def test():
parser = argparse.ArgumentParser(description='test similarity service')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
args = parser.parse_args()
#api = KnowledgeHubAPI(server='TEST', client_secret='39c644b3-1f23-4d94-a71f-e0fb43ebd760')
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
status = api.login(args.username, args.password)
print(status)
findings = api.eToxSys().getAllFindings(10)
def main():
parser = argparse.ArgumentParser(
description=
'Process parameters for collecting findings from primitive adapter')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
args = parser.parse_args()
api = KnowledgeHubAPI(server='TEST',
client_secret='39c644b3-1f23-4d94-a71f-e0fb43ebd760')
api.login(args.username, args.password)
compoundSmile = api.ChemistryService().getSMILESByName('omeprazole')
similar_compounds = api.SimilarityService().get(compoundSmile[0])
names = []
smiles = []
similarities = []
if similar_compounds is not None:
for similar_compound in similar_compounds:
names.append(similar_compound['name'])
smiles.append(similar_compound['smiles'])
similarities.append(similar_compound['distance'])
studies = filterStudies(api.eToxSys().getStudiesByCompoundNames(names))
print(f'Found {len(studies)} studies.')
for study in studies:
print(study)
api.SemanticService().getSocs(studies)
otherStudies = [
study for study in studies if study['FINDING']['__soc'] == 'Other'
]
print(f'#others:{len(otherStudies)}')
def main():
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
authenticate(api, 'tester', 'tester')
compound_name = 'omeprazole'
smiles = translate_compound_to_smiles(api, compound_name)
retrieve_similar_compounds(api, smiles, compound_name)
def main():
parser = argparse.ArgumentParser(description='test similarity service')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
args = parser.parse_args()
api = KnowledgeHubAPI()
api.set_server('DEV')
api = KnowledgeHubAPI(server='TEST', client_secret='39c644b3-1f23-4d94-a71f-e0fb43ebd760')
api.login('*****@*****.**', 'Crosby99!')
status = api.SimilarityService().spaces()
print(f'status={status}')
omeprazole = 'COc1ccc2[nH]c([S+]([O-])Cc3ncc(C)c(OC)c3C)nc2c1'
# omeprazole = 'CCC1=C(C)CN(C(=O)NCCC2=CC=C(C=C2)S(=O)(=O)NC(=O)NC2CCC(C)CC2)C1-Cl'
similar_compounds = api.SimilarityService().get(omeprazole)
pprint.pprint(similar_compounds)
def test():
parser = argparse.ArgumentParser(description='test similarity service')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
args = parser.parse_args()
api = KnowledgeHubAPI()
api.set_service('DEV')
status = api.login(args.username, args.password)
print(status)
terms = api.SemanticService().lookup('Terbinafine', 'RxNorm')
print(json.dumps(terms, indent=4, sort_keys=True))
#if len(terms['terms']) > 0:
#concepts = api.SemanticService().normalize(terms['terms'][0], 'RxNorm')
#print(json.dumps(concepts, indent=4, sort_keys=True))
#if len(concepts['concepts']) == 1:
compounds = [
"Minoxidil","Estradiol","Anastrozole","Felodipine","Amphetamine",",Adenosine","Azathioprine","Levamisole",
#"Zolmitriptan","Lidocaine","Alprazolam","Ropivacaine","Foscarnet","Rimonabant","Remoxipride","Cyclophosphamide",
#"Aripiprazole","Bambuterol","Sulfamethoxazole","Rosiglitazone","Clozapine","Budesonide","Omeprazole","Raltitrexed",
#"Clonidine","Gefitinib","Ximelagatran","Diazepam","Olanzapine","Zafirlukast","Nifedipine","Indomethacin","Erlotinib",
#"Formoterol","Diclofenac","Metoprolol","Enprofylline","Bicalutamide","Chlordiazepoxide","Simvastatin","Ranitidine",
#"Ticagrelor","Sulfinpyrazone","Phenylbutazone","Benazepril","Isosorbide Mononitrate","Deferoxamine","Guanfacine",
#"Naftifine","Chlorthalidone","Guanethidine","Valproic Acid","Clozapine","Baclofen","Maprotiline","Thioridazine",
#"Aminoglutethimide","Bromocriptine","Phentolamine","Amantadine","Thiethylperazine","Pindolol","Lidocaine",
#"Linezolid","Prednisolone","Candoxatril","Diazepam","Orlistat","Carprofen","Cilazapril"
]
def setUp(self):
super(ServiceTest, self).setUp()
