Tool for motif conservation analysis
Project description
==========================================
MoCA: Tool for MOtif Conservation Analysis
==========================================
.. image:: https://img.shields.io/pypi/v/moca.svg
:target: https://testpypi.python.org/pypi/moca/0.1.0
.. image:: https://img.shields.io/travis/saketkc/moca.svg
:target: https://travis-ci.org/saketkc/moca
.. image:: https://coveralls.io/repos/github/saketkc/moca/badge.svg?branch=master
:target: https://coveralls.io/github/saketkc/moca?branch=master
.. image:: https://landscape.io/github/saketkc/moca/master/landscape.svg?style=flat
:target: https://landscape.io/github/saketkc/moca/master
.. image:: https://requires.io/github/saketkc/moca/requirements.svg?branch=master
:target: https://requires.io/github/saketkc/moca/requirements/?branch=master
Python rewrite of `MoCA0.1.0`_
LICENSE
-------
ISC
API Documentation
-------------
http://saketkc.github.io/moca/
Installation
------------
``moca`` is most compatible with the `conda`_ environment.
::
$ git clone https://github.com:saketkc/moca.git
$ cd moca
$ conda create env -f environment.yml python=2.7
$ source activate mocatest
$ pip install .
A sample configuration file is available: `tests/data/application.cfg`
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
-----
::
$ mocacli --help
Usage: mocacli [OPTIONS]
Run moca
Options:
-i, --bedfile TEXT Bed file input [required]
-o, --oc TEXT Output Directory
-c, --configuration TEXT Configuration file [required]
--flank-seq INTEGER Flanking sequence length [required]
--flank-motif INTEGER Length of sequence flanking motif [required]
-g, -gb, --genome-build TEXT Key denoting genome build to use in
configuration file [required]
--help Show this message and exit.
Example
-------
::
$ mocacli -i tests/data/ENCFF002CDP.ctcf.bed\
-g hg19
-c tests/data/application.cfg\
-o output_dir
.. image:: http://www.saket-choudhary.me/moca/_static/img/ENCFF002CEL.png
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
=======
History
=======
0.2.3 (2016-05-29)
* Include package_dir in setup.py
* Include requirements.txt in MANIFEST
0.2.0 (2016-05-29)
------------------
* First release on PyPI.
MoCA: Tool for MOtif Conservation Analysis
==========================================
.. image:: https://img.shields.io/pypi/v/moca.svg
:target: https://testpypi.python.org/pypi/moca/0.1.0
.. image:: https://img.shields.io/travis/saketkc/moca.svg
:target: https://travis-ci.org/saketkc/moca
.. image:: https://coveralls.io/repos/github/saketkc/moca/badge.svg?branch=master
:target: https://coveralls.io/github/saketkc/moca?branch=master
.. image:: https://landscape.io/github/saketkc/moca/master/landscape.svg?style=flat
:target: https://landscape.io/github/saketkc/moca/master
.. image:: https://requires.io/github/saketkc/moca/requirements.svg?branch=master
:target: https://requires.io/github/saketkc/moca/requirements/?branch=master
Python rewrite of `MoCA0.1.0`_
LICENSE
-------
ISC
API Documentation
-------------
http://saketkc.github.io/moca/
Installation
------------
``moca`` is most compatible with the `conda`_ environment.
::
$ git clone https://github.com:saketkc/moca.git
$ cd moca
$ conda create env -f environment.yml python=2.7
$ source activate mocatest
$ pip install .
A sample configuration file is available: `tests/data/application.cfg`
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
-----
::
$ mocacli --help
Usage: mocacli [OPTIONS]
Run moca
Options:
-i, --bedfile TEXT Bed file input [required]
-o, --oc TEXT Output Directory
-c, --configuration TEXT Configuration file [required]
--flank-seq INTEGER Flanking sequence length [required]
--flank-motif INTEGER Length of sequence flanking motif [required]
-g, -gb, --genome-build TEXT Key denoting genome build to use in
configuration file [required]
--help Show this message and exit.
Example
-------
::
$ mocacli -i tests/data/ENCFF002CDP.ctcf.bed\
-g hg19
-c tests/data/application.cfg\
-o output_dir
.. image:: http://www.saket-choudhary.me/moca/_static/img/ENCFF002CEL.png
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
=======
History
=======
0.2.3 (2016-05-29)
* Include package_dir in setup.py
* Include requirements.txt in MANIFEST
0.2.0 (2016-05-29)
------------------
* First release on PyPI.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
moca-0.2.3.tar.gz
(47.9 kB
view hashes)
Built Distribution
moca-0.2.3-py2.7.egg
(79.0 kB
view hashes)