1. ChEA2: Gene-Set Libraries from ChIP-X Experiments to Decode the Transcription Regulome
- Author
-
Kou, Yan, Chen, Edward, Clark, Neil, Duan, Qiaonan, Tan, Christopher, Ma‘ayan, Avi, Ifip, Hal, Alfredo Cuzzocrea, Christian Kittl, Dimitris E. Simos, Edgar Weippl, Lida Xu, Department of pharmacology and systems therapeutics [Mount Sinai], and Icahn School of Medicine at Mount Sinai [New York] (MSSM)
- Subjects
Data Integration ,Microarrays ,[SHS.INFO]Humanities and Social Sciences/Library and information sciences ,Systems Biology ,Data Visualization ,[INFO] Computer Science [cs] ,ChIP-chip ,[SHS.INFO] Humanities and Social Sciences/Library and information sciences ,ChIP-seq ,[INFO]Computer Science [cs] ,Transcriptional Networks ,JavaScript D3 ,Enrichment Analysis ,ENCODE - Abstract
Part 1: Cross-Domain Conference and Workshop on Multidisciplinary Research and Practice for Information Systems (CD-ARES 2013); International audience; ChIP-seq experiments provide a plethora of data regarding transcription regulation in mammalian cells. Integrating ChIP-seq studies into a computable resource is potentially useful for further knowledge extraction from such data. We continually collect and expand a database where we convert results from ChIP-seq experiments into gene-set libraries. The manual portion of this database currently contains 200 transcription factors from 221 publications for a total of 458,471 transcription-factor/target interactions. In addition, we automatically compiled data from the ENCODE project which includes 920 experiments applied to 44 cell-lines profiling 160 transcription factors for a total of ~1.4 million transcription-factor/target-gene interactions. Moreover, we processed data from the NIH Epigenomics Roadmap project for 27 different types of histone marks in 64 different human cell-lines. All together the data was processed into three simple gene-set libraries where the set label is either a mammalian transcription factor or a histone modification mark in a particular cell line, organism and experiment. Such gene-set libraries are useful for elucidating the experimentally determined transcriptional networks regulating lists of genes of interest using gene-set enrichment analyses. Furthermore, from these three gene-set libraries, we constructed regulatory networks of transcription factors and histone modifications to identify groups of regulators that work together. For example, we found that the Polycomb Repressive Complex 2 (PRC2) is involved with three distinct clusters each interacting with different sets of transcription factors. Notably, the combined dataset is made into web-based application software where users can perform enrichment analyses or download the data in various formats. The open source ChEA2 web-based software and datasets are available freely online at http://amp.pharm.mssm.edu/ChEA2.
- Published
- 2013