Article abstract

Nature Methods 5, 829 - 834 (2008)
Published online: 17 August 2008 | doi:10.1038/nmeth.1246

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

Anton Valouev1,4, David S Johnson2,4, Andreas Sundquist3, Catherine Medina2, Elizabeth Anton2, Serafim Batzoglou3, Richard M Myers2 & Arend Sidow1,2

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.

  1. Department of Pathology, Stanford University Medical Center, 300 Pasteur Drive, Stanford, California 94305, USA.
  2. Department of Genetics, Stanford University Medical Center, 300 Pasteur Drive, Stanford, California 94305, USA.
  3. Department of Computer Science, Stanford University, 318 Campus Drive, Stanford, California 94305, USA.
  4. These authors contributed equally to this work.

Correspondence to: Arend Sidow1,2 e-mail:


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