def elsevier_unit_tests(query, elsevier_api_key):
user = User(elsevier_api_key=elsevier_api_key)
for result in sciencedirect_search(query, user=user):
print("- %s: %s" %
(str(result["eid"]),
str(result["title"].encode('ascii', errors='ignore').decode())))
def compound_adverse_event_unit_tests(chebi_id, pubchem_cid, umls_api_key):
user = User(umls_api_key=umls_api_key)
pubchem_cid_com = gnomics.objects.compound.Compound(
identifier=str(pubchem_cid),
identifier_type="PubChem CID",
source="PubChem")
print("\nGetting adverse events from PubChem CID (%s):" % pubchem_cid)
for ae in get_adverse_events(pubchem_cid_com):
for iden in ae.identifiers:
print("- %s (%s)" %
(str(iden["identifier"]), iden["identifier_type"]))
chebi_com = gnomics.objects.compound.Compound(identifier=str(chebi_id),
identifier_type="ChEBI ID",
source="ChEBI")
print("\nGetting adverse events from ChEBI ID (%s):" % chebi_id)
start = timeit.timeit()
all_ae = get_adverse_events(chebi_com)
end = timeit.timeit()
print("TIME ELAPSED: %s seconds." % str(end - start))
for ae in all_ae:
for iden in ae.identifiers:
print("- %s (%s)" %
(str(iden["identifier"]), iden["identifier_type"]))
def protein_tissue_unit_tests(uniprot_acc, openphacts_app_id,
openphacts_app_key):
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key)
uniprot_prot = gnomics.objects.protein.Protein(
identifier=uniprot_acc,
identifier_type="UniProt Accession",
source="OpenPHACTS")
print("\nGetting tissue identifiers from UniProt Accession (%s):" %
uniprot_acc)
for tiss in get_tissues(uniprot_prot, user=user):
for iden in tiss.identifiers:
print("- %s (%s) [%s]" % (iden["name"], str(
iden["identifier"]), iden["identifier_type"]))
print("\nGetting tissue expression from UniProt Accession (%s):" %
uniprot_acc)
for key, val in get_tissue_expression(uniprot_prot).items():
print("- %s" % key)
print(" - method: %s" % val["method"])
print(" - type: %s" % val["type"])
print(" - level: %s" % val["level"])
print(" - source: %s" % val["source"])
print(" - technology: %s" % val["technology"])
print(" - assay type: %s" % val["assay_type"])
def meddra_unit_tests(meddra_term, meddra_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
meddra_term_phen = gnomics.objects.phenotype.Phenotype(
identifier=meddra_term, identifier_type="MedDRA Term", source="MedDRA")
print("Getting MedDRA IDs from MedDRA term (%s):" % meddra_term)
for iden in get_meddra_id(meddra_term_phen, user):
print("- " + str(iden))
def hpo_unit_tests(mesh_uid, meddra_id, meddra_term, hpo_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
hpo_phen = gnomics.objects.phenotype.Phenotype(identifier=hpo_id,
identifier_type="HPO ID",
source="UMLS")
print("\nGetting HPO Terms from HPO ID (%s):" % hpo_id)
for iden in get_hpo_term(hpo_phen, user):
print("- " + str(iden))
mesh_phen = gnomics.objects.phenotype.Phenotype(identifier=mesh_uid,
identifier_type="MeSH UID",
source="MeSH")
print("Getting HPO IDs from MeSH UID (%s):" % mesh_uid)
for iden in get_hpo_id(mesh_phen, user):
print("- " + str(iden))
meddra_phen = gnomics.objects.phenotype.Phenotype(
identifier=meddra_id, identifier_type="MedDRA ID", source="MedDRA")
print("\nGetting HPO IDs from MedDRA ID (%s):" % meddra_id)
for iden in get_hpo_id(meddra_phen, user):
print("- " + str(iden))
meddra_term_phen = gnomics.objects.phenotype.Phenotype(
identifier=meddra_term, identifier_type="MedDRA Term", source="MedDRA")
print("\nGetting MedDRA IDs from MedDRA term (%s):" % meddra_term)
for iden in get_hpo_id(meddra_term_phen, user):
print("- " + str(iden))
def springer_unit_tests(query, journal_name, springer_api_key):
user = User(springer_api_key=springer_api_key)
print("\nObtaining information from journal query '%s'...\n" %
str(journal_name))
print(springer_integro_api(journal_name, user=user))
print("Obtaining Springer documents from metadata query '%s'...\n" %
str(query))
for ref in springer_metadata_service(query, user=user):
for iden in ref.identifiers:
print("- %s (%s) [%s]" %
(iden["name"].encode("ascii", errors="ignore").decode(),
iden["identifier"], iden["identifier_type"]))
