004 0.004 0.992 0.000
#> GSM1182251 1 0.3975 0.7151 0.760 0.000 0.000 0.240
#> GSM1182252 3 0.1978 0.8462 0.068 0.004 0.928 0.000
#> GSM1182253 3 0.0336 0.8502 0.000 0.008 0.992 0.000
#> GSM1182254 3 0.0000 0.8511 0.000 0.000 1.000 0.000
#> GSM1182255 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.2589 0.5485 0.116 0.000 0.000 0.884
#> GSM1182258 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.2921 0.8157 0.140 0.000 0.860 0.000
#> GSM1182261 3 0.2256 0.8263 0.020 0.056 0.924 0.000
#> GSM1182262 3 0.0804 0.8495 0.008 0.012 0.980 0.000
#> GSM1182263 1 0.4907 0.3081 0.580 0.000 0.000 0.420
#> GSM1182264 3 0.2973 0.8136 0.144 0.000 0.856 0.000
#> GSM1182265 3 0.1004 0.8495 0.004 0.024 0.972 0.000
#> GSM1182266 3 0.2868 0.8185 0.136 0.000 0.864 0.000
#> GSM1182267 4 0.7062 0.3751 0.224 0.204 0.000 0.572
#> GSM1182268 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182269 1 0.6763 0.7003 0.564 0.116 0.000 0.320
#> GSM1182270 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182271 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0000 0.8511 0.000 0.000 1.000 0.000
#> GSM1182275 3 0.1042 0.8541 0.020 0.008 0.972 0.000
#> GSM1182276 2 0.4483 0.8459 0.004 0.712 0.284 0.000
#> GSM1182277 4 0.7062 0.3751 0.224 0.204 0.000 0.572
#> GSM1182278 4 0.7168 0.3659 0.236 0.208 0.000 0.556
#> GSM1182279 1 0.3942 0.7191 0.764 0.000 0.000 0.236
#> GSM1182280 1 0.3801 0.7281 0.780 0.000 0.000 0.220
#> GSM1182281 4 0.7004 0.3808 0.220 0.200 0.000 0.580
#> GSM1182282 4 0.7140 0.3678 0.236 0.204 0.000 0.560
#> GSM1182283 4 0.7168 0.3659 0.236 0.208 0.000 0.556
#> GSM1182284 4 0.7114 0.3708 0.232 0.204 0.000 0.564
#> GSM1182285 3 0.1792 0.8449 0.068 0.000 0.932 0.000
#> GSM1182286 2 0.5558 0.8627 0.080 0.712 0.208 0.000
#> GSM1182287 3 0.2469 0.7870 0.000 0.108 0.892 0.000
#> GSM1182288 3 0.0927 0.8542 0.016 0.008 0.976 0.000
#> GSM1182289 1 0.3942 0.7191 0.764 0.000 0.000 0.236
#> GSM1182290 1 0.3801 0.7281 0.780 0.000 0.000 0.220
#> GSM1182291 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0592 0.8524 0.016 0.000 0.984 0.000
#> GSM1182292 2 0.5727 0.8631 0.080 0.692 0.228 0.000
#> GSM1182293 2 0.3801 0.8758 0.000 0.780 0.220 0.000
#> GSM1182294 2 0.4855 0.7757 0.004 0.644 0.352 0.000
#> GSM1182295 2 0.3726 0.8724 0.000 0.788 0.212 0.000
#> GSM1182296 2 0.5620 0.8613 0.084 0.708 0.208 0.000
#> GSM1182298 3 0.2760 0.8242 0.128 0.000 0.872 0.000
#> GSM1182299 3 0.4606 0.6019 0.012 0.264 0.724 0.000
#> GSM1182300 2 0.7061 0.7233 0.148 0.540 0.312 0.000
#> GSM1182301 2 0.5022 0.8747 0.044 0.736 0.220 0.000
#> GSM1182303 2 0.5543 0.6694 0.020 0.556 0.424 0.000
#> GSM1182304 1 0.3837 0.7270 0.776 0.000 0.000 0.224
#> GSM1182305 4 0.4877 0.0921 0.408 0.000 0.000 0.592
#> GSM1182306 4 0.2589 0.5485 0.116 0.000 0.000 0.884
#> GSM1182307 2 0.5756 0.8626 0.084 0.692 0.224 0.000
#> GSM1182309 2 0.4833 0.8785 0.032 0.740 0.228 0.000
#> GSM1182312 2 0.4980 0.8522 0.016 0.680 0.304 0.000
#> GSM1182314 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182316 3 0.5323 0.1263 0.020 0.352 0.628 0.000
#> GSM1182318 2 0.4769 0.8261 0.008 0.684 0.308 0.000
#> GSM1182319 3 0.6934 0.2750 0.152 0.276 0.572 0.000
#> GSM1182320 2 0.5508 0.7284 0.020 0.572 0.408 0.000
#> GSM1182321 3 0.5993 0.6362 0.148 0.160 0.692 0.000
#> GSM1182322 2 0.6792 0.5043 0.096 0.476 0.428 0.000
#> GSM1182324 3 0.3450 0.6956 0.008 0.156 0.836 0.000
#> GSM1182297 2 0.5558 0.8627 0.080 0.712 0.208 0.000
#> GSM1182302 4 0.4661 0.0225 0.348 0.000 0.000 0.652
#> GSM1182308 2 0.5013 0.8536 0.020 0.688 0.292 0.000
#> GSM1182310 3 0.4584 0.3391 0.004 0.300 0.696 0.000
#> GSM1182311 1 0.6746 0.7064 0.568 0.116 0.000 0.316
#> GSM1182313 4 0.0000 0.5971 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.4964 0.8782 0.032 0.724 0.244 0.000
#> GSM1182317 2 0.4456 0.8546 0.004 0.716 0.280 0.000
#> GSM1182323 1 0.6763 0.7003 0.564 0.116 0.000 0.320
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.6151 0.1326 0.596 0.032 0.000 0.284 0.088
#> GSM1182187 4 0.4914 0.6556 0.260 0.000 0.000 0.676 0.064
#> GSM1182188 4 0.1768 0.7779 0.072 0.000 0.000 0.924 0.004
#> GSM1182189 1 0.0703 0.4560 0.976 0.000 0.000 0.024 0.000
#> GSM1182190 1 0.0703 0.4560 0.976 0.000 0.000 0.024 0.000
#> GSM1182191 1 0.6390 0.2024 0.596 0.032 0.000 0.240 0.132
#> GSM1182192 1 0.6303 -0.4826 0.524 0.000 0.000 0.196 0.280
#> GSM1182193 1 0.6417 -0.5105 0.504 0.000 0.000 0.216 0.280
#> GSM1182194 3 0.2929 0.7811 0.000 0.000 0.820 0.000 0.180
#> GSM1182195 3 0.2516 0.7867 0.000 0.000 0.860 0.000 0.140
#> GSM1182196 3 0.5139 0.7186 0.000 0.104 0.708 0.008 0.180
#> GSM1182197 3 0.2707 0.8095 0.000 0.024 0.876 0.000 0.100
#> GSM1182198 3 0.3210 0.7634 0.000 0.000 0.788 0.000 0.212
#> GSM1182199 3 0.3395 0.7532 0.000 0.000 0.764 0.000 0.236
#> GSM1182200 3 0.4107 0.7612 0.000 0.124 0.808 0.032 0.036
#> GSM1182201 3 0.1774 0.8168 0.000 0.016 0.932 0.000 0.052
#> GSM1182202 4 0.5369 0.5076 0.388 0.000 0.000 0.552 0.060
#> GSM1182203 4 0.4788 0.6704 0.240 0.000 0.000 0.696 0.064
#> GSM1182204 4 0.5309 0.5418 0.364 0.000 0.000 0.576 0.060
#> GSM1182205 3 0.2769 0.8212 0.000 0.024 0.892 0.020 0.064
#> GSM1182206 3 0.5367 0.7380 0.000 0.120 0.732 0.056 0.092
#> GSM1182207 1 0.2712 0.4405 0.880 0.032 0.000 0.000 0.088
#> GSM1182208 1 0.2712 0.4405 0.880 0.032 0.000 0.000 0.088
#> GSM1182209 2 0.4576 0.6714 0.000 0.692 0.268 0.000 0.040
#> GSM1182210 2 0.2676 0.8469 0.000 0.884 0.080 0.000 0.036
#> GSM1182211 2 0.1768 0.8495 0.000 0.924 0.072 0.000 0.004
#> GSM1182212 3 0.4946 0.4967 0.000 0.368 0.596 0.000 0.036
#> GSM1182213 2 0.1697 0.8451 0.000 0.932 0.060 0.000 0.008
#> GSM1182214 2 0.1571 0.8457 0.000 0.936 0.060 0.000 0.004
#> GSM1182215 3 0.3709 0.7929 0.000 0.072 0.840 0.020 0.068
#> GSM1182216 2 0.4538 0.8129 0.000 0.776 0.140 0.060 0.024
#> GSM1182217 1 0.5309 -0.0187 0.576 0.000 0.000 0.364 0.060
#> GSM1182218 1 0.0703 0.4560 0.976 0.000 0.000 0.024 0.000
#> GSM1182219 2 0.1628 0.8454 0.000 0.936 0.056 0.000 0.008
#> GSM1182220 2 0.2644 0.8500 0.000 0.888 0.088 0.012 0.012
#> GSM1182221 2 0.4956 0.8157 0.000 0.760 0.124 0.060 0.056
#> GSM1182222 2 0.5087 0.7836 0.000 0.728 0.180 0.060 0.032
#> GSM1182223 3 0.2775 0.8005 0.000 0.068 0.888 0.008 0.036
#> GSM1182224 3 0.3355 0.8009 0.000 0.048 0.856 0.012 0.084
#> GSM1182225 2 0.4942 0.7964 0.000 0.744 0.164 0.060 0.032
#> GSM1182226 2 0.6255 0.4742 0.000 0.540 0.356 0.060 0.044
#> GSM1182227 1 0.6396 -0.5001 0.508 0.000 0.000 0.212 0.280
#> GSM1182228 3 0.4226 0.7936 0.000 0.060 0.764 0.000 0.176
#> GSM1182229 3 0.3113 0.7990 0.000 0.068 0.872 0.012 0.048
#> GSM1182230 3 0.3508 0.7941 0.000 0.076 0.848 0.012 0.064
#> GSM1182231 3 0.5635 0.4859 0.000 0.284 0.624 0.012 0.080
#> GSM1182232 1 0.3639 0.1693 0.812 0.000 0.000 0.144 0.044
#> GSM1182233 1 0.0880 0.4492 0.968 0.000 0.000 0.032 0.000
#> GSM1182234 1 0.6335 -0.4831 0.520 0.000 0.000 0.204 0.276
#> GSM1182235 2 0.3714 0.8383 0.000 0.832 0.056 0.012 0.100
#> GSM1182236 1 0.0703 0.4558 0.976 0.000 0.000 0.024 0.000
#> GSM1182237 3 0.6276 0.6122 0.000 0.228 0.584 0.012 0.176
#> GSM1182238 2 0.2878 0.8485 0.000 0.880 0.084 0.024 0.012
#> GSM1182239 3 0.5649 0.6690 0.000 0.132 0.664 0.012 0.192
#> GSM1182240 2 0.5380 0.4753 0.000 0.588 0.360 0.016 0.036
#> GSM1182241 3 0.4377 0.7513 0.000 0.044 0.756 0.008 0.192
#> GSM1182242 3 0.3914 0.8006 0.000 0.048 0.788 0.000 0.164
#> GSM1182243 3 0.3277 0.7965 0.000 0.068 0.856 0.004 0.072
#> GSM1182244 3 0.3616 0.8042 0.000 0.032 0.804 0.000 0.164
#> GSM1182245 1 0.6438 -0.5122 0.500 0.000 0.000 0.220 0.280
#> GSM1182246 4 0.1851 0.7775 0.088 0.000 0.000 0.912 0.000
#> GSM1182247 3 0.2782 0.8154 0.000 0.048 0.880 0.000 0.072
#> GSM1182248 3 0.2227 0.8100 0.000 0.048 0.916 0.004 0.032
#> GSM1182249 3 0.1830 0.8121 0.000 0.012 0.932 0.004 0.052
#> GSM1182250 3 0.1197 0.8129 0.000 0.000 0.952 0.000 0.048
#> GSM1182251 1 0.4945 0.3522 0.688 0.032 0.000 0.020 0.260
#> GSM1182252 3 0.3019 0.8143 0.000 0.048 0.864 0.000 0.088
#> GSM1182253 3 0.1267 0.8167 0.000 0.004 0.960 0.012 0.024
#> GSM1182254 3 0.0000 0.8130 0.000 0.000 1.000 0.000 0.000
#> GSM1182255 4 0.1892 0.7775 0.080 0.000 0.000 0.916 0.004
#> GSM1182256 4 0.1608 0.7787 0.072 0.000 0.000 0.928 0.000
#> GSM1182257 4 0.4937 0.6521 0.264 0.000 0.000 0.672 0.064
#> GSM1182258 4 0.1851 0.7775 0.088 0.000 0.000 0.912 0.000
#> GSM1182259 4 0.1608 0.7787 0.072 0.000 0.000 0.928 0.000
#> GSM1182260 3 0.2690 0.7893 0.000 0.000 0.844 0.000 0.156
#> GSM1182261 3 0.4037 0.7872 0.000 0.072 0.820 0.024 0.084
#> GSM1182262 3 0.3209 0.7977 0.000 0.068 0.864 0.008 0.060
#> GSM1182263 1 0.6459 0.2023 0.580 0.032 0.000 0.128 0.260
#> GSM1182264 3 0.2690 0.7858 0.000 0.000 0.844 0.000 0.156
#> GSM1182265 3 0.1717 0.8122 0.000 0.004 0.936 0.008 0.052
#> GSM1182266 3 0.2516 0.7931 0.000 0.000 0.860 0.000 0.140
#> GSM1182267 1 0.6287 -0.4776 0.528 0.000 0.000 0.196 0.276
#> GSM1182268 1 0.0703 0.4558 0.976 0.000 0.000 0.024 0.000
#> GSM1182269 1 0.0794 0.4545 0.972 0.000 0.000 0.028 0.000
#> GSM1182270 1 0.0609 0.4565 0.980 0.000 0.000 0.020 0.000
#> GSM1182271 4 0.2488 0.7559 0.124 0.000 0.000 0.872 0.004
#> GSM1182272 4 0.1608 0.7787 0.072 0.000 0.000 0.928 0.000
#> GSM1182273 3 0.0000 0.8130 0.000 0.000 1.000 0.000 0.000
#> GSM1182275 3 0.1041 0.8163 0.000 0.004 0.964 0.000 0.032
#> GSM1182276 2 0.2574 0.8382 0.000 0.876 0.112 0.000 0.012
#> GSM1182277 1 0.6335 -0.4862 0.520 0.000 0.000 0.204 0.276
#> GSM1182278 1 0.6374 -0.4981 0.512 0.000 0.000 0.208 0.280
#> GSM1182279 1 0.4855 0.3532 0.692 0.032 0.000 0.016 0.260
#> GSM1182280 1 0.4652 0.3562 0.700 0.032 0.000 0.008 0.260
#> GSM1182281 5 0.6623 0.0000 0.320 0.000 0.000 0.236 0.444
#> GSM1182282 1 0.6443 -0.5111 0.500 0.000 0.000 0.224 0.276
#> GSM1182283 1 0.6396 -0.5042 0.508 0.000 0.000 0.212 0.280
#> GSM1182284 1 0.6443 -0.5111 0.500 0.000 0.000 0.224 0.276
#> GSM1182285 3 0.3752 0.7962 0.000 0.048 0.804 0.000 0.148
#> GSM1182286 2 0.3817 0.8360 0.000 0.824 0.056 0.012 0.108
#> GSM1182287 3 0.3214 0.7898 0.000 0.104 0.856 0.008 0.032
#> GSM1182288 3 0.2536 0.8155 0.000 0.052 0.900 0.004 0.044
#> GSM1182289 1 0.4855 0.3532 0.692 0.032 0.000 0.016 0.260
#> GSM1182290 1 0.2712 0.4405 0.880 0.032 0.000 0.000 0.088
#> GSM1182291 4 0.1608 0.7787 0.072 0.000 0.000 0.928 0.000
#> GSM1182274 3 0.0290 0.8136 0.000 0.000 0.992 0.000 0.008
#> GSM1182292 2 0.4458 0.8178 0.000 0.780 0.108 0.012 0.100
#> GSM1182293 2 0.2782 0.8498 0.000 0.880 0.072 0.000 0.048
#> GSM1182294 2 0.5144 0.5455 0.000 0.640 0.292 0.000 0.068
#> GSM1182295 2 0.1410 0.8458 0.000 0.940 0.060 0.000 0.000
#> GSM1182296 2 0.3766 0.8360 0.000 0.828 0.056 0.012 0.104
#> GSM1182298 3 0.3452 0.7495 0.000 0.000 0.756 0.000 0.244
#> GSM1182299 3 0.4096 0.7113 0.000 0.200 0.760 0.000 0.040
#> GSM1182300 2 0.6141 0.6191 0.000 0.600 0.232 0.012 0.156
#> GSM1182301 2 0.3192 0.8306 0.000 0.848 0.112 0.000 0.040
#> GSM1182303 2 0.4578 0.7869 0.000 0.744 0.200 0.040 0.016
#> GSM1182304 1 0.4855 0.3529 0.692 0.032 0.000 0.016 0.260
#> GSM1182305 1 0.7195 0.0300 0.464 0.032 0.000 0.280 0.224
#> GSM1182306 4 0.4937 0.6521 0.264 0.000 0.000 0.672 0.064
#> GSM1182307 2 0.4285 0.8334 0.000 0.792 0.080 0.012 0.116
#> GSM1182309 2 0.4298 0.8384 0.000 0.788 0.096 0.008 0.108
#> GSM1182312 2 0.4711 0.8247 0.000 0.764 0.152 0.040 0.044
#> GSM1182314 4 0.1851 0.7775 0.088 0.000 0.000 0.912 0.000
#> GSM1182316 3 0.5790 0.4675 0.000 0.268 0.636 0.052 0.044
#> GSM1182318 2 0.4457 0.4781 0.000 0.620 0.368 0.000 0.012
#> GSM1182319 3 0.6347 0.4791 0.000 0.216 0.564 0.008 0.212
#> GSM1182320 3 0.6326 -0.2648 0.000 0.448 0.452 0.052 0.048
#> GSM1182321 3 0.5107 0.7026 0.000 0.108 0.688 0.000 0.204
#> GSM1182322 3 0.6537 0.2031 0.000 0.324 0.508 0.012 0.156
#> GSM1182324 3 0.3766 0.7459 0.000 0.104 0.828 0.012 0.056
#> GSM1182297 2 0.3727 0.8367 0.000 0.832 0.060 0.012 0.096
#> GSM1182302 4 0.5331 0.5280 0.372 0.000 0.000 0.568 0.060
#> GSM1182308 2 0.3739 0.8338 0.000 0.824 0.116 0.052 0.008
#> GSM1182310 3 0.5271 0.4292 0.000 0.284 0.652 0.016 0.048
#> GSM1182311 1 0.0703 0.4558 0.976 0.000 0.000 0.024 0.000
#> GSM1182313 4 0.1608 0.7787 0.072 0.000 0.000 0.928 0.000
#> GSM1182315 2 0.3340 0.8538 0.000 0.860 0.076 0.016 0.048
#> GSM1182317 2 0.4526 0.6260 0.000 0.672 0.300 0.000 0.028
#> GSM1182323 1 0.0609 0.4565 0.980 0.000 0.000 0.020 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.6031 0.3992 0.248 0.000 0.000 0.360 0.392 NA
#> GSM1182187 4 0.4104 0.7386 0.148 0.000 0.000 0.748 0.000 NA
#> GSM1182188 4 0.0632 0.8243 0.024 0.000 0.000 0.976 0.000 NA
#> GSM1182189 1 0.5490 0.4317 0.624 0.016 0.000 0.008 0.108 NA
#> GSM1182190 1 0.5468 0.4339 0.628 0.016 0.000 0.008 0.108 NA
#> GSM1182191 5 0.6001 0.4943 0.252 0.000 0.000 0.320 0.428 NA
#> GSM1182192 1 0.2178 0.5448 0.868 0.000 0.000 0.132 0.000 NA
#> GSM1182193 1 0.2662 0.5385 0.840 0.000 0.000 0.152 0.004 NA
#> GSM1182194 3 0.3659 0.6092 0.000 0.000 0.636 0.000 0.000 NA
#> GSM1182195 3 0.4009 0.6164 0.000 0.000 0.684 0.000 0.028 NA
#> GSM1182196 3 0.6691 0.4578 0.000 0.152 0.576 0.020 0.100 NA
#> GSM1182197 3 0.4632 0.6482 0.000 0.060 0.736 0.000 0.048 NA
#> GSM1182198 3 0.4252 0.5889 0.000 0.000 0.604 0.000 0.024 NA
#> GSM1182199 3 0.4326 0.5755 0.000 0.000 0.572 0.000 0.024 NA
#> GSM1182200 3 0.5470 0.5235 0.000 0.124 0.672 0.000 0.136 NA
#> GSM1182201 3 0.3725 0.6756 0.000 0.064 0.804 0.000 0.016 NA
#> GSM1182202 4 0.5007 0.6007 0.244 0.000 0.000 0.640 0.004 NA
#> GSM1182203 4 0.3914 0.7526 0.128 0.000 0.000 0.768 0.000 NA
#> GSM1182204 4 0.4725 0.6539 0.204 0.000 0.000 0.684 0.004 NA
#> GSM1182205 3 0.3867 0.6825 0.000 0.000 0.748 0.000 0.052 NA
#> GSM1182206 3 0.6265 0.5588 0.000 0.068 0.568 0.000 0.164 NA
#> GSM1182207 1 0.3881 -0.1685 0.600 0.000 0.000 0.004 0.396 NA
#> GSM1182208 1 0.3881 -0.1685 0.600 0.000 0.000 0.004 0.396 NA
#> GSM1182209 2 0.4883 0.6585 0.000 0.616 0.320 0.000 0.048 NA
#> GSM1182210 2 0.2398 0.7732 0.000 0.876 0.104 0.000 0.020 NA
#> GSM1182211 2 0.3514 0.7788 0.000 0.752 0.228 0.000 0.020 NA
#> GSM1182212 3 0.6033 0.0752 0.000 0.368 0.496 0.000 0.072 NA
#> GSM1182213 2 0.4049 0.7849 0.000 0.740 0.208 0.000 0.044 NA
#> GSM1182214 2 0.3183 0.7915 0.000 0.788 0.200 0.000 0.008 NA
#> GSM1182215 3 0.4399 0.6452 0.000 0.024 0.728 0.000 0.048 NA
#> GSM1182216 2 0.4713 0.7643 0.000 0.692 0.180 0.000 0.124 NA
#> GSM1182217 4 0.6465 0.3404 0.248 0.000 0.000 0.536 0.092 NA
#> GSM1182218 1 0.5468 0.4353 0.628 0.016 0.000 0.008 0.108 NA
#> GSM1182219 2 0.2581 0.7868 0.000 0.856 0.128 0.000 0.016 NA
#> GSM1182220 2 0.3394 0.7942 0.000 0.804 0.144 0.000 0.052 NA
#> GSM1182221 2 0.4909 0.7608 0.000 0.680 0.168 0.000 0.144 NA
#> GSM1182222 2 0.5137 0.7205 0.000 0.604 0.288 0.000 0.104 NA
#> GSM1182223 3 0.2883 0.6864 0.000 0.040 0.860 0.000 0.008 NA
#> GSM1182224 3 0.3288 0.6647 0.000 0.000 0.724 0.000 0.000 NA
#> GSM1182225 2 0.4893 0.7577 0.000 0.668 0.200 0.000 0.128 NA
#> GSM1182226 2 0.5342 0.6710 0.000 0.560 0.324 0.000 0.112 NA
#> GSM1182227 1 0.2520 0.5425 0.844 0.000 0.000 0.152 0.004 NA
#> GSM1182228 3 0.3704 0.6867 0.000 0.016 0.744 0.000 0.008 NA
#> GSM1182229 3 0.3033 0.6900 0.000 0.012 0.848 0.000 0.032 NA
#> GSM1182230 3 0.4580 0.6380 0.000 0.036 0.716 0.000 0.044 NA
#> GSM1182231 3 0.5650 0.5469 0.000 0.132 0.640 0.000 0.052 NA
#> GSM1182232 1 0.6250 0.4503 0.596 0.016 0.000 0.080 0.084 NA
#> GSM1182233 1 0.5189 0.4321 0.640 0.016 0.000 0.000 0.104 NA
#> GSM1182234 1 0.2260 0.5451 0.860 0.000 0.000 0.140 0.000 NA
#> GSM1182235 2 0.5103 0.7733 0.000 0.724 0.128 0.020 0.092 NA
#> GSM1182236 1 0.5229 0.4314 0.636 0.016 0.000 0.000 0.108 NA
#> GSM1182237 3 0.7467 0.4450 0.000 0.136 0.444 0.020 0.144 NA
#> GSM1182238 2 0.3139 0.7959 0.000 0.816 0.152 0.000 0.032 NA
#> GSM1182239 3 0.6837 0.3939 0.000 0.136 0.556 0.016 0.136 NA
#> GSM1182240 2 0.5110 0.6096 0.000 0.556 0.368 0.000 0.068 NA
#> GSM1182241 3 0.5911 0.5512 0.000 0.072 0.656 0.020 0.096 NA
#> GSM1182242 3 0.4134 0.6754 0.000 0.004 0.640 0.000 0.016 NA
#> GSM1182243 3 0.3837 0.6665 0.000 0.008 0.768 0.000 0.044 NA
#> GSM1182244 3 0.5219 0.6701 0.000 0.032 0.620 0.008 0.040 NA
#> GSM1182245 1 0.2805 0.5321 0.828 0.000 0.000 0.160 0.012 NA
#> GSM1182246 4 0.1155 0.8227 0.036 0.000 0.000 0.956 0.004 NA
#> GSM1182247 3 0.3136 0.6938 0.000 0.000 0.768 0.000 0.004 NA
#> GSM1182248 3 0.3231 0.6880 0.000 0.000 0.784 0.000 0.016 NA
#> GSM1182249 3 0.4041 0.6385 0.000 0.068 0.796 0.000 0.048 NA
#> GSM1182250 3 0.2625 0.6980 0.000 0.000 0.872 0.000 0.056 NA
#> GSM1182251 5 0.4504 0.7341 0.368 0.000 0.000 0.040 0.592 NA
#> GSM1182252 3 0.3351 0.6846 0.000 0.000 0.712 0.000 0.000 NA
#> GSM1182253 3 0.2340 0.6970 0.000 0.000 0.852 0.000 0.000 NA
#> GSM1182254 3 0.2342 0.6961 0.000 0.020 0.888 0.000 0.004 NA
#> GSM1182255 4 0.0713 0.8253 0.028 0.000 0.000 0.972 0.000 NA
#> GSM1182256 4 0.0547 0.8241 0.020 0.000 0.000 0.980 0.000 NA
#> GSM1182257 4 0.4209 0.7317 0.160 0.000 0.000 0.736 0.000 NA
#> GSM1182258 4 0.1080 0.8229 0.032 0.000 0.000 0.960 0.004 NA
#> GSM1182259 4 0.0547 0.8241 0.020 0.000 0.000 0.980 0.000 NA
#> GSM1182260 3 0.3533 0.6651 0.000 0.004 0.748 0.000 0.012 NA
#> GSM1182261 3 0.5238 0.6288 0.000 0.052 0.672 0.000 0.076 NA
#> GSM1182262 3 0.3867 0.6667 0.000 0.008 0.768 0.000 0.048 NA
#> GSM1182263 5 0.5042 0.6389 0.308 0.000 0.000 0.100 0.592 NA
#> GSM1182264 3 0.3860 0.6629 0.000 0.000 0.728 0.000 0.036 NA
#> GSM1182265 3 0.2814 0.7002 0.000 0.004 0.864 0.000 0.052 NA
#> GSM1182266 3 0.3509 0.6657 0.000 0.000 0.744 0.000 0.016 NA
#> GSM1182267 1 0.2048 0.5422 0.880 0.000 0.000 0.120 0.000 NA
#> GSM1182268 1 0.5229 0.4314 0.636 0.016 0.000 0.000 0.108 NA
#> GSM1182269 1 0.5646 0.4361 0.620 0.016 0.000 0.016 0.108 NA
#> GSM1182270 1 0.5468 0.4340 0.628 0.016 0.000 0.008 0.108 NA
#> GSM1182271 4 0.1866 0.8056 0.084 0.000 0.000 0.908 0.000 NA
#> GSM1182272 4 0.0547 0.8241 0.020 0.000 0.000 0.980 0.000 NA
#> GSM1182273 3 0.2112 0.6966 0.000 0.000 0.896 0.000 0.016 NA
#> GSM1182275 3 0.1787 0.7020 0.000 0.004 0.920 0.000 0.008 NA
#> GSM1182276 2 0.4703 0.7345 0.000 0.684 0.236 0.000 0.064 NA
#> GSM1182277 1 0.2219 0.5449 0.864 0.000 0.000 0.136 0.000 NA
#> GSM1182278 1 0.2340 0.5438 0.852 0.000 0.000 0.148 0.000 NA
#> GSM1182279 5 0.4400 0.7338 0.376 0.000 0.000 0.032 0.592 NA
#> GSM1182280 5 0.4283 0.7281 0.384 0.000 0.000 0.024 0.592 NA
#> GSM1182281 1 0.5436 0.1781 0.596 0.000 0.000 0.192 0.208 NA
#> GSM1182282 1 0.2558 0.5400 0.840 0.000 0.000 0.156 0.004 NA
#> GSM1182283 1 0.2558 0.5379 0.840 0.000 0.000 0.156 0.004 NA
#> GSM1182284 1 0.2520 0.5416 0.844 0.000 0.000 0.152 0.004 NA
#> GSM1182285 3 0.3737 0.6423 0.000 0.000 0.608 0.000 0.000 NA
#> GSM1182286 2 0.5232 0.7720 0.000 0.716 0.128 0.020 0.092 NA
#> GSM1182287 3 0.3760 0.6300 0.000 0.128 0.800 0.000 0.020 NA
#> GSM1182288 3 0.2664 0.6971 0.000 0.000 0.816 0.000 0.000 NA
#> GSM1182289 5 0.4400 0.7346 0.376 0.000 0.000 0.032 0.592 NA
#> GSM1182290 1 0.3881 -0.1685 0.600 0.000 0.000 0.004 0.396 NA
#> GSM1182291 4 0.0547 0.8241 0.020 0.000 0.000 0.980 0.000 NA
#> GSM1182274 3 0.2214 0.6970 0.000 0.016 0.888 0.000 0.000 NA
#> GSM1182292 2 0.5959 0.7466 0.000 0.612 0.232 0.020 0.100 NA
#> GSM1182293 2 0.3390 0.7979 0.000 0.808 0.152 0.000 0.032 NA
#> GSM1182294 2 0.5583 0.6028 0.000 0.588 0.288 0.000 0.032 NA
#> GSM1182295 2 0.2260 0.7922 0.000 0.860 0.140 0.000 0.000 NA
#> GSM1182296 2 0.5317 0.7753 0.000 0.704 0.144 0.020 0.092 NA
#> GSM1182298 3 0.4348 0.5699 0.000 0.000 0.560 0.000 0.024 NA
#> GSM1182299 3 0.5641 0.4240 0.000 0.240 0.620 0.000 0.064 NA
#> GSM1182300 2 0.6925 0.5188 0.000 0.460 0.336 0.020 0.096 NA
#> GSM1182301 2 0.4077 0.7919 0.000 0.736 0.212 0.000 0.044 NA
#> GSM1182303 2 0.5495 0.7140 0.000 0.612 0.224 0.000 0.148 NA
#> GSM1182304 5 0.4283 0.7281 0.384 0.000 0.000 0.024 0.592 NA
#> GSM1182305 5 0.5559 0.5621 0.176 0.000 0.000 0.284 0.540 NA
#> GSM1182306 4 0.4209 0.7317 0.160 0.000 0.000 0.736 0.000 NA
#> GSM1182307 2 0.5794 0.7554 0.000 0.640 0.212 0.020 0.084 NA
#> GSM1182309 2 0.5248 0.7529 0.000 0.656 0.248 0.020 0.056 NA
#> GSM1182312 2 0.4693 0.7636 0.000 0.692 0.188 0.000 0.116 NA
#> GSM1182314 4 0.1080 0.8229 0.032 0.000 0.000 0.960 0.004 NA
#> GSM1182316 3 0.5781 -0.1228 0.000 0.336 0.520 0.000 0.128 NA
#> GSM1182318 2 0.4967 0.5251 0.000 0.552 0.392 0.000 0.040 NA
#> GSM1182319 3 0.7122 0.0722 0.000 0.276 0.480 0.020 0.116 NA
#> GSM1182320 2 0.5757 0.4693 0.000 0.440 0.420 0.000 0.132 NA
#> GSM1182321 3 0.6470 0.4902 0.000 0.144 0.544 0.000 0.088 NA
#> GSM1182322 3 0.6758 -0.2614 0.000 0.372 0.444 0.020 0.104 NA
#> GSM1182324 3 0.5058 0.5386 0.000 0.144 0.708 0.000 0.088 NA
#> GSM1182297 2 0.5187 0.7738 0.000 0.716 0.132 0.020 0.096 NA
#> GSM1182302 4 0.4843 0.6379 0.216 0.000 0.000 0.668 0.004 NA
#> GSM1182308 2 0.4449 0.7800 0.000 0.712 0.164 0.000 0.124 NA
#> GSM1182310 3 0.4840 0.0316 0.000 0.360 0.580 0.000 0.056 NA
#> GSM1182311 1 0.5468 0.4340 0.628 0.016 0.000 0.008 0.108 NA
#> GSM1182313 4 0.0632 0.8256 0.024 0.000 0.000 0.976 0.000 NA
#> GSM1182315 2 0.3710 0.8001 0.000 0.788 0.144 0.000 0.064 NA
#> GSM1182317 2 0.4462 0.6099 0.000 0.612 0.356 0.000 0.020 NA
#> GSM1182323 1 0.5229 0.4314 0.636 0.016 0.000 0.000 0.108 NA
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:mclust 139 7.73e-02 1.000 2
#> CV:mclust 134 1.92e-04 0.162 3
#> CV:mclust 114 1.24e-04 0.367 4
#> CV:mclust 93 2.72e-04 0.165 5
#> CV:mclust 110 8.31e-05 0.308 6
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 46361 rows and 139 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.852 0.937 0.923 0.1006 1.000 1.000
#> 4 4 0.583 0.639 0.811 0.1650 0.966 0.935
#> 5 5 0.533 0.609 0.763 0.1162 0.789 0.585
#> 6 6 0.499 0.531 0.693 0.0602 0.898 0.701
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.4605 0.934 0.796 0.000 NA
#> GSM1182187 1 0.3116 0.943 0.892 0.000 NA
#> GSM1182188 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182189 1 0.4555 0.936 0.800 0.000 NA
#> GSM1182190 1 0.3816 0.941 0.852 0.000 NA
#> GSM1182191 1 0.4555 0.935 0.800 0.000 NA
#> GSM1182192 1 0.3192 0.942 0.888 0.000 NA
#> GSM1182193 1 0.0424 0.938 0.992 0.000 NA
#> GSM1182194 2 0.2448 0.948 0.000 0.924 NA
#> GSM1182195 2 0.2448 0.948 0.000 0.924 NA
#> GSM1182196 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182197 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182198 2 0.2261 0.950 0.000 0.932 NA
#> GSM1182199 2 0.2261 0.950 0.000 0.932 NA
#> GSM1182200 2 0.4062 0.880 0.000 0.836 NA
#> GSM1182201 2 0.1411 0.956 0.000 0.964 NA
#> GSM1182202 1 0.4605 0.934 0.796 0.000 NA
#> GSM1182203 1 0.2537 0.943 0.920 0.000 NA
#> GSM1182204 1 0.2959 0.941 0.900 0.000 NA
#> GSM1182205 2 0.1753 0.954 0.000 0.952 NA
#> GSM1182206 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182207 1 0.4654 0.935 0.792 0.000 NA
#> GSM1182208 1 0.4654 0.933 0.792 0.000 NA
#> GSM1182209 2 0.6180 0.614 0.000 0.584 NA
#> GSM1182210 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182211 2 0.3816 0.885 0.000 0.852 NA
#> GSM1182212 2 0.5363 0.775 0.000 0.724 NA
#> GSM1182213 2 0.3412 0.900 0.000 0.876 NA
#> GSM1182214 2 0.2356 0.930 0.000 0.928 NA
#> GSM1182215 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182216 2 0.1860 0.955 0.000 0.948 NA
#> GSM1182217 1 0.4555 0.935 0.800 0.000 NA
#> GSM1182218 1 0.4121 0.940 0.832 0.000 NA
#> GSM1182219 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182220 2 0.0592 0.952 0.000 0.988 NA
#> GSM1182221 2 0.0592 0.956 0.000 0.988 NA
#> GSM1182222 2 0.1753 0.954 0.000 0.952 NA
#> GSM1182223 2 0.2448 0.949 0.000 0.924 NA
#> GSM1182224 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182225 2 0.1289 0.955 0.000 0.968 NA
#> GSM1182226 2 0.1529 0.955 0.000 0.960 NA
#> GSM1182227 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182228 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182229 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182230 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182231 2 0.1753 0.954 0.000 0.952 NA
#> GSM1182232 1 0.3941 0.941 0.844 0.000 NA
#> GSM1182233 1 0.4555 0.935 0.800 0.000 NA
#> GSM1182234 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182235 2 0.2261 0.932 0.000 0.932 NA
#> GSM1182236 1 0.4504 0.936 0.804 0.000 NA
#> GSM1182237 2 0.0592 0.956 0.000 0.988 NA
#> GSM1182238 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182239 2 0.2625 0.924 0.000 0.916 NA
#> GSM1182240 2 0.0592 0.952 0.000 0.988 NA
#> GSM1182241 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182242 2 0.1860 0.954 0.000 0.948 NA
#> GSM1182243 2 0.2356 0.950 0.000 0.928 NA
#> GSM1182244 2 0.0424 0.955 0.000 0.992 NA
#> GSM1182245 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182246 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182247 2 0.2537 0.947 0.000 0.920 NA
#> GSM1182248 2 0.2537 0.947 0.000 0.920 NA
#> GSM1182249 2 0.1860 0.953 0.000 0.948 NA
#> GSM1182250 2 0.2261 0.950 0.000 0.932 NA
#> GSM1182251 1 0.4504 0.936 0.804 0.000 NA
#> GSM1182252 2 0.2448 0.948 0.000 0.924 NA
#> GSM1182253 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182254 2 0.2537 0.947 0.000 0.920 NA
#> GSM1182255 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182256 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182257 1 0.0892 0.940 0.980 0.000 NA
#> GSM1182258 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182259 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182260 2 0.0747 0.956 0.000 0.984 NA
#> GSM1182261 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182262 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182263 1 0.4178 0.941 0.828 0.000 NA
#> GSM1182264 2 0.0592 0.955 0.000 0.988 NA
#> GSM1182265 2 0.2261 0.950 0.000 0.932 NA
#> GSM1182266 2 0.0892 0.956 0.000 0.980 NA
#> GSM1182267 1 0.0592 0.938 0.988 0.000 NA
#> GSM1182268 1 0.4555 0.935 0.800 0.000 NA
#> GSM1182269 1 0.3619 0.942 0.864 0.000 NA
#> GSM1182270 1 0.4702 0.934 0.788 0.000 NA
#> GSM1182271 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182272 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182273 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182275 2 0.1860 0.955 0.000 0.948 NA
#> GSM1182276 2 0.2625 0.926 0.000 0.916 NA
#> GSM1182277 1 0.0592 0.938 0.988 0.000 NA
#> GSM1182278 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182279 1 0.4504 0.938 0.804 0.000 NA
#> GSM1182280 1 0.4702 0.934 0.788 0.000 NA
#> GSM1182281 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182282 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182283 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182284 1 0.0000 0.937 1.000 0.000 NA
#> GSM1182285 2 0.2356 0.949 0.000 0.928 NA
#> GSM1182286 2 0.0592 0.952 0.000 0.988 NA
#> GSM1182287 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182288 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182289 1 0.4605 0.936 0.796 0.000 NA
#> GSM1182290 1 0.4654 0.933 0.792 0.000 NA
#> GSM1182291 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182274 2 0.2165 0.951 0.000 0.936 NA
#> GSM1182292 2 0.4235 0.863 0.000 0.824 NA
#> GSM1182293 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182294 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182295 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182296 2 0.0892 0.950 0.000 0.980 NA
#> GSM1182298 2 0.2066 0.952 0.000 0.940 NA
#> GSM1182299 2 0.3116 0.911 0.000 0.892 NA
#> GSM1182300 2 0.0424 0.953 0.000 0.992 NA
#> GSM1182301 2 0.1163 0.948 0.000 0.972 NA
#> GSM1182303 2 0.3116 0.912 0.000 0.892 NA
#> GSM1182304 1 0.4654 0.933 0.792 0.000 NA
#> GSM1182305 1 0.2711 0.943 0.912 0.000 NA
#> GSM1182306 1 0.2878 0.943 0.904 0.000 NA
#> GSM1182307 2 0.4555 0.844 0.000 0.800 NA
#> GSM1182309 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182312 2 0.0237 0.954 0.000 0.996 NA
#> GSM1182314 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182316 2 0.0237 0.955 0.000 0.996 NA
#> GSM1182318 2 0.4399 0.855 0.000 0.812 NA
#> GSM1182319 2 0.0424 0.954 0.000 0.992 NA
#> GSM1182320 2 0.0592 0.955 0.000 0.988 NA
#> GSM1182321 2 0.0747 0.956 0.000 0.984 NA
#> GSM1182322 2 0.0424 0.954 0.000 0.992 NA
#> GSM1182324 2 0.2165 0.951 0.000 0.936 NA
#> GSM1182297 2 0.3038 0.913 0.000 0.896 NA
#> GSM1182302 1 0.4452 0.937 0.808 0.000 NA
#> GSM1182308 2 0.2448 0.929 0.000 0.924 NA
#> GSM1182310 2 0.1163 0.956 0.000 0.972 NA
#> GSM1182311 1 0.4504 0.937 0.804 0.000 NA
#> GSM1182313 1 0.0237 0.937 0.996 0.000 NA
#> GSM1182315 2 0.0592 0.952 0.000 0.988 NA
#> GSM1182317 2 0.2711 0.922 0.000 0.912 NA
#> GSM1182323 1 0.4702 0.932 0.788 0.000 NA
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.5073 0.8696 0.744 0.000 0.056 NA
#> GSM1182187 1 0.2988 0.8947 0.876 0.000 0.012 NA
#> GSM1182188 1 0.1004 0.8813 0.972 0.000 0.004 NA
#> GSM1182189 1 0.4804 0.8821 0.776 0.000 0.064 NA
#> GSM1182190 1 0.3694 0.8949 0.844 0.000 0.032 NA
#> GSM1182191 1 0.5458 0.8638 0.720 0.000 0.076 NA
#> GSM1182192 1 0.3931 0.8949 0.832 0.000 0.040 NA
#> GSM1182193 1 0.6133 0.8180 0.676 0.000 0.188 NA
#> GSM1182194 2 0.5277 -0.7255 0.000 0.532 0.460 NA
#> GSM1182195 3 0.4989 0.8734 0.000 0.472 0.528 NA
#> GSM1182196 2 0.0336 0.6431 0.000 0.992 0.008 NA
#> GSM1182197 2 0.1474 0.6498 0.000 0.948 0.000 NA
#> GSM1182198 3 0.4907 0.8914 0.000 0.420 0.580 NA
#> GSM1182199 3 0.4972 0.9234 0.000 0.456 0.544 NA
#> GSM1182200 2 0.4998 0.5771 0.000 0.748 0.052 NA
#> GSM1182201 2 0.2670 0.6244 0.000 0.904 0.072 NA
#> GSM1182202 1 0.3402 0.8910 0.832 0.000 0.004 NA
#> GSM1182203 1 0.1118 0.8889 0.964 0.000 0.000 NA
#> GSM1182204 1 0.1209 0.8875 0.964 0.000 0.004 NA
#> GSM1182205 2 0.3764 0.4085 0.000 0.784 0.216 NA
#> GSM1182206 2 0.3052 0.5598 0.000 0.860 0.136 NA
#> GSM1182207 1 0.7601 0.6612 0.472 0.000 0.296 NA
#> GSM1182208 1 0.7900 0.5424 0.368 0.000 0.332 NA
#> GSM1182209 2 0.5097 0.2852 0.000 0.568 0.004 NA
#> GSM1182210 2 0.2469 0.6356 0.000 0.892 0.000 NA
#> GSM1182211 2 0.4746 0.3909 0.000 0.632 0.000 NA
#> GSM1182212 2 0.4872 0.4059 0.000 0.640 0.004 NA
#> GSM1182213 2 0.4522 0.4521 0.000 0.680 0.000 NA
#> GSM1182214 2 0.4679 0.4083 0.000 0.648 0.000 NA
#> GSM1182215 2 0.3583 0.4928 0.000 0.816 0.180 NA
#> GSM1182216 2 0.5159 0.6070 0.000 0.756 0.088 NA
#> GSM1182217 1 0.3257 0.8922 0.844 0.000 0.004 NA
#> GSM1182218 1 0.2125 0.8962 0.920 0.000 0.004 NA
#> GSM1182219 2 0.2530 0.6333 0.000 0.888 0.000 NA
#> GSM1182220 2 0.3870 0.5803 0.000 0.788 0.004 NA
#> GSM1182221 2 0.2313 0.6502 0.000 0.924 0.032 NA
#> GSM1182222 2 0.2610 0.6122 0.000 0.900 0.088 NA
#> GSM1182223 2 0.3161 0.5705 0.000 0.864 0.124 NA
#> GSM1182224 2 0.4746 -0.3224 0.000 0.632 0.368 NA
#> GSM1182225 2 0.3474 0.6409 0.000 0.868 0.068 NA
#> GSM1182226 2 0.2345 0.6029 0.000 0.900 0.100 NA
#> GSM1182227 1 0.0921 0.8831 0.972 0.000 0.000 NA
#> GSM1182228 2 0.0188 0.6434 0.000 0.996 0.004 NA
#> GSM1182229 2 0.3448 0.5132 0.000 0.828 0.168 NA
#> GSM1182230 2 0.3444 0.4972 0.000 0.816 0.184 NA
#> GSM1182231 2 0.2345 0.6001 0.000 0.900 0.100 NA
#> GSM1182232 1 0.4462 0.8848 0.792 0.000 0.044 NA
#> GSM1182233 1 0.5218 0.8662 0.736 0.000 0.064 NA
#> GSM1182234 1 0.2751 0.8965 0.904 0.000 0.040 NA
#> GSM1182235 2 0.3873 0.5574 0.000 0.772 0.000 NA
#> GSM1182236 1 0.3946 0.8884 0.812 0.000 0.020 NA
#> GSM1182237 2 0.1211 0.6324 0.000 0.960 0.040 NA
#> GSM1182238 2 0.2868 0.6231 0.000 0.864 0.000 NA
#> GSM1182239 2 0.3311 0.6020 0.000 0.828 0.000 NA
#> GSM1182240 2 0.3400 0.5965 0.000 0.820 0.000 NA
#> GSM1182241 2 0.0188 0.6452 0.000 0.996 0.000 NA
#> GSM1182242 2 0.2760 0.5716 0.000 0.872 0.128 NA
#> GSM1182243 2 0.3402 0.5221 0.000 0.832 0.164 NA
#> GSM1182244 2 0.2647 0.5577 0.000 0.880 0.120 NA
#> GSM1182245 1 0.3301 0.8950 0.876 0.000 0.048 NA
#> GSM1182246 1 0.1356 0.8794 0.960 0.000 0.008 NA
#> GSM1182247 2 0.4137 0.4344 0.000 0.780 0.208 NA
#> GSM1182248 2 0.4250 0.2301 0.000 0.724 0.276 NA
#> GSM1182249 2 0.2868 0.5700 0.000 0.864 0.136 NA
#> GSM1182250 2 0.3444 0.4884 0.000 0.816 0.184 NA
#> GSM1182251 1 0.5212 0.8687 0.740 0.000 0.068 NA
#> GSM1182252 2 0.3907 0.3763 0.000 0.768 0.232 NA
#> GSM1182253 2 0.4564 -0.0915 0.000 0.672 0.328 NA
#> GSM1182254 2 0.4248 0.3964 0.000 0.768 0.220 NA
#> GSM1182255 1 0.1305 0.8778 0.960 0.000 0.004 NA
#> GSM1182256 1 0.1305 0.8778 0.960 0.000 0.004 NA
#> GSM1182257 1 0.0817 0.8888 0.976 0.000 0.000 NA
#> GSM1182258 1 0.0895 0.8854 0.976 0.000 0.004 NA
#> GSM1182259 1 0.1118 0.8788 0.964 0.000 0.000 NA
#> GSM1182260 2 0.2530 0.5655 0.000 0.888 0.112 NA
#> GSM1182261 2 0.3052 0.5599 0.000 0.860 0.136 NA
#> GSM1182262 2 0.3306 0.5321 0.000 0.840 0.156 NA
#> GSM1182263 1 0.4756 0.8836 0.784 0.000 0.072 NA
#> GSM1182264 2 0.4277 -0.1405 0.000 0.720 0.280 NA
#> GSM1182265 2 0.4406 0.0683 0.000 0.700 0.300 NA
#> GSM1182266 2 0.3074 0.4780 0.000 0.848 0.152 NA
#> GSM1182267 1 0.3885 0.8919 0.844 0.000 0.064 NA
#> GSM1182268 1 0.5212 0.8683 0.740 0.000 0.068 NA
#> GSM1182269 1 0.4937 0.8806 0.764 0.000 0.064 NA
#> GSM1182270 1 0.4524 0.8830 0.768 0.000 0.028 NA
#> GSM1182271 1 0.0921 0.8830 0.972 0.000 0.000 NA
#> GSM1182272 1 0.1118 0.8788 0.964 0.000 0.000 NA
#> GSM1182273 2 0.5158 -0.7756 0.000 0.524 0.472 NA
#> GSM1182275 2 0.3495 0.5565 0.000 0.844 0.140 NA
#> GSM1182276 2 0.4452 0.5277 0.000 0.732 0.008 NA
#> GSM1182277 1 0.1489 0.8929 0.952 0.000 0.004 NA
#> GSM1182278 1 0.1545 0.8887 0.952 0.000 0.008 NA
#> GSM1182279 1 0.5530 0.8599 0.712 0.000 0.076 NA
#> GSM1182280 1 0.6404 0.8180 0.644 0.000 0.136 NA
#> GSM1182281 1 0.1452 0.8807 0.956 0.000 0.008 NA
#> GSM1182282 1 0.3301 0.8930 0.876 0.000 0.048 NA
#> GSM1182283 1 0.3198 0.8972 0.880 0.000 0.040 NA
#> GSM1182284 1 0.0817 0.8826 0.976 0.000 0.000 NA
#> GSM1182285 2 0.4624 -0.1347 0.000 0.660 0.340 NA
#> GSM1182286 2 0.2973 0.6187 0.000 0.856 0.000 NA
#> GSM1182287 2 0.2988 0.5870 0.000 0.876 0.112 NA
#> GSM1182288 2 0.3688 0.4320 0.000 0.792 0.208 NA
#> GSM1182289 1 0.5434 0.8668 0.728 0.000 0.084 NA
#> GSM1182290 1 0.7563 0.6756 0.484 0.000 0.280 NA
#> GSM1182291 1 0.1109 0.8801 0.968 0.000 0.004 NA
#> GSM1182274 2 0.4122 0.3502 0.000 0.760 0.236 NA
#> GSM1182292 2 0.4643 0.4224 0.000 0.656 0.000 NA
#> GSM1182293 2 0.2053 0.6434 0.000 0.924 0.004 NA
#> GSM1182294 2 0.0188 0.6440 0.000 0.996 0.004 NA
#> GSM1182295 2 0.2760 0.6271 0.000 0.872 0.000 NA
#> GSM1182296 2 0.3123 0.6123 0.000 0.844 0.000 NA
#> GSM1182298 3 0.4985 0.9071 0.000 0.468 0.532 NA
#> GSM1182299 2 0.2868 0.6271 0.000 0.864 0.000 NA
#> GSM1182300 2 0.2011 0.6429 0.000 0.920 0.000 NA
#> GSM1182301 2 0.3837 0.5616 0.000 0.776 0.000 NA
#> GSM1182303 2 0.4283 0.5395 0.000 0.740 0.004 NA
#> GSM1182304 1 0.6027 0.8328 0.664 0.000 0.092 NA
#> GSM1182305 1 0.4586 0.8877 0.796 0.000 0.068 NA
#> GSM1182306 1 0.2334 0.8947 0.908 0.000 0.004 NA
#> GSM1182307 2 0.4991 0.3502 0.000 0.608 0.004 NA
#> GSM1182309 2 0.1398 0.6474 0.000 0.956 0.004 NA
#> GSM1182312 2 0.1004 0.6484 0.000 0.972 0.004 NA
#> GSM1182314 1 0.1356 0.8794 0.960 0.000 0.008 NA
#> GSM1182316 2 0.1938 0.6325 0.000 0.936 0.052 NA
#> GSM1182318 2 0.4814 0.4524 0.000 0.676 0.008 NA
#> GSM1182319 2 0.1557 0.6279 0.000 0.944 0.056 NA
#> GSM1182320 2 0.2329 0.6227 0.000 0.916 0.072 NA
#> GSM1182321 2 0.2011 0.6076 0.000 0.920 0.080 NA
#> GSM1182322 2 0.2149 0.6102 0.000 0.912 0.088 NA
#> GSM1182324 2 0.3751 0.4718 0.000 0.800 0.196 NA
#> GSM1182297 2 0.4134 0.5251 0.000 0.740 0.000 NA
#> GSM1182302 1 0.1557 0.8931 0.944 0.000 0.000 NA
#> GSM1182308 2 0.4485 0.5458 0.000 0.740 0.012 NA
#> GSM1182310 2 0.2868 0.5786 0.000 0.864 0.136 NA
#> GSM1182311 1 0.5267 0.8723 0.740 0.000 0.076 NA
#> GSM1182313 1 0.1452 0.8782 0.956 0.000 0.008 NA
#> GSM1182315 2 0.2831 0.6296 0.000 0.876 0.004 NA
#> GSM1182317 2 0.3873 0.5587 0.000 0.772 0.000 NA
#> GSM1182323 1 0.4204 0.8834 0.788 0.000 0.020 NA
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.4585 0.5877 0.628 0.000 0.000 0.020 0.352
#> GSM1182187 1 0.4021 0.6941 0.764 0.000 0.000 0.036 0.200
#> GSM1182188 1 0.2017 0.7017 0.912 0.000 0.000 0.008 0.080
#> GSM1182189 1 0.4736 0.5006 0.576 0.000 0.000 0.020 0.404
#> GSM1182190 1 0.3878 0.6958 0.748 0.000 0.000 0.016 0.236
#> GSM1182191 1 0.4744 0.5085 0.572 0.000 0.000 0.020 0.408
#> GSM1182192 1 0.3562 0.7137 0.788 0.000 0.000 0.016 0.196
#> GSM1182193 1 0.4812 0.6455 0.672 0.000 0.008 0.032 0.288
#> GSM1182194 3 0.2012 0.6883 0.000 0.020 0.920 0.060 0.000
#> GSM1182195 3 0.1408 0.6717 0.000 0.008 0.948 0.044 0.000
#> GSM1182196 3 0.4298 0.4442 0.000 0.352 0.640 0.008 0.000
#> GSM1182197 3 0.4914 0.5805 0.000 0.280 0.672 0.040 0.008
#> GSM1182198 3 0.2612 0.5802 0.000 0.008 0.868 0.124 0.000
#> GSM1182199 3 0.2574 0.6104 0.000 0.012 0.876 0.112 0.000
#> GSM1182200 3 0.5817 0.4975 0.000 0.292 0.608 0.084 0.016
#> GSM1182201 3 0.5161 0.6968 0.000 0.176 0.716 0.092 0.016
#> GSM1182202 1 0.3849 0.6808 0.752 0.000 0.000 0.016 0.232
#> GSM1182203 1 0.2953 0.7006 0.844 0.000 0.000 0.012 0.144
#> GSM1182204 1 0.3203 0.7002 0.820 0.000 0.000 0.012 0.168
#> GSM1182205 3 0.1557 0.7567 0.000 0.052 0.940 0.008 0.000
#> GSM1182206 3 0.2660 0.7613 0.000 0.128 0.864 0.008 0.000
#> GSM1182207 5 0.4223 0.8003 0.248 0.000 0.000 0.028 0.724
#> GSM1182208 5 0.3601 0.7540 0.128 0.000 0.000 0.052 0.820
#> GSM1182209 2 0.1121 0.4689 0.000 0.956 0.044 0.000 0.000
#> GSM1182210 2 0.4101 0.5689 0.000 0.628 0.372 0.000 0.000
#> GSM1182211 2 0.1430 0.4837 0.000 0.944 0.052 0.004 0.000
#> GSM1182212 2 0.5059 0.3610 0.000 0.548 0.416 0.036 0.000
#> GSM1182213 2 0.3949 0.5836 0.000 0.668 0.332 0.000 0.000
#> GSM1182214 2 0.1410 0.4945 0.000 0.940 0.060 0.000 0.000
#> GSM1182215 3 0.1697 0.7646 0.000 0.060 0.932 0.008 0.000
#> GSM1182216 2 0.4084 0.4789 0.000 0.668 0.328 0.004 0.000
#> GSM1182217 1 0.3942 0.6932 0.748 0.000 0.000 0.020 0.232
#> GSM1182218 1 0.3696 0.7056 0.772 0.000 0.000 0.016 0.212
#> GSM1182219 3 0.4273 0.0871 0.000 0.448 0.552 0.000 0.000
#> GSM1182220 3 0.5083 -0.1555 0.000 0.480 0.492 0.020 0.008
#> GSM1182221 2 0.4040 0.5507 0.000 0.724 0.260 0.016 0.000
#> GSM1182222 3 0.3430 0.6726 0.000 0.220 0.776 0.004 0.000
#> GSM1182223 3 0.4031 0.7529 0.000 0.124 0.804 0.064 0.008
#> GSM1182224 3 0.0404 0.7197 0.000 0.000 0.988 0.012 0.000
#> GSM1182225 3 0.4182 0.3986 0.000 0.352 0.644 0.004 0.000
#> GSM1182226 3 0.4658 0.1689 0.000 0.408 0.576 0.016 0.000
#> GSM1182227 1 0.3366 0.6939 0.828 0.000 0.000 0.032 0.140
#> GSM1182228 3 0.3890 0.6637 0.000 0.252 0.736 0.012 0.000
#> GSM1182229 3 0.2193 0.7709 0.000 0.092 0.900 0.008 0.000
#> GSM1182230 3 0.1704 0.7663 0.000 0.068 0.928 0.004 0.000
#> GSM1182231 3 0.2852 0.7380 0.000 0.172 0.828 0.000 0.000
#> GSM1182232 1 0.4165 0.6492 0.672 0.000 0.000 0.008 0.320
#> GSM1182233 1 0.4565 0.5261 0.580 0.000 0.000 0.012 0.408
#> GSM1182234 1 0.3877 0.6856 0.764 0.000 0.000 0.024 0.212
#> GSM1182235 2 0.3274 0.6374 0.000 0.780 0.220 0.000 0.000
#> GSM1182236 1 0.4127 0.6650 0.680 0.000 0.000 0.008 0.312
#> GSM1182237 3 0.4026 0.6632 0.000 0.244 0.736 0.020 0.000
#> GSM1182238 2 0.3143 0.6131 0.000 0.796 0.204 0.000 0.000
#> GSM1182239 2 0.4262 0.3649 0.000 0.560 0.440 0.000 0.000
#> GSM1182240 2 0.4410 0.3966 0.000 0.556 0.440 0.004 0.000
#> GSM1182241 3 0.4086 0.6147 0.000 0.284 0.704 0.012 0.000
#> GSM1182242 3 0.2712 0.7717 0.000 0.088 0.880 0.032 0.000
#> GSM1182243 3 0.2389 0.7649 0.000 0.116 0.880 0.004 0.000
#> GSM1182244 3 0.3536 0.7409 0.000 0.156 0.812 0.032 0.000
#> GSM1182245 1 0.3656 0.7043 0.784 0.000 0.000 0.020 0.196
#> GSM1182246 1 0.1800 0.6783 0.932 0.000 0.000 0.020 0.048
#> GSM1182247 3 0.3635 0.7144 0.000 0.068 0.836 0.088 0.008
#> GSM1182248 3 0.1469 0.7109 0.000 0.016 0.948 0.036 0.000
#> GSM1182249 3 0.3053 0.7419 0.000 0.164 0.828 0.008 0.000
#> GSM1182250 3 0.2017 0.7705 0.000 0.080 0.912 0.008 0.000
#> GSM1182251 1 0.4674 0.4973 0.568 0.000 0.000 0.016 0.416
#> GSM1182252 3 0.1750 0.7463 0.000 0.036 0.936 0.028 0.000
#> GSM1182253 3 0.0992 0.7308 0.000 0.008 0.968 0.024 0.000
#> GSM1182254 3 0.2359 0.7495 0.000 0.060 0.904 0.036 0.000
#> GSM1182255 1 0.1331 0.6803 0.952 0.000 0.000 0.008 0.040
#> GSM1182256 1 0.0865 0.6759 0.972 0.000 0.000 0.004 0.024
#> GSM1182257 1 0.1626 0.6900 0.940 0.000 0.000 0.016 0.044
#> GSM1182258 1 0.1430 0.6956 0.944 0.000 0.000 0.004 0.052
#> GSM1182259 1 0.1670 0.6619 0.936 0.000 0.000 0.012 0.052
#> GSM1182260 3 0.3355 0.7561 0.000 0.132 0.832 0.036 0.000
#> GSM1182261 3 0.2462 0.7656 0.000 0.112 0.880 0.008 0.000
#> GSM1182262 3 0.1831 0.7682 0.000 0.076 0.920 0.004 0.000
#> GSM1182263 1 0.4585 0.5500 0.628 0.000 0.000 0.020 0.352
#> GSM1182264 3 0.3432 0.7228 0.000 0.132 0.828 0.040 0.000
#> GSM1182265 3 0.2903 0.7602 0.000 0.080 0.872 0.048 0.000
#> GSM1182266 3 0.3307 0.7388 0.000 0.104 0.844 0.052 0.000
#> GSM1182267 1 0.3878 0.6755 0.748 0.000 0.000 0.016 0.236
#> GSM1182268 1 0.4505 0.5598 0.604 0.000 0.000 0.012 0.384
#> GSM1182269 1 0.4849 0.5885 0.608 0.000 0.000 0.032 0.360
#> GSM1182270 1 0.4585 0.6091 0.628 0.000 0.000 0.020 0.352
#> GSM1182271 1 0.1331 0.6833 0.952 0.000 0.000 0.008 0.040
#> GSM1182272 1 0.1670 0.6622 0.936 0.000 0.000 0.012 0.052
#> GSM1182273 3 0.0703 0.7063 0.000 0.000 0.976 0.024 0.000
#> GSM1182275 3 0.3916 0.7574 0.000 0.116 0.816 0.056 0.012
#> GSM1182276 2 0.5232 0.1706 0.000 0.492 0.472 0.028 0.008
#> GSM1182277 1 0.2886 0.7018 0.844 0.000 0.000 0.008 0.148
#> GSM1182278 1 0.2522 0.6986 0.880 0.000 0.000 0.012 0.108
#> GSM1182279 1 0.4821 0.4007 0.516 0.000 0.000 0.020 0.464
#> GSM1182280 1 0.4747 0.3137 0.500 0.000 0.000 0.016 0.484
#> GSM1182281 1 0.2325 0.6884 0.904 0.000 0.000 0.028 0.068
#> GSM1182282 1 0.3343 0.7041 0.812 0.000 0.000 0.016 0.172
#> GSM1182283 1 0.3724 0.7179 0.788 0.000 0.000 0.028 0.184
#> GSM1182284 1 0.2628 0.6869 0.884 0.000 0.000 0.028 0.088
#> GSM1182285 3 0.1310 0.7166 0.000 0.020 0.956 0.024 0.000
#> GSM1182286 2 0.3895 0.6160 0.000 0.680 0.320 0.000 0.000
#> GSM1182287 3 0.3134 0.7654 0.000 0.120 0.848 0.032 0.000
#> GSM1182288 3 0.1522 0.7546 0.000 0.044 0.944 0.012 0.000
#> GSM1182289 1 0.4696 0.4529 0.556 0.000 0.000 0.016 0.428
#> GSM1182290 5 0.4302 0.8303 0.248 0.000 0.000 0.032 0.720
#> GSM1182291 1 0.1670 0.6846 0.936 0.000 0.000 0.012 0.052
#> GSM1182274 3 0.2299 0.7505 0.000 0.052 0.912 0.032 0.004
#> GSM1182292 2 0.3395 0.6282 0.000 0.764 0.236 0.000 0.000
#> GSM1182293 2 0.3671 0.6275 0.000 0.756 0.236 0.008 0.000
#> GSM1182294 2 0.4906 0.2476 0.000 0.496 0.480 0.024 0.000
#> GSM1182295 2 0.3612 0.6397 0.000 0.732 0.268 0.000 0.000
#> GSM1182296 2 0.3837 0.6148 0.000 0.692 0.308 0.000 0.000
#> GSM1182298 3 0.3513 0.4996 0.000 0.020 0.800 0.180 0.000
#> GSM1182299 3 0.5120 0.1044 0.000 0.428 0.540 0.008 0.024
#> GSM1182300 3 0.4306 -0.1526 0.000 0.492 0.508 0.000 0.000
#> GSM1182301 2 0.3895 0.6026 0.000 0.680 0.320 0.000 0.000
#> GSM1182303 3 0.4815 0.0341 0.000 0.456 0.524 0.020 0.000
#> GSM1182304 1 0.4656 0.3352 0.508 0.000 0.000 0.012 0.480
#> GSM1182305 1 0.4465 0.6380 0.672 0.000 0.000 0.024 0.304
#> GSM1182306 1 0.2873 0.7115 0.856 0.000 0.000 0.016 0.128
#> GSM1182307 2 0.1197 0.4769 0.000 0.952 0.048 0.000 0.000
#> GSM1182309 2 0.3688 0.5566 0.000 0.808 0.160 0.024 0.008
#> GSM1182312 2 0.3391 0.5455 0.000 0.800 0.188 0.012 0.000
#> GSM1182314 1 0.1597 0.6917 0.940 0.000 0.000 0.012 0.048
#> GSM1182316 2 0.5263 0.4540 0.000 0.616 0.324 0.056 0.004
#> GSM1182318 2 0.2302 0.5191 0.000 0.904 0.080 0.008 0.008
#> GSM1182319 4 0.6496 0.7536 0.000 0.280 0.232 0.488 0.000
#> GSM1182320 2 0.5030 0.3634 0.000 0.688 0.236 0.072 0.004
#> GSM1182321 3 0.4909 0.6742 0.000 0.164 0.716 0.120 0.000
#> GSM1182322 4 0.6088 0.7874 0.000 0.296 0.156 0.548 0.000
#> GSM1182324 3 0.2932 0.7651 0.000 0.104 0.864 0.032 0.000
#> GSM1182297 2 0.2127 0.5633 0.000 0.892 0.108 0.000 0.000
#> GSM1182302 1 0.2997 0.6997 0.840 0.000 0.000 0.012 0.148
#> GSM1182308 2 0.4309 0.6193 0.000 0.676 0.308 0.016 0.000
#> GSM1182310 4 0.6049 0.7864 0.000 0.192 0.232 0.576 0.000
#> GSM1182311 1 0.4508 0.6120 0.648 0.000 0.000 0.020 0.332
#> GSM1182313 1 0.1485 0.6722 0.948 0.000 0.000 0.020 0.032
#> GSM1182315 2 0.2624 0.5244 0.000 0.872 0.116 0.012 0.000
#> GSM1182317 2 0.1942 0.4944 0.000 0.920 0.068 0.012 0.000
#> GSM1182323 1 0.4213 0.6526 0.680 0.000 0.000 0.012 0.308
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 1 0.192 0.58001 0.904 0.000 0.000 0.088 0.000 NA
#> GSM1182187 1 0.374 0.21960 0.672 0.000 0.000 0.320 0.000 NA
#> GSM1182188 4 0.386 0.54774 0.468 0.000 0.000 0.532 0.000 NA
#> GSM1182189 1 0.275 0.59233 0.864 0.000 0.000 0.068 0.000 NA
#> GSM1182190 1 0.368 0.52886 0.772 0.000 0.000 0.176 0.000 NA
#> GSM1182191 1 0.137 0.59365 0.944 0.000 0.000 0.044 0.000 NA
#> GSM1182192 1 0.326 0.48816 0.780 0.000 0.000 0.204 0.000 NA
#> GSM1182193 1 0.321 0.55003 0.832 0.000 0.000 0.120 0.008 NA
#> GSM1182194 3 0.314 0.69902 0.000 0.000 0.852 0.024 0.084 NA
#> GSM1182195 3 0.218 0.68999 0.000 0.004 0.904 0.016 0.072 NA
#> GSM1182196 3 0.498 -0.03242 0.000 0.444 0.496 0.000 0.056 NA
#> GSM1182197 3 0.596 0.49496 0.000 0.288 0.580 0.016 0.044 NA
#> GSM1182198 3 0.405 0.59471 0.000 0.008 0.776 0.036 0.160 NA
#> GSM1182199 3 0.344 0.64373 0.000 0.012 0.808 0.020 0.156 NA
#> GSM1182200 3 0.655 0.52188 0.000 0.216 0.584 0.036 0.072 NA
#> GSM1182201 3 0.592 0.66104 0.000 0.136 0.668 0.036 0.064 NA
#> GSM1182202 1 0.374 0.10110 0.648 0.000 0.000 0.348 0.000 NA
#> GSM1182203 1 0.389 -0.11341 0.596 0.000 0.000 0.400 0.000 NA
#> GSM1182204 1 0.401 -0.14745 0.584 0.000 0.000 0.408 0.000 NA
#> GSM1182205 3 0.239 0.74721 0.000 0.052 0.896 0.008 0.044 NA
#> GSM1182206 3 0.313 0.70813 0.000 0.168 0.808 0.000 0.024 NA
#> GSM1182207 1 0.343 0.42263 0.720 0.000 0.000 0.004 0.000 NA
#> GSM1182208 1 0.413 0.28244 0.504 0.000 0.000 0.004 0.004 NA
#> GSM1182209 2 0.211 0.36114 0.000 0.916 0.008 0.052 0.016 NA
#> GSM1182210 2 0.403 0.66124 0.000 0.712 0.256 0.020 0.012 NA
#> GSM1182211 2 0.283 0.48989 0.000 0.880 0.056 0.028 0.032 NA
#> GSM1182212 2 0.582 0.26452 0.000 0.476 0.428 0.032 0.044 NA
#> GSM1182213 2 0.395 0.64203 0.000 0.684 0.296 0.004 0.016 NA
#> GSM1182214 2 0.200 0.57217 0.000 0.908 0.076 0.004 0.012 NA
#> GSM1182215 3 0.343 0.73293 0.000 0.112 0.820 0.008 0.060 NA
#> GSM1182216 2 0.452 0.50710 0.000 0.592 0.376 0.012 0.020 NA
#> GSM1182217 1 0.387 -0.08253 0.604 0.000 0.000 0.392 0.000 NA
#> GSM1182218 1 0.395 0.46097 0.744 0.000 0.000 0.196 0.000 NA
#> GSM1182219 2 0.437 0.31862 0.000 0.540 0.440 0.000 0.016 NA
#> GSM1182220 2 0.490 0.34221 0.000 0.520 0.436 0.004 0.028 NA
#> GSM1182221 2 0.363 0.61363 0.000 0.752 0.224 0.004 0.020 NA
#> GSM1182222 3 0.390 0.39862 0.000 0.336 0.652 0.000 0.012 NA
#> GSM1182223 3 0.337 0.74076 0.000 0.112 0.832 0.008 0.040 NA
#> GSM1182224 3 0.200 0.71197 0.000 0.012 0.912 0.008 0.068 NA
#> GSM1182225 3 0.430 -0.08646 0.000 0.456 0.528 0.004 0.012 NA
#> GSM1182226 2 0.508 0.18395 0.000 0.476 0.460 0.008 0.056 NA
#> GSM1182227 1 0.526 0.29072 0.620 0.000 0.000 0.276 0.024 NA
#> GSM1182228 3 0.398 0.66344 0.000 0.228 0.736 0.008 0.024 NA
#> GSM1182229 3 0.218 0.73481 0.000 0.132 0.868 0.000 0.000 NA
#> GSM1182230 3 0.296 0.74018 0.000 0.120 0.840 0.000 0.040 NA
#> GSM1182231 3 0.351 0.64121 0.000 0.240 0.744 0.000 0.016 NA
#> GSM1182232 1 0.241 0.59568 0.880 0.000 0.000 0.092 0.000 NA
#> GSM1182233 1 0.126 0.59840 0.952 0.000 0.000 0.020 0.000 NA
#> GSM1182234 1 0.495 0.22412 0.616 0.000 0.000 0.284 0.000 NA
#> GSM1182235 2 0.363 0.66698 0.000 0.756 0.212 0.000 0.032 NA
#> GSM1182236 1 0.246 0.59270 0.880 0.000 0.000 0.084 0.000 NA
#> GSM1182237 3 0.525 0.55209 0.000 0.272 0.608 0.008 0.112 NA
#> GSM1182238 2 0.365 0.65798 0.000 0.756 0.216 0.004 0.024 NA
#> GSM1182239 2 0.468 0.51801 0.000 0.600 0.356 0.004 0.036 NA
#> GSM1182240 2 0.485 0.60445 0.000 0.624 0.320 0.020 0.032 NA
#> GSM1182241 3 0.428 0.50862 0.000 0.320 0.644 0.000 0.036 NA
#> GSM1182242 3 0.352 0.74696 0.000 0.072 0.844 0.032 0.032 NA
#> GSM1182243 3 0.186 0.74174 0.000 0.104 0.896 0.000 0.000 NA
#> GSM1182244 3 0.445 0.69904 0.000 0.152 0.724 0.004 0.120 NA
#> GSM1182245 4 0.475 0.58352 0.452 0.000 0.000 0.500 0.000 NA
#> GSM1182246 4 0.343 0.83020 0.304 0.000 0.000 0.696 0.000 NA
#> GSM1182247 3 0.398 0.73405 0.000 0.048 0.812 0.012 0.084 NA
#> GSM1182248 3 0.118 0.74174 0.000 0.024 0.960 0.004 0.004 NA
#> GSM1182249 3 0.408 0.62812 0.000 0.252 0.704 0.000 0.044 NA
#> GSM1182250 3 0.274 0.74630 0.000 0.120 0.852 0.000 0.028 NA
#> GSM1182251 1 0.203 0.60181 0.908 0.000 0.000 0.064 0.000 NA
#> GSM1182252 3 0.235 0.75395 0.000 0.064 0.900 0.004 0.024 NA
#> GSM1182253 3 0.248 0.73736 0.000 0.028 0.896 0.028 0.048 NA
#> GSM1182254 3 0.204 0.74907 0.000 0.068 0.912 0.008 0.004 NA
#> GSM1182255 4 0.355 0.83459 0.332 0.000 0.000 0.668 0.000 NA
#> GSM1182256 4 0.346 0.83637 0.312 0.000 0.000 0.688 0.000 NA
#> GSM1182257 4 0.441 0.81359 0.336 0.000 0.000 0.624 0.000 NA
#> GSM1182258 4 0.353 0.83577 0.328 0.000 0.000 0.672 0.000 NA
#> GSM1182259 4 0.407 0.82807 0.300 0.000 0.000 0.672 0.000 NA
#> GSM1182260 3 0.551 0.68921 0.000 0.156 0.680 0.008 0.088 NA
#> GSM1182261 3 0.306 0.73290 0.000 0.144 0.824 0.000 0.032 NA
#> GSM1182262 3 0.289 0.74585 0.000 0.108 0.852 0.004 0.036 NA
#> GSM1182263 1 0.397 0.51929 0.760 0.000 0.000 0.148 0.000 NA
#> GSM1182264 3 0.572 0.67035 0.000 0.128 0.676 0.016 0.104 NA
#> GSM1182265 3 0.591 0.65028 0.000 0.136 0.632 0.024 0.180 NA
#> GSM1182266 3 0.588 0.64269 0.000 0.108 0.672 0.028 0.076 NA
#> GSM1182267 1 0.502 -0.27203 0.532 0.000 0.000 0.392 0.000 NA
#> GSM1182268 1 0.286 0.58312 0.856 0.000 0.000 0.072 0.000 NA
#> GSM1182269 1 0.380 0.46975 0.748 0.000 0.000 0.208 0.000 NA
#> GSM1182270 1 0.238 0.59344 0.884 0.000 0.000 0.084 0.000 NA
#> GSM1182271 4 0.364 0.83794 0.320 0.000 0.000 0.676 0.000 NA
#> GSM1182272 4 0.390 0.82875 0.296 0.000 0.000 0.684 0.000 NA
#> GSM1182273 3 0.323 0.68976 0.000 0.028 0.860 0.028 0.016 NA
#> GSM1182275 3 0.460 0.72467 0.000 0.112 0.768 0.028 0.064 NA
#> GSM1182276 2 0.575 0.35250 0.000 0.488 0.420 0.028 0.044 NA
#> GSM1182277 1 0.473 -0.35935 0.520 0.000 0.000 0.432 0.000 NA
#> GSM1182278 1 0.460 -0.23018 0.544 0.000 0.000 0.416 0.000 NA
#> GSM1182279 1 0.236 0.57753 0.884 0.000 0.000 0.028 0.000 NA
#> GSM1182280 1 0.235 0.55396 0.880 0.000 0.000 0.020 0.000 NA
#> GSM1182281 4 0.388 0.82472 0.332 0.000 0.000 0.656 0.000 NA
#> GSM1182282 4 0.475 0.58559 0.444 0.000 0.000 0.508 0.000 NA
#> GSM1182283 1 0.483 0.10102 0.608 0.000 0.004 0.324 0.000 NA
#> GSM1182284 4 0.540 0.55330 0.412 0.000 0.000 0.492 0.008 NA
#> GSM1182285 3 0.194 0.72962 0.000 0.012 0.928 0.016 0.036 NA
#> GSM1182286 2 0.373 0.65639 0.000 0.716 0.264 0.000 0.020 NA
#> GSM1182287 3 0.273 0.74068 0.000 0.124 0.856 0.012 0.004 NA
#> GSM1182288 3 0.199 0.74643 0.000 0.040 0.924 0.008 0.020 NA
#> GSM1182289 1 0.404 0.46549 0.744 0.000 0.000 0.180 0.000 NA
#> GSM1182290 1 0.441 0.31384 0.560 0.000 0.000 0.020 0.004 NA
#> GSM1182291 4 0.346 0.83595 0.312 0.000 0.000 0.688 0.000 NA
#> GSM1182274 3 0.506 0.63727 0.000 0.080 0.724 0.048 0.012 NA
#> GSM1182292 2 0.353 0.58943 0.000 0.820 0.124 0.032 0.020 NA
#> GSM1182293 2 0.308 0.60974 0.000 0.844 0.112 0.004 0.036 NA
#> GSM1182294 2 0.473 0.61365 0.000 0.636 0.284 0.000 0.080 NA
#> GSM1182295 2 0.307 0.66985 0.000 0.788 0.204 0.000 0.008 NA
#> GSM1182296 2 0.402 0.65900 0.000 0.748 0.204 0.028 0.020 NA
#> GSM1182298 3 0.421 0.57260 0.000 0.016 0.740 0.028 0.208 NA
#> GSM1182299 3 0.584 -0.00833 0.000 0.432 0.452 0.004 0.024 NA
#> GSM1182300 2 0.412 0.54016 0.000 0.628 0.352 0.000 0.020 NA
#> GSM1182301 2 0.439 0.60200 0.000 0.760 0.160 0.040 0.024 NA
#> GSM1182303 3 0.538 -0.08585 0.000 0.436 0.496 0.020 0.032 NA
#> GSM1182304 1 0.201 0.56785 0.904 0.000 0.000 0.016 0.000 NA
#> GSM1182305 1 0.291 0.57452 0.848 0.000 0.000 0.104 0.000 NA
#> GSM1182306 1 0.370 0.02271 0.624 0.000 0.000 0.376 0.000 NA
#> GSM1182307 2 0.178 0.45683 0.000 0.936 0.020 0.020 0.020 NA
#> GSM1182309 2 0.347 0.55704 0.000 0.816 0.088 0.000 0.092 NA
#> GSM1182312 2 0.335 0.59736 0.000 0.828 0.112 0.004 0.052 NA
#> GSM1182314 4 0.367 0.76844 0.368 0.000 0.000 0.632 0.000 NA
#> GSM1182316 2 0.401 0.54032 0.000 0.768 0.124 0.004 0.104 NA
#> GSM1182318 2 0.271 0.55518 0.000 0.884 0.068 0.008 0.024 NA
#> GSM1182319 5 0.534 0.54169 0.000 0.360 0.116 0.000 0.524 NA
#> GSM1182320 2 0.434 0.41397 0.000 0.764 0.108 0.012 0.108 NA
#> GSM1182321 3 0.666 0.26598 0.000 0.224 0.456 0.048 0.272 NA
#> GSM1182322 5 0.407 0.73343 0.000 0.344 0.008 0.008 0.640 NA
#> GSM1182324 3 0.494 0.64744 0.000 0.172 0.688 0.016 0.124 NA
#> GSM1182297 2 0.278 0.63168 0.000 0.848 0.124 0.000 0.028 NA
#> GSM1182302 1 0.424 -0.31693 0.540 0.000 0.000 0.444 0.000 NA
#> GSM1182308 2 0.396 0.66221 0.000 0.696 0.280 0.000 0.020 NA
#> GSM1182310 5 0.482 0.73014 0.000 0.244 0.084 0.008 0.664 NA
#> GSM1182311 1 0.194 0.59817 0.920 0.000 0.000 0.040 0.004 NA
#> GSM1182313 4 0.395 0.63531 0.432 0.000 0.000 0.564 0.000 NA
#> GSM1182315 2 0.314 0.44645 0.000 0.848 0.056 0.012 0.084 NA
#> GSM1182317 2 0.161 0.45313 0.000 0.940 0.016 0.004 0.036 NA
#> GSM1182323 1 0.230 0.57825 0.872 0.000 0.000 0.120 0.000 NA
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> CV:NMF 139 7.73e-02 1.000 2
#> CV:NMF 139 7.73e-02 1.000 3
#> CV:NMF 112 3.10e-02 0.784 4
#> CV:NMF 111 5.13e-08 0.148 5
#> CV:NMF 101 1.54e-06 0.274 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.972 0.988 0.1533 0.927 0.859
#> 4 4 0.777 0.787 0.897 0.2236 0.840 0.643
#> 5 5 0.716 0.674 0.803 0.0590 0.963 0.873
#> 6 6 0.663 0.678 0.771 0.0376 0.909 0.683
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182187 1 0.5988 0.45649 0.632 0 0.368
#> GSM1182188 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182189 1 0.0237 0.96014 0.996 0 0.004
#> GSM1182190 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182191 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182192 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182193 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182194 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182195 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182196 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182197 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182198 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182199 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182200 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182201 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182202 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182203 1 0.1031 0.95264 0.976 0 0.024
#> GSM1182204 1 0.1031 0.95264 0.976 0 0.024
#> GSM1182205 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182206 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182207 1 0.0237 0.96031 0.996 0 0.004
#> GSM1182208 1 0.0237 0.96031 0.996 0 0.004
#> GSM1182209 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182210 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182211 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182212 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182213 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182214 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182215 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182216 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182217 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182218 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182219 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182220 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182221 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182222 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182223 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182224 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182225 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182226 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182227 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182228 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182229 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182230 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182231 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182232 1 0.2448 0.91510 0.924 0 0.076
