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Nat Methods. 2008 Sep;5(9):829-34. doi: 10.1038/nmeth.1246.

Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data.

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  • 1Department of Pathology, Stanford University Medical Center, 300 Pasteur Drive, Stanford, California 94305, USA.

Abstract

Molecular interactions between protein complexes and DNA mediate essential gene-regulatory functions. Uncovering such interactions by chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) has recently become the focus of intense interest. We here introduce quantitative enrichment of sequence tags (QuEST), a powerful statistical framework based on the kernel density estimation approach, which uses ChIP-Seq data to determine positions where protein complexes contact DNA. Using QuEST, we discovered several thousand binding sites for the human transcription factors SRF, GABP and NRSF at an average resolution of about 20 base pairs. MEME motif-discovery tool-based analyses of the QuEST-identified sequences revealed DNA binding by cofactors of SRF, providing evidence that cofactor binding specificity can be obtained from ChIP-Seq data. By combining QuEST analyses with Gene Ontology (GO) annotations and expression data, we illustrate how general functions of transcription factors can be inferred.

PMID:
19160518
[PubMed - indexed for MEDLINE]
PMCID:
PMC2917543
Free PMC Article

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