def run_l1000cds2(signature, nr_genes=500, signature_label='', plot_type='interactive'):
# Define results
l1000cds2_results = {'signature_label': signature_label}
# Define upperGenes Function
upperGenes = lambda genes: [gene.upper() for gene in genes]
# Get Data
data = {"upGenes":upperGenes(signature.index[:nr_genes]),"dnGenes":upperGenes(signature.index[-nr_genes:])}
# Loop through aggravate:
for aggravate in [True, False]:
# Send to API
config = {"aggravate":aggravate,"searchMethod":"geneSet","share":True,"combination":False,"db-version":"latest"}
r = requests.post('http://amp.pharm.mssm.edu/L1000CDS2/query',data=json.dumps({"data":data,"config":config}),headers={'content-type':'application/json'})
label = 'mimic' if aggravate else 'reverse'
# Add results
resGeneSet = r.json()
if resGeneSet.get('topMeta'):
l1000cds2_dataframe = pd.DataFrame(resGeneSet['topMeta'])[['cell_id', 'pert_desc', 'pert_dose', 'pert_dose_unit', 'pert_id', 'pert_time', 'pert_time_unit', 'pubchem_id', 'score', 'sig_id']].replace('-666', np.nan)
l1000cds2_results[label] = {'url': 'http://amp.pharm.mssm.edu/L1000CDS2/#/result/{}'.format(resGeneSet['shareId']), 'table': l1000cds2_dataframe}
else:
l1000cds2_results[label] = None
l1000cds2_results['plot_type'] = plot_type
# Return
return l1000cds2_results
def _google_translate(q, source, target, key):
import requests
params = {'q': q, 'target': target, 'key': key}
if source:
params['source'] = source
try:
r = requests.post(
'https://translation.googleapis.com/language/translate/v2',
data=params)
except requests.RequestException:
return app_log.exception('Cannot connect to Google Translate')
response = r.json()
if 'error' in response:
return app_log.error('Google Translate API error: %s',
response['error'])
return {
'q':
q,
't': [t['translatedText'] for t in response['data']['translations']],
'source': [
t.get('detectedSourceLanguage', params.get('source', None))
for t in response['data']['translations']
],
'target': [target] * len(q),
}