Bioinformatics and Systems Biology Lab, Federal University of Paraná, Curitiba, Brazil.
Department of Clinical Sciences, Section of Oncology and Pathology, Lund University, Lund 221 85, Sweden.
Bioinformatics. 2019 Dec 15;35(24):5357-5358. doi: 10.1093/bioinformatics/btz534.
MOTIVATION: Transcription factors (TFs) are key regulators of gene expression, and can activate or repress multiple target genes, forming regulatory units, or regulons. Understanding downstream effects of these regulators includes evaluating how TFs cooperate or compete within regulatory networks. Here we present RTNduals, an R/Bioconductor package that implements a general method for analyzing pairs of regulons. RESULTS: RTNduals identifies a dual regulon when the number of targets shared between a pair of regulators is statistically significant. The package extends the RTN (Reconstruction of Transcriptional Networks) package, and uses RTN transcriptional networks to identify significant co-regulatory associations between regulons. The Supplementary Information reports two case studies for TFs using the METABRIC and TCGA breast cancer cohorts. AVAILABILITY AND IMPLEMENTATION: RTNduals is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNduals/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
动机:转录因子(TFs)是基因表达的关键调节剂,它们可以激活或抑制多个靶基因,形成调控单元或调控群。理解这些调节剂的下游效应包括评估 TF 在调控网络中如何合作或竞争。在这里,我们提出了 RTNduals,这是一个 R/Bioconductor 包,它实现了一种分析双调控群的通用方法。
结果:当一对调节剂之间共享的靶标数量具有统计学意义时,RTNduals 会识别出一个双调控群。该软件包扩展了 RTN(转录网络重建)软件包,并使用 RTN 转录网络来识别调控群之间显著的共调控关联。补充信息报告了使用 METABRIC 和 TCGA 乳腺癌队列的两个 TF 案例研究。
可用性和实现:RTNduals 是用 R 语言编写的,并可从 http://bioconductor.org/packages/RTNduals/ 上的 Bioconductor 项目获得。
补充信息:补充数据可在 Bioinformatics 在线获得。
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