print("\nObtaining Springer documents from meta query '%s'...\n" %
str(query))
for ref in springer_meta_api_service(query, user=user):
for iden in ref.identifiers:
print("- %s (%s) [%s]" %
(iden["name"].encode("ascii", errors="ignore").decode(),
iden["identifier"], iden["identifier_type"]))
print("\nObtaining Springer documents from open-access query '%s'...\n" %
str(query))
for ref in springer_openaccess_api(query, user=user):
for iden in ref.identifiers:
print("- %s (%s) [%s]" %
(iden["name"].encode("ascii", errors="ignore").decode(),
iden["identifier"], iden["identifier_type"]))
def oclc_unit_tests(isbn, oclc, issn, lccn, oclc_wskey, oclc_wskey_secret,
query):
user = User(oclc_api_key=oclc_wskey)
for result in worldcat_search_api(query, user=user):
for iden in result.identifiers:
print("- %s [%s]" % (iden["identifier"], iden["identifier_type"]))
isbn_ref = gnomics.objects.reference.Reference(identifier=isbn,
identifier_type="ISBN",
language=None,
source="Open Library")
print(classify(isbn_ref))
oclc_ref = gnomics.objects.reference.Reference(
identifier=oclc,
identifier_type="OCLC Control Number",
language=None,
source="Open Library")
print(classify(oclc_ref))
issn_ref = gnomics.objects.reference.Reference(identifier=oclc,
identifier_type="ISSN",
language=None,
source="Open Library")
print(classify(issn_ref))
lccn_ref = gnomics.objects.reference.Reference(identifier=oclc,
identifier_type="LCCN",
language=None,
source="Open Library")
print(classify(lccn_ref))
def umls_unit_tests(omim_disease_id, doid, omim_api_key=None):
if omim_api_key is not None:
print("Creating user...")
user = User(omim_api_key=omim_api_key)
print("User created successfully.\n")
omim_disease = gnomics.objects.disease.Disease(
identifier=str(omim_disease_id),
identifier_type="MIM Number",
source="OMIM")
print("Getting UMLS IDs from MIM Number (%s):" % omim_disease_id)
for sno in get_umls(omim_disease, user=user):
print("- " + str(sno))
doid_dis = gnomics.objects.disease.Disease(identifier=str(doid),
identifier_type="DOID",
source="Disease Ontology")
print("\nGetting UMLS IDs from Disease Ontology ID (%s):" % doid)
for iden in get_umls(doid_dis):
print("- " + str(iden))
print("\nGetting UMLS terms from Disease Ontology ID (%s):" % doid)
for term in get_umls_terms(doid_dis):
print("- " + str(term))
def pathway_reference_unit_tests(wikipathways_id, openphacts_app_id,
openphacts_app_key, kegg_ko_pathway_id):
kegg_ko_pathway = gnomics.objects.pathway.Pathway(
identifier=kegg_ko_pathway_id,
identifier_type="KEGG KO PATHWAY ID",
source="KEGG")
print("\nGetting reference identifiers from KEGG KO PATHWAY ID (%s):" %
kegg_ko_pathway_id)
for ref in get_references(kegg_ko_pathway):
for iden in ref.identifiers:
print("- %s (%s)" %
(str(iden["identifier"]), iden["identifier_type"]))
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key)
wiki_pathway = gnomics.objects.pathway.Pathway(
identifier=wikipathways_id,
identifier_type="WikiPathways ID",
source="OpenPHACTS")
print("\nGetting reference identifiers from WikiPathways ID (%s):" %
wikipathways_id)
for ref in get_references(wiki_pathway, user=user):
for iden in ref.identifiers:
print("- %s (%s)" %
(str(iden["identifier"]), iden["identifier_type"]))
def aod_unit_tests(neu_id, uwda_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
neu_anat = gnomics.objects.anatomical_structure.AnatomicalStructure(
identifier=neu_id, identifier_type="NEU ID", source="UMLS")
print("Getting AOD IDs from NEU ID (%s):" % neu_id)
start = timeit.timeit()
aod_array = get_aod(neu_anat, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for aod in aod_array:
print("\t- %s" % str(aod))
uwda_anat = gnomics.objects.anatomical_structure.AnatomicalStructure(
identifier=uwda_id, identifier_type="UWDA ID", source="UMLS")
print("\nGetting AOD IDs from UWDA ID (%s):" % uwda_id)
start = timeit.timeit()
aod_array = get_aod(uwda_anat, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for aod in aod_array:
print("\t- %s" % str(aod))
def snomed_unit_tests(omim_disease_id, doid, omim_api_key=None):
if omim_api_key is not None:
print("Creating user...")