api = KnowledgeHubAPI()
api.set_server('DEV')
api.login(self.username, self.password)
self.services = Services(
api, 'https://dev.toxhub.etransafe.eu/registry.kh.svc/api/v1')
def main():
parser = argparse.ArgumentParser(
description=
'Process parameters for collecting findings from primitive adapter')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
args = parser.parse_args()
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
api.login(args.username, args.password)
socs = {}
studies = api.eToxSys().getStudiesByCompoundNames(['omeprazole'])
#studies = api.eToxSys().getStudiesBySMILES(['COc1ccc2[nH]c([S+]([O-])Cc3ncc(C)c(OC)c3C)nc2c1'])
print(f'#studies:{len(studies)}')
#print(studies[0])
findings_per_specimen_organ = {}
for study in studies:
if study['FINDING']['finding'] != None and study['FINDING'][
'finding'] != 'No abnormalities detected' and len(
study['FINDING']['finding']) > 0:
specimenOrgans = api.SemanticService().getSocs(
study['FINDING']['specimenOrgan'])
for specimenOrgan in specimenOrgans:
if len(specimenOrgan) > 0:
finding = study['FINDING']['specimenOrgan']
if specimenOrgan not in findings_per_specimen_organ:
findings_per_specimen_organ[specimenOrgan] = []
if finding not in findings_per_specimen_organ[
specimenOrgan]:
findings_per_specimen_organ[specimenOrgan].append(
finding)
for specimen_organ in findings_per_specimen_organ:
print(
f'{specimen_organ}: {len(findings_per_specimen_organ[specimen_organ])}'
)
for finding in findings_per_specimen_organ[specimen_organ]:
print(' ' + finding)
def main():
parser = argparse.ArgumentParser(
description=
'Process parameters for collecting findings from primitive adapter')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
parser.add_argument('-host', required=True, help='mysql server')
parser.add_argument('-database', required=True, help='mysql database')
parser.add_argument('-dbuser', required=True, help='mysql database user')
parser.add_argument('-dbpass',
required=True,
help='mysql database password')
parser.add_argument('-drug_mappings', required=False, help='password')
args = parser.parse_args()
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
mapper = Mapper(api)
status = api.login(args.username, args.password)
if status:
print('logged in')
else:
sys.exit(0)
if args.drug_mappings is None:
drugs = getDrugsMapping(api, getClinicalDatabases(api),
getPreclinicalDatabases(api))
else:
if os.path.isfile(args.drug_mappings):
with open(args.drug_mappings, 'r') as drug_file:
drugs = json.loads(drug_file.read())
else:
drugs = getDrugsMapping(api, getClinicalDatabases(api),
getPreclinicalDatabases(api))
with open(args.drug_mappings, 'x') as drug_file:
drug_file.write(json.dumps(drugs))
print(f'#drugs found: {len(drugs.keys())}')
db = mysql.connector.connect(host=args.host,
database=args.database,
username=args.dbuser,
password=args.dbpass)
ClinicalDatabases = getClinicalDatabases(api)
PreclinicalDatabases = getPreclinicalDatabases(api)
groups = {}
# get first the list of SOCs
preclinical_pts = {}
clinical_pts = {}
for drug in drugs:
preclinical_pts[drug] = getPTDrugFindings(
db=db,
drugInfo=drugs[drug],
databases=PreclinicalDatabases.keys(),
table='preclinical_meddra')
clinical_pts[drug] = getPTDrugFindings(
db=db,
drugInfo=drugs[drug],
databases=ClinicalDatabases.keys(),
table='clinical_meddra')
c = 0
all_preclinical_clinical_pts = getAllPreClinicalClinicalPTs(
db=db, tables=['preclinical_meddra', 'clinical_meddra'])
for pt in all_preclinical_clinical_pts:
c += 1
print(f'{c}/{len(all_preclinical_clinical_pts)}: {pt}')
groups[pt] = {'tp': 0, 'fp': 0, 'fn': 0, 'tn': 0}
for drug in drugs:
if pt in preclinical_pts[drug]:
if pt in clinical_pts[drug]:
groups[pt]['tp'] += 1
else:
groups[pt]['fp'] += 1
else:
if pt in clinical_pts[drug]:
groups[pt]['fn'] += 1
else:
groups[pt]['tn'] += 1
def main():
api = KnowledgeHubAPI()
terms = api.SemanticService().lookup('inflamm', 'HPATH')
print(terms)
with st.beta_expander("Click here for explanations"):
st.markdown("""
under construction!
...
