moca 0.2.5

Tool for motif conservation analysis

MoCA: Tool for MOtif Conservation Analysis

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).

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

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.

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.