user = User(omim_api_key=omim_api_key)
print("User created successfully.\n")
omim_disease = gnomics.objects.disease.Disease(
identifier=str(omim_disease_id),
identifier_type="MIM Number",
source="OMIM")
print("Getting SNOMED-CT IDs from MIM Number (%s):" % omim_disease_id)
for sno in get_snomed(omim_disease, user=user):
print("- " + str(sno))
doid_dis = gnomics.objects.disease.Disease(identifier=str(doid),
identifier_type="DOID",
source="Disease Ontology")
print("\nGetting SNOMED-CT IDs from DOID (%s):" % doid)
for sno in get_snomed(doid_dis):
print("- " + str(sno))
else:
doid_dis = gnomics.objects.disease.Disease(identifier=str(doid),
identifier_type="DOID",
source="Disease Ontology")
print("\nGetting SNOMED-CT IDs from DOID (%s):" % doid)
for sno in get_snomed(doid_dis):
print("- " + str(sno))
def eol_unit_tests(eol_id, tsn, index_fungorum_id, paleobiology_db_id, ncbi_taxonomy_id, wikidata_accession, eol_api_key = None):
print("Creating user...")
user = User(eol_api_key = eol_api_key)
print("User created successfully.\n")
eol_tax = gnomics.objects.taxon.Taxon(identifier = str(eol_id), identifier_type = "EOL ID", source = "EOL")
print("Getting EOL object from EOL ID (%s):" % eol_id)
# print(str(get_eol_object(eol_tax)).encode('utf-8'))
print("Getting EOL Traitbank object from EOL ID (%s):" % eol_id)
with open("traitbank_sample.txt", "w+", encoding="utf-8") as fil:
fil.write(str(get_eol_traitbank_object(eol_tax)))
print("\nGetting EOL ID from ITIS TSN (%s):" % tsn)
tsn_tax = gnomics.objects.taxon.Taxon(identifier = str(tsn), identifier_type = "TSN", source = "ITIS")
print("- %s" % get_eol_id(tsn_tax))
print("\nGetting EOL ID from Index Fungorum identifier (%s):" % index_fungorum_id)
fungorum_tax = gnomics.objects.taxon.Taxon(identifier = str(index_fungorum_id), identifier_type = "Index Fungorum Identifier", source = "Index Fungorum")
print("- %s" % get_eol_id(fungorum_tax))
print("\nGetting EOL ID from Paleobiology Database identifier (%s):" % paleobiology_db_id)
paleo_tax = gnomics.objects.taxon.Taxon(identifier = str(paleobiology_db_id), identifier_type = "Paleobiology Database Identifier", source = "Paleobiology Database")
print("- %s" % get_eol_id(paleo_tax))
print("\nGetting EOL ID from NCBI Taxonomy identifier (%s):" % ncbi_taxonomy_id)
ncbi_tax = gnomics.objects.taxon.Taxon(identifier = str(ncbi_taxonomy_id), identifier_type = "NCBI Taxonomy Identifier", source = "NCBI")
print("- %s" % get_eol_id(ncbi_tax))
wikidata_taxon = gnomics.objects.taxon.Taxon(identifier = str(wikidata_accession), identifier_type = "Wikidata Accession", source = "Wikidata")
print("\nGetting EOL ID from Wikidata Accession (%s):" % wikidata_accession)
print("- %s" % get_eol_id(wikidata_taxon))
def bto_unit_tests(caloha_id, uberon_id, hpa_accs, chembl_id,
openphacts_app_id, openphacts_app_key, ncbo_api_key):
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key,
ncbo_api_key=ncbo_api_key)
chembl_tiss = gnomics.objects.tissue.Tissue(identifier=chembl_id,
identifier_type="ChEMBL ID",
source="ChEMBL")
print("\nGetting BTO IDs from ChEMBL ID (%s):" % chembl_id)
start = timeit.timeit()
bto_array = get_bto_id(chembl_tiss, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for tiss in bto_array:
print("\t- %s" % str(tiss))
caloha_tiss = gnomics.objects.tissue.Tissue(identifier=caloha_id,
identifier_type="CALOHA ID",
source="OpenPHACTS")
print("\nGetting BTO IDs from CALOHA ID (%s):" % caloha_id)
start = timeit.timeit()
bto_array = get_bto_id(caloha_tiss, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for tiss in bto_array:
print("\t- %s" % str(tiss))
uberon_tiss = gnomics.objects.tissue.Tissue(identifier=uberon_id,
identifier_type="UBERON ID",
