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Computational Analysis of ChIP-chip Data

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Handbook of Statistical Bioinformatics

Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

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Abstract

Chromatin immunoprecipitation coupled with genome tiling array hybridization, also known as ChIP-chip, is a powerful technology to identify protein-DNA interactions in genomes. It is widely used to locate transcription factor binding sites and histone modifications. Data generated by ChIP-chip provide important information on gene regulation. This chapter reviews fundamental issues in ChIP-chip data analysis. Topics include data preprocessing, background correction, normalization, peak detection and motif analysis. Statistical models and principles that significantly improve data analysis are discussed. Popular software tools are briefly introduced.

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Acknowledgements

This work is partially supported by the Johns Hopkins Faculty Professional Development Fund to H.J. The author would like to thank Jennifer T. Judy for helpful comments and proofreading the draft of this chapter.

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Authors and Affiliations

  1. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA

    Hongkai Ji

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  1. Hongkai Ji
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Correspondence to Hongkai Ji .

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Editors and Affiliations

  1. , Institute of Statistics, National Chiao Tung University, Ta Hsueh Road 1001, Hsinchu, 30050, Taiwan, Taiwan R.O.C.

    Henry Horng-Shing Lu

  2. , Department of Empirical Inference, MPI for Intelligent Systems, Spemannstraße 38, Tübingen, 72076, Germany

    Bernhard Schölkopf

  3. School of Medicine, Dept. Epidemiology & Public Health, Yale University, College Street 60, New Haven, 06520, Connecticut, USA

    Hongyu Zhao

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Ji, H. (2011). Computational Analysis of ChIP-chip Data. In: Lu, HS., Schölkopf, B., Zhao, H. (eds) Handbook of Statistical Bioinformatics. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16345-6_12

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