title: Using MACS to identify peaks from ChIP-Seq data.
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.
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai, China.
authors.forename: Jianxing
authors.initials: J
authors.lastname: Feng
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts.
authors.forename: Tao
authors.initials: T
authors.lastname: Liu
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000378:metabolism*
chemical_list: D014157:Transcription Factors