source="OpenPHACTS")
print("\nGetting BTO IDs from UBERON ID (%s):" % uberon_id)
start = timeit.timeit()
bto_array = get_bto_id(uberon_tiss, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for tiss in bto_array:
print("\t- %s" % str(tiss))
for acc in hpa_accs:
hpa_tiss = gnomics.objects.tissue.Tissue(
identifier=acc,
identifier_type="HPA Accession",
language="en",
source="The Human Protein Atlas")
print("\nGetting UBERON IDs from HPA Accession (%s):" % acc)
start = timeit.timeit()
hpa_array = get_bto_id(hpa_tiss, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for tiss in hpa_array:
print("\t- %s" % str(tiss))
def oidd_unit_tests(bioassay_id, openphacts_app_id, openphacts_app_key):
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key)
bio_assay = gnomics.objects.assay.Assay(identifier=bioassay_id,
identifier_type="OIDD Bioassay ID",
source="OIDD")
get_oidd_bioassay_obj(bio_assay, user=user)
def pathway_compound_unit_tests(wikipathways_id, openphacts_app_id, openphacts_app_key):
user = User(openphacts_app_id = openphacts_app_id, openphacts_app_key = openphacts_app_key)
wiki_pathway = gnomics.objects.drug.Drug(identifier = wikipathways_id, identifier_type = "WikiPathways ID", source = "OpenPHACTS")
print("\nGetting compound identifiers from WikiPathways ID (%s):" % wikipathways_id)
for com in get_compounds(wiki_pathway, user = user):
for iden in com.identifiers:
print("- %s (%s)" % (str(iden["identifier"]), iden["identifier_type"]))
def isbndb_unit_tests(isbn, isbndb_api_key):
user = User(isbndb_api_key=isbndb_api_key)
isbn_ref = gnomics.objects.reference.Reference(identifier=isbn,
identifier_type="ISBN-13")
print("Getting book information for ISBN '%s'..." % str(isbn))
for x in get_isbndb_books(isbn_ref, user=user):
for field, field_info in x.items():
print("- %s: %s" % (str(field), str(field_info)))
def mesh_unit_tests(caloha_id, openphacts_app_id, openphacts_app_key):
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key)
caloha_tiss = gnomics.objects.tissue.Tissue(identifier=caloha_id,
identifier_type="CALOHA ID",
source="OpenPHACTS")
for mesh in get_mesh_uid(caloha_tiss, user=user):
print("- %s" % mesh)
def dpla_unit_tests(query, dpla_api_key):
user = User(dpla_api_key=dpla_api_key)
print("Obtaining DPLA documents from query '%s'...\n" % str(query))
for ref in dpla_search(query, user=user):
for iden in ref.identifiers:
print("- %s (%s) [%s]" %
(iden["name"].encode("ascii", errors="ignore").decode(),
iden["identifier"], iden["identifier_type"]))
def loc_unit_tests(neu_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
neu_anat = gnomics.objects.anatomical_structure.AnatomicalStructure(
identifier=neu_id, identifier_type="NEU ID", source="UMLS")
print("Getting Library of Congress Subject Headings from NEU ID (%s):" %
neu_id)
for loc in get_loc_sh(neu_anat, user=user):
print("- " + str(loc))
def snomed_unit_tests(hpo_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
hpo_phen = gnomics.objects.compound.Compound(
identifier=str(hpo_id),
identifier_type="HPO ID",
source="Human Phenotype Ontology")
print("Getting SNOMED-CT IDs from HPO ID (%s):" % hpo_id)
for sno in get_snomed_ct_id(hpo_phen, user=user):
print("- " + str(sno))
def uwda_unit_tests(neu_id, umls_api_key):
user = User(umls_api_key=umls_api_key)
neu_anat = gnomics.objects.anatomical_structure.AnatomicalStructure(
identifier=neu_id, identifier_type="NEU ID", source="UMLS")
print("Getting UWDA IDs from NEU ID (%s):" % neu_id)
for uwda in get_uwda_id(neu_anat, user=user):
print("- " + str(uwda))
def formula_unit_tests(chemspider_id, pubchem_cid, chemspider_security_token):
if chemspider_security_token is not None:
print("Creating user...")
