TCGEx: A visual interface for multifaceted analyses of The Cancer Genome Atlas gene expression data

The Cancer Genome Atlas (TCGA) initiative has been essential for revealing key mechanisms in human cancer leading to the development of novel therapeutics. TCGA data repository consists of genomic, transcriptomic, epigenetic data and clinical metadata from 11000+ patients across 33+ cancer types. Analysis of such large data sets require coding skills that are associated with a steep learning curve for most non-specialists. To enable a wider utilization of TCGA gene expression data, we introduce The Cancer Genome Explorer (TCGEx), a web-based visual data analysis interface that can perform a number of sophisticated analyses ranging from survival modeling and gene set enrichment analysis to unsupervised clustering and linear regression-based machine learning. TCGEx offers customizable options to tailor the analysis to different study contexts and helps generate publication-ready plots. Developed using R/Shiny framework, this open-source tool enables researchers with no programming expertise to analyze TCGA RNA and miRNA sequencing data from multiple angles. Pre-processed data in TCGEx contains cancer subtype information as well as previously reported intratumoral immune cell signatures making it possible to investigate the possible tumor-immune interactions. TCGEx, available at https://tcgex.iyte.edu.tr, provides an interactive solution to extract meaningful insights from TCGA data and guide scientific research.