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ChEA2: Gene-Set Libraries from ChIP-X Experiments to Decode the Transcription Regulome

  • Yan Kou
  • Edward Y. Chen
  • Neil R. Clark
  • Qiaonan Duan
  • Christopher M. Tan
  • Avi Ma‘ayan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8127)

Abstract

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.

Keywords

ChIP-seq ChIP-chip Microarrays Systems Biology ENCODE Enrichment Analysis Transcriptional Networks Data Integration Data Visualization JavaScript D3 

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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Yan Kou
    • 1
  • Edward Y. Chen
    • 1
  • Neil R. Clark
    • 1
  • Qiaonan Duan
    • 1
  • Christopher M. Tan
    • 1
  • Avi Ma‘ayan
    • 1
  1. 1.Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY)Icahn School of Medicine at Mount SinaiNew YorkUSA

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