user = User(chemspider_security_token=chemspider_security_token)
print("User created successfully.\n")
chemspider_com = gnomics.objects.compound.Compound(
identifier=str(chemspider_id),
identifier_type="ChemSpider ID",
source="ChemSpider")
print("\nGetting molecular formula from ChemSpider ID (%s):" %
chemspider_id)
start = timeit.timeit()
molec_array = get_molecular_formula(chemspider_com, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for com in molec_array:
print("\t- %s" % str(com))
pubchem_com = gnomics.objects.compound.Compound(
identifier=str(pubchem_cid),
identifier_type="PubChem CID",
source="PubChem")
print("\nGetting molecular formula from PubChem CID (%s):" %
pubchem_cid)
start = timeit.timeit()
molec_array = get_molecular_formula(pubchem_com)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for com in molec_array:
print("\t- %s" % str(com))
else:
print(
"No user provided. Cannot test ChemSpider conversion without ChemSpider security token.\n"
)
print("Continuing with PubChem CID conversion...\n")
pubchem_com = gnomics.objects.compound.Compound(
identifier=str(pubchem_cid),
identifier_type="PubChem CID",
source="PubChem")
print("\nGetting molecular formula from PubChem CID (%s):" %
pubchem_cid)
start = timeit.timeit()
molec_array = get_molecular_formula(pubchem_com)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for com in molec_array:
print("\t- %s" % str(com))
def vernacular_name_unit_tests(eol_id, eol_api_key=None):
print("Creating user...")
user = User(eol_api_key=eol_api_key)
print("User created successfully.\n")
eol_tax = gnomics.objects.taxon.Taxon(identifier=str(eol_id),
identifier_type="EOL ID",
source="EOL")
print("Getting EOL object from EOL ID (%s):" % eol_id)
for iden in get_vernacular_names(eol_tax):
print("- %s" % iden)
def chemspider_unit_tests(inchi_id, chemspider_security_token):
user = User(chemspider_security_token=chemspider_security_token)
inchi_compound = gnomics.objects.compound.Compound(identifier = str(inchi_id), identifier_type = "InChi", source = "PubChem")
print("Getting ChemSpider ID from InChI (%s):" % inchi_id)
start = timeit.timeit()
cs_array = get_chemspider_id(inchi_compound, user = user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for com in cs_array:
print("\t- %s" % str(com))
def reference_pathway_unit_tests(pmid, openphacts_app_id, openphacts_app_key):
user = User(openphacts_app_id=openphacts_app_id,
openphacts_app_key=openphacts_app_key)
pm_ref = gnomics.objects.reference.Reference(identifier=pmid,
identifier_type="PubMed ID",
source="OpenPHACTS")
print("\nGetting pathway identifiers from PubMed ID (%s):" % pmid)
for path in get_pathways(pm_ref, user=user):
for iden in path.identifiers:
print("- %s (%s)" %
(str(iden["identifier"]), iden["identifier_type"]))
def drug_gene_unit_tests(drugbank_id, openphacts_app_id, openphacts_app_key):
user = User(openphacts_app_id = openphacts_app_id, openphacts_app_key = openphacts_app_key)
drugbank_drug = gnomics.objects.drug.Drug(identifier = drugbank_id, identifier_type = "DrugBank ID", source = "OpenPHACTS")
start = timeit.timeit()
all_genes = get_genes(drugbank_drug, user = user)
end = timeit.timeit()
print("TIME ELAPSED: %s seconds." % str(end - start))
for gene in all_genes:
for iden in gene.identifiers:
if iden["identifier_type"] == "HGNC Approved Symbol":
print("- %s (%s)" % (iden["identifier"], iden["identifier_type"]))
def basic_search_unit_tests(basic_query, umls_api_key, ncbo_api_key):
print("Beginning basic search for '%s'..." % basic_query)
basic_search_results = search(basic_query, source="ebi")
print(
"\nSearch returned %s result(s) with the following identifiers (EBI):"
% str(len(basic_search_results)))