#> GSM1182233 1 0.2448 0.91510 0.924 0 0.076
#> GSM1182234 3 0.6295 -0.00815 0.472 0 0.528
#> GSM1182235 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182236 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182237 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182238 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182239 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182240 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182241 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182242 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182243 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182244 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182245 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182246 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182247 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182248 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182249 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182250 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182251 1 0.0237 0.96031 0.996 0 0.004
#> GSM1182252 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182253 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182254 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182255 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182256 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182257 1 0.2066 0.93143 0.940 0 0.060
#> GSM1182258 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182259 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182260 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182261 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182262 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182263 1 0.1753 0.93957 0.952 0 0.048
#> GSM1182264 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182265 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182266 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182267 1 0.5431 0.63731 0.716 0 0.284
#> GSM1182268 1 0.3340 0.87346 0.880 0 0.120
#> GSM1182269 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182270 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182271 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182272 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182273 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182275 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182276 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182277 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182278 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182279 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182280 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182281 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182282 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182283 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182284 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182285 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182286 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182287 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182288 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182289 1 0.0237 0.96031 0.996 0 0.004
#> GSM1182290 1 0.0237 0.96031 0.996 0 0.004
#> GSM1182291 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182274 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182292 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182293 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182294 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182295 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182296 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182298 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182299 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182300 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182301 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182303 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182304 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182305 1 0.1860 0.93719 0.948 0 0.052
#> GSM1182306 1 0.1964 0.93423 0.944 0 0.056
#> GSM1182307 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182309 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182312 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182314 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182316 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182318 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182319 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182320 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182321 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182322 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182324 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182297 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182302 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182308 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182310 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182311 1 0.0000 0.96070 1.000 0 0.000
#> GSM1182313 3 0.0000 0.97567 0.000 0 1.000
#> GSM1182315 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182317 2 0.0000 1.00000 0.000 1 0.000
#> GSM1182323 1 0.0000 0.96070 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182187 1 0.4746 0.45649 0.632 0.000 0.000 0.368
#> GSM1182188 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.0188 0.96014 0.996 0.000 0.000 0.004
#> GSM1182190 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182191 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182192 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182193 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182194 3 0.0188 0.49833 0.000 0.004 0.996 0.000
#> GSM1182195 3 0.0000 0.49353 0.000 0.000 1.000 0.000
#> GSM1182196 2 0.2589 0.71769 0.000 0.884 0.116 0.000
#> GSM1182197 2 0.3726 0.50825 0.000 0.788 0.212 0.000
#> GSM1182198 3 0.0000 0.49353 0.000 0.000 1.000 0.000
#> GSM1182199 3 0.0000 0.49353 0.000 0.000 1.000 0.000
#> GSM1182200 2 0.0188 0.87884 0.000 0.996 0.004 0.000
#> GSM1182201 2 0.0188 0.87884 0.000 0.996 0.004 0.000
#> GSM1182202 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182203 1 0.0817 0.95264 0.976 0.000 0.000 0.024
#> GSM1182204 1 0.0817 0.95264 0.976 0.000 0.000 0.024
#> GSM1182205 3 0.4605 0.74522 0.000 0.336 0.664 0.000
#> GSM1182206 3 0.4605 0.74522 0.000 0.336 0.664 0.000
#> GSM1182207 1 0.0188 0.96031 0.996 0.000 0.000 0.004
#> GSM1182208 1 0.0188 0.96031 0.996 0.000 0.000 0.004
#> GSM1182209 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182210 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182211 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182212 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182213 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182214 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182215 3 0.4907 0.72880 0.000 0.420 0.580 0.000
#> GSM1182216 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182217 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182218 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182219 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182220 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182221 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182222 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182223 3 0.4994 0.64669 0.000 0.480 0.520 0.000
#> GSM1182224 3 0.4331 0.72828 0.000 0.288 0.712 0.000
#> GSM1182225 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182226 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182227 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182228 3 0.4985 0.67108 0.000 0.468 0.532 0.000
#> GSM1182229 3 0.4955 0.71026 0.000 0.444 0.556 0.000
#> GSM1182230 3 0.4898 0.73080 0.000 0.416 0.584 0.000
#> GSM1182231 3 0.4907 0.72880 0.000 0.420 0.580 0.000
#> GSM1182232 1 0.1940 0.91510 0.924 0.000 0.000 0.076
#> GSM1182233 1 0.1940 0.91510 0.924 0.000 0.000 0.076
#> GSM1182234 4 0.4989 -0.00815 0.472 0.000 0.000 0.528
#> GSM1182235 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182236 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182237 3 0.4907 0.72880 0.000 0.420 0.580 0.000
#> GSM1182238 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182239 2 0.0469 0.87051 0.000 0.988 0.012 0.000
#> GSM1182240 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182241 2 0.0188 0.87884 0.000 0.996 0.004 0.000
#> GSM1182242 3 0.4948 0.71506 0.000 0.440 0.560 0.000
#> GSM1182243 2 0.4713 -0.03595 0.000 0.640 0.360 0.000
#> GSM1182244 3 0.4331 0.72828 0.000 0.288 0.712 0.000
#> GSM1182245 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182246 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.4933 0.72371 0.000 0.432 0.568 0.000
#> GSM1182248 3 0.4933 0.72371 0.000 0.432 0.568 0.000
#> GSM1182249 2 0.4730 -0.05577 0.000 0.636 0.364 0.000
#> GSM1182250 2 0.4730 -0.05577 0.000 0.636 0.364 0.000
#> GSM1182251 1 0.0188 0.96031 0.996 0.000 0.000 0.004
#> GSM1182252 3 0.4933 0.72371 0.000 0.432 0.568 0.000
#> GSM1182253 3 0.4955 0.70756 0.000 0.444 0.556 0.000
#> GSM1182254 2 0.4989 -0.52115 0.000 0.528 0.472 0.000
#> GSM1182255 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182257 1 0.1637 0.93143 0.940 0.000 0.000 0.060
#> GSM1182258 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182260 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182261 3 0.4907 0.72880 0.000 0.420 0.580 0.000
#> GSM1182262 3 0.4907 0.72880 0.000 0.420 0.580 0.000
#> GSM1182263 1 0.1389 0.93957 0.952 0.000 0.000 0.048
#> GSM1182264 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182265 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182266 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182267 1 0.4304 0.63731 0.716 0.000 0.000 0.284
#> GSM1182268 1 0.2647 0.87346 0.880 0.000 0.000 0.120
#> GSM1182269 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182273 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182275 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182276 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182277 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182278 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182279 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182280 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182281 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182282 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182283 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182284 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182285 3 0.4356 0.73012 0.000 0.292 0.708 0.000
#> GSM1182286 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182287 3 0.4996 0.63714 0.000 0.484 0.516 0.000
#> GSM1182288 3 0.4941 0.71893 0.000 0.436 0.564 0.000
#> GSM1182289 1 0.0188 0.96031 0.996 0.000 0.000 0.004
#> GSM1182290 1 0.0188 0.96031 0.996 0.000 0.000 0.004
#> GSM1182291 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182274 2 0.4713 -0.02448 0.000 0.640 0.360 0.000
#> GSM1182292 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182293 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182294 2 0.0188 0.87869 0.000 0.996 0.004 0.000
#> GSM1182295 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182296 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182298 3 0.0000 0.49353 0.000 0.000 1.000 0.000
#> GSM1182299 2 0.0336 0.87482 0.000 0.992 0.008 0.000
#> GSM1182300 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182301 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182303 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182304 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182305 1 0.1474 0.93719 0.948 0.000 0.000 0.052
#> GSM1182306 1 0.1557 0.93423 0.944 0.000 0.000 0.056
#> GSM1182307 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182309 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182312 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182314 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182318 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182319 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182320 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182321 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182322 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182324 2 0.0817 0.85583 0.000 0.976 0.024 0.000
#> GSM1182297 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182302 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182308 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182310 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182311 1 0.0000 0.96070 1.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.97567 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182317 2 0.0000 0.88225 0.000 1.000 0.000 0.000
#> GSM1182323 1 0.0000 0.96070 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
#> GSM1182186 5 0.4101 0.440 0.372 0.000 0.000 0.000 0.628
#> GSM1182187 5 0.4570 0.118 0.020 0.000 0.000 0.348 0.632
#> GSM1182188 4 0.0566 0.940 0.012 0.000 0.000 0.984 0.004
#> GSM1182189 1 0.3949 0.756 0.668 0.000 0.000 0.000 0.332
#> GSM1182190 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
#> GSM1182191 5 0.4101 0.440 0.372 0.000 0.000 0.000 0.628
#> GSM1182192 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182193 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182194 3 0.2439 0.509 0.120 0.004 0.876 0.000 0.000
#> GSM1182195 3 0.2377 0.498 0.128 0.000 0.872 0.000 0.000
#> GSM1182196 2 0.3460 0.715 0.044 0.828 0.128 0.000 0.000
#> GSM1182197 2 0.3876 0.337 0.000 0.684 0.316 0.000 0.000
#> GSM1182198 3 0.2377 0.498 0.128 0.000 0.872 0.000 0.000
#> GSM1182199 3 0.2377 0.498 0.128 0.000 0.872 0.000 0.000
#> GSM1182200 2 0.1568 0.826 0.036 0.944 0.020 0.000 0.000
#> GSM1182201 2 0.1568 0.826 0.036 0.944 0.020 0.000 0.000
#> GSM1182202 5 0.0703 0.487 0.024 0.000 0.000 0.000 0.976
#> GSM1182203 5 0.0693 0.486 0.008 0.000 0.000 0.012 0.980
#> GSM1182204 5 0.0693 0.486 0.008 0.000 0.000 0.012 0.980
#> GSM1182205 3 0.3366 0.779 0.000 0.232 0.768 0.000 0.000
#> GSM1182206 3 0.3366 0.779 0.000 0.232 0.768 0.000 0.000
#> GSM1182207 5 0.4074 0.443 0.364 0.000 0.000 0.000 0.636
#> GSM1182208 5 0.4074 0.443 0.364 0.000 0.000 0.000 0.636
#> GSM1182209 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182210 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182211 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182212 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182213 2 0.0510 0.834 0.016 0.984 0.000 0.000 0.000
#> GSM1182214 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182215 3 0.3876 0.775 0.000 0.316 0.684 0.000 0.000
#> GSM1182216 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182217 5 0.0963 0.480 0.036 0.000 0.000 0.000 0.964
#> GSM1182218 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
#> GSM1182219 2 0.0324 0.838 0.004 0.992 0.004 0.000 0.000
#> GSM1182220 2 0.0324 0.838 0.004 0.992 0.004 0.000 0.000
#> GSM1182221 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182222 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182223 3 0.4114 0.715 0.000 0.376 0.624 0.000 0.000
#> GSM1182224 3 0.2966 0.758 0.000 0.184 0.816 0.000 0.000
#> GSM1182225 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182226 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182227 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182228 3 0.4074 0.734 0.000 0.364 0.636 0.000 0.000
#> GSM1182229 3 0.3983 0.763 0.000 0.340 0.660 0.000 0.000
#> GSM1182230 3 0.3857 0.777 0.000 0.312 0.688 0.000 0.000
#> GSM1182231 3 0.3876 0.775 0.000 0.316 0.684 0.000 0.000
#> GSM1182232 1 0.3707 0.711 0.716 0.000 0.000 0.000 0.284
#> GSM1182233 1 0.3707 0.711 0.716 0.000 0.000 0.000 0.284
#> GSM1182234 1 0.6213 0.148 0.452 0.000 0.000 0.408 0.140
#> GSM1182235 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182236 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
#> GSM1182237 3 0.3876 0.775 0.000 0.316 0.684 0.000 0.000
#> GSM1182238 2 0.0404 0.839 0.000 0.988 0.012 0.000 0.000
#> GSM1182239 2 0.0955 0.837 0.004 0.968 0.028 0.000 0.000
#> GSM1182240 2 0.0510 0.834 0.016 0.984 0.000 0.000 0.000
#> GSM1182241 2 0.0671 0.835 0.016 0.980 0.004 0.000 0.000
#> GSM1182242 3 0.3966 0.767 0.000 0.336 0.664 0.000 0.000
#> GSM1182243 2 0.4291 -0.244 0.000 0.536 0.464 0.000 0.000
#> GSM1182244 3 0.2966 0.758 0.000 0.184 0.816 0.000 0.000
#> GSM1182245 4 0.2488 0.925 0.124 0.000 0.000 0.872 0.004
#> GSM1182246 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.3932 0.773 0.000 0.328 0.672 0.000 0.000
#> GSM1182248 3 0.3932 0.773 0.000 0.328 0.672 0.000 0.000
#> GSM1182249 2 0.4294 -0.259 0.000 0.532 0.468 0.000 0.000
#> GSM1182250 2 0.4294 -0.259 0.000 0.532 0.468 0.000 0.000
#> GSM1182251 5 0.4088 0.442 0.368 0.000 0.000 0.000 0.632
#> GSM1182252 3 0.3932 0.773 0.000 0.328 0.672 0.000 0.000
#> GSM1182253 3 0.3983 0.761 0.000 0.340 0.660 0.000 0.000
#> GSM1182254 3 0.4235 0.600 0.000 0.424 0.576 0.000 0.000
#> GSM1182255 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 5 0.1579 0.465 0.024 0.000 0.000 0.032 0.944
#> GSM1182258 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182261 3 0.3876 0.775 0.000 0.316 0.684 0.000 0.000
#> GSM1182262 3 0.3876 0.775 0.000 0.316 0.684 0.000 0.000
#> GSM1182263 5 0.4686 0.384 0.384 0.000 0.000 0.020 0.596
#> GSM1182264 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182265 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182266 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182267 1 0.5597 0.426 0.640 0.000 0.000 0.160 0.200
#> GSM1182268 1 0.3424 0.655 0.760 0.000 0.000 0.000 0.240
#> GSM1182269 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
#> GSM1182270 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
#> GSM1182271 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182275 2 0.1357 0.819 0.048 0.948 0.004 0.000 0.000
#> GSM1182276 2 0.1357 0.819 0.048 0.948 0.004 0.000 0.000
#> GSM1182277 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182278 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182279 5 0.4101 0.440 0.372 0.000 0.000 0.000 0.628
#> GSM1182280 5 0.4101 0.440 0.372 0.000 0.000 0.000 0.628
#> GSM1182281 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182282 4 0.2488 0.925 0.124 0.000 0.000 0.872 0.004
#> GSM1182283 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182284 4 0.2843 0.919 0.144 0.000 0.000 0.848 0.008
#> GSM1182285 3 0.3003 0.760 0.000 0.188 0.812 0.000 0.000
#> GSM1182286 2 0.0290 0.839 0.000 0.992 0.008 0.000 0.000
#> GSM1182287 3 0.4126 0.708 0.000 0.380 0.620 0.000 0.000
#> GSM1182288 3 0.3949 0.770 0.000 0.332 0.668 0.000 0.000
#> GSM1182289 5 0.4074 0.443 0.364 0.000 0.000 0.000 0.636
#> GSM1182290 5 0.4074 0.443 0.364 0.000 0.000 0.000 0.636
#> GSM1182291 4 0.0000 0.943 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.4291 -0.235 0.000 0.536 0.464 0.000 0.000
#> GSM1182292 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182293 2 0.0794 0.833 0.000 0.972 0.028 0.000 0.000
#> GSM1182294 2 0.0880 0.832 0.000 0.968 0.032 0.000 0.000
#> GSM1182295 2 0.0290 0.839 0.000 0.992 0.008 0.000 0.000
#> GSM1182296 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182298 3 0.2377 0.498 0.128 0.000 0.872 0.000 0.000
#> GSM1182299 2 0.0992 0.835 0.008 0.968 0.024 0.000 0.000
#> GSM1182300 2 0.0566 0.839 0.004 0.984 0.012 0.000 0.000
#> GSM1182301 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182303 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182304 5 0.4101 0.440 0.372 0.000 0.000 0.000 0.628
#> GSM1182305 5 0.4768 0.380 0.384 0.000 0.000 0.024 0.592
#> GSM1182306 5 0.1493 0.467 0.024 0.000 0.000 0.028 0.948
#> GSM1182307 2 0.1270 0.815 0.052 0.948 0.000 0.000 0.000
#> GSM1182309 2 0.0510 0.838 0.000 0.984 0.016 0.000 0.000
#> GSM1182312 2 0.1121 0.826 0.000 0.956 0.044 0.000 0.000
#> GSM1182314 4 0.0162 0.942 0.004 0.000 0.000 0.996 0.000
#> GSM1182316 2 0.1410 0.812 0.000 0.940 0.060 0.000 0.000
#> GSM1182318 2 0.0510 0.838 0.000 0.984 0.016 0.000 0.000
#> GSM1182319 2 0.1908 0.785 0.000 0.908 0.092 0.000 0.000
#> GSM1182320 2 0.1478 0.809 0.000 0.936 0.064 0.000 0.000
#> GSM1182321 2 0.1908 0.785 0.000 0.908 0.092 0.000 0.000
#> GSM1182322 2 0.1908 0.785 0.000 0.908 0.092 0.000 0.000
#> GSM1182324 2 0.2230 0.757 0.000 0.884 0.116 0.000 0.000
#> GSM1182297 2 0.0290 0.839 0.000 0.992 0.008 0.000 0.000
#> GSM1182302 5 0.0794 0.485 0.028 0.000 0.000 0.000 0.972
#> GSM1182308 2 0.0324 0.838 0.004 0.992 0.004 0.000 0.000
#> GSM1182310 2 0.1908 0.785 0.000 0.908 0.092 0.000 0.000
#> GSM1182311 1 0.3966 0.759 0.664 0.000 0.000 0.000 0.336
#> GSM1182313 4 0.0162 0.942 0.004 0.000 0.000 0.996 0.000
#> GSM1182315 2 0.0510 0.838 0.000 0.984 0.016 0.000 0.000
#> GSM1182317 2 0.1410 0.812 0.000 0.940 0.060 0.000 0.000
#> GSM1182323 1 0.3949 0.763 0.668 0.000 0.000 0.000 0.332
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.0146 0.6306 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182187 1 0.7133 -0.2660 0.416 0.000 0.000 0.100 0.212 0.272
#> GSM1182188 4 0.4096 0.9526 0.008 0.000 0.000 0.508 0.000 0.484
#> GSM1182189 1 0.3838 0.8356 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182190 1 0.3828 0.8441 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182191 5 0.0146 0.6306 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182192 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182193 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182194 3 0.3766 0.2249 0.012 0.000 0.684 0.304 0.000 0.000
#> GSM1182195 3 0.3888 0.2123 0.016 0.000 0.672 0.312 0.000 0.000
#> GSM1182196 2 0.4261 0.6857 0.008 0.748 0.148 0.096 0.000 0.000
#> GSM1182197 2 0.4709 0.0032 0.004 0.596 0.352 0.048 0.000 0.000
#> GSM1182198 3 0.3888 0.2123 0.016 0.000 0.672 0.312 0.000 0.000
#> GSM1182199 3 0.3888 0.2123 0.016 0.000 0.672 0.312 0.000 0.000
#> GSM1182200 2 0.2849 0.8557 0.008 0.864 0.044 0.084 0.000 0.000
#> GSM1182201 2 0.2849 0.8557 0.008 0.864 0.044 0.084 0.000 0.000
#> GSM1182202 5 0.4276 0.5475 0.416 0.000 0.000 0.020 0.564 0.000
#> GSM1182203 5 0.4482 0.5438 0.416 0.000 0.000 0.032 0.552 0.000
#> GSM1182204 5 0.4482 0.5438 0.416 0.000 0.000 0.032 0.552 0.000
#> GSM1182205 3 0.2871 0.7227 0.000 0.192 0.804 0.004 0.000 0.000
#> GSM1182206 3 0.2871 0.7227 0.000 0.192 0.804 0.004 0.000 0.000
#> GSM1182207 5 0.0146 0.6323 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182208 5 0.0146 0.6323 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182209 2 0.1901 0.8603 0.008 0.912 0.004 0.076 0.000 0.000
#> GSM1182210 2 0.1901 0.8603 0.008 0.912 0.004 0.076 0.000 0.000
#> GSM1182211 2 0.1845 0.8615 0.008 0.916 0.004 0.072 0.000 0.000
#> GSM1182212 2 0.2261 0.8484 0.008 0.884 0.004 0.104 0.000 0.000
#> GSM1182213 2 0.1411 0.8827 0.000 0.936 0.004 0.060 0.000 0.000
#> GSM1182214 2 0.1701 0.8626 0.008 0.920 0.000 0.072 0.000 0.000
#> GSM1182215 3 0.3555 0.7409 0.000 0.280 0.712 0.008 0.000 0.000
#> GSM1182216 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182217 5 0.4318 0.5325 0.448 0.000 0.000 0.020 0.532 0.000
#> GSM1182218 1 0.3828 0.8441 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182219 2 0.0820 0.8938 0.000 0.972 0.012 0.016 0.000 0.000
#> GSM1182220 2 0.0820 0.8938 0.000 0.972 0.012 0.016 0.000 0.000
#> GSM1182221 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182222 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182223 3 0.3758 0.7248 0.000 0.324 0.668 0.008 0.000 0.000
#> GSM1182224 3 0.3129 0.6949 0.004 0.152 0.820 0.024 0.000 0.000
#> GSM1182225 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182226 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182227 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182228 3 0.3619 0.7323 0.000 0.316 0.680 0.004 0.000 0.000
#> GSM1182229 3 0.3508 0.7443 0.000 0.292 0.704 0.004 0.000 0.000
#> GSM1182230 3 0.3534 0.7412 0.000 0.276 0.716 0.008 0.000 0.000
#> GSM1182231 3 0.3555 0.7409 0.000 0.280 0.712 0.008 0.000 0.000
#> GSM1182232 1 0.5117 0.7825 0.480 0.000 0.000 0.004 0.448 0.068
#> GSM1182233 1 0.5117 0.7825 0.480 0.000 0.000 0.004 0.448 0.068
#> GSM1182234 6 0.5285 -0.0606 0.108 0.000 0.000 0.000 0.368 0.524
#> GSM1182235 2 0.0993 0.8931 0.000 0.964 0.024 0.012 0.000 0.000
#> GSM1182236 1 0.3828 0.8441 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182237 3 0.3555 0.7409 0.000 0.280 0.712 0.008 0.000 0.000
#> GSM1182238 2 0.0891 0.8925 0.000 0.968 0.024 0.008 0.000 0.000
#> GSM1182239 2 0.1934 0.8838 0.000 0.916 0.044 0.040 0.000 0.000
#> GSM1182240 2 0.1219 0.8858 0.000 0.948 0.004 0.048 0.000 0.000
#> GSM1182241 2 0.1625 0.8827 0.000 0.928 0.012 0.060 0.000 0.000
#> GSM1182242 3 0.3371 0.7447 0.000 0.292 0.708 0.000 0.000 0.000
#> GSM1182243 3 0.4393 0.5066 0.004 0.480 0.500 0.016 0.000 0.000
#> GSM1182244 3 0.2872 0.6986 0.004 0.152 0.832 0.012 0.000 0.000
#> GSM1182245 6 0.0547 0.6262 0.000 0.000 0.000 0.020 0.000 0.980
#> GSM1182246 4 0.3868 0.9775 0.000 0.000 0.000 0.504 0.000 0.496
#> GSM1182247 3 0.3330 0.7466 0.000 0.284 0.716 0.000 0.000 0.000
#> GSM1182248 3 0.3330 0.7466 0.000 0.284 0.716 0.000 0.000 0.000
#> GSM1182249 3 0.4392 0.5158 0.004 0.476 0.504 0.016 0.000 0.000
#> GSM1182250 3 0.4392 0.5158 0.004 0.476 0.504 0.016 0.000 0.000
#> GSM1182251 5 0.0000 0.6316 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 3 0.3330 0.7466 0.000 0.284 0.716 0.000 0.000 0.000
#> GSM1182253 3 0.3595 0.7447 0.000 0.288 0.704 0.008 0.000 0.000
#> GSM1182254 3 0.4099 0.6802 0.000 0.372 0.612 0.016 0.000 0.000
#> GSM1182255 4 0.3998 0.9870 0.004 0.000 0.000 0.504 0.000 0.492
#> GSM1182256 4 0.3998 0.9870 0.004 0.000 0.000 0.504 0.000 0.492
#> GSM1182257 5 0.5215 0.5274 0.412 0.000 0.000 0.056 0.516 0.016
#> GSM1182258 4 0.3998 0.9870 0.004 0.000 0.000 0.504 0.000 0.492
#> GSM1182259 6 0.3868 -0.9652 0.000 0.000 0.000 0.496 0.000 0.504
#> GSM1182260 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182261 3 0.3555 0.7409 0.000 0.280 0.712 0.008 0.000 0.000
#> GSM1182262 3 0.3555 0.7409 0.000 0.280 0.712 0.008 0.000 0.000
#> GSM1182263 5 0.1515 0.5940 0.008 0.000 0.000 0.020 0.944 0.028
#> GSM1182264 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182265 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182266 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182267 5 0.6182 -0.5498 0.316 0.000 0.000 0.004 0.404 0.276
#> GSM1182268 1 0.5516 0.7473 0.460 0.000 0.000 0.004 0.424 0.112
#> GSM1182269 1 0.3828 0.8441 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182270 1 0.3828 0.8441 0.560 0.000 0.000 0.000 0.440 0.000
#> GSM1182271 4 0.3998 0.9870 0.004 0.000 0.000 0.504 0.000 0.492
#> GSM1182272 6 0.3868 -0.9652 0.000 0.000 0.000 0.496 0.000 0.504
#> GSM1182273 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182275 2 0.2468 0.8548 0.008 0.880 0.016 0.096 0.000 0.000
#> GSM1182276 2 0.2468 0.8548 0.008 0.880 0.016 0.096 0.000 0.000
#> GSM1182277 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182278 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182279 5 0.0146 0.6306 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182280 5 0.0146 0.6306 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182281 6 0.3868 -0.9652 0.000 0.000 0.000 0.496 0.000 0.504
#> GSM1182282 6 0.0547 0.6262 0.000 0.000 0.000 0.020 0.000 0.980
#> GSM1182283 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182284 6 0.0146 0.6519 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM1182285 3 0.2988 0.6964 0.000 0.152 0.824 0.024 0.000 0.000
#> GSM1182286 2 0.0717 0.8944 0.000 0.976 0.016 0.008 0.000 0.000
#> GSM1182287 3 0.3774 0.7210 0.000 0.328 0.664 0.008 0.000 0.000
#> GSM1182288 3 0.3351 0.7456 0.000 0.288 0.712 0.000 0.000 0.000
#> GSM1182289 5 0.0146 0.6323 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182290 5 0.0146 0.6323 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182291 4 0.3998 0.9870 0.004 0.000 0.000 0.504 0.000 0.492
#> GSM1182274 3 0.4313 0.5039 0.004 0.480 0.504 0.012 0.000 0.000
#> GSM1182292 2 0.1728 0.8658 0.008 0.924 0.004 0.064 0.000 0.000
#> GSM1182293 2 0.1320 0.8850 0.000 0.948 0.036 0.016 0.000 0.000
#> GSM1182294 2 0.1594 0.8758 0.000 0.932 0.052 0.016 0.000 0.000
#> GSM1182295 2 0.0508 0.8956 0.000 0.984 0.012 0.004 0.000 0.000
#> GSM1182296 2 0.1728 0.8658 0.008 0.924 0.004 0.064 0.000 0.000
#> GSM1182298 3 0.3888 0.2123 0.016 0.000 0.672 0.312 0.000 0.000
#> GSM1182299 2 0.2585 0.8595 0.004 0.880 0.048 0.068 0.000 0.000
#> GSM1182300 2 0.0806 0.8952 0.000 0.972 0.020 0.008 0.000 0.000
#> GSM1182301 2 0.1845 0.8615 0.008 0.916 0.004 0.072 0.000 0.000
#> GSM1182303 2 0.2261 0.8484 0.008 0.884 0.004 0.104 0.000 0.000
#> GSM1182304 5 0.0146 0.6306 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182305 5 0.1478 0.5916 0.004 0.000 0.000 0.020 0.944 0.032
#> GSM1182306 5 0.5169 0.5279 0.416 0.000 0.000 0.052 0.516 0.016
#> GSM1182307 2 0.1701 0.8626 0.008 0.920 0.000 0.072 0.000 0.000
#> GSM1182309 2 0.1151 0.8886 0.000 0.956 0.032 0.012 0.000 0.000
#> GSM1182312 2 0.1745 0.8681 0.000 0.920 0.068 0.012 0.000 0.000
#> GSM1182314 4 0.3868 0.9802 0.000 0.000 0.000 0.508 0.000 0.492
#> GSM1182316 2 0.2006 0.8472 0.000 0.904 0.080 0.016 0.000 0.000
#> GSM1182318 2 0.1074 0.8923 0.000 0.960 0.028 0.012 0.000 0.000
#> GSM1182319 2 0.2887 0.7835 0.000 0.844 0.120 0.036 0.000 0.000
#> GSM1182320 2 0.2384 0.8315 0.000 0.884 0.084 0.032 0.000 0.000
#> GSM1182321 2 0.2887 0.7835 0.000 0.844 0.120 0.036 0.000 0.000
#> GSM1182322 2 0.2887 0.7835 0.000 0.844 0.120 0.036 0.000 0.000
#> GSM1182324 2 0.3062 0.7468 0.000 0.824 0.144 0.032 0.000 0.000
#> GSM1182297 2 0.0909 0.8941 0.000 0.968 0.020 0.012 0.000 0.000
#> GSM1182302 5 0.4289 0.5447 0.424 0.000 0.000 0.020 0.556 0.000
#> GSM1182308 2 0.0820 0.8938 0.000 0.972 0.012 0.016 0.000 0.000
#> GSM1182310 2 0.2887 0.7835 0.000 0.844 0.120 0.036 0.000 0.000
#> GSM1182311 1 0.3966 0.8409 0.552 0.000 0.000 0.004 0.444 0.000
#> GSM1182313 4 0.3868 0.9802 0.000 0.000 0.000 0.508 0.000 0.492
#> GSM1182315 2 0.1049 0.8896 0.000 0.960 0.032 0.008 0.000 0.000
#> GSM1182317 2 0.2006 0.8472 0.000 0.904 0.080 0.016 0.000 0.000
#> GSM1182323 1 0.3828 0.8441 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:hclust 139 7.73e-02 1.000 2
#> MAD:hclust 137 1.27e-01 0.792 3
#> MAD:hclust 122 2.10e-05 0.441 4
#> MAD:hclust 103 1.57e-05 0.227 5
#> MAD:hclust 127 1.73e-05 0.544 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.731 0.941 0.826 0.2945 0.815 0.645
#> 4 4 0.605 0.850 0.761 0.1272 0.924 0.774
#> 5 5 0.714 0.768 0.765 0.0837 0.984 0.941
#> 6 6 0.690 0.659 0.733 0.0505 0.906 0.652
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182187 1 0.465 0.861 0.792 0.000 0.208
#> GSM1182188 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182189 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182190 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182191 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182192 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182193 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182194 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182195 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182196 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182197 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182198 3 0.660 0.977 0.012 0.384 0.604
#> GSM1182199 3 0.660 0.977 0.012 0.384 0.604
#> GSM1182200 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182201 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182202 1 0.597 0.859 0.636 0.000 0.364
#> GSM1182203 1 0.514 0.860 0.748 0.000 0.252
#> GSM1182204 1 0.599 0.858 0.632 0.000 0.368
#> GSM1182205 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182206 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182207 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182208 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182209 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182210 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182211 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182212 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182213 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182214 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182215 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182216 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182217 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182218 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182219 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182220 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182221 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182222 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182223 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182224 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182225 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182226 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182227 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182228 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182229 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182230 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182231 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182232 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182233 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182234 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182235 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182236 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182237 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182238 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182239 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182240 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182241 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182242 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182243 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182244 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182245 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182246 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182247 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182248 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182249 3 0.624 0.921 0.000 0.440 0.560
#> GSM1182250 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182251 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182252 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182253 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182254 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182255 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182256 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182257 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182258 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182259 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182260 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182261 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182262 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182263 1 0.518 0.865 0.744 0.000 0.256
#> GSM1182264 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182265 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182266 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182267 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182268 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182269 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182270 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182271 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182272 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182273 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182275 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182276 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182277 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182278 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182279 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182280 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182281 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182282 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182283 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182284 1 0.000 0.850 1.000 0.000 0.000
#> GSM1182285 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182286 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182287 3 0.613 0.991 0.000 0.400 0.600
#> GSM1182288 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182289 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182290 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182291 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182274 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182292 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182293 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182294 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182295 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182296 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182298 3 0.611 0.997 0.000 0.396 0.604
#> GSM1182299 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182300 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182301 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182303 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182304 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182305 1 0.529 0.865 0.732 0.000 0.268
#> GSM1182306 1 0.406 0.854 0.836 0.000 0.164
#> GSM1182307 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182309 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182312 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182314 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182316 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182318 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182319 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182320 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182321 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182322 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182324 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182297 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182302 1 0.597 0.859 0.636 0.000 0.364
#> GSM1182308 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182310 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182311 1 0.581 0.862 0.664 0.000 0.336
#> GSM1182313 1 0.207 0.836 0.940 0.000 0.060
#> GSM1182315 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182317 2 0.000 1.000 0.000 1.000 0.000
#> GSM1182323 1 0.581 0.862 0.664 0.000 0.336
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182187 4 0.4539 0.19689 0.272 0.000 0.008 0.720
#> GSM1182188 4 0.0188 0.81197 0.000 0.000 0.004 0.996
#> GSM1182189 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182190 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182191 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182192 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182193 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182194 3 0.5728 0.88368 0.104 0.188 0.708 0.000
#> GSM1182195 3 0.5396 0.86147 0.104 0.156 0.740 0.000
#> GSM1182196 2 0.2988 0.87411 0.112 0.876 0.012 0.000
#> GSM1182197 2 0.4844 0.76192 0.108 0.784 0.108 0.000
#> GSM1182198 3 0.5257 0.85036 0.104 0.144 0.752 0.000
#> GSM1182199 3 0.5257 0.85036 0.104 0.144 0.752 0.000
#> GSM1182200 2 0.2831 0.87333 0.120 0.876 0.004 0.000
#> GSM1182201 3 0.6975 0.70760 0.148 0.292 0.560 0.000
#> GSM1182202 1 0.5070 0.90900 0.580 0.000 0.004 0.416
#> GSM1182203 4 0.4746 0.00362 0.304 0.000 0.008 0.688
#> GSM1182204 1 0.5105 0.88684 0.564 0.000 0.004 0.432
#> GSM1182205 3 0.4163 0.91502 0.020 0.188 0.792 0.000
#> GSM1182206 3 0.3852 0.91658 0.008 0.192 0.800 0.000
#> GSM1182207 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182208 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182209 2 0.2647 0.88065 0.120 0.880 0.000 0.000
#> GSM1182210 2 0.2589 0.88203 0.116 0.884 0.000 0.000
#> GSM1182211 2 0.2647 0.88065 0.120 0.880 0.000 0.000
#> GSM1182212 2 0.2530 0.87858 0.112 0.888 0.000 0.000
#> GSM1182213 2 0.2589 0.87814 0.116 0.884 0.000 0.000
#> GSM1182214 2 0.2589 0.88255 0.116 0.884 0.000 0.000
#> GSM1182215 3 0.3937 0.91719 0.012 0.188 0.800 0.000
#> GSM1182216 2 0.0657 0.89001 0.012 0.984 0.004 0.000
#> GSM1182217 1 0.5279 0.92411 0.588 0.000 0.012 0.400
#> GSM1182218 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182219 2 0.2408 0.88418 0.104 0.896 0.000 0.000
#> GSM1182220 2 0.2704 0.87644 0.124 0.876 0.000 0.000
#> GSM1182221 2 0.2773 0.86605 0.116 0.880 0.004 0.000
#> GSM1182222 2 0.0657 0.89001 0.012 0.984 0.004 0.000
#> GSM1182223 3 0.6578 0.72187 0.108 0.300 0.592 0.000
#> GSM1182224 3 0.5728 0.88368 0.104 0.188 0.708 0.000
#> GSM1182225 2 0.0469 0.89031 0.012 0.988 0.000 0.000
#> GSM1182226 2 0.0779 0.88991 0.016 0.980 0.004 0.000
#> GSM1182227 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182228 3 0.6627 0.72417 0.112 0.300 0.588 0.000
#> GSM1182229 3 0.3810 0.91645 0.008 0.188 0.804 0.000
#> GSM1182230 3 0.3668 0.91652 0.004 0.188 0.808 0.000
#> GSM1182231 2 0.3037 0.81210 0.020 0.880 0.100 0.000
#> GSM1182232 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182233 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182234 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182235 2 0.0657 0.89001 0.012 0.984 0.004 0.000
#> GSM1182236 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182237 3 0.5489 0.82389 0.040 0.296 0.664 0.000
#> GSM1182238 2 0.0657 0.89001 0.012 0.984 0.004 0.000
#> GSM1182239 2 0.1398 0.89129 0.040 0.956 0.004 0.000
#> GSM1182240 2 0.2530 0.87858 0.112 0.888 0.000 0.000
#> GSM1182241 2 0.3351 0.86249 0.148 0.844 0.008 0.000
#> GSM1182242 3 0.4163 0.91675 0.020 0.188 0.792 0.000
#> GSM1182243 3 0.4636 0.91277 0.040 0.188 0.772 0.000
#> GSM1182244 3 0.5728 0.88368 0.104 0.188 0.708 0.000
#> GSM1182245 4 0.4410 0.77287 0.064 0.000 0.128 0.808
#> GSM1182246 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.4054 0.91558 0.016 0.188 0.796 0.000
#> GSM1182248 3 0.4054 0.91558 0.016 0.188 0.796 0.000
#> GSM1182249 3 0.6316 0.74425 0.080 0.324 0.596 0.000
#> GSM1182250 3 0.4636 0.91277 0.040 0.188 0.772 0.000
#> GSM1182251 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182252 3 0.4054 0.91558 0.016 0.188 0.796 0.000
#> GSM1182253 3 0.4054 0.91558 0.016 0.188 0.796 0.000
#> GSM1182254 3 0.4549 0.91349 0.036 0.188 0.776 0.000
#> GSM1182255 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0937 0.80829 0.012 0.000 0.012 0.976
#> GSM1182258 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.4677 0.91149 0.040 0.192 0.768 0.000
#> GSM1182261 3 0.4755 0.90933 0.040 0.200 0.760 0.000
#> GSM1182262 3 0.3852 0.91683 0.008 0.192 0.800 0.000
#> GSM1182263 1 0.5510 0.78525 0.504 0.000 0.016 0.480
#> GSM1182264 3 0.4636 0.91277 0.040 0.188 0.772 0.000
#> GSM1182265 3 0.5318 0.89509 0.072 0.196 0.732 0.000
#> GSM1182266 3 0.4636 0.91277 0.040 0.188 0.772 0.000
#> GSM1182267 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182268 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182269 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182270 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182271 4 0.0188 0.81197 0.000 0.000 0.004 0.996
#> GSM1182272 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.4636 0.91277 0.040 0.188 0.772 0.000
#> GSM1182275 3 0.5410 0.89352 0.080 0.192 0.728 0.000
#> GSM1182276 2 0.2530 0.87858 0.112 0.888 0.000 0.000
#> GSM1182277 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182278 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182279 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182280 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182281 4 0.1118 0.81040 0.000 0.000 0.036 0.964
#> GSM1182282 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182283 4 0.4711 0.76516 0.064 0.000 0.152 0.784
#> GSM1182284 4 0.4663 0.76652 0.064 0.000 0.148 0.788
#> GSM1182285 3 0.5728 0.88368 0.104 0.188 0.708 0.000
#> GSM1182286 2 0.1867 0.88968 0.072 0.928 0.000 0.000
#> GSM1182287 3 0.6949 0.62251 0.124 0.348 0.528 0.000
#> GSM1182288 3 0.4054 0.91558 0.016 0.188 0.796 0.000
#> GSM1182289 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182290 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182291 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.4716 0.90988 0.040 0.196 0.764 0.000
#> GSM1182292 2 0.2647 0.88065 0.120 0.880 0.000 0.000
#> GSM1182293 2 0.2814 0.85302 0.132 0.868 0.000 0.000
#> GSM1182294 2 0.3529 0.83796 0.152 0.836 0.012 0.000
#> GSM1182295 2 0.0817 0.88954 0.024 0.976 0.000 0.000
#> GSM1182296 2 0.2647 0.88065 0.120 0.880 0.000 0.000
#> GSM1182298 3 0.5396 0.86147 0.104 0.156 0.740 0.000
#> GSM1182299 2 0.2466 0.88327 0.096 0.900 0.004 0.000
#> GSM1182300 2 0.2149 0.87734 0.088 0.912 0.000 0.000
#> GSM1182301 2 0.2647 0.88065 0.120 0.880 0.000 0.000
#> GSM1182303 2 0.2530 0.87858 0.112 0.888 0.000 0.000
#> GSM1182304 1 0.5279 0.92481 0.588 0.000 0.012 0.400
#> GSM1182305 1 0.5508 0.79541 0.508 0.000 0.016 0.476
#> GSM1182306 4 0.3591 0.56126 0.168 0.000 0.008 0.824
#> GSM1182307 2 0.2530 0.88316 0.112 0.888 0.000 0.000
#> GSM1182309 2 0.2999 0.85167 0.132 0.864 0.004 0.000
#> GSM1182312 2 0.3157 0.85098 0.144 0.852 0.004 0.000
#> GSM1182314 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.2921 0.84995 0.140 0.860 0.000 0.000
#> GSM1182318 2 0.2216 0.87028 0.092 0.908 0.000 0.000
#> GSM1182319 2 0.3672 0.83063 0.164 0.824 0.012 0.000
#> GSM1182320 2 0.2921 0.84995 0.140 0.860 0.000 0.000
#> GSM1182321 2 0.3672 0.83063 0.164 0.824 0.012 0.000
#> GSM1182322 2 0.3672 0.83063 0.164 0.824 0.012 0.000
#> GSM1182324 2 0.3672 0.83063 0.164 0.824 0.012 0.000
#> GSM1182297 2 0.0707 0.89082 0.020 0.980 0.000 0.000
#> GSM1182302 1 0.5203 0.91029 0.576 0.000 0.008 0.416
#> GSM1182308 2 0.2216 0.88642 0.092 0.908 0.000 0.000
#> GSM1182310 2 0.3672 0.83063 0.164 0.824 0.012 0.000
#> GSM1182311 1 0.6384 0.91351 0.532 0.000 0.068 0.400
#> GSM1182313 4 0.0000 0.81416 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.2408 0.86707 0.104 0.896 0.000 0.000
#> GSM1182317 2 0.2814 0.85302 0.132 0.868 0.000 0.000
#> GSM1182323 1 0.6384 0.91351 0.532 0.000 0.068 0.400
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182187 1 0.4993 0.107 0.624 0.000 0.024 0.340 NA
#> GSM1182188 4 0.4190 0.787 0.256 0.000 0.008 0.724 NA
#> GSM1182189 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182190 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182191 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182192 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182193 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182194 3 0.6393 0.755 0.000 0.060 0.636 0.160 NA
#> GSM1182195 3 0.6109 0.743 0.000 0.040 0.652 0.164 NA
#> GSM1182196 2 0.5611 0.758 0.000 0.700 0.092 0.044 NA
#> GSM1182197 2 0.7015 0.421 0.000 0.528 0.292 0.080 NA
#> GSM1182198 3 0.6072 0.739 0.000 0.036 0.652 0.168 NA
#> GSM1182199 3 0.6072 0.739 0.000 0.036 0.652 0.168 NA
#> GSM1182200 2 0.1507 0.773 0.000 0.952 0.024 0.012 NA
#> GSM1182201 3 0.5307 0.630 0.000 0.316 0.628 0.036 NA
#> GSM1182202 1 0.1893 0.800 0.936 0.000 0.024 0.028 NA
#> GSM1182203 1 0.4839 0.248 0.660 0.000 0.024 0.304 NA
#> GSM1182204 1 0.2060 0.794 0.928 0.000 0.024 0.036 NA
#> GSM1182205 3 0.3054 0.861 0.000 0.060 0.880 0.032 NA
#> GSM1182206 3 0.3758 0.852 0.000 0.060 0.840 0.072 NA
#> GSM1182207 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182208 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182209 2 0.0510 0.794 0.000 0.984 0.000 0.000 NA
#> GSM1182210 2 0.0510 0.794 0.000 0.984 0.000 0.000 NA
#> GSM1182211 2 0.0510 0.794 0.000 0.984 0.000 0.000 NA
#> GSM1182212 2 0.0566 0.788 0.000 0.984 0.000 0.012 NA
#> GSM1182213 2 0.0290 0.790 0.000 0.992 0.000 0.000 NA
#> GSM1182214 2 0.1485 0.800 0.000 0.948 0.000 0.020 NA
#> GSM1182215 3 0.3432 0.862 0.000 0.060 0.860 0.052 NA
#> GSM1182216 2 0.4791 0.797 0.000 0.740 0.012 0.072 NA
#> GSM1182217 1 0.1725 0.821 0.936 0.000 0.020 0.000 NA
#> GSM1182218 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182219 2 0.2230 0.797 0.000 0.912 0.000 0.044 NA
#> GSM1182220 2 0.0771 0.788 0.000 0.976 0.000 0.004 NA
#> GSM1182221 2 0.5107 0.775 0.000 0.596 0.000 0.048 NA
#> GSM1182222 2 0.4684 0.798 0.000 0.744 0.008 0.072 NA
#> GSM1182223 3 0.5177 0.651 0.000 0.292 0.652 0.040 NA
#> GSM1182224 3 0.6393 0.756 0.000 0.060 0.636 0.160 NA
#> GSM1182225 2 0.4372 0.801 0.000 0.756 0.000 0.072 NA
#> GSM1182226 2 0.4895 0.796 0.000 0.728 0.012 0.072 NA
#> GSM1182227 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182228 3 0.5115 0.668 0.000 0.280 0.664 0.040 NA
#> GSM1182229 3 0.1731 0.866 0.000 0.060 0.932 0.004 NA
#> GSM1182230 3 0.2790 0.867 0.000 0.060 0.892 0.028 NA
#> GSM1182231 2 0.7218 0.524 0.000 0.524 0.252 0.072 NA
#> GSM1182232 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182233 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182234 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182235 2 0.4755 0.798 0.000 0.744 0.012 0.072 NA
#> GSM1182236 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182237 3 0.5646 0.734 0.000 0.064 0.704 0.076 NA
#> GSM1182238 2 0.4791 0.797 0.000 0.740 0.012 0.072 NA
#> GSM1182239 2 0.4583 0.800 0.000 0.760 0.012 0.068 NA
#> GSM1182240 2 0.0451 0.789 0.000 0.988 0.000 0.008 NA
#> GSM1182241 2 0.2351 0.783 0.000 0.916 0.020 0.036 NA
#> GSM1182242 3 0.2199 0.866 0.000 0.060 0.916 0.016 NA
#> GSM1182243 3 0.3034 0.860 0.000 0.060 0.880 0.040 NA
#> GSM1182244 3 0.6393 0.756 0.000 0.060 0.636 0.160 NA
#> GSM1182245 4 0.7049 0.758 0.312 0.000 0.020 0.448 NA
#> GSM1182246 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182247 3 0.2590 0.864 0.000 0.060 0.900 0.028 NA
#> GSM1182248 3 0.2590 0.864 0.000 0.060 0.900 0.028 NA
#> GSM1182249 3 0.6043 0.695 0.000 0.092 0.672 0.072 NA
#> GSM1182250 3 0.2967 0.862 0.000 0.060 0.884 0.032 NA
#> GSM1182251 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182252 3 0.2778 0.864 0.000 0.060 0.892 0.032 NA
#> GSM1182253 3 0.2502 0.865 0.000 0.060 0.904 0.024 NA
#> GSM1182254 3 0.2590 0.864 0.000 0.060 0.900 0.028 NA
#> GSM1182255 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182256 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182257 4 0.5200 0.780 0.264 0.000 0.024 0.672 NA
#> GSM1182258 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182259 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182260 3 0.2967 0.862 0.000 0.060 0.884 0.032 NA
#> GSM1182261 3 0.3960 0.838 0.000 0.060 0.828 0.080 NA
#> GSM1182262 3 0.3414 0.862 0.000 0.060 0.860 0.056 NA
#> GSM1182263 1 0.3272 0.728 0.860 0.000 0.008 0.072 NA
#> GSM1182264 3 0.2199 0.866 0.000 0.060 0.916 0.008 NA
#> GSM1182265 3 0.3818 0.847 0.000 0.060 0.836 0.028 NA
#> GSM1182266 3 0.2074 0.866 0.000 0.060 0.920 0.004 NA
#> GSM1182267 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182268 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182269 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182270 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182271 4 0.4190 0.787 0.256 0.000 0.008 0.724 NA
#> GSM1182272 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182273 3 0.2074 0.866 0.000 0.060 0.920 0.004 NA
#> GSM1182275 3 0.3265 0.840 0.000 0.128 0.844 0.012 NA
#> GSM1182276 2 0.0566 0.788 0.000 0.984 0.000 0.012 NA
#> GSM1182277 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182278 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182279 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182280 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182281 4 0.5059 0.795 0.256 0.000 0.000 0.668 NA
#> GSM1182282 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182283 4 0.7150 0.749 0.316 0.000 0.020 0.420 NA
#> GSM1182284 4 0.7099 0.755 0.312 0.000 0.020 0.436 NA
#> GSM1182285 3 0.6358 0.756 0.000 0.060 0.640 0.156 NA
#> GSM1182286 2 0.3410 0.801 0.000 0.840 0.000 0.068 NA
#> GSM1182287 3 0.5194 0.508 0.000 0.412 0.552 0.024 NA
#> GSM1182288 3 0.2590 0.864 0.000 0.060 0.900 0.028 NA
#> GSM1182289 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182290 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182291 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182274 3 0.3138 0.860 0.000 0.060 0.876 0.032 NA
#> GSM1182292 2 0.0898 0.791 0.000 0.972 0.000 0.008 NA
#> GSM1182293 2 0.4287 0.744 0.000 0.540 0.000 0.000 NA
#> GSM1182294 2 0.4549 0.738 0.000 0.528 0.008 0.000 NA
#> GSM1182295 2 0.3534 0.806 0.000 0.744 0.000 0.000 NA
#> GSM1182296 2 0.0798 0.793 0.000 0.976 0.000 0.008 NA
#> GSM1182298 3 0.6109 0.743 0.000 0.040 0.652 0.164 NA
#> GSM1182299 2 0.3627 0.801 0.000 0.840 0.020 0.040 NA
#> GSM1182300 2 0.4074 0.779 0.000 0.636 0.000 0.000 NA
#> GSM1182301 2 0.0992 0.792 0.000 0.968 0.000 0.008 NA
#> GSM1182303 2 0.0566 0.788 0.000 0.984 0.000 0.012 NA
#> GSM1182304 1 0.1082 0.826 0.964 0.000 0.008 0.000 NA
#> GSM1182305 1 0.2872 0.759 0.884 0.000 0.008 0.060 NA
#> GSM1182306 1 0.5256 -0.380 0.492 0.000 0.024 0.472 NA
#> GSM1182307 2 0.0794 0.798 0.000 0.972 0.000 0.000 NA
#> GSM1182309 2 0.4287 0.744 0.000 0.540 0.000 0.000 NA
#> GSM1182312 2 0.5032 0.742 0.000 0.520 0.000 0.032 NA
#> GSM1182314 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182316 2 0.4287 0.744 0.000 0.540 0.000 0.000 NA
#> GSM1182318 2 0.4101 0.777 0.000 0.628 0.000 0.000 NA
#> GSM1182319 2 0.4695 0.736 0.000 0.524 0.008 0.004 NA
#> GSM1182320 2 0.4430 0.743 0.000 0.540 0.000 0.004 NA
#> GSM1182321 2 0.4695 0.736 0.000 0.524 0.008 0.004 NA
#> GSM1182322 2 0.4698 0.734 0.000 0.520 0.008 0.004 NA
#> GSM1182324 2 0.4698 0.734 0.000 0.520 0.008 0.004 NA
#> GSM1182297 2 0.4238 0.803 0.000 0.768 0.000 0.068 NA
#> GSM1182302 1 0.2277 0.802 0.920 0.000 0.024 0.028 NA
#> GSM1182308 2 0.1124 0.802 0.000 0.960 0.000 0.004 NA
#> GSM1182310 2 0.4698 0.734 0.000 0.520 0.008 0.004 NA
#> GSM1182311 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
#> GSM1182313 4 0.3534 0.800 0.256 0.000 0.000 0.744 NA
#> GSM1182315 2 0.4321 0.771 0.000 0.600 0.000 0.004 NA
#> GSM1182317 2 0.4287 0.744 0.000 0.540 0.000 0.000 NA
#> GSM1182323 1 0.2886 0.801 0.844 0.000 0.008 0.000 NA
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.1124 0.8253 0.036 0.000 0.000 0.000 0.956 0.008
#> GSM1182187 5 0.5271 0.0558 0.040 0.000 0.016 0.348 0.580 0.016
#> GSM1182188 4 0.3192 0.7782 0.004 0.000 0.000 0.776 0.216 0.004
#> GSM1182189 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182190 5 0.3426 0.8024 0.124 0.000 0.000 0.000 0.808 0.068
#> GSM1182191 5 0.1124 0.8253 0.036 0.000 0.000 0.000 0.956 0.008
#> GSM1182192 4 0.6849 0.7273 0.044 0.000 0.004 0.420 0.284 0.248
#> GSM1182193 4 0.6849 0.7273 0.044 0.000 0.004 0.420 0.284 0.248
#> GSM1182194 6 0.4124 0.9749 0.000 0.024 0.332 0.000 0.000 0.644
#> GSM1182195 6 0.4185 0.9766 0.000 0.020 0.332 0.004 0.000 0.644
#> GSM1182196 2 0.7103 -0.0248 0.232 0.364 0.344 0.048 0.000 0.012
#> GSM1182197 3 0.6765 0.3613 0.084 0.260 0.544 0.052 0.000 0.060
#> GSM1182198 6 0.4105 0.9716 0.000 0.016 0.332 0.004 0.000 0.648
#> GSM1182199 6 0.4105 0.9716 0.000 0.016 0.332 0.004 0.000 0.648
#> GSM1182200 2 0.2201 0.6098 0.024 0.916 0.036 0.016 0.000 0.008
#> GSM1182201 3 0.4805 0.5499 0.032 0.216 0.704 0.036 0.000 0.012
