TCGAnalyzeR: a web application for integrative visualization of molecular and clinical data of cancer patients for cohort and associated gene discovery

Abstract

MotivationThe vast size and complexity of The Cancer Genome Atlas (TCGA) database with multidimensional molecular and clinical data of ~11,000 cancer patients of 33 cancer types challenge the effective utilization of this valuable resource. Therefore, we built a web application named TCGAnalyzeR with the main idea of presenting an integrative visualization of mutations, transcriptome profile, copy number variation and clinical data allowing researchers to facilitate the identification of customized patient cohorts and gene sets for better decision-making for oncologists and cancer researchers. ResultsWe present TCGAnalyzeR for integrative visualization of pre-analyzed TCGA data with the several novel modules: (i) Simple nucleotide variations with driver prediction; (ii) Recurrent copy number alterations; (iii) Differential expression in tumor versus normal, with pathway enrichment and the survival analysis; (iii) TCGA clinical data and survival analysis; (iv) External subcohorts from literature, curatedTCGAData and BiocOncoTK R packages; (v) Internal patient clusters determined using iClusterPlus R package or signature-based expression analysis. TCGAnalyzeR provides clinical oncologists and cancer researchers interactive and integrative representations of these multi-omic, pan-cancer TCGA data with availability of subcohort analysis and visualization. TCGAnalyzeR can be used to create their own custom gene sets for pan-cancer comparisons, to create custom patient subcohorts comparing external subcohorts (MSI, Immune, PAM50, Triple Negative, IDH1, miRNA, etc) along with our internal patient clusters, to visualize cohort-centric or gene-centric results along with pathway enrichment and survival analysis graphically on an interactive web tool. AvailabilityTCGAnalyzeR is freely available on the web at http://tcganalyzer.mu.edu.tr. Contacttugbasuzek@mu.edu.tr Supplementary informationSupplementary data are available at Bioinformatics online.