for anat in basic_search_results:
for iden in anat.identifiers:
print("- %s: %s (%s)" %
(iden["identifier"], iden["name"], iden["identifier_type"]))
user = User(umls_api_key=umls_api_key)
start = timeit.timeit()
basic_search_results = search(basic_query, source="umls", user=user)
end = timeit.timeit()
print("TIME ELAPSED: %s seconds." % str(end - start))
print(
"\nSearch returned %s result(s) with the following identifiers (UMLS):"
% str(len(basic_search_results)))
for anat in basic_search_results:
for iden in anat.identifiers:
print("- %s: %s (%s)" %
(iden["identifier"], iden["name"], iden["identifier_type"]))
user = User(ncbo_api_key=ncbo_api_key)
start = timeit.timeit()
basic_search_results = search(basic_query, source="ncbo", user=user)
end = timeit.timeit()
print("TIME ELAPSED: %s seconds." % str(end - start))
print(
"\nSearch returned %s result(s) with the following identifiers (NCBO):"
% str(len(basic_search_results)))
for anat in basic_search_results:
for iden in anat.identifiers:
print("- %s: %s (%s)" %
(iden["identifier"], iden["name"], iden["identifier_type"]))
def mesh_unit_tests(meddra_id, umls_api_key, ncbo_api_key):
user = User(umls_api_key=umls_api_key, ncbo_api_key=ncbo_api_key)
meddra_ae = gnomics.objects.adverse_event.AdverseEvent(
identifier=meddra_id, identifier_type="MedDRA ID", source="UMLS")
print("Getting MeSH UIDs from MedDRA ID (%s):" % meddra_id)
start = timeit.timeit()
mesh_array = get_mesh_uid(meddra_ae, user=user)
end = timeit.timeit()
print("\tTIME ELAPSED: %s seconds." % str(end - start))
print("\tRESULTS:")
for mesh in mesh_array:
print("\t- %s" % str(mesh))
def icd10_unit_tests(kegg_disease_id,
omim_disease_id,
doid,
omim_api_key=None):
if omim_api_key is not None:
print("Creating user...")
user = User(omim_api_key=omim_api_key)
print("User created successfully.\n")
omim_disease = gnomics.objects.disease.Disease(
identifier=str(omim_disease_id),
identifier_type="MIM Number",
source="OMIM")
print("Getting ICD-10-CM IDs from MIM Number (%s):" % omim_disease_id)
for icd in get_icd10(omim_disease, user=user):
print("- " + str(icd))
kegg_disease = gnomics.objects.disease.Disease(
identifier=str(kegg_disease_id),
identifier_type="KEGG Disease ID",
source="KEGG")
print("\nGetting ICD-10-CM IDs from KEGG Disease ID (%s):" %
kegg_disease_id)
for icd10 in get_icd10(kegg_disease):
print("- " + str(icd10))
doid_dis = gnomics.objects.disease.Disease(identifier=str(doid),
identifier_type="DOID",
source="Disease Ontology")
print("\nGetting ICD-10-CM IDs from DOID (%s):" % doid)
for icd10 in get_icd10(doid_dis):
print("- " + str(icd10))
else:
kegg_disease = gnomics.objects.disease.Disease(
identifier=str(kegg_disease_id),
identifier_type="KEGG Disease ID",
source="KEGG")
print("\nGetting ICD-10-CM IDs from KEGG Disease ID (%s):" %
kegg_disease_id)
for icd10 in get_icd10(kegg_disease):
print("- " + str(icd10))
doid_dis = gnomics.objects.disease.Disease(identifier=str(doid),
identifier_type="DOID",
source="Disease Ontology")
print("\nGetting ICD-10-CM IDs from DOID (%s):" % doid)
for icd10 in get_icd10(doid_dis):
print("- " + str(icd10))
def basic_search_unit_tests(basic_query, umls_api_key):
user = User(umls_api_key=umls_api_key)
print("Beginning basic searches for '%s'..." % basic_query)
start = timeit.timeit()
basic_search_results = search(basic_query, user, search_type="exact")
end = timeit.timeit()
print("TIME ELAPSED: %s seconds." % str(end - start))
print(
"\nSearch returned %s exact result(s) with the following procedure identifiers:"
% str(len(basic_search_results)))
for proc in basic_search_results:
for iden in proc.identifiers:
print("- %s (%s)" % (iden["identifier"], iden["identifier_type"]))
