get_sssom_df

pyobo.get_sssom_df(prefix, *, predicate_id='oboinowl:hasDbXref', justification='sempav:UnspecifiedMatching', **kwargs)[source]

Get xrefs from a source as an SSSOM dataframe.

Parameters:

prefix (str) – The ontology to look in for xrefs
predicate_id (str) – The predicate used in the SSSOM document. By default, ontologies don’t typically ascribe semantics to xrefs so oboinowl:hasDbXref is used
justification (str) – The justification for the mapping. By default, ontologies don’t typically ascribe semantics, so this is left with sempav:UnspecifiedMatching

Return type:

DataFrame

Returns:

A SSSOM-compliant dataframe of xrefs

For example, if you want to get UMLS as an SSSOM dataframe, you can do

>>> import pyobo
>>> df = pyobo.get_sssom_df("umls")
>>> df.to_csv("umls.sssom.tsv", sep="\t", index=False)

Note

This assumes the Bioregistry as the prefix map