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_tcga_api/v3/cohorts/create?name={COHORT NAME}" -H "Content-Type: application/json" -d '{"program_short_name": ["TCGA-UCS", "TCGA-CESC"], "age_at_diagnosis_lte": 60}"

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_tcga_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': ['TCGA-BRCA', 'TCGA-UCS'], 'age_at_diagnosis_gte': 90}
data = service.cohorts().create(name=name, body=body).execute()

Request

HTTP request:

POST https://api-dot-isb-cgc.appspot.com/_ah/api/isb_cgc_tcga_api/v3/tcga/cohorts/create?name=TCGA-test&fields=case_count%2Cfilters%2Cid%2Clast_date_saved%2Cname%2Csample_count
{
“Common”: {
“project_short_name”: [
“TCGA-UCS”, “TCGA-CESC”

]

}, “Clinical”: {

“age_at_diagnosis_lte”: 60

}

}

Parameters

Parameter name Value Description
name string Required.

Request body

In the request body, supply a metadata resource with the following properties:

{
  "age_at_diagnosis": [integer],
  "age_at_diagnosis_gte": integer,
  "age_at_diagnosis_lte": integer,
  "age_began_smoking_in_years": [integer],
  "age_began_smoking_in_years_gte": integer,
  "age_began_smoking_in_years_lte": integer,
  "anatomic_neoplasm_subdivision": [string],
  "avg_percent_lymphocyte_infiltration": [number],
  "avg_percent_lymphocyte_infiltration_gte": number,
  "avg_percent_lymphocyte_infiltration_lte": number,
  "avg_percent_monocyte_infiltration": [number],
  "avg_percent_monocyte_infiltration_gte": number,
  "avg_percent_monocyte_infiltration_lte": number,
  "avg_percent_necrosis": [number],
  "avg_percent_necrosis_gte": number,
  "avg_percent_necrosis_lte": number,
  "avg_percent_neutrophil_infiltration": [number],
  "avg_percent_neutrophil_infiltration_gte": number,
  "avg_percent_neutrophil_infiltration_lte": number,
  "avg_percent_normal_cells": [number],
  "avg_percent_normal_cells_gte": number,
  "avg_percent_normal_cells_lte": number,
  "avg_percent_stromal_cells": [number],
  "avg_percent_stromal_cells_gte": number,
  "avg_percent_stromal_cells_lte": number,
  "avg_percent_tumor_cells": [number],
  "avg_percent_tumor_cells_gte": number,
  "avg_percent_tumor_cells_lte": number,
  "avg_percent_tumor_nuclei": [number],
  "avg_percent_tumor_nuclei_gte": number,
  "avg_percent_tumor_nuclei_lte": number,
  "batch_number": [integer],
  "batch_number_gte": integer,
  "batch_number_lte": integer,
  "bcr": [string],
  "bmi": [number],
  "bmi_gte": number,
  "bmi_lte": number,
  "case_barcode": [string],
  "case_gdc_id": [string],
  "clinical_M": [string],
  "clinical_N": [string],
  "clinical_stage": [string],
  "clinical_T": [string],
  "colorectal_cancer": [string],
  "country": [string],
  "days_to_birth": [integer],
  "days_to_birth_gte": integer,
  "days_to_birth_lte": integer,
  "days_to_collection": [integer],
  "days_to_collection_gte": integer,
  "days_to_collection_lte": integer,
  "days_to_death": [integer],
  "days_to_death_gte": integer,
  "days_to_death_lte": integer,
  "days_to_initial_pathologic_diagnosis": [integer],
  "days_to_initial_pathologic_diagnosis_gte": integer,
  "days_to_initial_pathologic_diagnosis_lte": integer,
  "days_to_last_followup": [integer],
  "days_to_last_followup_gte": integer,
  "days_to_last_followup_lte": integer,
  "days_to_last_known_alive": [integer],
  "days_to_last_known_alive_gte": integer,
  "days_to_last_known_alive_lte": integer,
  "days_to_sample_procurement": [integer],
  "days_to_sample_procurement_gte": integer,
  "days_to_sample_procurement_lte": integer,
  "days_to_submitted_specimen_dx": [integer],
