tbrittoborges / goenrich

GO enrichment with python -- pandas meets networkx

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

goenrich README

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/gene_association.goa_ref_human.gz -O db/gene_association.goa_ref_human.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_ref_human.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

This work is licenced under the MIT licence

Contributions are welcome!

Building the documentation

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

About

GO enrichment with python -- pandas meets networkx


Languages

Language:Python 100.0%