#> GSM1182202 5 0.2508 0.7998 0.048 0.000 0.016 0.024 0.900 0.012
#> GSM1182203 5 0.5096 0.2013 0.040 0.000 0.016 0.320 0.612 0.012
#> GSM1182204 5 0.2672 0.7884 0.040 0.000 0.016 0.040 0.892 0.012
#> GSM1182205 3 0.3898 0.4323 0.004 0.024 0.748 0.008 0.000 0.216
#> GSM1182206 3 0.4601 0.6075 0.032 0.028 0.772 0.096 0.000 0.072
#> GSM1182207 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182208 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182209 2 0.0632 0.6410 0.024 0.976 0.000 0.000 0.000 0.000
#> GSM1182210 2 0.0632 0.6410 0.024 0.976 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.0547 0.6432 0.020 0.980 0.000 0.000 0.000 0.000
#> GSM1182212 2 0.0912 0.6445 0.004 0.972 0.004 0.012 0.000 0.008
#> GSM1182213 2 0.0000 0.6488 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182214 2 0.2101 0.6371 0.028 0.912 0.000 0.052 0.000 0.008
#> GSM1182215 3 0.4430 0.6140 0.036 0.024 0.784 0.096 0.000 0.060
#> GSM1182216 2 0.7263 0.2644 0.220 0.504 0.064 0.160 0.000 0.052
#> GSM1182217 5 0.2151 0.8211 0.072 0.000 0.016 0.000 0.904 0.008
#> GSM1182218 5 0.3426 0.8024 0.124 0.000 0.000 0.000 0.808 0.068
#> GSM1182219 2 0.4923 0.5303 0.068 0.728 0.012 0.152 0.000 0.040
#> GSM1182220 2 0.1492 0.6434 0.024 0.940 0.000 0.036 0.000 0.000
#> GSM1182221 1 0.6725 0.3880 0.448 0.344 0.020 0.156 0.000 0.032
#> GSM1182222 2 0.7263 0.2644 0.220 0.504 0.064 0.160 0.000 0.052
#> GSM1182223 3 0.3709 0.5947 0.012 0.184 0.780 0.012 0.000 0.012
#> GSM1182224 6 0.4315 0.9690 0.004 0.024 0.348 0.000 0.000 0.624
#> GSM1182225 2 0.7091 0.2818 0.220 0.520 0.052 0.156 0.000 0.052
#> GSM1182226 2 0.7402 0.1802 0.248 0.472 0.064 0.164 0.000 0.052
#> GSM1182227 4 0.6734 0.7273 0.044 0.000 0.000 0.420 0.284 0.252
#> GSM1182228 3 0.3540 0.6136 0.012 0.164 0.800 0.012 0.000 0.012
#> GSM1182229 3 0.1321 0.6895 0.000 0.024 0.952 0.004 0.000 0.020
#> GSM1182230 3 0.4168 0.6249 0.028 0.024 0.800 0.096 0.000 0.052
#> GSM1182231 3 0.8228 -0.1454 0.156 0.268 0.348 0.172 0.000 0.056
#> GSM1182232 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182233 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182234 4 0.6898 0.7241 0.048 0.000 0.004 0.416 0.284 0.248
#> GSM1182235 2 0.7247 0.2736 0.216 0.508 0.060 0.160 0.000 0.056
#> GSM1182236 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182237 3 0.6567 0.3544 0.164 0.028 0.580 0.172 0.000 0.056
#> GSM1182238 2 0.7263 0.2644 0.220 0.504 0.064 0.160 0.000 0.052
#> GSM1182239 2 0.7089 0.3183 0.196 0.536 0.060 0.152 0.000 0.056
#> GSM1182240 2 0.0582 0.6465 0.004 0.984 0.004 0.004 0.000 0.004
#> GSM1182241 2 0.4056 0.5672 0.040 0.808 0.088 0.048 0.000 0.016
#> GSM1182242 3 0.2728 0.6429 0.004 0.024 0.876 0.012 0.000 0.084
#> GSM1182243 3 0.2265 0.7008 0.028 0.024 0.912 0.032 0.000 0.004
#> GSM1182244 6 0.4554 0.9628 0.004 0.024 0.348 0.008 0.000 0.616
#> GSM1182245 4 0.6838 0.7333 0.048 0.000 0.004 0.436 0.280 0.232
#> GSM1182246 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182247 3 0.2990 0.6062 0.004 0.024 0.844 0.004 0.000 0.124
#> GSM1182248 3 0.2990 0.6062 0.004 0.024 0.844 0.004 0.000 0.124
#> GSM1182249 3 0.4924 0.6065 0.132 0.040 0.744 0.044 0.000 0.040
#> GSM1182250 3 0.2620 0.6951 0.048 0.024 0.888 0.040 0.000 0.000
#> GSM1182251 5 0.1124 0.8253 0.036 0.000 0.000 0.000 0.956 0.008
#> GSM1182252 3 0.2990 0.6058 0.004 0.024 0.844 0.004 0.000 0.124
#> GSM1182253 3 0.2826 0.6229 0.000 0.024 0.856 0.008 0.000 0.112
#> GSM1182254 3 0.1966 0.6990 0.024 0.024 0.924 0.028 0.000 0.000
#> GSM1182255 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182256 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182257 4 0.5140 0.7526 0.040 0.000 0.016 0.680 0.224 0.040
#> GSM1182258 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182259 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182260 3 0.2550 0.6954 0.048 0.024 0.892 0.036 0.000 0.000
#> GSM1182261 3 0.4491 0.6139 0.044 0.024 0.780 0.100 0.000 0.052
#> GSM1182262 3 0.4287 0.6139 0.028 0.024 0.792 0.096 0.000 0.060
#> GSM1182263 5 0.3325 0.6964 0.036 0.000 0.000 0.092 0.840 0.032
#> GSM1182264 3 0.3249 0.6817 0.044 0.024 0.864 0.028 0.000 0.040
#> GSM1182265 3 0.3452 0.6642 0.116 0.024 0.824 0.036 0.000 0.000
#> GSM1182266 3 0.3103 0.6813 0.040 0.024 0.872 0.024 0.000 0.040
#> GSM1182267 4 0.6784 0.7239 0.048 0.000 0.000 0.416 0.284 0.252
#> GSM1182268 5 0.3482 0.8045 0.116 0.000 0.004 0.000 0.812 0.068
#> GSM1182269 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182270 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
#> GSM1182271 4 0.3192 0.7782 0.004 0.000 0.000 0.776 0.216 0.004
#> GSM1182272 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182273 3 0.3171 0.6813 0.044 0.024 0.868 0.024 0.000 0.040
#> GSM1182275 3 0.3803 0.6592 0.032 0.088 0.824 0.036 0.000 0.020
#> GSM1182276 2 0.0798 0.6449 0.004 0.976 0.004 0.012 0.000 0.004
#> GSM1182277 4 0.6734 0.7273 0.044 0.000 0.000 0.420 0.284 0.252
#> GSM1182278 4 0.6734 0.7273 0.044 0.000 0.000 0.420 0.284 0.252
#> GSM1182279 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182280 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182281 4 0.4838 0.7765 0.028 0.000 0.004 0.696 0.216 0.056
#> GSM1182282 4 0.6886 0.7274 0.048 0.000 0.004 0.420 0.284 0.244
#> GSM1182283 4 0.6734 0.7273 0.044 0.000 0.000 0.420 0.284 0.252
#> GSM1182284 4 0.6713 0.7312 0.044 0.000 0.000 0.428 0.280 0.248
#> GSM1182285 6 0.4315 0.9690 0.004 0.024 0.348 0.000 0.000 0.624
#> GSM1182286 2 0.5739 0.4769 0.108 0.668 0.020 0.152 0.000 0.052
#> GSM1182287 3 0.4882 0.2448 0.012 0.448 0.512 0.016 0.000 0.012
#> GSM1182288 3 0.2848 0.6089 0.000 0.024 0.848 0.004 0.000 0.124
#> GSM1182289 5 0.1124 0.8253 0.036 0.000 0.000 0.000 0.956 0.008
#> GSM1182290 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182291 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182274 3 0.2550 0.6954 0.048 0.024 0.892 0.036 0.000 0.000
#> GSM1182292 2 0.0837 0.6419 0.020 0.972 0.000 0.004 0.000 0.004
#> GSM1182293 1 0.3499 0.8613 0.680 0.320 0.000 0.000 0.000 0.000
#> GSM1182294 1 0.4116 0.8625 0.684 0.288 0.012 0.016 0.000 0.000
#> GSM1182295 2 0.4184 -0.2363 0.408 0.576 0.000 0.016 0.000 0.000
#> GSM1182296 2 0.0837 0.6419 0.020 0.972 0.000 0.004 0.000 0.004
#> GSM1182298 6 0.4185 0.9766 0.000 0.020 0.332 0.004 0.000 0.644
#> GSM1182299 2 0.5321 0.4824 0.156 0.700 0.080 0.048 0.000 0.016
#> GSM1182300 2 0.4264 -0.5256 0.484 0.500 0.000 0.016 0.000 0.000
#> GSM1182301 2 0.1225 0.6353 0.032 0.956 0.004 0.004 0.000 0.004
#> GSM1182303 2 0.0798 0.6449 0.004 0.976 0.004 0.012 0.000 0.004
#> GSM1182304 5 0.0972 0.8273 0.028 0.000 0.000 0.000 0.964 0.008
#> GSM1182305 5 0.3089 0.7252 0.040 0.000 0.000 0.080 0.856 0.024
#> GSM1182306 4 0.5432 0.3488 0.040 0.000 0.016 0.476 0.452 0.016
#> GSM1182307 2 0.1151 0.6386 0.032 0.956 0.000 0.012 0.000 0.000
#> GSM1182309 1 0.3464 0.8644 0.688 0.312 0.000 0.000 0.000 0.000
#> GSM1182312 1 0.5598 0.6617 0.572 0.288 0.000 0.124 0.000 0.016
#> GSM1182314 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182316 1 0.3482 0.8638 0.684 0.316 0.000 0.000 0.000 0.000
#> GSM1182318 1 0.4184 0.5325 0.504 0.484 0.000 0.012 0.000 0.000
#> GSM1182319 1 0.3855 0.8598 0.704 0.276 0.016 0.000 0.000 0.004
#> GSM1182320 1 0.3619 0.8645 0.680 0.316 0.000 0.000 0.000 0.004
#> GSM1182321 1 0.3875 0.8585 0.700 0.280 0.016 0.000 0.000 0.004
#> GSM1182322 1 0.3855 0.8598 0.704 0.276 0.016 0.000 0.000 0.004
#> GSM1182324 1 0.3855 0.8598 0.704 0.276 0.016 0.000 0.000 0.004
#> GSM1182297 2 0.6838 0.2997 0.216 0.540 0.032 0.156 0.000 0.056
#> GSM1182302 5 0.2728 0.8015 0.056 0.000 0.016 0.024 0.888 0.016
#> GSM1182308 2 0.1723 0.6339 0.036 0.928 0.000 0.036 0.000 0.000
#> GSM1182310 1 0.3855 0.8598 0.704 0.276 0.016 0.000 0.000 0.004
#> GSM1182311 5 0.3525 0.8027 0.120 0.000 0.004 0.000 0.808 0.068
#> GSM1182313 4 0.2912 0.7828 0.000 0.000 0.000 0.784 0.216 0.000
#> GSM1182315 1 0.5021 0.6465 0.536 0.408 0.000 0.032 0.000 0.024
#> GSM1182317 1 0.3482 0.8638 0.684 0.316 0.000 0.000 0.000 0.000
#> GSM1182323 5 0.3384 0.8045 0.120 0.000 0.000 0.000 0.812 0.068
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:kmeans 139 7.73e-02 1.000 2
#> MAD:kmeans 139 3.55e-07 0.393 3
#> MAD:kmeans 137 1.90e-06 0.419 4
#> MAD:kmeans 135 5.20e-07 0.421 5
#> MAD:kmeans 117 3.51e-11 0.315 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.994 0.997 0.4802 0.521 0.521
#> 3 3 1.000 0.991 0.997 0.3819 0.815 0.645
#> 4 4 1.000 0.960 0.974 0.1117 0.925 0.777
#> 5 5 0.842 0.790 0.860 0.0658 0.924 0.725
#> 6 6 0.809 0.714 0.845 0.0441 0.941 0.735
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1182186 1 0.000 1.000 1.000 0.000
#> GSM1182187 1 0.000 1.000 1.000 0.000
#> GSM1182188 1 0.000 1.000 1.000 0.000
#> GSM1182189 1 0.000 1.000 1.000 0.000
#> GSM1182190 1 0.000 1.000 1.000 0.000
#> GSM1182191 1 0.000 1.000 1.000 0.000
#> GSM1182192 1 0.000 1.000 1.000 0.000
#> GSM1182193 1 0.000 1.000 1.000 0.000
#> GSM1182194 2 0.000 0.996 0.000 1.000
#> GSM1182195 2 0.000 0.996 0.000 1.000
#> GSM1182196 2 0.000 0.996 0.000 1.000
#> GSM1182197 2 0.000 0.996 0.000 1.000
#> GSM1182198 2 0.722 0.753 0.200 0.800
#> GSM1182199 2 0.615 0.822 0.152 0.848
#> GSM1182200 2 0.000 0.996 0.000 1.000
#> GSM1182201 2 0.000 0.996 0.000 1.000
#> GSM1182202 1 0.000 1.000 1.000 0.000
#> GSM1182203 1 0.000 1.000 1.000 0.000
#> GSM1182204 1 0.000 1.000 1.000 0.000
#> GSM1182205 2 0.000 0.996 0.000 1.000
#> GSM1182206 2 0.000 0.996 0.000 1.000
#> GSM1182207 1 0.000 1.000 1.000 0.000
#> GSM1182208 1 0.000 1.000 1.000 0.000
#> GSM1182209 2 0.000 0.996 0.000 1.000
#> GSM1182210 2 0.000 0.996 0.000 1.000
#> GSM1182211 2 0.000 0.996 0.000 1.000
#> GSM1182212 2 0.000 0.996 0.000 1.000
#> GSM1182213 2 0.000 0.996 0.000 1.000
#> GSM1182214 2 0.000 0.996 0.000 1.000
#> GSM1182215 2 0.000 0.996 0.000 1.000
#> GSM1182216 2 0.000 0.996 0.000 1.000
#> GSM1182217 1 0.000 1.000 1.000 0.000
#> GSM1182218 1 0.000 1.000 1.000 0.000
#> GSM1182219 2 0.000 0.996 0.000 1.000
#> GSM1182220 2 0.000 0.996 0.000 1.000
#> GSM1182221 2 0.000 0.996 0.000 1.000
#> GSM1182222 2 0.000 0.996 0.000 1.000
#> GSM1182223 2 0.000 0.996 0.000 1.000
#> GSM1182224 2 0.000 0.996 0.000 1.000
#> GSM1182225 2 0.000 0.996 0.000 1.000
#> GSM1182226 2 0.000 0.996 0.000 1.000
#> GSM1182227 1 0.000 1.000 1.000 0.000
#> GSM1182228 2 0.000 0.996 0.000 1.000
#> GSM1182229 2 0.000 0.996 0.000 1.000
#> GSM1182230 2 0.000 0.996 0.000 1.000
#> GSM1182231 2 0.000 0.996 0.000 1.000
#> GSM1182232 1 0.000 1.000 1.000 0.000
#> GSM1182233 1 0.000 1.000 1.000 0.000
#> GSM1182234 1 0.000 1.000 1.000 0.000
#> GSM1182235 2 0.000 0.996 0.000 1.000
#> GSM1182236 1 0.000 1.000 1.000 0.000
#> GSM1182237 2 0.000 0.996 0.000 1.000
#> GSM1182238 2 0.000 0.996 0.000 1.000
#> GSM1182239 2 0.000 0.996 0.000 1.000
#> GSM1182240 2 0.000 0.996 0.000 1.000
#> GSM1182241 2 0.000 0.996 0.000 1.000
#> GSM1182242 2 0.000 0.996 0.000 1.000
#> GSM1182243 2 0.000 0.996 0.000 1.000
#> GSM1182244 2 0.000 0.996 0.000 1.000
#> GSM1182245 1 0.000 1.000 1.000 0.000
#> GSM1182246 1 0.000 1.000 1.000 0.000
#> GSM1182247 2 0.000 0.996 0.000 1.000
#> GSM1182248 2 0.000 0.996 0.000 1.000
#> GSM1182249 2 0.000 0.996 0.000 1.000
#> GSM1182250 2 0.000 0.996 0.000 1.000
#> GSM1182251 1 0.000 1.000 1.000 0.000
#> GSM1182252 2 0.000 0.996 0.000 1.000
#> GSM1182253 2 0.000 0.996 0.000 1.000
#> GSM1182254 2 0.000 0.996 0.000 1.000
#> GSM1182255 1 0.000 1.000 1.000 0.000
#> GSM1182256 1 0.000 1.000 1.000 0.000
#> GSM1182257 1 0.000 1.000 1.000 0.000
#> GSM1182258 1 0.000 1.000 1.000 0.000
#> GSM1182259 1 0.000 1.000 1.000 0.000
#> GSM1182260 2 0.000 0.996 0.000 1.000
#> GSM1182261 2 0.000 0.996 0.000 1.000
#> GSM1182262 2 0.000 0.996 0.000 1.000
#> GSM1182263 1 0.000 1.000 1.000 0.000
#> GSM1182264 2 0.000 0.996 0.000 1.000
#> GSM1182265 2 0.000 0.996 0.000 1.000
#> GSM1182266 2 0.000 0.996 0.000 1.000
#> GSM1182267 1 0.000 1.000 1.000 0.000
#> GSM1182268 1 0.000 1.000 1.000 0.000
#> GSM1182269 1 0.000 1.000 1.000 0.000
#> GSM1182270 1 0.000 1.000 1.000 0.000
#> GSM1182271 1 0.000 1.000 1.000 0.000
#> GSM1182272 1 0.000 1.000 1.000 0.000
#> GSM1182273 2 0.000 0.996 0.000 1.000
#> GSM1182275 2 0.000 0.996 0.000 1.000
#> GSM1182276 2 0.000 0.996 0.000 1.000
#> GSM1182277 1 0.000 1.000 1.000 0.000
#> GSM1182278 1 0.000 1.000 1.000 0.000
#> GSM1182279 1 0.000 1.000 1.000 0.000
#> GSM1182280 1 0.000 1.000 1.000 0.000
#> GSM1182281 1 0.000 1.000 1.000 0.000
#> GSM1182282 1 0.000 1.000 1.000 0.000
#> GSM1182283 1 0.000 1.000 1.000 0.000
#> GSM1182284 1 0.000 1.000 1.000 0.000
#> GSM1182285 2 0.000 0.996 0.000 1.000
#> GSM1182286 2 0.000 0.996 0.000 1.000
#> GSM1182287 2 0.000 0.996 0.000 1.000
#> GSM1182288 2 0.000 0.996 0.000 1.000
#> GSM1182289 1 0.000 1.000 1.000 0.000
#> GSM1182290 1 0.000 1.000 1.000 0.000
#> GSM1182291 1 0.000 1.000 1.000 0.000
#> GSM1182274 2 0.000 0.996 0.000 1.000
#> GSM1182292 2 0.000 0.996 0.000 1.000
#> GSM1182293 2 0.000 0.996 0.000 1.000
#> GSM1182294 2 0.000 0.996 0.000 1.000
#> GSM1182295 2 0.000 0.996 0.000 1.000
#> GSM1182296 2 0.000 0.996 0.000 1.000
#> GSM1182298 2 0.000 0.996 0.000 1.000
#> GSM1182299 2 0.000 0.996 0.000 1.000
#> GSM1182300 2 0.000 0.996 0.000 1.000
#> GSM1182301 2 0.000 0.996 0.000 1.000
#> GSM1182303 2 0.000 0.996 0.000 1.000
#> GSM1182304 1 0.000 1.000 1.000 0.000
#> GSM1182305 1 0.000 1.000 1.000 0.000
#> GSM1182306 1 0.000 1.000 1.000 0.000
#> GSM1182307 2 0.000 0.996 0.000 1.000
#> GSM1182309 2 0.000 0.996 0.000 1.000
#> GSM1182312 2 0.000 0.996 0.000 1.000
#> GSM1182314 1 0.000 1.000 1.000 0.000
#> GSM1182316 2 0.000 0.996 0.000 1.000
#> GSM1182318 2 0.000 0.996 0.000 1.000
#> GSM1182319 2 0.000 0.996 0.000 1.000
#> GSM1182320 2 0.000 0.996 0.000 1.000
#> GSM1182321 2 0.000 0.996 0.000 1.000
#> GSM1182322 2 0.000 0.996 0.000 1.000
#> GSM1182324 2 0.000 0.996 0.000 1.000
#> GSM1182297 2 0.000 0.996 0.000 1.000
#> GSM1182302 1 0.000 1.000 1.000 0.000
#> GSM1182308 2 0.000 0.996 0.000 1.000
#> GSM1182310 2 0.000 0.996 0.000 1.000
#> GSM1182311 1 0.000 1.000 1.000 0.000
#> GSM1182313 1 0.000 1.000 1.000 0.000
#> GSM1182315 2 0.000 0.996 0.000 1.000
#> GSM1182317 2 0.000 0.996 0.000 1.000
#> GSM1182323 1 0.000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 1.000 1 0.000 0.000
#> GSM1182187 1 0.0000 1.000 1 0.000 0.000
#> GSM1182188 1 0.0000 1.000 1 0.000 0.000
#> GSM1182189 1 0.0000 1.000 1 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1 0.000 0.000
#> GSM1182191 1 0.0000 1.000 1 0.000 0.000
#> GSM1182192 1 0.0000 1.000 1 0.000 0.000
#> GSM1182193 1 0.0000 1.000 1 0.000 0.000
#> GSM1182194 3 0.0000 0.987 0 0.000 1.000
#> GSM1182195 3 0.0000 0.987 0 0.000 1.000
#> GSM1182196 2 0.0000 1.000 0 1.000 0.000
#> GSM1182197 2 0.0000 1.000 0 1.000 0.000
#> GSM1182198 3 0.0000 0.987 0 0.000 1.000
#> GSM1182199 3 0.0000 0.987 0 0.000 1.000
#> GSM1182200 2 0.0000 1.000 0 1.000 0.000
#> GSM1182201 3 0.0424 0.980 0 0.008 0.992
#> GSM1182202 1 0.0000 1.000 1 0.000 0.000
#> GSM1182203 1 0.0000 1.000 1 0.000 0.000
#> GSM1182204 1 0.0000 1.000 1 0.000 0.000
#> GSM1182205 3 0.0000 0.987 0 0.000 1.000
#> GSM1182206 3 0.0000 0.987 0 0.000 1.000
#> GSM1182207 1 0.0000 1.000 1 0.000 0.000
#> GSM1182208 1 0.0000 1.000 1 0.000 0.000
#> GSM1182209 2 0.0000 1.000 0 1.000 0.000
#> GSM1182210 2 0.0000 1.000 0 1.000 0.000
#> GSM1182211 2 0.0000 1.000 0 1.000 0.000
#> GSM1182212 2 0.0000 1.000 0 1.000 0.000
#> GSM1182213 2 0.0000 1.000 0 1.000 0.000
#> GSM1182214 2 0.0000 1.000 0 1.000 0.000
#> GSM1182215 3 0.0000 0.987 0 0.000 1.000
#> GSM1182216 2 0.0000 1.000 0 1.000 0.000
#> GSM1182217 1 0.0000 1.000 1 0.000 0.000
#> GSM1182218 1 0.0000 1.000 1 0.000 0.000
#> GSM1182219 2 0.0000 1.000 0 1.000 0.000
#> GSM1182220 2 0.0000 1.000 0 1.000 0.000
#> GSM1182221 2 0.0000 1.000 0 1.000 0.000
#> GSM1182222 2 0.0000 1.000 0 1.000 0.000
#> GSM1182223 3 0.0000 0.987 0 0.000 1.000
#> GSM1182224 3 0.0000 0.987 0 0.000 1.000
#> GSM1182225 2 0.0000 1.000 0 1.000 0.000
#> GSM1182226 2 0.0000 1.000 0 1.000 0.000
#> GSM1182227 1 0.0000 1.000 1 0.000 0.000
#> GSM1182228 3 0.0000 0.987 0 0.000 1.000
#> GSM1182229 3 0.0000 0.987 0 0.000 1.000
#> GSM1182230 3 0.0000 0.987 0 0.000 1.000
#> GSM1182231 2 0.0000 1.000 0 1.000 0.000
#> GSM1182232 1 0.0000 1.000 1 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1 0.000 0.000
#> GSM1182235 2 0.0000 1.000 0 1.000 0.000
#> GSM1182236 1 0.0000 1.000 1 0.000 0.000
#> GSM1182237 3 0.0000 0.987 0 0.000 1.000
#> GSM1182238 2 0.0000 1.000 0 1.000 0.000
#> GSM1182239 2 0.0000 1.000 0 1.000 0.000
#> GSM1182240 2 0.0000 1.000 0 1.000 0.000
#> GSM1182241 2 0.0000 1.000 0 1.000 0.000
#> GSM1182242 3 0.0000 0.987 0 0.000 1.000
#> GSM1182243 3 0.0000 0.987 0 0.000 1.000
#> GSM1182244 3 0.0000 0.987 0 0.000 1.000
#> GSM1182245 1 0.0000 1.000 1 0.000 0.000
#> GSM1182246 1 0.0000 1.000 1 0.000 0.000
#> GSM1182247 3 0.0000 0.987 0 0.000 1.000
#> GSM1182248 3 0.0000 0.987 0 0.000 1.000
#> GSM1182249 3 0.6225 0.241 0 0.432 0.568
#> GSM1182250 3 0.0000 0.987 0 0.000 1.000
#> GSM1182251 1 0.0000 1.000 1 0.000 0.000
#> GSM1182252 3 0.0000 0.987 0 0.000 1.000
#> GSM1182253 3 0.0000 0.987 0 0.000 1.000
#> GSM1182254 3 0.0000 0.987 0 0.000 1.000
#> GSM1182255 1 0.0000 1.000 1 0.000 0.000
#> GSM1182256 1 0.0000 1.000 1 0.000 0.000
#> GSM1182257 1 0.0000 1.000 1 0.000 0.000
#> GSM1182258 1 0.0000 1.000 1 0.000 0.000
#> GSM1182259 1 0.0000 1.000 1 0.000 0.000
#> GSM1182260 3 0.0000 0.987 0 0.000 1.000
#> GSM1182261 3 0.0000 0.987 0 0.000 1.000
#> GSM1182262 3 0.0000 0.987 0 0.000 1.000
#> GSM1182263 1 0.0000 1.000 1 0.000 0.000
#> GSM1182264 3 0.0000 0.987 0 0.000 1.000
#> GSM1182265 3 0.0000 0.987 0 0.000 1.000
#> GSM1182266 3 0.0000 0.987 0 0.000 1.000
#> GSM1182267 1 0.0000 1.000 1 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1 0.000 0.000
#> GSM1182271 1 0.0000 1.000 1 0.000 0.000
#> GSM1182272 1 0.0000 1.000 1 0.000 0.000
#> GSM1182273 3 0.0000 0.987 0 0.000 1.000
#> GSM1182275 3 0.0000 0.987 0 0.000 1.000
#> GSM1182276 2 0.0000 1.000 0 1.000 0.000
#> GSM1182277 1 0.0000 1.000 1 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1 0.000 0.000
#> GSM1182279 1 0.0000 1.000 1 0.000 0.000
#> GSM1182280 1 0.0000 1.000 1 0.000 0.000
#> GSM1182281 1 0.0000 1.000 1 0.000 0.000
#> GSM1182282 1 0.0000 1.000 1 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1 0.000 0.000
#> GSM1182285 3 0.0000 0.987 0 0.000 1.000
#> GSM1182286 2 0.0000 1.000 0 1.000 0.000
#> GSM1182287 3 0.0592 0.977 0 0.012 0.988
#> GSM1182288 3 0.0000 0.987 0 0.000 1.000
#> GSM1182289 1 0.0000 1.000 1 0.000 0.000
#> GSM1182290 1 0.0000 1.000 1 0.000 0.000
#> GSM1182291 1 0.0000 1.000 1 0.000 0.000
#> GSM1182274 3 0.0000 0.987 0 0.000 1.000
#> GSM1182292 2 0.0000 1.000 0 1.000 0.000
#> GSM1182293 2 0.0000 1.000 0 1.000 0.000
#> GSM1182294 2 0.0000 1.000 0 1.000 0.000
#> GSM1182295 2 0.0000 1.000 0 1.000 0.000
#> GSM1182296 2 0.0000 1.000 0 1.000 0.000
#> GSM1182298 3 0.0000 0.987 0 0.000 1.000
#> GSM1182299 2 0.0000 1.000 0 1.000 0.000
#> GSM1182300 2 0.0000 1.000 0 1.000 0.000
#> GSM1182301 2 0.0000 1.000 0 1.000 0.000
#> GSM1182303 2 0.0000 1.000 0 1.000 0.000
#> GSM1182304 1 0.0000 1.000 1 0.000 0.000
#> GSM1182305 1 0.0000 1.000 1 0.000 0.000
#> GSM1182306 1 0.0000 1.000 1 0.000 0.000
#> GSM1182307 2 0.0000 1.000 0 1.000 0.000
#> GSM1182309 2 0.0000 1.000 0 1.000 0.000
#> GSM1182312 2 0.0000 1.000 0 1.000 0.000
#> GSM1182314 1 0.0000 1.000 1 0.000 0.000
#> GSM1182316 2 0.0000 1.000 0 1.000 0.000
#> GSM1182318 2 0.0000 1.000 0 1.000 0.000
#> GSM1182319 2 0.0000 1.000 0 1.000 0.000
#> GSM1182320 2 0.0000 1.000 0 1.000 0.000
#> GSM1182321 2 0.0000 1.000 0 1.000 0.000
#> GSM1182322 2 0.0000 1.000 0 1.000 0.000
#> GSM1182324 2 0.0000 1.000 0 1.000 0.000
#> GSM1182297 2 0.0000 1.000 0 1.000 0.000
#> GSM1182302 1 0.0000 1.000 1 0.000 0.000
#> GSM1182308 2 0.0000 1.000 0 1.000 0.000
#> GSM1182310 2 0.0000 1.000 0 1.000 0.000
#> GSM1182311 1 0.0000 1.000 1 0.000 0.000
#> GSM1182313 1 0.0000 1.000 1 0.000 0.000
#> GSM1182315 2 0.0000 1.000 0 1.000 0.000
#> GSM1182317 2 0.0000 1.000 0 1.000 0.000
#> GSM1182323 1 0.0000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182187 1 0.4564 0.549 0.672 0.000 0.000 0.328
#> GSM1182188 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182189 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182191 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182192 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182193 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182194 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182195 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182196 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182197 2 0.0804 0.983 0.000 0.980 0.012 0.008
#> GSM1182198 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182199 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182200 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182201 3 0.1256 0.953 0.000 0.028 0.964 0.008
#> GSM1182202 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182203 1 0.4564 0.549 0.672 0.000 0.000 0.328
#> GSM1182204 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182205 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182206 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182207 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182209 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182210 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182211 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182212 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182213 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182214 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182215 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182216 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182217 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182218 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182219 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182220 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182221 2 0.0469 0.988 0.000 0.988 0.000 0.012
#> GSM1182222 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182223 3 0.1042 0.960 0.000 0.020 0.972 0.008
#> GSM1182224 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182225 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182226 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182227 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182228 3 0.1042 0.960 0.000 0.020 0.972 0.008
#> GSM1182229 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182230 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182231 2 0.0336 0.988 0.000 0.992 0.008 0.000
#> GSM1182232 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182234 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182235 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182236 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182237 3 0.0336 0.975 0.000 0.008 0.992 0.000
#> GSM1182238 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182239 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182240 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182241 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182242 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182243 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182244 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182245 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182246 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182247 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182248 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182249 3 0.4933 0.235 0.000 0.432 0.568 0.000
#> GSM1182250 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182251 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182252 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182253 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182254 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182255 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182256 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182257 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182258 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182259 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182260 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182261 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182262 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182263 1 0.4382 0.607 0.704 0.000 0.000 0.296
#> GSM1182264 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182265 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182266 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182267 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182268 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182272 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182273 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182275 3 0.0336 0.975 0.000 0.000 0.992 0.008
#> GSM1182276 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182277 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182278 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182279 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182280 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182281 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182282 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182283 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182284 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182285 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182286 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182287 3 0.1356 0.949 0.000 0.032 0.960 0.008
#> GSM1182288 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182289 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182290 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182291 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182274 3 0.0000 0.979 0.000 0.000 1.000 0.000
#> GSM1182292 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182293 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182294 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182295 2 0.0188 0.990 0.000 0.996 0.000 0.004
#> GSM1182296 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182298 3 0.0469 0.976 0.000 0.000 0.988 0.012
#> GSM1182299 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182300 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182301 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182303 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182304 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182305 1 0.3528 0.757 0.808 0.000 0.000 0.192
#> GSM1182306 1 0.4564 0.549 0.672 0.000 0.000 0.328
#> GSM1182307 2 0.0336 0.991 0.000 0.992 0.000 0.008
#> GSM1182309 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182312 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182314 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182316 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182318 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182319 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182320 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182321 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182322 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182324 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182297 2 0.0000 0.991 0.000 1.000 0.000 0.000
#> GSM1182302 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182308 2 0.0188 0.991 0.000 0.996 0.000 0.004
#> GSM1182310 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182311 1 0.0000 0.946 1.000 0.000 0.000 0.000
#> GSM1182313 4 0.1211 1.000 0.040 0.000 0.000 0.960
#> GSM1182315 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182317 2 0.0707 0.986 0.000 0.980 0.000 0.020
#> GSM1182323 1 0.0000 0.946 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
#> GSM1182186 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182187 1 0.4192 0.417 0.596 0.000 0.000 0.404 0.000
#> GSM1182188 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182192 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182193 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182194 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182195 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182196 2 0.2377 0.619 0.000 0.872 0.000 0.000 0.128
#> GSM1182197 2 0.4787 0.371 0.000 0.640 0.324 0.000 0.036
#> GSM1182198 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182199 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182200 2 0.0955 0.687 0.000 0.968 0.028 0.000 0.004
#> GSM1182201 2 0.4808 0.354 0.000 0.620 0.348 0.000 0.032
#> GSM1182202 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182203 1 0.4192 0.417 0.596 0.000 0.000 0.404 0.000
#> GSM1182204 1 0.0609 0.926 0.980 0.000 0.000 0.020 0.000
#> GSM1182205 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182206 3 0.1168 0.884 0.000 0.008 0.960 0.000 0.032
#> GSM1182207 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182209 2 0.1043 0.699 0.000 0.960 0.000 0.000 0.040
#> GSM1182210 2 0.1270 0.696 0.000 0.948 0.000 0.000 0.052
#> GSM1182211 2 0.1043 0.699 0.000 0.960 0.000 0.000 0.040
#> GSM1182212 2 0.0162 0.705 0.000 0.996 0.000 0.000 0.004
#> GSM1182213 2 0.0000 0.706 0.000 1.000 0.000 0.000 0.000
#> GSM1182214 2 0.1341 0.698 0.000 0.944 0.000 0.000 0.056
#> GSM1182215 3 0.1197 0.883 0.000 0.000 0.952 0.000 0.048
#> GSM1182216 2 0.2852 0.576 0.000 0.828 0.000 0.000 0.172
#> GSM1182217 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182218 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.1792 0.677 0.000 0.916 0.000 0.000 0.084
#> GSM1182220 2 0.0000 0.706 0.000 1.000 0.000 0.000 0.000
#> GSM1182221 2 0.4283 -0.538 0.000 0.544 0.000 0.000 0.456
#> GSM1182222 2 0.2852 0.576 0.000 0.828 0.000 0.000 0.172
#> GSM1182223 2 0.4455 0.277 0.000 0.588 0.404 0.000 0.008
#> GSM1182224 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182225 2 0.2852 0.576 0.000 0.828 0.000 0.000 0.172
#> GSM1182226 2 0.3242 0.483 0.000 0.784 0.000 0.000 0.216
#> GSM1182227 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182228 2 0.4403 0.325 0.000 0.608 0.384 0.000 0.008
#> GSM1182229 3 0.0000 0.884 0.000 0.000 1.000 0.000 0.000
#> GSM1182230 3 0.1043 0.884 0.000 0.000 0.960 0.000 0.040
#> GSM1182231 2 0.5074 0.491 0.000 0.700 0.132 0.000 0.168
#> GSM1182232 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182234 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182235 2 0.2852 0.576 0.000 0.828 0.000 0.000 0.172
#> GSM1182236 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.3550 0.757 0.000 0.020 0.796 0.000 0.184
#> GSM1182238 2 0.2929 0.562 0.000 0.820 0.000 0.000 0.180
#> GSM1182239 2 0.2074 0.657 0.000 0.896 0.000 0.000 0.104
#> GSM1182240 2 0.0162 0.706 0.000 0.996 0.000 0.000 0.004
#> GSM1182241 2 0.0290 0.704 0.000 0.992 0.000 0.000 0.008
#> GSM1182242 3 0.0290 0.884 0.000 0.000 0.992 0.000 0.008
#> GSM1182243 3 0.1124 0.879 0.000 0.004 0.960 0.000 0.036
#> GSM1182244 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182245 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182246 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.0162 0.885 0.000 0.000 0.996 0.000 0.004
#> GSM1182248 3 0.0404 0.885 0.000 0.000 0.988 0.000 0.012
#> GSM1182249 3 0.4594 0.599 0.000 0.036 0.680 0.000 0.284
#> GSM1182250 3 0.0880 0.881 0.000 0.000 0.968 0.000 0.032
#> GSM1182251 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182252 3 0.0794 0.884 0.000 0.000 0.972 0.000 0.028
#> GSM1182253 3 0.1043 0.883 0.000 0.000 0.960 0.000 0.040
#> GSM1182254 3 0.1041 0.880 0.000 0.004 0.964 0.000 0.032
#> GSM1182255 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.1124 0.879 0.000 0.004 0.960 0.000 0.036
#> GSM1182261 3 0.1082 0.880 0.000 0.008 0.964 0.000 0.028
#> GSM1182262 3 0.1124 0.884 0.000 0.004 0.960 0.000 0.036
#> GSM1182263 1 0.3774 0.612 0.704 0.000 0.000 0.296 0.000
#> GSM1182264 3 0.0794 0.883 0.000 0.000 0.972 0.000 0.028
#> GSM1182265 3 0.2773 0.794 0.000 0.000 0.836 0.000 0.164
#> GSM1182266 3 0.0880 0.882 0.000 0.000 0.968 0.000 0.032
#> GSM1182267 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182268 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 3 0.0880 0.883 0.000 0.000 0.968 0.000 0.032
#> GSM1182275 3 0.2536 0.793 0.000 0.128 0.868 0.000 0.004
#> GSM1182276 2 0.0290 0.706 0.000 0.992 0.000 0.000 0.008
#> GSM1182277 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182278 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182279 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182280 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182281 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182282 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182283 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182284 4 0.0703 0.990 0.000 0.000 0.000 0.976 0.024
#> GSM1182285 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182286 2 0.1478 0.692 0.000 0.936 0.000 0.000 0.064
#> GSM1182287 2 0.4380 0.342 0.000 0.616 0.376 0.000 0.008
#> GSM1182288 3 0.0510 0.885 0.000 0.000 0.984 0.000 0.016
#> GSM1182289 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182290 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 3 0.1124 0.879 0.000 0.004 0.960 0.000 0.036
#> GSM1182292 2 0.0963 0.699 0.000 0.964 0.000 0.000 0.036
#> GSM1182293 5 0.4138 0.978 0.000 0.384 0.000 0.000 0.616
#> GSM1182294 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182295 2 0.3508 0.385 0.000 0.748 0.000 0.000 0.252
#> GSM1182296 2 0.1043 0.699 0.000 0.960 0.000 0.000 0.040
#> GSM1182298 3 0.3913 0.772 0.000 0.000 0.676 0.000 0.324
#> GSM1182299 2 0.0000 0.706 0.000 1.000 0.000 0.000 0.000
#> GSM1182300 2 0.4291 -0.603 0.000 0.536 0.000 0.000 0.464
#> GSM1182301 2 0.1121 0.695 0.000 0.956 0.000 0.000 0.044
#> GSM1182303 2 0.0290 0.706 0.000 0.992 0.000 0.000 0.008
#> GSM1182304 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182305 1 0.3039 0.757 0.808 0.000 0.000 0.192 0.000
#> GSM1182306 1 0.4210 0.398 0.588 0.000 0.000 0.412 0.000
#> GSM1182307 2 0.2074 0.653 0.000 0.896 0.000 0.000 0.104
#> GSM1182309 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182312 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182314 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182318 2 0.4307 -0.704 0.000 0.504 0.000 0.000 0.496
#> GSM1182319 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182320 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182321 5 0.4138 0.978 0.000 0.384 0.000 0.000 0.616
#> GSM1182322 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182324 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182297 2 0.2732 0.585 0.000 0.840 0.000 0.000 0.160
#> GSM1182302 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182308 2 0.1792 0.677 0.000 0.916 0.000 0.000 0.084
#> GSM1182310 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182311 1 0.0000 0.939 1.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.990 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 5 0.4291 0.794 0.000 0.464 0.000 0.000 0.536
#> GSM1182317 5 0.4126 0.984 0.000 0.380 0.000 0.000 0.620
#> GSM1182323 1 0.0000 0.939 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
#> GSM1182186 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182187 5 0.4103 0.2985 0.004 0.000 0.000 0.448 0.544 0.004
#> GSM1182188 4 0.0146 0.9673 0.004 0.000 0.000 0.996 0.000 0.000
#> GSM1182189 5 0.1176 0.9068 0.020 0.000 0.000 0.000 0.956 0.024
#> GSM1182190 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182191 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182192 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182193 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182194 6 0.1501 0.7174 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1182195 6 0.1501 0.7174 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1182196 2 0.2489 0.7241 0.128 0.860 0.012 0.000 0.000 0.000
#> GSM1182197 3 0.3695 0.4506 0.024 0.244 0.732 0.000 0.000 0.000
#> GSM1182198 6 0.1501 0.7174 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1182199 6 0.1501 0.7174 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1182200 2 0.0909 0.7397 0.020 0.968 0.012 0.000 0.000 0.000
#> GSM1182201 2 0.4453 -0.0198 0.032 0.568 0.400 0.000 0.000 0.000
#> GSM1182202 5 0.0291 0.9119 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM1182203 5 0.4082 0.3405 0.004 0.000 0.000 0.432 0.560 0.004
#> GSM1182204 5 0.1615 0.8744 0.004 0.000 0.000 0.064 0.928 0.004
#> GSM1182205 6 0.2092 0.7037 0.000 0.000 0.124 0.000 0.000 0.876
#> GSM1182206 3 0.3917 0.4734 0.024 0.008 0.728 0.000 0.000 0.240
#> GSM1182207 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182208 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182209 2 0.1327 0.7555 0.064 0.936 0.000 0.000 0.000 0.000
#> GSM1182210 2 0.1444 0.7533 0.072 0.928 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.1327 0.7555 0.064 0.936 0.000 0.000 0.000 0.000
#> GSM1182212 2 0.0291 0.7535 0.004 0.992 0.004 0.000 0.000 0.000
#> GSM1182213 2 0.0363 0.7599 0.012 0.988 0.000 0.000 0.000 0.000
#> GSM1182214 2 0.2282 0.7473 0.088 0.888 0.024 0.000 0.000 0.000
#> GSM1182215 3 0.3799 0.4316 0.020 0.000 0.704 0.000 0.000 0.276
#> GSM1182216 2 0.5643 0.4717 0.216 0.536 0.248 0.000 0.000 0.000
#> GSM1182217 5 0.0291 0.9119 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM1182218 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182219 2 0.3921 0.6878 0.116 0.768 0.116 0.000 0.000 0.000
#> GSM1182220 2 0.0806 0.7628 0.020 0.972 0.008 0.000 0.000 0.000
#> GSM1182221 1 0.5089 0.5253 0.620 0.244 0.136 0.000 0.000 0.000
#> GSM1182222 2 0.5643 0.4717 0.216 0.536 0.248 0.000 0.000 0.000
#> GSM1182223 3 0.4859 0.2480 0.016 0.452 0.504 0.000 0.000 0.028
#> GSM1182224 6 0.1610 0.7177 0.000 0.000 0.084 0.000 0.000 0.916
#> GSM1182225 2 0.5351 0.5344 0.200 0.592 0.208 0.000 0.000 0.000
#> GSM1182226 2 0.5737 0.4366 0.236 0.516 0.248 0.000 0.000 0.000
#> GSM1182227 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182228 3 0.4490 0.1634 0.016 0.472 0.504 0.000 0.000 0.008
#> GSM1182229 3 0.3368 0.4616 0.012 0.000 0.756 0.000 0.000 0.232
#> GSM1182230 3 0.3922 0.3637 0.016 0.000 0.664 0.000 0.000 0.320
#> GSM1182231 2 0.5779 0.3756 0.180 0.452 0.368 0.000 0.000 0.000
#> GSM1182232 5 0.0603 0.9112 0.004 0.000 0.000 0.000 0.980 0.016
#> GSM1182233 5 0.0717 0.9108 0.008 0.000 0.000 0.000 0.976 0.016
#> GSM1182234 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182235 2 0.5561 0.4926 0.204 0.552 0.244 0.000 0.000 0.000
#> GSM1182236 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182237 3 0.4853 0.4617 0.152 0.016 0.700 0.000 0.000 0.132
#> GSM1182238 2 0.5643 0.4717 0.216 0.536 0.248 0.000 0.000 0.000
#> GSM1182239 2 0.4459 0.6440 0.132 0.712 0.156 0.000 0.000 0.000
#> GSM1182240 2 0.0363 0.7601 0.012 0.988 0.000 0.000 0.000 0.000
#> GSM1182241 2 0.0291 0.7576 0.004 0.992 0.004 0.000 0.000 0.000
#> GSM1182242 6 0.4493 0.2633 0.016 0.008 0.488 0.000 0.000 0.488
#> GSM1182243 3 0.1219 0.6261 0.004 0.000 0.948 0.000 0.000 0.048
#> GSM1182244 6 0.1910 0.7099 0.000 0.000 0.108 0.000 0.000 0.892
#> GSM1182245 4 0.1480 0.9692 0.020 0.000 0.000 0.940 0.000 0.040
#> GSM1182246 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 6 0.4264 0.2850 0.016 0.000 0.488 0.000 0.000 0.496
#> GSM1182248 6 0.4264 0.2926 0.016 0.000 0.484 0.000 0.000 0.500
#> GSM1182249 3 0.2656 0.5739 0.120 0.012 0.860 0.000 0.000 0.008
#> GSM1182250 3 0.1524 0.6241 0.008 0.000 0.932 0.000 0.000 0.060
#> GSM1182251 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 6 0.4096 0.2890 0.008 0.000 0.484 0.000 0.000 0.508
#> GSM1182253 6 0.4192 0.3965 0.016 0.000 0.412 0.000 0.000 0.572
#> GSM1182254 3 0.2255 0.6080 0.016 0.004 0.892 0.000 0.000 0.088
#> GSM1182255 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.0436 0.9627 0.004 0.000 0.000 0.988 0.004 0.004
#> GSM1182258 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 3 0.1549 0.6251 0.020 0.000 0.936 0.000 0.000 0.044
#> GSM1182261 3 0.1074 0.6208 0.012 0.000 0.960 0.000 0.000 0.028
#> GSM1182262 3 0.3608 0.4394 0.012 0.000 0.716 0.000 0.000 0.272
#> GSM1182263 5 0.3351 0.6073 0.000 0.000 0.000 0.288 0.712 0.000
#> GSM1182264 3 0.3756 0.3494 0.020 0.000 0.712 0.000 0.000 0.268
#> GSM1182265 3 0.3572 0.5154 0.204 0.000 0.764 0.000 0.000 0.032
#> GSM1182266 3 0.4094 0.3395 0.032 0.004 0.700 0.000 0.000 0.264
#> GSM1182267 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182268 5 0.1092 0.9078 0.020 0.000 0.000 0.000 0.960 0.020
#> GSM1182269 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182270 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182271 4 0.0146 0.9673 0.004 0.000 0.000 0.996 0.000 0.000
#> GSM1182272 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 3 0.3879 0.3038 0.020 0.000 0.688 0.000 0.000 0.292
#> GSM1182275 3 0.6449 0.1032 0.024 0.252 0.440 0.000 0.000 0.284
#> GSM1182276 2 0.0291 0.7535 0.004 0.992 0.004 0.000 0.000 0.000
#> GSM1182277 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182278 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182279 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182280 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182281 4 0.1564 0.9690 0.024 0.000 0.000 0.936 0.000 0.040
#> GSM1182282 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182283 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182284 4 0.1633 0.9686 0.024 0.000 0.000 0.932 0.000 0.044
#> GSM1182285 6 0.1610 0.7177 0.000 0.000 0.084 0.000 0.000 0.916
#> GSM1182286 2 0.3787 0.6988 0.120 0.780 0.100 0.000 0.000 0.000
#> GSM1182287 2 0.4090 0.2231 0.016 0.652 0.328 0.000 0.000 0.004
#> GSM1182288 6 0.4260 0.3155 0.016 0.000 0.472 0.000 0.000 0.512
#> GSM1182289 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182290 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182291 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.1682 0.6237 0.020 0.000 0.928 0.000 0.000 0.052
#> GSM1182292 2 0.0547 0.7582 0.020 0.980 0.000 0.000 0.000 0.000
#> GSM1182293 1 0.1910 0.8855 0.892 0.108 0.000 0.000 0.000 0.000
#> GSM1182294 1 0.2446 0.8720 0.864 0.124 0.012 0.000 0.000 0.000
#> GSM1182295 2 0.3833 0.4295 0.344 0.648 0.008 0.000 0.000 0.000
#> GSM1182296 2 0.1387 0.7538 0.068 0.932 0.000 0.000 0.000 0.000
#> GSM1182298 6 0.1501 0.7174 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1182299 2 0.0717 0.7626 0.016 0.976 0.008 0.000 0.000 0.000
#> GSM1182300 1 0.3838 0.2969 0.552 0.448 0.000 0.000 0.000 0.000
#> GSM1182301 2 0.1267 0.7482 0.060 0.940 0.000 0.000 0.000 0.000
#> GSM1182303 2 0.0291 0.7535 0.004 0.992 0.004 0.000 0.000 0.000
#> GSM1182304 5 0.0000 0.9128 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182305 5 0.2527 0.7741 0.000 0.000 0.000 0.168 0.832 0.000
#> GSM1182306 5 0.4128 0.1602 0.004 0.000 0.000 0.492 0.500 0.004
#> GSM1182307 2 0.2003 0.7303 0.116 0.884 0.000 0.000 0.000 0.000
#> GSM1182309 1 0.1765 0.8868 0.904 0.096 0.000 0.000 0.000 0.000
#> GSM1182312 1 0.2230 0.8700 0.892 0.084 0.024 0.000 0.000 0.000
#> GSM1182314 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 1 0.2092 0.8789 0.876 0.124 0.000 0.000 0.000 0.000
#> GSM1182318 1 0.3756 0.5629 0.644 0.352 0.004 0.000 0.000 0.000
#> GSM1182319 1 0.1714 0.8860 0.908 0.092 0.000 0.000 0.000 0.000
#> GSM1182320 1 0.1765 0.8856 0.904 0.096 0.000 0.000 0.000 0.000
#> GSM1182321 1 0.1765 0.8856 0.904 0.096 0.000 0.000 0.000 0.000
#> GSM1182322 1 0.1714 0.8860 0.908 0.092 0.000 0.000 0.000 0.000
#> GSM1182324 1 0.1714 0.8860 0.908 0.092 0.000 0.000 0.000 0.000
#> GSM1182297 2 0.4752 0.6072 0.184 0.676 0.140 0.000 0.000 0.000
#> GSM1182302 5 0.0291 0.9119 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM1182308 2 0.2450 0.7280 0.116 0.868 0.016 0.000 0.000 0.000
#> GSM1182310 1 0.1714 0.8860 0.908 0.092 0.000 0.000 0.000 0.000
#> GSM1182311 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
#> GSM1182313 4 0.0000 0.9690 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 1 0.3710 0.6567 0.696 0.292 0.012 0.000 0.000 0.000
#> GSM1182317 1 0.2003 0.8827 0.884 0.116 0.000 0.000 0.000 0.000
#> GSM1182323 5 0.1334 0.9056 0.020 0.000 0.000 0.000 0.948 0.032
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:skmeans 139 7.73e-02 1.000 2
#> MAD:skmeans 138 4.45e-07 0.409 3
#> MAD:skmeans 138 1.23e-06 0.482 4
#> MAD:skmeans 125 4.48e-11 0.200 5
#> MAD:skmeans 107 5.23e-08 0.561 6
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 46361 rows and 139 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 0.997 0.999 0.4796 0.521 0.521
#> 3 3 0.713 0.806 0.846 0.2924 0.834 0.681
#> 4 4 0.858 0.885 0.949 0.1699 0.882 0.686
#> 5 5 0.839 0.880 0.929 0.0501 0.961 0.860
#> 6 6 0.784 0.676 0.828 0.0585 0.907 0.643
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
#> GSM1182186 1 0.000 1.000 1.000 0.000
#> GSM1182187 1 0.000 1.000 1.000 0.000
#> GSM1182188 1 0.000 1.000 1.000 0.000
#> GSM1182189 1 0.000 1.000 1.000 0.000
#> GSM1182190 1 0.000 1.000 1.000 0.000
#> GSM1182191 1 0.000 1.000 1.000 0.000
#> GSM1182192 1 0.000 1.000 1.000 0.000
#> GSM1182193 1 0.000 1.000 1.000 0.000
#> GSM1182194 2 0.000 0.998 0.000 1.000
#> GSM1182195 2 0.000 0.998 0.000 1.000
#> GSM1182196 2 0.000 0.998 0.000 1.000
#> GSM1182197 2 0.000 0.998 0.000 1.000
#> GSM1182198 2 0.541 0.860 0.124 0.876
#> GSM1182199 2 0.224 0.962 0.036 0.964
#> GSM1182200 2 0.000 0.998 0.000 1.000
#> GSM1182201 2 0.000 0.998 0.000 1.000
#> GSM1182202 1 0.000 1.000 1.000 0.000
#> GSM1182203 1 0.000 1.000 1.000 0.000
#> GSM1182204 1 0.000 1.000 1.000 0.000
#> GSM1182205 2 0.000 0.998 0.000 1.000
#> GSM1182206 2 0.000 0.998 0.000 1.000
#> GSM1182207 1 0.000 1.000 1.000 0.000
#> GSM1182208 1 0.000 1.000 1.000 0.000
#> GSM1182209 2 0.000 0.998 0.000 1.000
#> GSM1182210 2 0.000 0.998 0.000 1.000
#> GSM1182211 2 0.000 0.998 0.000 1.000
#> GSM1182212 2 0.000 0.998 0.000 1.000
#> GSM1182213 2 0.000 0.998 0.000 1.000
#> GSM1182214 2 0.000 0.998 0.000 1.000
#> GSM1182215 2 0.000 0.998 0.000 1.000
#> GSM1182216 2 0.000 0.998 0.000 1.000
#> GSM1182217 1 0.000 1.000 1.000 0.000
#> GSM1182218 1 0.000 1.000 1.000 0.000
#> GSM1182219 2 0.000 0.998 0.000 1.000
#> GSM1182220 2 0.000 0.998 0.000 1.000
#> GSM1182221 2 0.000 0.998 0.000 1.000
#> GSM1182222 2 0.000 0.998 0.000 1.000
#> GSM1182223 2 0.000 0.998 0.000 1.000
#> GSM1182224 2 0.000 0.998 0.000 1.000
#> GSM1182225 2 0.000 0.998 0.000 1.000
#> GSM1182226 2 0.000 0.998 0.000 1.000
#> GSM1182227 1 0.000 1.000 1.000 0.000
#> GSM1182228 2 0.000 0.998 0.000 1.000
#> GSM1182229 2 0.000 0.998 0.000 1.000
#> GSM1182230 2 0.000 0.998 0.000 1.000
#> GSM1182231 2 0.000 0.998 0.000 1.000
#> GSM1182232 1 0.000 1.000 1.000 0.000
#> GSM1182233 1 0.000 1.000 1.000 0.000
#> GSM1182234 1 0.000 1.000 1.000 0.000
#> GSM1182235 2 0.000 0.998 0.000 1.000
#> GSM1182236 1 0.000 1.000 1.000 0.000
#> GSM1182237 2 0.000 0.998 0.000 1.000
#> GSM1182238 2 0.000 0.998 0.000 1.000
#> GSM1182239 2 0.000 0.998 0.000 1.000
#> GSM1182240 2 0.000 0.998 0.000 1.000
#> GSM1182241 2 0.000 0.998 0.000 1.000
#> GSM1182242 2 0.000 0.998 0.000 1.000
#> GSM1182243 2 0.000 0.998 0.000 1.000
#> GSM1182244 2 0.000 0.998 0.000 1.000
#> GSM1182245 1 0.000 1.000 1.000 0.000
#> GSM1182246 1 0.000 1.000 1.000 0.000
#> GSM1182247 2 0.000 0.998 0.000 1.000
#> GSM1182248 2 0.000 0.998 0.000 1.000
#> GSM1182249 2 0.000 0.998 0.000 1.000
#> GSM1182250 2 0.000 0.998 0.000 1.000
#> GSM1182251 1 0.000 1.000 1.000 0.000
#> GSM1182252 2 0.000 0.998 0.000 1.000
#> GSM1182253 2 0.000 0.998 0.000 1.000
#> GSM1182254 2 0.000 0.998 0.000 1.000
#> GSM1182255 1 0.000 1.000 1.000 0.000
#> GSM1182256 1 0.000 1.000 1.000 0.000
#> GSM1182257 1 0.000 1.000 1.000 0.000
#> GSM1182258 1 0.000 1.000 1.000 0.000
#> GSM1182259 1 0.000 1.000 1.000 0.000
#> GSM1182260 2 0.000 0.998 0.000 1.000
#> GSM1182261 2 0.000 0.998 0.000 1.000
#> GSM1182262 2 0.000 0.998 0.000 1.000
#> GSM1182263 1 0.000 1.000 1.000 0.000
#> GSM1182264 2 0.000 0.998 0.000 1.000
#> GSM1182265 2 0.000 0.998 0.000 1.000
#> GSM1182266 2 0.000 0.998 0.000 1.000
#> GSM1182267 1 0.000 1.000 1.000 0.000
#> GSM1182268 1 0.000 1.000 1.000 0.000
#> GSM1182269 1 0.000 1.000 1.000 0.000
#> GSM1182270 1 0.000 1.000 1.000 0.000
#> GSM1182271 1 0.000 1.000 1.000 0.000
#> GSM1182272 1 0.000 1.000 1.000 0.000
#> GSM1182273 2 0.000 0.998 0.000 1.000
#> GSM1182275 2 0.000 0.998 0.000 1.000
#> GSM1182276 2 0.000 0.998 0.000 1.000
#> GSM1182277 1 0.000 1.000 1.000 0.000
#> GSM1182278 1 0.000 1.000 1.000 0.000
#> GSM1182279 1 0.000 1.000 1.000 0.000
#> GSM1182280 1 0.000 1.000 1.000 0.000
#> GSM1182281 1 0.000 1.000 1.000 0.000
#> GSM1182282 1 0.000 1.000 1.000 0.000
#> GSM1182283 1 0.000 1.000 1.000 0.000
#> GSM1182284 1 0.000 1.000 1.000 0.000
#> GSM1182285 2 0.000 0.998 0.000 1.000
#> GSM1182286 2 0.000 0.998 0.000 1.000
#> GSM1182287 2 0.000 0.998 0.000 1.000
#> GSM1182288 2 0.000 0.998 0.000 1.000
#> GSM1182289 1 0.000 1.000 1.000 0.000
#> GSM1182290 1 0.000 1.000 1.000 0.000
#> GSM1182291 1 0.000 1.000 1.000 0.000
#> GSM1182274 2 0.000 0.998 0.000 1.000
#> GSM1182292 2 0.000 0.998 0.000 1.000
#> GSM1182293 2 0.000 0.998 0.000 1.000
#> GSM1182294 2 0.000 0.998 0.000 1.000
#> GSM1182295 2 0.000 0.998 0.000 1.000
#> GSM1182296 2 0.000 0.998 0.000 1.000
#> GSM1182298 2 0.141 0.979 0.020 0.980
#> GSM1182299 2 0.000 0.998 0.000 1.000
#> GSM1182300 2 0.000 0.998 0.000 1.000
#> GSM1182301 2 0.000 0.998 0.000 1.000
#> GSM1182303 2 0.000 0.998 0.000 1.000
#> GSM1182304 1 0.000 1.000 1.000 0.000
#> GSM1182305 1 0.000 1.000 1.000 0.000
#> GSM1182306 1 0.000 1.000 1.000 0.000
#> GSM1182307 2 0.000 0.998 0.000 1.000
#> GSM1182309 2 0.000 0.998 0.000 1.000
#> GSM1182312 2 0.000 0.998 0.000 1.000
#> GSM1182314 1 0.000 1.000 1.000 0.000
#> GSM1182316 2 0.000 0.998 0.000 1.000
#> GSM1182318 2 0.000 0.998 0.000 1.000
#> GSM1182319 2 0.000 0.998 0.000 1.000
#> GSM1182320 2 0.000 0.998 0.000 1.000
#> GSM1182321 2 0.000 0.998 0.000 1.000
#> GSM1182322 2 0.000 0.998 0.000 1.000
#> GSM1182324 2 0.000 0.998 0.000 1.000
#> GSM1182297 2 0.000 0.998 0.000 1.000
#> GSM1182302 1 0.000 1.000 1.000 0.000
#> GSM1182308 2 0.000 0.998 0.000 1.000
#> GSM1182310 2 0.000 0.998 0.000 1.000
#> GSM1182311 1 0.000 1.000 1.000 0.000
#> GSM1182313 1 0.000 1.000 1.000 0.000
#> GSM1182315 2 0.000 0.998 0.000 1.000
#> GSM1182317 2 0.000 0.998 0.000 1.000
#> GSM1182323 1 0.000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182187 1 0.5363 0.8281 0.724 0.000 0.276
#> GSM1182188 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182189 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182190 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182191 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182192 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182194 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182195 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182196 2 0.6045 -0.2259 0.000 0.620 0.380
#> GSM1182197 2 0.6244 -0.4620 0.000 0.560 0.440
#> GSM1182198 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182199 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182200 2 0.5497 0.1983 0.000 0.708 0.292
#> GSM1182201 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182202 1 0.5098 0.8379 0.752 0.000 0.248
#> GSM1182203 1 0.5098 0.8379 0.752 0.000 0.248
#> GSM1182204 1 0.5098 0.8379 0.752 0.000 0.248
#> GSM1182205 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182206 2 0.4555 0.5542 0.000 0.800 0.200
#> GSM1182207 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182208 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182209 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182210 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182211 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182212 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182213 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182214 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182215 2 0.4121 0.6370 0.000 0.832 0.168
#> GSM1182216 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182217 1 0.1163 0.9004 0.972 0.000 0.028
#> GSM1182218 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182219 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182220 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182221 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182222 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182223 2 0.2448 0.7770 0.000 0.924 0.076
#> GSM1182224 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182225 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182226 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182227 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182228 2 0.5650 0.2127 0.000 0.688 0.312
#> GSM1182229 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182230 2 0.6095 -0.2001 0.000 0.608 0.392
#> GSM1182231 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182232 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182235 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182236 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182237 2 0.1163 0.8327 0.000 0.972 0.028
#> GSM1182238 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182239 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182240 2 0.0237 0.8533 0.000 0.996 0.004
#> GSM1182241 2 0.6180 -0.3777 0.000 0.584 0.416
#> GSM1182242 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182243 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182244 2 0.5678 0.1984 0.000 0.684 0.316
#> GSM1182245 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182246 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182247 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182248 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182249 2 0.6260 -0.4885 0.000 0.552 0.448
#> GSM1182250 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182251 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182252 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182253 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182254 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182255 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182256 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182257 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182258 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182259 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182260 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182261 2 0.1860 0.8080 0.000 0.948 0.052
#> GSM1182262 2 0.4178 0.6168 0.000 0.828 0.172
#> GSM1182263 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182264 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182265 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182266 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182267 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182270 1 0.0237 0.9048 0.996 0.000 0.004
#> GSM1182271 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182272 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182273 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182275 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182276 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182277 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182279 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182280 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182281 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182282 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182285 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182286 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182287 2 0.4555 0.5542 0.000 0.800 0.200