  "days_to_submitted_specimen_dx_gte": integer,
  "days_to_submitted_specimen_dx_lte": integer,
  "disease_code": [string],
  "endpoint_type": [string],
  "ethnicity": [string],
  "gender": [string],
  "gleason_score_combined": [integer],
  "gleason_score_combined_gte": integer,
  "gleason_score_combined_lte": integer,
  "h_pylori_infection": [string],
  "height": [integer],
  "height_gte": integer,
  "height_lte": integer,
  "histological_type": [string],
  "history_of_colon_polyps": [string],
  "history_of_neoadjuvant_treatment": [string],
  "hpv_calls": [string],
  "hpv_status": [string],
  "icd_10": [string],
  "icd_o_3_histology": [string],
  "icd_o_3_site": [string],
  "lymphatic_invasion": [string],
  "lymphnodes_examined": [string],
  "lymphovascular_invasion_present": [string],
  "max_percent_lymphocyte_infiltration": [number],
  "max_percent_lymphocyte_infiltration_gte": number,
  "max_percent_lymphocyte_infiltration_lte": number,
  "max_percent_monocyte_infiltration": [number],
  "max_percent_monocyte_infiltration_gte": number,
  "max_percent_monocyte_infiltration_lte": number,
  "max_percent_necrosis": [number],
  "max_percent_necrosis_gte": number,
  "max_percent_necrosis_lte": number,
  "max_percent_neutrophil_infiltration": [number],
  "max_percent_neutrophil_infiltration_gte": number,
  "max_percent_neutrophil_infiltration_lte": number,
  "max_percent_normal_cells": [number],
  "max_percent_normal_cells_gte": number,
  "max_percent_normal_cells_lte": number,
  "max_percent_stromal_cells": [number],
  "max_percent_stromal_cells_gte": number,
  "max_percent_stromal_cells_lte": number,
  "max_percent_tumor_cells": [number],
  "max_percent_tumor_cells_gte": number,
  "max_percent_tumor_cells_lte": number,
  "max_percent_tumor_nuclei": [number],
  "max_percent_tumor_nuclei_gte": number,
  "max_percent_tumor_nuclei_lte": number,
  "menopause_status": [string],
  "min_percent_lymphocyte_infiltration": [number],
  "min_percent_lymphocyte_infiltration_gte": number,
  "min_percent_lymphocyte_infiltration_lte": number,
  "min_percent_monocyte_infiltration": [number],
  "min_percent_monocyte_infiltration_gte": number,
  "min_percent_monocyte_infiltration_lte": number,
  "min_percent_necrosis": [number],
  "min_percent_necrosis_gte": number,
  "min_percent_necrosis_lte": number,
  "min_percent_neutrophil_infiltration": [number],
  "min_percent_neutrophil_infiltration_gte": number,
  "min_percent_neutrophil_infiltration_lte": number,
  "min_percent_normal_cells": [number],
  "min_percent_normal_cells_gte": number,
  "min_percent_normal_cells_lte": number,
  "min_percent_stromal_cells": [number],
  "min_percent_stromal_cells_gte": number,
  "min_percent_stromal_cells_lte": number,
  "min_percent_tumor_cells": [number],
  "min_percent_tumor_cells_gte": number,
  "min_percent_tumor_cells_lte": number,
  "min_percent_tumor_nuclei": [number],
  "min_percent_tumor_nuclei_gte": number,
  "min_percent_tumor_nuclei_lte": number,
  "mononucleotide_and_dinucleotide_marker_panel_analysis_status": [string],
  "neoplasm_histologic_grade": [string],
  "new_tumor_event_after_initial_treatment": [string],
  "num_portions": [integer],
  "num_portions_gte": integer,
  "num_portions_lte": integer,
  "num_slides": [integer],
  "num_slides_gte": integer,
  "num_slides_lte": integer,
  "number_of_lymphnodes_examined": [integer],
  "number_of_lymphnodes_examined_gte": integer,
  "number_of_lymphnodes_examined_lte": integer,
  "number_of_lymphnodes_positive_by_he": [integer],
  "number_of_lymphnodes_positive_by_he_gte": integer,
