• Media type: E-Article
  • Title: REGGAE: a novel approach for the identification of key transcriptional regulators
  • Contributor: Kehl, Tim [Author]; Schneider, Lara [Author]; Kattler, Kathrin [Author]; Stöckel, Daniel [Author]; Wegert, Jenny [Author]; Gerstner, Nico [Author]; Ludwig, Nicole [Author]; Distler, Ute [Author]; Schick, Markus [Author]; Keller, Ulrich [Author]; Tenzer, Stefan [Author]; Gessler, Manfred [Author]; Walter, Jörn [Author]; Keller, Andreas [Author]; Graf, Norbert [Author]; Meese, Eckart [Author]; Lenhof, Hans-Peter [Author]
  • Published: Saarländische Universitäts- und Landesbibliothek, 2018
  • Language: English
  • DOI: https://doi.org/10.22028/D291-35403; https://doi.org/10.1093/bioinformatics/bty372
  • ISSN: 1460-2059; 1367-4803
  • Origination:
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  • Description: 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 progres sion. 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 be tween 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.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)