Metadata-Version: 1.1
Name: moca
Version: 0.2.7
Summary: Tool for motif conservation analysis
Home-page: https://github.com/saketkc/moca
Author: Saket Choudhary
Author-email: saketkc@gmail.com
License: ISC
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
        ------------
        
        Requirements
        ~~~~~~~~~~~~
        
        * bedtools>=2.25.0
        * biopython>=1.66
        * pandas>=0.18
        * scipy>=0.17
        * statsmodels>=0.6
        * pybigwig>=0.2.8
        * seaborn>=0.7.0
        
        Using Conda
        ~~~~~~~~~~~
        ``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 .
        
        Yes we mix pip and conda.
        Using pip
        ~~~~~~~~~
        
        ::
           $ pip install moca
        
        
        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
           :width: 50%
        
        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.
        
        
        A sample configuration file is available: `tests/data/application.cfg`
        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
        =======
        
        0.2.4 (2016-05-29)
        ------------------
        
        * Cleaned up unused scripts under scripts directory
        * Add configuration file example
        
        
        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.
        
Keywords: moca
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: ISC License (ISCL)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