  "number_of_lymphnodes_positive_by_he_lte": integer,
  "number_pack_years_smoked": [integer],
  "number_pack_years_smoked_gte": integer,
  "number_pack_years_smoked_lte": integer,
  "other_dx": [string],
  "other_malignancy_anatomic_site": [string],
  "other_malignancy_histological_type": [string],
  "other_malignancy_type": [string],
  "pathologic_M": [string],
  "pathologic_N": [string],
  "pathologic_stage": [string],
  "pathologic_T": [string],
  "pathology_report_uuid": [string],
  "person_neoplasm_cancer_status": [string],
  "pregnancies": [string],
  "preservation_method": [string],
  "primary_neoplasm_melanoma_dx": [string],
  "primary_therapy_outcome_success": [string],
  "program_name": [string],
  "project_short_name": [string],
  "psa_value": [number],
  "psa_value_gte": number,
  "psa_value_lte": number,
  "race": [string],
  "residual_tumor": [string],
  "sample_barcode": [string],
  "sample_gdc_id": [string],
  "sample_type": [string],
  "stopped_smoking_year": [integer],
  "stopped_smoking_year_gte": integer,
  "stopped_smoking_year_lte": integer,
  "summary_file_count": [integer],
  "summary_file_count_gte": integer,
  "summary_file_count_lte": integer,
  "tobacco_smoking_history": [string],
  "tss_code": [string],
  "tumor_tissue_site": [string],
  "tumor_type": [string],
  "venous_invasion": [string],
  "vital_status": [string],
  "weight": [integer],
  "weight_gte": integer,
  "weight_lte": integer,
  "year_of_diagnosis": [integer],
  "year_of_diagnosis_gte": integer,
  "year_of_diagnosis_lte": integer,
  "year_of_tobacco_smoking_onset": [integer],
  "year_of_tobacco_smoking_onset_gte": integer,
  "year_of_tobacco_smoking_onset_lte": integer
}
Parameter name Value Description
age_at_diagnosis[] list Optional.
age_at_diagnosis_gte integer Optional.
age_at_diagnosis_lte integer Optional.
age_began_smoking_in_years[] list Optional.
age_began_smoking_in_years_gte integer Optional.
age_began_smoking_in_years_lte integer Optional.
anatomic_neoplasm_subdivision[] list Optional. Possible values include: ‘Alveolar Ridge’, ‘Antrum/Distal’, ‘Ascending Colon’, ‘Base of tongue’, ‘Bilateral’, ‘Bladder - NOS’, ‘Body of Pancreas’, ‘Bronchial’, ‘Buccal Mucosa’, ‘Cardia/Proximal’, ‘Cecum’, ‘Descending Colon’, ‘Dome’, ‘Endometrium’, ‘Floor of mouth’, ‘Fundus uteri’, ‘Fundus/Body’, ‘Gastroesophageal Junction’, ‘Hard Palate’, ‘Head of Pancreas’, ‘Hepatic Flexure’, ‘Hypopharynx’, ‘L-Lower’, ‘L-Upper’, ‘Larynx’, ‘Left’, ‘Left Lower Inner Quadrant’, ‘Left Lower Outer Quadrant’, ‘Left Upper Inner Quadrant’, ‘Left Upper Outer Quadrant’, ‘Lip’, ‘Lower uterine segment/Isthmus uteri’, ‘Myometrium’, ‘Neck’, ‘Oral Cavity’, ‘Oral Tongue’, ‘Oropharynx’, ‘Other (please specify)’, ‘R-Lower’, ‘R-Middle’, ‘R-Upper’, ‘Rectosigmoid Junction’, ‘Rectum’, ‘Right’, ‘Right Lower Inner Quadrant’, ‘Right Lower Outer Quadrant’, ‘Right Upper Inner Quadrant’, ‘Right Upper Outer Quadrant’, ‘Sigmoid Colon’, ‘Splenic Flexure’, ‘Stomach (NOS)’, ‘Tail of Pancreas’, ‘Tonsil’, ‘Transverse Colon’, ‘Trigone’, ‘Unknown - Uterus NOS’, ‘Wall Anterior’, ‘Wall Lateral’, ‘Wall NOS’, ‘Wall Posterior’.
avg_percent_lymphocyte_infiltration[] list Optional.
avg_percent_lymphocyte_infiltration_gte number Optional.
avg_percent_lymphocyte_infiltration_lte number Optional.
avg_percent_monocyte_infiltration[] list Optional.
avg_percent_monocyte_infiltration_gte number Optional.
avg_percent_monocyte_infiltration_lte number Optional.
avg_percent_necrosis[] list Optional.
avg_percent_necrosis_gte number Optional.
