Tool for motif conservation analysis
Project description
MoCA: Tool for MOtif Conservation Analysis
Python rewrite of MoCA0.1.0
LICENSE
ISC
API Documentation
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.
Project details
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