A hierarchical spike-and-slab model for pan-cancer survival using pan-omic data - Samorodnitsky, Sarah; Hoadley, Katherine A.; Lock, Eric F. (BMC bioinformatics, 2022)
Keywords: Algorithms; Analysis; Bayes Theorem; Bayesian analysis; Bayesian hierarchical modeling; Bidimensionally-linked matrices; Bioinformatics; Biomedical and Life Sciences; Cancer; Carcinoma; Carcinoma, Renal Cell; Clinical outcomes; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Diagnosis; Endometrial cancer; Endometrium; Feature selection; Genomes; Heterogeneity; Humans; Kidney cancer; Kidney Neoplasms; Life Sciences; Linked Data; Medical research; Methods; Microarrays; Molecular dynamics; Multilevel analysis; pan-cancer; Pan-omics; Patients; Principal components analysis; Research Design; Sparsity; Spike-and-slab priors; Survival; survival analysis; Tumors; Uterine cancer; Uterus; United States; Bidimensionally-linked matrices; Pan-omics; pan-cancer; survival analysis; Bayesian hierarchical modeling; The Cancer Genome Atlas (TCGA ); Spike-and-slab priors