3CPET: finding co-factor complexes from ChIA-PET data using a hierarchical Dirichlet process
Mohamed Nadhir Djekidel1, Zhengyu Liang2, Qi Wang3
1MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing, 100084, China. nde12@mails.tsinghua.edu.cn.
Abstract:
Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies. 3CPET does so by combining data from ChIA-PET, transcription factor binding sites, and protein interactions. 3CPET results show biologically significant and accurate predictions when validated against experimental and simulation data.