#> GSM1182288 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182289 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182290 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182291 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182274 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182292 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182293 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182294 2 0.0237 0.8534 0.000 0.996 0.004
#> GSM1182295 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182296 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182298 3 0.5948 0.9958 0.000 0.360 0.640
#> GSM1182299 2 0.5733 0.0456 0.000 0.676 0.324
#> GSM1182300 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182301 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182303 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182304 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182305 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182306 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182307 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182309 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182312 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182314 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182316 2 0.0747 0.8423 0.000 0.984 0.016
#> GSM1182318 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182319 2 0.3482 0.6934 0.000 0.872 0.128
#> GSM1182320 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182321 3 0.6026 0.9676 0.000 0.376 0.624
#> GSM1182322 2 0.6235 -0.4484 0.000 0.564 0.436
#> GSM1182324 3 0.6140 0.9115 0.000 0.404 0.596
#> GSM1182297 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182302 1 0.5098 0.8379 0.752 0.000 0.248
#> GSM1182308 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182310 2 0.2261 0.7847 0.000 0.932 0.068
#> GSM1182311 1 0.0000 0.9073 1.000 0.000 0.000
#> GSM1182313 1 0.5948 0.7956 0.640 0.000 0.360
#> GSM1182315 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182317 2 0.0000 0.8564 0.000 1.000 0.000
#> GSM1182323 1 0.0000 0.9073 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182187 1 0.4406 0.593 0.700 0.000 0.000 0.300
#> GSM1182188 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182191 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182192 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182193 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182194 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182195 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182196 3 0.4164 0.685 0.000 0.264 0.736 0.000
#> GSM1182197 3 0.3649 0.750 0.000 0.204 0.796 0.000
#> GSM1182198 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182199 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182200 3 0.4679 0.532 0.000 0.352 0.648 0.000
#> GSM1182201 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182202 1 0.4134 0.657 0.740 0.000 0.000 0.260
#> GSM1182203 1 0.4193 0.651 0.732 0.000 0.000 0.268
#> GSM1182204 1 0.4134 0.657 0.740 0.000 0.000 0.260
#> GSM1182205 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182206 2 0.3649 0.758 0.000 0.796 0.204 0.000
#> GSM1182207 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182209 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182210 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182211 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182212 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182213 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182214 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182215 2 0.3266 0.809 0.000 0.832 0.168 0.000
#> GSM1182216 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182217 1 0.0921 0.924 0.972 0.000 0.000 0.028
#> GSM1182218 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182219 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182220 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182221 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182222 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182223 2 0.2011 0.886 0.000 0.920 0.080 0.000
#> GSM1182224 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182225 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182226 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182227 1 0.3486 0.753 0.812 0.000 0.000 0.188
#> GSM1182228 2 0.4477 0.603 0.000 0.688 0.312 0.000
#> GSM1182229 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182230 2 0.4843 0.429 0.000 0.604 0.396 0.000
#> GSM1182231 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182232 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182233 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182234 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182235 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182236 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182237 2 0.0921 0.925 0.000 0.972 0.028 0.000
#> GSM1182238 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182239 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182240 2 0.2921 0.812 0.000 0.860 0.140 0.000
#> GSM1182241 3 0.3873 0.726 0.000 0.228 0.772 0.000
#> GSM1182242 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182243 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182244 2 0.4522 0.590 0.000 0.680 0.320 0.000
#> GSM1182245 4 0.4907 0.265 0.420 0.000 0.000 0.580
#> GSM1182246 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182247 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182248 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182249 3 0.3569 0.758 0.000 0.196 0.804 0.000
#> GSM1182250 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182251 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182252 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182253 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182254 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182255 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.3024 0.793 0.148 0.000 0.000 0.852
#> GSM1182258 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182261 2 0.1474 0.909 0.000 0.948 0.052 0.000
#> GSM1182262 2 0.3311 0.797 0.000 0.828 0.172 0.000
#> GSM1182263 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182264 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182265 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182266 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182267 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182268 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182275 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182276 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182277 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182278 1 0.0469 0.939 0.988 0.000 0.000 0.012
#> GSM1182279 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182280 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182281 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182282 1 0.2081 0.877 0.916 0.000 0.000 0.084
#> GSM1182283 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182284 1 0.3801 0.704 0.780 0.000 0.000 0.220
#> GSM1182285 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182286 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182287 2 0.3649 0.758 0.000 0.796 0.204 0.000
#> GSM1182288 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182289 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182290 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.0188 0.928 0.000 0.004 0.996 0.000
#> GSM1182292 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182293 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182294 2 0.0188 0.939 0.000 0.996 0.004 0.000
#> GSM1182295 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182296 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182298 3 0.0000 0.931 0.000 0.000 1.000 0.000
#> GSM1182299 3 0.4522 0.595 0.000 0.320 0.680 0.000
#> GSM1182300 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182301 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182303 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182304 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182305 1 0.0336 0.941 0.992 0.000 0.000 0.008
#> GSM1182306 4 0.4134 0.628 0.260 0.000 0.000 0.740
#> GSM1182307 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182309 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182312 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182314 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.4040 0.641 0.000 0.752 0.248 0.000
#> GSM1182318 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182319 2 0.2814 0.833 0.000 0.868 0.132 0.000
#> GSM1182320 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182321 3 0.0592 0.919 0.000 0.016 0.984 0.000
#> GSM1182322 3 0.3688 0.746 0.000 0.208 0.792 0.000
#> GSM1182324 3 0.1389 0.894 0.000 0.048 0.952 0.000
#> GSM1182297 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182302 1 0.4134 0.657 0.740 0.000 0.000 0.260
#> GSM1182308 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182310 2 0.1792 0.893 0.000 0.932 0.068 0.000
#> GSM1182311 1 0.0000 0.942 1.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.935 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182317 2 0.0000 0.942 0.000 1.000 0.000 0.000
#> GSM1182323 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
#> GSM1182186 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182187 5 0.6063 0.631 0.176 0.000 0.000 0.256 0.568
#> GSM1182188 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182190 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182191 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182192 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182195 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182196 3 0.4465 0.706 0.000 0.212 0.732 0.000 0.056
#> GSM1182197 3 0.3177 0.755 0.000 0.208 0.792 0.000 0.000
#> GSM1182198 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182199 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182200 3 0.4030 0.544 0.000 0.352 0.648 0.000 0.000
#> GSM1182201 3 0.0162 0.927 0.000 0.004 0.996 0.000 0.000
#> GSM1182202 5 0.5336 0.678 0.100 0.000 0.000 0.252 0.648
#> GSM1182203 5 0.6460 0.562 0.248 0.000 0.000 0.252 0.500
#> GSM1182204 5 0.6072 0.632 0.180 0.000 0.000 0.252 0.568
#> GSM1182205 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182206 2 0.3177 0.770 0.000 0.792 0.208 0.000 0.000
#> GSM1182207 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182208 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182209 2 0.0290 0.928 0.000 0.992 0.000 0.000 0.008
#> GSM1182210 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182211 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182212 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182215 2 0.2852 0.818 0.000 0.828 0.172 0.000 0.000
#> GSM1182216 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182217 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182218 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182219 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182220 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182221 2 0.0609 0.925 0.000 0.980 0.000 0.000 0.020
#> GSM1182222 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182223 2 0.1608 0.892 0.000 0.928 0.072 0.000 0.000
#> GSM1182224 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182225 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182226 2 0.0404 0.927 0.000 0.988 0.000 0.000 0.012
#> GSM1182227 1 0.0703 0.952 0.976 0.000 0.000 0.024 0.000
#> GSM1182228 2 0.3857 0.624 0.000 0.688 0.312 0.000 0.000
#> GSM1182229 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182230 2 0.4171 0.453 0.000 0.604 0.396 0.000 0.000
#> GSM1182231 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182232 1 0.0794 0.973 0.972 0.000 0.000 0.000 0.028
#> GSM1182233 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182234 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182236 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182237 2 0.0609 0.923 0.000 0.980 0.020 0.000 0.000
#> GSM1182238 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182239 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182240 2 0.2516 0.810 0.000 0.860 0.140 0.000 0.000
#> GSM1182241 3 0.3336 0.734 0.000 0.228 0.772 0.000 0.000
#> GSM1182242 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182243 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182244 2 0.3895 0.611 0.000 0.680 0.320 0.000 0.000
#> GSM1182245 4 0.4517 0.223 0.436 0.000 0.000 0.556 0.008
#> GSM1182246 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182248 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182249 3 0.3586 0.761 0.000 0.188 0.792 0.000 0.020
#> GSM1182250 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182251 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182252 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182253 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182254 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182255 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.2813 0.741 0.168 0.000 0.000 0.832 0.000
#> GSM1182258 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182261 2 0.1121 0.913 0.000 0.956 0.044 0.000 0.000
#> GSM1182262 2 0.2891 0.808 0.000 0.824 0.176 0.000 0.000
#> GSM1182263 5 0.1965 0.878 0.096 0.000 0.000 0.000 0.904
#> GSM1182264 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182265 3 0.0290 0.926 0.000 0.000 0.992 0.000 0.008
#> GSM1182266 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182267 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182269 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182270 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182271 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182275 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182276 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182277 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182280 5 0.2127 0.869 0.108 0.000 0.000 0.000 0.892
#> GSM1182281 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182282 1 0.1851 0.880 0.912 0.000 0.000 0.088 0.000
#> GSM1182283 1 0.0000 0.969 1.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0290 0.964 0.992 0.000 0.000 0.008 0.000
#> GSM1182285 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182286 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182287 2 0.3177 0.770 0.000 0.792 0.208 0.000 0.000
#> GSM1182288 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182289 5 0.1732 0.883 0.080 0.000 0.000 0.000 0.920
#> GSM1182290 5 0.1671 0.885 0.076 0.000 0.000 0.000 0.924
#> GSM1182291 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 3 0.0162 0.927 0.000 0.004 0.996 0.000 0.000
#> GSM1182292 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182293 2 0.1671 0.904 0.000 0.924 0.000 0.000 0.076
#> GSM1182294 2 0.1205 0.918 0.000 0.956 0.004 0.000 0.040
#> GSM1182295 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182296 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182298 3 0.0000 0.930 0.000 0.000 1.000 0.000 0.000
#> GSM1182299 3 0.3895 0.607 0.000 0.320 0.680 0.000 0.000
#> GSM1182300 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182301 2 0.1608 0.906 0.000 0.928 0.000 0.000 0.072
#> GSM1182303 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182304 5 0.1732 0.884 0.080 0.000 0.000 0.000 0.920
#> GSM1182305 5 0.1892 0.882 0.080 0.000 0.000 0.004 0.916
#> GSM1182306 4 0.4226 0.668 0.140 0.000 0.000 0.776 0.084
#> GSM1182307 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182309 2 0.1671 0.904 0.000 0.924 0.000 0.000 0.076
#> GSM1182312 2 0.1671 0.904 0.000 0.924 0.000 0.000 0.076
#> GSM1182314 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 2 0.5010 0.599 0.000 0.676 0.248 0.000 0.076
#> GSM1182318 2 0.1544 0.908 0.000 0.932 0.000 0.000 0.068
#> GSM1182319 2 0.3980 0.806 0.000 0.796 0.128 0.000 0.076
#> GSM1182320 2 0.1671 0.904 0.000 0.924 0.000 0.000 0.076
#> GSM1182321 3 0.1956 0.877 0.000 0.008 0.916 0.000 0.076
#> GSM1182322 3 0.4069 0.767 0.000 0.136 0.788 0.000 0.076
#> GSM1182324 3 0.2694 0.856 0.000 0.040 0.884 0.000 0.076
#> GSM1182297 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182302 5 0.6301 0.597 0.216 0.000 0.000 0.252 0.532
#> GSM1182308 2 0.0000 0.929 0.000 1.000 0.000 0.000 0.000
#> GSM1182310 2 0.3180 0.862 0.000 0.856 0.068 0.000 0.076
#> GSM1182311 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
#> GSM1182313 4 0.0000 0.925 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.0510 0.926 0.000 0.984 0.000 0.000 0.016
#> GSM1182317 2 0.1671 0.904 0.000 0.924 0.000 0.000 0.076
#> GSM1182323 1 0.0963 0.974 0.964 0.000 0.000 0.000 0.036
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.0000 0.8638 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182187 5 0.5351 0.5898 0.104 0.000 0.000 0.256 0.620 0.020
#> GSM1182188 4 0.0260 0.9166 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1182189 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182190 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182191 5 0.0000 0.8638 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182192 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.0000 0.7484 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1182195 3 0.0260 0.7443 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182196 6 0.4866 0.0404 0.000 0.116 0.236 0.000 0.000 0.648
#> GSM1182197 6 0.6111 -0.1019 0.000 0.340 0.296 0.000 0.000 0.364
#> GSM1182198 3 0.0000 0.7484 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1182199 3 0.0000 0.7484 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1182200 2 0.6001 -0.2482 0.000 0.424 0.248 0.000 0.000 0.328
#> GSM1182201 3 0.3789 0.7527 0.000 0.008 0.660 0.000 0.000 0.332
#> GSM1182202 5 0.4640 0.6283 0.032 0.000 0.000 0.256 0.680 0.032
#> GSM1182203 5 0.6151 0.4676 0.216 0.000 0.000 0.256 0.508 0.020
#> GSM1182204 5 0.5904 0.5209 0.172 0.000 0.000 0.256 0.552 0.020
#> GSM1182205 3 0.0547 0.7500 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM1182206 2 0.3923 0.2644 0.000 0.620 0.372 0.000 0.000 0.008
#> GSM1182207 5 0.0260 0.8635 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM1182208 5 0.0260 0.8635 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM1182209 2 0.3515 0.2155 0.000 0.676 0.000 0.000 0.000 0.324
#> GSM1182210 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.2135 0.6494 0.000 0.872 0.000 0.000 0.000 0.128
#> GSM1182212 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182215 2 0.4634 0.1899 0.000 0.556 0.400 0.000 0.000 0.044
#> GSM1182216 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182217 1 0.2358 0.9376 0.876 0.000 0.000 0.000 0.016 0.108
#> GSM1182218 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182219 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182220 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182221 2 0.2300 0.6386 0.000 0.856 0.000 0.000 0.000 0.144
#> GSM1182222 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182223 2 0.2542 0.6558 0.000 0.876 0.080 0.000 0.000 0.044
#> GSM1182224 3 0.0260 0.7443 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182225 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182226 2 0.2416 0.6172 0.000 0.844 0.000 0.000 0.000 0.156
#> GSM1182227 1 0.0458 0.9343 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM1182228 2 0.3872 0.2336 0.000 0.604 0.392 0.000 0.000 0.004
#> GSM1182229 3 0.3531 0.7578 0.000 0.000 0.672 0.000 0.000 0.328
#> GSM1182230 3 0.3998 0.3901 0.000 0.248 0.712 0.000 0.000 0.040
#> GSM1182231 2 0.0632 0.7481 0.000 0.976 0.000 0.000 0.000 0.024
#> GSM1182232 1 0.1531 0.9500 0.928 0.000 0.000 0.000 0.004 0.068
#> GSM1182233 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182234 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182236 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182237 2 0.1124 0.7363 0.000 0.956 0.008 0.000 0.000 0.036
#> GSM1182238 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182239 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182240 2 0.2442 0.6166 0.000 0.852 0.004 0.000 0.000 0.144
#> GSM1182241 2 0.6101 -0.2870 0.000 0.372 0.288 0.000 0.000 0.340
#> GSM1182242 3 0.3531 0.7578 0.000 0.000 0.672 0.000 0.000 0.328
#> GSM1182243 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182244 3 0.4173 0.3332 0.000 0.268 0.688 0.000 0.000 0.044
#> GSM1182245 4 0.3993 0.1261 0.476 0.000 0.000 0.520 0.004 0.000
#> GSM1182246 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 3 0.1141 0.7595 0.000 0.000 0.948 0.000 0.000 0.052
#> GSM1182248 3 0.0146 0.7498 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1182249 6 0.6083 -0.1167 0.000 0.304 0.300 0.000 0.000 0.396
#> GSM1182250 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182251 5 0.0000 0.8638 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 3 0.1814 0.7589 0.000 0.000 0.900 0.000 0.000 0.100
#> GSM1182253 3 0.3531 0.7578 0.000 0.000 0.672 0.000 0.000 0.328
#> GSM1182254 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182255 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.2597 0.7457 0.176 0.000 0.000 0.824 0.000 0.000
#> GSM1182258 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182261 2 0.2197 0.6885 0.000 0.900 0.056 0.000 0.000 0.044
#> GSM1182262 2 0.4186 0.3333 0.000 0.656 0.312 0.000 0.000 0.032
#> GSM1182263 5 0.0865 0.8518 0.036 0.000 0.000 0.000 0.964 0.000
#> GSM1182264 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182265 3 0.3804 0.6882 0.000 0.000 0.576 0.000 0.000 0.424
#> GSM1182266 3 0.3647 0.7537 0.000 0.000 0.640 0.000 0.000 0.360
#> GSM1182267 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182269 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182270 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182271 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 3 0.3647 0.7537 0.000 0.000 0.640 0.000 0.000 0.360
#> GSM1182275 3 0.3547 0.7568 0.000 0.000 0.668 0.000 0.000 0.332
#> GSM1182276 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182277 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.0146 0.8639 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182280 5 0.1434 0.8399 0.048 0.000 0.000 0.000 0.940 0.012
#> GSM1182281 4 0.0146 0.9196 0.004 0.000 0.000 0.996 0.000 0.000
#> GSM1182282 1 0.1663 0.8654 0.912 0.000 0.000 0.088 0.000 0.000
#> GSM1182283 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.9432 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182285 3 0.0260 0.7443 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1182286 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182287 2 0.4389 0.2291 0.000 0.596 0.372 0.000 0.000 0.032
#> GSM1182288 3 0.1327 0.7612 0.000 0.000 0.936 0.000 0.000 0.064
#> GSM1182289 5 0.0146 0.8628 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182290 5 0.0260 0.8635 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM1182291 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.3659 0.7520 0.000 0.000 0.636 0.000 0.000 0.364
#> GSM1182292 2 0.0458 0.7547 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM1182293 6 0.3867 0.3307 0.000 0.488 0.000 0.000 0.000 0.512
#> GSM1182294 2 0.3309 0.4279 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM1182295 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182296 2 0.1663 0.6945 0.000 0.912 0.000 0.000 0.000 0.088
#> GSM1182298 3 0.0000 0.7484 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1182299 6 0.5848 0.1455 0.000 0.296 0.224 0.000 0.000 0.480
#> GSM1182300 2 0.0260 0.7592 0.000 0.992 0.000 0.000 0.000 0.008
#> GSM1182301 6 0.3868 0.3231 0.000 0.492 0.000 0.000 0.000 0.508
#> GSM1182303 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182304 5 0.0547 0.8600 0.000 0.000 0.000 0.000 0.980 0.020
#> GSM1182305 5 0.0146 0.8628 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182306 4 0.4294 0.6928 0.128 0.000 0.000 0.760 0.092 0.020
#> GSM1182307 2 0.2219 0.6403 0.000 0.864 0.000 0.000 0.000 0.136
#> GSM1182309 6 0.3867 0.3307 0.000 0.488 0.000 0.000 0.000 0.512
#> GSM1182312 6 0.3866 0.3360 0.000 0.484 0.000 0.000 0.000 0.516
#> GSM1182314 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 6 0.3766 0.4483 0.000 0.304 0.012 0.000 0.000 0.684
#> GSM1182318 2 0.3868 -0.3502 0.000 0.504 0.000 0.000 0.000 0.496
#> GSM1182319 6 0.3955 0.3647 0.000 0.436 0.004 0.000 0.000 0.560
#> GSM1182320 6 0.3866 0.3360 0.000 0.484 0.000 0.000 0.000 0.516
#> GSM1182321 6 0.2520 0.2256 0.000 0.004 0.152 0.000 0.000 0.844
#> GSM1182322 6 0.3125 0.3809 0.000 0.084 0.080 0.000 0.000 0.836
#> GSM1182324 6 0.2218 0.2647 0.000 0.012 0.104 0.000 0.000 0.884
#> GSM1182297 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182302 5 0.6108 0.5110 0.172 0.000 0.000 0.256 0.540 0.032
#> GSM1182308 2 0.0000 0.7636 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182310 6 0.3833 0.3562 0.000 0.444 0.000 0.000 0.000 0.556
#> GSM1182311 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
#> GSM1182313 4 0.0000 0.9223 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.3330 0.3375 0.000 0.716 0.000 0.000 0.000 0.284
#> GSM1182317 6 0.3867 0.3307 0.000 0.488 0.000 0.000 0.000 0.512
#> GSM1182323 1 0.2020 0.9508 0.896 0.000 0.000 0.000 0.008 0.096
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:pam 139 0.077250 1.000 2
#> MAD:pam 129 0.000883 0.538 3
#> MAD:pam 137 0.007049 0.650 4
#> MAD:pam 137 0.014093 0.775 5
#> MAD:pam 108 0.155107 0.968 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.751 0.917 0.906 0.3354 0.818 0.650
#> 4 4 0.627 0.598 0.788 0.1263 0.906 0.737
#> 5 5 0.648 0.496 0.738 0.0707 0.831 0.500
#> 6 6 0.688 0.667 0.776 0.0448 0.906 0.635
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182187 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182188 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182189 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182190 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182191 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182192 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182193 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182194 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182195 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182196 2 0.4346 0.960 0.000 0.816 0.184
#> GSM1182197 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182198 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182199 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182200 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182201 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182202 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182203 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182204 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182205 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182206 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182207 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182208 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182209 3 0.6280 -0.195 0.000 0.460 0.540
#> GSM1182210 3 0.1529 0.927 0.000 0.040 0.960
#> GSM1182211 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182212 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182213 3 0.1860 0.920 0.000 0.052 0.948
#> GSM1182214 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182215 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182216 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182217 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182218 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182219 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182220 3 0.0237 0.936 0.000 0.004 0.996
#> GSM1182221 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182222 3 0.0747 0.935 0.000 0.016 0.984
#> GSM1182223 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182224 2 0.4291 0.963 0.000 0.820 0.180
#> GSM1182225 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182226 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182227 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182228 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182229 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182230 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182231 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182232 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182235 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182236 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182237 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182238 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182239 2 0.6095 0.647 0.000 0.608 0.392
#> GSM1182240 2 0.5988 0.661 0.000 0.632 0.368
#> GSM1182241 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182242 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182243 2 0.4654 0.945 0.000 0.792 0.208
#> GSM1182244 2 0.4887 0.930 0.000 0.772 0.228
#> GSM1182245 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182246 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182247 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182248 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182249 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182250 2 0.4452 0.956 0.000 0.808 0.192
#> GSM1182251 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182252 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182253 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182254 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182255 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182256 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182257 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182258 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182259 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182260 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182261 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182262 2 0.4887 0.930 0.000 0.772 0.228
#> GSM1182263 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182264 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182265 2 0.4346 0.961 0.000 0.816 0.184
#> GSM1182266 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182267 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182270 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182271 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182272 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182273 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182275 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182276 2 0.4346 0.958 0.000 0.816 0.184
#> GSM1182277 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182279 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182280 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182281 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182282 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182284 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182285 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182286 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182287 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182288 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182289 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182290 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182291 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182274 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182292 3 0.3192 0.857 0.000 0.112 0.888
#> GSM1182293 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182294 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182295 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182296 3 0.1643 0.924 0.000 0.044 0.956
#> GSM1182298 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182299 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182300 3 0.0237 0.936 0.000 0.004 0.996
#> GSM1182301 3 0.6168 0.103 0.000 0.412 0.588
#> GSM1182303 2 0.4178 0.966 0.000 0.828 0.172
#> GSM1182304 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182305 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182306 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182307 3 0.1529 0.929 0.000 0.040 0.960
#> GSM1182309 3 0.0237 0.936 0.000 0.004 0.996
#> GSM1182312 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182314 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182316 3 0.2165 0.905 0.000 0.064 0.936
#> GSM1182318 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182319 3 0.5138 0.583 0.000 0.252 0.748
#> GSM1182320 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182321 2 0.5016 0.920 0.000 0.760 0.240
#> GSM1182322 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182324 2 0.5058 0.917 0.000 0.756 0.244
#> GSM1182297 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182302 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182308 3 0.0000 0.935 0.000 0.000 1.000
#> GSM1182310 3 0.1411 0.931 0.000 0.036 0.964
#> GSM1182311 1 0.0000 0.916 1.000 0.000 0.000
#> GSM1182313 1 0.4178 0.939 0.828 0.172 0.000
#> GSM1182315 3 0.0237 0.936 0.000 0.004 0.996
#> GSM1182317 3 0.1289 0.932 0.000 0.032 0.968
#> GSM1182323 1 0.0000 0.916 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182187 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182188 4 0.4585 0.1913 0.332 0.000 0.000 0.668
#> GSM1182189 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182190 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182191 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182192 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182193 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182194 3 0.2399 0.7834 0.032 0.048 0.920 0.000
#> GSM1182195 3 0.2376 0.7804 0.016 0.068 0.916 0.000
#> GSM1182196 3 0.4382 0.6323 0.000 0.296 0.704 0.000
#> GSM1182197 3 0.3649 0.6914 0.000 0.204 0.796 0.000
#> GSM1182198 3 0.1174 0.7732 0.012 0.020 0.968 0.000
#> GSM1182199 3 0.1174 0.7732 0.012 0.020 0.968 0.000
#> GSM1182200 3 0.4630 0.6954 0.036 0.196 0.768 0.000
#> GSM1182201 3 0.4500 0.7019 0.032 0.192 0.776 0.000
#> GSM1182202 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182203 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182204 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182205 3 0.2546 0.7859 0.028 0.060 0.912 0.000
#> GSM1182206 3 0.5028 0.3762 0.004 0.400 0.596 0.000
#> GSM1182207 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182208 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182209 3 0.7619 -0.1129 0.208 0.356 0.436 0.000
#> GSM1182210 2 0.1302 0.7945 0.000 0.956 0.044 0.000
#> GSM1182211 2 0.2179 0.7909 0.012 0.924 0.064 0.000
#> GSM1182212 3 0.4922 0.6962 0.036 0.228 0.736 0.000
#> GSM1182213 2 0.3498 0.7313 0.008 0.832 0.160 0.000
#> GSM1182214 2 0.1767 0.7944 0.012 0.944 0.044 0.000
#> GSM1182215 3 0.5016 0.3816 0.004 0.396 0.600 0.000
#> GSM1182216 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182217 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182218 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182219 2 0.2589 0.7583 0.000 0.884 0.116 0.000
#> GSM1182220 2 0.3024 0.7274 0.000 0.852 0.148 0.000
#> GSM1182221 2 0.3444 0.7927 0.184 0.816 0.000 0.000
#> GSM1182222 2 0.1978 0.7905 0.004 0.928 0.068 0.000
#> GSM1182223 3 0.2399 0.7819 0.032 0.048 0.920 0.000
#> GSM1182224 3 0.4372 0.6058 0.004 0.268 0.728 0.000
#> GSM1182225 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182226 2 0.3958 0.7988 0.160 0.816 0.024 0.000
#> GSM1182227 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182228 3 0.2644 0.7845 0.032 0.060 0.908 0.000
#> GSM1182229 3 0.2644 0.7825 0.032 0.060 0.908 0.000
#> GSM1182230 3 0.5028 0.3762 0.004 0.400 0.596 0.000
#> GSM1182231 2 0.5080 0.1051 0.004 0.576 0.420 0.000
#> GSM1182232 4 0.4830 0.1069 0.392 0.000 0.000 0.608
#> GSM1182233 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182234 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182235 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182236 4 0.4830 0.1069 0.392 0.000 0.000 0.608
#> GSM1182237 3 0.5028 0.3762 0.004 0.400 0.596 0.000
#> GSM1182238 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182239 3 0.5080 0.3135 0.004 0.420 0.576 0.000
#> GSM1182240 3 0.4567 0.6088 0.008 0.276 0.716 0.000
#> GSM1182241 3 0.3649 0.6914 0.000 0.204 0.796 0.000
#> GSM1182242 3 0.2313 0.7818 0.032 0.044 0.924 0.000
#> GSM1182243 3 0.4632 0.5548 0.004 0.308 0.688 0.000
#> GSM1182244 3 0.4872 0.4554 0.004 0.356 0.640 0.000
#> GSM1182245 1 0.4877 0.6275 0.592 0.000 0.000 0.408
#> GSM1182246 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182247 3 0.2224 0.7803 0.032 0.040 0.928 0.000
#> GSM1182248 3 0.2313 0.7821 0.032 0.044 0.924 0.000
#> GSM1182249 2 0.5112 0.0708 0.004 0.560 0.436 0.000
#> GSM1182250 3 0.3208 0.7441 0.004 0.148 0.848 0.000
#> GSM1182251 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182252 3 0.3280 0.7639 0.016 0.124 0.860 0.000
#> GSM1182253 3 0.2399 0.7834 0.032 0.048 0.920 0.000
#> GSM1182254 3 0.1724 0.7760 0.032 0.020 0.948 0.000
#> GSM1182255 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182256 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182257 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182258 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182259 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182260 3 0.3219 0.7274 0.000 0.164 0.836 0.000
#> GSM1182261 3 0.5028 0.3762 0.004 0.400 0.596 0.000
#> GSM1182262 3 0.5016 0.3860 0.004 0.396 0.600 0.000
#> GSM1182263 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182264 3 0.2021 0.7739 0.012 0.056 0.932 0.000
#> GSM1182265 3 0.4485 0.6754 0.028 0.200 0.772 0.000
#> GSM1182266 3 0.1297 0.7780 0.016 0.020 0.964 0.000
#> GSM1182267 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182268 4 0.4830 0.1069 0.392 0.000 0.000 0.608
#> GSM1182269 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182270 4 0.4817 0.1133 0.388 0.000 0.000 0.612
#> GSM1182271 4 0.4406 0.2459 0.300 0.000 0.000 0.700
#> GSM1182272 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182273 3 0.1042 0.7744 0.008 0.020 0.972 0.000
#> GSM1182275 3 0.2483 0.7840 0.032 0.052 0.916 0.000
#> GSM1182276 3 0.5021 0.6902 0.036 0.240 0.724 0.000
#> GSM1182277 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182278 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182279 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182280 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182281 1 0.4981 0.4589 0.536 0.000 0.000 0.464
#> GSM1182282 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182283 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182284 1 0.4134 0.9301 0.740 0.000 0.000 0.260
#> GSM1182285 3 0.2722 0.7849 0.032 0.064 0.904 0.000
#> GSM1182286 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182287 3 0.2399 0.7819 0.032 0.048 0.920 0.000
#> GSM1182288 3 0.2224 0.7803 0.032 0.040 0.928 0.000
#> GSM1182289 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182290 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182291 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182274 3 0.3047 0.7552 0.012 0.116 0.872 0.000
#> GSM1182292 2 0.4897 0.4027 0.008 0.660 0.332 0.000
#> GSM1182293 2 0.3400 0.7937 0.180 0.820 0.000 0.000
#> GSM1182294 2 0.3806 0.8004 0.156 0.824 0.020 0.000
#> GSM1182295 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182296 2 0.1474 0.7939 0.000 0.948 0.052 0.000
#> GSM1182298 3 0.1938 0.7792 0.012 0.052 0.936 0.000
#> GSM1182299 3 0.3688 0.6883 0.000 0.208 0.792 0.000
#> GSM1182300 2 0.0376 0.8014 0.004 0.992 0.004 0.000
#> GSM1182301 2 0.5846 -0.1193 0.032 0.516 0.452 0.000
#> GSM1182303 3 0.4922 0.6967 0.036 0.228 0.736 0.000
#> GSM1182304 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182305 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182306 4 0.0188 0.6365 0.004 0.000 0.000 0.996
#> GSM1182307 2 0.3128 0.7944 0.040 0.884 0.076 0.000
#> GSM1182309 2 0.4464 0.7841 0.208 0.768 0.024 0.000
#> GSM1182312 2 0.3972 0.7866 0.204 0.788 0.008 0.000
#> GSM1182314 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182316 2 0.7091 0.5948 0.208 0.568 0.224 0.000
#> GSM1182318 2 0.5077 0.7855 0.160 0.760 0.080 0.000
#> GSM1182319 2 0.5620 0.7638 0.208 0.708 0.084 0.000
#> GSM1182320 2 0.5458 0.7675 0.204 0.720 0.076 0.000
#> GSM1182321 2 0.7586 0.1988 0.196 0.416 0.388 0.000
#> GSM1182322 2 0.5494 0.7668 0.208 0.716 0.076 0.000
#> GSM1182324 2 0.7485 0.3805 0.192 0.472 0.336 0.000
#> GSM1182297 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182302 4 0.0000 0.6378 0.000 0.000 0.000 1.000
#> GSM1182308 2 0.0000 0.8006 0.000 1.000 0.000 0.000
#> GSM1182310 2 0.5494 0.7668 0.208 0.716 0.076 0.000
#> GSM1182311 4 0.4830 0.1069 0.392 0.000 0.000 0.608
#> GSM1182313 4 0.4679 0.1556 0.352 0.000 0.000 0.648
#> GSM1182315 2 0.4426 0.7848 0.204 0.772 0.024 0.000
#> GSM1182317 2 0.5494 0.7668 0.208 0.716 0.076 0.000
#> GSM1182323 4 0.4817 0.1133 0.388 0.000 0.000 0.612
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182187 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182188 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182189 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182190 4 0.4307 -0.18390 0.500 0.000 0.000 0.500 0.000
#> GSM1182191 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182192 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182193 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182194 3 0.3039 0.67847 0.000 0.000 0.808 0.000 0.192
#> GSM1182195 3 0.3700 0.66849 0.000 0.008 0.752 0.000 0.240
#> GSM1182196 2 0.6465 0.23722 0.000 0.484 0.308 0.000 0.208
#> GSM1182197 2 0.6791 0.00744 0.000 0.360 0.356 0.000 0.284
#> GSM1182198 3 0.3876 0.64045 0.000 0.000 0.684 0.000 0.316
#> GSM1182199 3 0.3876 0.64045 0.000 0.000 0.684 0.000 0.316
#> GSM1182200 2 0.6777 0.09232 0.000 0.372 0.352 0.000 0.276
#> GSM1182201 3 0.5287 0.60910 0.000 0.092 0.648 0.000 0.260
#> GSM1182202 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182203 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182204 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182205 3 0.1750 0.69891 0.000 0.036 0.936 0.000 0.028
#> GSM1182206 3 0.5024 0.35311 0.000 0.440 0.528 0.000 0.032
#> GSM1182207 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182208 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182209 2 0.6369 0.22851 0.000 0.520 0.236 0.000 0.244
#> GSM1182210 2 0.0992 0.53550 0.000 0.968 0.024 0.000 0.008
#> GSM1182211 2 0.2409 0.51347 0.000 0.900 0.068 0.000 0.032
#> GSM1182212 2 0.6729 0.14535 0.000 0.396 0.348 0.000 0.256
#> GSM1182213 2 0.5544 0.33957 0.000 0.648 0.184 0.000 0.168
#> GSM1182214 2 0.0693 0.53416 0.000 0.980 0.012 0.000 0.008
#> GSM1182215 3 0.5096 0.34488 0.000 0.444 0.520 0.000 0.036
#> GSM1182216 2 0.0404 0.52910 0.000 0.988 0.000 0.000 0.012
#> GSM1182217 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182218 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182219 2 0.0992 0.53456 0.000 0.968 0.024 0.000 0.008
#> GSM1182220 2 0.1918 0.52117 0.000 0.928 0.036 0.000 0.036
#> GSM1182221 2 0.4074 -0.17480 0.000 0.636 0.000 0.000 0.364
#> GSM1182222 2 0.1211 0.52980 0.000 0.960 0.024 0.000 0.016
#> GSM1182223 3 0.1121 0.69263 0.000 0.044 0.956 0.000 0.000
#> GSM1182224 3 0.4479 0.60086 0.000 0.264 0.700 0.000 0.036
#> GSM1182225 2 0.0000 0.53258 0.000 1.000 0.000 0.000 0.000
#> GSM1182226 2 0.3728 0.16624 0.000 0.748 0.008 0.000 0.244
#> GSM1182227 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182228 3 0.1818 0.68659 0.000 0.044 0.932 0.000 0.024
#> GSM1182229 3 0.0963 0.69266 0.000 0.036 0.964 0.000 0.000
#> GSM1182230 3 0.5096 0.34488 0.000 0.444 0.520 0.000 0.036
#> GSM1182231 2 0.4937 -0.15033 0.000 0.544 0.428 0.000 0.028
#> GSM1182232 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182233 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182234 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182235 2 0.0290 0.52977 0.000 0.992 0.000 0.000 0.008
#> GSM1182236 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182237 3 0.4968 0.32770 0.000 0.456 0.516 0.000 0.028
#> GSM1182238 2 0.0609 0.52305 0.000 0.980 0.000 0.000 0.020
#> GSM1182239 2 0.6265 0.25880 0.000 0.540 0.240 0.000 0.220
#> GSM1182240 2 0.6593 0.23700 0.000 0.464 0.284 0.000 0.252
#> GSM1182241 2 0.6690 0.18114 0.000 0.432 0.300 0.000 0.268
#> GSM1182242 3 0.0963 0.69266 0.000 0.036 0.964 0.000 0.000
#> GSM1182243 3 0.4338 0.58685 0.000 0.280 0.696 0.000 0.024
#> GSM1182244 3 0.4419 0.55479 0.000 0.312 0.668 0.000 0.020
#> GSM1182245 1 0.2516 0.50818 0.860 0.000 0.000 0.140 0.000
#> GSM1182246 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182247 3 0.0963 0.69266 0.000 0.036 0.964 0.000 0.000
#> GSM1182248 3 0.0963 0.69266 0.000 0.036 0.964 0.000 0.000
#> GSM1182249 3 0.6229 0.44724 0.000 0.268 0.540 0.000 0.192
#> GSM1182250 3 0.5274 0.63352 0.000 0.132 0.676 0.000 0.192
#> GSM1182251 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 3 0.1697 0.69534 0.000 0.060 0.932 0.000 0.008
#> GSM1182253 3 0.3409 0.69699 0.000 0.032 0.824 0.000 0.144
#> GSM1182254 3 0.4150 0.67321 0.000 0.036 0.748 0.000 0.216
#> GSM1182255 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182256 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182257 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182259 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182260 3 0.5203 0.64089 0.000 0.080 0.648 0.000 0.272
#> GSM1182261 3 0.4961 0.34317 0.000 0.448 0.524 0.000 0.028
#> GSM1182262 3 0.4966 0.41906 0.000 0.404 0.564 0.000 0.032
#> GSM1182263 4 0.0609 0.92545 0.020 0.000 0.000 0.980 0.000
#> GSM1182264 3 0.4025 0.65171 0.000 0.008 0.700 0.000 0.292
#> GSM1182265 3 0.5538 0.57996 0.000 0.088 0.588 0.000 0.324
#> GSM1182266 3 0.4404 0.66829 0.000 0.032 0.704 0.000 0.264
#> GSM1182267 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182268 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182269 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182270 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182271 1 0.5112 0.28670 0.496 0.000 0.000 0.468 0.036
#> GSM1182272 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182273 3 0.3730 0.65462 0.000 0.000 0.712 0.000 0.288
#> GSM1182275 3 0.3922 0.68646 0.000 0.040 0.780 0.000 0.180
#> GSM1182276 3 0.5529 -0.13944 0.000 0.420 0.512 0.000 0.068
#> GSM1182277 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182278 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182279 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182280 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182281 1 0.4398 0.44616 0.720 0.000 0.000 0.240 0.040
#> GSM1182282 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182283 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182284 1 0.0290 0.54996 0.992 0.000 0.000 0.008 0.000
#> GSM1182285 3 0.1364 0.69455 0.000 0.036 0.952 0.000 0.012
#> GSM1182286 2 0.0404 0.53482 0.000 0.988 0.012 0.000 0.000
#> GSM1182287 3 0.1626 0.68776 0.000 0.044 0.940 0.000 0.016
#> GSM1182288 3 0.0963 0.69266 0.000 0.036 0.964 0.000 0.000
#> GSM1182289 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182290 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182291 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182274 3 0.5342 0.63520 0.000 0.076 0.612 0.000 0.312
#> GSM1182292 2 0.5902 0.30182 0.000 0.600 0.192 0.000 0.208
#> GSM1182293 2 0.4126 -0.22022 0.000 0.620 0.000 0.000 0.380
#> GSM1182294 2 0.4655 -0.11067 0.000 0.644 0.028 0.000 0.328
#> GSM1182295 2 0.0290 0.53091 0.000 0.992 0.000 0.000 0.008
#> GSM1182296 2 0.0955 0.53583 0.000 0.968 0.028 0.000 0.004
#> GSM1182298 3 0.4339 0.64669 0.000 0.020 0.684 0.000 0.296
#> GSM1182299 2 0.6610 0.22559 0.000 0.460 0.280 0.000 0.260
#> GSM1182300 2 0.0566 0.53026 0.000 0.984 0.004 0.000 0.012
#> GSM1182301 2 0.6422 0.26394 0.000 0.488 0.316 0.000 0.196
#> GSM1182303 3 0.5499 -0.08549 0.000 0.400 0.532 0.000 0.068
#> GSM1182304 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182305 4 0.0404 0.94336 0.000 0.000 0.000 0.988 0.012
#> GSM1182306 4 0.0510 0.93887 0.000 0.000 0.000 0.984 0.016
#> GSM1182307 2 0.3297 0.48146 0.000 0.848 0.084 0.000 0.068
#> GSM1182309 5 0.4774 0.49642 0.000 0.424 0.020 0.000 0.556
#> GSM1182312 5 0.4306 0.39580 0.000 0.492 0.000 0.000 0.508
#> GSM1182314 1 0.5173 0.29330 0.500 0.000 0.000 0.460 0.040
#> GSM1182316 5 0.4994 0.67346 0.000 0.208 0.096 0.000 0.696
#> GSM1182318 2 0.5357 0.10451 0.000 0.588 0.068 0.000 0.344
#> GSM1182319 5 0.4276 0.76360 0.000 0.244 0.032 0.000 0.724
#> GSM1182320 5 0.4114 0.75883 0.000 0.244 0.024 0.000 0.732
#> GSM1182321 5 0.6195 0.50316 0.000 0.208 0.240 0.000 0.552
#> GSM1182322 5 0.4167 0.76177 0.000 0.252 0.024 0.000 0.724
#> GSM1182324 5 0.6309 0.46299 0.000 0.208 0.264 0.000 0.528
#> GSM1182297 2 0.0404 0.52910 0.000 0.988 0.000 0.000 0.012
#> GSM1182302 4 0.0000 0.95507 0.000 0.000 0.000 1.000 0.000
#> GSM1182308 2 0.0290 0.53230 0.000 0.992 0.000 0.000 0.008
#> GSM1182310 5 0.4276 0.76360 0.000 0.244 0.032 0.000 0.724
#> GSM1182311 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
#> GSM1182313 1 0.5176 0.28793 0.492 0.000 0.000 0.468 0.040
#> GSM1182315 2 0.4689 -0.27948 0.000 0.560 0.016 0.000 0.424
#> GSM1182317 5 0.4167 0.76177 0.000 0.252 0.024 0.000 0.724
#> GSM1182323 1 0.4307 0.11632 0.500 0.000 0.000 0.500 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182187 5 0.0935 0.80185 0.004 0.000 0.000 0.032 0.964 0.000
#> GSM1182188 4 0.5211 0.73142 0.108 0.000 0.000 0.612 0.272 0.008
#> GSM1182189 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182190 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182191 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182192 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182193 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182194 3 0.3126 0.67880 0.000 0.000 0.752 0.000 0.000 0.248
#> GSM1182195 3 0.3489 0.62912 0.004 0.000 0.708 0.000 0.000 0.288
#> GSM1182196 2 0.5727 -0.15713 0.032 0.452 0.440 0.000 0.000 0.076
#> GSM1182197 6 0.6352 0.70541 0.020 0.240 0.288 0.000 0.000 0.452
#> GSM1182198 3 0.3534 0.62021 0.008 0.000 0.716 0.000 0.000 0.276
#> GSM1182199 3 0.3534 0.62021 0.008 0.000 0.716 0.000 0.000 0.276
#> GSM1182200 6 0.5848 0.82191 0.004 0.212 0.272 0.000 0.000 0.512
#> GSM1182201 3 0.5114 -0.45863 0.004 0.068 0.488 0.000 0.000 0.440
#> GSM1182202 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182203 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182204 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182205 3 0.2094 0.72030 0.000 0.020 0.900 0.000 0.000 0.080
#> GSM1182206 3 0.4639 0.67029 0.012 0.188 0.708 0.000 0.000 0.092
#> GSM1182207 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182208 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182209 2 0.6139 0.27834 0.080 0.596 0.168 0.000 0.000 0.156
#> GSM1182210 2 0.1708 0.71078 0.040 0.932 0.024 0.000 0.000 0.004
#> GSM1182211 2 0.3269 0.63882 0.020 0.832 0.028 0.000 0.000 0.120
#> GSM1182212 6 0.5848 0.82191 0.004 0.212 0.272 0.000 0.000 0.512
#> GSM1182213 2 0.4074 0.56251 0.020 0.756 0.040 0.000 0.000 0.184
#> GSM1182214 2 0.1615 0.70190 0.004 0.928 0.004 0.000 0.000 0.064
#> GSM1182215 3 0.5469 0.64610 0.052 0.144 0.664 0.000 0.000 0.140
#> GSM1182216 2 0.1327 0.71600 0.064 0.936 0.000 0.000 0.000 0.000
#> GSM1182217 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182218 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182219 2 0.2823 0.71494 0.044 0.872 0.016 0.000 0.000 0.068
#> GSM1182220 2 0.2631 0.67514 0.004 0.876 0.044 0.000 0.000 0.076
#> GSM1182221 1 0.3684 0.67406 0.664 0.332 0.000 0.000 0.000 0.004
#> GSM1182222 2 0.3458 0.63880 0.068 0.820 0.104 0.000 0.000 0.008
#> GSM1182223 3 0.3595 0.49281 0.000 0.008 0.704 0.000 0.000 0.288
#> GSM1182224 3 0.4815 0.69132 0.040 0.140 0.724 0.000 0.000 0.096
#> GSM1182225 2 0.1007 0.72267 0.044 0.956 0.000 0.000 0.000 0.000
#> GSM1182226 1 0.3653 0.71253 0.692 0.300 0.000 0.000 0.000 0.008
#> GSM1182227 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182228 3 0.4518 0.26500 0.000 0.044 0.604 0.000 0.000 0.352
#> GSM1182229 3 0.2302 0.70235 0.000 0.008 0.872 0.000 0.000 0.120
#> GSM1182230 3 0.5099 0.66692 0.048 0.148 0.700 0.000 0.000 0.104
#> GSM1182231 3 0.4704 0.55968 0.000 0.300 0.628 0.000 0.000 0.072
#> GSM1182232 5 0.3592 0.68007 0.000 0.000 0.000 0.344 0.656 0.000
#> GSM1182233 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182234 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182235 2 0.1007 0.72267 0.044 0.956 0.000 0.000 0.000 0.000
#> GSM1182236 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182237 3 0.5568 0.63883 0.052 0.156 0.652 0.000 0.000 0.140
#> GSM1182238 2 0.2048 0.66560 0.120 0.880 0.000 0.000 0.000 0.000
#> GSM1182239 2 0.6692 0.16729 0.088 0.512 0.184 0.000 0.000 0.216
#> GSM1182240 2 0.5819 -0.21094 0.004 0.520 0.264 0.000 0.000 0.212
#> GSM1182241 6 0.6444 0.56606 0.016 0.356 0.268 0.000 0.000 0.360
#> GSM1182242 3 0.2346 0.70006 0.000 0.008 0.868 0.000 0.000 0.124
#> GSM1182243 3 0.4081 0.69787 0.016 0.152 0.768 0.000 0.000 0.064
#> GSM1182244 3 0.5064 0.68201 0.048 0.144 0.704 0.000 0.000 0.104
#> GSM1182245 4 0.2664 0.76783 0.016 0.000 0.000 0.848 0.136 0.000
#> GSM1182246 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182247 3 0.2302 0.70235 0.000 0.008 0.872 0.000 0.000 0.120
#> GSM1182248 3 0.2212 0.70653 0.000 0.008 0.880 0.000 0.000 0.112
#> GSM1182249 3 0.4358 0.68410 0.056 0.100 0.772 0.000 0.000 0.072
#> GSM1182250 3 0.3835 0.70328 0.048 0.068 0.812 0.000 0.000 0.072
#> GSM1182251 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 3 0.2875 0.72980 0.000 0.052 0.852 0.000 0.000 0.096
#> GSM1182253 3 0.1297 0.72088 0.000 0.012 0.948 0.000 0.000 0.040
#> GSM1182254 3 0.1909 0.71104 0.004 0.024 0.920 0.000 0.000 0.052
#> GSM1182255 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182256 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182257 5 0.1700 0.75557 0.004 0.000 0.000 0.080 0.916 0.000
#> GSM1182258 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182259 4 0.5052 0.77195 0.108 0.000 0.000 0.656 0.224 0.012
#> GSM1182260 3 0.3271 0.71831 0.020 0.060 0.844 0.000 0.000 0.076
#> GSM1182261 3 0.5543 0.63689 0.048 0.160 0.652 0.000 0.000 0.140
#> GSM1182262 3 0.4811 0.68052 0.044 0.148 0.724 0.000 0.000 0.084
#> GSM1182263 5 0.1858 0.74067 0.004 0.000 0.000 0.092 0.904 0.000
#> GSM1182264 3 0.2489 0.71666 0.012 0.000 0.860 0.000 0.000 0.128
#> GSM1182265 3 0.3940 0.70683 0.048 0.068 0.804 0.000 0.000 0.080
#> GSM1182266 3 0.1841 0.72520 0.008 0.008 0.920 0.000 0.000 0.064
#> GSM1182267 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182268 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182269 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182270 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182271 4 0.5317 0.70459 0.104 0.000 0.000 0.580 0.308 0.008
#> GSM1182272 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182273 3 0.2346 0.71884 0.008 0.000 0.868 0.000 0.000 0.124
#> GSM1182275 3 0.1672 0.70943 0.004 0.016 0.932 0.000 0.000 0.048
#> GSM1182276 6 0.5539 0.77680 0.000 0.244 0.200 0.000 0.000 0.556
#> GSM1182277 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182278 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182279 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182280 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182281 4 0.4689 0.77911 0.108 0.000 0.000 0.700 0.184 0.008
