Abstract
ChIP-Seq is widely used to characterize genome-wide binding patterns of transcription factors and other chromatin-associated proteins. Although comparison of ChIP-Seq data sets is critical for understanding cell-type-dependent binding, and thus the study of cell-type-specific regulation, few quantitative approaches have been developed. This chapter describes a simple and effective method, MAnorm, for quantitative comparison of ChIP-Seq data sets. It exhibits good performance when applied to ChIP-Seq data for both epigenetic modifications and transcription factor binding site identification. The quantitative binding differences inferred by MAnorm strongly correlate with both the changes in expression of target genes and the binding of cell-type-specific regulators. Comparisons to prior methods using genome-wide signals for normalization reveal that output of MAnorm contains much lower level of bias and better reflects authentic biological changes. At the end of this chapter, an integrative pipeline of using MAnorm to identify high-confidence cell-type-specific enhancers will be presented, which can serve as a simple but illustrative example of downstream applications.
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Acknowledgments
We sincerely thank Prof. Stuart H. Orkin and Prof. David J. Waxman for the great guidance during development of MAnorm model. We also thank the laboratories associated with the ENCODE project for generating and maintaining the data sets used in our analyses, as well as Drs. Jian Xu, Han Xu, and Aarathi Sugathan for useful discussions.
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Shao, Z., Zhang, Y. (2015). Quantitative Comparison of ChIP-Seq Data Sets Using MAnorm. In: Teschendorff, A. (eds) Computational and Statistical Epigenomics. Translational Bioinformatics, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9927-0_4
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DOI: https://doi.org/10.1007/978-94-017-9927-0_4
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