mapping gene ids with mygene

Mapping gene ids is one of the routine jobs for bioinformatics. I was aware of several ways to do it including Biomart.

Update on 10/30/14, a mygene bioconductor package is online http://bioconductor.org/packages/release/bioc/html/mygene.html

Recently I got to know mygene, a python wrapper for the mygene.info services to map gene ids.
I found it very handy to convert gene ids.  see a gist below.

	#! /usr/bin/env python
	# ID mapping using mygene
	# https://pypi.python.org/pypi/mygene
	# http://nbviewer.ipython.org/gist/newgene/6771106
	# http://mygene-py.readthedocs.org/en/latest/
	# 08/30/14
	__author__ = 'tommy'
	import mygene
	import fileinput
	import sys
	mg = mygene.MyGeneInfo()
	# mapping gene symbols to Entrez gene ids and Ensemble gene ids.
	# fileinput will loop through all the lines in the input specified as file names given in command-line arguments,
	# or the standard input if no arguments are provided.
	# build a list from an input file with one gene name in each line
	def get_gene_symbols():
	gene_symbols = []
	for line in fileinput.input():
	gene_symbol = line.strip() # assume each line contains only one gene symbol
	gene_symbols.append(gene_symbol)
	fileinput.close()
	return gene_symbols
	Entrez_ids = mg.querymany(get_gene_symbols(), scopes='symbol', fields='entrezgene, ensembl.gene', species='human',
	as_dataframe=True, verbose=False)
	# set as_dataframe to True will return a pandas dataframe object, verbose=False suppress the messages like "finished".
	# Entrez_ids.to_csv(sys.stdout, sep="\t") # write the dataframe to stdout, but will not have NaNs on the screen
	# if no matches were found
	sys.stdout.write(Entrez_ids.to_string()) # sys.stdout.write() expects the character buffer object
	# Entrez_ids.to_csv("Entrez_ids.txt", sep="\t") # write the pandas dataframe to csv

view raw geneSymbol2Entrez.py hosted with ❤ by GitHub

To use it,  cat input.txt | python geneSymbol2Entrez.py > output.txt
or python geneSymbol2Entrez.py input.txt > output.txt  where input.txt contains one gene name in each line. pretty neat!