#> GSM1182282 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182283 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182284 4 0.0632 0.75902 0.000 0.000 0.000 0.976 0.024 0.000
#> GSM1182285 3 0.2805 0.70123 0.000 0.012 0.828 0.000 0.000 0.160
#> GSM1182286 2 0.1152 0.72235 0.044 0.952 0.004 0.000 0.000 0.000
#> GSM1182287 3 0.4362 0.19154 0.000 0.028 0.584 0.000 0.000 0.388
#> GSM1182288 3 0.2302 0.70235 0.000 0.008 0.872 0.000 0.000 0.120
#> GSM1182289 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182290 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182291 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182274 3 0.2986 0.72419 0.012 0.032 0.852 0.000 0.000 0.104
#> GSM1182292 2 0.5281 0.31342 0.016 0.648 0.176 0.000 0.000 0.160
#> GSM1182293 1 0.3923 0.52680 0.580 0.416 0.000 0.000 0.000 0.004
#> GSM1182294 1 0.3476 0.75335 0.732 0.260 0.004 0.000 0.000 0.004
#> GSM1182295 2 0.1007 0.72267 0.044 0.956 0.000 0.000 0.000 0.000
#> GSM1182296 2 0.1426 0.72058 0.028 0.948 0.008 0.000 0.000 0.016
#> GSM1182298 3 0.3426 0.62245 0.004 0.000 0.720 0.000 0.000 0.276
#> GSM1182299 2 0.6569 -0.40653 0.032 0.432 0.248 0.000 0.000 0.288
#> GSM1182300 2 0.1858 0.70496 0.092 0.904 0.000 0.000 0.000 0.004
#> GSM1182301 2 0.5470 0.00492 0.004 0.584 0.244 0.000 0.000 0.168
#> GSM1182303 6 0.5421 0.78332 0.000 0.212 0.208 0.000 0.000 0.580
#> GSM1182304 5 0.0146 0.82414 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM1182305 5 0.2532 0.74280 0.052 0.000 0.000 0.060 0.884 0.004
#> GSM1182306 5 0.1219 0.80037 0.048 0.000 0.000 0.004 0.948 0.000
#> GSM1182307 2 0.3434 0.66327 0.064 0.836 0.028 0.000 0.000 0.072
#> GSM1182309 1 0.2402 0.81475 0.856 0.140 0.004 0.000 0.000 0.000
#> GSM1182312 1 0.2562 0.80601 0.828 0.172 0.000 0.000 0.000 0.000
#> GSM1182314 4 0.5027 0.77264 0.108 0.000 0.000 0.660 0.220 0.012
#> GSM1182316 1 0.3500 0.78865 0.816 0.120 0.052 0.000 0.000 0.012
#> GSM1182318 2 0.5867 0.45716 0.228 0.584 0.032 0.000 0.000 0.156
#> GSM1182319 1 0.2234 0.81486 0.872 0.124 0.004 0.000 0.000 0.000
#> GSM1182320 1 0.2234 0.81486 0.872 0.124 0.004 0.000 0.000 0.000
#> GSM1182321 1 0.6110 0.28366 0.492 0.080 0.364 0.000 0.000 0.064
#> GSM1182322 1 0.2234 0.81486 0.872 0.124 0.004 0.000 0.000 0.000
#> GSM1182324 1 0.6123 0.25809 0.484 0.080 0.372 0.000 0.000 0.064
#> GSM1182297 2 0.1588 0.71552 0.072 0.924 0.000 0.000 0.000 0.004
#> GSM1182302 5 0.0000 0.82525 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182308 2 0.1152 0.72235 0.044 0.952 0.004 0.000 0.000 0.000
#> GSM1182310 1 0.2234 0.81486 0.872 0.124 0.004 0.000 0.000 0.000
#> GSM1182311 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 0.000
#> GSM1182313 4 0.5093 0.76375 0.108 0.000 0.000 0.636 0.248 0.008
#> GSM1182315 1 0.3405 0.70151 0.724 0.272 0.004 0.000 0.000 0.000
#> GSM1182317 1 0.2320 0.81453 0.864 0.132 0.004 0.000 0.000 0.000
#> GSM1182323 5 0.3578 0.68315 0.000 0.000 0.000 0.340 0.660 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:mclust 139 7.73e-02 1.0000 2
#> MAD:mclust 137 5.66e-07 0.0787 3
#> MAD:mclust 101 6.79e-06 0.1232 4
#> MAD:mclust 84 1.90e-07 0.1267 5
#> MAD:mclust 125 7.87e-08 0.2613 6
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 46361 rows and 139 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 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.960 0.980 0.0487 0.984 0.969
#> 4 4 0.617 0.693 0.821 0.2400 0.918 0.840
#> 5 5 0.622 0.655 0.825 0.1571 0.786 0.530
#> 6 6 0.543 0.483 0.664 0.0326 0.876 0.597
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0592 0.972 0.988 0.000 0.012
#> GSM1182187 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182188 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182189 1 0.1529 0.941 0.960 0.000 0.040
#> GSM1182190 3 0.5327 0.833 0.272 0.000 0.728
#> GSM1182191 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182192 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182193 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182194 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182195 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182196 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182197 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182198 2 0.0661 0.981 0.004 0.988 0.008
#> GSM1182199 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182200 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182201 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182202 1 0.3116 0.834 0.892 0.000 0.108
#> GSM1182203 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182204 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182205 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182206 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182207 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182208 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182209 2 0.6299 0.203 0.000 0.524 0.476
#> GSM1182210 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182211 2 0.1163 0.972 0.000 0.972 0.028
#> GSM1182212 2 0.4121 0.817 0.000 0.832 0.168
#> GSM1182213 2 0.0892 0.978 0.000 0.980 0.020
#> GSM1182214 2 0.0592 0.984 0.000 0.988 0.012
#> GSM1182215 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182216 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182217 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182218 3 0.6111 0.693 0.396 0.000 0.604
#> GSM1182219 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182220 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182221 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182222 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182223 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182224 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182225 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182226 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182227 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182228 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182229 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182230 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182231 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182232 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182233 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182234 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182235 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182236 1 0.0592 0.972 0.988 0.000 0.012
#> GSM1182237 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182238 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182239 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182240 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182241 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182242 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182243 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182244 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182245 1 0.0237 0.975 0.996 0.000 0.004
#> GSM1182246 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182247 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182248 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182249 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182250 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182251 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182252 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182253 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182254 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182255 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182256 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182257 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182258 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182259 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182260 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182261 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182262 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182263 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182264 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182265 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182266 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182267 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182268 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182269 1 0.1031 0.960 0.976 0.000 0.024
#> GSM1182270 3 0.4062 0.787 0.164 0.000 0.836
#> GSM1182271 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182272 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182273 2 0.0237 0.986 0.000 0.996 0.004
#> GSM1182275 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182276 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182277 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182279 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182280 1 0.0424 0.975 0.992 0.000 0.008
#> GSM1182281 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182282 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182283 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182284 1 0.0424 0.971 0.992 0.000 0.008
#> GSM1182285 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182286 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182287 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182288 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182289 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182290 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182291 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182274 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182292 2 0.1964 0.946 0.000 0.944 0.056
#> GSM1182293 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182294 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182295 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182296 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182298 2 0.0424 0.984 0.000 0.992 0.008
#> GSM1182299 2 0.1031 0.975 0.000 0.976 0.024
#> GSM1182300 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182301 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182303 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182304 1 0.1643 0.936 0.956 0.000 0.044
#> GSM1182305 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182306 1 0.0237 0.977 0.996 0.000 0.004
#> GSM1182307 2 0.1031 0.975 0.000 0.976 0.024
#> GSM1182309 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182312 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182314 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182316 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182318 2 0.1753 0.954 0.000 0.952 0.048
#> GSM1182319 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182320 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182321 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182322 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182324 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182297 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182302 1 0.1031 0.960 0.976 0.000 0.024
#> GSM1182308 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182310 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182311 1 0.1031 0.960 0.976 0.000 0.024
#> GSM1182313 1 0.0000 0.977 1.000 0.000 0.000
#> GSM1182315 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182317 2 0.0424 0.986 0.000 0.992 0.008
#> GSM1182323 1 0.6140 -0.184 0.596 0.000 0.404
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.6027 0.7522 0.088 0.000 0.252 0.660
#> GSM1182187 4 0.2814 0.7976 0.000 0.000 0.132 0.868
#> GSM1182188 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182189 4 0.6466 0.7209 0.104 0.000 0.288 0.608
#> GSM1182190 1 0.4050 0.1527 0.820 0.000 0.144 0.036
#> GSM1182191 4 0.6214 0.7396 0.092 0.000 0.272 0.636
#> GSM1182192 4 0.1867 0.7683 0.000 0.000 0.072 0.928
#> GSM1182193 4 0.2593 0.7499 0.000 0.004 0.104 0.892
#> GSM1182194 2 0.2530 0.7604 0.000 0.888 0.112 0.000
#> GSM1182195 2 0.2704 0.7616 0.000 0.876 0.124 0.000
#> GSM1182196 2 0.1722 0.8157 0.048 0.944 0.008 0.000
#> GSM1182197 2 0.0657 0.8142 0.004 0.984 0.012 0.000
#> GSM1182198 2 0.2868 0.7577 0.000 0.864 0.136 0.000
#> GSM1182199 2 0.2868 0.7582 0.000 0.864 0.136 0.000
#> GSM1182200 2 0.1406 0.8155 0.016 0.960 0.024 0.000
#> GSM1182201 2 0.1118 0.8088 0.000 0.964 0.036 0.000
#> GSM1182202 4 0.5880 0.7595 0.088 0.000 0.232 0.680
#> GSM1182203 4 0.3402 0.7944 0.004 0.000 0.164 0.832
#> GSM1182204 4 0.4538 0.7817 0.024 0.000 0.216 0.760
#> GSM1182205 2 0.1557 0.8048 0.000 0.944 0.056 0.000
#> GSM1182206 2 0.0188 0.8151 0.000 0.996 0.004 0.000
#> GSM1182207 4 0.6340 0.7299 0.096 0.000 0.284 0.620
#> GSM1182208 4 0.6340 0.7299 0.096 0.000 0.284 0.620
#> GSM1182209 1 0.4018 0.2046 0.772 0.224 0.004 0.000
#> GSM1182210 2 0.4399 0.7411 0.224 0.760 0.016 0.000
#> GSM1182211 2 0.4817 0.5156 0.388 0.612 0.000 0.000
#> GSM1182212 2 0.4019 0.7719 0.196 0.792 0.012 0.000
#> GSM1182213 2 0.4250 0.7067 0.276 0.724 0.000 0.000
#> GSM1182214 2 0.4655 0.6538 0.312 0.684 0.004 0.000
#> GSM1182215 2 0.1767 0.8125 0.012 0.944 0.044 0.000
#> GSM1182216 2 0.4741 0.7302 0.228 0.744 0.028 0.000
#> GSM1182217 4 0.4004 0.7927 0.024 0.000 0.164 0.812
#> GSM1182218 1 0.3439 0.1359 0.868 0.000 0.048 0.084
#> GSM1182219 2 0.3311 0.7799 0.172 0.828 0.000 0.000
#> GSM1182220 2 0.3486 0.7704 0.188 0.812 0.000 0.000
#> GSM1182221 2 0.5067 0.7265 0.216 0.736 0.048 0.000
#> GSM1182222 2 0.3969 0.7716 0.180 0.804 0.016 0.000
#> GSM1182223 2 0.0707 0.8118 0.000 0.980 0.020 0.000
#> GSM1182224 2 0.2469 0.7762 0.000 0.892 0.108 0.000
#> GSM1182225 2 0.3791 0.7637 0.200 0.796 0.004 0.000
#> GSM1182226 2 0.4920 0.7447 0.192 0.756 0.052 0.000
#> GSM1182227 3 0.4877 0.3769 0.000 0.000 0.592 0.408
#> GSM1182228 2 0.0707 0.8118 0.000 0.980 0.020 0.000
#> GSM1182229 2 0.0707 0.8118 0.000 0.980 0.020 0.000
#> GSM1182230 2 0.1398 0.8131 0.004 0.956 0.040 0.000
#> GSM1182231 2 0.1109 0.8168 0.028 0.968 0.004 0.000
#> GSM1182232 4 0.4849 0.7902 0.064 0.000 0.164 0.772
#> GSM1182233 4 0.6112 0.7507 0.096 0.000 0.248 0.656
#> GSM1182234 4 0.1389 0.7749 0.000 0.000 0.048 0.952
#> GSM1182235 2 0.4228 0.7385 0.232 0.760 0.008 0.000
#> GSM1182236 4 0.6080 0.6638 0.236 0.000 0.100 0.664
#> GSM1182237 2 0.2319 0.8112 0.036 0.924 0.040 0.000
#> GSM1182238 2 0.4922 0.7256 0.228 0.736 0.036 0.000
#> GSM1182239 2 0.3172 0.7887 0.160 0.840 0.000 0.000
#> GSM1182240 2 0.3751 0.7728 0.196 0.800 0.004 0.000
#> GSM1182241 2 0.0672 0.8154 0.008 0.984 0.008 0.000
#> GSM1182242 2 0.1716 0.7957 0.000 0.936 0.064 0.000
#> GSM1182243 2 0.0592 0.8126 0.000 0.984 0.016 0.000
#> GSM1182244 2 0.2149 0.7974 0.000 0.912 0.088 0.000
#> GSM1182245 4 0.2589 0.7725 0.000 0.000 0.116 0.884
#> GSM1182246 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182247 2 0.1792 0.7935 0.000 0.932 0.068 0.000
#> GSM1182248 2 0.2149 0.7806 0.000 0.912 0.088 0.000
#> GSM1182249 2 0.1936 0.8144 0.028 0.940 0.032 0.000
#> GSM1182250 2 0.1474 0.8067 0.000 0.948 0.052 0.000
#> GSM1182251 4 0.5979 0.7466 0.076 0.000 0.272 0.652
#> GSM1182252 2 0.1940 0.7885 0.000 0.924 0.076 0.000
#> GSM1182253 2 0.2408 0.7678 0.000 0.896 0.104 0.000
#> GSM1182254 2 0.1474 0.8013 0.000 0.948 0.052 0.000
#> GSM1182255 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182258 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182260 2 0.1792 0.7931 0.000 0.932 0.068 0.000
#> GSM1182261 2 0.0524 0.8160 0.004 0.988 0.008 0.000
#> GSM1182262 2 0.0707 0.8120 0.000 0.980 0.020 0.000
#> GSM1182263 4 0.4671 0.7828 0.028 0.000 0.220 0.752
#> GSM1182264 2 0.2469 0.7637 0.000 0.892 0.108 0.000
#> GSM1182265 2 0.2466 0.7917 0.004 0.900 0.096 0.000
#> GSM1182266 2 0.2081 0.7835 0.000 0.916 0.084 0.000
#> GSM1182267 4 0.2714 0.7738 0.004 0.000 0.112 0.884
#> GSM1182268 4 0.7031 0.6750 0.200 0.000 0.224 0.576
#> GSM1182269 4 0.6415 0.7234 0.100 0.000 0.288 0.612
#> GSM1182270 1 0.7372 -0.0689 0.524 0.000 0.236 0.240
#> GSM1182271 4 0.0188 0.7891 0.000 0.000 0.004 0.996
#> GSM1182272 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182273 2 0.2530 0.7604 0.000 0.888 0.112 0.000
#> GSM1182275 2 0.1022 0.8090 0.000 0.968 0.032 0.000
#> GSM1182276 2 0.3672 0.7853 0.164 0.824 0.012 0.000
#> GSM1182277 4 0.4222 0.4325 0.000 0.000 0.272 0.728
#> GSM1182278 4 0.1389 0.7740 0.000 0.000 0.048 0.952
#> GSM1182279 4 0.6164 0.7443 0.092 0.000 0.264 0.644
#> GSM1182280 4 0.6140 0.7488 0.096 0.000 0.252 0.652
#> GSM1182281 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182282 4 0.1389 0.7753 0.000 0.000 0.048 0.952
#> GSM1182283 4 0.2011 0.7637 0.000 0.000 0.080 0.920
#> GSM1182284 3 0.4999 0.2052 0.000 0.000 0.508 0.492
#> GSM1182285 2 0.2281 0.7739 0.000 0.904 0.096 0.000
#> GSM1182286 2 0.4049 0.7543 0.212 0.780 0.008 0.000
#> GSM1182287 2 0.0895 0.8133 0.004 0.976 0.020 0.000
#> GSM1182288 2 0.1637 0.7978 0.000 0.940 0.060 0.000
#> GSM1182289 4 0.5785 0.7510 0.064 0.000 0.272 0.664
#> GSM1182290 4 0.6340 0.7299 0.096 0.000 0.284 0.620
#> GSM1182291 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182274 2 0.2530 0.7640 0.000 0.888 0.112 0.000
#> GSM1182292 2 0.4477 0.6601 0.312 0.688 0.000 0.000
#> GSM1182293 2 0.4922 0.7240 0.228 0.736 0.036 0.000
#> GSM1182294 2 0.4916 0.7482 0.184 0.760 0.056 0.000
#> GSM1182295 2 0.4158 0.7456 0.224 0.768 0.008 0.000
#> GSM1182296 2 0.3873 0.7485 0.228 0.772 0.000 0.000
#> GSM1182298 2 0.4304 0.5585 0.000 0.716 0.284 0.000
#> GSM1182299 2 0.2704 0.8030 0.124 0.876 0.000 0.000
#> GSM1182300 2 0.3852 0.7676 0.192 0.800 0.008 0.000
#> GSM1182301 2 0.4088 0.7486 0.232 0.764 0.004 0.000
#> GSM1182303 2 0.3479 0.7928 0.148 0.840 0.012 0.000
#> GSM1182304 4 0.6572 0.7215 0.120 0.000 0.272 0.608
#> GSM1182305 4 0.0817 0.7940 0.000 0.000 0.024 0.976
#> GSM1182306 4 0.2011 0.7983 0.000 0.000 0.080 0.920
#> GSM1182307 1 0.4989 -0.1037 0.528 0.472 0.000 0.000
#> GSM1182309 2 0.6157 0.6324 0.232 0.660 0.108 0.000
#> GSM1182312 2 0.5599 0.6887 0.228 0.700 0.072 0.000
#> GSM1182314 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.5458 0.6910 0.236 0.704 0.060 0.000
#> GSM1182318 1 0.4994 -0.1425 0.520 0.480 0.000 0.000
#> GSM1182319 2 0.6934 0.4160 0.164 0.580 0.256 0.000
#> GSM1182320 2 0.6262 0.5699 0.280 0.628 0.092 0.000
#> GSM1182321 2 0.3497 0.7990 0.104 0.860 0.036 0.000
#> GSM1182322 3 0.6883 0.1929 0.212 0.192 0.596 0.000
#> GSM1182324 2 0.3013 0.8064 0.080 0.888 0.032 0.000
#> GSM1182297 2 0.4428 0.7017 0.276 0.720 0.004 0.000
#> GSM1182302 4 0.4957 0.7800 0.048 0.000 0.204 0.748
#> GSM1182308 2 0.4072 0.7255 0.252 0.748 0.000 0.000
#> GSM1182310 3 0.6886 0.1925 0.204 0.200 0.596 0.000
#> GSM1182311 1 0.5799 -0.0781 0.668 0.000 0.068 0.264
#> GSM1182313 4 0.0000 0.7878 0.000 0.000 0.000 1.000
#> GSM1182315 1 0.6568 0.0931 0.512 0.408 0.080 0.000
#> GSM1182317 1 0.5508 0.1955 0.692 0.252 0.056 0.000
#> GSM1182323 1 0.6031 0.0910 0.676 0.000 0.216 0.108
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.3816 0.6179 0.696 0.000 0.000 0.304 0.000
#> GSM1182187 4 0.0609 0.8542 0.020 0.000 0.000 0.980 0.000
#> GSM1182188 4 0.0000 0.8566 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0794 0.8382 0.972 0.000 0.000 0.028 0.000
#> GSM1182190 2 0.4059 0.1189 0.292 0.700 0.000 0.004 0.004
#> GSM1182191 1 0.2230 0.8415 0.884 0.000 0.000 0.116 0.000
#> GSM1182192 4 0.3089 0.7974 0.012 0.016 0.060 0.884 0.028
#> GSM1182193 5 0.6182 0.3384 0.004 0.016 0.088 0.336 0.556
#> GSM1182194 3 0.0693 0.7718 0.000 0.012 0.980 0.000 0.008
#> GSM1182195 3 0.1670 0.7544 0.000 0.012 0.936 0.000 0.052
#> GSM1182196 3 0.3210 0.7353 0.000 0.212 0.788 0.000 0.000
#> GSM1182197 3 0.3234 0.7839 0.008 0.144 0.836 0.000 0.012
#> GSM1182198 3 0.2835 0.6923 0.004 0.016 0.868 0.000 0.112
#> GSM1182199 3 0.2818 0.6772 0.000 0.012 0.856 0.000 0.132
#> GSM1182200 3 0.3053 0.7912 0.008 0.128 0.852 0.000 0.012
#> GSM1182201 3 0.1869 0.7927 0.016 0.036 0.936 0.000 0.012
#> GSM1182202 4 0.3003 0.7391 0.188 0.000 0.000 0.812 0.000
#> GSM1182203 4 0.1270 0.8442 0.052 0.000 0.000 0.948 0.000
#> GSM1182204 4 0.1608 0.8353 0.072 0.000 0.000 0.928 0.000
#> GSM1182205 3 0.0898 0.7919 0.000 0.020 0.972 0.000 0.008
#> GSM1182206 3 0.3093 0.7684 0.000 0.168 0.824 0.000 0.008
#> GSM1182207 1 0.1408 0.8446 0.948 0.008 0.000 0.044 0.000
#> GSM1182208 1 0.0865 0.8350 0.972 0.004 0.000 0.024 0.000
#> GSM1182209 2 0.0880 0.6094 0.000 0.968 0.032 0.000 0.000
#> GSM1182210 2 0.4283 0.1995 0.000 0.544 0.456 0.000 0.000
#> GSM1182211 2 0.1851 0.6633 0.000 0.912 0.088 0.000 0.000
#> GSM1182212 3 0.3942 0.6726 0.000 0.260 0.728 0.000 0.012
#> GSM1182213 2 0.4302 0.1166 0.000 0.520 0.480 0.000 0.000
#> GSM1182214 2 0.1608 0.6533 0.000 0.928 0.072 0.000 0.000
#> GSM1182215 3 0.3705 0.7810 0.000 0.120 0.816 0.000 0.064
#> GSM1182216 2 0.2773 0.6779 0.000 0.836 0.164 0.000 0.000
#> GSM1182217 4 0.2424 0.7981 0.132 0.000 0.000 0.868 0.000
#> GSM1182218 2 0.4377 0.1466 0.248 0.720 0.000 0.028 0.004
#> GSM1182219 3 0.3949 0.5539 0.000 0.332 0.668 0.000 0.000
#> GSM1182220 3 0.4030 0.5025 0.000 0.352 0.648 0.000 0.000
#> GSM1182221 2 0.3388 0.6769 0.000 0.792 0.200 0.000 0.008
#> GSM1182222 3 0.4088 0.4675 0.000 0.368 0.632 0.000 0.000
#> GSM1182223 3 0.2416 0.7962 0.000 0.100 0.888 0.000 0.012
#> GSM1182224 3 0.0880 0.7766 0.000 0.000 0.968 0.000 0.032
#> GSM1182225 3 0.4302 0.0381 0.000 0.480 0.520 0.000 0.000
#> GSM1182226 2 0.4508 0.5221 0.000 0.648 0.332 0.000 0.020
#> GSM1182227 5 0.1410 0.6736 0.000 0.000 0.000 0.060 0.940
#> GSM1182228 3 0.2416 0.7962 0.000 0.100 0.888 0.000 0.012
#> GSM1182229 3 0.1894 0.7985 0.000 0.072 0.920 0.000 0.008
#> GSM1182230 3 0.3229 0.7858 0.000 0.128 0.840 0.000 0.032
#> GSM1182231 3 0.3519 0.7275 0.000 0.216 0.776 0.000 0.008
#> GSM1182232 4 0.4415 0.3560 0.388 0.000 0.000 0.604 0.008
#> GSM1182233 1 0.2852 0.7902 0.828 0.000 0.000 0.172 0.000
#> GSM1182234 4 0.4675 0.7535 0.108 0.012 0.016 0.784 0.080
#> GSM1182235 2 0.3895 0.5509 0.000 0.680 0.320 0.000 0.000
#> GSM1182236 4 0.6104 0.3903 0.296 0.140 0.000 0.560 0.004
#> GSM1182237 3 0.4100 0.7376 0.000 0.192 0.764 0.000 0.044
#> GSM1182238 2 0.2471 0.6751 0.000 0.864 0.136 0.000 0.000
#> GSM1182239 3 0.3983 0.5380 0.000 0.340 0.660 0.000 0.000
#> GSM1182240 3 0.3949 0.5516 0.000 0.332 0.668 0.000 0.000
#> GSM1182241 3 0.2848 0.7761 0.000 0.156 0.840 0.000 0.004
#> GSM1182242 3 0.0981 0.7842 0.008 0.008 0.972 0.000 0.012
#> GSM1182243 3 0.2230 0.7943 0.000 0.116 0.884 0.000 0.000
#> GSM1182244 3 0.1997 0.7946 0.000 0.040 0.924 0.000 0.036
#> GSM1182245 4 0.3340 0.7841 0.044 0.016 0.056 0.872 0.012
#> GSM1182246 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182247 3 0.0566 0.7851 0.000 0.004 0.984 0.000 0.012
#> GSM1182248 3 0.0854 0.7771 0.008 0.004 0.976 0.000 0.012
#> GSM1182249 3 0.3438 0.7611 0.000 0.172 0.808 0.000 0.020
#> GSM1182250 3 0.1809 0.7994 0.000 0.060 0.928 0.000 0.012
#> GSM1182251 1 0.3003 0.8001 0.812 0.000 0.000 0.188 0.000
#> GSM1182252 3 0.0404 0.7888 0.000 0.012 0.988 0.000 0.000
#> GSM1182253 3 0.1200 0.7692 0.008 0.012 0.964 0.000 0.016
#> GSM1182254 3 0.1012 0.7912 0.000 0.020 0.968 0.000 0.012
#> GSM1182255 4 0.0000 0.8566 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182257 4 0.0000 0.8566 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182259 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182260 3 0.1314 0.7852 0.016 0.012 0.960 0.000 0.012
#> GSM1182261 3 0.3284 0.7778 0.000 0.148 0.828 0.000 0.024
#> GSM1182262 3 0.2464 0.7975 0.000 0.096 0.888 0.000 0.016
#> GSM1182263 1 0.3109 0.7791 0.800 0.000 0.000 0.200 0.000
#> GSM1182264 3 0.2140 0.7439 0.040 0.012 0.924 0.000 0.024
#> GSM1182265 3 0.3694 0.7298 0.020 0.024 0.824 0.000 0.132
#> GSM1182266 3 0.1701 0.7564 0.028 0.012 0.944 0.000 0.016
#> GSM1182267 1 0.5686 0.5078 0.624 0.008 0.012 0.060 0.296
#> GSM1182268 1 0.1386 0.8236 0.952 0.032 0.000 0.016 0.000
#> GSM1182269 1 0.1205 0.8405 0.956 0.004 0.000 0.040 0.000
#> GSM1182270 4 0.5965 0.1988 0.392 0.112 0.000 0.496 0.000
#> GSM1182271 4 0.0000 0.8566 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182273 3 0.1787 0.7483 0.032 0.012 0.940 0.000 0.016
#> GSM1182275 3 0.1809 0.7981 0.000 0.060 0.928 0.000 0.012
#> GSM1182276 3 0.3884 0.6327 0.000 0.288 0.708 0.000 0.004
#> GSM1182277 5 0.4297 0.5834 0.036 0.000 0.008 0.200 0.756
#> GSM1182278 4 0.4181 0.4806 0.000 0.004 0.004 0.676 0.316
#> GSM1182279 1 0.1792 0.8488 0.916 0.000 0.000 0.084 0.000
#> GSM1182280 1 0.1792 0.8481 0.916 0.000 0.000 0.084 0.000
#> GSM1182281 4 0.1043 0.8396 0.000 0.000 0.000 0.960 0.040
#> GSM1182282 4 0.5026 0.6822 0.196 0.016 0.016 0.732 0.040
#> GSM1182283 4 0.6002 0.1330 0.008 0.012 0.060 0.524 0.396
#> GSM1182284 5 0.1851 0.6750 0.000 0.000 0.000 0.088 0.912
#> GSM1182285 3 0.0451 0.7792 0.000 0.004 0.988 0.000 0.008
#> GSM1182286 2 0.4262 0.2645 0.000 0.560 0.440 0.000 0.000
#> GSM1182287 3 0.2771 0.7888 0.000 0.128 0.860 0.000 0.012
#> GSM1182288 3 0.0798 0.7902 0.000 0.016 0.976 0.000 0.008
#> GSM1182289 1 0.2813 0.8009 0.832 0.000 0.000 0.168 0.000
#> GSM1182290 1 0.1282 0.8430 0.952 0.004 0.000 0.044 0.000
#> GSM1182291 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182274 3 0.2312 0.7402 0.060 0.016 0.912 0.000 0.012
#> GSM1182292 2 0.4171 0.3694 0.000 0.604 0.396 0.000 0.000
#> GSM1182293 2 0.3424 0.6444 0.000 0.760 0.240 0.000 0.000
#> GSM1182294 2 0.4980 0.0483 0.000 0.488 0.484 0.000 0.028
#> GSM1182295 2 0.4201 0.3641 0.000 0.592 0.408 0.000 0.000
#> GSM1182296 2 0.4305 0.0510 0.000 0.512 0.488 0.000 0.000
#> GSM1182298 3 0.4527 0.1989 0.000 0.012 0.596 0.000 0.392
#> GSM1182299 3 0.4793 0.6728 0.056 0.236 0.704 0.000 0.004
#> GSM1182300 3 0.4359 0.3204 0.000 0.412 0.584 0.000 0.004
#> GSM1182301 3 0.4235 0.2979 0.000 0.424 0.576 0.000 0.000
#> GSM1182303 3 0.3582 0.7181 0.000 0.224 0.768 0.000 0.008
#> GSM1182304 1 0.1697 0.8464 0.932 0.008 0.000 0.060 0.000
#> GSM1182305 4 0.1908 0.8250 0.092 0.000 0.000 0.908 0.000
#> GSM1182306 4 0.0609 0.8542 0.020 0.000 0.000 0.980 0.000
#> GSM1182307 2 0.1544 0.6510 0.000 0.932 0.068 0.000 0.000
#> GSM1182309 2 0.2012 0.6413 0.000 0.920 0.060 0.000 0.020
#> GSM1182312 2 0.2110 0.6494 0.000 0.912 0.072 0.000 0.016
#> GSM1182314 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182316 2 0.4374 0.5981 0.000 0.700 0.272 0.000 0.028
#> GSM1182318 2 0.1341 0.6404 0.000 0.944 0.056 0.000 0.000
#> GSM1182319 5 0.6234 0.0262 0.000 0.304 0.172 0.000 0.524
#> GSM1182320 2 0.2505 0.6599 0.000 0.888 0.092 0.000 0.020
#> GSM1182321 3 0.4987 0.6501 0.000 0.236 0.684 0.000 0.080
#> GSM1182322 5 0.2891 0.6390 0.000 0.176 0.000 0.000 0.824
#> GSM1182324 3 0.4237 0.7271 0.000 0.200 0.752 0.000 0.048
#> GSM1182297 2 0.2179 0.6729 0.000 0.888 0.112 0.000 0.000
#> GSM1182302 4 0.2377 0.8004 0.128 0.000 0.000 0.872 0.000
#> GSM1182308 2 0.3774 0.5886 0.000 0.704 0.296 0.000 0.000
#> GSM1182310 5 0.2286 0.6674 0.000 0.108 0.004 0.000 0.888
#> GSM1182311 1 0.7025 -0.0324 0.376 0.288 0.000 0.008 0.328
#> GSM1182313 4 0.0162 0.8569 0.000 0.000 0.000 0.996 0.004
#> GSM1182315 2 0.1549 0.6168 0.000 0.944 0.040 0.000 0.016
#> GSM1182317 2 0.0865 0.5978 0.000 0.972 0.024 0.000 0.004
#> GSM1182323 2 0.5786 -0.2917 0.380 0.524 0.000 0.096 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.4396 0.09342 0.000 0.000 0.000 0.456 0.520 0.024
#> GSM1182187 4 0.0993 0.80958 0.000 0.000 0.000 0.964 0.024 0.012
#> GSM1182188 4 0.0146 0.81843 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182189 5 0.0777 0.76488 0.000 0.000 0.004 0.000 0.972 0.024
#> GSM1182190 6 0.5819 0.65085 0.000 0.368 0.000 0.000 0.188 0.444
#> GSM1182191 5 0.2170 0.77239 0.000 0.000 0.000 0.100 0.888 0.012
#> GSM1182192 4 0.7185 0.31569 0.080 0.000 0.164 0.552 0.080 0.124
#> GSM1182193 1 0.7583 0.42273 0.472 0.000 0.120 0.248 0.080 0.080
#> GSM1182194 3 0.2065 0.49942 0.004 0.032 0.912 0.000 0.000 0.052
#> GSM1182195 3 0.3126 0.46125 0.044 0.028 0.856 0.000 0.000 0.072
#> GSM1182196 2 0.4322 0.03899 0.000 0.528 0.452 0.000 0.000 0.020
#> GSM1182197 3 0.5457 0.20270 0.000 0.444 0.448 0.000 0.004 0.104
#> GSM1182198 3 0.4082 0.30681 0.068 0.012 0.764 0.000 0.000 0.156
#> GSM1182199 3 0.4222 0.36318 0.120 0.016 0.764 0.000 0.000 0.100
#> GSM1182200 3 0.4269 0.50465 0.000 0.316 0.648 0.000 0.000 0.036
#> GSM1182201 3 0.4443 0.55832 0.000 0.232 0.696 0.000 0.004 0.068
#> GSM1182202 4 0.2867 0.73435 0.000 0.000 0.000 0.848 0.112 0.040
#> GSM1182203 4 0.1151 0.80781 0.000 0.000 0.000 0.956 0.032 0.012
#> GSM1182204 4 0.1225 0.80622 0.000 0.000 0.000 0.952 0.036 0.012
#> GSM1182205 3 0.2821 0.54893 0.004 0.096 0.860 0.000 0.000 0.040
#> GSM1182206 3 0.4498 0.33105 0.004 0.428 0.544 0.000 0.000 0.024
#> GSM1182207 5 0.1700 0.77748 0.000 0.000 0.000 0.024 0.928 0.048
#> GSM1182208 5 0.1644 0.75578 0.000 0.000 0.000 0.004 0.920 0.076
#> GSM1182209 2 0.3940 -0.26692 0.000 0.652 0.008 0.000 0.004 0.336
#> GSM1182210 2 0.4769 0.52295 0.000 0.656 0.240 0.000 0.000 0.104
#> GSM1182211 2 0.3377 0.28805 0.000 0.784 0.028 0.000 0.000 0.188
#> GSM1182212 2 0.4705 0.01391 0.000 0.484 0.472 0.000 0.000 0.044
#> GSM1182213 2 0.4783 0.48196 0.000 0.616 0.308 0.000 0.000 0.076
#> GSM1182214 2 0.3123 0.58772 0.000 0.824 0.136 0.000 0.000 0.040
#> GSM1182215 3 0.5972 0.38164 0.092 0.360 0.504 0.000 0.000 0.044
#> GSM1182216 2 0.4949 0.51244 0.008 0.664 0.216 0.000 0.000 0.112
#> GSM1182217 4 0.2383 0.75847 0.000 0.000 0.000 0.880 0.096 0.024
#> GSM1182218 6 0.6170 0.62414 0.000 0.396 0.000 0.032 0.132 0.440
#> GSM1182219 2 0.4150 0.25623 0.000 0.592 0.392 0.000 0.000 0.016
#> GSM1182220 2 0.4276 0.22606 0.000 0.564 0.416 0.000 0.000 0.020
#> GSM1182221 2 0.3424 0.57024 0.000 0.772 0.204 0.000 0.000 0.024
#> GSM1182222 2 0.4386 0.35721 0.004 0.620 0.348 0.000 0.000 0.028
#> GSM1182223 3 0.3584 0.52514 0.000 0.308 0.688 0.000 0.000 0.004
#> GSM1182224 3 0.4545 0.56139 0.068 0.148 0.744 0.000 0.000 0.040
#> GSM1182225 2 0.4594 0.37792 0.000 0.608 0.340 0.000 0.000 0.052
#> GSM1182226 2 0.5573 0.47011 0.052 0.624 0.240 0.000 0.000 0.084
#> GSM1182227 1 0.2708 0.54501 0.884 0.004 0.004 0.072 0.012 0.024
#> GSM1182228 3 0.3725 0.52096 0.000 0.316 0.676 0.000 0.000 0.008
#> GSM1182229 3 0.4110 0.45304 0.000 0.376 0.608 0.000 0.000 0.016
#> GSM1182230 3 0.4825 0.32189 0.012 0.432 0.524 0.000 0.000 0.032
#> GSM1182231 3 0.4664 0.16941 0.004 0.476 0.488 0.000 0.000 0.032
#> GSM1182232 4 0.4950 0.20412 0.032 0.000 0.000 0.540 0.408 0.020
#> GSM1182233 5 0.3220 0.73126 0.000 0.000 0.016 0.088 0.844 0.052
#> GSM1182234 4 0.7900 0.03084 0.208 0.000 0.072 0.448 0.156 0.116
#> GSM1182235 2 0.4325 0.51672 0.000 0.692 0.244 0.000 0.000 0.064
#> GSM1182236 6 0.7965 0.40118 0.028 0.132 0.000 0.292 0.224 0.324
#> GSM1182237 2 0.5861 -0.16364 0.068 0.448 0.436 0.000 0.000 0.048
#> GSM1182238 2 0.4867 0.52612 0.016 0.684 0.208 0.000 0.000 0.092
#> GSM1182239 2 0.4580 0.36315 0.000 0.612 0.336 0.000 0.000 0.052
#> GSM1182240 2 0.4453 0.38522 0.000 0.624 0.332 0.000 0.000 0.044
#> GSM1182241 3 0.3993 0.39057 0.000 0.400 0.592 0.000 0.000 0.008
#> GSM1182242 3 0.2956 0.56518 0.000 0.120 0.840 0.000 0.000 0.040
#> GSM1182243 3 0.4109 0.38039 0.000 0.412 0.576 0.000 0.000 0.012
#> GSM1182244 3 0.5304 0.53097 0.060 0.280 0.620 0.000 0.000 0.040
#> GSM1182245 4 0.7167 0.14389 0.020 0.000 0.212 0.468 0.068 0.232
#> GSM1182246 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 3 0.3133 0.57916 0.000 0.212 0.780 0.000 0.000 0.008
#> GSM1182248 3 0.2968 0.58214 0.000 0.168 0.816 0.000 0.000 0.016
#> GSM1182249 3 0.4722 0.19071 0.012 0.476 0.488 0.000 0.000 0.024
#> GSM1182250 3 0.4922 0.40916 0.020 0.392 0.556 0.000 0.000 0.032
#> GSM1182251 5 0.2593 0.73770 0.000 0.000 0.000 0.148 0.844 0.008
#> GSM1182252 3 0.3974 0.54427 0.000 0.296 0.680 0.000 0.000 0.024
#> GSM1182253 3 0.2696 0.50137 0.004 0.048 0.872 0.000 0.000 0.076
#> GSM1182254 3 0.4062 0.52646 0.000 0.316 0.660 0.000 0.000 0.024
#> GSM1182255 4 0.0146 0.81772 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182256 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182258 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 3 0.5425 0.43757 0.008 0.364 0.548 0.000 0.012 0.068
#> GSM1182261 3 0.5754 0.29463 0.044 0.412 0.480 0.000 0.000 0.064
#> GSM1182262 3 0.5019 0.45536 0.020 0.356 0.580 0.000 0.000 0.044
#> GSM1182263 5 0.2911 0.73926 0.000 0.000 0.000 0.144 0.832 0.024
#> GSM1182264 3 0.6121 0.50749 0.028 0.248 0.592 0.000 0.032 0.100
#> GSM1182265 3 0.7180 0.19509 0.200 0.360 0.364 0.000 0.012 0.064
#> GSM1182266 3 0.4496 0.55673 0.004 0.176 0.728 0.000 0.008 0.084
#> GSM1182267 5 0.5911 0.16313 0.412 0.000 0.012 0.036 0.480 0.060
#> GSM1182268 5 0.2263 0.74892 0.016 0.000 0.000 0.000 0.884 0.100
#> GSM1182269 5 0.5220 0.45927 0.000 0.000 0.052 0.044 0.632 0.272
#> GSM1182270 6 0.7238 0.66982 0.000 0.204 0.004 0.100 0.276 0.416
#> GSM1182271 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 3 0.4968 0.54599 0.016 0.164 0.712 0.000 0.016 0.092
#> GSM1182275 3 0.3552 0.48634 0.000 0.116 0.800 0.000 0.000 0.084
#> GSM1182276 2 0.5074 0.07825 0.000 0.472 0.452 0.000 0.000 0.076
#> GSM1182277 1 0.3766 0.55009 0.764 0.000 0.012 0.204 0.008 0.012
#> GSM1182278 4 0.4488 -0.10065 0.468 0.000 0.016 0.508 0.000 0.008
#> GSM1182279 5 0.1333 0.78466 0.000 0.000 0.000 0.048 0.944 0.008
#> GSM1182280 5 0.1564 0.77851 0.000 0.000 0.000 0.040 0.936 0.024
#> GSM1182281 4 0.2669 0.73178 0.024 0.000 0.004 0.864 0.000 0.108
#> GSM1182282 4 0.8090 -0.03435 0.084 0.000 0.088 0.396 0.232 0.200
#> GSM1182283 1 0.5054 0.27460 0.544 0.000 0.016 0.400 0.036 0.004
#> GSM1182284 1 0.2196 0.56211 0.884 0.000 0.004 0.108 0.000 0.004
#> GSM1182285 3 0.2772 0.55014 0.004 0.092 0.864 0.000 0.000 0.040
#> GSM1182286 2 0.3956 0.51969 0.000 0.704 0.264 0.000 0.000 0.032
#> GSM1182287 3 0.4065 0.52225 0.000 0.300 0.672 0.000 0.000 0.028
#> GSM1182288 3 0.2956 0.56114 0.000 0.120 0.840 0.000 0.000 0.040
#> GSM1182289 5 0.2954 0.76279 0.000 0.000 0.000 0.108 0.844 0.048
#> GSM1182290 5 0.1950 0.77161 0.000 0.000 0.000 0.024 0.912 0.064
#> GSM1182291 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.7239 0.31082 0.024 0.312 0.436 0.000 0.076 0.152
#> GSM1182292 2 0.5165 0.38717 0.000 0.616 0.156 0.000 0.000 0.228
#> GSM1182293 2 0.3134 0.58687 0.000 0.820 0.144 0.000 0.000 0.036
#> GSM1182294 2 0.3678 0.55483 0.008 0.748 0.228 0.000 0.000 0.016
#> GSM1182295 2 0.3221 0.58726 0.000 0.792 0.188 0.000 0.000 0.020
#> GSM1182296 2 0.4734 0.51780 0.000 0.672 0.208 0.000 0.000 0.120
#> GSM1182298 3 0.4667 0.30320 0.164 0.020 0.720 0.000 0.000 0.096
#> GSM1182299 2 0.5473 0.10664 0.000 0.520 0.392 0.000 0.036 0.052
#> GSM1182300 2 0.3582 0.53422 0.000 0.732 0.252 0.000 0.000 0.016
#> GSM1182301 2 0.5565 0.34287 0.000 0.552 0.208 0.000 0.000 0.240
#> GSM1182303 3 0.4523 0.10725 0.000 0.452 0.516 0.000 0.000 0.032
#> GSM1182304 5 0.1745 0.76221 0.000 0.000 0.000 0.020 0.924 0.056
#> GSM1182305 4 0.3269 0.67489 0.000 0.000 0.000 0.792 0.184 0.024
#> GSM1182306 4 0.1434 0.80035 0.000 0.000 0.000 0.940 0.048 0.012
#> GSM1182307 2 0.2623 0.38987 0.000 0.852 0.016 0.000 0.000 0.132
#> GSM1182309 2 0.2924 0.57257 0.024 0.864 0.084 0.000 0.000 0.028
#> GSM1182312 2 0.2673 0.59143 0.004 0.852 0.132 0.000 0.000 0.012
#> GSM1182314 4 0.0000 0.81900 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 2 0.4233 0.57790 0.024 0.768 0.148 0.000 0.004 0.056
#> GSM1182318 2 0.2278 0.59242 0.000 0.868 0.128 0.000 0.000 0.004
#> GSM1182319 2 0.6521 0.07826 0.316 0.488 0.088 0.000 0.000 0.108
#> GSM1182320 2 0.3928 0.41184 0.008 0.764 0.052 0.000 0.000 0.176
#> GSM1182321 3 0.5875 0.03075 0.024 0.376 0.488 0.000 0.000 0.112
#> GSM1182322 1 0.4536 0.15301 0.560 0.408 0.004 0.000 0.000 0.028
#> GSM1182324 2 0.4867 -0.00266 0.020 0.504 0.452 0.000 0.000 0.024
#> GSM1182297 2 0.4305 0.54438 0.000 0.708 0.216 0.000 0.000 0.076
#> GSM1182302 4 0.1895 0.78186 0.000 0.000 0.000 0.912 0.072 0.016
#> GSM1182308 2 0.3766 0.58087 0.000 0.748 0.212 0.000 0.000 0.040
#> GSM1182310 1 0.3874 0.37006 0.732 0.228 0.000 0.000 0.000 0.040
#> GSM1182311 1 0.6908 -0.08584 0.396 0.072 0.000 0.008 0.384 0.140
#> GSM1182313 4 0.0146 0.81843 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182315 2 0.2471 0.53324 0.020 0.896 0.040 0.000 0.000 0.044
#> GSM1182317 2 0.1858 0.50234 0.000 0.912 0.012 0.000 0.000 0.076
#> GSM1182323 6 0.6741 0.66429 0.000 0.228 0.000 0.048 0.300 0.424
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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> MAD:NMF 139 7.73e-02 1.0000 2
#> MAD:NMF 137 7.12e-02 0.8683 3
#> MAD:NMF 123 2.44e-01 1.0000 4
#> MAD:NMF 116 4.88e-05 0.0337 5
#> MAD:NMF 80 7.16e-05 0.1638 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.47910 0.521 0.521
#> 3 3 0.967 0.974 0.987 0.14848 0.928 0.861
#> 4 4 1.000 0.978 0.991 0.04205 0.979 0.954
#> 5 5 0.997 0.967 0.985 0.01213 0.991 0.978
#> 6 6 0.986 0.948 0.977 0.00601 0.999 0.998
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.556 0.586 0.300 0 0.700
#> GSM1182187 3 0.000 0.951 0.000 0 1.000
#> GSM1182188 3 0.000 0.951 0.000 0 1.000
#> GSM1182189 1 0.000 0.970 1.000 0 0.000
#> GSM1182190 1 0.000 0.970 1.000 0 0.000
#> GSM1182191 3 0.556 0.586 0.300 0 0.700
#> GSM1182192 1 0.000 0.970 1.000 0 0.000
#> GSM1182193 1 0.000 0.970 1.000 0 0.000
#> GSM1182194 2 0.000 1.000 0.000 1 0.000
#> GSM1182195 2 0.000 1.000 0.000 1 0.000
#> GSM1182196 2 0.000 1.000 0.000 1 0.000
#> GSM1182197 2 0.000 1.000 0.000 1 0.000
#> GSM1182198 2 0.000 1.000 0.000 1 0.000
#> GSM1182199 2 0.000 1.000 0.000 1 0.000
#> GSM1182200 2 0.000 1.000 0.000 1 0.000
#> GSM1182201 2 0.000 1.000 0.000 1 0.000
#> GSM1182202 3 0.000 0.951 0.000 0 1.000
#> GSM1182203 3 0.000 0.951 0.000 0 1.000
#> GSM1182204 3 0.000 0.951 0.000 0 1.000
#> GSM1182205 2 0.000 1.000 0.000 1 0.000
#> GSM1182206 2 0.000 1.000 0.000 1 0.000
#> GSM1182207 1 0.000 0.970 1.000 0 0.000
#> GSM1182208 1 0.000 0.970 1.000 0 0.000
#> GSM1182209 2 0.000 1.000 0.000 1 0.000
#> GSM1182210 2 0.000 1.000 0.000 1 0.000
#> GSM1182211 2 0.000 1.000 0.000 1 0.000
#> GSM1182212 2 0.000 1.000 0.000 1 0.000
#> GSM1182213 2 0.000 1.000 0.000 1 0.000
#> GSM1182214 2 0.000 1.000 0.000 1 0.000
#> GSM1182215 2 0.000 1.000 0.000 1 0.000
#> GSM1182216 2 0.000 1.000 0.000 1 0.000
#> GSM1182217 3 0.556 0.586 0.300 0 0.700
#> GSM1182218 1 0.000 0.970 1.000 0 0.000
#> GSM1182219 2 0.000 1.000 0.000 1 0.000
#> GSM1182220 2 0.000 1.000 0.000 1 0.000
#> GSM1182221 2 0.000 1.000 0.000 1 0.000
#> GSM1182222 2 0.000 1.000 0.000 1 0.000
#> GSM1182223 2 0.000 1.000 0.000 1 0.000
#> GSM1182224 2 0.000 1.000 0.000 1 0.000
#> GSM1182225 2 0.000 1.000 0.000 1 0.000
#> GSM1182226 2 0.000 1.000 0.000 1 0.000
#> GSM1182227 1 0.000 0.970 1.000 0 0.000
#> GSM1182228 2 0.000 1.000 0.000 1 0.000
#> GSM1182229 2 0.000 1.000 0.000 1 0.000
#> GSM1182230 2 0.000 1.000 0.000 1 0.000
#> GSM1182231 2 0.000 1.000 0.000 1 0.000
#> GSM1182232 1 0.000 0.970 1.000 0 0.000
#> GSM1182233 1 0.000 0.970 1.000 0 0.000
#> GSM1182234 1 0.000 0.970 1.000 0 0.000
#> GSM1182235 2 0.000 1.000 0.000 1 0.000
#> GSM1182236 1 0.000 0.970 1.000 0 0.000
#> GSM1182237 2 0.000 1.000 0.000 1 0.000
#> GSM1182238 2 0.000 1.000 0.000 1 0.000
#> GSM1182239 2 0.000 1.000 0.000 1 0.000
#> GSM1182240 2 0.000 1.000 0.000 1 0.000
#> GSM1182241 2 0.000 1.000 0.000 1 0.000
#> GSM1182242 2 0.000 1.000 0.000 1 0.000
#> GSM1182243 2 0.000 1.000 0.000 1 0.000
#> GSM1182244 2 0.000 1.000 0.000 1 0.000
#> GSM1182245 1 0.000 0.970 1.000 0 0.000
#> GSM1182246 3 0.000 0.951 0.000 0 1.000
#> GSM1182247 2 0.000 1.000 0.000 1 0.000
#> GSM1182248 2 0.000 1.000 0.000 1 0.000
#> GSM1182249 2 0.000 1.000 0.000 1 0.000
#> GSM1182250 2 0.000 1.000 0.000 1 0.000
#> GSM1182251 1 0.312 0.898 0.892 0 0.108
#> GSM1182252 2 0.000 1.000 0.000 1 0.000
#> GSM1182253 2 0.000 1.000 0.000 1 0.000
#> GSM1182254 2 0.000 1.000 0.000 1 0.000
#> GSM1182255 3 0.000 0.951 0.000 0 1.000
#> GSM1182256 3 0.000 0.951 0.000 0 1.000
#> GSM1182257 3 0.000 0.951 0.000 0 1.000
#> GSM1182258 3 0.000 0.951 0.000 0 1.000
#> GSM1182259 3 0.000 0.951 0.000 0 1.000
#> GSM1182260 2 0.000 1.000 0.000 1 0.000
#> GSM1182261 2 0.000 1.000 0.000 1 0.000
#> GSM1182262 2 0.000 1.000 0.000 1 0.000
#> GSM1182263 1 0.312 0.898 0.892 0 0.108
#> GSM1182264 2 0.000 1.000 0.000 1 0.000
#> GSM1182265 2 0.000 1.000 0.000 1 0.000
#> GSM1182266 2 0.000 1.000 0.000 1 0.000
#> GSM1182267 1 0.000 0.970 1.000 0 0.000
#> GSM1182268 1 0.000 0.970 1.000 0 0.000
#> GSM1182269 1 0.000 0.970 1.000 0 0.000
#> GSM1182270 1 0.000 0.970 1.000 0 0.000
#> GSM1182271 3 0.000 0.951 0.000 0 1.000
#> GSM1182272 3 0.000 0.951 0.000 0 1.000
#> GSM1182273 2 0.000 1.000 0.000 1 0.000
#> GSM1182275 2 0.000 1.000 0.000 1 0.000
#> GSM1182276 2 0.000 1.000 0.000 1 0.000
#> GSM1182277 1 0.000 0.970 1.000 0 0.000
#> GSM1182278 1 0.000 0.970 1.000 0 0.000
#> GSM1182279 1 0.312 0.898 0.892 0 0.108
#> GSM1182280 1 0.312 0.898 0.892 0 0.108
#> GSM1182281 1 0.312 0.898 0.892 0 0.108
#> GSM1182282 1 0.000 0.970 1.000 0 0.000
#> GSM1182283 1 0.000 0.970 1.000 0 0.000
#> GSM1182284 1 0.000 0.970 1.000 0 0.000
#> GSM1182285 2 0.000 1.000 0.000 1 0.000
#> GSM1182286 2 0.000 1.000 0.000 1 0.000
#> GSM1182287 2 0.000 1.000 0.000 1 0.000
#> GSM1182288 2 0.000 1.000 0.000 1 0.000
#> GSM1182289 1 0.312 0.898 0.892 0 0.108
#> GSM1182290 1 0.000 0.970 1.000 0 0.000
#> GSM1182291 3 0.000 0.951 0.000 0 1.000
#> GSM1182274 2 0.000 1.000 0.000 1 0.000
#> GSM1182292 2 0.000 1.000 0.000 1 0.000
#> GSM1182293 2 0.000 1.000 0.000 1 0.000
#> GSM1182294 2 0.000 1.000 0.000 1 0.000
#> GSM1182295 2 0.000 1.000 0.000 1 0.000
#> GSM1182296 2 0.000 1.000 0.000 1 0.000
#> GSM1182298 2 0.000 1.000 0.000 1 0.000
#> GSM1182299 2 0.000 1.000 0.000 1 0.000
#> GSM1182300 2 0.000 1.000 0.000 1 0.000
#> GSM1182301 2 0.000 1.000 0.000 1 0.000
#> GSM1182303 2 0.000 1.000 0.000 1 0.000
#> GSM1182304 1 0.312 0.898 0.892 0 0.108
#> GSM1182305 1 0.319 0.894 0.888 0 0.112
#> GSM1182306 3 0.000 0.951 0.000 0 1.000
#> GSM1182307 2 0.000 1.000 0.000 1 0.000
#> GSM1182309 2 0.000 1.000 0.000 1 0.000
#> GSM1182312 2 0.000 1.000 0.000 1 0.000
#> GSM1182314 3 0.000 0.951 0.000 0 1.000
#> GSM1182316 2 0.000 1.000 0.000 1 0.000
#> GSM1182318 2 0.000 1.000 0.000 1 0.000
#> GSM1182319 2 0.000 1.000 0.000 1 0.000
#> GSM1182320 2 0.000 1.000 0.000 1 0.000
#> GSM1182321 2 0.000 1.000 0.000 1 0.000
#> GSM1182322 2 0.000 1.000 0.000 1 0.000
#> GSM1182324 2 0.000 1.000 0.000 1 0.000
#> GSM1182297 2 0.000 1.000 0.000 1 0.000
#> GSM1182302 3 0.000 0.951 0.000 0 1.000
#> GSM1182308 2 0.000 1.000 0.000 1 0.000
#> GSM1182310 2 0.000 1.000 0.000 1 0.000
#> GSM1182311 1 0.000 0.970 1.000 0 0.000
#> GSM1182313 3 0.000 0.951 0.000 0 1.000
#> GSM1182315 2 0.000 1.000 0.000 1 0.000
#> GSM1182317 2 0.000 1.000 0.000 1 0.000
#> GSM1182323 1 0.000 0.970 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.4888 0.376 0.000 0 0.412 0.588
#> GSM1182187 4 0.0469 0.927 0.000 0 0.012 0.988
#> GSM1182188 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182189 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182191 4 0.4888 0.376 0.000 0 0.412 0.588
#> GSM1182192 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182193 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182202 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182203 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182204 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182207 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182208 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182217 4 0.4888 0.376 0.000 0 0.412 0.588
#> GSM1182218 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182227 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182232 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182236 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182245 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182246 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182251 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182255 4 0.0469 0.927 0.000 0 0.012 0.988
#> GSM1182256 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182257 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182258 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182259 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182263 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182267 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182271 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182272 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182277 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182279 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182280 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182281 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182282 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182289 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182290 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182291 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182304 3 0.0188 0.999 0.004 0 0.996 0.000
#> GSM1182305 3 0.0000 0.995 0.000 0 1.000 0.000
#> GSM1182306 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182314 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182302 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182311 1 0.0000 1.000 1.000 0 0.000 0.000
#> GSM1182313 4 0.0000 0.934 0.000 0 0.000 1.000
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000 0.000
#> GSM1182323 1 0.0000 1.000 1.000 0 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 5 0.0000 0.624 0 0 0.000 0.000 1.000
#> GSM1182187 5 0.4219 0.510 0 0 0.000 0.416 0.584
#> GSM1182188 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182189 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182191 5 0.0000 0.624 0 0 0.000 0.000 1.000
#> GSM1182192 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182193 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182194 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182195 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182196 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182197 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182198 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182199 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182200 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182201 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182202 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182203 4 0.3003 0.694 0 0 0.000 0.812 0.188
#> GSM1182204 5 0.4278 0.429 0 0 0.000 0.452 0.548
#> GSM1182205 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182206 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182207 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182208 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182209 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182210 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182211 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182212 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182213 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182214 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182215 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182216 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182217 5 0.0000 0.624 0 0 0.000 0.000 1.000
#> GSM1182218 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182219 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182220 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182221 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182222 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182223 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182224 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182225 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182226 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182227 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182228 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182229 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182230 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182231 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182232 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182235 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182236 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182237 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182238 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182239 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182240 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182241 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182242 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182243 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182244 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182245 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182247 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182248 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182249 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182250 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182251 3 0.0162 0.942 0 0 0.996 0.000 0.004
#> GSM1182252 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182253 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182254 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182255 5 0.4219 0.510 0 0 0.000 0.416 0.584
#> GSM1182256 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182257 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182258 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182260 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182261 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182262 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182263 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182264 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182265 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182266 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182267 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182272 4 0.2891 0.718 0 0 0.000 0.824 0.176
#> GSM1182273 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182275 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182276 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182277 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182279 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182280 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182281 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182282 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182285 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182286 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182287 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182288 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182289 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182290 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182274 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182292 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182293 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182294 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182295 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182296 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182298 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182299 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182300 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182301 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182303 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182304 3 0.0000 0.945 0 0 1.000 0.000 0.000
#> GSM1182305 3 0.4210 0.483 0 0 0.588 0.000 0.412
#> GSM1182306 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182307 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182309 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182312 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182314 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182316 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182318 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182319 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182320 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182321 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182322 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182324 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182297 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182302 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182308 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182310 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182311 1 0.0000 1.000 1 0 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.964 0 0 0.000 1.000 0.000
#> GSM1182315 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182317 2 0.0000 1.000 0 1 0.000 0.000 0.000
#> GSM1182323 1 0.0000 1.000 1 0 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
#> GSM1182186 6 0.3515 0.361 0.000 0.000 0.324 0.000 0.000 0.676
#> GSM1182187 6 0.3620 0.571 0.000 0.000 0.000 0.352 0.000 0.648
#> GSM1182188 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182189 1 0.0146 0.996 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182190 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182191 6 0.3515 0.361 0.000 0.000 0.324 0.000 0.000 0.676
#> GSM1182192 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0146 0.996 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182194 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182195 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182196 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182197 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182198 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182199 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182200 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182201 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182202 4 0.1204 0.908 0.000 0.000 0.000 0.944 0.000 0.056
#> GSM1182203 4 0.3151 0.619 0.000 0.000 0.000 0.748 0.000 0.252
#> GSM1182204 6 0.3727 0.500 0.000 0.000 0.000 0.388 0.000 0.612
#> GSM1182205 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182206 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182207 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182208 1 0.0146 0.996 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182209 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182210 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182211 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182212 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182213 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182214 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182215 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182216 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182217 6 0.3515 0.361 0.000 0.000 0.324 0.000 0.000 0.676
