MoCA: Tool for MOtif Conservation Analysis

June 23, 2022 · View on GitHub

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

MoCA: Tool for MOtif Conservation Analysis

========================================== MoCA: Tool for MOtif Conservation Analysis

LICENSE

Installation

Workflow

Usage