Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, 900 North Glebe Road, Arlington, VA, 22203, USA.
Baylor Research Institute, 3310 Live Oak St, Dallas, TX, 75204, USA.
Sci Rep. 2020 May 14;10(1):7960. doi: 10.1038/s41598-020-63043-2.
Genome-wide transcription factor (TF) binding signal analyses reveal co-localization of TF binding sites based on inferred cis-regulatory modules (CRMs). CRMs play a key role in understanding the cooperation of multiple TFs under specific conditions. However, the functions of CRMs and their effects on nearby gene transcription are highly dynamic and context-specific and therefore are challenging to characterize. BICORN (Bayesian Inference of COoperative Regulatory Network) builds a hierarchical Bayesian model and infers context-specific CRMs based on TF-gene binding events and gene expression data for a particular cell type. BICORN automatically searches for a list of candidate CRMs based on the input TF bindings at regulatory regions associated with genes of interest. Applying Gibbs sampling, BICORN iteratively estimates model parameters of CRMs, TF activities, and corresponding regulation on gene transcription, which it models as a sparse network of functional CRMs regulating target genes. The BICORN package is implemented in R (version 3.4 or later) and is publicly available on the CRAN server at https://cran.r-project.org/web/packages/BICORN/index.html.
全基因组转录因子（TF）结合信号分析揭示了基于推断的顺式调控模块（CRMs）的 TF 结合位点的共定位。CRMs 在理解特定条件下多个 TF 的合作中起着关键作用。然而，CRMs 的功能及其对附近基因转录的影响是高度动态和特定于上下文的，因此难以进行表征。BICORN（合作调控网络的贝叶斯推断）构建了一个层次贝叶斯模型，并基于特定细胞类型的 TF-基因结合事件和基因表达数据推断特定于上下文的 CRM。BICORN 自动根据与感兴趣基因相关的调节区域中与输入 TF 结合的列表搜索候选 CRM。通过吉布斯抽样，BICORN 迭代估计 CRM、TF 活性和对应于基因转录的调节的模型参数，它将其建模为一个稀疏的功能 CRM 网络，用于调节靶基因。BICORN 包是在 R（版本 3.4 或更高版本）中实现的，并在 CRAN 服务器上公开提供，网址为 https://cran.r-project.org/web/packages/BICORN/index.html。
