Using MACS to Identify Peaks from ChIP‐Seq Data

Jianxing Feng1, Tao Liu2, Yong Zhang1

1 School of Life Sciences and Technology, Tongji University, Shanghai, China, 2 Department of Biostatistics and Computational Biology, Dana‐Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 2.14
DOI:  10.1002/0471250953.bi0214s34
Online Posting Date:  June, 2011
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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. Curr. Protoc. Bioinform. 34:2.14.1‐2.14.14. © 2011 by John Wiley & Sons, Inc.

Keywords: MACS; ChIP‐Seq; peak‐calling; cistrome; epigenome

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Running MACS Program to Identify Transcription Factor Binding Sites
  • Basic Protocol 2: Running MACS Program to Profile Histone Modification Status
  • Support Protocol 1: Obtaining and Installing MACS Program
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

  •   FigureFigure 2.14.1 Shifting size model for FoxA1 ChIP‐Seq data. The red curve represents the distribution of locations relative to the midpoints for reads from the forward strand, while the blue curve represents the same for reads from the reverse strand. d is determined as the distance between the summits of red and blue curves, and MACS shifts all reads by d/2 toward the 3′ ends to improve the spatial resolution of inferred TF binding sites. The black curve is drawn based on the locations of shifted reads.
  •   FigureFigure 2.14.2 Visualization of wiggle and BED files for FoxA1 ChIP‐Seq data in Affymetrix IGB. Genome region: chr1: 215,756,000 to 215,757,000.
  •   FigureFigure 2.14.3 Visualization of wiggle and BED files for H3K27me3 ChIP‐Seq data in Affymetrix IGB. Genome region: chr1: 93,627,000 to 93,637,000.

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Literature Cited

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