avg_percent_necrosis_lte number Optional.
avg_percent_neutrophil_infiltration[] list Optional.
avg_percent_neutrophil_infiltration_gte number Optional.
avg_percent_neutrophil_infiltration_lte number Optional.
avg_percent_normal_cells[] list Optional.
avg_percent_normal_cells_gte number Optional.
avg_percent_normal_cells_lte number Optional.
avg_percent_stromal_cells[] list Optional.
avg_percent_stromal_cells_gte number Optional.
avg_percent_stromal_cells_lte number Optional.
avg_percent_tumor_cells[] list Optional.
avg_percent_tumor_cells_gte number Optional.
avg_percent_tumor_cells_lte number Optional.
avg_percent_tumor_nuclei[] list Optional.
avg_percent_tumor_nuclei_gte number Optional.
avg_percent_tumor_nuclei_lte number Optional.
batch_number[] list Optional.
batch_number_gte integer Optional.
batch_number_lte integer Optional.
bcr[] list Optional. Possible values include: ‘Nationwide Children’s Hospital’, ‘Washington University’.
bmi[] list Optional.
bmi_gte number Optional.
bmi_lte number Optional.
case_barcode[] list Optional.
case_gdc_id[] list Optional.
clinical_M[] list Optional. Possible values include: ‘M0’, ‘M1’, ‘M1a’, ‘M1b’, ‘M1c’, ‘MX’.
clinical_N[] list Optional. Possible values include: ‘N0’, ‘N1’, ‘N2’, ‘N2a’, ‘N2b’, ‘N2c’, ‘N3’, ‘NX’.
clinical_stage[] list Optional. Possible values include: ‘Stage I’, ‘Stage IA’, ‘Stage IA1’, ‘Stage IA2’, ‘Stage IB’, ‘Stage IB1’, ‘Stage IB2’, ‘Stage IC’, ‘Stage II’, ‘Stage IIA’, ‘Stage IIA1’, ‘Stage IIA2’, ‘Stage IIB’, ‘Stage IIC’, ‘Stage III’, ‘Stage IIIA’, ‘Stage IIIB’, ‘Stage IIIC’, ‘Stage IIIC1’, ‘Stage IIIC2’, ‘Stage IS’, ‘Stage IV’, ‘Stage IVA’, ‘Stage IVB’, ‘Stage IVC’.
clinical_T[] list Optional. Possible values include: ‘T1’, ‘T1a’, ‘T1b’, ‘T1c’, ‘T2’, ‘T2a’, ‘T2b’, ‘T2c’, ‘T3’, ‘T3a’, ‘T3b’, ‘T4’, ‘T4a’, ‘T4b’, ‘T4c’, ‘T4d’, ‘T4e’, ‘TX’.
colorectal_cancer[] list Optional. Possible values include: ‘NO’, ‘YES’.
country[] list Optional. Possible values include: ‘Afghanistan’, ‘Algeria’, ‘American Samoa’, ‘Australia’, ‘Brazil’, ‘Bulgaria’, ‘Canada’, ‘Croatia’, ‘Czech Republic’, ‘France’, ‘Georgia’, ‘Germany’, ‘Hamburg/Germany’, ‘Israel’, ‘Italy’, ‘Korea’, ‘Korea South’, ‘Moldova’, ‘Netherlands’, ‘Nigeria’, ‘Ontario Canada’, ‘Ontario/Canada’, ‘Pakistan’, ‘Poland’, ‘Puerto Rico’, ‘Republic of Moldova’, ‘Romania’, ‘Russia’, ‘Sao Paulo’, ‘Singapore’, ‘Spain’, ‘Switzerland’, ‘Ukraine’, ‘United Kingdom’, ‘United States’, ‘Vietnam’, ‘Yemen’.
days_to_birth[] list Optional.
days_to_birth_gte integer Optional.
days_to_birth_lte integer Optional.
days_to_collection[] list Optional.
days_to_collection_gte integer Optional.
days_to_collection_lte integer Optional.
days_to_death[] list Optional.
days_to_death_gte integer Optional.
days_to_death_lte integer Optional.
days_to_initial_pathologic_diagnosis[] list Optional.
days_to_initial_pathologic_diagnosis_gte integer Optional.
days_to_initial_pathologic_diagnosis_lte integer Optional.
days_to_last_followup[] list Optional.
days_to_last_followup_gte integer Optional.
days_to_last_followup_lte integer Optional.
days_to_last_known_alive[] list Optional.
days_to_last_known_alive_gte integer Optional.
days_to_last_known_alive_lte integer Optional.
days_to_sample_procurement[] list Optional.
days_to_sample_procurement_gte integer Optional.
days_to_sample_procurement_lte integer Optional.
days_to_submitted_specimen_dx[] list Optional.
days_to_submitted_specimen_dx_gte integer Optional.
days_to_submitted_specimen_dx_lte integer Optional.
