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1 # MACS: Model-based Analysis for ChIP-Seq
3     
5 [](https://pypistats.org/packages/macs3) [](https://anaconda.org/bioconda/macs3)
7 Latest Release:
8 * Github: [](https://github.com/macs3-project/MACS/releases)
9 * PyPI: [  ](https://pypi.org/project/macs3/)
10 * Bioconda: [ ](https://anaconda.org/bioconda/macs3)
11 * Debian Med: [](https://packages.debian.org/stable/macs) [](https://packages.debian.org/sid/macs)
13 ## Introduction
15 With the improvement of sequencing techniques, chromatin
16 immunoprecipitation followed by high throughput sequencing (ChIP-Seq)
17 is getting popular to study genome-wide protein-DNA interactions. To
18 address the lack of powerful ChIP-Seq analysis method, we presented
19 the **M**odel-based **A**nalysis of **C**hIP-**S**eq (MACS), for
20 identifying transcript factor binding sites. MACS captures the
21 influence of genome complexity to evaluate the significance of
22 enriched ChIP regions and MACS improves the spatial resolution of
23 binding sites through combining the information of both sequencing tag
24 position and orientation. MACS can be easily used for ChIP-Seq data
25 alone, or with a control sample with the increase of
26 specificity. Moreover, as a general peak-caller, MACS can also be
27 applied to any "DNA enrichment assays" if the question to be asked is
28 simply: *where we can find significant reads coverage than the random
29 background*.
31 **Please note that current MACS3 is still in beta stage. However, we
32 utilize Github Action to implement the CI (Continous Integration) to
33 make sure that the main branch passes unit testing on certain
34 functions and subcommands to reproduce the correct outputs. We will
35 add more new features in the future.**
37 ## Recent Changes for MACS (3.0.0b2)
39 ### 3.0.0b2
40 The second beta version of MACS3, with HMMRATAC feature refined.
42 * New features from beta1:
44 1) HMMRATAC module fixes
46 Cutoff analysis function added
47 Description regarding it has been added
49 2) Memory monitoring in the runtime message
51 3) testing for s390x, armv7 and power64le is back. However, we turned off the function to check if the `hmmratac` results from non-x86 architectures are the same as the standard results, because in order to let the testing run, we need to use old python libraries (scipy and sklearn) through the distribution of Debian/Linux bullseye.
53 ## Install
55 The common way to install MACS is through
56 [PYPI](https://pypi.org/project/macs3/)) or
57 [conda](https://anaconda.org/bioconda/macs3). Please check the
58 [INSTALL](./docs/INSTALL.md) document for detail.
60 MACS3 has been tested in CI for every push and PR in the following
61 architectures:
63 * x86_64
64 * aarch64
65 * armv7
66 * ppc64le
67 * s390x
69 ## Usage
71 Example for regular peak calling on TF ChIP-seq:
73 `macs3 callpeak -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01`
75 Example for broad peak calling on Histone Mark ChIP-seq:
77 `macs3 callpeak -t ChIP.bam -c Control.bam --broad -g hs --broad-cutoff 0.1`
79 Example for peak calling on ATAC-seq (paired-end mode):
81 `macs3 callpeak -f BAMPE -t ATAC.bam -g hs -n test -B -q 0.01`
83 There are currently 14 functions available in MACS3 serving as
84 sub-commands. Please click on the link to see the detail description
85 of the subcommands.
87 Subcommand | Description
88 -----------|----------
89 [`callpeak`](./docs/callpeak.md) | Main MACS3 Function to call peaks from alignment results.
90 [`bdgpeakcall`](./docs/bdgpeakcall.md) | Call peaks from bedGraph output.
91 [`bdgbroadcall`](./docs/bdgbroadcall.md) | Call broad peaks from bedGraph output.
92 [`bdgcmp`](./docs/bdgcmp.md) | Comparing two signal tracks in bedGraph format.
93 [`bdgopt`](./docs/bdgopt.md) | Operate the score column of bedGraph file.
94 [`cmbreps`](./docs/cmbreps.md) | Combine BEDGraphs of scores from replicates.
95 [`bdgdiff`](./docs/bdgdiff.md) | Differential peak detection based on paired four bedGraph files.
96 [`filterdup`](./docs/filterdup.md) | Remove duplicate reads, then save in BED/BEDPE format.
97 [`predictd`](./docs/predictd.md) | Predict d or fragment size from alignment results.
98 [`pileup`](./docs/pileup.md) | Pileup aligned reads (single-end) or fragments (paired-end)
99 [`randsample`](./docs/randsample.md) | Randomly choose a number/percentage of total reads.
100 [`refinepeak`](./docs/refinepeak.md) | Take raw reads alignment, refine peak summits.
101 [`callvar`](./docs/callvar.md) | Call variants in given peak regions from the alignment BAM files.
102 [`hmmratac`](./docs/hmmratac.md) | Dedicated peak calling based on Hidden Markov Model for ATAC-seq data.
104 For advanced usage, for example, to run `macs3` in a modular way,
105 please read the [advanced usage](./docs/advanced_usage.md). There is a
106 [Q&A](./docs/qa.md) document where we collected some common questions
107 from users.
109 ## Contribute
111 Please read our [CODE OF CONDUCT](./CODE_OF_CONDUCT.md) and
112 [How to contribute](./CONTRIBUTING.md) documents. If you have any
113 questions, suggestion/ideas, or just want to have conversions with
114 developers and other users in the community, we recommand you use the
115 [MACS Discussions](https://github.com/macs3-project/MACS/discussions)
116 instead of posting to our
117 [Issues](https://github.com/macs3-project/MACS/issues) page.
119 ## Ackowledgement
121 MACS3 project is sponsored by
122 [CZI EOSS](https://chanzuckerberg.com/eoss/). And we particularly want
123 to thank the user community for their supports, feedbacks and
124 contributions over the years.
126 ## Other useful links
128 * [Cistrome](http://cistrome.org/)
129 * [bedTools](http://code.google.com/p/bedtools/)
130 * [UCSC toolkits](http://hgdownload.cse.ucsc.edu/admin/exe/)
131 * [deepTools](https://github.com/deeptools/deepTools/)