#> GSM1182218 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182220 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182221 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182222 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182223 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182224 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182225 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182226 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182227 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182228 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182229 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182230 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182231 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182232 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182236 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182237 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182238 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182239 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182240 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182241 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182242 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182243 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182244 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182245 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182248 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182249 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182250 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182251 5 0.2697 0.883 0.000 0.000 0.188 0.000 0.812 0.000
#> GSM1182252 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182253 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182254 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182255 6 0.3620 0.571 0.000 0.000 0.000 0.352 0.000 0.648
#> GSM1182256 4 0.1204 0.908 0.000 0.000 0.000 0.944 0.000 0.056
#> GSM1182257 4 0.0363 0.938 0.000 0.000 0.000 0.988 0.000 0.012
#> GSM1182258 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182259 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182260 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182261 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182262 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182263 5 0.0000 0.873 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182264 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182265 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182266 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182267 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182272 4 0.3076 0.644 0.000 0.000 0.000 0.760 0.000 0.240
#> GSM1182273 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182275 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182276 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182277 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.2491 0.899 0.000 0.000 0.164 0.000 0.836 0.000
#> GSM1182280 5 0.0000 0.873 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182281 5 0.2491 0.899 0.000 0.000 0.164 0.000 0.836 0.000
#> GSM1182282 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182285 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182286 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182287 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182288 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182289 5 0.2491 0.899 0.000 0.000 0.164 0.000 0.836 0.000
#> GSM1182290 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182291 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182292 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182293 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182294 2 0.3337 0.649 0.000 0.736 0.004 0.000 0.000 0.260
#> GSM1182295 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182296 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182298 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182299 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182300 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182301 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182303 2 0.0146 0.993 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1182304 5 0.0000 0.873 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182305 3 0.0405 0.000 0.000 0.000 0.988 0.000 0.004 0.008
#> GSM1182306 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182307 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182309 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182312 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182314 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182318 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182319 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182320 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182321 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182322 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182324 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182297 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182302 4 0.0363 0.938 0.000 0.000 0.000 0.988 0.000 0.012
#> GSM1182308 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182310 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182311 1 0.0000 1.000 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.0146 0.942 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182315 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182317 2 0.0000 0.997 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1182323 1 0.0000 1.000 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:hclust 139 0.0773 1.000 2
#> ATC:hclust 139 0.1209 0.888 3
#> ATC:hclust 136 0.1818 0.793 4
#> ATC:hclust 137 0.1374 0.777 5
#> ATC:hclust 134 0.2033 0.826 6
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 46361 rows and 139 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 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.619 0.826 0.785 0.2814 1.000 1.000
#> 4 4 0.558 0.487 0.533 0.1322 0.740 0.503
#> 5 5 0.544 0.569 0.652 0.0732 0.797 0.397
#> 6 6 0.608 0.538 0.692 0.0610 0.919 0.660
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182187 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182188 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182189 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182190 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182191 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182192 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182193 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182194 2 0.4654 0.794 0.000 0.792 NA
#> GSM1182195 2 0.4121 0.791 0.000 0.832 NA
#> GSM1182196 2 0.4121 0.807 0.000 0.832 NA
#> GSM1182197 2 0.6079 0.807 0.000 0.612 NA
#> GSM1182198 2 0.6126 0.805 0.000 0.600 NA
#> GSM1182199 2 0.4605 0.796 0.000 0.796 NA
#> GSM1182200 2 0.5882 0.808 0.000 0.652 NA
#> GSM1182201 2 0.5835 0.809 0.000 0.660 NA
#> GSM1182202 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182203 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182204 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182205 2 0.4062 0.790 0.000 0.836 NA
#> GSM1182206 2 0.3752 0.791 0.000 0.856 NA
#> GSM1182207 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182208 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182209 2 0.5968 0.808 0.000 0.636 NA
#> GSM1182210 2 0.4842 0.832 0.000 0.776 NA
#> GSM1182211 2 0.4931 0.834 0.000 0.768 NA
#> GSM1182212 2 0.5138 0.826 0.000 0.748 NA
#> GSM1182213 2 0.5254 0.823 0.000 0.736 NA
#> GSM1182214 2 0.5216 0.824 0.000 0.740 NA
#> GSM1182215 2 0.3619 0.798 0.000 0.864 NA
#> GSM1182216 2 0.5431 0.819 0.000 0.716 NA
#> GSM1182217 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182218 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182219 2 0.3116 0.806 0.000 0.892 NA
#> GSM1182220 2 0.2796 0.826 0.000 0.908 NA
#> GSM1182221 2 0.3267 0.841 0.000 0.884 NA
#> GSM1182222 2 0.0592 0.829 0.000 0.988 NA
#> GSM1182223 2 0.3619 0.794 0.000 0.864 NA
#> GSM1182224 2 0.3816 0.790 0.000 0.852 NA
#> GSM1182225 2 0.4931 0.830 0.000 0.768 NA
#> GSM1182226 2 0.4750 0.833 0.000 0.784 NA
#> GSM1182227 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182228 2 0.5465 0.821 0.000 0.712 NA
#> GSM1182229 2 0.4002 0.801 0.000 0.840 NA
#> GSM1182230 2 0.3752 0.793 0.000 0.856 NA
#> GSM1182231 2 0.3192 0.843 0.000 0.888 NA
#> GSM1182232 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182233 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182234 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182235 2 0.2959 0.840 0.000 0.900 NA
#> GSM1182236 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182237 2 0.4002 0.824 0.000 0.840 NA
#> GSM1182238 2 0.5216 0.824 0.000 0.740 NA
#> GSM1182239 2 0.5905 0.808 0.000 0.648 NA
#> GSM1182240 2 0.5882 0.808 0.000 0.652 NA
#> GSM1182241 2 0.6154 0.797 0.000 0.592 NA
#> GSM1182242 2 0.5835 0.811 0.000 0.660 NA
#> GSM1182243 2 0.4452 0.809 0.000 0.808 NA
#> GSM1182244 2 0.4504 0.792 0.000 0.804 NA
#> GSM1182245 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182246 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182247 2 0.3879 0.791 0.000 0.848 NA
#> GSM1182248 2 0.4399 0.793 0.000 0.812 NA
#> GSM1182249 2 0.5178 0.840 0.000 0.744 NA
#> GSM1182250 2 0.5785 0.820 0.000 0.668 NA
#> GSM1182251 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182252 2 0.3941 0.791 0.000 0.844 NA
#> GSM1182253 2 0.4002 0.791 0.000 0.840 NA
#> GSM1182254 2 0.5882 0.821 0.000 0.652 NA
#> GSM1182255 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182256 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182257 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182258 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182259 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182260 2 0.6008 0.808 0.000 0.628 NA
#> GSM1182261 2 0.3619 0.805 0.000 0.864 NA
#> GSM1182262 2 0.4178 0.804 0.000 0.828 NA
#> GSM1182263 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182264 2 0.6008 0.811 0.000 0.628 NA
#> GSM1182265 2 0.5988 0.812 0.000 0.632 NA
#> GSM1182266 2 0.6079 0.809 0.000 0.612 NA
#> GSM1182267 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182268 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182269 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182270 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182271 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182272 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182273 2 0.5905 0.814 0.000 0.648 NA
#> GSM1182275 2 0.6140 0.812 0.000 0.596 NA
#> GSM1182276 2 0.3038 0.838 0.000 0.896 NA
#> GSM1182277 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182278 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182279 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182280 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182281 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182282 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182283 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182284 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182285 2 0.4002 0.791 0.000 0.840 NA
#> GSM1182286 2 0.4555 0.839 0.000 0.800 NA
#> GSM1182287 2 0.5098 0.810 0.000 0.752 NA
#> GSM1182288 2 0.4452 0.807 0.000 0.808 NA
#> GSM1182289 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182290 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182291 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182274 2 0.5968 0.809 0.000 0.636 NA
#> GSM1182292 2 0.6154 0.792 0.000 0.592 NA
#> GSM1182293 2 0.4178 0.805 0.000 0.828 NA
#> GSM1182294 2 0.4399 0.800 0.000 0.812 NA
#> GSM1182295 2 0.5016 0.827 0.000 0.760 NA
#> GSM1182296 2 0.5216 0.823 0.000 0.740 NA
#> GSM1182298 2 0.4399 0.793 0.000 0.812 NA
#> GSM1182299 2 0.6280 0.778 0.000 0.540 NA
#> GSM1182300 2 0.4452 0.812 0.000 0.808 NA
#> GSM1182301 2 0.6126 0.800 0.000 0.600 NA
#> GSM1182303 2 0.4235 0.799 0.000 0.824 NA
#> GSM1182304 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182305 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182306 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182307 2 0.5327 0.822 0.000 0.728 NA
#> GSM1182309 2 0.4291 0.807 0.000 0.820 NA
#> GSM1182312 2 0.2448 0.839 0.000 0.924 NA
#> GSM1182314 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182316 2 0.6260 0.782 0.000 0.552 NA
#> GSM1182318 2 0.6280 0.777 0.000 0.540 NA
#> GSM1182319 2 0.4555 0.799 0.000 0.800 NA
#> GSM1182320 2 0.5560 0.814 0.000 0.700 NA
#> GSM1182321 2 0.4750 0.795 0.000 0.784 NA
#> GSM1182322 2 0.6140 0.802 0.000 0.596 NA
#> GSM1182324 2 0.4654 0.805 0.000 0.792 NA
#> GSM1182297 2 0.5859 0.819 0.000 0.656 NA
#> GSM1182302 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182308 2 0.3686 0.809 0.000 0.860 NA
#> GSM1182310 2 0.4235 0.805 0.000 0.824 NA
#> GSM1182311 1 0.6008 0.878 0.628 0.000 NA
#> GSM1182313 1 0.0000 0.815 1.000 0.000 NA
#> GSM1182315 2 0.5363 0.826 0.000 0.724 NA
#> GSM1182317 2 0.5835 0.807 0.000 0.660 NA
#> GSM1182323 1 0.6008 0.878 0.628 0.000 NA
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.228 0.6985 0.000 0.000 0.096 0.904
#> GSM1182187 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182188 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182190 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182191 4 0.276 0.6702 0.000 0.000 0.128 0.872
#> GSM1182192 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182193 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182194 2 0.293 0.5305 0.056 0.896 0.048 0.000
#> GSM1182195 2 0.230 0.5423 0.048 0.924 0.028 0.000
#> GSM1182196 2 0.747 0.2377 0.352 0.464 0.184 0.000
#> GSM1182197 3 0.580 0.6690 0.068 0.264 0.668 0.000
#> GSM1182198 2 0.615 0.2151 0.084 0.636 0.280 0.000
#> GSM1182199 2 0.307 0.5245 0.044 0.888 0.068 0.000
#> GSM1182200 3 0.462 0.6723 0.008 0.284 0.708 0.000
#> GSM1182201 3 0.453 0.6698 0.004 0.292 0.704 0.000
#> GSM1182202 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182203 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182204 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182205 2 0.211 0.5444 0.044 0.932 0.024 0.000
#> GSM1182206 2 0.106 0.5519 0.012 0.972 0.016 0.000
#> GSM1182207 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182208 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182209 3 0.602 0.6529 0.084 0.260 0.656 0.000
#> GSM1182210 2 0.663 -0.3094 0.084 0.500 0.416 0.000
#> GSM1182211 3 0.670 0.4423 0.088 0.428 0.484 0.000
#> GSM1182212 3 0.665 0.4476 0.084 0.436 0.480 0.000
#> GSM1182213 3 0.646 0.5071 0.072 0.408 0.520 0.000
#> GSM1182214 3 0.653 0.4785 0.076 0.416 0.508 0.000
#> GSM1182215 2 0.222 0.5407 0.032 0.928 0.040 0.000
#> GSM1182216 3 0.653 0.5245 0.080 0.388 0.532 0.000
#> GSM1182217 4 0.228 0.6985 0.000 0.000 0.096 0.904
#> GSM1182218 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182219 2 0.355 0.5152 0.064 0.864 0.072 0.000
#> GSM1182220 2 0.430 0.4911 0.064 0.816 0.120 0.000
#> GSM1182221 2 0.631 -0.0328 0.072 0.576 0.352 0.000
#> GSM1182222 2 0.522 0.3620 0.064 0.736 0.200 0.000
#> GSM1182223 2 0.161 0.5478 0.016 0.952 0.032 0.000
#> GSM1182224 2 0.130 0.5519 0.020 0.964 0.016 0.000
#> GSM1182225 2 0.666 -0.3880 0.084 0.476 0.440 0.000
#> GSM1182226 2 0.653 -0.3504 0.076 0.504 0.420 0.000
#> GSM1182227 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182228 3 0.667 0.5041 0.088 0.404 0.508 0.000
#> GSM1182229 2 0.266 0.5278 0.036 0.908 0.056 0.000
#> GSM1182230 2 0.158 0.5549 0.036 0.952 0.012 0.000
#> GSM1182231 2 0.634 0.0546 0.084 0.600 0.316 0.000
#> GSM1182232 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182233 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182234 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182235 2 0.642 -0.0586 0.084 0.580 0.336 0.000
#> GSM1182236 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182237 2 0.471 0.4573 0.072 0.788 0.140 0.000
#> GSM1182238 3 0.665 0.4572 0.084 0.428 0.488 0.000
#> GSM1182239 3 0.469 0.6791 0.012 0.276 0.712 0.000
#> GSM1182240 3 0.440 0.6797 0.004 0.272 0.724 0.000
#> GSM1182241 3 0.543 0.6650 0.064 0.224 0.712 0.000
#> GSM1182242 2 0.522 0.3281 0.056 0.728 0.216 0.000
#> GSM1182243 2 0.373 0.5270 0.044 0.848 0.108 0.000
#> GSM1182244 2 0.309 0.5458 0.060 0.888 0.052 0.000
#> GSM1182245 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182246 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182247 2 0.141 0.5516 0.024 0.960 0.016 0.000
#> GSM1182248 2 0.213 0.5442 0.036 0.932 0.032 0.000
#> GSM1182249 2 0.586 -0.4528 0.032 0.488 0.480 0.000
#> GSM1182250 3 0.551 0.6569 0.032 0.332 0.636 0.000
#> GSM1182251 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182252 2 0.152 0.5498 0.024 0.956 0.020 0.000
#> GSM1182253 2 0.158 0.5487 0.036 0.952 0.012 0.000
#> GSM1182254 3 0.595 0.6551 0.064 0.300 0.636 0.000
#> GSM1182255 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182258 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182260 3 0.703 0.5202 0.180 0.248 0.572 0.000
#> GSM1182261 2 0.365 0.5341 0.092 0.856 0.052 0.000
#> GSM1182262 2 0.267 0.5369 0.024 0.904 0.072 0.000
#> GSM1182263 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182264 3 0.577 0.6747 0.060 0.280 0.660 0.000
#> GSM1182265 3 0.562 0.6756 0.048 0.292 0.660 0.000
#> GSM1182266 3 0.562 0.6702 0.064 0.248 0.688 0.000
#> GSM1182267 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182268 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182269 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182270 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182271 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182273 3 0.584 0.6645 0.064 0.280 0.656 0.000
#> GSM1182275 3 0.633 0.3962 0.060 0.452 0.488 0.000
#> GSM1182276 2 0.624 0.1481 0.092 0.632 0.276 0.000
#> GSM1182277 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182278 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182279 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182280 4 0.730 -0.4983 0.344 0.000 0.164 0.492
#> GSM1182281 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182282 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182283 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182284 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182285 2 0.221 0.5455 0.044 0.928 0.028 0.000
#> GSM1182286 2 0.674 -0.3390 0.092 0.480 0.428 0.000
#> GSM1182287 2 0.497 0.4420 0.076 0.768 0.156 0.000
#> GSM1182288 2 0.354 0.5144 0.060 0.864 0.076 0.000
#> GSM1182289 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182290 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182291 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182274 3 0.550 0.6779 0.048 0.272 0.680 0.000
#> GSM1182292 3 0.693 0.5225 0.184 0.228 0.588 0.000
#> GSM1182293 2 0.749 0.2293 0.364 0.452 0.184 0.000
#> GSM1182294 2 0.740 0.2345 0.380 0.452 0.168 0.000
#> GSM1182295 2 0.787 0.0249 0.352 0.372 0.276 0.000
#> GSM1182296 2 0.787 0.0176 0.336 0.380 0.284 0.000
#> GSM1182298 2 0.249 0.5438 0.048 0.916 0.036 0.000
#> GSM1182299 3 0.550 0.6280 0.088 0.188 0.724 0.000
#> GSM1182300 2 0.763 0.1879 0.364 0.428 0.208 0.000
#> GSM1182301 3 0.778 0.2444 0.336 0.252 0.412 0.000
#> GSM1182303 2 0.680 0.3278 0.356 0.536 0.108 0.000
#> GSM1182304 4 0.738 -0.4517 0.328 0.000 0.180 0.492
#> GSM1182305 4 0.340 0.6153 0.000 0.000 0.180 0.820
#> GSM1182306 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182307 3 0.663 0.4801 0.084 0.412 0.504 0.000
#> GSM1182309 2 0.751 0.2224 0.360 0.452 0.188 0.000
#> GSM1182312 2 0.628 0.0888 0.084 0.612 0.304 0.000
#> GSM1182314 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182316 3 0.715 0.4353 0.264 0.184 0.552 0.000
#> GSM1182318 3 0.730 0.4051 0.288 0.188 0.524 0.000
#> GSM1182319 2 0.736 0.2549 0.368 0.468 0.164 0.000
#> GSM1182320 1 0.791 -0.6600 0.352 0.348 0.300 0.000
#> GSM1182321 2 0.726 0.2724 0.368 0.480 0.152 0.000
#> GSM1182322 3 0.734 0.4804 0.220 0.252 0.528 0.000
#> GSM1182324 2 0.765 0.1891 0.360 0.428 0.212 0.000
#> GSM1182297 3 0.650 0.5906 0.092 0.328 0.580 0.000
#> GSM1182302 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182308 2 0.736 0.2585 0.368 0.468 0.164 0.000
#> GSM1182310 2 0.753 0.2162 0.372 0.440 0.188 0.000
#> GSM1182311 1 0.500 0.8930 0.508 0.000 0.000 0.492
#> GSM1182313 4 0.000 0.7655 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.791 -0.0987 0.344 0.356 0.300 0.000
#> GSM1182317 3 0.787 0.2026 0.348 0.276 0.376 0.000
#> GSM1182323 1 0.500 0.8930 0.508 0.000 0.000 0.492
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 1 0.7182 -0.7168 0.416 0.000 0.056 0.400 0.128
#> GSM1182187 4 0.5188 0.9441 0.416 0.000 0.044 0.540 0.000
#> GSM1182188 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182189 1 0.0794 0.8071 0.972 0.000 0.028 0.000 0.000
#> GSM1182190 1 0.0162 0.8111 0.996 0.000 0.004 0.000 0.000
#> GSM1182191 1 0.7417 -0.6454 0.416 0.000 0.056 0.360 0.168
#> GSM1182192 1 0.0609 0.8083 0.980 0.000 0.020 0.000 0.000
#> GSM1182193 1 0.0703 0.8073 0.976 0.000 0.024 0.000 0.000
#> GSM1182194 3 0.4044 0.7108 0.000 0.120 0.800 0.076 0.004
#> GSM1182195 3 0.3722 0.7215 0.000 0.104 0.828 0.060 0.008
#> GSM1182196 2 0.3801 0.4930 0.000 0.808 0.152 0.012 0.028
#> GSM1182197 2 0.7768 -0.0605 0.000 0.380 0.064 0.240 0.316
#> GSM1182198 3 0.6907 0.4229 0.000 0.228 0.564 0.148 0.060
#> GSM1182199 3 0.3961 0.7169 0.000 0.108 0.812 0.072 0.008
#> GSM1182200 5 0.7923 0.2116 0.000 0.296 0.092 0.212 0.400
#> GSM1182201 5 0.8190 0.2159 0.000 0.296 0.124 0.216 0.364
#> GSM1182202 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182203 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182204 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182205 3 0.3007 0.7428 0.000 0.104 0.864 0.028 0.004
#> GSM1182206 3 0.4149 0.7335 0.000 0.124 0.792 0.004 0.080
#> GSM1182207 1 0.0703 0.8085 0.976 0.000 0.024 0.000 0.000
#> GSM1182208 1 0.0703 0.8085 0.976 0.000 0.024 0.000 0.000
#> GSM1182209 5 0.6359 0.5609 0.000 0.288 0.056 0.072 0.584
#> GSM1182210 5 0.6521 0.6600 0.000 0.244 0.216 0.008 0.532
#> GSM1182211 5 0.6216 0.6982 0.000 0.280 0.136 0.012 0.572
#> GSM1182212 5 0.5618 0.7247 0.000 0.224 0.144 0.000 0.632
#> GSM1182213 5 0.5650 0.7171 0.000 0.224 0.120 0.008 0.648
#> GSM1182214 5 0.5743 0.7224 0.000 0.232 0.124 0.008 0.636
#> GSM1182215 3 0.5367 0.6729 0.000 0.124 0.696 0.012 0.168
#> GSM1182216 5 0.5608 0.7143 0.000 0.224 0.116 0.008 0.652
#> GSM1182217 1 0.7182 -0.7168 0.416 0.000 0.056 0.400 0.128
#> GSM1182218 1 0.0162 0.8111 0.996 0.000 0.004 0.000 0.000
#> GSM1182219 3 0.6302 0.4685 0.000 0.144 0.560 0.012 0.284
#> GSM1182220 3 0.6649 0.3390 0.000 0.164 0.508 0.016 0.312
#> GSM1182221 5 0.6740 0.5242 0.000 0.216 0.272 0.012 0.500
#> GSM1182222 3 0.6768 0.0797 0.000 0.180 0.448 0.012 0.360
#> GSM1182223 3 0.4912 0.7072 0.000 0.128 0.736 0.008 0.128
#> GSM1182224 3 0.3243 0.7494 0.000 0.116 0.848 0.004 0.032
#> GSM1182225 5 0.6293 0.6885 0.000 0.240 0.200 0.004 0.556
#> GSM1182226 5 0.6246 0.7011 0.000 0.236 0.196 0.004 0.564
#> GSM1182227 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182228 5 0.6662 0.6908 0.000 0.220 0.132 0.056 0.592
#> GSM1182229 3 0.5705 0.6195 0.000 0.128 0.644 0.008 0.220
#> GSM1182230 3 0.3780 0.7450 0.000 0.132 0.808 0.000 0.060
#> GSM1182231 5 0.7035 0.4137 0.000 0.204 0.344 0.020 0.432
#> GSM1182232 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0162 0.8111 0.996 0.000 0.004 0.000 0.000
#> GSM1182234 1 0.0609 0.8083 0.980 0.000 0.020 0.000 0.000
#> GSM1182235 5 0.6712 0.5122 0.000 0.216 0.292 0.008 0.484
#> GSM1182236 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.6380 0.4179 0.000 0.136 0.528 0.012 0.324
#> GSM1182238 5 0.5898 0.7233 0.000 0.232 0.140 0.008 0.620
#> GSM1182239 5 0.7807 0.1582 0.000 0.320 0.076 0.212 0.392
#> GSM1182240 5 0.7732 0.1885 0.000 0.316 0.068 0.216 0.400
#> GSM1182241 2 0.7380 0.0136 0.000 0.404 0.032 0.256 0.308
#> GSM1182242 3 0.6300 0.5616 0.000 0.152 0.644 0.056 0.148
#> GSM1182243 3 0.6067 0.6698 0.000 0.172 0.668 0.080 0.080
#> GSM1182244 3 0.4703 0.6986 0.000 0.212 0.732 0.024 0.032
#> GSM1182245 1 0.0162 0.8110 0.996 0.000 0.004 0.000 0.000
#> GSM1182246 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182247 3 0.3497 0.7509 0.000 0.108 0.840 0.008 0.044
#> GSM1182248 3 0.3218 0.7476 0.000 0.108 0.856 0.020 0.016
#> GSM1182249 3 0.8355 -0.3609 0.000 0.296 0.340 0.160 0.204
#> GSM1182250 2 0.8385 -0.2173 0.000 0.316 0.152 0.228 0.304
#> GSM1182251 1 0.3838 0.5648 0.716 0.000 0.004 0.000 0.280
#> GSM1182252 3 0.2886 0.7497 0.000 0.116 0.864 0.004 0.016
#> GSM1182253 3 0.2733 0.7475 0.000 0.112 0.872 0.012 0.004
#> GSM1182254 2 0.8191 -0.0409 0.000 0.372 0.120 0.260 0.248
#> GSM1182255 4 0.5188 0.9441 0.416 0.000 0.044 0.540 0.000
#> GSM1182256 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182257 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182258 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182259 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182260 2 0.7155 0.2607 0.000 0.520 0.056 0.252 0.172
#> GSM1182261 3 0.5641 0.6773 0.000 0.220 0.656 0.012 0.112
#> GSM1182262 3 0.5736 0.6862 0.000 0.144 0.676 0.024 0.156
#> GSM1182263 1 0.3934 0.5657 0.716 0.000 0.008 0.000 0.276
#> GSM1182264 2 0.8122 -0.1103 0.000 0.340 0.100 0.252 0.308
#> GSM1182265 2 0.8175 -0.1226 0.000 0.344 0.112 0.236 0.308
#> GSM1182266 2 0.7854 -0.0188 0.000 0.380 0.072 0.248 0.300
#> GSM1182267 1 0.0290 0.8109 0.992 0.000 0.008 0.000 0.000
#> GSM1182268 1 0.0510 0.8100 0.984 0.000 0.016 0.000 0.000
#> GSM1182269 1 0.0703 0.8083 0.976 0.000 0.024 0.000 0.000
#> GSM1182270 1 0.0162 0.8111 0.996 0.000 0.004 0.000 0.000
#> GSM1182271 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182272 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182273 2 0.8194 -0.0718 0.000 0.348 0.112 0.256 0.284
#> GSM1182275 5 0.7471 0.5681 0.000 0.208 0.264 0.060 0.468
#> GSM1182276 5 0.6721 0.3994 0.000 0.192 0.348 0.008 0.452
#> GSM1182277 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 1 0.3838 0.5648 0.716 0.000 0.004 0.000 0.280
#> GSM1182280 1 0.3715 0.5875 0.736 0.000 0.004 0.000 0.260
#> GSM1182281 1 0.3838 0.5648 0.716 0.000 0.004 0.000 0.280
#> GSM1182282 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0404 0.8105 0.988 0.000 0.012 0.000 0.000
#> GSM1182284 1 0.0000 0.8112 1.000 0.000 0.000 0.000 0.000
#> GSM1182285 3 0.3478 0.7414 0.000 0.096 0.848 0.040 0.016
#> GSM1182286 5 0.6662 0.7031 0.000 0.240 0.164 0.032 0.564
#> GSM1182287 3 0.7142 0.0892 0.000 0.140 0.444 0.048 0.368
#> GSM1182288 3 0.4841 0.7092 0.000 0.120 0.748 0.012 0.120
#> GSM1182289 1 0.3838 0.5648 0.716 0.000 0.004 0.000 0.280
#> GSM1182290 1 0.0404 0.8099 0.988 0.000 0.012 0.000 0.000
#> GSM1182291 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182274 2 0.7783 -0.0825 0.000 0.360 0.064 0.240 0.336
#> GSM1182292 2 0.5844 0.2402 0.000 0.612 0.008 0.116 0.264
#> GSM1182293 2 0.4446 0.4810 0.000 0.776 0.156 0.028 0.040
#> GSM1182294 2 0.4938 0.4651 0.000 0.740 0.168 0.068 0.024
#> GSM1182295 2 0.4536 0.4997 0.000 0.784 0.100 0.024 0.092
#> GSM1182296 2 0.4892 0.4755 0.000 0.752 0.108 0.020 0.120
#> GSM1182298 3 0.3409 0.7286 0.000 0.112 0.836 0.052 0.000
#> GSM1182299 2 0.6988 0.0959 0.000 0.436 0.012 0.260 0.292
#> GSM1182300 2 0.4037 0.4999 0.000 0.800 0.148 0.020 0.032
#> GSM1182301 2 0.4521 0.4774 0.000 0.784 0.024 0.080 0.112
#> GSM1182303 2 0.5263 0.3968 0.000 0.704 0.208 0.036 0.052
#> GSM1182304 1 0.3934 0.5657 0.716 0.000 0.008 0.000 0.276
#> GSM1182305 1 0.7041 -0.5037 0.416 0.000 0.012 0.300 0.272
#> GSM1182306 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182307 5 0.6048 0.7012 0.000 0.236 0.108 0.028 0.628
#> GSM1182309 2 0.4110 0.4899 0.000 0.792 0.152 0.012 0.044
#> GSM1182312 5 0.6962 0.4616 0.000 0.208 0.336 0.016 0.440
#> GSM1182314 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182316 2 0.5670 0.3995 0.000 0.660 0.020 0.224 0.096
#> GSM1182318 2 0.4176 0.4579 0.000 0.792 0.004 0.108 0.096
#> GSM1182319 2 0.3318 0.4706 0.000 0.808 0.180 0.012 0.000
#> GSM1182320 2 0.3126 0.5280 0.000 0.868 0.088 0.028 0.016
#> GSM1182321 2 0.3697 0.4721 0.000 0.796 0.180 0.016 0.008
#> GSM1182322 2 0.5964 0.3865 0.000 0.668 0.040 0.152 0.140
#> GSM1182324 2 0.3201 0.5161 0.000 0.844 0.132 0.008 0.016
#> GSM1182297 5 0.6102 0.6271 0.000 0.296 0.064 0.044 0.596
#> GSM1182302 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182308 2 0.4665 0.4679 0.000 0.756 0.168 0.020 0.056
#> GSM1182310 2 0.3544 0.4895 0.000 0.812 0.164 0.016 0.008
#> GSM1182311 1 0.0510 0.8100 0.984 0.000 0.016 0.000 0.000
#> GSM1182313 4 0.4219 0.9932 0.416 0.000 0.000 0.584 0.000
#> GSM1182315 2 0.3604 0.4808 0.000 0.836 0.056 0.008 0.100
#> GSM1182317 2 0.3378 0.5087 0.000 0.864 0.032 0.048 0.056
#> GSM1182323 1 0.0162 0.8111 0.996 0.000 0.004 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 4 0.5663 0.6727 0.440 0.004 0.020 0.460 0.000 0.076
#> GSM1182187 4 0.4958 0.9021 0.252 0.004 0.020 0.664 0.000 0.060
#> GSM1182188 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182189 1 0.4815 0.8183 0.552 0.004 0.000 0.000 0.396 0.048
#> GSM1182190 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182191 1 0.5653 -0.6416 0.480 0.004 0.020 0.420 0.000 0.076
#> GSM1182192 1 0.4861 0.8184 0.552 0.004 0.000 0.000 0.392 0.052
#> GSM1182193 1 0.4861 0.8184 0.552 0.004 0.000 0.000 0.392 0.052
#> GSM1182194 3 0.4961 0.6593 0.000 0.076 0.748 0.096 0.056 0.024
#> GSM1182195 3 0.4907 0.6641 0.000 0.052 0.752 0.092 0.080 0.024
#> GSM1182196 6 0.4005 0.8713 0.000 0.072 0.108 0.012 0.012 0.796
#> GSM1182197 2 0.3350 0.4808 0.000 0.852 0.024 0.020 0.028 0.076
#> GSM1182198 3 0.6592 0.5160 0.000 0.220 0.580 0.096 0.056 0.048
#> GSM1182199 3 0.4902 0.6647 0.000 0.076 0.752 0.088 0.064 0.020
#> GSM1182200 2 0.1938 0.4512 0.000 0.920 0.040 0.004 0.036 0.000
#> GSM1182201 2 0.2853 0.4472 0.000 0.868 0.056 0.004 0.068 0.004
#> GSM1182202 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182203 4 0.3290 0.9574 0.252 0.000 0.004 0.744 0.000 0.000
#> GSM1182204 4 0.3290 0.9574 0.252 0.000 0.004 0.744 0.000 0.000
#> GSM1182205 3 0.3036 0.7103 0.000 0.060 0.872 0.016 0.028 0.024
#> GSM1182206 3 0.3207 0.6931 0.000 0.060 0.860 0.008 0.044 0.028
#> GSM1182207 1 0.4905 0.8168 0.552 0.000 0.004 0.000 0.388 0.056
#> GSM1182208 1 0.5029 0.8152 0.552 0.004 0.004 0.000 0.384 0.056
#> GSM1182209 2 0.5397 -0.0866 0.000 0.584 0.032 0.016 0.336 0.032
#> GSM1182210 5 0.6840 0.7376 0.000 0.352 0.216 0.004 0.384 0.044
#> GSM1182211 5 0.7032 0.6529 0.000 0.372 0.164 0.008 0.384 0.072
#> GSM1182212 2 0.6308 -0.5906 0.000 0.432 0.156 0.000 0.380 0.032
#> GSM1182213 2 0.6373 -0.4707 0.000 0.476 0.120 0.016 0.360 0.028
#> GSM1182214 2 0.6538 -0.5323 0.000 0.452 0.124 0.016 0.372 0.036
#> GSM1182215 3 0.4302 0.6055 0.000 0.068 0.780 0.016 0.116 0.020
#> GSM1182216 2 0.6492 -0.5333 0.000 0.460 0.148 0.016 0.352 0.024
#> GSM1182217 4 0.5663 0.6727 0.440 0.004 0.020 0.460 0.000 0.076
#> GSM1182218 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182219 3 0.5968 0.2405 0.000 0.084 0.612 0.016 0.236 0.052
#> GSM1182220 3 0.6550 -0.0135 0.000 0.160 0.532 0.012 0.248 0.048
#> GSM1182221 2 0.7106 -0.7630 0.000 0.340 0.284 0.008 0.320 0.048
#> GSM1182222 3 0.6937 -0.3949 0.000 0.184 0.480 0.016 0.264 0.056
#> GSM1182223 3 0.3889 0.6521 0.000 0.052 0.816 0.012 0.088 0.032
#> GSM1182224 3 0.2007 0.7172 0.000 0.040 0.924 0.008 0.012 0.016
#> GSM1182225 2 0.6951 -0.7281 0.000 0.384 0.204 0.016 0.360 0.036
#> GSM1182226 2 0.7032 -0.7379 0.000 0.380 0.208 0.020 0.356 0.036
#> GSM1182227 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182228 2 0.6411 -0.3913 0.000 0.472 0.092 0.040 0.376 0.020
#> GSM1182229 3 0.5226 0.5012 0.000 0.092 0.708 0.028 0.148 0.024
#> GSM1182230 3 0.3248 0.7123 0.000 0.048 0.856 0.004 0.036 0.056
#> GSM1182231 5 0.6862 0.7362 0.000 0.328 0.296 0.000 0.332 0.044
#> GSM1182232 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182233 1 0.4224 0.8245 0.552 0.000 0.000 0.000 0.432 0.016
#> GSM1182234 1 0.4861 0.8184 0.552 0.004 0.000 0.000 0.392 0.052
#> GSM1182235 5 0.7206 0.7896 0.000 0.316 0.280 0.016 0.344 0.044
#> GSM1182236 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182237 3 0.6518 0.0111 0.000 0.172 0.536 0.020 0.240 0.032
#> GSM1182238 2 0.6571 -0.5360 0.000 0.456 0.140 0.016 0.356 0.032
#> GSM1182239 2 0.2402 0.4596 0.000 0.896 0.032 0.000 0.060 0.012
#> GSM1182240 2 0.1933 0.4497 0.000 0.920 0.032 0.004 0.044 0.000
#> GSM1182241 2 0.2571 0.4843 0.000 0.892 0.004 0.020 0.024 0.060
#> GSM1182242 3 0.5778 0.5557 0.000 0.188 0.644 0.060 0.100 0.008
#> GSM1182243 3 0.5090 0.6093 0.000 0.216 0.684 0.008 0.040 0.052
#> GSM1182244 3 0.4372 0.6830 0.000 0.056 0.776 0.016 0.028 0.124
#> GSM1182245 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182246 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182247 3 0.2469 0.7139 0.000 0.048 0.900 0.008 0.032 0.012
#> GSM1182248 3 0.1931 0.7156 0.000 0.068 0.916 0.004 0.008 0.004
#> GSM1182249 2 0.4879 0.1692 0.000 0.608 0.340 0.008 0.028 0.016
#> GSM1182250 2 0.3376 0.4560 0.000 0.844 0.088 0.008 0.024 0.036
#> GSM1182251 1 0.0000 0.4807 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182252 3 0.1738 0.7169 0.000 0.052 0.928 0.000 0.004 0.016
#> GSM1182253 3 0.2495 0.7176 0.000 0.052 0.896 0.004 0.012 0.036
#> GSM1182254 2 0.3970 0.4679 0.000 0.820 0.064 0.024 0.044 0.048
#> GSM1182255 4 0.4958 0.9021 0.252 0.004 0.020 0.664 0.000 0.060
#> GSM1182256 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182257 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182258 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182259 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182260 2 0.5114 0.3144 0.000 0.696 0.048 0.012 0.048 0.196
#> GSM1182261 3 0.5666 0.5646 0.000 0.052 0.656 0.024 0.060 0.208
#> GSM1182262 3 0.5017 0.6516 0.000 0.116 0.736 0.016 0.076 0.056
#> GSM1182263 1 0.0363 0.4830 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1182264 2 0.3060 0.4807 0.000 0.868 0.040 0.004 0.040 0.048
#> GSM1182265 2 0.3286 0.4719 0.000 0.848 0.068 0.000 0.040 0.044
#> GSM1182266 2 0.2937 0.4823 0.000 0.876 0.032 0.012 0.020 0.060
#> GSM1182267 1 0.4294 0.8243 0.552 0.000 0.000 0.000 0.428 0.020
#> GSM1182268 1 0.4766 0.8191 0.552 0.004 0.000 0.000 0.400 0.044
#> GSM1182269 1 0.4815 0.8183 0.552 0.004 0.000 0.000 0.396 0.048
#> GSM1182270 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 0.000
#> GSM1182271 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182272 4 0.3290 0.9574 0.252 0.000 0.004 0.744 0.000 0.000
#> GSM1182273 2 0.3566 0.4757 0.000 0.844 0.052 0.020 0.032 0.052
#> GSM1182275 2 0.6379 -0.3965 0.000 0.460 0.232 0.016 0.288 0.004
#> GSM1182276 5 0.7101 0.7751 0.000 0.272 0.320 0.016 0.356 0.036
#> GSM1182277 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182278 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182279 1 0.0000 0.4807 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182280 1 0.0909 0.5030 0.968 0.000 0.000 0.000 0.020 0.012
#> GSM1182281 1 0.0000 0.4807 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182282 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182283 1 0.4423 0.8236 0.552 0.000 0.000 0.000 0.420 0.028
#> GSM1182284 1 0.3966 0.8244 0.552 0.000 0.000 0.000 0.444 0.004
#> GSM1182285 3 0.3430 0.7042 0.000 0.048 0.852 0.040 0.044 0.016
#> GSM1182286 2 0.7124 -0.6052 0.000 0.392 0.128 0.032 0.388 0.060
#> GSM1182287 3 0.6776 -0.2833 0.000 0.176 0.420 0.032 0.356 0.016
#> GSM1182288 3 0.4320 0.6187 0.000 0.108 0.760 0.012 0.116 0.004
#> GSM1182289 1 0.0000 0.4807 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182290 1 0.4350 0.8218 0.552 0.000 0.004 0.000 0.428 0.016
#> GSM1182291 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182274 2 0.2039 0.4841 0.000 0.916 0.020 0.000 0.012 0.052
#> GSM1182292 2 0.5845 0.0200 0.000 0.504 0.016 0.016 0.080 0.384
#> GSM1182293 6 0.4896 0.8637 0.000 0.100 0.092 0.032 0.028 0.748
#> GSM1182294 6 0.5134 0.8347 0.000 0.068 0.088 0.084 0.024 0.736
#> GSM1182295 6 0.5446 0.8298 0.000 0.160 0.060 0.028 0.056 0.696
#> GSM1182296 6 0.5460 0.8120 0.000 0.168 0.072 0.020 0.052 0.688
#> GSM1182298 3 0.4621 0.6826 0.000 0.056 0.776 0.088 0.048 0.032
#> GSM1182299 2 0.2114 0.4801 0.000 0.904 0.000 0.008 0.012 0.076
#> GSM1182300 6 0.4445 0.8736 0.000 0.104 0.084 0.012 0.028 0.772
#> GSM1182301 6 0.5440 0.6963 0.000 0.280 0.008 0.048 0.044 0.620
#> GSM1182303 6 0.5108 0.8103 0.000 0.088 0.140 0.028 0.024 0.720
#> GSM1182304 1 0.0363 0.4830 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1182305 1 0.3972 -0.4118 0.680 0.000 0.004 0.300 0.000 0.016
#> GSM1182306 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182307 2 0.6341 -0.4793 0.000 0.480 0.128 0.012 0.352 0.028
#> GSM1182309 6 0.4023 0.8744 0.000 0.092 0.096 0.012 0.008 0.792
#> GSM1182312 5 0.7365 0.7861 0.000 0.296 0.280 0.024 0.352 0.048
#> GSM1182314 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182316 2 0.5817 -0.1150 0.000 0.548 0.024 0.032 0.048 0.348
#> GSM1182318 6 0.5328 0.5204 0.000 0.376 0.008 0.032 0.032 0.552
#> GSM1182319 6 0.3597 0.8650 0.000 0.076 0.104 0.004 0.004 0.812
#> GSM1182320 6 0.4813 0.8515 0.000 0.144 0.080 0.016 0.024 0.736
#> GSM1182321 6 0.3447 0.8610 0.000 0.064 0.108 0.000 0.008 0.820
#> GSM1182322 2 0.5516 -0.2163 0.000 0.524 0.032 0.012 0.036 0.396
#> GSM1182324 6 0.4286 0.8664 0.000 0.108 0.088 0.008 0.020 0.776
#> GSM1182297 2 0.6051 -0.3040 0.000 0.512 0.052 0.016 0.368 0.052
#> GSM1182302 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182308 6 0.4909 0.8499 0.000 0.092 0.108 0.024 0.032 0.744
#> GSM1182310 6 0.4004 0.8734 0.000 0.092 0.096 0.004 0.016 0.792
#> GSM1182311 1 0.4641 0.8199 0.552 0.000 0.000 0.000 0.404 0.044
#> GSM1182313 4 0.3151 0.9590 0.252 0.000 0.000 0.748 0.000 0.000
#> GSM1182315 6 0.5044 0.8253 0.000 0.156 0.080 0.012 0.036 0.716
#> GSM1182317 6 0.5184 0.7672 0.000 0.228 0.044 0.028 0.024 0.676
#> GSM1182323 1 0.3838 0.8245 0.552 0.000 0.000 0.000 0.448 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:kmeans 139 7.73e-02 1.000 2
#> ATC:kmeans 139 7.73e-02 1.000 3
#> ATC:kmeans 90 2.65e-01 0.547 4
#> ATC:kmeans 92 2.47e-04 0.222 5
#> ATC:kmeans 93 6.97e-11 0.133 6
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 46361 rows and 139 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 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 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.986 0.977 0.1637 0.926 0.857
#> 4 4 0.665 0.889 0.850 0.1691 1.000 1.000
#> 5 5 0.629 0.599 0.768 0.0780 0.834 0.629
#> 6 6 0.616 0.581 0.748 0.0488 0.840 0.544
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182187 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182188 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182189 1 0.0237 0.996 0.996 0.000 0.004
#> GSM1182190 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182191 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182192 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182193 1 0.0237 0.996 0.996 0.000 0.004
#> GSM1182194 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182195 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182196 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182197 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182198 2 0.1643 0.978 0.000 0.956 0.044
#> GSM1182199 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182200 2 0.0892 0.987 0.000 0.980 0.020
#> GSM1182201 2 0.0892 0.986 0.000 0.980 0.020
#> GSM1182202 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182203 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182204 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182205 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182206 2 0.1163 0.982 0.000 0.972 0.028
#> GSM1182207 1 0.0237 0.996 0.996 0.000 0.004
#> GSM1182208 1 0.0237 0.996 0.996 0.000 0.004
#> GSM1182209 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182210 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182211 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182212 2 0.0747 0.986 0.000 0.984 0.016
#> GSM1182213 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182214 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182215 2 0.1163 0.982 0.000 0.972 0.028
#> GSM1182216 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182217 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182218 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182219 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182220 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182221 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182222 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182223 2 0.0892 0.985 0.000 0.980 0.020
#> GSM1182224 2 0.1411 0.978 0.000 0.964 0.036
#> GSM1182225 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182226 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182227 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182228 2 0.0592 0.987 0.000 0.988 0.012
#> GSM1182229 2 0.1289 0.980 0.000 0.968 0.032
#> GSM1182230 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182231 2 0.0592 0.988 0.000 0.988 0.012
#> GSM1182232 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182235 2 0.0592 0.987 0.000 0.988 0.012
#> GSM1182236 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182237 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182238 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182239 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182240 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182241 2 0.0747 0.986 0.000 0.984 0.016
#> GSM1182242 2 0.1753 0.978 0.000 0.952 0.048
#> GSM1182243 2 0.1163 0.984 0.000 0.972 0.028
#> GSM1182244 2 0.1289 0.979 0.000 0.968 0.032
#> GSM1182245 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182246 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182247 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182248 2 0.1643 0.978 0.000 0.956 0.044
#> GSM1182249 2 0.0892 0.987 0.000 0.980 0.020
#> GSM1182250 2 0.1163 0.986 0.000 0.972 0.028
#> GSM1182251 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182252 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182253 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182254 2 0.1163 0.986 0.000 0.972 0.028
#> GSM1182255 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182256 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182257 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182258 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182259 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182260 2 0.0892 0.987 0.000 0.980 0.020
#> GSM1182261 2 0.0747 0.986 0.000 0.984 0.016
#> GSM1182262 2 0.1163 0.981 0.000 0.972 0.028
#> GSM1182263 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182264 2 0.1163 0.985 0.000 0.972 0.028
#> GSM1182265 2 0.1031 0.986 0.000 0.976 0.024
#> GSM1182266 2 0.0892 0.986 0.000 0.980 0.020
#> GSM1182267 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182270 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182271 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182272 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182273 2 0.0892 0.986 0.000 0.980 0.020
#> GSM1182275 2 0.1411 0.984 0.000 0.964 0.036
#> GSM1182276 2 0.0592 0.987 0.000 0.988 0.012
#> GSM1182277 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182279 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182280 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182281 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182282 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182284 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182285 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182286 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182287 2 0.1529 0.979 0.000 0.960 0.040
#> GSM1182288 2 0.1753 0.978 0.000 0.952 0.048
#> GSM1182289 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182290 1 0.0237 0.996 0.996 0.000 0.004
#> GSM1182291 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182274 2 0.0892 0.986 0.000 0.980 0.020
#> GSM1182292 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182293 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182294 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182295 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182296 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182298 2 0.1529 0.977 0.000 0.960 0.040
#> GSM1182299 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182300 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182301 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182303 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182304 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182305 3 0.5591 0.644 0.304 0.000 0.696
#> GSM1182306 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182307 2 0.0592 0.986 0.000 0.988 0.012
#> GSM1182309 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182312 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182314 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182316 2 0.0747 0.987 0.000 0.984 0.016
#> GSM1182318 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182319 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182320 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182321 2 0.0892 0.984 0.000 0.980 0.020
#> GSM1182322 2 0.0747 0.986 0.000 0.984 0.016
#> GSM1182324 2 0.0592 0.987 0.000 0.988 0.012
#> GSM1182297 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182302 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182308 2 0.0237 0.987 0.000 0.996 0.004
#> GSM1182310 2 0.0424 0.987 0.000 0.992 0.008
#> GSM1182311 1 0.0000 0.999 1.000 0.000 0.000
#> GSM1182313 3 0.1964 0.988 0.056 0.000 0.944
#> GSM1182315 2 0.0000 0.987 0.000 1.000 0.000
#> GSM1182317 2 0.0592 0.987 0.000 0.988 0.012
#> GSM1182323 1 0.0000 0.999 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182187 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182188 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182189 1 0.0188 0.980 0.996 0.000 NA 0.000
#> GSM1182190 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182191 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182192 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182193 1 0.0188 0.980 0.996 0.000 NA 0.000
#> GSM1182194 2 0.4585 0.801 0.000 0.668 NA 0.000
#> GSM1182195 2 0.4661 0.794 0.000 0.652 NA 0.000
#> GSM1182196 2 0.3726 0.848 0.000 0.788 NA 0.000
#> GSM1182197 2 0.3400 0.832 0.000 0.820 NA 0.000
#> GSM1182198 2 0.4713 0.810 0.000 0.640 NA 0.000
#> GSM1182199 2 0.4661 0.800 0.000 0.652 NA 0.000
#> GSM1182200 2 0.3444 0.823 0.000 0.816 NA 0.000
#> GSM1182201 2 0.3610 0.833 0.000 0.800 NA 0.000
#> GSM1182202 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182203 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182204 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182205 2 0.4564 0.801 0.000 0.672 NA 0.000
#> GSM1182206 2 0.4277 0.822 0.000 0.720 NA 0.000
#> GSM1182207 1 0.1716 0.958 0.936 0.000 NA 0.000
#> GSM1182208 1 0.4356 0.766 0.708 0.000 NA 0.000
#> GSM1182209 2 0.3219 0.828 0.000 0.836 NA 0.000
#> GSM1182210 2 0.1940 0.861 0.000 0.924 NA 0.000
#> GSM1182211 2 0.2814 0.845 0.000 0.868 NA 0.000
#> GSM1182212 2 0.2408 0.845 0.000 0.896 NA 0.000
#> GSM1182213 2 0.2868 0.840 0.000 0.864 NA 0.000
#> GSM1182214 2 0.2760 0.840 0.000 0.872 NA 0.000
#> GSM1182215 2 0.4134 0.835 0.000 0.740 NA 0.000
#> GSM1182216 2 0.3074 0.830 0.000 0.848 NA 0.000
#> GSM1182217 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182218 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182219 2 0.3688 0.845 0.000 0.792 NA 0.000
#> GSM1182220 2 0.3074 0.857 0.000 0.848 NA 0.000
#> GSM1182221 2 0.2011 0.865 0.000 0.920 NA 0.000
#> GSM1182222 2 0.3024 0.857 0.000 0.852 NA 0.000
#> GSM1182223 2 0.4222 0.829 0.000 0.728 NA 0.000
#> GSM1182224 2 0.4564 0.799 0.000 0.672 NA 0.000
#> GSM1182225 2 0.2530 0.850 0.000 0.888 NA 0.000
#> GSM1182226 2 0.2704 0.851 0.000 0.876 NA 0.000
#> GSM1182227 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182228 2 0.3123 0.860 0.000 0.844 NA 0.000
#> GSM1182229 2 0.4134 0.835 0.000 0.740 NA 0.000
#> GSM1182230 2 0.4522 0.805 0.000 0.680 NA 0.000
#> GSM1182231 2 0.2760 0.866 0.000 0.872 NA 0.000
#> GSM1182232 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182233 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182234 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182235 2 0.1867 0.861 0.000 0.928 NA 0.000
#> GSM1182236 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182237 2 0.3266 0.861 0.000 0.832 NA 0.000
#> GSM1182238 2 0.2647 0.842 0.000 0.880 NA 0.000
#> GSM1182239 2 0.3219 0.823 0.000 0.836 NA 0.000
#> GSM1182240 2 0.3356 0.822 0.000 0.824 NA 0.000
#> GSM1182241 2 0.3400 0.823 0.000 0.820 NA 0.000
#> GSM1182242 2 0.4406 0.830 0.000 0.700 NA 0.000
#> GSM1182243 2 0.4134 0.848 0.000 0.740 NA 0.000
#> GSM1182244 2 0.4643 0.795 0.000 0.656 NA 0.000
#> GSM1182245 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182246 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182247 2 0.4304 0.817 0.000 0.716 NA 0.000
#> GSM1182248 2 0.4500 0.813 0.000 0.684 NA 0.000
#> GSM1182249 2 0.3219 0.867 0.000 0.836 NA 0.000
#> GSM1182250 2 0.3688 0.857 0.000 0.792 NA 0.000
#> GSM1182251 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182252 2 0.4382 0.815 0.000 0.704 NA 0.000
#> GSM1182253 2 0.4522 0.811 0.000 0.680 NA 0.000
#> GSM1182254 2 0.3528 0.860 0.000 0.808 NA 0.000
#> GSM1182255 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182256 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182257 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182258 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182259 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182260 2 0.4164 0.861 0.000 0.736 NA 0.000
#> GSM1182261 2 0.4103 0.845 0.000 0.744 NA 0.000
#> GSM1182262 2 0.4304 0.827 0.000 0.716 NA 0.000
#> GSM1182263 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182264 2 0.4164 0.824 0.000 0.736 NA 0.000
#> GSM1182265 2 0.3907 0.835 0.000 0.768 NA 0.000
#> GSM1182266 2 0.3764 0.830 0.000 0.784 NA 0.000
#> GSM1182267 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182268 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182269 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182270 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182271 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182272 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182273 2 0.3764 0.826 0.000 0.784 NA 0.000
#> GSM1182275 2 0.3975 0.848 0.000 0.760 NA 0.000
#> GSM1182276 2 0.2149 0.866 0.000 0.912 NA 0.000
#> GSM1182277 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182278 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182279 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182280 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182281 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182282 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182283 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182284 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182285 2 0.4522 0.802 0.000 0.680 NA 0.000
#> GSM1182286 2 0.2081 0.867 0.000 0.916 NA 0.000
#> GSM1182287 2 0.3528 0.856 0.000 0.808 NA 0.000
#> GSM1182288 2 0.4193 0.826 0.000 0.732 NA 0.000
#> GSM1182289 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182290 1 0.1557 0.962 0.944 0.000 NA 0.000
#> GSM1182291 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182274 2 0.3688 0.822 0.000 0.792 NA 0.000
#> GSM1182292 2 0.3074 0.842 0.000 0.848 NA 0.000
#> GSM1182293 2 0.3610 0.847 0.000 0.800 NA 0.000
#> GSM1182294 2 0.4843 0.741 0.000 0.604 NA 0.000
#> GSM1182295 2 0.2868 0.858 0.000 0.864 NA 0.000
#> GSM1182296 2 0.3266 0.856 0.000 0.832 NA 0.000
#> GSM1182298 2 0.4605 0.798 0.000 0.664 NA 0.000
#> GSM1182299 2 0.3528 0.822 0.000 0.808 NA 0.000
#> GSM1182300 2 0.3726 0.849 0.000 0.788 NA 0.000
#> GSM1182301 2 0.3074 0.855 0.000 0.848 NA 0.000
#> GSM1182303 2 0.3837 0.842 0.000 0.776 NA 0.000
#> GSM1182304 1 0.1474 0.963 0.948 0.000 NA 0.000
#> GSM1182305 4 0.4801 0.716 0.188 0.000 NA 0.764
#> GSM1182306 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182307 2 0.2647 0.840 0.000 0.880 NA 0.000
#> GSM1182309 2 0.3801 0.843 0.000 0.780 NA 0.000
#> GSM1182312 2 0.2814 0.862 0.000 0.868 NA 0.000
#> GSM1182314 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182316 2 0.3569 0.828 0.000 0.804 NA 0.000
#> GSM1182318 2 0.3400 0.842 0.000 0.820 NA 0.000
#> GSM1182319 2 0.4382 0.827 0.000 0.704 NA 0.000
#> GSM1182320 2 0.3569 0.851 0.000 0.804 NA 0.000
#> GSM1182321 2 0.4564 0.818 0.000 0.672 NA 0.000
#> GSM1182322 2 0.3400 0.842 0.000 0.820 NA 0.000
#> GSM1182324 2 0.3907 0.851 0.000 0.768 NA 0.000
#> GSM1182297 2 0.2647 0.853 0.000 0.880 NA 0.000
#> GSM1182302 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182308 2 0.3649 0.845 0.000 0.796 NA 0.000
#> GSM1182310 2 0.3942 0.841 0.000 0.764 NA 0.000
#> GSM1182311 1 0.0000 0.982 1.000 0.000 NA 0.000
#> GSM1182313 4 0.0000 0.990 0.000 0.000 NA 1.000
#> GSM1182315 2 0.3311 0.851 0.000 0.828 NA 0.000
#> GSM1182317 2 0.3024 0.855 0.000 0.852 NA 0.000
#> GSM1182323 1 0.0000 0.982 1.000 0.000 NA 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182187 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182188 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0324 0.9439 0.992 0.004 0.000 0.000 0.004
#> GSM1182190 1 0.0000 0.9455 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 4 0.0404 0.9714 0.000 0.012 0.000 0.988 0.000
#> GSM1182192 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182193 1 0.0451 0.9434 0.988 0.004 0.000 0.000 0.008
#> GSM1182194 3 0.3622 0.3346 0.000 0.136 0.816 0.000 0.048
#> GSM1182195 3 0.3216 0.3400 0.000 0.108 0.848 0.000 0.044
#> GSM1182196 3 0.4681 0.4607 0.000 0.252 0.696 0.000 0.052
#> GSM1182197 2 0.4798 0.7133 0.000 0.580 0.396 0.000 0.024
#> GSM1182198 3 0.4758 0.2522 0.000 0.276 0.676 0.000 0.048
#> GSM1182199 3 0.3639 0.3433 0.000 0.144 0.812 0.000 0.044
#> GSM1182200 2 0.4387 0.7199 0.000 0.640 0.348 0.000 0.012
#> GSM1182201 2 0.4718 0.6816 0.000 0.540 0.444 0.000 0.016
#> GSM1182202 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182203 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182204 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182205 3 0.2795 0.4111 0.000 0.100 0.872 0.000 0.028
#> GSM1182206 3 0.2331 0.5483 0.000 0.080 0.900 0.000 0.020
#> GSM1182207 1 0.3749 0.8645 0.816 0.080 0.000 0.000 0.104
#> GSM1182208 1 0.4787 0.5535 0.548 0.020 0.000 0.000 0.432
#> GSM1182209 2 0.4088 0.7402 0.000 0.632 0.368 0.000 0.000
#> GSM1182210 3 0.4437 -0.3805 0.000 0.464 0.532 0.000 0.004
#> GSM1182211 2 0.4415 0.6599 0.000 0.552 0.444 0.000 0.004
#> GSM1182212 2 0.4420 0.6980 0.000 0.548 0.448 0.000 0.004
#> GSM1182213 2 0.4249 0.7145 0.000 0.568 0.432 0.000 0.000
#> GSM1182214 2 0.4410 0.6726 0.000 0.556 0.440 0.000 0.004
#> GSM1182215 3 0.3224 0.5149 0.000 0.160 0.824 0.000 0.016
#> GSM1182216 2 0.4331 0.7319 0.000 0.596 0.400 0.000 0.004
#> GSM1182217 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182218 1 0.0000 0.9455 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 3 0.3421 0.5035 0.000 0.204 0.788 0.000 0.008
#> GSM1182220 3 0.3890 0.4343 0.000 0.252 0.736 0.000 0.012
#> GSM1182221 3 0.4138 -0.0163 0.000 0.384 0.616 0.000 0.000
#> GSM1182222 3 0.4026 0.4003 0.000 0.244 0.736 0.000 0.020
#> GSM1182223 3 0.2660 0.5316 0.000 0.128 0.864 0.000 0.008
#> GSM1182224 3 0.2491 0.4237 0.000 0.068 0.896 0.000 0.036
#> GSM1182225 3 0.4306 -0.5498 0.000 0.492 0.508 0.000 0.000
#> GSM1182226 2 0.4448 0.6455 0.000 0.516 0.480 0.000 0.004
#> GSM1182227 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182228 3 0.4546 -0.4929 0.000 0.460 0.532 0.000 0.008
#> GSM1182229 3 0.3013 0.4893 0.000 0.160 0.832 0.000 0.008
#> GSM1182230 3 0.2069 0.5325 0.000 0.076 0.912 0.000 0.012
#> GSM1182231 3 0.3861 0.3587 0.000 0.264 0.728 0.000 0.008
#> GSM1182232 1 0.0000 0.9455 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0162 0.9451 0.996 0.004 0.000 0.000 0.000
#> GSM1182234 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182235 3 0.4262 -0.3357 0.000 0.440 0.560 0.000 0.000
#> GSM1182236 1 0.0000 0.9455 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.3837 0.2210 0.000 0.308 0.692 0.000 0.000
