cohorts().create()¶
Creates and saves a cohort. Takes a JSON object in the request body to use as the cohort’s filters. Authentication is required. Returns information about the saved cohort, including the number of cases and the number of samples in that cohort.
Example:
python isb_curl.py "https://api-dot-isb-cgc.appspot.com/_ah/api/isb_cgc_ccle_api/v3/cohorts/create?name={COHORT NAME}" -H "Content-Type: application/json" -d '{"program_short_name": ["CCLE-BLCA", "CCLE-LUSC"], "gender": "Male"}'
API explorer example:
Click here to see this endpoint in Google’s API explorer.
Python API Client Example:
from googleapiclient.discovery import build
from oauth2client.client import OAuth2WebServerFlow
from oauth2client import tools
from oauth2client.file import Storage
import httplib2
import os
CLIENT_ID = '907668440978-0ol0griu70qkeb6k3gnn2vipfa5mgl60.apps.googleusercontent.com'
CLIENT_SECRET = 'To_WJH7-1V-TofhNGcEqmEYi'
EMAIL_SCOPE = 'https://www.googleapis.com/auth/userinfo.email'
DEFAULT_STORAGE_FILE = os.path.join(os.path.expanduser('~'), '.isb_credentials')
def get_credentials():
oauth_flow_args = ['--noauth_local_webserver']
storage = Storage(DEFAULT_STORAGE_FILE)
credentials = storage.get()
if not credentials or credentials.invalid:
flow = OAuth2WebServerFlow(CLIENT_ID, CLIENT_SECRET, EMAIL_SCOPE)
flow.auth_uri = flow.auth_uri.rstrip('/') + '?approval_prompt=force'
credentials = tools.run_flow(flow, storage, tools.argparser.parse_args(oauth_flow_args))
return credentials
def get_authorized_service():
api = 'isb_cgc_ccle_api'
version = 'v3'
site = 'https://api-dot-isb-cgc.appspot.com'
discovery_url = '%s/_ah/api/discovery/v1/apis/%s/%s/rest' % (site, api, version)
credentials = get_credentials()
http = credentials.authorize(httplib2.Http())
if credentials.access_token_expired or credentials.invalid:
credentials.refresh(http)
authorized_service = build(api, version, discoveryServiceUrl=discovery_url, http=http)
return authorized_service
service = get_authorized_service()
body = {'program_short_name': ['CCLE-BLCA', 'CCLE-LUSC'], 'gender': 'Male'}
data = service.cohorts().create(name=name, body=body).execute()
Request
HTTP request:
POST https://api-dot-isb-cgc.appspot.com/_ah/api/isb_cgc_ccle_api/v3/ccle/cohorts/create?name=Cohort_test&fields=case_count%2Cfilters%2Cid%2Clast_date_saved%2Cname%2Csample_count
- {
- “Common”: {
- “project_short_name”: [
- “CCLE-BLCA”, “CCLE-LUSC”
]
}, “Clinical”: {
- “gender”: [
- “Male”
]
}
}
Parameters
| Parameter name | Value | Description |
|---|---|---|
| name | string | Required. |
Request body
In the request body, supply a metadata resource with the following properties:
{
"case_barcode": [string],
"case_gdc_id": [string],
"disease_code": [string],
"endpoint_type": [string],
"gender": [string],
"hist_subtype": [string],
"histology": [string],
"program_name": [string],
"project_short_name": [string],
"sample_barcode": [string],
"sample_gdc_id": [string],
"sample_type": [string],
"site_primary": [string],
"source": [string],
"summary_file_count": [integer],
"summary_file_count_gte": integer,
"summary_file_count_lte": integer
}
| Parameter name | Value | Description |
|---|---|---|
| case_barcode[] | list | Optional. |
| case_gdc_id[] | list | Optional. |
| disease_code[] | list | Optional. Possible values include: ‘BLCA’, ‘BRCA’, ‘CESC’, ‘COAD’, ‘DLBC’, ‘ESCA’, ‘HNSC’, ‘KIRC’, ‘LCLL’, ‘LGG’, ‘LIHC’, ‘LUSC’, ‘MESO’, ‘MM’, ‘OV’, ‘PAAD’, ‘PRAD’, ‘SARC’, ‘SKCM’, ‘STAD’, ‘THCA’, ‘UCEC’. |
| endpoint_type[] | list | Optional. Possible values include: ‘legacy’. |
| gender[] | list | Optional. Possible values include: ‘F’, ‘M’, ‘U’. |
