|Alternative names||Model-based Analysis for ChIP-Seq, MACS2, macs2|
|Interface||Command line interface|
|Restrictions to use||None|
|Input data||A tag file, a treatment file.|
|Output data||A file with information about called peaks, peak locations, peak summits locations, negative peaks, a script to produce a PDF image, a file that can be viewed through the UCSC genome browser, a diagnosis report and an optional file for the subpeaks option.|
|Programming languages||C, Python|
|License||BSD 3-clause “New” or “Revised” License|
|Requirements||Numpy, GCC, Cython|
Add your version
- Issues: https://github.com/taoliu/MACS/
- person_outline Wei Li <>
- person_outline Tao Liu <>
Publication for Model-based Analysis for ChIP-Seq
MACS IN pipelines(45)
[…] external chip-seq data for h4r3me2s (geo accession gse37604)  were aligned to the mm9 genome assembly using bowtie2 v2.1.0  and uniquely aligned reads were extracted for peak detection using macs2. to identify repeats enriched for h4r3me2s, the number of chip-seq peaks overlapping each repeat class were compared with a random control where peaks were shuffled (using bedtools) […]
[…] only uniquely aligned and properly paired read tags with mapping score >15 were retained for subsequent analysis. (supplementary tables s13 and s14). methylated regions were identified with macs269. regions obtained from different samples were merged by the bedtools suite66 and statistical analyses were performed on the matrix of read counts over all regions. data were normalized using […]
[…] to the mouse genome (mm10) with bowtie (version 1.0.0 ) and displayed on a local mirror of ucsc genome browser as coverage. islands of h3k27ac- and h3k4me2-enrichment were identified using macs2 (version 126.96.36.19930712 ). manorm, software designed for the quantitative comparison of chip-seq datasets , was applied to compare the enrichment profile of h3k27ac or h3k4me2 […]
[…] aligner . the quality metrics of chip-seq libraries (additional file 1: table s1) were assessed by phantompeakqualtools software (https://www.encodeproject.org/software/phantompeakqualtools/). macs2  algorithm with nucleosome-optimized parameters (−-shift 37 --extsize 73) was applied to call both broad and narrow peaks from the pooled data. public sequencing data on mnase-treated input […]
[…] reads were mapped against gcrh37 with bowtie 2 (version 2.2.9, -n 0 -l 32 --fr --local --maxins 1000 --minins 0). post-processing was done using sam tools (version 1.3.1). peaks were called using macs2 (version 2.1.1) with default parameters for human. afterwards a diffbind (version 2.0.6 with deseq2 1.12.4) analysis was performed to detect differentially bound regions for the control […]
I think it's important to understand that it is designed for point-source data, and for that it works perfectly (that's why I gave maximum rating, despite the constraints described in the following section, which I don't see as a fault - it's really not intended for the tasks below.) Numerous tests show (even a paper published by the MACS authors) that when it comes to diffuse enrichments, most notably, ChIP-seq with histone marks, then MACS fails to identify the peaks correctly. Usually it manages to detect some parts of it, some local summits within the dispersed signal, if it detects something at all. Although in the literature it is used for various datasets, including histone marks, ATAC-seq, MeDIP-seq etc., I wouldn't recommend it for detecting other enrichments than point-source peaks. There are much superior tools out there for diffuse signals (like SICER). I have to mention though that maybe H3K4me3 is an exception, it is a very "TF-like" histone mark, with sharp, clear, high enrichments, and for that mark only MACS might be acceptable. But I wouldn't trust it for any other HMs (and I've been working with ChIP-seq data of all histone marks you can imagine for ~10 years). I would also take the results of MeDIP-seq. ATAC-seq and similar data with a grain of salt if it was processed with MACS, because while it can certainly detect some enrichment, not all ofthem can be considered point-source, many methylated regions, open chromatin etc. are way broader than that.
With that said, I think it's a great tool for what it was designed.
Be aware that the MACS website is still saying that the newest version is version 1.4.2, which is not true, it has long been superceded by the major version 2, which you can find on GitHub (at the time of writing this review the latest stable version is 2.1.0).
Easy to install and use.