Additional file 1: Supplemental File containing all Supplemental Figures, Supplemental Tables, and Supplemental Note including additional details on the method and data analysis. Table S1. Supplementary Table summarizing input data of 18 cancer types across number of samples analyzed and total number of features that went into clustering for mutation, Copy Number (CN), Methylation, mRNA expression, miRNA and Protein. Table S2. Supplementary Table showing comparisons of survClust integrated solution versus unsupervised clustering results from published TCGA studies. Table S3. Summary of survival association for the survClust Copy Number solutions versus unsupervised TCGA solutions using the logrank statistic. Table S4. Summary of survival association for the survClust Methylation expression solution versus available TCGA solutions using the logrank statistic. Table S5. Summary of survival association for the survClust mRNA expression solution versus available TCGA solutions using the logrank statistic. Table S6. Summary of survival association for the survClust miRNA expression solution versus available TCGA solutions using the logrank statistic. Table S7. Summary of survival association for the survClust Protein expression solution vs available TCGA solutions using the logrank statistic. Table S8. Cross tabulation of the ovarian cancer copy number survClust class labels vs AKT gene Copy number changes. Figure S1. survClust simulation analysis. Figure S2. A second simulation example. Figure S3. survClust integrated solution of low grade glioma (LGG). Figure S4. survClust identifies tumor mutation burden (TMB) patterns across cancer types. Figure S5. CD8 expression stratified by the survClust mutation subclasses across various cancer types. Figure S6. survClus tidentifies copy number alteration patterns across cancer types, Global view of Copy Number Changes. Figure S7. survClust identifies FGA patterns across cancer types that associate with survival (Kaplan Meier curves). Figure S8. survClust integrated solution across six molecular platforms in various cancer types. Supplementary Note Description of data pre-processing, simulation details and the centroid re-labeling approach.