Metadata-Version: 2.1
Name: MACS3
Version: 3.0.0a7
Summary: Model Based Analysis for ChIP-Seq data
Home-page: http://github.com/macs3-project/MACS/
Author: Tao Liu
Author-email: vladimir.liu@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Cython
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# MACS: Model-based Analysis for ChIP-Seq

![Status](https://img.shields.io/pypi/status/macs3.svg) ![License](https://img.shields.io/github/license/macs3-project/MACS) ![Programming languages](https://img.shields.io/github/languages/top/macs3-project/MACS) ![CI x64](https://github.com/macs3-project/MACS/workflows/CI%20x64/badge.svg) ![CI non x64](https://github.com/macs3-project/MACS/workflows/CI%20non%20x64,%20python%203.7/badge.svg)

[![PyPI download](https://img.shields.io/pypi/dm/macs3?label=pypi%20downloads)](https://pypistats.org/packages/macs3) [![Bioconda download](https://img.shields.io/conda/dn/bioconda/macs3?label=bioconda%20downloads)](https://anaconda.org/bioconda/macs3)

Latest Release:
* Github: [![Github Release](https://img.shields.io/github/v/release/macs3-project/MACS)](https://github.com/macs3-project/MACS/releases)
* PyPI: [![PyPI Release](https://img.shields.io/pypi/v/macs3.svg) ![PyPI Python Version](https://img.shields.io/pypi/pyversions/MACS3) ![PyPI Format](https://img.shields.io/pypi/format/macs3)](https://pypi.org/project/macs3/)
* Bioconda: [![Bioconda Release](https://img.shields.io/conda/v/bioconda/macs3) ![Bioconda Platform](https://img.shields.io/conda/pn/bioconda/macs3)](https://anaconda.org/bioconda/macs3)
* Debian Med: [![Debian Stable](https://img.shields.io/debian/v/macs/stable?label=debian%20stable)](https://packages.debian.org/stable/macs) [![Debian Unstable](https://img.shields.io/debian/v/macs/sid?label=debian%20sid)](https://packages.debian.org/sid/macs)

## Introduction

With the improvement of sequencing techniques, chromatin
immunoprecipitation followed by high throughput sequencing (ChIP-Seq)
is getting popular to study genome-wide protein-DNA interactions. To
address the lack of powerful ChIP-Seq analysis method, we presented
the **M**odel-based **A**nalysis of **C**hIP-**S**eq (MACS), for
identifying transcript factor binding sites. MACS captures the
influence of genome complexity to evaluate the significance of
enriched ChIP regions and MACS improves the spatial resolution of
binding sites through combining the information of both sequencing tag
position and orientation. MACS can be easily used for ChIP-Seq data
alone, or with a control sample with the increase of
specificity. Moreover, as a general peak-caller, MACS can also be
applied to any "DNA enrichment assays" if the question to be asked is
simply: *where we can find significant reads coverage than the random
background*.

**Please note that current MACS3 is still in alpha stage. However, we
utilize Github Action to implement the CI (Continous Integration) to
make sure that the main branch passes unit testing on certain
functions and subcommands to reproduce the correct outputs. We will
add more new features in the future.**

## Recent Changes for MACS (3.0.0a7)

### 3.0.0a7

	* New features:

	1) Speed/memory optimization.  Use the cykhash to replace python
	dictionary. Use buffer (10MB) to read and parse input file (not
	available for BAM file parser). And many optimization tweaks.

	2) Code cleanup. Reorganize source codes.

	3) Unit testing.

	4) R wrappers for MACS -- MACSr

	5) Switch to Github Action for CI, support multi-arch testing
	including x64, armv7, aarch64, s390x and ppc64le.

	6) MACS tag-shifting model has been refined. Now it will use a
	naive peak calling approach to find ALL possible paired peaks at +
	and - strand, then use all of them to calculate the
	cross-correlation. (a related bug has been fix #442)

	7) Call variants in peak regions directly from BAM files. The 
	function was originally developed under code name SAPPER. Now 
	SAPPER has been merged into MACS. Also, `simde` has been added as 
	a submodule in order to support fermi-lite library under non-x64 
	architectures.