#> GSM1182238 2 0.4249 0.6935 0.000 0.568 0.432 0.000 0.000
#> GSM1182239 2 0.4151 0.7361 0.000 0.652 0.344 0.000 0.004
#> GSM1182240 2 0.4416 0.7430 0.000 0.632 0.356 0.000 0.012
#> GSM1182241 2 0.4402 0.7468 0.000 0.636 0.352 0.000 0.012
#> GSM1182242 3 0.3934 0.3691 0.000 0.244 0.740 0.000 0.016
#> GSM1182243 3 0.3355 0.4965 0.000 0.184 0.804 0.000 0.012
#> GSM1182244 3 0.3099 0.3672 0.000 0.124 0.848 0.000 0.028
#> GSM1182245 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182246 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.1872 0.5340 0.000 0.052 0.928 0.000 0.020
#> GSM1182248 3 0.3141 0.4913 0.000 0.108 0.852 0.000 0.040
#> GSM1182249 3 0.4610 -0.1038 0.000 0.388 0.596 0.000 0.016
#> GSM1182250 3 0.4551 -0.0857 0.000 0.368 0.616 0.000 0.016
#> GSM1182251 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182252 3 0.3099 0.4990 0.000 0.124 0.848 0.000 0.028
#> GSM1182253 3 0.2124 0.4872 0.000 0.056 0.916 0.000 0.028
#> GSM1182254 3 0.4767 -0.3446 0.000 0.420 0.560 0.000 0.020
#> GSM1182255 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.5077 -0.0705 0.000 0.392 0.568 0.000 0.040
#> GSM1182261 3 0.3639 0.5125 0.000 0.184 0.792 0.000 0.024
#> GSM1182262 3 0.2753 0.5399 0.000 0.136 0.856 0.000 0.008
#> GSM1182263 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182264 2 0.5059 0.5041 0.000 0.548 0.416 0.000 0.036
#> GSM1182265 2 0.5103 0.5117 0.000 0.512 0.452 0.000 0.036
#> GSM1182266 2 0.5044 0.6243 0.000 0.556 0.408 0.000 0.036
#> GSM1182267 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182268 1 0.0162 0.9451 0.996 0.004 0.000 0.000 0.000
#> GSM1182269 1 0.0162 0.9451 0.996 0.004 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.9455 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 2 0.4746 0.6802 0.000 0.600 0.376 0.000 0.024
#> GSM1182275 3 0.4470 -0.0883 0.000 0.372 0.616 0.000 0.012
#> GSM1182276 3 0.3966 0.1627 0.000 0.336 0.664 0.000 0.000
#> GSM1182277 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182278 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182279 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182280 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182281 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182282 1 0.0324 0.9445 0.992 0.004 0.000 0.000 0.004
#> GSM1182283 1 0.0162 0.9453 0.996 0.000 0.000 0.000 0.004
#> GSM1182284 1 0.0324 0.9450 0.992 0.004 0.000 0.000 0.004
#> GSM1182285 3 0.3216 0.3983 0.000 0.108 0.848 0.000 0.044
#> GSM1182286 3 0.4392 -0.0930 0.000 0.380 0.612 0.000 0.008
#> GSM1182287 3 0.3821 0.4317 0.000 0.216 0.764 0.000 0.020
#> GSM1182288 3 0.2969 0.5135 0.000 0.128 0.852 0.000 0.020
#> GSM1182289 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182290 1 0.3754 0.8631 0.816 0.084 0.000 0.000 0.100
#> GSM1182291 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.4570 0.7045 0.000 0.632 0.348 0.000 0.020
#> GSM1182292 2 0.4787 0.5730 0.000 0.548 0.432 0.000 0.020
#> GSM1182293 3 0.4735 0.4279 0.000 0.272 0.680 0.000 0.048
#> GSM1182294 5 0.6055 0.0000 0.000 0.120 0.408 0.000 0.472
#> GSM1182295 3 0.4880 0.2449 0.000 0.348 0.616 0.000 0.036
#> GSM1182296 3 0.5019 0.2820 0.000 0.316 0.632 0.000 0.052
#> GSM1182298 3 0.3506 0.3558 0.000 0.132 0.824 0.000 0.044
#> GSM1182299 2 0.4525 0.7398 0.000 0.624 0.360 0.000 0.016
#> GSM1182300 3 0.4946 0.3799 0.000 0.300 0.648 0.000 0.052
#> GSM1182301 3 0.4937 -0.1073 0.000 0.428 0.544 0.000 0.028
#> GSM1182303 3 0.4573 0.4695 0.000 0.256 0.700 0.000 0.044
#> GSM1182304 1 0.3526 0.8721 0.832 0.096 0.000 0.000 0.072
#> GSM1182305 4 0.6232 0.5222 0.212 0.096 0.000 0.636 0.056
#> GSM1182306 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182307 2 0.4192 0.7207 0.000 0.596 0.404 0.000 0.000
#> GSM1182309 3 0.4890 0.4494 0.000 0.256 0.680 0.000 0.064
#> GSM1182312 3 0.4524 0.2423 0.000 0.336 0.644 0.000 0.020
#> GSM1182314 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 2 0.5213 0.5962 0.000 0.556 0.396 0.000 0.048
#> GSM1182318 2 0.5435 0.5294 0.000 0.512 0.428 0.000 0.060
#> GSM1182319 3 0.4465 0.4263 0.000 0.204 0.736 0.000 0.060
#> GSM1182320 3 0.4990 0.2956 0.000 0.324 0.628 0.000 0.048
#> GSM1182321 3 0.4204 0.4562 0.000 0.196 0.756 0.000 0.048
#> GSM1182322 2 0.5505 0.4935 0.000 0.484 0.452 0.000 0.064
#> GSM1182324 3 0.4735 0.4419 0.000 0.284 0.672 0.000 0.044
#> GSM1182297 2 0.4546 0.6563 0.000 0.532 0.460 0.000 0.008
#> GSM1182302 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182308 3 0.4602 0.4484 0.000 0.240 0.708 0.000 0.052
#> GSM1182310 3 0.4795 0.4664 0.000 0.224 0.704 0.000 0.072
#> GSM1182311 1 0.0162 0.9449 0.996 0.000 0.000 0.000 0.004
#> GSM1182313 4 0.0000 0.9815 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 3 0.5168 0.1970 0.000 0.356 0.592 0.000 0.052
#> GSM1182317 3 0.4878 -0.1911 0.000 0.440 0.536 0.000 0.024
#> GSM1182323 1 0.0000 0.9455 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
#> GSM1182186 4 0.0547 0.9587 0.000 0.000 0.000 0.980 0.000 0.020
#> GSM1182187 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182188 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 1 0.0806 0.8308 0.972 0.000 0.000 0.000 0.008 0.020
#> GSM1182190 1 0.0260 0.8405 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1182191 4 0.1075 0.9339 0.000 0.000 0.000 0.952 0.000 0.048
#> GSM1182192 1 0.0820 0.8384 0.972 0.000 0.000 0.000 0.016 0.012
#> GSM1182193 1 0.1176 0.8288 0.956 0.000 0.000 0.000 0.024 0.020
#> GSM1182194 3 0.4340 0.6031 0.000 0.224 0.708 0.000 0.064 0.004
#> GSM1182195 3 0.3992 0.6118 0.000 0.176 0.756 0.000 0.064 0.004
#> GSM1182196 3 0.5229 0.2690 0.000 0.424 0.492 0.000 0.080 0.004
#> GSM1182197 2 0.4494 0.5580 0.000 0.720 0.140 0.000 0.136 0.004
#> GSM1182198 3 0.5131 0.4287 0.000 0.272 0.620 0.000 0.100 0.008
#> GSM1182199 3 0.4650 0.5706 0.000 0.232 0.684 0.000 0.076 0.008
#> GSM1182200 2 0.3063 0.5766 0.000 0.840 0.068 0.000 0.092 0.000
#> GSM1182201 2 0.4046 0.5645 0.000 0.748 0.168 0.000 0.084 0.000
#> GSM1182202 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182203 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182204 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182205 3 0.3987 0.6390 0.000 0.224 0.732 0.000 0.040 0.004
#> GSM1182206 3 0.4034 0.5807 0.000 0.336 0.648 0.000 0.012 0.004
#> GSM1182207 1 0.4294 0.3418 0.692 0.000 0.000 0.000 0.060 0.248
#> GSM1182208 5 0.5759 0.0000 0.392 0.000 0.000 0.000 0.436 0.172
#> GSM1182209 2 0.2325 0.6021 0.000 0.892 0.060 0.000 0.048 0.000
#> GSM1182210 2 0.3626 0.5313 0.000 0.776 0.188 0.000 0.028 0.008
#> GSM1182211 2 0.3050 0.6001 0.000 0.832 0.136 0.000 0.028 0.004
#> GSM1182212 2 0.2586 0.6095 0.000 0.868 0.100 0.000 0.032 0.000
#> GSM1182213 2 0.2451 0.6013 0.000 0.888 0.068 0.000 0.040 0.004
#> GSM1182214 2 0.2365 0.6029 0.000 0.888 0.072 0.000 0.040 0.000
#> GSM1182215 3 0.4689 0.4182 0.000 0.440 0.516 0.000 0.044 0.000
#> GSM1182216 2 0.2563 0.5981 0.000 0.876 0.072 0.000 0.052 0.000
#> GSM1182217 4 0.0146 0.9710 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM1182218 1 0.0146 0.8408 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1182219 2 0.4874 -0.2562 0.000 0.496 0.456 0.000 0.040 0.008
#> GSM1182220 2 0.4726 -0.1308 0.000 0.536 0.424 0.000 0.032 0.008
#> GSM1182221 2 0.4034 0.4320 0.000 0.692 0.280 0.000 0.024 0.004
#> GSM1182222 2 0.4576 0.0966 0.000 0.592 0.368 0.000 0.036 0.004
#> GSM1182223 3 0.4310 0.5078 0.000 0.396 0.580 0.000 0.024 0.000
#> GSM1182224 3 0.3599 0.6394 0.000 0.220 0.756 0.000 0.020 0.004
#> GSM1182225 2 0.3210 0.5831 0.000 0.812 0.152 0.000 0.036 0.000
#> GSM1182226 2 0.4131 0.5738 0.000 0.744 0.180 0.000 0.072 0.004
#> GSM1182227 1 0.0909 0.8362 0.968 0.000 0.000 0.000 0.020 0.012
#> GSM1182228 2 0.3652 0.5440 0.000 0.768 0.188 0.000 0.044 0.000
#> GSM1182229 3 0.4513 0.3947 0.000 0.440 0.528 0.000 0.032 0.000
#> GSM1182230 3 0.4357 0.6278 0.000 0.304 0.660 0.000 0.020 0.016
#> GSM1182231 2 0.4346 0.2805 0.000 0.632 0.336 0.000 0.028 0.004
#> GSM1182232 1 0.0405 0.8423 0.988 0.000 0.000 0.000 0.008 0.004
#> GSM1182233 1 0.0000 0.8416 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182234 1 0.0820 0.8377 0.972 0.000 0.000 0.000 0.016 0.012
#> GSM1182235 2 0.4102 0.4927 0.000 0.720 0.232 0.000 0.044 0.004
#> GSM1182236 1 0.0146 0.8419 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1182237 2 0.4531 0.2062 0.000 0.608 0.352 0.000 0.036 0.004
#> GSM1182238 2 0.3054 0.5897 0.000 0.840 0.116 0.000 0.040 0.004
#> GSM1182239 2 0.1970 0.5938 0.000 0.912 0.028 0.000 0.060 0.000
#> GSM1182240 2 0.2197 0.5905 0.000 0.900 0.044 0.000 0.056 0.000
#> GSM1182241 2 0.2966 0.5920 0.000 0.848 0.076 0.000 0.076 0.000
#> GSM1182242 3 0.4698 0.2987 0.000 0.452 0.504 0.000 0.044 0.000
#> GSM1182243 3 0.4681 0.4108 0.000 0.432 0.524 0.000 0.044 0.000
#> GSM1182244 3 0.3730 0.6299 0.000 0.192 0.768 0.000 0.032 0.008
#> GSM1182245 1 0.0909 0.8357 0.968 0.000 0.000 0.000 0.020 0.012
#> GSM1182246 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 3 0.4286 0.6103 0.000 0.320 0.648 0.000 0.028 0.004
#> GSM1182248 3 0.3876 0.6218 0.000 0.276 0.700 0.000 0.024 0.000
#> GSM1182249 2 0.4972 0.1062 0.000 0.536 0.392 0.000 0.072 0.000
#> GSM1182250 2 0.4760 0.3476 0.000 0.604 0.328 0.000 0.068 0.000
#> GSM1182251 1 0.3221 0.4942 0.736 0.000 0.000 0.000 0.000 0.264
#> GSM1182252 3 0.4152 0.6210 0.000 0.304 0.664 0.000 0.032 0.000
#> GSM1182253 3 0.3860 0.6400 0.000 0.236 0.728 0.000 0.036 0.000
#> GSM1182254 2 0.5007 0.4055 0.000 0.596 0.320 0.000 0.080 0.004
#> GSM1182255 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182256 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182258 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 2 0.5508 0.0302 0.000 0.472 0.412 0.000 0.112 0.004
#> GSM1182261 3 0.4933 0.5389 0.000 0.340 0.588 0.000 0.068 0.004
#> GSM1182262 3 0.4370 0.5664 0.000 0.356 0.616 0.000 0.020 0.008
#> GSM1182263 1 0.3244 0.4915 0.732 0.000 0.000 0.000 0.000 0.268
#> GSM1182264 2 0.4845 0.4230 0.000 0.660 0.208 0.000 0.132 0.000
#> GSM1182265 2 0.5034 0.4105 0.000 0.628 0.240 0.000 0.132 0.000
#> GSM1182266 2 0.4774 0.4824 0.000 0.672 0.192 0.000 0.136 0.000
#> GSM1182267 1 0.0820 0.8377 0.972 0.000 0.000 0.000 0.016 0.012
#> GSM1182268 1 0.0458 0.8392 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM1182269 1 0.0363 0.8400 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1182270 1 0.0260 0.8405 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1182271 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 2 0.4825 0.4995 0.000 0.668 0.180 0.000 0.152 0.000
#> GSM1182275 2 0.4621 0.3309 0.000 0.632 0.304 0.000 0.064 0.000
#> GSM1182276 2 0.4476 0.3616 0.000 0.640 0.308 0.000 0.052 0.000
#> GSM1182277 1 0.0806 0.8354 0.972 0.000 0.000 0.000 0.020 0.008
#> GSM1182278 1 0.0909 0.8362 0.968 0.000 0.000 0.000 0.020 0.012
#> GSM1182279 1 0.3221 0.4942 0.736 0.000 0.000 0.000 0.000 0.264
#> GSM1182280 1 0.3244 0.4915 0.732 0.000 0.000 0.000 0.000 0.268
#> GSM1182281 4 0.0865 0.9451 0.000 0.000 0.000 0.964 0.000 0.036
#> GSM1182282 1 0.1003 0.8359 0.964 0.000 0.000 0.000 0.020 0.016
#> GSM1182283 1 0.1003 0.8367 0.964 0.000 0.000 0.000 0.020 0.016
#> GSM1182284 1 0.1480 0.8237 0.940 0.000 0.000 0.000 0.020 0.040
#> GSM1182285 3 0.3932 0.6326 0.000 0.248 0.720 0.000 0.028 0.004
#> GSM1182286 2 0.4077 0.5318 0.000 0.724 0.228 0.000 0.044 0.004
#> GSM1182287 2 0.4664 -0.1875 0.000 0.484 0.480 0.000 0.032 0.004
#> GSM1182288 3 0.4443 0.5349 0.000 0.368 0.596 0.000 0.036 0.000
#> GSM1182289 1 0.3221 0.4942 0.736 0.000 0.000 0.000 0.000 0.264
#> GSM1182290 1 0.4059 0.4333 0.720 0.000 0.000 0.000 0.052 0.228
#> GSM1182291 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 2 0.3883 0.5211 0.000 0.768 0.088 0.000 0.144 0.000
#> GSM1182292 2 0.3953 0.5429 0.000 0.744 0.196 0.000 0.060 0.000
#> GSM1182293 3 0.5572 0.2346 0.000 0.400 0.500 0.000 0.076 0.024
#> GSM1182294 6 0.6031 0.0000 0.000 0.092 0.220 0.000 0.092 0.596
#> GSM1182295 2 0.4753 0.3307 0.000 0.596 0.348 0.000 0.052 0.004
#> GSM1182296 2 0.5144 0.3213 0.000 0.604 0.304 0.000 0.080 0.012
#> GSM1182298 3 0.4035 0.6097 0.000 0.204 0.740 0.000 0.052 0.004
#> GSM1182299 2 0.3017 0.5746 0.000 0.844 0.072 0.000 0.084 0.000
#> GSM1182300 2 0.5523 -0.0752 0.000 0.484 0.420 0.000 0.076 0.020
#> GSM1182301 2 0.4843 0.4101 0.000 0.616 0.300 0.000 0.084 0.000
#> GSM1182303 3 0.5631 0.2971 0.000 0.372 0.524 0.000 0.068 0.036
#> GSM1182304 1 0.3383 0.4817 0.728 0.000 0.000 0.000 0.004 0.268
#> GSM1182305 4 0.5296 0.2774 0.184 0.000 0.000 0.600 0.000 0.216
#> GSM1182306 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182307 2 0.2641 0.6014 0.000 0.876 0.072 0.000 0.048 0.004
#> GSM1182309 3 0.5453 0.3116 0.000 0.388 0.516 0.000 0.080 0.016
#> GSM1182312 2 0.4831 0.2050 0.000 0.600 0.340 0.000 0.052 0.008
#> GSM1182314 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 2 0.4881 0.4808 0.000 0.656 0.208 0.000 0.136 0.000
#> GSM1182318 2 0.4468 0.5162 0.000 0.696 0.212 0.000 0.092 0.000
#> GSM1182319 3 0.5117 0.5005 0.000 0.288 0.620 0.000 0.076 0.016
#> GSM1182320 2 0.5364 -0.0375 0.000 0.488 0.420 0.000 0.084 0.008
#> GSM1182321 3 0.5576 0.5171 0.000 0.272 0.588 0.000 0.120 0.020
#> GSM1182322 2 0.4851 0.5026 0.000 0.672 0.220 0.000 0.100 0.008
#> GSM1182324 3 0.5304 0.4139 0.000 0.388 0.516 0.000 0.092 0.004
#> GSM1182297 2 0.3134 0.5988 0.000 0.820 0.144 0.000 0.036 0.000
#> GSM1182302 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182308 3 0.5397 0.2306 0.000 0.436 0.484 0.000 0.052 0.028
#> GSM1182310 3 0.5516 0.3256 0.000 0.360 0.536 0.000 0.084 0.020
#> GSM1182311 1 0.0458 0.8373 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM1182313 4 0.0000 0.9737 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.4917 0.4434 0.000 0.656 0.256 0.000 0.072 0.016
#> GSM1182317 2 0.4677 0.4558 0.000 0.664 0.264 0.000 0.064 0.008
#> GSM1182323 1 0.0458 0.8391 0.984 0.000 0.000 0.000 0.000 0.016
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:skmeans 139 0.0773 1.000 2
#> ATC:skmeans 139 0.0843 0.949 3
#> ATC:skmeans 139 0.0843 0.949 4
#> ATC:skmeans 88 0.2204 0.838 5
#> ATC:skmeans 89 0.5862 0.594 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 1.000 0.990 0.997 0.1519 0.927 0.859
#> 4 4 1.000 0.989 0.996 0.0390 0.976 0.947
#> 5 5 0.829 0.926 0.949 0.0548 0.992 0.981
#> 6 6 0.651 0.538 0.806 0.1487 0.913 0.794
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.00 0.977 0.000 0 1.000
#> GSM1182187 3 0.00 0.977 0.000 0 1.000
#> GSM1182188 3 0.00 0.977 0.000 0 1.000
#> GSM1182189 1 0.00 1.000 1.000 0 0.000
#> GSM1182190 1 0.00 1.000 1.000 0 0.000
#> GSM1182191 3 0.00 0.977 0.000 0 1.000
#> GSM1182192 1 0.00 1.000 1.000 0 0.000
#> GSM1182193 1 0.00 1.000 1.000 0 0.000
#> GSM1182194 2 0.00 1.000 0.000 1 0.000
#> GSM1182195 2 0.00 1.000 0.000 1 0.000
#> GSM1182196 2 0.00 1.000 0.000 1 0.000
#> GSM1182197 2 0.00 1.000 0.000 1 0.000
#> GSM1182198 2 0.00 1.000 0.000 1 0.000
#> GSM1182199 2 0.00 1.000 0.000 1 0.000
#> GSM1182200 2 0.00 1.000 0.000 1 0.000
#> GSM1182201 2 0.00 1.000 0.000 1 0.000
#> GSM1182202 3 0.00 0.977 0.000 0 1.000
#> GSM1182203 3 0.00 0.977 0.000 0 1.000
#> GSM1182204 3 0.00 0.977 0.000 0 1.000
#> GSM1182205 2 0.00 1.000 0.000 1 0.000
#> GSM1182206 2 0.00 1.000 0.000 1 0.000
#> GSM1182207 1 0.00 1.000 1.000 0 0.000
#> GSM1182208 1 0.00 1.000 1.000 0 0.000
#> GSM1182209 2 0.00 1.000 0.000 1 0.000
#> GSM1182210 2 0.00 1.000 0.000 1 0.000
#> GSM1182211 2 0.00 1.000 0.000 1 0.000
#> GSM1182212 2 0.00 1.000 0.000 1 0.000
#> GSM1182213 2 0.00 1.000 0.000 1 0.000
#> GSM1182214 2 0.00 1.000 0.000 1 0.000
#> GSM1182215 2 0.00 1.000 0.000 1 0.000
#> GSM1182216 2 0.00 1.000 0.000 1 0.000
#> GSM1182217 3 0.00 0.977 0.000 0 1.000
#> GSM1182218 1 0.00 1.000 1.000 0 0.000
#> GSM1182219 2 0.00 1.000 0.000 1 0.000
#> GSM1182220 2 0.00 1.000 0.000 1 0.000
#> GSM1182221 2 0.00 1.000 0.000 1 0.000
#> GSM1182222 2 0.00 1.000 0.000 1 0.000
#> GSM1182223 2 0.00 1.000 0.000 1 0.000
#> GSM1182224 2 0.00 1.000 0.000 1 0.000
#> GSM1182225 2 0.00 1.000 0.000 1 0.000
#> GSM1182226 2 0.00 1.000 0.000 1 0.000
#> GSM1182227 1 0.00 1.000 1.000 0 0.000
#> GSM1182228 2 0.00 1.000 0.000 1 0.000
#> GSM1182229 2 0.00 1.000 0.000 1 0.000
#> GSM1182230 2 0.00 1.000 0.000 1 0.000
#> GSM1182231 2 0.00 1.000 0.000 1 0.000
#> GSM1182232 1 0.00 1.000 1.000 0 0.000
#> GSM1182233 1 0.00 1.000 1.000 0 0.000
#> GSM1182234 1 0.00 1.000 1.000 0 0.000
#> GSM1182235 2 0.00 1.000 0.000 1 0.000
#> GSM1182236 1 0.00 1.000 1.000 0 0.000
#> GSM1182237 2 0.00 1.000 0.000 1 0.000
#> GSM1182238 2 0.00 1.000 0.000 1 0.000
#> GSM1182239 2 0.00 1.000 0.000 1 0.000
#> GSM1182240 2 0.00 1.000 0.000 1 0.000
#> GSM1182241 2 0.00 1.000 0.000 1 0.000
#> GSM1182242 2 0.00 1.000 0.000 1 0.000
#> GSM1182243 2 0.00 1.000 0.000 1 0.000
#> GSM1182244 2 0.00 1.000 0.000 1 0.000
#> GSM1182245 1 0.00 1.000 1.000 0 0.000
#> GSM1182246 3 0.00 0.977 0.000 0 1.000
#> GSM1182247 2 0.00 1.000 0.000 1 0.000
#> GSM1182248 2 0.00 1.000 0.000 1 0.000
#> GSM1182249 2 0.00 1.000 0.000 1 0.000
#> GSM1182250 2 0.00 1.000 0.000 1 0.000
#> GSM1182251 1 0.00 1.000 1.000 0 0.000
#> GSM1182252 2 0.00 1.000 0.000 1 0.000
#> GSM1182253 2 0.00 1.000 0.000 1 0.000
#> GSM1182254 2 0.00 1.000 0.000 1 0.000
#> GSM1182255 3 0.00 0.977 0.000 0 1.000
#> GSM1182256 3 0.00 0.977 0.000 0 1.000
#> GSM1182257 3 0.00 0.977 0.000 0 1.000
#> GSM1182258 3 0.00 0.977 0.000 0 1.000
#> GSM1182259 3 0.00 0.977 0.000 0 1.000
#> GSM1182260 2 0.00 1.000 0.000 1 0.000
#> GSM1182261 2 0.00 1.000 0.000 1 0.000
#> GSM1182262 2 0.00 1.000 0.000 1 0.000
#> GSM1182263 1 0.00 1.000 1.000 0 0.000
#> GSM1182264 2 0.00 1.000 0.000 1 0.000
#> GSM1182265 2 0.00 1.000 0.000 1 0.000
#> GSM1182266 2 0.00 1.000 0.000 1 0.000
#> GSM1182267 1 0.00 1.000 1.000 0 0.000
#> GSM1182268 1 0.00 1.000 1.000 0 0.000
#> GSM1182269 1 0.00 1.000 1.000 0 0.000
#> GSM1182270 1 0.00 1.000 1.000 0 0.000
#> GSM1182271 3 0.00 0.977 0.000 0 1.000
#> GSM1182272 3 0.00 0.977 0.000 0 1.000
#> GSM1182273 2 0.00 1.000 0.000 1 0.000
#> GSM1182275 2 0.00 1.000 0.000 1 0.000
#> GSM1182276 2 0.00 1.000 0.000 1 0.000
#> GSM1182277 1 0.00 1.000 1.000 0 0.000
#> GSM1182278 1 0.00 1.000 1.000 0 0.000
#> GSM1182279 1 0.00 1.000 1.000 0 0.000
#> GSM1182280 1 0.00 1.000 1.000 0 0.000
#> GSM1182281 1 0.00 1.000 1.000 0 0.000
#> GSM1182282 1 0.00 1.000 1.000 0 0.000
#> GSM1182283 1 0.00 1.000 1.000 0 0.000
#> GSM1182284 1 0.00 1.000 1.000 0 0.000
#> GSM1182285 2 0.00 1.000 0.000 1 0.000
#> GSM1182286 2 0.00 1.000 0.000 1 0.000
#> GSM1182287 2 0.00 1.000 0.000 1 0.000
#> GSM1182288 2 0.00 1.000 0.000 1 0.000
#> GSM1182289 1 0.00 1.000 1.000 0 0.000
#> GSM1182290 1 0.00 1.000 1.000 0 0.000
#> GSM1182291 3 0.00 0.977 0.000 0 1.000
#> GSM1182274 2 0.00 1.000 0.000 1 0.000
#> GSM1182292 2 0.00 1.000 0.000 1 0.000
#> GSM1182293 2 0.00 1.000 0.000 1 0.000
#> GSM1182294 2 0.00 1.000 0.000 1 0.000
#> GSM1182295 2 0.00 1.000 0.000 1 0.000
#> GSM1182296 2 0.00 1.000 0.000 1 0.000
#> GSM1182298 2 0.00 1.000 0.000 1 0.000
#> GSM1182299 2 0.00 1.000 0.000 1 0.000
#> GSM1182300 2 0.00 1.000 0.000 1 0.000
#> GSM1182301 2 0.00 1.000 0.000 1 0.000
#> GSM1182303 2 0.00 1.000 0.000 1 0.000
#> GSM1182304 1 0.00 1.000 1.000 0 0.000
#> GSM1182305 3 0.63 0.106 0.472 0 0.528
#> GSM1182306 3 0.00 0.977 0.000 0 1.000
#> GSM1182307 2 0.00 1.000 0.000 1 0.000
#> GSM1182309 2 0.00 1.000 0.000 1 0.000
#> GSM1182312 2 0.00 1.000 0.000 1 0.000
#> GSM1182314 3 0.00 0.977 0.000 0 1.000
#> GSM1182316 2 0.00 1.000 0.000 1 0.000
#> GSM1182318 2 0.00 1.000 0.000 1 0.000
#> GSM1182319 2 0.00 1.000 0.000 1 0.000
#> GSM1182320 2 0.00 1.000 0.000 1 0.000
#> GSM1182321 2 0.00 1.000 0.000 1 0.000
#> GSM1182322 2 0.00 1.000 0.000 1 0.000
#> GSM1182324 2 0.00 1.000 0.000 1 0.000
#> GSM1182297 2 0.00 1.000 0.000 1 0.000
#> GSM1182302 3 0.00 0.977 0.000 0 1.000
#> GSM1182308 2 0.00 1.000 0.000 1 0.000
#> GSM1182310 2 0.00 1.000 0.000 1 0.000
#> GSM1182311 1 0.00 1.000 1.000 0 0.000
#> GSM1182313 3 0.00 0.977 0.000 0 1.000
#> GSM1182315 2 0.00 1.000 0.000 1 0.000
#> GSM1182317 2 0.00 1.000 0.000 1 0.000
#> GSM1182323 1 0.00 1.000 1.000 0 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.458 0.473 0 0 0.332 0.668
#> GSM1182187 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182188 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182189 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182190 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182191 3 0.410 0.642 0 0 0.744 0.256
#> GSM1182192 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182193 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182194 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182195 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182196 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182197 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182198 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182199 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182200 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182201 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182202 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182203 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182204 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182205 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182206 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182207 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182208 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182209 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182210 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182211 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182212 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182213 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182214 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182215 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182216 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182217 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182218 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182219 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182220 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182221 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182222 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182223 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182224 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182225 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182226 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182227 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182228 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182229 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182230 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182231 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182232 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182233 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182234 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182235 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182236 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182237 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182238 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182239 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182240 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182241 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182242 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182243 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182244 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182245 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182246 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182247 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182248 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182249 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182250 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182251 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182252 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182253 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182254 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182255 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182256 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182257 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182258 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182259 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182260 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182261 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182262 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182263 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182264 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182265 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182266 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182267 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182268 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182269 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182270 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182271 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182272 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182273 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182275 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182276 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182277 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182278 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182279 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182280 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182281 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182282 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182283 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182284 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182285 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182286 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182287 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182288 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182289 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182290 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182291 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182274 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182292 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182293 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182294 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182295 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182296 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182298 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182299 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182300 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182301 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182303 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182304 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182305 3 0.000 0.967 0 0 1.000 0.000
#> GSM1182306 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182307 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182309 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182312 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182314 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182316 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182318 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182319 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182320 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182321 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182322 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182324 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182297 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182302 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182308 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182310 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182311 1 0.000 1.000 1 0 0.000 0.000
#> GSM1182313 4 0.000 0.981 0 0 0.000 1.000
#> GSM1182315 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182317 2 0.000 1.000 0 1 0.000 0.000
#> GSM1182323 1 0.000 1.000 1 0 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 5 0.2561 0.599 0.000 0.000 0.144 0.000 0.856
#> GSM1182187 5 0.4210 0.465 0.000 0.000 0.000 0.412 0.588
#> GSM1182188 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 5 0.2561 0.599 0.000 0.000 0.144 0.000 0.856
#> GSM1182192 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182194 2 0.0609 0.950 0.000 0.980 0.000 0.000 0.020
#> GSM1182195 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182196 2 0.0794 0.953 0.000 0.972 0.000 0.000 0.028
#> GSM1182197 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182198 2 0.2561 0.920 0.000 0.856 0.000 0.000 0.144
#> GSM1182199 2 0.1544 0.946 0.000 0.932 0.000 0.000 0.068
#> GSM1182200 2 0.2424 0.919 0.000 0.868 0.000 0.000 0.132
#> GSM1182201 2 0.2424 0.919 0.000 0.868 0.000 0.000 0.132
#> GSM1182202 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182203 4 0.0963 0.905 0.000 0.000 0.000 0.964 0.036
#> GSM1182204 4 0.4307 -0.356 0.000 0.000 0.000 0.504 0.496
#> GSM1182205 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182206 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182207 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182208 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182209 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182210 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182211 2 0.0510 0.951 0.000 0.984 0.000 0.000 0.016
#> GSM1182212 2 0.2471 0.920 0.000 0.864 0.000 0.000 0.136
#> GSM1182213 2 0.2329 0.921 0.000 0.876 0.000 0.000 0.124
#> GSM1182214 2 0.0510 0.951 0.000 0.984 0.000 0.000 0.016
#> GSM1182215 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182216 2 0.0290 0.952 0.000 0.992 0.000 0.000 0.008
#> GSM1182217 5 0.2561 0.697 0.000 0.000 0.000 0.144 0.856
#> GSM1182218 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182220 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182221 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182222 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182223 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182224 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182225 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182226 2 0.0290 0.951 0.000 0.992 0.000 0.000 0.008
#> GSM1182227 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182228 2 0.2329 0.926 0.000 0.876 0.000 0.000 0.124
#> GSM1182229 2 0.0609 0.950 0.000 0.980 0.000 0.000 0.020
#> GSM1182230 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182231 2 0.0510 0.953 0.000 0.984 0.000 0.000 0.016
#> GSM1182232 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182236 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182238 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182239 2 0.2127 0.929 0.000 0.892 0.000 0.000 0.108
#> GSM1182240 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182241 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182242 2 0.2471 0.923 0.000 0.864 0.000 0.000 0.136
#> GSM1182243 2 0.0609 0.953 0.000 0.980 0.000 0.000 0.020
#> GSM1182244 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182245 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182246 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 2 0.0880 0.952 0.000 0.968 0.000 0.000 0.032
#> GSM1182248 2 0.0880 0.952 0.000 0.968 0.000 0.000 0.032
#> GSM1182249 2 0.1608 0.942 0.000 0.928 0.000 0.000 0.072
#> GSM1182250 2 0.2329 0.921 0.000 0.876 0.000 0.000 0.124
#> GSM1182251 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182252 2 0.0703 0.952 0.000 0.976 0.000 0.000 0.024
#> GSM1182253 2 0.2424 0.925 0.000 0.868 0.000 0.000 0.132
#> GSM1182254 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182255 5 0.4161 0.505 0.000 0.000 0.000 0.392 0.608
#> GSM1182256 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182261 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182262 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182263 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182264 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182265 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182266 2 0.2516 0.920 0.000 0.860 0.000 0.000 0.140
#> GSM1182267 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.2516 0.765 0.000 0.000 0.000 0.860 0.140
#> GSM1182273 2 0.2424 0.919 0.000 0.868 0.000 0.000 0.132
#> GSM1182275 2 0.2471 0.920 0.000 0.864 0.000 0.000 0.136
#> GSM1182276 2 0.1410 0.948 0.000 0.940 0.000 0.000 0.060
#> GSM1182277 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182280 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182281 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182282 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182285 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182286 2 0.2280 0.926 0.000 0.880 0.000 0.000 0.120
#> GSM1182287 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182288 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182289 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182290 1 0.1121 0.953 0.956 0.000 0.044 0.000 0.000
#> GSM1182291 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182292 2 0.2127 0.928 0.000 0.892 0.000 0.000 0.108
#> GSM1182293 2 0.0162 0.952 0.000 0.996 0.000 0.000 0.004
#> GSM1182294 2 0.0404 0.950 0.000 0.988 0.000 0.000 0.012
#> GSM1182295 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182296 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182298 2 0.0794 0.952 0.000 0.972 0.000 0.000 0.028
#> GSM1182299 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182300 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182301 2 0.2329 0.921 0.000 0.876 0.000 0.000 0.124
#> GSM1182303 2 0.0510 0.950 0.000 0.984 0.000 0.000 0.016
#> GSM1182304 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> GSM1182305 3 0.3480 0.700 0.000 0.000 0.752 0.000 0.248
#> GSM1182306 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182307 2 0.0404 0.952 0.000 0.988 0.000 0.000 0.012
#> GSM1182309 2 0.0404 0.950 0.000 0.988 0.000 0.000 0.012
#> GSM1182312 2 0.0162 0.951 0.000 0.996 0.000 0.000 0.004
#> GSM1182314 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 2 0.2377 0.919 0.000 0.872 0.000 0.000 0.128
#> GSM1182318 2 0.2020 0.931 0.000 0.900 0.000 0.000 0.100
#> GSM1182319 2 0.0510 0.952 0.000 0.984 0.000 0.000 0.016
#> GSM1182320 2 0.0290 0.952 0.000 0.992 0.000 0.000 0.008
#> GSM1182321 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182322 2 0.2074 0.930 0.000 0.896 0.000 0.000 0.104
#> GSM1182324 2 0.1851 0.940 0.000 0.912 0.000 0.000 0.088
#> GSM1182297 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182302 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182308 2 0.0404 0.950 0.000 0.988 0.000 0.000 0.012
#> GSM1182310 2 0.0404 0.952 0.000 0.988 0.000 0.000 0.012
#> GSM1182311 1 0.0000 0.998 1.000 0.000 0.000 0.000 0.000
#> GSM1182313 4 0.0000 0.942 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 2 0.0000 0.951 0.000 1.000 0.000 0.000 0.000
#> GSM1182317 2 0.1341 0.945 0.000 0.944 0.000 0.000 0.056
#> GSM1182323 1 0.0000 0.998 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
#> GSM1182186 6 0.0000 0.7536 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1182187 4 0.5963 0.1362 0.000 0.000 0.240 0.440 0.000 0.320
#> GSM1182188 4 0.1387 0.7968 0.000 0.000 0.068 0.932 0.000 0.000
#> GSM1182189 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182190 1 0.0363 0.9743 0.988 0.000 0.012 0.000 0.000 0.000
#> GSM1182191 6 0.0000 0.7536 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1182192 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182193 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182194 2 0.2260 0.5317 0.000 0.860 0.140 0.000 0.000 0.000
#> GSM1182195 2 0.2260 0.5337 0.000 0.860 0.140 0.000 0.000 0.000
#> GSM1182196 2 0.2340 0.5284 0.000 0.852 0.148 0.000 0.000 0.000
#> GSM1182197 2 0.3823 -0.6833 0.000 0.564 0.436 0.000 0.000 0.000
#> GSM1182198 2 0.3847 -0.4529 0.000 0.544 0.456 0.000 0.000 0.000
#> GSM1182199 2 0.2883 0.4822 0.000 0.788 0.212 0.000 0.000 0.000
#> GSM1182200 3 0.3868 0.7530 0.000 0.496 0.504 0.000 0.000 0.000
#> GSM1182201 3 0.3851 0.8284 0.000 0.460 0.540 0.000 0.000 0.000
#> GSM1182202 4 0.2969 0.7455 0.000 0.000 0.224 0.776 0.000 0.000
#> GSM1182203 4 0.3420 0.7261 0.000 0.000 0.240 0.748 0.000 0.012
#> GSM1182204 4 0.5911 0.2101 0.000 0.000 0.240 0.464 0.000 0.296
#> GSM1182205 2 0.2135 0.5634 0.000 0.872 0.128 0.000 0.000 0.000
#> GSM1182206 2 0.1327 0.5838 0.000 0.936 0.064 0.000 0.000 0.000
#> GSM1182207 1 0.0790 0.9726 0.968 0.000 0.032 0.000 0.000 0.000
#> GSM1182208 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182209 2 0.3828 -0.5959 0.000 0.560 0.440 0.000 0.000 0.000
#> GSM1182210 2 0.2416 0.5495 0.000 0.844 0.156 0.000 0.000 0.000
#> GSM1182211 2 0.3101 0.3875 0.000 0.756 0.244 0.000 0.000 0.000
#> GSM1182212 2 0.3747 -0.4026 0.000 0.604 0.396 0.000 0.000 0.000
#> GSM1182213 2 0.3774 -0.5007 0.000 0.592 0.408 0.000 0.000 0.000
#> GSM1182214 2 0.3244 0.3661 0.000 0.732 0.268 0.000 0.000 0.000
#> GSM1182215 2 0.1957 0.5876 0.000 0.888 0.112 0.000 0.000 0.000
#> GSM1182216 2 0.2697 0.5236 0.000 0.812 0.188 0.000 0.000 0.000
#> GSM1182217 6 0.0000 0.7536 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1182218 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182219 2 0.1075 0.5886 0.000 0.952 0.048 0.000 0.000 0.000
#> GSM1182220 2 0.1501 0.5853 0.000 0.924 0.076 0.000 0.000 0.000
#> GSM1182221 2 0.2631 0.5104 0.000 0.820 0.180 0.000 0.000 0.000
#> GSM1182222 2 0.2092 0.5603 0.000 0.876 0.124 0.000 0.000 0.000
#> GSM1182223 2 0.1141 0.5693 0.000 0.948 0.052 0.000 0.000 0.000
#> GSM1182224 2 0.1075 0.5724 0.000 0.952 0.048 0.000 0.000 0.000
#> GSM1182225 2 0.2823 0.5379 0.000 0.796 0.204 0.000 0.000 0.000
#> GSM1182226 2 0.3221 0.4430 0.000 0.736 0.264 0.000 0.000 0.000
#> GSM1182227 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182228 2 0.3706 -0.1674 0.000 0.620 0.380 0.000 0.000 0.000
#> GSM1182229 2 0.1501 0.5718 0.000 0.924 0.076 0.000 0.000 0.000
#> GSM1182230 2 0.2092 0.5500 0.000 0.876 0.124 0.000 0.000 0.000
#> GSM1182231 2 0.2631 0.5599 0.000 0.820 0.180 0.000 0.000 0.000
#> GSM1182232 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182233 1 0.0790 0.9726 0.968 0.000 0.032 0.000 0.000 0.000
#> GSM1182234 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182235 2 0.2697 0.5308 0.000 0.812 0.188 0.000 0.000 0.000
#> GSM1182236 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182237 2 0.2260 0.5732 0.000 0.860 0.140 0.000 0.000 0.000
#> GSM1182238 2 0.3023 0.4908 0.000 0.768 0.232 0.000 0.000 0.000
#> GSM1182239 2 0.3823 -0.5844 0.000 0.564 0.436 0.000 0.000 0.000
#> GSM1182240 3 0.3868 0.7351 0.000 0.496 0.504 0.000 0.000 0.000
#> GSM1182241 3 0.3851 0.8301 0.000 0.460 0.540 0.000 0.000 0.000
#> GSM1182242 2 0.3747 -0.2578 0.000 0.604 0.396 0.000 0.000 0.000
#> GSM1182243 2 0.3126 0.5102 0.000 0.752 0.248 0.000 0.000 0.000
#> GSM1182244 2 0.1444 0.5782 0.000 0.928 0.072 0.000 0.000 0.000
#> GSM1182245 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182246 4 0.1267 0.8052 0.000 0.000 0.060 0.940 0.000 0.000
#> GSM1182247 2 0.2378 0.5653 0.000 0.848 0.152 0.000 0.000 0.000
#> GSM1182248 2 0.2762 0.5270 0.000 0.804 0.196 0.000 0.000 0.000
#> GSM1182249 2 0.3309 0.3307 0.000 0.720 0.280 0.000 0.000 0.000
#> GSM1182250 2 0.3717 -0.4138 0.000 0.616 0.384 0.000 0.000 0.000
#> GSM1182251 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 2 0.3371 0.4324 0.000 0.708 0.292 0.000 0.000 0.000
#> GSM1182253 2 0.3482 0.0818 0.000 0.684 0.316 0.000 0.000 0.000
#> GSM1182254 2 0.3843 -0.7257 0.000 0.548 0.452 0.000 0.000 0.000
#> GSM1182255 6 0.5951 -0.1972 0.000 0.000 0.220 0.368 0.000 0.412
#> GSM1182256 4 0.3023 0.7407 0.000 0.000 0.232 0.768 0.000 0.000
#> GSM1182257 4 0.0146 0.8127 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182258 4 0.0260 0.8114 0.000 0.000 0.008 0.992 0.000 0.000
#> GSM1182259 4 0.1387 0.7968 0.000 0.000 0.068 0.932 0.000 0.000
#> GSM1182260 3 0.3847 0.7917 0.000 0.456 0.544 0.000 0.000 0.000
#> GSM1182261 2 0.2092 0.5565 0.000 0.876 0.124 0.000 0.000 0.000
#> GSM1182262 2 0.2178 0.5891 0.000 0.868 0.132 0.000 0.000 0.000
#> GSM1182263 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182264 3 0.3833 0.8382 0.000 0.444 0.556 0.000 0.000 0.000
#> GSM1182265 3 0.3860 0.7999 0.000 0.472 0.528 0.000 0.000 0.000
#> GSM1182266 3 0.3857 0.7983 0.000 0.468 0.532 0.000 0.000 0.000
#> GSM1182267 1 0.0146 0.9744 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182268 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182269 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182270 1 0.0146 0.9740 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182271 4 0.1387 0.7968 0.000 0.000 0.068 0.932 0.000 0.000
#> GSM1182272 4 0.4075 0.6918 0.000 0.000 0.240 0.712 0.000 0.048
#> GSM1182273 3 0.3866 0.6526 0.000 0.484 0.516 0.000 0.000 0.000
#> GSM1182275 2 0.3862 -0.6976 0.000 0.524 0.476 0.000 0.000 0.000
#> GSM1182276 2 0.3515 0.1601 0.000 0.676 0.324 0.000 0.000 0.000
#> GSM1182277 1 0.0146 0.9740 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1182278 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182279 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182280 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182281 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182282 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182283 1 0.0790 0.9726 0.968 0.000 0.032 0.000 0.000 0.000
#> GSM1182284 1 0.0260 0.9736 0.992 0.000 0.008 0.000 0.000 0.000
#> GSM1182285 2 0.2260 0.5377 0.000 0.860 0.140 0.000 0.000 0.000
#> GSM1182286 2 0.3563 -0.1508 0.000 0.664 0.336 0.000 0.000 0.000
#> GSM1182287 2 0.2135 0.5310 0.000 0.872 0.128 0.000 0.000 0.000
#> GSM1182288 2 0.3221 0.3918 0.000 0.736 0.264 0.000 0.000 0.000
#> GSM1182289 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182290 1 0.2593 0.8181 0.844 0.000 0.008 0.000 0.148 0.000
#> GSM1182291 4 0.0000 0.8123 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 3 0.3810 0.8125 0.000 0.428 0.572 0.000 0.000 0.000
#> GSM1182292 2 0.3737 -0.4206 0.000 0.608 0.392 0.000 0.000 0.000
#> GSM1182293 2 0.2416 0.5320 0.000 0.844 0.156 0.000 0.000 0.000
#> GSM1182294 2 0.1556 0.5831 0.000 0.920 0.080 0.000 0.000 0.000
#> GSM1182295 2 0.2178 0.5457 0.000 0.868 0.132 0.000 0.000 0.000
#> GSM1182296 2 0.1501 0.5888 0.000 0.924 0.076 0.000 0.000 0.000
#> GSM1182298 2 0.2730 0.5180 0.000 0.808 0.192 0.000 0.000 0.000
#> GSM1182299 3 0.3828 0.8013 0.000 0.440 0.560 0.000 0.000 0.000
#> GSM1182300 2 0.2697 0.5211 0.000 0.812 0.188 0.000 0.000 0.000
#> GSM1182301 2 0.3847 -0.6933 0.000 0.544 0.456 0.000 0.000 0.000
#> GSM1182303 2 0.1141 0.5807 0.000 0.948 0.052 0.000 0.000 0.000
#> GSM1182304 5 0.0000 0.9467 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182305 5 0.3911 0.4780 0.000 0.000 0.008 0.000 0.624 0.368
#> GSM1182306 4 0.1387 0.7968 0.000 0.000 0.068 0.932 0.000 0.000
#> GSM1182307 2 0.2912 0.5045 0.000 0.784 0.216 0.000 0.000 0.000
#> GSM1182309 2 0.1556 0.5934 0.000 0.920 0.080 0.000 0.000 0.000
#> GSM1182312 2 0.2697 0.5044 0.000 0.812 0.188 0.000 0.000 0.000
#> GSM1182314 4 0.0146 0.8127 0.000 0.000 0.004 0.996 0.000 0.000
#> GSM1182316 2 0.3843 -0.6295 0.000 0.548 0.452 0.000 0.000 0.000
#> GSM1182318 2 0.3706 -0.3122 0.000 0.620 0.380 0.000 0.000 0.000
#> GSM1182319 2 0.2912 0.5548 0.000 0.784 0.216 0.000 0.000 0.000
#> GSM1182320 2 0.3175 0.5140 0.000 0.744 0.256 0.000 0.000 0.000
#> GSM1182321 2 0.2697 0.5754 0.000 0.812 0.188 0.000 0.000 0.000
#> GSM1182322 2 0.3765 -0.3276 0.000 0.596 0.404 0.000 0.000 0.000
#> GSM1182324 2 0.3151 0.4029 0.000 0.748 0.252 0.000 0.000 0.000
#> GSM1182297 2 0.2996 0.5425 0.000 0.772 0.228 0.000 0.000 0.000
#> GSM1182302 4 0.2730 0.7614 0.000 0.000 0.192 0.808 0.000 0.000
#> GSM1182308 2 0.1957 0.5885 0.000 0.888 0.112 0.000 0.000 0.000
#> GSM1182310 2 0.3198 0.4733 0.000 0.740 0.260 0.000 0.000 0.000
#> GSM1182311 1 0.0937 0.9709 0.960 0.000 0.040 0.000 0.000 0.000
#> GSM1182313 4 0.1387 0.7968 0.000 0.000 0.068 0.932 0.000 0.000
#> GSM1182315 2 0.2854 0.4761 0.000 0.792 0.208 0.000 0.000 0.000
#> GSM1182317 2 0.3547 0.1675 0.000 0.668 0.332 0.000 0.000 0.000
#> GSM1182323 1 0.0260 0.9736 0.992 0.000 0.008 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:pam 139 0.0773 1.000 2
#> ATC:pam 138 0.0646 0.899 3
#> ATC:pam 138 0.1724 0.793 4
#> ATC:pam 137 0.1858 0.777 5
#> ATC:pam 104 0.0967 0.818 6
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 46361 rows and 139 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 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.591 0.840 0.786 0.2677 1.000 1.000
#> 4 4 0.611 0.469 0.739 0.1278 0.830 0.674
#> 5 5 0.616 0.518 0.720 0.0910 0.784 0.482
#> 6 6 0.659 0.580 0.730 0.0643 0.845 0.491
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 1 0.5397 0.881 0.720 0.000 0.280
#> GSM1182187 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182188 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182189 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182190 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182191 1 0.5397 0.881 0.720 0.000 0.280
#> GSM1182192 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182193 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182194 2 0.2356 0.816 0.000 0.928 0.072
#> GSM1182195 2 0.2261 0.815 0.000 0.932 0.068
#> GSM1182196 2 0.4750 0.837 0.000 0.784 0.216
#> GSM1182197 2 0.6154 0.817 0.000 0.592 0.408
#> GSM1182198 2 0.3816 0.833 0.000 0.852 0.148
#> GSM1182199 2 0.2959 0.817 0.000 0.900 0.100
#> GSM1182200 2 0.6026 0.826 0.000 0.624 0.376
#> GSM1182201 2 0.5465 0.825 0.000 0.712 0.288
#> GSM1182202 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182203 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182204 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182205 2 0.3686 0.785 0.000 0.860 0.140
#> GSM1182206 2 0.3816 0.782 0.000 0.852 0.148
#> GSM1182207 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182208 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182209 2 0.6180 0.812 0.000 0.584 0.416
#> GSM1182210 2 0.5905 0.842 0.000 0.648 0.352
#> GSM1182211 2 0.6095 0.830 0.000 0.608 0.392
#> GSM1182212 2 0.6045 0.831 0.000 0.620 0.380
#> GSM1182213 2 0.6126 0.821 0.000 0.600 0.400
#> GSM1182214 2 0.6140 0.828 0.000 0.596 0.404
#> GSM1182215 2 0.2711 0.809 0.000 0.912 0.088
#> GSM1182216 2 0.6154 0.827 0.000 0.592 0.408
#> GSM1182217 1 0.5988 0.869 0.632 0.000 0.368
#> GSM1182218 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182219 2 0.4235 0.781 0.000 0.824 0.176
#> GSM1182220 2 0.4931 0.796 0.000 0.768 0.232
#> GSM1182221 2 0.5785 0.848 0.000 0.668 0.332
#> GSM1182222 2 0.5529 0.805 0.000 0.704 0.296
#> GSM1182223 2 0.3941 0.776 0.000 0.844 0.156
#> GSM1182224 2 0.3941 0.776 0.000 0.844 0.156
#> GSM1182225 2 0.5988 0.838 0.000 0.632 0.368
#> GSM1182226 2 0.5988 0.832 0.000 0.632 0.368
#> GSM1182227 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182228 2 0.3816 0.847 0.000 0.852 0.148
#> GSM1182229 2 0.3941 0.776 0.000 0.844 0.156
#> GSM1182230 2 0.2878 0.806 0.000 0.904 0.096
#> GSM1182231 2 0.1529 0.839 0.000 0.960 0.040
#> GSM1182232 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182233 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182234 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182235 2 0.6045 0.823 0.000 0.620 0.380
#> GSM1182236 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182237 2 0.3038 0.803 0.000 0.896 0.104
#> GSM1182238 2 0.6168 0.827 0.000 0.588 0.412
#> GSM1182239 2 0.6286 0.795 0.000 0.536 0.464
#> GSM1182240 2 0.6192 0.810 0.000 0.580 0.420
#> GSM1182241 2 0.5327 0.814 0.000 0.728 0.272
#> GSM1182242 2 0.2261 0.827 0.000 0.932 0.068
#> GSM1182243 2 0.1753 0.842 0.000 0.952 0.048
#> GSM1182244 2 0.2165 0.819 0.000 0.936 0.064
#> GSM1182245 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182246 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182247 2 0.1529 0.825 0.000 0.960 0.040
#> GSM1182248 2 0.0892 0.828 0.000 0.980 0.020
#> GSM1182249 2 0.4399 0.846 0.000 0.812 0.188
#> GSM1182250 2 0.4750 0.843 0.000 0.784 0.216
#> GSM1182251 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182252 2 0.1411 0.823 0.000 0.964 0.036
#> GSM1182253 2 0.2959 0.804 0.000 0.900 0.100
#> GSM1182254 2 0.6062 0.826 0.000 0.616 0.384
#> GSM1182255 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182256 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182257 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182258 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182259 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182260 2 0.5926 0.832 0.000 0.644 0.356
#> GSM1182261 2 0.3412 0.843 0.000 0.876 0.124
#> GSM1182262 2 0.3340 0.842 0.000 0.880 0.120
#> GSM1182263 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182264 2 0.5397 0.811 0.000 0.720 0.280
#> GSM1182265 2 0.5291 0.814 0.000 0.732 0.268
#> GSM1182266 2 0.5363 0.812 0.000 0.724 0.276
#> GSM1182267 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182268 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182269 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182270 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182271 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182272 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182273 2 0.5254 0.814 0.000 0.736 0.264
#> GSM1182275 2 0.4291 0.842 0.000 0.820 0.180
#> GSM1182276 2 0.5327 0.821 0.000 0.728 0.272
#> GSM1182277 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182278 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182279 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182280 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182281 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182282 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182283 1 0.0000 0.854 1.000 0.000 0.000
#> GSM1182284 1 0.0237 0.855 0.996 0.000 0.004
#> GSM1182285 2 0.2448 0.813 0.000 0.924 0.076
#> GSM1182286 2 0.4796 0.856 0.000 0.780 0.220
#> GSM1182287 2 0.1643 0.839 0.000 0.956 0.044
#> GSM1182288 2 0.2066 0.819 0.000 0.940 0.060
#> GSM1182289 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182290 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182291 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182274 2 0.5254 0.814 0.000 0.736 0.264
#> GSM1182292 2 0.6111 0.821 0.000 0.604 0.396
#> GSM1182293 2 0.4702 0.837 0.000 0.788 0.212
#> GSM1182294 2 0.4399 0.840 0.000 0.812 0.188
#> GSM1182295 2 0.5254 0.841 0.000 0.736 0.264
#> GSM1182296 2 0.5529 0.840 0.000 0.704 0.296
#> GSM1182298 2 0.2537 0.817 0.000 0.920 0.080
#> GSM1182299 2 0.6291 0.793 0.000 0.532 0.468
#> GSM1182300 2 0.4654 0.837 0.000 0.792 0.208
#> GSM1182301 2 0.5882 0.833 0.000 0.652 0.348
#> GSM1182303 2 0.4654 0.837 0.000 0.792 0.208
#> GSM1182304 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182305 1 0.5138 0.884 0.748 0.000 0.252
#> GSM1182306 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182307 2 0.5948 0.834 0.000 0.640 0.360
#> GSM1182309 2 0.4452 0.839 0.000 0.808 0.192
#> GSM1182312 2 0.5678 0.841 0.000 0.684 0.316
#> GSM1182314 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182316 2 0.6140 0.820 0.000 0.596 0.404
#> GSM1182318 2 0.6140 0.819 0.000 0.596 0.404
#> GSM1182319 2 0.4235 0.839 0.000 0.824 0.176
#> GSM1182320 2 0.6026 0.828 0.000 0.624 0.376
#> GSM1182321 2 0.4235 0.839 0.000 0.824 0.176
#> GSM1182322 2 0.6079 0.825 0.000 0.612 0.388
#> GSM1182324 2 0.4346 0.840 0.000 0.816 0.184
#> GSM1182297 2 0.5733 0.841 0.000 0.676 0.324
#> GSM1182302 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182308 2 0.4702 0.837 0.000 0.788 0.212
#> GSM1182310 2 0.4346 0.840 0.000 0.816 0.184
#> GSM1182311 1 0.0237 0.855 0.996 0.000 0.004
#> GSM1182313 1 0.6008 0.868 0.628 0.000 0.372
#> GSM1182315 2 0.5591 0.839 0.000 0.696 0.304
#> GSM1182317 2 0.5968 0.829 0.000 0.636 0.364
#> GSM1182323 1 0.0237 0.855 0.996 0.000 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.7646 -0.1890 0.384 0.000 0.208 0.408
#> GSM1182187 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182188 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182189 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182191 4 0.7646 -0.1890 0.384 0.000 0.208 0.408
#> GSM1182192 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182194 2 0.4994 -0.5991 0.000 0.520 0.480 0.000
#> GSM1182195 2 0.4999 -0.6578 0.000 0.508 0.492 0.000
#> GSM1182196 2 0.3266 0.3355 0.000 0.832 0.168 0.000
#> GSM1182197 2 0.2281 0.4731 0.000 0.904 0.096 0.000
#> GSM1182198 2 0.4972 -0.1305 0.000 0.544 0.456 0.000
#> GSM1182199 2 0.4999 -0.4824 0.000 0.508 0.492 0.000
#> GSM1182200 2 0.4477 0.4103 0.000 0.688 0.312 0.000
#> GSM1182201 2 0.4605 0.3490 0.000 0.664 0.336 0.000
#> GSM1182202 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182203 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182204 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182205 3 0.4961 0.8276 0.000 0.448 0.552 0.000
#> GSM1182206 3 0.4925 0.8367 0.000 0.428 0.572 0.000
#> GSM1182207 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182208 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182209 2 0.4500 0.3935 0.000 0.684 0.316 0.000
#> GSM1182210 2 0.4679 0.1780 0.000 0.648 0.352 0.000
#> GSM1182211 2 0.4605 0.2458 0.000 0.664 0.336 0.000
#> GSM1182212 2 0.4585 0.3097 0.000 0.668 0.332 0.000
#> GSM1182213 2 0.4661 0.3632 0.000 0.652 0.348 0.000
#> GSM1182214 2 0.4543 0.2941 0.000 0.676 0.324 0.000
#> GSM1182215 3 0.4989 0.7859 0.000 0.472 0.528 0.000
#> GSM1182216 2 0.4643 0.3080 0.000 0.656 0.344 0.000
#> GSM1182217 4 0.3725 0.7666 0.008 0.000 0.180 0.812
#> GSM1182218 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182219 3 0.4830 0.7793 0.000 0.392 0.608 0.000
#> GSM1182220 3 0.4925 0.7106 0.000 0.428 0.572 0.000
#> GSM1182221 2 0.4406 0.2124 0.000 0.700 0.300 0.000
#> GSM1182222 3 0.4992 0.5520 0.000 0.476 0.524 0.000
#> GSM1182223 3 0.4907 0.8344 0.000 0.420 0.580 0.000
#> GSM1182224 3 0.4907 0.8344 0.000 0.420 0.580 0.000
#> GSM1182225 2 0.4624 0.2341 0.000 0.660 0.340 0.000
#> GSM1182226 2 0.4522 0.3168 0.000 0.680 0.320 0.000
#> GSM1182227 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182228 2 0.4331 0.1657 0.000 0.712 0.288 0.000
#> GSM1182229 3 0.4916 0.8365 0.000 0.424 0.576 0.000
#> GSM1182230 3 0.4999 0.6876 0.000 0.492 0.508 0.000
#> GSM1182231 2 0.4661 -0.1279 0.000 0.652 0.348 0.000
#> GSM1182232 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182235 2 0.4967 -0.3619 0.000 0.548 0.452 0.000
#> GSM1182236 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182237 3 0.4961 0.8267 0.000 0.448 0.552 0.000
#> GSM1182238 2 0.4713 0.2635 0.000 0.640 0.360 0.000
#> GSM1182239 2 0.3569 0.4328 0.000 0.804 0.196 0.000
#> GSM1182240 2 0.4500 0.4038 0.000 0.684 0.316 0.000
#> GSM1182241 2 0.4643 0.3569 0.000 0.656 0.344 0.000
#> GSM1182242 2 0.4933 -0.5068 0.000 0.568 0.432 0.000
#> GSM1182243 2 0.4679 -0.0860 0.000 0.648 0.352 0.000
#> GSM1182244 2 0.4985 -0.5832 0.000 0.532 0.468 0.000
#> GSM1182245 1 0.0188 0.8511 0.996 0.000 0.004 0.000
#> GSM1182246 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182247 2 0.4933 -0.4709 0.000 0.568 0.432 0.000
#> GSM1182248 2 0.4877 -0.2698 0.000 0.592 0.408 0.000
