REGGAE: a Novel Approach for the Identification of Key Transcriptional Regulators

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2018 May 10

PMID 29741575

Citations 5

Authors

Tim Kehl

Lara Schneider

Kathrin Kattler

Daniel Stockel

Jenny Wegert

Nico Gerstner

Nicole Ludwig

Ute Distler

Markus Schick

Ulrich Keller

Stefan Tenzer

Manfred Gessler

Jorn Walter

Andreas Keller

Norbert Graf

Eckart Meese

Hans-Peter Lenhof

Affiliations

Soon will be listed here.

Abstract

Motivation: Transcriptional regulators play a major role in most biological processes. Alterations in their activities are associated with a variety of diseases and in particular with tumor development and progression. Hence, it is important to assess the effects of deregulated regulators on pathological processes.

Results: Here, we present REGulator-Gene Association Enrichment (REGGAE), a novel method for the identification of key transcriptional regulators that have a significant effect on the expression of a given set of genes, e.g. genes that are differentially expressed between two sample groups. REGGAE uses a Kolmogorov-Smirnov-like test statistic that implicitly combines associations between regulators and their target genes with an enrichment approach to prioritize the influence of transcriptional regulators. We evaluated our method in two different application scenarios, which demonstrate that REGGAE is well suited for uncovering the influence of transcriptional regulators and is a valuable tool for the elucidation of complex regulatory mechanisms.

Availability And Implementation: REGGAE is freely available at https://regulatortrail.bioinf.uni-sb.de.

Supplementary Information: Supplementary data are available at Bioinformatics online.

Citing Articles

GeneTrail: A Framework for the Analysis of High-Throughput Profiles.

Gerstner N, Kehl T, Lenhof K, Eckhart L, Schneider L, Stockel D Front Mol Biosci. 2021; 8:716544.

PMID: 34604304 PMC: 8481803. DOI: 10.3389/fmolb.2021.716544.

Discovering key transcriptomic regulators in pancreatic ductal adenocarcinoma using Dirichlet process Gaussian mixture model.

Hossain S, Halsana A, Khatun L, Ray S, Mukhopadhyay A Sci Rep. 2021; 11(1):7853.

PMID: 33846515 PMC: 8041769. DOI: 10.1038/s41598-021-87234-7.

The Efficacy of Sunitinib Treatment of Renal Cancer Cells Is Associated with the Protein PHAX In Vitro.

Al-Lamki R, Hudson N, Bradley J, Warren A, Eisen T, Welsh S Biology (Basel). 2020; 9(4).

PMID: 32272660 PMC: 7236799. DOI: 10.3390/biology9040074.

Enhanced identification of significant regulators of gene expression.

Ehsani R, Drablos F BMC Bioinformatics. 2020; 21(1):134.

PMID: 32252623 PMC: 7132893. DOI: 10.1186/s12859-020-3468-z.

Improved linking of motifs to their TFs using domain information.

Baumgarten N, Schmidt F, Schulz M Bioinformatics. 2019; 36(6):1655-1662.

PMID: 31742324 PMC: 7703792. DOI: 10.1093/bioinformatics/btz855.

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