	8) BAI index and random access to BAM file now is supported. #449
	And user can use original BAM file (instead of the subset of BAM
	file as in SAPPER) in the `callvar` command. 

	9) Support of Python > 3.10 #497 #498

	* Other fixes:

    1) Missing header line while no peaks can be called #501 #502

## Install

The common way to install MACS is through
[PYPI](https://pypi.org/project/macs3/)) or
[conda](https://anaconda.org/bioconda/macs3). Please check the
[INSTALL](./docs/INSTALL.md) document for detail.

MACS3 has been tested in CI for every push and PR in the following
architectures:

 * x86_64
 * aarch64
 * armv7
 * ppc64le
 * s390x 

## Usage

Example for regular peak calling on TF ChIP-seq:

`macs3 callpeak -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01`

Example for broad peak calling on Histone Mark ChIP-seq:

`macs3 callpeak -t ChIP.bam -c Control.bam --broad -g hs --broad-cutoff 0.1`

Example for peak calling on ATAC-seq (paired-end mode):

`macs3 callpeak -f BAMPE -t ATAC.bam -g hs -n test -B -q 0.01`

There are currently twelve functions available in MAC3 serving as
sub-commands. Please click on the link to see the detail description
of the subcommands.

Subcommand | Description
-----------|----------
[`callpeak`](./docs/callpeak.md) | Main MACS3 Function to call peaks from alignment results.
[`bdgpeakcall`](./docs/bdgpeakcall.md) | Call peaks from bedGraph output.
[`bdgbroadcall`](./docs/bdgbroadcall.md) | Call broad peaks from bedGraph output.
[`bdgcmp`](./docs/bdgcmp.md) | Comparing two signal tracks in bedGraph format.
[`bdgopt`](./docs/bdgopt.md) | Operate the score column of bedGraph file.
[`cmbreps`](./docs/cmbreps.md) | Combine BEDGraphs of scores from replicates.
[`bdgdiff`](./docs/bdgdiff.md) | Differential peak detection based on paired four bedGraph files.
[`filterdup`](./docs/filterdup.md) | Remove duplicate reads, then save in BED/BEDPE format.
[`predictd`](./docs/predictd.md) | Predict d or fragment size from alignment results.
[`pileup`](./docs/pileup.md) | Pileup aligned reads (single-end) or fragments (paired-end)
[`randsample`](./docs/randsample.md) | Randomly choose a number/percentage of total reads.
[`refinepeak`](./docs/refinepeak.md) | Take raw reads alignment, refine peak summits.
[`callvar`](./docs/callvar.md) | Call variants in given peak regions from the alignment BAM files.


For advanced usage, for example, to run `macs3` in a modular way,
please read the [advanced usage](./docs/advanced_usage.md). There is a
[Q&A](./docs/qa.md) document where we collected some common questions
from users.

## Contribute

Please read our [CODE OF CONDUCT](./CODE_OF_CONDUCT.md) and
[How to contribute](./CONTRIBUTING.md) documents. If you have any
questions, suggestion/ideas, or just want to have conversions with
developers and other users in the community, we recommand you use the
[MACS Discussions](https://github.com/macs3-project/MACS/discussions)
instead of posting to our
[Issues](https://github.com/macs3-project/MACS/issues) page.

## Ackowledgement

MACS3 project is sponsored by
[CZI EOSS](https://chanzuckerberg.com/eoss/). And we particularly want
to thank the user community for their supports, feedbacks and
contributions over the years.

## Other useful links

 * [Cistrome](http://cistrome.org/)
 * [bedTools](http://code.google.com/p/bedtools/)
 * [UCSC toolkits](http://hgdownload.cse.ucsc.edu/admin/exe/)
 * [deepTools](https://github.com/deeptools/deepTools/)