#> GSM1182249 2 0.4040 0.3167 0.000 0.752 0.248 0.000
#> GSM1182250 2 0.3649 0.3963 0.000 0.796 0.204 0.000
#> GSM1182251 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182252 2 0.4933 -0.4695 0.000 0.568 0.432 0.000
#> GSM1182253 3 0.4977 0.8044 0.000 0.460 0.540 0.000
#> GSM1182254 2 0.1792 0.4842 0.000 0.932 0.068 0.000
#> GSM1182255 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182256 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182257 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182258 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182259 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182260 2 0.2149 0.4783 0.000 0.912 0.088 0.000
#> GSM1182261 2 0.4500 -0.0386 0.000 0.684 0.316 0.000
#> GSM1182262 2 0.3764 0.2443 0.000 0.784 0.216 0.000
#> GSM1182263 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182264 2 0.4888 0.2639 0.000 0.588 0.412 0.000
#> GSM1182265 2 0.4866 0.2839 0.000 0.596 0.404 0.000
#> GSM1182266 2 0.4830 0.2888 0.000 0.608 0.392 0.000
#> GSM1182267 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182272 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182273 2 0.4746 0.3270 0.000 0.632 0.368 0.000
#> GSM1182275 2 0.4790 -0.0669 0.000 0.620 0.380 0.000
#> GSM1182276 3 0.4994 0.6057 0.000 0.480 0.520 0.000
#> GSM1182277 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182279 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182280 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182281 1 0.6745 0.6301 0.612 0.000 0.176 0.212
#> GSM1182282 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.8521 1.000 0.000 0.000 0.000
#> GSM1182284 1 0.0188 0.8507 0.996 0.000 0.000 0.004
#> GSM1182285 2 0.4996 -0.6470 0.000 0.516 0.484 0.000
#> GSM1182286 2 0.3610 0.3195 0.000 0.800 0.200 0.000
#> GSM1182287 2 0.4522 -0.0512 0.000 0.680 0.320 0.000
#> GSM1182288 2 0.4961 -0.5497 0.000 0.552 0.448 0.000
#> GSM1182289 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182290 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182291 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182274 2 0.4746 0.3270 0.000 0.632 0.368 0.000
#> GSM1182292 2 0.2216 0.4813 0.000 0.908 0.092 0.000
#> GSM1182293 2 0.3610 0.3369 0.000 0.800 0.200 0.000
#> GSM1182294 2 0.3444 0.3158 0.000 0.816 0.184 0.000
#> GSM1182295 2 0.3219 0.3870 0.000 0.836 0.164 0.000
#> GSM1182296 2 0.2704 0.4261 0.000 0.876 0.124 0.000
#> GSM1182298 2 0.4985 -0.5517 0.000 0.532 0.468 0.000
#> GSM1182299 2 0.3528 0.4298 0.000 0.808 0.192 0.000
#> GSM1182300 2 0.3400 0.3417 0.000 0.820 0.180 0.000
#> GSM1182301 2 0.2408 0.4642 0.000 0.896 0.104 0.000
#> GSM1182303 2 0.3610 0.3325 0.000 0.800 0.200 0.000
#> GSM1182304 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182305 1 0.7007 0.6141 0.580 0.000 0.208 0.212
#> GSM1182306 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182307 2 0.3528 0.4397 0.000 0.808 0.192 0.000
#> GSM1182309 2 0.3764 0.3235 0.000 0.784 0.216 0.000
#> GSM1182312 2 0.3074 0.4225 0.000 0.848 0.152 0.000
#> GSM1182314 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182316 2 0.2530 0.4652 0.000 0.888 0.112 0.000
#> GSM1182318 2 0.1867 0.4799 0.000 0.928 0.072 0.000
#> GSM1182319 2 0.3266 0.3248 0.000 0.832 0.168 0.000
#> GSM1182320 2 0.2345 0.4852 0.000 0.900 0.100 0.000
#> GSM1182321 2 0.3400 0.3108 0.000 0.820 0.180 0.000
#> GSM1182322 2 0.2281 0.4774 0.000 0.904 0.096 0.000
#> GSM1182324 2 0.3266 0.3251 0.000 0.832 0.168 0.000
#> GSM1182297 2 0.2868 0.4657 0.000 0.864 0.136 0.000
#> GSM1182302 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182308 2 0.3688 0.3272 0.000 0.792 0.208 0.000
#> GSM1182310 2 0.3311 0.3217 0.000 0.828 0.172 0.000
#> GSM1182311 1 0.0817 0.8448 0.976 0.000 0.024 0.000
#> GSM1182313 4 0.0000 0.9286 0.000 0.000 0.000 1.000
#> GSM1182315 2 0.2589 0.4275 0.000 0.884 0.116 0.000
#> GSM1182317 2 0.1302 0.4666 0.000 0.956 0.044 0.000
#> GSM1182323 1 0.0921 0.8433 0.972 0.000 0.028 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 5 0.5447 0.75946 0.172 0.000 0.000 0.168 0.660
#> GSM1182187 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182188 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182189 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182190 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182191 5 0.5447 0.75946 0.172 0.000 0.000 0.168 0.660
#> GSM1182192 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182194 3 0.3409 0.35409 0.000 0.144 0.824 0.000 0.032
#> GSM1182195 3 0.2535 0.43558 0.000 0.076 0.892 0.000 0.032
#> GSM1182196 3 0.5831 0.20641 0.000 0.160 0.604 0.000 0.236
#> GSM1182197 2 0.5483 0.37334 0.000 0.512 0.424 0.000 0.064
#> GSM1182198 3 0.4808 -0.07706 0.000 0.348 0.620 0.000 0.032
#> GSM1182199 3 0.3977 0.26477 0.000 0.204 0.764 0.000 0.032
#> GSM1182200 2 0.4238 0.38892 0.000 0.628 0.368 0.000 0.004
#> GSM1182201 3 0.4942 0.01933 0.000 0.432 0.540 0.000 0.028
#> GSM1182202 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182203 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182204 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182205 3 0.3757 0.42192 0.000 0.208 0.772 0.000 0.020
#> GSM1182206 3 0.4113 0.39926 0.000 0.232 0.740 0.000 0.028
#> GSM1182207 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182208 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182209 2 0.4288 0.30504 0.000 0.612 0.384 0.000 0.004
#> GSM1182210 3 0.4557 0.17423 0.000 0.476 0.516 0.000 0.008
#> GSM1182211 3 0.4256 0.22280 0.000 0.436 0.564 0.000 0.000
#> GSM1182212 2 0.4291 0.00341 0.000 0.536 0.464 0.000 0.000
#> GSM1182213 2 0.3999 0.30557 0.000 0.656 0.344 0.000 0.000
#> GSM1182214 2 0.4450 -0.11673 0.000 0.508 0.488 0.000 0.004
#> GSM1182215 3 0.3958 0.42296 0.000 0.184 0.776 0.000 0.040
#> GSM1182216 2 0.4114 0.06859 0.000 0.624 0.376 0.000 0.000
#> GSM1182217 4 0.3766 0.61947 0.004 0.000 0.000 0.728 0.268
#> GSM1182218 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182219 3 0.4958 0.31745 0.000 0.372 0.592 0.000 0.036
#> GSM1182220 3 0.4555 0.23483 0.000 0.472 0.520 0.000 0.008
#> GSM1182221 3 0.4557 0.19464 0.000 0.476 0.516 0.000 0.008
#> GSM1182222 3 0.4560 0.22156 0.000 0.484 0.508 0.000 0.008
#> GSM1182223 3 0.4254 0.39296 0.000 0.220 0.740 0.000 0.040
#> GSM1182224 3 0.3849 0.39870 0.000 0.232 0.752 0.000 0.016
#> GSM1182225 3 0.4437 0.18016 0.000 0.464 0.532 0.000 0.004
#> GSM1182226 2 0.4227 0.06828 0.000 0.580 0.420 0.000 0.000
#> GSM1182227 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182228 3 0.6738 -0.35964 0.000 0.320 0.408 0.000 0.272
#> GSM1182229 3 0.4254 0.39296 0.000 0.220 0.740 0.000 0.040
#> GSM1182230 3 0.3278 0.44389 0.000 0.156 0.824 0.000 0.020
#> GSM1182231 3 0.3806 0.43286 0.000 0.084 0.812 0.000 0.104
#> GSM1182232 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182234 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182235 2 0.4307 -0.24595 0.000 0.500 0.500 0.000 0.000
#> GSM1182236 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.4028 0.41824 0.000 0.192 0.768 0.000 0.040
#> GSM1182238 2 0.4383 -0.03188 0.000 0.572 0.424 0.000 0.004
#> GSM1182239 2 0.4184 0.48475 0.000 0.700 0.284 0.000 0.016
#> GSM1182240 2 0.3949 0.45900 0.000 0.668 0.332 0.000 0.000
#> GSM1182241 2 0.6046 0.47081 0.000 0.524 0.344 0.000 0.132
#> GSM1182242 3 0.2540 0.42969 0.000 0.088 0.888 0.000 0.024
#> GSM1182243 3 0.3242 0.36746 0.000 0.116 0.844 0.000 0.040
#> GSM1182244 3 0.2712 0.46368 0.000 0.088 0.880 0.000 0.032
#> GSM1182245 1 0.0162 0.96797 0.996 0.000 0.000 0.000 0.004
#> GSM1182246 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182247 3 0.3051 0.45275 0.000 0.120 0.852 0.000 0.028
#> GSM1182248 3 0.2278 0.45319 0.000 0.060 0.908 0.000 0.032
#> GSM1182249 3 0.5642 0.11358 0.000 0.136 0.624 0.000 0.240
#> GSM1182250 3 0.6455 -0.24873 0.000 0.264 0.500 0.000 0.236
#> GSM1182251 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182252 3 0.2570 0.46240 0.000 0.084 0.888 0.000 0.028
#> GSM1182253 3 0.3550 0.43345 0.000 0.184 0.796 0.000 0.020
#> GSM1182254 3 0.6388 -0.16712 0.000 0.284 0.508 0.000 0.208
#> GSM1182255 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182256 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182257 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182258 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182259 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182260 3 0.6574 -0.25239 0.000 0.288 0.468 0.000 0.244
#> GSM1182261 3 0.2850 0.46268 0.000 0.092 0.872 0.000 0.036
#> GSM1182262 3 0.4010 0.37286 0.000 0.136 0.792 0.000 0.072
#> GSM1182263 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182264 2 0.6773 0.39161 0.000 0.396 0.304 0.000 0.300
#> GSM1182265 2 0.6734 0.37404 0.000 0.408 0.324 0.000 0.268
#> GSM1182266 2 0.6792 0.39067 0.000 0.380 0.324 0.000 0.296
#> GSM1182267 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182269 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182270 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182271 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182272 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182273 2 0.6783 0.39128 0.000 0.388 0.316 0.000 0.296
#> GSM1182275 3 0.5188 0.19373 0.000 0.328 0.612 0.000 0.060
#> GSM1182276 3 0.4555 0.23365 0.000 0.472 0.520 0.000 0.008
#> GSM1182277 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182280 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182281 1 0.5433 -0.02437 0.620 0.000 0.000 0.092 0.288
#> GSM1182282 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.97186 1.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0290 0.96350 0.992 0.000 0.000 0.000 0.008
#> GSM1182285 3 0.2344 0.44597 0.000 0.064 0.904 0.000 0.032
#> GSM1182286 3 0.4199 0.38419 0.000 0.180 0.764 0.000 0.056
#> GSM1182287 3 0.2139 0.45621 0.000 0.052 0.916 0.000 0.032
#> GSM1182288 3 0.2388 0.46145 0.000 0.072 0.900 0.000 0.028
#> GSM1182289 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182290 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182291 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182274 2 0.6555 0.43257 0.000 0.460 0.320 0.000 0.220
#> GSM1182292 2 0.4562 0.27396 0.000 0.500 0.492 0.000 0.008
#> GSM1182293 3 0.5708 0.15649 0.000 0.300 0.588 0.000 0.112
#> GSM1182294 3 0.5472 0.23520 0.000 0.156 0.656 0.000 0.188
#> GSM1182295 3 0.4419 0.25812 0.000 0.312 0.668 0.000 0.020
#> GSM1182296 3 0.5252 0.02368 0.000 0.364 0.580 0.000 0.056
#> GSM1182298 3 0.2654 0.42308 0.000 0.084 0.884 0.000 0.032
#> GSM1182299 2 0.4138 0.48456 0.000 0.708 0.276 0.000 0.016
#> GSM1182300 3 0.6018 0.06039 0.000 0.272 0.568 0.000 0.160
#> GSM1182301 2 0.5071 0.38166 0.000 0.540 0.424 0.000 0.036
#> GSM1182303 3 0.5851 0.15971 0.000 0.288 0.580 0.000 0.132
#> GSM1182304 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182305 5 0.4306 0.94531 0.328 0.000 0.000 0.012 0.660
#> GSM1182306 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182307 3 0.4305 0.03391 0.000 0.488 0.512 0.000 0.000
#> GSM1182309 3 0.5265 0.23712 0.000 0.248 0.656 0.000 0.096
#> GSM1182312 3 0.4620 0.25911 0.000 0.392 0.592 0.000 0.016
#> GSM1182314 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182316 2 0.5815 0.44139 0.000 0.540 0.356 0.000 0.104
#> GSM1182318 2 0.5359 0.40521 0.000 0.532 0.412 0.000 0.056
#> GSM1182319 3 0.5440 0.23936 0.000 0.156 0.660 0.000 0.184
#> GSM1182320 3 0.5236 -0.24308 0.000 0.464 0.492 0.000 0.044
#> GSM1182321 3 0.5339 0.25931 0.000 0.152 0.672 0.000 0.176
#> GSM1182322 2 0.5906 0.39967 0.000 0.492 0.404 0.000 0.104
#> GSM1182324 3 0.5854 0.12944 0.000 0.160 0.600 0.000 0.240
#> GSM1182297 2 0.6475 0.42212 0.000 0.428 0.388 0.000 0.184
#> GSM1182302 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182308 3 0.5697 0.15602 0.000 0.288 0.596 0.000 0.116
#> GSM1182310 3 0.5673 0.19024 0.000 0.156 0.628 0.000 0.216
#> GSM1182311 1 0.0703 0.94386 0.976 0.000 0.000 0.000 0.024
#> GSM1182313 4 0.0000 0.98429 0.000 0.000 0.000 1.000 0.000
#> GSM1182315 3 0.5284 -0.01780 0.000 0.376 0.568 0.000 0.056
#> GSM1182317 3 0.5256 -0.13975 0.000 0.420 0.532 0.000 0.048
#> GSM1182323 1 0.0703 0.94386 0.976 0.000 0.000 0.000 0.024
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 5 0.0146 0.96035 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182187 4 0.0146 0.99646 0.000 0.004 0.000 0.996 0.000 0.000
#> GSM1182188 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182189 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182190 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182191 5 0.0146 0.96035 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182192 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182193 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182194 2 0.5744 0.16410 0.000 0.424 0.408 0.000 0.000 0.168
#> GSM1182195 2 0.4644 0.05711 0.000 0.504 0.456 0.000 0.000 0.040
#> GSM1182196 2 0.5054 0.44538 0.000 0.572 0.336 0.000 0.000 0.092
#> GSM1182197 2 0.5022 -0.15117 0.000 0.496 0.072 0.000 0.000 0.432
#> GSM1182198 6 0.6033 -0.01406 0.000 0.336 0.256 0.000 0.000 0.408
#> GSM1182199 2 0.5937 0.19859 0.000 0.436 0.340 0.000 0.000 0.224
#> GSM1182200 6 0.5520 0.45783 0.000 0.200 0.240 0.000 0.000 0.560
#> GSM1182201 3 0.6053 -0.09376 0.000 0.272 0.408 0.000 0.000 0.320
#> GSM1182202 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182203 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182204 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182205 3 0.3354 0.58819 0.000 0.128 0.812 0.000 0.000 0.060
#> GSM1182206 3 0.1867 0.58070 0.000 0.064 0.916 0.000 0.000 0.020
#> GSM1182207 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182208 5 0.0000 0.96140 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182209 6 0.5537 0.38989 0.000 0.152 0.328 0.000 0.000 0.520
#> GSM1182210 3 0.4045 0.58985 0.000 0.120 0.756 0.000 0.000 0.124
#> GSM1182211 3 0.4273 0.57506 0.000 0.148 0.732 0.000 0.000 0.120
#> GSM1182212 3 0.5079 0.47610 0.000 0.148 0.628 0.000 0.000 0.224
#> GSM1182213 6 0.5683 0.26878 0.000 0.168 0.348 0.000 0.000 0.484
#> GSM1182214 3 0.5425 0.41063 0.000 0.148 0.552 0.000 0.000 0.300
#> GSM1182215 3 0.3744 0.58838 0.000 0.184 0.764 0.000 0.000 0.052
#> GSM1182216 3 0.5799 0.14491 0.000 0.180 0.428 0.000 0.000 0.392
#> GSM1182217 5 0.4513 0.31293 0.000 0.028 0.000 0.396 0.572 0.004
#> GSM1182218 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182219 3 0.1500 0.58586 0.000 0.012 0.936 0.000 0.000 0.052
#> GSM1182220 3 0.1970 0.58292 0.000 0.028 0.912 0.000 0.000 0.060
#> GSM1182221 3 0.3834 0.59029 0.000 0.108 0.776 0.000 0.000 0.116
#> GSM1182222 3 0.1657 0.58526 0.000 0.016 0.928 0.000 0.000 0.056
#> GSM1182223 3 0.1720 0.57840 0.000 0.032 0.928 0.000 0.000 0.040
#> GSM1182224 3 0.2163 0.57425 0.000 0.092 0.892 0.000 0.000 0.016
#> GSM1182225 3 0.4348 0.57139 0.000 0.152 0.724 0.000 0.000 0.124
#> GSM1182226 3 0.5883 0.11518 0.000 0.204 0.436 0.000 0.000 0.360
#> GSM1182227 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182228 2 0.5508 -0.19888 0.000 0.480 0.132 0.000 0.000 0.388
#> GSM1182229 3 0.1863 0.58583 0.000 0.044 0.920 0.000 0.000 0.036
#> GSM1182230 3 0.3171 0.50927 0.000 0.204 0.784 0.000 0.000 0.012
#> GSM1182231 3 0.5160 0.30556 0.000 0.332 0.564 0.000 0.000 0.104
#> GSM1182232 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182233 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182234 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182235 3 0.2197 0.60152 0.000 0.044 0.900 0.000 0.000 0.056
#> GSM1182236 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182237 3 0.4243 0.58403 0.000 0.164 0.732 0.000 0.000 0.104
#> GSM1182238 3 0.5659 0.31916 0.000 0.168 0.496 0.000 0.000 0.336
#> GSM1182239 6 0.4729 0.58186 0.000 0.248 0.096 0.000 0.000 0.656
#> GSM1182240 6 0.5392 0.49890 0.000 0.192 0.224 0.000 0.000 0.584
#> GSM1182241 6 0.5030 0.60767 0.000 0.268 0.116 0.000 0.000 0.616
#> GSM1182242 2 0.5361 0.03559 0.000 0.452 0.440 0.000 0.000 0.108
#> GSM1182243 2 0.5003 0.42953 0.000 0.608 0.288 0.000 0.000 0.104
#> GSM1182244 3 0.4795 0.22354 0.000 0.324 0.604 0.000 0.000 0.072
#> GSM1182245 1 0.0551 0.96351 0.984 0.008 0.000 0.000 0.004 0.004
#> GSM1182246 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182247 3 0.4309 0.45056 0.000 0.296 0.660 0.000 0.000 0.044
#> GSM1182248 2 0.5296 0.00368 0.000 0.456 0.444 0.000 0.000 0.100
#> GSM1182249 2 0.5341 0.27897 0.000 0.592 0.224 0.000 0.000 0.184
#> GSM1182250 2 0.4663 0.18139 0.000 0.660 0.088 0.000 0.000 0.252
#> GSM1182251 5 0.0000 0.96140 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182252 3 0.4700 0.29043 0.000 0.340 0.600 0.000 0.000 0.060
#> GSM1182253 3 0.2981 0.57627 0.000 0.160 0.820 0.000 0.000 0.020
#> GSM1182254 2 0.4281 0.26877 0.000 0.708 0.072 0.000 0.000 0.220
#> GSM1182255 4 0.0146 0.99661 0.000 0.004 0.000 0.996 0.000 0.000
#> GSM1182256 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182257 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182258 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182259 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182260 2 0.4516 0.18213 0.000 0.668 0.072 0.000 0.000 0.260
#> GSM1182261 3 0.4247 0.35320 0.000 0.296 0.664 0.000 0.000 0.040
#> GSM1182262 2 0.5421 0.19315 0.000 0.452 0.432 0.000 0.000 0.116
#> GSM1182263 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182264 6 0.4532 0.55901 0.000 0.308 0.056 0.000 0.000 0.636
#> GSM1182265 6 0.5364 0.56481 0.000 0.276 0.152 0.000 0.000 0.572
#> GSM1182266 6 0.4917 0.54420 0.000 0.348 0.076 0.000 0.000 0.576
#> GSM1182267 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182268 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182269 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182270 1 0.0146 0.97013 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1182271 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182272 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182273 6 0.4392 0.54355 0.000 0.332 0.040 0.000 0.000 0.628
#> GSM1182275 3 0.5289 0.39880 0.000 0.140 0.580 0.000 0.000 0.280
#> GSM1182276 3 0.2390 0.59972 0.000 0.056 0.888 0.000 0.000 0.056
#> GSM1182277 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182278 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182279 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182280 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182281 1 0.5945 0.01838 0.464 0.032 0.000 0.076 0.420 0.008
#> GSM1182282 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182283 1 0.0000 0.97068 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1182284 1 0.0603 0.96076 0.980 0.016 0.000 0.000 0.000 0.004
#> GSM1182285 3 0.4977 0.14856 0.000 0.372 0.552 0.000 0.000 0.076
#> GSM1182286 3 0.5260 -0.09187 0.000 0.440 0.464 0.000 0.000 0.096
#> GSM1182287 3 0.4886 0.15286 0.000 0.396 0.540 0.000 0.000 0.064
#> GSM1182288 3 0.5065 0.14818 0.000 0.396 0.524 0.000 0.000 0.080
#> GSM1182289 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182290 5 0.0146 0.96154 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182291 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182274 6 0.4939 0.59799 0.000 0.292 0.096 0.000 0.000 0.612
#> GSM1182292 2 0.5595 -0.07086 0.000 0.464 0.144 0.000 0.000 0.392
#> GSM1182293 2 0.5324 0.39096 0.000 0.540 0.340 0.000 0.000 0.120
#> GSM1182294 2 0.3954 0.46470 0.000 0.740 0.204 0.000 0.000 0.056
#> GSM1182295 2 0.5386 0.40312 0.000 0.548 0.316 0.000 0.000 0.136
#> GSM1182296 2 0.5156 0.42791 0.000 0.620 0.164 0.000 0.000 0.216
#> GSM1182298 2 0.5387 0.09989 0.000 0.464 0.424 0.000 0.000 0.112
#> GSM1182299 6 0.4522 0.58299 0.000 0.252 0.076 0.000 0.000 0.672
#> GSM1182300 2 0.4942 0.48227 0.000 0.652 0.192 0.000 0.000 0.156
#> GSM1182301 2 0.5020 0.02087 0.000 0.548 0.080 0.000 0.000 0.372
#> GSM1182303 2 0.5377 0.27191 0.000 0.528 0.348 0.000 0.000 0.124
#> GSM1182304 5 0.0000 0.96140 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1182305 5 0.0146 0.96035 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM1182306 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182307 3 0.5871 0.03599 0.000 0.196 0.408 0.000 0.000 0.396
#> GSM1182309 2 0.5315 0.43101 0.000 0.564 0.304 0.000 0.000 0.132
#> GSM1182312 3 0.5467 0.36941 0.000 0.304 0.544 0.000 0.000 0.152
#> GSM1182314 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182316 6 0.4717 0.40937 0.000 0.364 0.056 0.000 0.000 0.580
#> GSM1182318 2 0.4929 -0.11204 0.000 0.508 0.064 0.000 0.000 0.428
#> GSM1182319 2 0.3588 0.50010 0.000 0.776 0.180 0.000 0.000 0.044
#> GSM1182320 2 0.5792 0.17599 0.000 0.500 0.228 0.000 0.000 0.272
#> GSM1182321 2 0.3709 0.48144 0.000 0.756 0.204 0.000 0.000 0.040
#> GSM1182322 2 0.4996 -0.09019 0.000 0.520 0.072 0.000 0.000 0.408
#> GSM1182324 2 0.4205 0.48725 0.000 0.728 0.188 0.000 0.000 0.084
#> GSM1182297 6 0.5392 0.32570 0.000 0.444 0.112 0.000 0.000 0.444
#> GSM1182302 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182308 2 0.5411 0.38025 0.000 0.532 0.336 0.000 0.000 0.132
#> GSM1182310 2 0.3771 0.48740 0.000 0.764 0.180 0.000 0.000 0.056
#> GSM1182311 1 0.1232 0.94484 0.956 0.016 0.000 0.000 0.024 0.004
#> GSM1182313 4 0.0000 0.99958 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1182315 2 0.4823 0.40219 0.000 0.660 0.124 0.000 0.000 0.216
#> GSM1182317 2 0.5245 0.26170 0.000 0.560 0.116 0.000 0.000 0.324
#> GSM1182323 1 0.1049 0.94426 0.960 0.008 0.000 0.000 0.032 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:mclust 139 0.0773 1.000 2
#> ATC:mclust 139 0.0773 1.000 3
#> ATC:mclust 65 0.2048 0.477 4
#> ATC:mclust 53 0.5576 0.523 5
#> ATC:mclust 79 0.0436 0.610 6
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 46361 rows and 139 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 1.000 1.000 1.000 0.4791 0.521 0.521
#> 3 3 0.931 0.947 0.928 0.1159 0.926 0.857
#> 4 4 0.929 0.930 0.944 0.0321 0.994 0.988
#> 5 5 0.890 0.917 0.936 0.0241 0.994 0.988
#> 6 6 0.876 0.911 0.928 0.0263 0.994 0.988
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
#> GSM1182186 1 0 1 1 0
#> GSM1182187 1 0 1 1 0
#> GSM1182188 1 0 1 1 0
#> GSM1182189 1 0 1 1 0
#> GSM1182190 1 0 1 1 0
#> GSM1182191 1 0 1 1 0
#> GSM1182192 1 0 1 1 0
#> GSM1182193 1 0 1 1 0
#> GSM1182194 2 0 1 0 1
#> GSM1182195 2 0 1 0 1
#> GSM1182196 2 0 1 0 1
#> GSM1182197 2 0 1 0 1
#> GSM1182198 2 0 1 0 1
#> GSM1182199 2 0 1 0 1
#> GSM1182200 2 0 1 0 1
#> GSM1182201 2 0 1 0 1
#> GSM1182202 1 0 1 1 0
#> GSM1182203 1 0 1 1 0
#> GSM1182204 1 0 1 1 0
#> GSM1182205 2 0 1 0 1
#> GSM1182206 2 0 1 0 1
#> GSM1182207 1 0 1 1 0
#> GSM1182208 1 0 1 1 0
#> GSM1182209 2 0 1 0 1
#> GSM1182210 2 0 1 0 1
#> GSM1182211 2 0 1 0 1
#> GSM1182212 2 0 1 0 1
#> GSM1182213 2 0 1 0 1
#> GSM1182214 2 0 1 0 1
#> GSM1182215 2 0 1 0 1
#> GSM1182216 2 0 1 0 1
#> GSM1182217 1 0 1 1 0
#> GSM1182218 1 0 1 1 0
#> GSM1182219 2 0 1 0 1
#> GSM1182220 2 0 1 0 1
#> GSM1182221 2 0 1 0 1
#> GSM1182222 2 0 1 0 1
#> GSM1182223 2 0 1 0 1
#> GSM1182224 2 0 1 0 1
#> GSM1182225 2 0 1 0 1
#> GSM1182226 2 0 1 0 1
#> GSM1182227 1 0 1 1 0
#> GSM1182228 2 0 1 0 1
#> GSM1182229 2 0 1 0 1
#> GSM1182230 2 0 1 0 1
#> GSM1182231 2 0 1 0 1
#> GSM1182232 1 0 1 1 0
#> GSM1182233 1 0 1 1 0
#> GSM1182234 1 0 1 1 0
#> GSM1182235 2 0 1 0 1
#> GSM1182236 1 0 1 1 0
#> GSM1182237 2 0 1 0 1
#> GSM1182238 2 0 1 0 1
#> GSM1182239 2 0 1 0 1
#> GSM1182240 2 0 1 0 1
#> GSM1182241 2 0 1 0 1
#> GSM1182242 2 0 1 0 1
#> GSM1182243 2 0 1 0 1
#> GSM1182244 2 0 1 0 1
#> GSM1182245 1 0 1 1 0
#> GSM1182246 1 0 1 1 0
#> GSM1182247 2 0 1 0 1
#> GSM1182248 2 0 1 0 1
#> GSM1182249 2 0 1 0 1
#> GSM1182250 2 0 1 0 1
#> GSM1182251 1 0 1 1 0
#> GSM1182252 2 0 1 0 1
#> GSM1182253 2 0 1 0 1
#> GSM1182254 2 0 1 0 1
#> GSM1182255 1 0 1 1 0
#> GSM1182256 1 0 1 1 0
#> GSM1182257 1 0 1 1 0
#> GSM1182258 1 0 1 1 0
#> GSM1182259 1 0 1 1 0
#> GSM1182260 2 0 1 0 1
#> GSM1182261 2 0 1 0 1
#> GSM1182262 2 0 1 0 1
#> GSM1182263 1 0 1 1 0
#> GSM1182264 2 0 1 0 1
#> GSM1182265 2 0 1 0 1
#> GSM1182266 2 0 1 0 1
#> GSM1182267 1 0 1 1 0
#> GSM1182268 1 0 1 1 0
#> GSM1182269 1 0 1 1 0
#> GSM1182270 1 0 1 1 0
#> GSM1182271 1 0 1 1 0
#> GSM1182272 1 0 1 1 0
#> GSM1182273 2 0 1 0 1
#> GSM1182275 2 0 1 0 1
#> GSM1182276 2 0 1 0 1
#> GSM1182277 1 0 1 1 0
#> GSM1182278 1 0 1 1 0
#> GSM1182279 1 0 1 1 0
#> GSM1182280 1 0 1 1 0
#> GSM1182281 1 0 1 1 0
#> GSM1182282 1 0 1 1 0
#> GSM1182283 1 0 1 1 0
#> GSM1182284 1 0 1 1 0
#> GSM1182285 2 0 1 0 1
#> GSM1182286 2 0 1 0 1
#> GSM1182287 2 0 1 0 1
#> GSM1182288 2 0 1 0 1
#> GSM1182289 1 0 1 1 0
#> GSM1182290 1 0 1 1 0
#> GSM1182291 1 0 1 1 0
#> GSM1182274 2 0 1 0 1
#> GSM1182292 2 0 1 0 1
#> GSM1182293 2 0 1 0 1
#> GSM1182294 2 0 1 0 1
#> GSM1182295 2 0 1 0 1
#> GSM1182296 2 0 1 0 1
#> GSM1182298 2 0 1 0 1
#> GSM1182299 2 0 1 0 1
#> GSM1182300 2 0 1 0 1
#> GSM1182301 2 0 1 0 1
#> GSM1182303 2 0 1 0 1
#> GSM1182304 1 0 1 1 0
#> GSM1182305 1 0 1 1 0
#> GSM1182306 1 0 1 1 0
#> GSM1182307 2 0 1 0 1
#> GSM1182309 2 0 1 0 1
#> GSM1182312 2 0 1 0 1
#> GSM1182314 1 0 1 1 0
#> GSM1182316 2 0 1 0 1
#> GSM1182318 2 0 1 0 1
#> GSM1182319 2 0 1 0 1
#> GSM1182320 2 0 1 0 1
#> GSM1182321 2 0 1 0 1
#> GSM1182322 2 0 1 0 1
#> GSM1182324 2 0 1 0 1
#> GSM1182297 2 0 1 0 1
#> GSM1182302 1 0 1 1 0
#> GSM1182308 2 0 1 0 1
#> GSM1182310 2 0 1 0 1
#> GSM1182311 1 0 1 1 0
#> GSM1182313 1 0 1 1 0
#> GSM1182315 2 0 1 0 1
#> GSM1182317 2 0 1 0 1
#> GSM1182323 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1182186 3 0.5785 0.868 0.332 0 0.668
#> GSM1182187 3 0.5254 0.950 0.264 0 0.736
#> GSM1182188 3 0.5098 0.954 0.248 0 0.752
#> GSM1182189 1 0.1411 0.859 0.964 0 0.036
#> GSM1182190 1 0.1031 0.896 0.976 0 0.024
#> GSM1182191 3 0.5810 0.861 0.336 0 0.664
#> GSM1182192 1 0.0747 0.890 0.984 0 0.016
#> GSM1182193 1 0.1860 0.843 0.948 0 0.052
#> GSM1182194 2 0.0000 1.000 0.000 1 0.000
#> GSM1182195 2 0.0000 1.000 0.000 1 0.000
#> GSM1182196 2 0.0000 1.000 0.000 1 0.000
#> GSM1182197 2 0.0000 1.000 0.000 1 0.000
#> GSM1182198 2 0.0000 1.000 0.000 1 0.000
#> GSM1182199 2 0.0000 1.000 0.000 1 0.000
#> GSM1182200 2 0.0000 1.000 0.000 1 0.000
#> GSM1182201 2 0.0000 1.000 0.000 1 0.000
#> GSM1182202 3 0.5254 0.950 0.264 0 0.736
#> GSM1182203 3 0.5178 0.954 0.256 0 0.744
#> GSM1182204 3 0.5216 0.952 0.260 0 0.740
#> GSM1182205 2 0.0000 1.000 0.000 1 0.000
#> GSM1182206 2 0.0000 1.000 0.000 1 0.000
#> GSM1182207 1 0.2165 0.830 0.936 0 0.064
#> GSM1182208 1 0.2261 0.825 0.932 0 0.068
#> GSM1182209 2 0.0000 1.000 0.000 1 0.000
#> GSM1182210 2 0.0000 1.000 0.000 1 0.000
#> GSM1182211 2 0.0000 1.000 0.000 1 0.000
#> GSM1182212 2 0.0000 1.000 0.000 1 0.000
#> GSM1182213 2 0.0000 1.000 0.000 1 0.000
#> GSM1182214 2 0.0000 1.000 0.000 1 0.000
#> GSM1182215 2 0.0000 1.000 0.000 1 0.000
#> GSM1182216 2 0.0000 1.000 0.000 1 0.000
#> GSM1182217 3 0.5465 0.926 0.288 0 0.712
#> GSM1182218 1 0.2165 0.887 0.936 0 0.064
#> GSM1182219 2 0.0000 1.000 0.000 1 0.000
#> GSM1182220 2 0.0000 1.000 0.000 1 0.000
#> GSM1182221 2 0.0000 1.000 0.000 1 0.000
#> GSM1182222 2 0.0000 1.000 0.000 1 0.000
#> GSM1182223 2 0.0000 1.000 0.000 1 0.000
#> GSM1182224 2 0.0000 1.000 0.000 1 0.000
#> GSM1182225 2 0.0000 1.000 0.000 1 0.000
#> GSM1182226 2 0.0000 1.000 0.000 1 0.000
#> GSM1182227 1 0.2261 0.886 0.932 0 0.068
#> GSM1182228 2 0.0000 1.000 0.000 1 0.000
#> GSM1182229 2 0.0000 1.000 0.000 1 0.000
#> GSM1182230 2 0.0000 1.000 0.000 1 0.000
#> GSM1182231 2 0.0000 1.000 0.000 1 0.000
#> GSM1182232 1 0.1753 0.897 0.952 0 0.048
#> GSM1182233 1 0.0000 0.886 1.000 0 0.000
#> GSM1182234 1 0.1163 0.897 0.972 0 0.028
#> GSM1182235 2 0.0000 1.000 0.000 1 0.000
#> GSM1182236 1 0.1643 0.898 0.956 0 0.044
#> GSM1182237 2 0.0000 1.000 0.000 1 0.000
#> GSM1182238 2 0.0000 1.000 0.000 1 0.000
#> GSM1182239 2 0.0000 1.000 0.000 1 0.000
#> GSM1182240 2 0.0000 1.000 0.000 1 0.000
#> GSM1182241 2 0.0000 1.000 0.000 1 0.000
#> GSM1182242 2 0.0000 1.000 0.000 1 0.000
#> GSM1182243 2 0.0000 1.000 0.000 1 0.000
#> GSM1182244 2 0.0000 1.000 0.000 1 0.000
#> GSM1182245 1 0.1643 0.898 0.956 0 0.044
#> GSM1182246 3 0.5138 0.955 0.252 0 0.748
#> GSM1182247 2 0.0000 1.000 0.000 1 0.000
#> GSM1182248 2 0.0000 1.000 0.000 1 0.000
#> GSM1182249 2 0.0000 1.000 0.000 1 0.000
#> GSM1182250 2 0.0000 1.000 0.000 1 0.000
#> GSM1182251 1 0.5926 0.221 0.644 0 0.356
#> GSM1182252 2 0.0000 1.000 0.000 1 0.000
#> GSM1182253 2 0.0000 1.000 0.000 1 0.000
#> GSM1182254 2 0.0000 1.000 0.000 1 0.000
#> GSM1182255 3 0.5254 0.950 0.264 0 0.736
#> GSM1182256 3 0.5138 0.955 0.252 0 0.748
#> GSM1182257 3 0.5138 0.955 0.252 0 0.748
#> GSM1182258 3 0.5098 0.954 0.248 0 0.752
#> GSM1182259 3 0.5098 0.954 0.248 0 0.752
#> GSM1182260 2 0.0000 1.000 0.000 1 0.000
#> GSM1182261 2 0.0000 1.000 0.000 1 0.000
#> GSM1182262 2 0.0000 1.000 0.000 1 0.000
#> GSM1182263 1 0.4121 0.760 0.832 0 0.168
#> GSM1182264 2 0.0000 1.000 0.000 1 0.000
#> GSM1182265 2 0.0000 1.000 0.000 1 0.000
#> GSM1182266 2 0.0000 1.000 0.000 1 0.000
#> GSM1182267 1 0.1529 0.898 0.960 0 0.040
#> GSM1182268 1 0.0592 0.878 0.988 0 0.012
#> GSM1182269 1 0.0747 0.876 0.984 0 0.016
#> GSM1182270 1 0.1289 0.897 0.968 0 0.032
#> GSM1182271 3 0.5098 0.954 0.248 0 0.752
#> GSM1182272 3 0.5138 0.955 0.252 0 0.748
#> GSM1182273 2 0.0000 1.000 0.000 1 0.000
#> GSM1182275 2 0.0000 1.000 0.000 1 0.000
#> GSM1182276 2 0.0000 1.000 0.000 1 0.000
#> GSM1182277 1 0.1860 0.895 0.948 0 0.052
#> GSM1182278 1 0.1860 0.895 0.948 0 0.052
#> GSM1182279 1 0.5497 0.469 0.708 0 0.292
#> GSM1182280 1 0.2796 0.863 0.908 0 0.092
#> GSM1182281 3 0.6140 0.730 0.404 0 0.596
#> GSM1182282 1 0.1753 0.897 0.952 0 0.048
#> GSM1182283 1 0.1643 0.898 0.956 0 0.044
#> GSM1182284 1 0.4399 0.725 0.812 0 0.188
#> GSM1182285 2 0.0000 1.000 0.000 1 0.000
#> GSM1182286 2 0.0000 1.000 0.000 1 0.000
#> GSM1182287 2 0.0000 1.000 0.000 1 0.000
#> GSM1182288 2 0.0000 1.000 0.000 1 0.000
#> GSM1182289 1 0.5591 0.430 0.696 0 0.304
#> GSM1182290 1 0.0892 0.873 0.980 0 0.020
#> GSM1182291 3 0.5098 0.954 0.248 0 0.752
#> GSM1182274 2 0.0000 1.000 0.000 1 0.000
#> GSM1182292 2 0.0000 1.000 0.000 1 0.000
#> GSM1182293 2 0.0000 1.000 0.000 1 0.000
#> GSM1182294 2 0.0000 1.000 0.000 1 0.000
#> GSM1182295 2 0.0000 1.000 0.000 1 0.000
#> GSM1182296 2 0.0000 1.000 0.000 1 0.000
#> GSM1182298 2 0.0000 1.000 0.000 1 0.000
#> GSM1182299 2 0.0000 1.000 0.000 1 0.000
#> GSM1182300 2 0.0000 1.000 0.000 1 0.000
#> GSM1182301 2 0.0000 1.000 0.000 1 0.000
#> GSM1182303 2 0.0000 1.000 0.000 1 0.000
#> GSM1182304 1 0.3412 0.826 0.876 0 0.124
#> GSM1182305 3 0.6267 0.604 0.452 0 0.548
#> GSM1182306 3 0.5098 0.954 0.248 0 0.752
#> GSM1182307 2 0.0000 1.000 0.000 1 0.000
#> GSM1182309 2 0.0000 1.000 0.000 1 0.000
#> GSM1182312 2 0.0000 1.000 0.000 1 0.000
#> GSM1182314 3 0.5098 0.954 0.248 0 0.752
#> GSM1182316 2 0.0000 1.000 0.000 1 0.000
#> GSM1182318 2 0.0000 1.000 0.000 1 0.000
#> GSM1182319 2 0.0000 1.000 0.000 1 0.000
#> GSM1182320 2 0.0000 1.000 0.000 1 0.000
#> GSM1182321 2 0.0000 1.000 0.000 1 0.000
#> GSM1182322 2 0.0000 1.000 0.000 1 0.000
#> GSM1182324 2 0.0000 1.000 0.000 1 0.000
#> GSM1182297 2 0.0000 1.000 0.000 1 0.000
#> GSM1182302 3 0.5138 0.955 0.252 0 0.748
#> GSM1182308 2 0.0000 1.000 0.000 1 0.000
#> GSM1182310 2 0.0000 1.000 0.000 1 0.000
#> GSM1182311 1 0.0424 0.890 0.992 0 0.008
#> GSM1182313 3 0.5098 0.954 0.248 0 0.752
#> GSM1182315 2 0.0000 1.000 0.000 1 0.000
#> GSM1182317 2 0.0000 1.000 0.000 1 0.000
#> GSM1182323 1 0.2066 0.891 0.940 0 0.060
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1182186 4 0.5778 0.631 0.356 0.000 NA 0.604
#> GSM1182187 4 0.4204 0.875 0.192 0.000 NA 0.788
#> GSM1182188 4 0.3581 0.903 0.116 0.000 NA 0.852
#> GSM1182189 1 0.1792 0.870 0.932 0.000 NA 0.000
#> GSM1182190 1 0.0779 0.908 0.980 0.000 NA 0.016
#> GSM1182191 4 0.6014 0.616 0.360 0.000 NA 0.588
#> GSM1182192 1 0.0927 0.904 0.976 0.000 NA 0.008
#> GSM1182193 1 0.2593 0.844 0.892 0.000 NA 0.004
#> GSM1182194 2 0.1489 0.962 0.000 0.952 NA 0.004
#> GSM1182195 2 0.1489 0.962 0.000 0.952 NA 0.004
#> GSM1182196 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182197 2 0.0336 0.991 0.000 0.992 NA 0.000
#> GSM1182198 2 0.1722 0.956 0.000 0.944 NA 0.008
#> GSM1182199 2 0.1635 0.959 0.000 0.948 NA 0.008
#> GSM1182200 2 0.0336 0.991 0.000 0.992 NA 0.000
#> GSM1182201 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182202 4 0.4121 0.882 0.184 0.000 NA 0.796
#> GSM1182203 4 0.3900 0.893 0.164 0.000 NA 0.816
#> GSM1182204 4 0.4406 0.873 0.192 0.000 NA 0.780
#> GSM1182205 2 0.0336 0.990 0.000 0.992 NA 0.000
#> GSM1182206 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182207 1 0.2760 0.829 0.872 0.000 NA 0.000
#> GSM1182208 1 0.3024 0.811 0.852 0.000 NA 0.000
#> GSM1182209 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182210 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182211 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182212 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182213 2 0.0592 0.988 0.000 0.984 NA 0.000
#> GSM1182214 2 0.0592 0.988 0.000 0.984 NA 0.000
#> GSM1182215 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182216 2 0.0592 0.988 0.000 0.984 NA 0.000
#> GSM1182217 4 0.5444 0.779 0.264 0.000 NA 0.688
#> GSM1182218 1 0.1489 0.899 0.952 0.000 NA 0.044
#> GSM1182219 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182220 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182221 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182222 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182223 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182224 2 0.0592 0.986 0.000 0.984 NA 0.000
#> GSM1182225 2 0.0592 0.988 0.000 0.984 NA 0.000
#> GSM1182226 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182227 1 0.1545 0.899 0.952 0.000 NA 0.040
#> GSM1182228 2 0.0921 0.980 0.000 0.972 NA 0.000
#> GSM1182229 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182230 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182231 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182232 1 0.0817 0.907 0.976 0.000 NA 0.024
#> GSM1182233 1 0.0592 0.903 0.984 0.000 NA 0.000
#> GSM1182234 1 0.0804 0.907 0.980 0.000 NA 0.008
#> GSM1182235 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182236 1 0.0921 0.905 0.972 0.000 NA 0.028
#> GSM1182237 2 0.0336 0.991 0.000 0.992 NA 0.000
#> GSM1182238 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182239 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182240 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182241 2 0.0707 0.986 0.000 0.980 NA 0.000
#> GSM1182242 2 0.1118 0.974 0.000 0.964 NA 0.000
#> GSM1182243 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182244 2 0.0336 0.990 0.000 0.992 NA 0.000
#> GSM1182245 1 0.0592 0.908 0.984 0.000 NA 0.016
#> GSM1182246 4 0.3335 0.909 0.128 0.000 NA 0.856
#> GSM1182247 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182248 2 0.0336 0.990 0.000 0.992 NA 0.000
#> GSM1182249 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182250 2 0.0336 0.990 0.000 0.992 NA 0.000
#> GSM1182251 1 0.5219 0.565 0.712 0.000 NA 0.244
#> GSM1182252 2 0.0336 0.990 0.000 0.992 NA 0.000
#> GSM1182253 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182254 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182255 4 0.3813 0.900 0.148 0.000 NA 0.828
#> GSM1182256 4 0.2704 0.908 0.124 0.000 NA 0.876
#> GSM1182257 4 0.2888 0.908 0.124 0.000 NA 0.872
#> GSM1182258 4 0.3523 0.900 0.112 0.000 NA 0.856
#> GSM1182259 4 0.3523 0.900 0.112 0.000 NA 0.856
#> GSM1182260 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182261 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182262 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182263 1 0.2949 0.852 0.888 0.000 NA 0.088
#> GSM1182264 2 0.1022 0.975 0.000 0.968 NA 0.000
#> GSM1182265 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182266 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182267 1 0.0524 0.907 0.988 0.000 NA 0.004
#> GSM1182268 1 0.1209 0.895 0.964 0.000 NA 0.004
#> GSM1182269 1 0.1004 0.899 0.972 0.000 NA 0.004
#> GSM1182270 1 0.1004 0.907 0.972 0.000 NA 0.024
#> GSM1182271 4 0.3105 0.908 0.120 0.000 NA 0.868
#> GSM1182272 4 0.3161 0.908 0.124 0.000 NA 0.864
#> GSM1182273 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182275 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182276 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182277 1 0.0707 0.908 0.980 0.000 NA 0.020
#> GSM1182278 1 0.0707 0.908 0.980 0.000 NA 0.020
#> GSM1182279 1 0.4423 0.725 0.792 0.000 NA 0.168
#> GSM1182280 1 0.1743 0.890 0.940 0.000 NA 0.056
#> GSM1182281 4 0.6442 0.370 0.440 0.000 NA 0.492
#> GSM1182282 1 0.0804 0.909 0.980 0.000 NA 0.012
#> GSM1182283 1 0.0804 0.907 0.980 0.000 NA 0.012
#> GSM1182284 1 0.3367 0.828 0.864 0.000 NA 0.108
#> GSM1182285 2 0.1398 0.966 0.000 0.956 NA 0.004
#> GSM1182286 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182287 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182288 2 0.0469 0.990 0.000 0.988 NA 0.000
#> GSM1182289 1 0.4677 0.682 0.768 0.000 NA 0.192
#> GSM1182290 1 0.2197 0.865 0.916 0.000 NA 0.004
#> GSM1182291 4 0.3485 0.904 0.116 0.000 NA 0.856
#> GSM1182274 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182292 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182293 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182294 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182295 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182296 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182298 2 0.1398 0.966 0.000 0.956 NA 0.004
#> GSM1182299 2 0.0336 0.991 0.000 0.992 NA 0.000
#> GSM1182300 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182301 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182303 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182304 1 0.2198 0.874 0.920 0.000 NA 0.072
#> GSM1182305 1 0.6527 -0.167 0.508 0.000 NA 0.416
#> GSM1182306 4 0.3542 0.905 0.120 0.000 NA 0.852
#> GSM1182307 2 0.0707 0.986 0.000 0.980 NA 0.000
#> GSM1182309 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182312 2 0.0336 0.991 0.000 0.992 NA 0.000
#> GSM1182314 4 0.3542 0.905 0.120 0.000 NA 0.852
#> GSM1182316 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182318 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182319 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182320 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182321 2 0.0188 0.991 0.000 0.996 NA 0.000
#> GSM1182322 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182324 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182297 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182302 4 0.3495 0.903 0.140 0.000 NA 0.844
#> GSM1182308 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182310 2 0.0000 0.992 0.000 1.000 NA 0.000
#> GSM1182311 1 0.0804 0.906 0.980 0.000 NA 0.008
#> GSM1182313 4 0.3441 0.906 0.120 0.000 NA 0.856
#> GSM1182315 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182317 2 0.0188 0.992 0.000 0.996 NA 0.000
#> GSM1182323 1 0.1109 0.906 0.968 0.000 NA 0.028
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1182186 4 0.5506 0.591 0.284 0.000 NA 0.616 0.000
#> GSM1182187 4 0.3752 0.816 0.148 0.000 NA 0.804 0.000
#> GSM1182188 4 0.1195 0.876 0.028 0.000 NA 0.960 0.000
#> GSM1182189 1 0.1270 0.876 0.948 0.000 NA 0.000 0.000
#> GSM1182190 1 0.1725 0.912 0.936 0.000 NA 0.044 0.000
#> GSM1182191 4 0.5394 0.604 0.280 0.000 NA 0.628 0.000
#> GSM1182192 1 0.1568 0.909 0.944 0.000 NA 0.036 0.000
#> GSM1182193 1 0.1831 0.863 0.920 0.000 NA 0.000 0.004
#> GSM1182194 2 0.3102 0.885 0.000 0.860 NA 0.000 0.056
#> GSM1182195 2 0.2983 0.893 0.000 0.868 NA 0.000 0.056
#> GSM1182196 2 0.0324 0.981 0.000 0.992 NA 0.000 0.004
#> GSM1182197 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182198 2 0.3601 0.844 0.000 0.820 NA 0.000 0.052
#> GSM1182199 2 0.3307 0.869 0.000 0.844 NA 0.000 0.052
#> GSM1182200 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182201 2 0.0000 0.980 0.000 1.000 NA 0.000 0.000
#> GSM1182202 4 0.2915 0.847 0.116 0.000 NA 0.860 0.000
#> GSM1182203 4 0.2407 0.867 0.088 0.000 NA 0.896 0.004
#> GSM1182204 4 0.3432 0.831 0.132 0.000 NA 0.828 0.000
#> GSM1182205 2 0.1043 0.966 0.000 0.960 NA 0.000 0.040
#> GSM1182206 2 0.0510 0.978 0.000 0.984 NA 0.000 0.016
#> GSM1182207 1 0.2392 0.848 0.888 0.000 NA 0.004 0.004
#> GSM1182208 1 0.2570 0.841 0.880 0.000 NA 0.004 0.008
#> GSM1182209 2 0.0510 0.979 0.000 0.984 NA 0.000 0.016
#> GSM1182210 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182211 2 0.0510 0.979 0.000 0.984 NA 0.000 0.016
#> GSM1182212 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182213 2 0.0510 0.980 0.000 0.984 NA 0.000 0.016
#> GSM1182214 2 0.0510 0.979 0.000 0.984 NA 0.000 0.016
#> GSM1182215 2 0.0162 0.980 0.000 0.996 NA 0.000 0.004
#> GSM1182216 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182217 4 0.4701 0.739 0.204 0.000 NA 0.720 0.000
#> GSM1182218 1 0.2300 0.910 0.904 0.000 NA 0.072 0.000
#> GSM1182219 2 0.0000 0.980 0.000 1.000 NA 0.000 0.000
#> GSM1182220 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182221 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182222 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182223 2 0.0162 0.980 0.000 0.996 NA 0.000 0.004
#> GSM1182224 2 0.1357 0.958 0.000 0.948 NA 0.000 0.048
#> GSM1182225 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182226 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182227 1 0.2144 0.911 0.912 0.000 NA 0.068 0.000
#> GSM1182228 2 0.1544 0.947 0.000 0.932 NA 0.000 0.068
#> GSM1182229 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182230 2 0.0510 0.978 0.000 0.984 NA 0.000 0.016
#> GSM1182231 2 0.0162 0.980 0.000 0.996 NA 0.000 0.004
#> GSM1182232 1 0.1894 0.910 0.920 0.000 NA 0.072 0.000
#> GSM1182233 1 0.1661 0.899 0.940 0.000 NA 0.024 0.000
#> GSM1182234 1 0.1364 0.911 0.952 0.000 NA 0.036 0.000
#> GSM1182235 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182236 1 0.1981 0.912 0.920 0.000 NA 0.064 0.000
#> GSM1182237 2 0.0000 0.980 0.000 1.000 NA 0.000 0.000
#> GSM1182238 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182239 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182240 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182241 2 0.0794 0.973 0.000 0.972 NA 0.000 0.028
#> GSM1182242 2 0.1701 0.951 0.000 0.936 NA 0.000 0.048
#> GSM1182243 2 0.0404 0.979 0.000 0.988 NA 0.000 0.012
#> GSM1182244 2 0.1205 0.964 0.000 0.956 NA 0.000 0.040
#> GSM1182245 1 0.1942 0.911 0.920 0.000 NA 0.068 0.000
#> GSM1182246 4 0.1444 0.880 0.040 0.000 NA 0.948 0.000
#> GSM1182247 2 0.0609 0.976 0.000 0.980 NA 0.000 0.020
#> GSM1182248 2 0.0703 0.975 0.000 0.976 NA 0.000 0.024
#> GSM1182249 2 0.0162 0.980 0.000 0.996 NA 0.000 0.004
#> GSM1182250 2 0.0404 0.979 0.000 0.988 NA 0.000 0.012
#> GSM1182251 1 0.5641 0.518 0.612 0.000 NA 0.268 0.000
#> GSM1182252 2 0.0880 0.971 0.000 0.968 NA 0.000 0.032
#> GSM1182253 2 0.0794 0.972 0.000 0.972 NA 0.000 0.028
#> GSM1182254 2 0.0000 0.980 0.000 1.000 NA 0.000 0.000
#> GSM1182255 4 0.2208 0.873 0.072 0.000 NA 0.908 0.000
#> GSM1182256 4 0.1430 0.879 0.052 0.000 NA 0.944 0.000
#> GSM1182257 4 0.1282 0.880 0.044 0.000 NA 0.952 0.000
#> GSM1182258 4 0.0992 0.872 0.024 0.000 NA 0.968 0.000
#> GSM1182259 4 0.1372 0.871 0.024 0.000 NA 0.956 0.004
#> GSM1182260 2 0.0671 0.978 0.000 0.980 NA 0.000 0.016
#> GSM1182261 2 0.0000 0.980 0.000 1.000 NA 0.000 0.000
#> GSM1182262 2 0.0404 0.979 0.000 0.988 NA 0.000 0.012
#> GSM1182263 1 0.3620 0.856 0.824 0.000 NA 0.108 0.000
#> GSM1182264 2 0.2067 0.938 0.000 0.920 NA 0.000 0.048
#> GSM1182265 2 0.0404 0.979 0.000 0.988 NA 0.000 0.012
#> GSM1182266 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182267 1 0.1270 0.913 0.948 0.000 NA 0.052 0.000
#> GSM1182268 1 0.1331 0.887 0.952 0.000 NA 0.008 0.000
#> GSM1182269 1 0.1300 0.895 0.956 0.000 NA 0.016 0.000
#> GSM1182270 1 0.1809 0.914 0.928 0.000 NA 0.060 0.000
#> GSM1182271 4 0.1041 0.877 0.032 0.000 NA 0.964 0.000
#> GSM1182272 4 0.1522 0.880 0.044 0.000 NA 0.944 0.000
#> GSM1182273 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182275 2 0.0404 0.979 0.000 0.988 NA 0.000 0.012
#> GSM1182276 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182277 1 0.1830 0.911 0.924 0.000 NA 0.068 0.000
#> GSM1182278 1 0.1830 0.911 0.924 0.000 NA 0.068 0.000
#> GSM1182279 1 0.5136 0.682 0.688 0.000 NA 0.196 0.000
#> GSM1182280 1 0.2580 0.905 0.892 0.000 NA 0.064 0.000
#> GSM1182281 4 0.5829 0.406 0.372 0.000 NA 0.536 0.004
#> GSM1182282 1 0.1809 0.914 0.928 0.000 NA 0.060 0.000
#> GSM1182283 1 0.1809 0.914 0.928 0.000 NA 0.060 0.000
#> GSM1182284 1 0.3826 0.839 0.812 0.000 NA 0.128 0.004
#> GSM1182285 2 0.2450 0.922 0.000 0.900 NA 0.000 0.052
#> GSM1182286 2 0.0290 0.981 0.000 0.992 NA 0.000 0.008
#> GSM1182287 2 0.0510 0.979 0.000 0.984 NA 0.000 0.016
#> GSM1182288 2 0.0865 0.974 0.000 0.972 NA 0.000 0.024
#> GSM1182289 1 0.5234 0.651 0.680 0.000 NA 0.220 0.004
#> GSM1182290 1 0.1851 0.864 0.912 0.000 NA 0.000 0.000
#> GSM1182291 4 0.1300 0.875 0.028 0.000 NA 0.956 0.000
#> GSM1182274 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182292 2 0.0703 0.975 0.000 0.976 NA 0.000 0.024
#> GSM1182293 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182294 2 0.0671 0.977 0.000 0.980 NA 0.000 0.016
#> GSM1182295 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182296 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182298 2 0.3307 0.869 0.000 0.844 NA 0.000 0.052
#> GSM1182299 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182300 2 0.0566 0.980 0.000 0.984 NA 0.000 0.012
#> GSM1182301 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182303 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182304 1 0.3339 0.868 0.840 0.000 NA 0.112 0.000
#> GSM1182305 4 0.6100 0.133 0.428 0.000 NA 0.448 0.000
#> GSM1182306 4 0.1168 0.877 0.032 0.000 NA 0.960 0.000
#> GSM1182307 2 0.0963 0.969 0.000 0.964 NA 0.000 0.036
#> GSM1182309 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182312 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182314 4 0.1364 0.879 0.036 0.000 NA 0.952 0.000
#> GSM1182316 2 0.0162 0.981 0.000 0.996 NA 0.000 0.004
#> GSM1182318 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182319 2 0.0671 0.977 0.000 0.980 NA 0.000 0.016
#> GSM1182320 2 0.0324 0.981 0.000 0.992 NA 0.000 0.004
#> GSM1182321 2 0.0671 0.977 0.000 0.980 NA 0.000 0.016
#> GSM1182322 2 0.0324 0.981 0.000 0.992 NA 0.000 0.004
#> GSM1182324 2 0.0324 0.980 0.000 0.992 NA 0.000 0.004
#> GSM1182297 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182302 4 0.1764 0.877 0.064 0.000 NA 0.928 0.000
#> GSM1182308 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182310 2 0.0162 0.981 0.000 0.996 NA 0.000 0.000
#> GSM1182311 1 0.1668 0.908 0.940 0.000 NA 0.032 0.000
#> GSM1182313 4 0.1195 0.876 0.028 0.000 NA 0.960 0.000
#> GSM1182315 2 0.0404 0.980 0.000 0.988 NA 0.000 0.012
#> GSM1182317 2 0.0290 0.980 0.000 0.992 NA 0.000 0.008
#> GSM1182323 1 0.2171 0.911 0.912 0.000 NA 0.064 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1182186 4 0.4949 0.6220 0.248 0.000 NA 0.644 NA 0.000
#> GSM1182187 4 0.2609 0.8741 0.096 0.000 NA 0.868 NA 0.000
#> GSM1182188 4 0.1346 0.9177 0.024 0.000 NA 0.952 NA 0.000
#> GSM1182189 1 0.0951 0.8949 0.968 0.000 NA 0.004 NA 0.000
#> GSM1182190 1 0.1957 0.9147 0.920 0.000 NA 0.048 NA 0.000
#> GSM1182191 4 0.4990 0.6059 0.256 0.000 NA 0.636 NA 0.004
#> GSM1182192 1 0.0993 0.9075 0.964 0.000 NA 0.024 NA 0.000
#> GSM1182193 1 0.1230 0.8946 0.956 0.000 NA 0.008 NA 0.000
#> GSM1182194 2 0.2793 0.8356 0.000 0.800 NA 0.000 NA 0.200
#> GSM1182195 2 0.2491 0.8708 0.000 0.836 NA 0.000 NA 0.164
#> GSM1182196 2 0.0260 0.9635 0.000 0.992 NA 0.000 NA 0.008
#> GSM1182197 2 0.0858 0.9632 0.000 0.968 NA 0.000 NA 0.004
#> GSM1182198 2 0.3371 0.7279 0.000 0.708 NA 0.000 NA 0.292
#> GSM1182199 2 0.3101 0.7875 0.000 0.756 NA 0.000 NA 0.244
#> GSM1182200 2 0.0935 0.9618 0.000 0.964 NA 0.000 NA 0.004
#> GSM1182201 2 0.0405 0.9635 0.000 0.988 NA 0.000 NA 0.008
#> GSM1182202 4 0.1719 0.9077 0.060 0.000 NA 0.924 NA 0.000
#> GSM1182203 4 0.1857 0.9134 0.044 0.000 NA 0.924 NA 0.000
#> GSM1182204 4 0.2265 0.8941 0.076 0.000 NA 0.896 NA 0.000
#> GSM1182205 2 0.1204 0.9502 0.000 0.944 NA 0.000 NA 0.056
#> GSM1182206 2 0.0632 0.9611 0.000 0.976 NA 0.000 NA 0.024
#> GSM1182207 1 0.1471 0.8787 0.932 0.000 NA 0.000 NA 0.000
#> GSM1182208 1 0.1812 0.8685 0.912 0.000 NA 0.000 NA 0.000
#> GSM1182209 2 0.0865 0.9590 0.000 0.964 NA 0.000 NA 0.000
#> GSM1182210 2 0.0547 0.9626 0.000 0.980 NA 0.000 NA 0.000
#> GSM1182211 2 0.0865 0.9590 0.000 0.964 NA 0.000 NA 0.000
#> GSM1182212 2 0.0790 0.9599 0.000 0.968 NA 0.000 NA 0.000
#> GSM1182213 2 0.1501 0.9415 0.000 0.924 NA 0.000 NA 0.000
#> GSM1182214 2 0.1007 0.9568 0.000 0.956 NA 0.000 NA 0.000
#> GSM1182215 2 0.0820 0.9642 0.000 0.972 NA 0.000 NA 0.016
#> GSM1182216 2 0.1082 0.9591 0.000 0.956 NA 0.000 NA 0.004
#> GSM1182217 4 0.3720 0.8003 0.152 0.000 NA 0.788 NA 0.000
#> GSM1182218 1 0.2265 0.9075 0.896 0.000 NA 0.076 NA 0.000
#> GSM1182219 2 0.0508 0.9638 0.000 0.984 NA 0.000 NA 0.012
#> GSM1182220 2 0.0405 0.9641 0.000 0.988 NA 0.000 NA 0.004
#> GSM1182221 2 0.0146 0.9636 0.000 0.996 NA 0.000 NA 0.000
#> GSM1182222 2 0.0260 0.9638 0.000 0.992 NA 0.000 NA 0.000
#> GSM1182223 2 0.0777 0.9618 0.000 0.972 NA 0.000 NA 0.024
#> GSM1182224 2 0.1411 0.9465 0.000 0.936 NA 0.000 NA 0.060
#> GSM1182225 2 0.0935 0.9618 0.000 0.964 NA 0.000 NA 0.004
#> GSM1182226 2 0.0935 0.9615 0.000 0.964 NA 0.000 NA 0.004
#> GSM1182227 1 0.2632 0.9045 0.880 0.000 NA 0.076 NA 0.000
#> GSM1182228 2 0.3454 0.8051 0.000 0.768 NA 0.000 NA 0.024
#> GSM1182229 2 0.0914 0.9643 0.000 0.968 NA 0.000 NA 0.016
#> GSM1182230 2 0.0790 0.9594 0.000 0.968 NA 0.000 NA 0.032
#> GSM1182231 2 0.0291 0.9638 0.000 0.992 NA 0.000 NA 0.004
#> GSM1182232 1 0.2036 0.9121 0.912 0.000 NA 0.064 NA 0.000
#> GSM1182233 1 0.1245 0.9095 0.952 0.000 NA 0.032 NA 0.000
#> GSM1182234 1 0.1485 0.9103 0.944 0.000 NA 0.028 NA 0.000
#> GSM1182235 2 0.0935 0.9610 0.000 0.964 NA 0.000 NA 0.004
#> GSM1182236 1 0.1882 0.9129 0.920 0.000 NA 0.060 NA 0.000
#> GSM1182237 2 0.0820 0.9645 0.000 0.972 NA 0.000 NA 0.016
#> GSM1182238 2 0.1010 0.9603 0.000 0.960 NA 0.000 NA 0.004
#> GSM1182239 2 0.0632 0.9621 0.000 0.976 NA 0.000 NA 0.000
#> GSM1182240 2 0.0692 0.9634 0.000 0.976 NA 0.000 NA 0.004
#> GSM1182241 2 0.1663 0.9315 0.000 0.912 NA 0.000 NA 0.000
#> GSM1182242 2 0.2257 0.9099 0.000 0.876 NA 0.000 NA 0.116
#> GSM1182243 2 0.0713 0.9603 0.000 0.972 NA 0.000 NA 0.028
#> GSM1182244 2 0.1075 0.9533 0.000 0.952 NA 0.000 NA 0.048
#> GSM1182245 1 0.1594 0.9157 0.932 0.000 NA 0.052 NA 0.000
#> GSM1182246 4 0.0858 0.9222 0.028 0.000 NA 0.968 NA 0.000
#> GSM1182247 2 0.0937 0.9568 0.000 0.960 NA 0.000 NA 0.040
#> GSM1182248 2 0.1007 0.9554 0.000 0.956 NA 0.000 NA 0.044
#> GSM1182249 2 0.0458 0.9627 0.000 0.984 NA 0.000 NA 0.016
#> GSM1182250 2 0.0458 0.9627 0.000 0.984 NA 0.000 NA 0.016
#> GSM1182251 1 0.4836 0.5953 0.644 0.000 NA 0.268 NA 0.004
#> GSM1182252 2 0.1204 0.9502 0.000 0.944 NA 0.000 NA 0.056
#> GSM1182253 2 0.1007 0.9555 0.000 0.956 NA 0.000 NA 0.044
#> GSM1182254 2 0.0405 0.9635 0.000 0.988 NA 0.000 NA 0.008
#> GSM1182255 4 0.1718 0.9144 0.044 0.000 NA 0.932 NA 0.000
#> GSM1182256 4 0.0777 0.9220 0.024 0.000 NA 0.972 NA 0.000
#> GSM1182257 4 0.0632 0.9217 0.024 0.000 NA 0.976 NA 0.000
#> GSM1182258 4 0.0993 0.9204 0.024 0.000 NA 0.964 NA 0.000
#> GSM1182259 4 0.0891 0.9217 0.024 0.000 NA 0.968 NA 0.000
#> GSM1182260 2 0.0790 0.9621 0.000 0.968 NA 0.000 NA 0.032
#> GSM1182261 2 0.0458 0.9630 0.000 0.984 NA 0.000 NA 0.016
#> GSM1182262 2 0.0692 0.9627 0.000 0.976 NA 0.000 NA 0.020
#> GSM1182263 1 0.3107 0.8569 0.832 0.000 NA 0.116 NA 0.000
#> GSM1182264 2 0.2697 0.8486 0.000 0.812 NA 0.000 NA 0.188
#> GSM1182265 2 0.0790 0.9606 0.000 0.968 NA 0.000 NA 0.032
#> GSM1182266 2 0.0603 0.9636 0.000 0.980 NA 0.000 NA 0.016
#> GSM1182267 1 0.1801 0.9137 0.924 0.000 NA 0.056 NA 0.000
#> GSM1182268 1 0.0806 0.9011 0.972 0.000 NA 0.008 NA 0.000
#> GSM1182269 1 0.1401 0.9075 0.948 0.000 NA 0.028 NA 0.000
#> GSM1182270 1 0.1914 0.9142 0.920 0.000 NA 0.056 NA 0.000
#> GSM1182271 4 0.0922 0.9218 0.024 0.000 NA 0.968 NA 0.000
#> GSM1182272 4 0.0777 0.9218 0.024 0.000 NA 0.972 NA 0.000
#> GSM1182273 2 0.1151 0.9600 0.000 0.956 NA 0.000 NA 0.012
#> GSM1182275 2 0.0508 0.9635 0.000 0.984 NA 0.000 NA 0.012
#> GSM1182276 2 0.0363 0.9636 0.000 0.988 NA 0.000 NA 0.000
#> GSM1182277 1 0.1807 0.9135 0.920 0.000 NA 0.060 NA 0.000
#> GSM1182278 1 0.2011 0.9115 0.912 0.000 NA 0.064 NA 0.000
#> GSM1182279 1 0.4114 0.7393 0.732 0.000 NA 0.196 NA 0.000
#> GSM1182280 1 0.1995 0.9069 0.912 0.000 NA 0.052 NA 0.000
#> GSM1182281 4 0.5242 0.3940 0.348 0.000 NA 0.564 NA 0.000
#> GSM1182282 1 0.1769 0.9135 0.924 0.000 NA 0.060 NA 0.000
#> GSM1182283 1 0.1578 0.9143 0.936 0.000 NA 0.048 NA 0.000
#> GSM1182284 1 0.3196 0.8515 0.824 0.000 NA 0.136 NA 0.000
#> GSM1182285 2 0.2006 0.9172 0.000 0.892 NA 0.000 NA 0.104
#> GSM1182286 2 0.0547 0.9648 0.000 0.980 NA 0.000 NA 0.000
#> GSM1182287 2 0.1092 0.9643 0.000 0.960 NA 0.000 NA 0.020
#> GSM1182288 2 0.1196 0.9571 0.000 0.952 NA 0.000 NA 0.040
#> GSM1182289 1 0.4229 0.7081 0.712 0.000 NA 0.220 NA 0.000
#> GSM1182290 1 0.1588 0.8775 0.924 0.000 NA 0.000 NA 0.000
#> GSM1182291 4 0.0777 0.9216 0.024 0.000 NA 0.972 NA 0.000
#> GSM1182274 2 0.1391 0.9544 0.000 0.944 NA 0.000 NA 0.016
#> GSM1182292 2 0.1075 0.9566 0.000 0.952 NA 0.000 NA 0.000
#> GSM1182293 2 0.0458 0.9631 0.000 0.984 NA 0.000 NA 0.000
#> GSM1182294 2 0.1168 0.9582 0.000 0.956 NA 0.000 NA 0.016
#> GSM1182295 2 0.0632 0.9617 0.000 0.976 NA 0.000 NA 0.000
#> GSM1182296 2 0.0858 0.9618 0.000 0.968 NA 0.000 NA 0.000
#> GSM1182298 2 0.3050 0.7961 0.000 0.764 NA 0.000 NA 0.236
#> GSM1182299 2 0.0935 0.9610 0.000 0.964 NA 0.000 NA 0.004
#> GSM1182300 2 0.0405 0.9643 0.000 0.988 NA 0.000 NA 0.004
#> GSM1182301 2 0.1082 0.9578 0.000 0.956 NA 0.000 NA 0.000
#> GSM1182303 2 0.0363 0.9634 0.000 0.988 NA 0.000 NA 0.000
#> GSM1182304 1 0.2390 0.8973 0.888 0.000 NA 0.056 NA 0.000
#> GSM1182305 1 0.5705 0.0162 0.448 0.000 NA 0.424 NA 0.004
#> GSM1182306 4 0.1138 0.9201 0.024 0.000 NA 0.960 NA 0.000
#> GSM1182307 2 0.1663 0.9318 0.000 0.912 NA 0.000 NA 0.000
#> GSM1182309 2 0.0363 0.9644 0.000 0.988 NA 0.000 NA 0.000
#> GSM1182312 2 0.0547 0.9630 0.000 0.980 NA 0.000 NA 0.000
#> GSM1182314 4 0.0891 0.9210 0.024 0.000 NA 0.968 NA 0.000
#> GSM1182316 2 0.0363 0.9636 0.000 0.988 NA 0.000 NA 0.000
#> GSM1182318 2 0.0547 0.9624 0.000 0.980 NA 0.000 NA 0.000
#> GSM1182319 2 0.1010 0.9585 0.000 0.960 NA 0.000 NA 0.036
#> GSM1182320 2 0.0363 0.9634 0.000 0.988 NA 0.000 NA 0.000
#> GSM1182321 2 0.1285 0.9528 0.000 0.944 NA 0.000 NA 0.052
#> GSM1182322 2 0.0291 0.9640 0.000 0.992 NA 0.000 NA 0.004
#> GSM1182324 2 0.0363 0.9631 0.000 0.988 NA 0.000 NA 0.012
#> GSM1182297 2 0.0632 0.9628 0.000 0.976 NA 0.000 NA 0.000
#> GSM1182302 4 0.1049 0.9205 0.032 0.000 NA 0.960 NA 0.000
#> GSM1182308 2 0.0458 0.9631 0.000 0.984 NA 0.000 NA 0.000
#> GSM1182310 2 0.0622 0.9642 0.000 0.980 NA 0.000 NA 0.012
#> GSM1182311 1 0.1421 0.9100 0.944 0.000 NA 0.028 NA 0.000
#> GSM1182313 4 0.0777 0.9216 0.024 0.000 NA 0.972 NA 0.000
#> GSM1182315 2 0.1007 0.9585 0.000 0.956 NA 0.000 NA 0.000
#> GSM1182317 2 0.0458 0.9633 0.000 0.984 NA 0.000 NA 0.000
#> GSM1182323 1 0.2011 0.9122 0.912 0.000 NA 0.064 NA 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)
Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.
test_to_known_factors(res)
#> n disease.state(p) gender(p) k
#> ATC:NMF 139 0.0773 1.000 2
#> ATC:NMF 136 0.1286 0.964 3
#> ATC:NMF 137 0.0743 0.908 4
#> ATC:NMF 137 0.0743 0.908 5
#> ATC:NMF 137 0.0743 0.908 6
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