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https://github.com/saketkc/moca
:m: Tool for motif conservation analysis
https://github.com/saketkc/moca
bioinformatics chip-seq motif-discovery transcription-factor-binding transcription-factors
Last synced: 18 days ago
JSON representation
:m: Tool for motif conservation analysis
- Host: GitHub
- URL: https://github.com/saketkc/moca
- Owner: saketkc
- License: isc
- Created: 2016-02-02T02:57:58.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2022-06-23T19:58:45.000Z (over 2 years ago)
- Last Synced: 2024-11-18T09:43:42.509Z (about 1 month ago)
- Topics: bioinformatics, chip-seq, motif-discovery, transcription-factor-binding, transcription-factors
- Language: PostScript
- Homepage: http://saket-choudhary.me/moca
- Size: 31.5 MB
- Stars: 9
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- Changelog: HISTORY.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
README
==========================================
MoCA: Tool for MOtif Conservation Analysis
==========================================
.. image:: https://img.shields.io/pypi/v/moca.svg
:target: https://pypi.python.org/pypi/moca/
.. image:: https://img.shields.io/travis/saketkc/moca.svg
:target: https://travis-ci.org/saketkc/moca
.. image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg
:target: https://bioconda.github.io/recipes/moca/README.html
.. image:: https://coveralls.io/repos/github/saketkc/moca/badge.svg?branch=master
:target: https://coveralls.io/github/saketkc/moca?branch=master
.. image:: https://zenodo.org/badge/50889586.svg
:target: https://zenodo.org/badge/latestdoi/50889586
LICENSE
-------
ISC
Installation
------------
Requirements
~~~~~~~~~~~~
* pybedtools
* biopython
* pandas
* scipy
* statsmodels
* pybigwig
* seaborn
* MEME==4.10.2
NOTE: MoCA also relies on `fasta-shuffle-letters` that was introduced in MEME `4.11.0`
hence if you are using `4.10.2` make sure the `fasta-shuffle-letters` is the updated one.
For a sample script see `travis/install_meme.sh`
Using Conda
~~~~~~~~~~~
``moca`` is most compatible with the `conda`_ environment.
::
$ conda config --add channels bioconda
$ conda install moca
Using pip
~~~~~~~~~
::
$ pip install moca
For development
~~~~~~~~~~~~~~~
::
$ git clone https://github.com:saketkc/moca.git
$ cd moca
$ conda env create -f environment.yml python=2.7
$ source activate mocadev
$ python setup.py install
Workflow
--------
MoCA makes use of PhyloP/PhastCons/GERP scores to assess the quality of a
motif, the hypothesis being a 'true motif' would evolve slower as compared
to its surrounding(flanking sequences).
.. image:: https://raw.githubusercontent.com/saketkc/moca_web/master/docs/abstract/workflow.png
Usage
-----
::
$ moca
Usage: moca [OPTIONS] COMMAND [ARGS]...
moca: Motif Conservation Analysis
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
find_motifs Run meme to locate motifs and create...
plot Create stacked conservation plots
Motif analysis using MEME
~~~~~~~~~~~~~~~~~~~~~~~~~
MoCA can perform motif analysis for you given a bedfile containing
ChIP-Seq peaks.
Genome builds and MEME binary locations are specified through a configuraton file.
A sample configuration file is available: `tests/data/application.cfg` and should be
self-explanatory.
moca find_motifs
~~~~~~~~~~~~~~~~
::
$ moca find_motifs -h
Usage: moca find_motifs [OPTIONS]
Run meme to locate motifs and create conservation stacked plots
Options:
-i, --bedfile TEXT Bed file input [required]
-o, --oc TEXT Output Directory [required]
-c, --configuration TEXT Configuration file [required]
--slop-length INTEGER Flanking sequence length [required]
--flank-motif INTEGER Length of sequence flanking motif [required]
--n-motif INTEGER Number of motifs
-t, --cores INTEGER Number of parallel MEME jobs [required]
-g, -gb, --genome-build TEXT Key denoting genome build to use in
configuration file [required]
--show-progress Print progress
-h, --help Show this message and exit.
moca plot
~~~~~~~~~
::
$ moca plot -h
Usage: moca plot [OPTIONS]
Create stacked conservation plots
Options:
--meme-dir, --meme_dir TEXT MEME output directory [required]
--centrimo-dir, --centrimo_dir TEXT
Centrimo output directory [required]
--fimo-dir-sample, --fimo_dir_sample TEXT
Sample fimo.txt [required]
--fimo-dir-control, --fimo_dir_control TEXT
Control fimo.txt [required]
--name TEXT Plot title
--flank-motif INTEGER Length of sequence flanking motif
[required]
--motif INTEGER Motif number
-o, --oc TEXT Output Directory [required]
-c, --configuration TEXT Configuration file [required]
--show-progress Print progress
-g, -gb, --genome-build TEXT Key denoting genome build to use in
configuration file [required]
-h, --help Show this message and exit.
Example
-------
Most users will require using the command line version only:
::
$ moca find_motifs -i encode_test_data/ENCFF002DAR.bed\
-c tests/data/application.cfg -g hg19 --show-progress
Creating plots if you already have run MEME and Centrimo:
::
$ moca plot -c tests/data/application.cfg -g hg19\
--meme-dir moca_output/meme_out\
--centrimo-dir moca_output/centrimo_out\
--fimo-dir-sample moca_output/meme_out/fimo_out_1\
--fimo-dir-control moca_output/meme_out/fimo_random_1\
--name ENCODEID
.. image:: http://www.saket-choudhary.me/moca/_static/img/ENCFF002CEL.png
There is also a structured API available,
however it might be missing examples and documentation at places.
API Documentation
-----------------
http://saketkc.github.io/moca/
Tests
-----
``moca`` is mostly extensively tested. See `code-coverage`_.
Run tests locally
::
$ ./runtests.sh
Credits
---------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _`MoCA0.1.0`: https://github.com/saketkc/moca_web
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
.. _`conda`: http://conda.pydata.org/docs/using/using.html
.. _`code-coverage`: https://coveralls.io/github/saketkc/moca?branch=master