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Unified Analysis of Multiple ChIP-Seq Datasets

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DNA Modifications

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2198))

Abstract

High-throughput sequencing technologies are increasingly used in molecular cell biology to assess genome-wide chromatin dynamics of proteins bound to DNA, through techniques such as chromatin immunoprecipitation sequencing (ChIP-seq). These techniques often rely on an analysis strategy based on identifying genomic regions with increased sequencing signal to infer the binding location or chemical modifications of proteins bound to DNA. Peak calling within individual samples has been well described, however relatively little attention has been devoted to the merging of replicate samples, and the cross-comparison of many samples. Here, we present a generalized strategy to enable the unification of ChIP-seq datasets, enabling enhanced cross-comparison of binding patterns. The strategy works by merging peak data between different (even unrelated) samples, and then using a local background to recalculate enrichment. This strategy redefines the peaks within each experiment, allowing for more accurate cross-comparison of datasets.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (31970589, 31801217, 31850410463, and 31850410486), and by the Center for Computational Science and Engineering of Southern University of Science and Technology.

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Authors and Affiliations

  1. Department of Biology, Southern University of Science and Technology, Shenzhen, China

    Gang Ma, Isaac A. Babarinde, Qiang Zhuang & Andrew P. Hutchins

  2. State Key Laboratory of Medicinal Chemical Biology and College of Life Sciences, Nankai University, Tianjin, China

    Qiang Zhuang

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  1. Gang Ma
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  2. Isaac A. Babarinde
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  3. Qiang Zhuang
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  4. Andrew P. Hutchins
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Correspondence to Andrew P. Hutchins .

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Editors and Affiliations

  1. Centre for Biomolecular Sciences, University Park, University of Nottingham, Nottingham, UK

    Alexey Ruzov

  2. School of Life Sciences, Queen’s Medical Centre, University of Nottingham, Nottingham, UK

    Martin Gering

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Ma, G., Babarinde, I.A., Zhuang, Q., Hutchins, A.P. (2021). Unified Analysis of Multiple ChIP-Seq Datasets. In: Ruzov, A., Gering, M. (eds) DNA Modifications. Methods in Molecular Biology, vol 2198. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0876-0_33

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  • DOI: https://doi.org/10.1007/978-1-0716-0876-0_33

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