Quantitative Biology

, Volume 1, Issue 1, pp 54–70 | Cite as

Computational methodology for ChIP-seq analysis

  • Hyunjin Shin
  • Tao Liu
  • Xikun Duan
  • Yong Zhang
  • X. Shirley Liu


Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) is a powerful technology to identify the genome-wide locations of DNA binding proteins such as transcription factors or modified histones. As more and more experimental laboratories are adopting ChIP-seq to unravel the transcriptional and epigenetic regulatory mechanisms, computational analyses of ChIP-seq also become increasingly comprehensive and sophisticated. In this article, we review current computational methodology for ChIP-seq analysis, recommend useful algorithms and workflows, and introduce quality control measures at different analytical steps. We also discuss how ChIP-seq could be integrated with other types of genomic assays, such as gene expression profiling and genome-wide association studies, to provide a more comprehensive view of gene regulatory mechanisms in important physiological and pathological processes.


Histone Mark Nucleosome Occupancy Peak Calling Chromatin Signature Target Gene Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Higher Education Press and Springer-Verlag GmbH 2013

Authors and Affiliations

  • Hyunjin Shin
    • 1
  • Tao Liu
    • 1
  • Xikun Duan
    • 2
  • Yong Zhang
    • 2
  • X. Shirley Liu
    • 1
  1. 1.Department of Biostatistics and Computational BiologyDana-Farber Cancer Institute/Harvard School of Public HealthBostonUSA
  2. 2.Department of Bioinformatics, School of Life Science and TechnologyTongji UniversityShanghaiChina

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