disease_code[] list Optional. Possible values include: ‘ACC’, ‘BLCA’, ‘BRCA’, ‘CESC’, ‘CHOL’, ‘COAD’, ‘DLBC’, ‘ESCA’, ‘GBM’, ‘HNSC’, ‘KICH’, ‘KIRC’, ‘KIRP’, ‘LAML’, ‘LGG’, ‘LIHC’, ‘LUAD’, ‘LUSC’, ‘MESO’, ‘OV’, ‘PAAD’, ‘PCPG’, ‘PRAD’, ‘READ’, ‘SARC’, ‘SKCM’, ‘STAD’, ‘TGCT’, ‘THCA’, ‘THYM’, ‘UCEC’, ‘UCS’, ‘UVM’.
endpoint_type[] list Optional. Possible values include: ‘current’, ‘legacy’.
ethnicity[] list Optional. Possible values include: ‘HISPANIC OR LATINO’, ‘NOT HISPANIC OR LATINO’.
gender[] list Optional. Possible values include: ‘FEMALE’, ‘MALE’.
gleason_score_combined[] list Optional.
gleason_score_combined_gte integer Optional.
gleason_score_combined_lte integer Optional.
h_pylori_infection[] list Optional. Possible values include: ‘Current’, ‘Never’, ‘No’, ‘Yes’.
height[] list Optional.
height_gte integer Optional.
height_lte integer Optional.
histological_type[] list Optional.
history_of_colon_polyps[] list Optional. Possible values include: ‘NO’, ‘YES’.
history_of_neoadjuvant_treatment[] list Optional. Possible values include: ‘No’, ‘Yes’, ‘Yes, Pharmaceutical Treatment Prior to Resection’, ‘Yes, Radiation Prior to Resection’.
hpv_calls[] list Optional. Possible values include: ‘HPV16’, ‘HPV16;HPV18’, ‘HPV16;HPV18;HPV58’, ‘HPV16;HPV31’, ‘HPV16;HPV33’, ‘HPV16;HPV35’, ‘HPV16;HPV39’, ‘HPV16;HPV52’, ‘HPV16;HPV66’, ‘HPV18’, ‘HPV18;HPV31’, ‘HPV31’, ‘HPV33’, ‘HPV35’, ‘HPV39’, ‘HPV45’, ‘HPV51’, ‘HPV52’, ‘HPV56’, ‘HPV58’, ‘HPV59’, ‘HPV68’, ‘HPV73’.
hpv_status[] list Optional. Possible values include: ‘Indeterminate’, ‘Negative’, ‘Positive’.
icd_10[] list Optional.
icd_o_3_histology[] list Optional.
icd_o_3_site[] list Optional.
lymphatic_invasion[] list Optional. Possible values include: ‘NO’, ‘YES’.
lymphnodes_examined[] list Optional. Possible values include: ‘NO’, ‘YES’.
lymphovascular_invasion_present[] list Optional. Possible values include: ‘NO’, ‘YES’.
max_percent_lymphocyte_infiltration[] list Optional.
max_percent_lymphocyte_infiltration_gte number Optional.
max_percent_lymphocyte_infiltration_lte number Optional.
max_percent_monocyte_infiltration[] list Optional.
max_percent_monocyte_infiltration_gte number Optional.
max_percent_monocyte_infiltration_lte number Optional.
max_percent_necrosis[] list Optional.
max_percent_necrosis_gte number Optional.
max_percent_necrosis_lte number Optional.
max_percent_neutrophil_infiltration[] list Optional.
max_percent_neutrophil_infiltration_gte number Optional.
max_percent_neutrophil_infiltration_lte number Optional.
max_percent_normal_cells[] list Optional.
max_percent_normal_cells_gte number Optional.
max_percent_normal_cells_lte number Optional.
max_percent_stromal_cells[] list Optional.
max_percent_stromal_cells_gte number Optional.
max_percent_stromal_cells_lte number Optional.
max_percent_tumor_cells[] list Optional.
max_percent_tumor_cells_gte number Optional.
max_percent_tumor_cells_lte number Optional.
max_percent_tumor_nuclei[] list Optional.
max_percent_tumor_nuclei_gte number Optional.
max_percent_tumor_nuclei_lte number Optional.
menopause_status[] list Optional. Possible values include: ‘Indeterminate (neither Pre or Postmenopausal)’, ‘Peri (6-12 months since last menstrual period)’, ‘Post (prior bilateral ovariectomy OR >12 mo since LMP with no prior hysterectomy)’, ‘Pre (<6 months since LMP AND no prior bilateral ovariectomy AND not on estrogen replacement)’.
min_percent_lymphocyte_infiltration[] list Optional.
min_percent_lymphocyte_infiltration_gte number Optional.
min_percent_lymphocyte_infiltration_lte number Optional.
min_percent_monocyte_infiltration[] list Optional.
min_percent_monocyte_infiltration_gte number Optional.
