semmed-biolink

normalization of sememd db to biolink model

Steps

• Run download_convert.sh to download SemMedDB and related files and convert mysql dump to csv
• Run the ipynbs in order

01-initial_data_clean.ipynb

• Expand predicates with OR operations into individual predicates
• Convert cuis that are entrez ids into cuis
• Change neg props to the same prop with a negative flag
• Make a separate nodes table

02-normalize_node_types_to_biolink.ipynb

• For each node, get the UMLS semantic type for each umls cui
• Map umls semantic types to biolink node types (blm_to_umls_nodes.json)
• Nodes with no matching type are removed

03-filter_nodes_edges.ipynb

• Remove edges with nodes with no umls type or label
• Remove the following predicates: ['compared_with', 'higher_than', 'lower_than', 'different_from', 'different_than', 'same_as','OCCURS_IN', 'PROCESS_OF', 'DIAGNOSES', 'METHOD_OF', 'USES','AUGMENTS', 'ADMINISTERED_TO', 'COMPLICATES']

04-filter_biolink

• Filter specific domain and ranges for: CAUSES, LOCATION_OF, TREATS, PREDISPOSES, PREVENTS
• rename 'converts_to' edge to 'derives_into'
• rename 'isa' edge to 'subclass of'
• rename 'disrupts' edge to 'affects'
• rename 'associated_with' edge to 'related_to'
• rename 'STIMULATES' edge to 'positively_regulates'
• rename 'INHIBITS' edge to 'negatively_regulates'
• associated_with/related_to edges with domain: gene, range: disease; rename to gene_associated_with_condition

05-xrefs Get xrefs from a variety of sources

• Drugs: UMLS has mesh xrefs. From mesh, we can get UNII and CAS. From UNII_FDA, we can get inchikeys (lookup using cas or unii). From chembl, we can get chembl IDs from the inchikeys So: UMLS -> mesh -> unii/cas -> inchikey -> chembl insane, I know.
• Anatomy: uberon has umls xrefs
• disease: DO has umls, umls has NCI, ICD10PCS, SNOMEDCT_US, ICD10CM, OMIM
• proteins: umls has uniprot xrefs
• biological_process_or_activity/activity_and_behavior: umls has GO
• gene: umls has HGNC and OMIM

06-neo4j

• reformat for neo4j import

Result

Start:
20,620,113 edges
268,918 nodes
32 predicates
15 node types

End:
14,033,126 edges
165,658 nodes
18 predicates
13 node types