""",
unsafe_allow_html=True)
session_state = SessionState.get(compoundName="Omeprazole",
compoundSmile="",
similar_compounds="",
compoundIds=[],
compoundNames=[],
studies={},
df_sim=[])
api = KnowledgeHubAPI()
compoundSmile = ''
############1. Translate compound to SMILES using semantic services
compoundName = st.text_input("compound name: (e.g. Omeprazole)",
value=session_state.compoundName)
session_state.compoundName = compoundName
if st.button('Retrieve') and len(compoundName) > 0:
compound = api.SemanticService().normalize(compoundName,
['RxNorm', 'smiles'])
if 'concepts' in compound:
for concept in compound['concepts']:
if 'vocabularyId' in concept:
if concept['vocabularyId'] == 'smiles':
# global compoundSmile
compoundSmile = concept['conceptCode']
st.text(f'Found SMILES {compoundSmile} for {compoundName}')
from knowledgehub.api import KnowledgeHubAPI
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
api.login('tester', 'tester')
compoundSmile = api.ChemicalService().getSMILESByName('omeprazole')
print(f'Found SMILES {compoundSmile[0]} for {"omeprazole"}')
similar_compounds = api.SimilarityService().get(compoundSmile)
print(f'similar compounds:{similar_compounds}')
from knowledgehub.api import KnowledgeHubAPI
api = KnowledgeHubAPI(server='DEV', client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
api.login('tester', 'tester')
clinical_cpds = api.Faers().getAllCompounds() + api.ClinicalTrials().getAllCompounds() + api.Medline().getAllCompounds() + api.DailyMed().getAllCompounds()
def main():
parser = argparse.ArgumentParser(
description=
'Process parameters for collecting findings from primitive adapter')
parser.add_argument('-username', required=True, help='username')
parser.add_argument('-password', required=True, help='password')
parser.add_argument('-host', required=True, help='mysql server')
parser.add_argument('-database', required=True, help='mysql database')
parser.add_argument('-dbuser', required=True, help='mysql database user')
parser.add_argument('-dbpass',
required=True,
help='mysql database password')
parser.add_argument('-drug_mappings', required=False, help='password')
parser.add_argument('-clear',
required=False,
action='store_true',
help='clear database')
args = parser.parse_args()
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
mapper = Mapper(api)
logged_in = api.login(args.username, args.password)
if logged_in:
print(f'logged in')
else:
print(f'not logged in')
sys.exit(0)
db = mysql.connector.connect(host=args.host,
database=args.database,
username=args.dbuser,
password=args.dbpass)
if args.clear:
cursor = db.cursor(prepared=True)
cursor.execute("DELETE FROM preclinical_meddra")
cursor.execute("DELETE FROM clinical_meddra")
db.commit()
records = []
# retrieve the preclinical records and map them to MedDRA
maximum = 0
cursor = db.cursor(prepared=True)
cursor.execute(
'SELECT distinct id, findingCode, specimenOrganCode FROM preclinical_findings WHERE mapped > -1'
)
for r in cursor.fetchall():
mapped_clinical_findings = mapper.mapToClinical([{
'findingCode':
r[1],
'specimenOrganCode':
r[2]
}])
preclinical_code = mapper.getKey({
'findingCode': r[1],
'specimenOrganCode': r[2]
})
# find the mapping(s) with the minimal absolute distance
values = [
item['distance']
for item in mapped_clinical_findings[preclinical_code]
]
if len(values) > 0:
minimum = min(values)
min_values = [
item for item in mapped_clinical_findings[preclinical_code]
if item['distance'] == minimum
]
if len(min_values) > maximum:
maximum = len(min_values)
for min_value in min_values:
records.append((r[0], r[1], r[2], min_value['findingCode'],
min_value['name'], min_value['distance']))
# store the mappings
try:
cursor = db.cursor(prepared=True)
cursor.executemany(
'INSERT INTO preclinical_meddra (id, findingCode, specimenOrganCode, PTCode, name, distance) VALUES (%s, %s, %s, %s, %s, %s)',
records)
db.commit()
except mysql.connector.errors.InterfaceError as e:
print(e)
# retrieve the clinical records and store them in the database
try:
cursor = db.cursor(prepared=True)
cursor2 = db.cursor(prepared=True)
cursor.execute(
'SELECT distinct id, findingCode, specimenOrganCode, findingCode, finding, mapped FROM clinical_findings WHERE mapped > -1'
)
cursor2.executemany(
'INSERT INTO clinical_meddra (id, findingCode, specimenOrganCode, PTCode, name, distance) VALUES (%s, %s, %s, %s, %s, %s)',
cursor.fetchall())
db.commit()
except mysql.connector.errors.InterfaceError as e:
print(e)
"""
test how the response from eToxSys looks like
"""
# api = KnowledgeHubAPI(server='TEST', client_secret='39c644b3-1f23-4d94-a71f-e0fb43ebd760')
from knowledgehub.api import KnowledgeHubAPI
import sys
from Concordance.condordance_utils import getPreclinicalCompounds
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
status = api.login('tester', 'tester')
drugs = getPreclinicalCompounds(api)
for drug in drugs:
print(drug)
from knowledgehub.api import KnowledgeHubAPI
api = KnowledgeHubAPI(server='DEV',
client_secret='3db5a6d7-4694-48a4-8a2e-e9c30d78f9ab')
api.login('tester', 'tester')
socs = api.SemanticService().getSocByCode('10000060')
print(socs)