min_percent_monocyte_infiltration_lte number Optional.
min_percent_necrosis[] list Optional.
min_percent_necrosis_gte number Optional.
min_percent_necrosis_lte number Optional.
min_percent_neutrophil_infiltration[] list Optional.
min_percent_neutrophil_infiltration_gte number Optional.
min_percent_neutrophil_infiltration_lte number Optional.
min_percent_normal_cells[] list Optional.
min_percent_normal_cells_gte number Optional.
min_percent_normal_cells_lte number Optional.
min_percent_stromal_cells[] list Optional.
min_percent_stromal_cells_gte number Optional.
min_percent_stromal_cells_lte number Optional.
min_percent_tumor_cells[] list Optional.
min_percent_tumor_cells_gte number Optional.
min_percent_tumor_cells_lte number Optional.
min_percent_tumor_nuclei[] list Optional.
min_percent_tumor_nuclei_gte number Optional.
min_percent_tumor_nuclei_lte number Optional.
mononucleotide_and_dinucleotide_marker_panel_analysis_status[] list Optional. Possible values include: ‘Indeterminate’, ‘MSI-H’, ‘MSI-L’, ‘MSS’, ‘Not Tested’.
neoplasm_histologic_grade[] list Optional. Possible values include: ‘G1’, ‘G2’, ‘G3’, ‘G4’, ‘GB’, ‘GX’, ‘High Grade’, ‘Low Grade’.
new_tumor_event_after_initial_treatment[] list Optional. Possible values include: ‘NO’, ‘YES’.
num_portions[] list Optional.
num_portions_gte integer Optional.
num_portions_lte integer Optional.
num_slides[] list Optional.
num_slides_gte integer Optional.
num_slides_lte integer Optional.
number_of_lymphnodes_examined[] list Optional.
number_of_lymphnodes_examined_gte integer Optional.
number_of_lymphnodes_examined_lte integer Optional.
number_of_lymphnodes_positive_by_he[] list Optional.
number_of_lymphnodes_positive_by_he_gte integer Optional.
number_of_lymphnodes_positive_by_he_lte integer Optional.
number_pack_years_smoked[] list Optional.
number_pack_years_smoked_gte integer Optional.
number_pack_years_smoked_lte integer Optional.
other_dx[] list Optional. Possible values include: ‘Both History of Synchronous/ Bilateral and Prior Malignancy’, ‘No’, ‘Yes, History of Prior Malignancy’, ‘Yes, History of Synchronous/Bilateral Malignancy’.
other_malignancy_anatomic_site[] list Optional.
other_malignancy_histological_type[] list Optional. Possible values include: ‘Adenocarcinoma, Not Otherwise Specified’, ‘Adenocarcinoma, Not Otherwise Specified, Adenocarcinoma, Not Otherwise Specified’, ‘Adenocarcinoma, Not Otherwise Specified, Colon Adenocarcinoma’, ‘Adenocarcinoma, Not Otherwise Specified, Kidney Clear Cell Renal Carcinoma’, ‘Adenocarcinoma, Not Otherwise Specified, Lung Acinar Adenocarcinoma’, ‘Adenocarcinoma, Not Otherwise Specified, Other, specify’, ‘Adenocarcinoma, Not Otherwise Specified, Other, specify, Other, specify’, ‘Adenocarcinoma, Not Otherwise Specified, Squamous Cell Carcinoma, Not Otherwise Specified’, ‘Adenosquamous’, ‘Astrocytoma’, ‘Basaloid Squamous Cell’, ‘Basaloid Squamous Cell, Adenocarcinoma, Not Otherwise Specified’, ‘Clear Cell Adenocarcinoma’, ‘Clear Cell Squamous Cell’, ‘Colon Adenocarcinoma’, ‘Colon Adenocarcinoma, Colon Adenocarcinoma’, ‘Colon Mucinous Adenocarcinoma’, ‘Endometrioid endometrial adenocarcinoma (Grade 1 or 2)’, ‘Endometrioid endometrial adenocarcinoma (Grade 3)’, ‘Head & Neck Squamous Cell Carcinoma’, ‘Hepatocellular Carcinoma’, ‘Kidney Clear Cell Renal Carcinoma’, ‘Kidney Clear Cell Renal Carcinoma, Kidney Clear Cell Renal Carcinoma’, ‘Kidney Clear Cell Renal Carcinoma, Kidney Clear Cell Renal Carcinoma, Other, specify’, ‘Kidney Clear Cell Renal Carcinoma, Kidney Papillary Renal Cell