Accurate differential analysis of transcription factor activity from gene expression

• DOI: 10.1093/bioinformatics/btz398
• Publication Date: 2019-05-08T19:28:40Z
• Authors: Viren Amin; Didem Ağaç; Spencer D Barnes; Murat Can Çobanoğlu
• Keywords: Regulon

Abstract Motivation Activity of transcriptional regulators is crucial in elucidating the mechanism phenotypes. However regulatory activity hypotheses are difficult to experimentally test. Therefore, we need accurate and reliable computational methods for regulator inference. There extensive work this area, however, current have difficulty with one or more following: resolving TFs overlapping regulons, reflecting known relationships, flexible modeling TF over regulon. Results We present Effector Perturbation Estimation Engine (EPEE), a method differential analysis transcription factor (TF) from gene expression data. EPEE addresses each these principal challenges field. Firstly, collectively models all single multivariate model, thereby accounting intrinsic coupling among that share targets, which highly frequent. Secondly, incorporates context-specific TF-gene networks therefore adapts biological context. Finally, can flexibly reflect different its potential targets. This allows flexibility implicitly recover other influences such as co-activators repressors. comparatively validated 15 datasets three well-studied contexts, namely immunology, cancer, hematopoiesis. show addressing aforementioned enable outperform alternative reliably produce results. Availability implementation https://github.com/Cobanoglu-Lab/EPEE. Supplementary information data available at Bioinformatics online.