Exploring drivers of gene expression in the Cancer Genome Atlas. Bioinformatics 2019 Jan 01;35(1):62-68
Date
12/19/2018Pubmed ID
30561551Pubmed Central ID
PMC6298045DOI
10.1093/bioinformatics/bty551Scopus ID
2-s2.0-85058741070 (requires institutional sign-in at Scopus site) 18 CitationsAbstract
MOTIVATION: The Cancer Genome Atlas (TCGA) has greatly advanced cancer research by generating, curating and publicly releasing deeply measured molecular data from thousands of tumor samples. In particular, gene expression measures, both within and across cancer types, have been used to determine the genes and proteins that are active in tumor cells.
RESULTS: To more thoroughly investigate the behavior of gene expression in TCGA tumor samples, we introduce a statistical framework for partitioning the variation in gene expression due to a variety of molecular variables including somatic mutations, transcription factors (TFs), microRNAs, copy number alternations, methylation and germ-line genetic variation. As proof-of-principle, we identify and validate specific TFs that influence the expression of PTPN14 in breast cancer cells.
AVAILABILITY AND IMPLEMENTATION: We provide a freely available, user-friendly, browseable interactive web-based application for exploring the results of our transcriptome-wide analyses across 17 different cancers in TCGA at http://ls-shiny-prod.uwm.edu/edge_in_tcga. All TCGA Open Access tier data are available at the Broad Institute GDAC Firehose and were downloaded using the TCGA2STAT R package. TCGA Controlled Access tier data are available via controlled access through the Genomic Data Commons (GDC). R scripts used to download, format and analyze the data and produce the interactive R/Shiny web app have been made available on GitHub at https://github.com/andreamrau/EDGE-in-TCGA.
Author List
Rau A, Flister M, Rui H, Auer PLAuthor
Paul L. Auer PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Gene Expression ProfilingGenes, Neoplasm
Humans
Internet
Neoplasms
Software