Carcinoma’, ‘Kidney Clear Cell Renal Carcinoma, Other, specify’, ‘Kidney Papillary Renal Cell Carcinoma’, ‘Kidney Papillary Renal Cell Carcinoma, Kidney Papillary Renal Cell Carcinoma’, ‘Kidney Papillary Renal Cell Carcinoma, Kidney Papillary Renal Cell Carcinoma, Adenocarcinoma, Not Otherwise Specified’, ‘Lung Adenocarcinoma Mixed Subtype’, ‘Lung Adenocarcinoma- Not Otherwise Specified (NOS)’, ‘Lung Adenocarcinoma- Not Otherwise Specified (NOS), Adenocarcinoma, Not Otherwise Specified’, ‘Lung Bronchioloalveolar Carcinoma Nonmucinous’, ‘Lung Clear Cell Squamous Cell Carcinoma’, ‘Lung Clear Cell Squamous Cell Carcinoma, Other, specify’, ‘Lung Papillary Adenocarcinoma’, ‘Lung Small Cell Squamous Cell Carcinoma’, ‘Other, specify’, ‘Other, specify, Adenocarcinoma, Not Otherwise Specified’, ‘Other, specify, Adenocarcinoma, Not Otherwise Specified, Other, specify’, ‘Other, specify, Basaloid Squamous Cell’, ‘Other, specify, Clear Cell Adenocarcinoma’, ‘Other, specify, Kidney Papillary Renal Cell Carcinoma’, ‘Other, specify, Kidney Papillary Renal Cell Carcinoma, Kidney Papillary Renal Cell Carcinoma’, ‘Other, specify, Lung Mucinous Adenocarcinoma’, ‘Other, specify, Other, specify’, ‘Other, specify, Other, specify, Kidney Papillary Renal Cell Carcinoma’, ‘Other, specify, Other, specify, Other, specify’, ‘Other, specify, Other, specify, Other, specify, Other, specify’, ‘Other, specify, Other, specify, Squamous Cell Carcinoma, Not Otherwise Specified’, ‘Other, specify, Squamous Cell Carcinoma, Not Otherwise Specified’, ‘Papillary Squamous Cell’, ‘Rectal Adenocarcinoma’, ‘Small Cell Squamous Cell’, ‘Squamous Cell Carcinoma, Not Otherwise Specified’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Basaloid Squamous Cell’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Kidney Papillary Renal Cell Carcinoma’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Lung Adenocarcinoma Mixed Subtype’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Other, specify’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Other, specify, Other, specify’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Squamous Cell Carcinoma, Not Otherwise Specified’, ‘Squamous Cell Carcinoma, Not Otherwise Specified, Squamous Cell Carcinoma, Not Otherwise Specified, Basaloid Squamous Cell’, ‘Thyroid Papillary Carcinoma - Classical/usual’, ‘Thyroid Papillary Carcinoma - Classical/usual, Adenocarcinoma, Not Otherwise Specified’, ‘Thyroid Papillary Carcinoma - Follicular (>= 99% follicular patterned)’, ‘Thyroid Papillary Carcinoma - Other, specify’, ‘Thyroid Papillary Carcinoma - Other, specify, Thyroid Papillary Carcinoma - Other, specify, Other, specify’, ‘Uterine serous endometrial adenocarcinoma’.
other_malignancy_type[] list Optional. Possible values include: ‘Prior Malignancy’, ‘Prior Malignancy, Prior Malignancy’, ‘Prior Malignancy, Prior Malignancy, Prior Malignancy’, ‘Prior Malignancy, Prior Malignancy, Prior Malignancy, Synchronous Malignancy’, ‘Prior Malignancy, Prior Malignancy, Synchronous Malignancy’, ‘Prior Malignancy, Synchronous Malignancy’, ‘Prior Malignancy, Synchronous Malignancy, Prior Malignancy’, ‘Synchronous Malignancy’, ‘Synchronous Malignancy, Prior Malignancy’, ‘Synchronous Malignancy, Prior Malignancy, Prior Malignancy, Prior Malignancy’, ‘Synchronous Malignancy, Prior Malignancy, Synchronous Malignancy’, ‘Synchronous Malignancy, Synchronous Malignancy’, ‘Synchronous Malignancy, Synchronous Malignancy, Prior Malignancy’.
pathologic_M[] list Optional. Possible values include: ‘cM0 (i+)’, ‘M0’, ‘M1’, ‘M1a’, ‘M1b’, ‘M1c’, ‘MX’.
