Motivation: It seems to be a recurrent question on Ensembl website (http://www.ensembl.org/Help/Faq?id=125) so let us see how to solve the following question using BioServices:
How do I convert IDs? I have ENSG... IDs and I would like HGNC symbols and EntrezGene IDs along with matching Affymetrix platform HC G110 probes.The solution from Ensembl web page is to use BioMart.
Using a list of ENSG symbols (e.g., ENSG00000162367 and ENSG00000187048).
The instructions from the Ensembl web page is to use the BioMart web page as follows. We will enter in the list of genes and export IDs from multiple databases. You need to fill the input boxes:
Here below, we will use the programmatic approach using BioServices
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from bioservices import biomart
#reload(biomart)
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s = biomart.BioMart()
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# First, we need to know the datasets of ensembl database
# From the Ensembl web page, the database is "Ensembl genes" but it looks like "ensembl" is enough
datasets = s.datasets("ensembl")
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# From the list of datasets, the suggested name is "Homo sapiens genes"
# Can we find it ?
for d in datasets:
if 'sapiens' in d.lower():
print d
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# well again it is a bit different from the web page suggestion but it should be that one we are interested in ;-)
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#What are the filters ?
filters = s.filters('hsapiens_gene_ensembl')
filters is a dictionary with lots of keys such as ensembl_gene_id. Each filter has some values/options to be provided
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filters['ensembl_gene_id']
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Similary attributes have to be provided. What are they ? Check out the content of attributes.keys()
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attributes = s.attributes('hsapiens_gene_ensembl')
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# Let us first build the XML request
# Note that the list of identifiers should be actually a string separated by commas
s.new_query()
s.add_dataset_to_xml('hsapiens_gene_ensembl')
s.add_attribute_to_xml('affy_hc_g110')
s.add_attribute_to_xml('entrezgene')
s.add_attribute_to_xml('hgnc_symbol')
s.add_attribute_to_xml('ensembl_gene_id')
s.add_filter_to_xml('ensembl_gene_id', 'ENSG00000162367,ENSG00000187048')
xml = s.get_xml()
print xml
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# now we call the requests itself
res = s.query(xml)
print res
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# We can parse the results using Pandas to have a better rendering and more convenient way of handling the data
import pandas as pd
import StringIO
df = pd.read_csv(StringIO.StringIO(res), sep="\t", header=None)
df.columns=['affyhc_g110', 'entrezgene', 'hgnc_symbol', 'ensembl_gene_id']
df = df.drop_duplicates()
df = df.set_index('ensembl_gene_id')
# df.ix['ENSG00000162367']['hgnc_symbol']
df
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