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Using MACS to Identify Peaks from ChIP‐Seq Data

Year: 2011

Type: article

Abstract: Model-based Analysis of ChIP-Seq (MACS) is a command-line tool designed by X. Shirley Liu and colleagues to analyze data generated by ChIP-Seq experiments in eukaryotes, especially mammals. MACS can be used to identify transcription factor binding sites and histone modification-enriched regions if the ChIP-Seq data, with or without control samples, are given. This unit describes two basic protocols that provide detailed information on how to use MACS to identify either the binding sites of a transcription factor or the enriched regions of a histone modification with broad peaks. Furthermore, the basic ideas for the MACS algorithm and its appropriate usage are discussed.

Source: Current Protocols in Bioinformatics

DOI: 10.1002/0471250953.bi0214s34

Authors: Jianxing Feng, Tao Liu, Yong Zhang

Institutions: Tongji University, Harvard University, Dana-Farber Cancer Institute, Dana-Farber/Harvard Cancer Center

Language: English

Topic: Genomics and Chromatin Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Human Genome Research Institute, National Institute of Diabetes and Digestive and Kidney Diseases