| hist_subtype[] | list | Optional. Possible values include: ‘acute_lymphoblastic_B_cell_leukaemia’, ‘acute_lymphoblastic_T_cell_leukaemia’, ‘acute_myeloid_leukaemia’, ‘adenocarcinoma’, ‘adult_T_cell_lymphoma-leukaemia’, ‘alveolar’, ‘anaplastic_carcinoma’, ‘anaplastic_large_cell_lymphoma’, ‘astrocytoma’, ‘astrocytoma_Grade_III’, ‘astrocytoma_Grade_IV’, ‘blast_phase_chronic_myeloid_leukaemia’, ‘Brenner_tumour’, ‘bronchioloalveolar_adenocarcinoma’, ‘Burkitt_lymphoma’, ‘B_cell_lymphoma_unspecified’, ‘carcinosarcoma-malignant_mesodermal_mixed_tumour’, ‘chronic_lymphocytic_leukaemia-small_lymphocytic_lymphoma’, ‘chronic_myeloid_leukaemia’, ‘clear_cell_carcinoma’, ‘clear_cell_renal_cell_carcinoma’, ‘dedifferentiated’, ‘diffuse_adenocarcinoma’, ‘diffuse_large_B_cell_lymphoma’, ‘ductal_carcinoma’, ‘embryonal’, ‘endometrioid_carcinoma’, ‘essential_thrombocythaemia’, ‘follicular_carcinoma’, ‘giant_cell_tumour’, ‘gliosarcoma’, ‘granulosa_cell_tumour’, ‘hepatoblastoma’, ‘hepatocellular_carcinoma’, ‘Hodgkin_lymphoma’, ‘intestinal_adenocarcinoma’, ‘large_cell_carcinoma’, ‘mantle_cell_lymphoma’, ‘medullary_carcinoma’, ‘metaplasia’, ‘metaplastic_carcinoma’, ‘mixed_adenosquamous_carcinoma’, ‘mixed_carcinoma’, ‘mucinous_carcinoma’, ‘mucoepidermoid_carcinoma’, ‘mycosis_fungoides-Sezary_syndrome’, ‘non_small_cell_carcinoma’, ‘NS’, ‘oligodendroglioma’, ‘papillary_carcinoma’, ‘papilloma’, ‘peripheral_T_cell_lymphoma_unspecified’, ‘plasma_cell_myeloma’, ‘renal_cell_carcinoma’, ‘serous_carcinoma’, ‘signet_ring_adenocarcinoma’, ‘small_cell_adenocarcinoma’, ‘small_cell_carcinoma’, ‘squamous_cell_carcinoma’, ‘transitional_cell_carcinoma’, ‘tubular_adenocarcinoma’, ‘undifferentiated_adenocarcinoma’, ‘undifferentiated_carcinoma’. |
| histology[] | list | Optional. Possible values include: ‘carcinoid-endocrine_tumour’, ‘carcinoma’, ‘chondrosarcoma’, ‘Ewings_sarcoma-peripheral_primitive_neuroectodermal_tumour’, ‘fibrosarcoma’, ‘giant_cell_tumour’, ‘glioma’, ‘haematopoietic_neoplasm’, ‘leiomyosarcoma’, ‘lymphoid_neoplasm’, ‘malignant_fibrous_histiocytoma-pleomorphic_sarcoma’, ‘malignant_melanoma’, ‘mesothelioma’, ‘neuroblastoma’, ‘osteosarcoma’, ‘other’, ‘primitive_neuroectodermal_tumour-medulloblastoma’, ‘rhabdoid_tumour’, ‘rhabdomyosarcoma’, ‘sarcoma’, ‘sex_cord-stromal_tumour’. |
| program_name[] | list | Optional. Possible values include: ‘CCLE’. |
| project_short_name[] | list | Optional. Possible values include: ‘CCLE-BLCA’, ‘CCLE-BRCA’, ‘CCLE-CESC’, ‘CCLE-COAD’, ‘CCLE-DLBC’, ‘CCLE-ESCA’, ‘CCLE-HNSC’, ‘CCLE-KIRC’, ‘CCLE-LCLL’, ‘CCLE-LGG’, ‘CCLE-LIHC’, ‘CCLE-LUSC’, ‘CCLE-MESO’, ‘CCLE-MM’, ‘CCLE-OV’, ‘CCLE-PAAD’, ‘CCLE-PRAD’, ‘CCLE-SARC’, ‘CCLE-SKCM’, ‘CCLE-STAD’, ‘CCLE-THCA’, ‘CCLE-UCEC’. |
| sample_barcode[] | list | Optional. |
| sample_gdc_id[] | list | Optional. |
| sample_type[] | list | Optional. Possible values include: ‘13’, ‘50’. |
| site_primary[] | list | Optional. Possible values include: ‘autonomic_ganglia’, ‘biliary_tract’, ‘bone’, ‘breast’, ‘central_nervous_system’, ‘endometrium’, ‘haematopoietic_and_lymphoid_tissue’, ‘kidney’, ‘large_intestine’, ‘liver’, ‘lung’, ‘oesophagus’, ‘ovary’, ‘pancreas’, ‘pleura’, ‘prostate’, ‘salivary_gland’, ‘skin’, ‘small_intestine’, ‘soft_tissue’, ‘stomach’, ‘thyroid’, ‘upper_aerodigestive_tract’, ‘urinary_tract’. |
| source[] | list | Optional. Possible values include: ‘Academic Lab’, ‘ATCC’, ‘DSMZ’, ‘ECACC’, ‘HSRRB’, ‘ICLC’, ‘KCLB’, ‘NCI/DCTD’, ‘RIKEN’. |
| summary_file_count[] | list | Optional. |
| summary_file_count_gte | integer | Optional. |
| summary_file_count_lte | integer | Optional. |
Response
If successful, this method returns a response body with the following structure:
{
"case_count": integer,
"filters": [
{
"name": string,
"value": string
}
],
"id": string,
"last_date_saved": string,
"name": string,
"sample_count": integer
}
| Parameter name | Value | Description |
|---|---|---|
| case_count | integer | Number of unique case barcodes in the cohort. |
| filters[] | list | List of filters applied to create cohort, if any. |
| filters[].name | string | Names of filtering parameters used to create the cohort. |
| filters[].value | string | Values of filtering parameters used to create the cohort. |
| id | string | Cohort id. |
| last_date_saved | string | Last date the cohort was saved. |
| name | string | Name of cohort. |
| sample_count | integer | Number of unique sample barcodes in the cohort. |