RT Journal Article
SR Electronic
T1 TCGEx: A visual interface for multifaceted analyses of The Cancer Genome Atlas gene expression data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.08.14.553075
DO 10.1101/2023.08.14.553075
A1 Kus, M. Emre
A1 Sahin, Cagatay
A1 Kilic, Emre
A1 Askin, Arda
A1 Ozgur, M. Mert
A1 Karahanogulları, Gokhan
A1 Aksit, Ahmet
A1 O’Connell, Ryan M.
A1 Ekiz, H. Atakan
YR 2023
UL http://biorxiv.org/content/early/2023/08/16/2023.08.14.553075.abstract
AB 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 opensource 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 tumorimmune interactions. TCGEx, available at https://tcgex.iyte.edu.tr, provides an interactive solution to extract meaningful insights from TCGA data and guide scientific research.Competing Interest StatementThe authors have declared no competing interest.