ChIP-PED enhances the analysis of ChIP-seq and ChIP-chip data.

George Wu, Jason T. Yustein, Matthew N. McCall, Michael Zilliox, Rafael A. Irizarry, Karen Zeller, Chi V. Dang, Hongkai Ji

Research output: Contribution to journalArticle

Abstract

Although chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip) is increasingly used to map genome-wide-binding sites of transcription factors (TFs), it still remains difficult to generate a quality ChIPx (i.e. ChIP-seq or ChIP-chip) dataset because of the tremendous amount of effort required to develop effective antibodies and efficient protocols. Moreover, most laboratories are unable to easily obtain ChIPx data for one or more TF(s) in more than a handful of biological contexts. Thus, standard ChIPx analyses primarily focus on analyzing data from one experiment, and the discoveries are restricted to a specific biological context. We propose to enrich this existing data analysis paradigm by developing a novel approach, ChIP-PED, which superimposes ChIPx data on large amounts of publicly available human and mouse gene expression data containing a diverse collection of cell types, tissues and disease conditions to discover new biological contexts with potential TF regulatory activities. We demonstrate ChIP-PED using a number of examples, including a novel discovery that MYC, a human TF, plays an important functional role in pediatric Ewing sarcoma cell lines. These examples show that ChIP-PED increases the value of ChIPx data by allowing one to expand the scope of possible discoveries made from a ChIPx experiment. http://www.biostat.jhsph.edu/~gewu/ChIPPED/

Original languageEnglish (US)
Pages (from-to)1182-1189
Number of pages8
JournalUnknown Journal
Volume29
Issue number9
StatePublished - May 1 2013

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ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Wu, G., Yustein, J. T., McCall, M. N., Zilliox, M., Irizarry, R. A., Zeller, K., Dang, C. V., & Ji, H. (2013). ChIP-PED enhances the analysis of ChIP-seq and ChIP-chip data. Unknown Journal, 29(9), 1182-1189.