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GO enrichment with python -- pandas meets networkx

Project description

goenrich

https://readthedocs.org/projects/goenrich/badge/?version=latest https://travis-ci.org/jdrudolph/goenrich.svg?branch=master

Convenient GO enrichments from python. For use in python projects.

  1. Builds the GO-ontology graph
  2. Propagates GO-annotations up the graph
  3. Performs enrichment test for all categories
  4. Performs multiple testing correction
  5. Allows for export to pandas for processing and graphviz for visualization

Installation

Install package from pypi and download ontology and needed annotations.
pip install goenrich
mkdir db
# Ontology
wget http://purl.obolibrary.org/obo/go/go-basic.obo -O db/go-basic.obo
# UniprotACC
wget http://geneontology.org/gene-associations/goa_human.gaf.gz -O db/gene_association.goa_human.gaf.gz
# Yeast SGD
wget http://downloads.yeastgenome.org/curation/literature/gene_association.sgd.gz -O db/gene_association.sgd.gz
# Entrez GeneID
wget ftp://ftp.ncbi.nlm.nih.gov/gene/DATA/gene2go.gz -O db/gene2go.gz

Run GO enrichment

import goenrich

# build the ontology
O = goenrich.obo.ontology('db/go-basic.obo')

# use all entrez geneid associations form gene2go as background
# use annot = goenrich.read.goa('db/gene_association.goa_human.gaf.gz') for uniprot
# use annot = goenrich.read.sgd('db/gene_association.sgd.gz') for yeast
gene2go = goenrich.read.gene2go('db/gene2go.gz')
# use values = {k: set(v) for k,v in annot.groupby('go_id')['db_object_symbol']} for uniprot/yeast
values = {k: set(v) for k,v in gene2go.groupby('GO_ID')['GeneID']}

# propagate the background through the ontology
background_attribute = 'gene2go'
goenrich.enrich.propagate(O, values, background_attribute)

# extract some list of entries as example query
# use query = annot['db_object_symbol'].unique()[:20]
query = gene2go['GeneID'].unique()[:20]

# for additional export to graphviz just specify the gvfile argument
# the show argument keeps the graph reasonably small
df = goenrich.enrich.analyze(O, query, background_attribute, gvfile='test.dot')

# generate html
df.dropna().head().to_html('example.html')

# call to graphviz
import subprocess
subprocess.check_call(['dot', '-Tpng', 'test.dot', '-o', 'test.png'])

Generate png image using graphviz:

dot -Tpng example.dot > example.png

or directly from python:

import subprocess
subprocess.check_call(['dot', '-Tpng', 'example.dot', '-o', 'example.png'])
https://cloud.githubusercontent.com/assets/2606663/8525018/cad3a288-23fe-11e5-813c-bd205a47eed8.png

Check the documentation for all available parameters

Licence & Contributors

This work is licenced under the MIT licence

Contributions are welcome!

Special thanks

  • @lukauskas for implementing i/o support for file-like objects.
  • @zfrenchee for fixing a bug in the calculation of the test statistic.
  • @pommy1 for implementing support for networkx >= 2.0.0.

Building the documentation

sphinx-apidoc -f -o docs goenrich goenrich/tests

Project details


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