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Identifying ChIP-seq enrichment using MACS

Nature Protocols volume 7, pages 1728–1740 (2012)Cite this article

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Abstract

Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.

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Figure 1: Workflow of MACS 1.4.2.
Figure 2: Peak model built by MACS using the FoxA1 data set.
Figure 3: IGV visualization of MACS results using the FoxA1 data set.
Figure 4: IGV visualization of MACS results using the University of Washington H3K4me3 data set.
Figure 5: IGV visualization of MACS results using the Broad Institute H3K36me3 data set.

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Acknowledgements

This project was supported by the National Natural Science Foundation of China (31028011 and 31071114); the National Basic Research Program of China (973 Program: 2010CB944904 and 2011CB965104); US National Institutes of Health grant HG4069; and the Excellent Young Teachers Program of Tongji University (2010KJ041).

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Author notes

  1. Jianxing Feng and Tao Liu: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai, China

    Jianxing Feng, Bo Qin & Yong Zhang

  2. Department of Biostatistics and Computational Biology, Harvard School of Public Health, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Tao Liu & Xiaole Shirley Liu

Authors
  1. Jianxing Feng
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  2. Tao Liu
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  3. Bo Qin
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Contributions

Y.Z., T.L. and X.S.L. developed the original MACS algorithm. T.L. developed the current version of the MACS program. J.F. and B.Q. performed the data analysis. J.F., T.L. and X.S.L. wrote the initial manuscript. All authors contributed to the discussion and writing of the final manuscript.

Corresponding authors

Correspondence to Yong Zhang or Xiaole Shirley Liu.

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Feng, J., Liu, T., Qin, B. et al. Identifying ChIP-seq enrichment using MACS. Nat Protoc 7, 1728–1740 (2012). https://doi.org/10.1038/nprot.2012.101

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