Clinical Data#

The module clinical_data provides functions related to Clinical Data section of cBioPortal Web Public API.

pybioportal.clinical_data.fetch_all_clinical_data_in_study(study_id, attribute_ids=[], ids=[], clinical_data_type='SAMPLE', projection='SUMMARY', ret_format='WIDE')#

Fetch clinical data by patient IDs or sample IDs in a specific study.

Parameters:

study_id (str) – Study ID (e.g., “acc_tcga”).
attribute_ids (list of str) – List of attribute IDs.
ids (list of str) – List of patient or sample IDs.
clinical_data_type (str) –
Type of clinical data.

Possible values:
- ”PATIENT”: Clinical data for patients.
- ”SAMPLE”: Clinical data for samples (default).
projection (str) –
Level of detail of the response.

Possible values:
- ”DETAILED”: Detailed information.
- ”ID”: Information with only IDs.
- ”META”: Metadata information.
- ”SUMMARY”: Summary information (default).
ret_format (str) –
Return format of the dataframe.

Possible values:
- ”LONG”: Long dataframe with repeated record for patient/sample.
- ”WIDE”: Wide dataframe with distinct record for patient/sample (default).

Returns:

A DataFrame containing clinical data in the specified study based on the provided filter.

Return type:

pandas.DataFrame

pybioportal.clinical_data.fetch_clinical_data(attribute_ids, entity_study_ids, clinical_data_type='SAMPLE', projection='SUMMARY', ret_format='WIDE')#

Fetch clinical data by patient IDs or sample IDs (all studies) from cBioPortal.

Parameters:

attribute_ids (list of str) –
List of attribute IDs.
- e.g. for PATIENT data type:
  
  [“SEX”, “RACE”]
- e.g. for SAMPLE data type:
  
  [“ORGAN_SYSTEM”, “SUBTYPE”]
entity_study_ids (list of dict) –
List of patient or sample identifiers and study IDs.

Each list should have the following format:
- e.g. for PATIENT data type:
  
  entity_study_ids = [
  
  {“entity_ids”: [“P-0000004”, “P-0000950”],
  “study”: “msk_met_2021”},
  
  {“entity_ids”: [“TCGA-5T-A9QA”, “TCGA-A1-A0SB”],
  “study”: “brca_tcga”}
  
  ]
- e.g. for SAMPLE data type:
  
  entity_study_ids = [
  
  {“entity_ids”: [“P-0000004-T01-IM3”, “P-0000950-T01-IM3”],
  “study”: “msk_met_2021”},
  
  {“entity_ids”: [“TCGA-5T-A9QA-01”, “TCGA-A1-A0SB-01”],
  “study”: “brca_tcga”}
  
  ]
clinical_data_type (str) –
Type of the clinical data.

Possible values:
- ”PATIENT”: Clinical data for patients.
- ”SAMPLE”: Clinical data for samples (default).
projection (str) –
Level of detail of the response.

Possible values:
- ”DETAILED”: Detailed information.
- ”ID”: Information with only IDs.
- ”META”: Metadata information.
- ”SUMMARY”: Summary information (default).
ret_format (str) –
Return format of the dataframe.

Possible values:
- ”LONG”: Long dataframe with repeated record for patient/sample.
- ”WIDE”: Wide dataframe with distinct record for patient/sample (default).

Returns:

A DataFrame containing the fetched clinical data.

Return type:

pandas.DataFrame

pybioportal.clinical_data.get_all_clinical_data_in_study(study_id, attribute_id=None, clinical_data_type='SAMPLE', direction='ASC', pageNumber=0, pageSize=10000000, projection='SUMMARY', sortBy=None)#

Get all clinical data in a study. n :param study_id: Study ID (e.g., “acc_tcga”).

Parameters:

attribute_id (str) – Attribute ID (e.g., “CANCER_TYPE”).
clinical_data_type (str) –
Type of clinical data.

Possible values:
- ”PATIENT”: Clinical data for patients.
- ”SAMPLE”: Clinical data for samples (default).
direction (str) –
Direction of the sort.

Possible values:
- ”ASC”: Ascending (default).
- ”DESC”: Descending.
pageNumber (int) –
Page number of the result list.
- Minimum value is 0.
pageSize (int) –
Page size of the result list.
- Minimum value is 1, maximum value is 10000000.
projection (str) –
Level of detail of the response.

Possible values:
- ”DETAILED”: Detailed information.
- ”ID”: Information with only IDs.
- ”META”: Metadata information.
- ”SUMMARY”: Summary information (default).
sortBy (str) –
Name of the property that the result list is sorted by.

Possible values:
- ”clinicalAttributeId”
- ”value”

Returns:

A DataFrame containing clinical data in the specified study.

Return type:

pandas.DataFrame

pybioportal.clinical_data.get_all_clinical_data_of_patient_in_study(study_id, patient_id, attributeId=None, direction='ASC', pageNumber=0, pageSize=10000000, projection='SUMMARY', sortBy=None)#

Get all clinical data of a patient in a study.

