Extended Data Fig. 10: Association between MOFA latent factors and the clusters identified by consensus clustering (a-d) and integrative clustering (e-h).
a) Kruskal-Wallis rank sum test significance (P value) between each K (row) and the LFs (column), for K from 2 to 5 from consensus clustering results and the first four LFs. b) Kruskal-Wallis rank sum test significance (P value) between each K (row) and the LFs (column), for K from 2 to 5 from integrative clustering results and the first four LFs. c) Consensus clustering results for K = 3. Samples are visualized in MOFA latent factor space of LF2 vs. LF3 and colored by the consensus clustering results. d) Integrative clustering results for K = 4. Samples are visualized in MOFA latent factor space of LF2 vs. LF3 and colored by the integrative clustering results. On the right, we show the samples in one-dimensional space of LF1 using beeswarm plot. e) Consensus clustering results for K = 4. f) Integrative clustering results for K = 5. Samples are visualized in MOFA latent factor space of LF2 vs. LF3 and colored by the integrative clustering results. On the right, we show the samples in one-dimensional space of LF1 and LF4 using beeswarm plot. g) Top-left: average silhouette width for consensus clustering with different K. Bottom-left: proportion of samples below the selected silhouette width threshold for consensus clustering with different K. Right: consensus matrix heatmap for K = 3. Color gradient represents consensus values from 0–1. h) Top-left: average silhouette width for integrative clustering with different K. Bottom-left: proportion of samples below the selected silhouette width threshold for integrative clustering with different K. Right: heatmap of the frequencies of samples being clustered together among all clustering results using the set of iClusterPlus lambda values for K = 4. Color gradient represents consensus values from 0–1.
