Bioinformatics. 2010 Oct 1;26(19):2438-44. doi: 10.1093/bioinformatics/btq466. Epub 2010 Aug 13.

ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments.

Lachmann A, Xu H, Krishnan J, Berger SI, Mazloom AR, Ma'ayan A.

Source

Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.

Abstract

MOTIVATION:

Experiments such as ChIP-chip, ChIP-seq, ChIP-PET and DamID (the four methods referred herein as ChIP-X) are used to profile the binding of transcription factors to DNA at a genome-wide scale. Such experiments provide hundreds to thousands of potential binding sites for a given transcription factor in proximity to gene coding regions.

RESULTS:

In order to integrate data from such studies and utilize it for further biological discovery, we collected interactions from such experiments to construct a mammalian ChIP-X database. The database contains 189,933 interactions, manually extracted from 87 publications, describing the binding of 92 transcription factors to 31,932 target genes. We used the database to analyze mRNA expression data where we perform gene-list enrichment analysis using the ChIP-X database as the prior biological knowledge gene-list library. The system is delivered as a web-based interactive application called ChIP Enrichment Analysis (ChEA). With ChEA, users can input lists of mammalian gene symbols for which the program computes over-representation of transcription factor targets from the ChIP-X database. The ChEA database allowed us to reconstruct an initial network of transcription factors connected based on shared overlapping targets and binding site proximity. To demonstrate the utility of ChEA we present three case studies. We show how by combining the Connectivity Map (CMAP) with ChEA, we can rank pairs of compounds to be used to target specific transcription factor activity in cancer cells.