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A computational pipeline for comparative ChIP-seq analyses

Nature Protocols volume 7, pages 45–61 (2012)Cite this article

Abstract

Chromatin immunoprecipitation (ChIP) followed by deep sequencing can now easily be performed across different conditions, time points and even species. However, analyzing such data is not trivial and standard methods are as yet unavailable. Here we present a protocol to systematically compare ChIP-sequencing (ChIP-seq) data across conditions. We first describe technical guidelines for data preprocessing, read mapping, read-density visualization and peak calling. We then describe methods and provide code with specific examples to compare different data sets across species and across conditions, including a threshold-free approach to measure global similarity, a strategy to assess the binary conservation of binding events and measurements for quantitative changes of binding. We discuss how differences in binding can be related to gene functions, gene expression and sequence changes. Once established, this protocol should take about 2 d to complete and be generally applicable to many data sets.

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Figure 1: Computational pipeline for comparative analyses of ChIP-seq data.
Figure 2: Choice of sensitive thresholds when comparing ChIP-seq samples.
Figure 3: Assessing choice of thresholds and its impact on conservation estimates.
Figure 4: Binding conservation at different peak ranks.
Figure 5: Sensitive estimation of conservation in vertebrates.
Figure 6: Comparative ChIP-seq data of the C. elegans transcription factor PHA4/FOXA across conditions.

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Acknowledgements

We thank M. Jaritz; I. Tamir; A. Sommer; O. Yanez-Cuna; D. Gerlach (Institute of Molecular Pathology); J. Steinmann (Institute of Molecular Biotechnology (IMBA)); and S. Meier and C. Seidel (Stowers Institute for Medical Research) for discussions, help and advice. A.F.B. was supported by the Austrian Ministry for Science and Research through the Genome Research in Austria (GEN-AU) Bioinformatics Integration Network III. J.Z. is a Pew scholar. A.S. is supported by a European Research Council (ERC) Starting Grant from the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 242922. Basic research at the IMP is supported by Boehringer Ingelheim.

Author information

Authors and Affiliations

  1. Research Institute of Molecular Pathology, Vienna, Austria

    Anaïs F Bardet & Alexander Stark

  2. Stowers Institute for Medical Research, Kansas City, Missouri, USA

    Qiye He & Julia Zeitlinger

  3. Department of Pathology, University of Kansas Medical School, Kansas City, Kansas, USA

    Julia Zeitlinger

Authors
  1. Anaïs F Bardet
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  2. Qiye He
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  3. Julia Zeitlinger
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  4. Alexander Stark
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Contributions

A.F.B. and A.S. established the analysis pipeline. Q.H. and J.Z. performed the comparative ChIP-seq experiments. A.F.B., A.S. and J.Z. wrote the manuscript.

Corresponding authors

Correspondence to Julia Zeitlinger or Alexander Stark.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Tables 1-3

Table S1: Performance of coordinate translation in vertebrates Table S2: Read mapping sensitivity for Drosophila species Table S3: Read translation sensitivity for Drosophila species (DOC 60 kb)

Supplementary Data

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Bardet, A., He, Q., Zeitlinger, J. et al. A computational pipeline for comparative ChIP-seq analyses. Nat Protoc 7, 45–61 (2012). https://doi.org/10.1038/nprot.2011.420

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