pathologic_N[] list Optional. Possible values include: ‘N0’, ‘N0 (i+)’, ‘N0 (i-)’, ‘N0 (mol+)’, ‘N1’, ‘N1a’, ‘N1b’, ‘N1c’, ‘N1mi’, ‘N2’, ‘N2a’, ‘N2b’, ‘N2c’, ‘N3’, ‘N3a’, ‘N3b’, ‘N3c’, ‘NX’.
pathologic_stage[] list Optional. Possible values include: ‘I/II NOS’, ‘IS’, ‘Stage 0’, ‘Stage I’, ‘Stage IA’, ‘Stage IB’, ‘Stage II’, ‘Stage IIA’, ‘Stage IIB’, ‘Stage IIC’, ‘Stage III’, ‘Stage IIIA’, ‘Stage IIIB’, ‘Stage IIIC’, ‘Stage IV’, ‘Stage IVA’, ‘Stage IVB’, ‘Stage IVC’, ‘Stage X’.
pathologic_T[] list Optional. Possible values include: ‘T0’, ‘T1’, ‘T1a’, ‘T1a1’, ‘T1b’, ‘T1b1’, ‘T1b2’, ‘T1c’, ‘T2’, ‘T2a’, ‘T2a1’, ‘T2a2’, ‘T2b’, ‘T2c’, ‘T3’, ‘T3a’, ‘T3b’, ‘T3c’, ‘T4’, ‘T4a’, ‘T4b’, ‘T4c’, ‘T4d’, ‘T4e’, ‘Tis’, ‘TX’.
pathology_report_uuid[] list Optional.
person_neoplasm_cancer_status[] list Optional. Possible values include: ‘TUMOR FREE’, ‘WITH TUMOR’.
pregnancies[] list Optional. Possible values include: ‘0’, ‘1’, ‘2’, ‘3’, ‘4+’.
preservation_method[] list Optional. Possible values include: ‘FFPE’, ‘frozen’.
primary_neoplasm_melanoma_dx[] list Optional. Possible values include: ‘NO’, ‘YES’.
primary_therapy_outcome_success[] list Optional. Possible values include: ‘Complete Remission/Response’, ‘No Measureable Tumor or Tumor Markers’, ‘Normalization of Tumor Markers, but Residual Tumor Mass’, ‘Partial Remission/Response’, ‘Persistent Disease’, ‘Progressive Disease’, ‘Stable Disease’.
program_name[] list Optional. Possible values include: ‘TCGA’.
project_short_name[] list Optional. Possible values include: ‘TCGA-ACC’, ‘TCGA-BLCA’, ‘TCGA-BRCA’, ‘TCGA-CESC’, ‘TCGA-CHOL’, ‘TCGA-COAD’, ‘TCGA-DLBC’, ‘TCGA-ESCA’, ‘TCGA-GBM’, ‘TCGA-HNSC’, ‘TCGA-KICH’, ‘TCGA-KIRC’, ‘TCGA-KIRP’, ‘TCGA-LAML’, ‘TCGA-LGG’, ‘TCGA-LIHC’, ‘TCGA-LUAD’, ‘TCGA-LUSC’, ‘TCGA-MESO’, ‘TCGA-OV’, ‘TCGA-PAAD’, ‘TCGA-PCPG’, ‘TCGA-PRAD’, ‘TCGA-READ’, ‘TCGA-SARC’, ‘TCGA-SKCM’, ‘TCGA-STAD’, ‘TCGA-TGCT’, ‘TCGA-THCA’, ‘TCGA-THYM’, ‘TCGA-UCEC’, ‘TCGA-UCS’, ‘TCGA-UVM’.
psa_value[] list Optional.
psa_value_gte number Optional.
psa_value_lte number Optional.
race[] list Optional. Possible values include: ‘AMERICAN INDIAN OR ALASKA NATIVE’, ‘ASIAN’, ‘BLACK OR AFRICAN AMERICAN’, ‘NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER’, ‘WHITE’.
residual_tumor[] list Optional. Possible values include: ‘R0’, ‘R1’, ‘R2’, ‘RX’.
sample_barcode[] list Optional.
sample_gdc_id[] list Optional.
sample_type[] list Optional. Possible values include: ‘01’, ‘02’, ‘03’, ‘05’, ‘06’, ‘07’, ‘10’, ‘11’, ‘12’, ‘14’.
stopped_smoking_year[] list Optional.
stopped_smoking_year_gte integer Optional.
stopped_smoking_year_lte integer Optional.
summary_file_count[] list Optional.
summary_file_count_gte integer Optional.
summary_file_count_lte integer Optional.
tobacco_smoking_history[] list Optional. Possible values include: ‘1’, ‘2’, ‘3’, ‘4’, ‘5’.
tss_code[] list Optional.
tumor_tissue_site[] list Optional.
tumor_type[] list Optional. Possible values include: ‘Primary’, ‘Type 1’, ‘Type 2’.
venous_invasion[] list Optional. Possible values include: ‘NO’, ‘YES’.
vital_status[] list Optional. Possible values include: ‘Alive’, ‘Dead’.
weight[] list Optional.
weight_gte integer Optional.
weight_lte integer Optional.
year_of_diagnosis[] list Optional.
year_of_diagnosis_gte integer Optional.
year_of_diagnosis_lte integer Optional.
year_of_tobacco_smoking_onset[] list Optional.
year_of_tobacco_smoking_onset_gte integer Optional.
year_of_tobacco_smoking_onset_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.

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