Parameters:

study_id (str) – Study ID (e.g., “acc_tcga”).
patient_id (str) – Patient ID (e.g., “TCGA-OR-A5J2”).
attributeId (str) – Attribute ID (e.g., “AGE”).
direction (str) –
Direction of the sort.

Possible values:
- ”ASC”: Ascending (default).
- ”DESC”: Descending.
pageNumber (int) –
Page number of the result list.
- Minimum value is 0.
pageSize (int) –
Page size of the result list.
- Minimum value is 1, maximum value is 10000000.
projection (str) –
Level of detail of the response.

Possible values:
- ”DETAILED”: Detailed information.
- ”ID”: Information with only IDs.
- ”META”: Metadata information.
- ”SUMMARY”: Summary information (default).
sortBy (str) –
Name of the property that the result list is sorted by.

Possible values:
- ”clinicalAttributeId”
- ”value”

Returns:

A DataFrame containing clinical data of the specified patient in the study.

Return type:

pandas.DataFrame

pybioportal.clinical_data.get_all_clinical_data_of_sample_in_study(study_id, sample_id, attribute_id=None, direction='ASC', pageNumber=0, pageSize=10000000, projection='SUMMARY', sortBy=None)#

Get all clinical data of a sample in a study.

Parameters:

study_id (str) – Study ID (e.g., “acc_tcga”).
sample_id (str) – Sample ID (e.g., “TCGA-OR-A5J2-01”).
attributeId (str) – Attribute ID (e.g., “CANCER_TYPE”).
direction (str) –
Direction of the sort.

Possible values:
- ”ASC”: Ascending (default).
- ”DESC”: Descending.
pageNumber (int) –
Page number of the result list.
- Minimum value is 0.
pageSize (int) –
Page size of the result list.
- Minimum value is 1, maximum value is 10000000.
projection (str) –
Level of detail of the response.

Possible values:
- ”DETAILED”: Detailed information.
- ”ID”: Information with only IDs.
- ”META”: Metadata information.
- ”SUMMARY”: Summary information (default).
sortBy (str) –
Name of the property that the result list is sorted by.

Possible values:
- ”clinicalAttributeId”
- ”value”

Returns:

A DataFrame containing clinical data for the specified sample in the study.

Return type:

pandas.DataFrame

Examples#

from pybioportal import clinical_data as cd

df1a = cd.fetch_clinical_data(attribute_ids=["SEX", "RACE"],
                              entity_study_ids=[
                                      {"entity_ids": ["P-0000004", "P-0000950"], "study": "msk_met_2021"},
                                      {"entity_ids": ["TCGA-5T-A9QA", "TCGA-A1-A0SB"], "study": "brca_tcga"}
                              ],
                              clinical_data_type="PATIENT", ret_format="LONG")
df1a

	uniquePatientKey	patientId	studyId	clinicalAttributeId	value
0	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB	brca_tcga	RACE	WHITE
1	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB	brca_tcga	SEX	Female
2	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	RACE	BLACK OR AFRICAN AMERICAN
3	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	SEX	Female
4	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004	msk_met_2021	RACE	White
5	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004	msk_met_2021	SEX	Female
6	UC0wMDAwOTUwOm1za19tZXRfMjAyMQ	P-0000950	msk_met_2021	RACE	Other
7	UC0wMDAwOTUwOm1za19tZXRfMjAyMQ	P-0000950	msk_met_2021	SEX	Male

df1b = cd.fetch_clinical_data(attribute_ids=["ORGAN_SYSTEM", "SUBTYPE", "CANCER_TYPE", "MUTATION_COUNT"],
                              entity_study_ids=[
                                      {"entity_ids": ["P-0000004-T01-IM3", "P-0000950-T01-IM3"], "study": "msk_met_2021"},
                                      {"entity_ids": ["TCGA-5T-A9QA-01", "TCGA-A1-A0SB-01"], "study": "brca_tcga"}
                              ],
                              clinical_data_type="SAMPLE", ret_format="WIDE")
df1b

clinicalAttributeId	uniqueSampleKey	uniquePatientKey	sampleId	patientId	studyId	CANCER_TYPE	MUTATION_COUNT	ORGAN_SYSTEM	SUBTYPE
0	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	Breast Cancer	4	Breast	Breast Ductal HR+HER2-
1	UC0wMDAwOTUwLVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwOTUwOm1za19tZXRfMjAyMQ	P-0000950-T01-IM3	P-0000950	msk_met_2021	Small Bowel Cancer	12	Core GI	Small Bowel cancer
2	VENHQS01VC1BOVFBLTAxOmJyY2FfdGNnYQ	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA-01	TCGA-5T-A9QA	brca_tcga	Breast Cancer	NaN	NaN	NaN
3	VENHQS1BMS1BMFNCLTAxOmJyY2FfdGNnYQ	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB-01	TCGA-A1-A0SB	brca_tcga	Breast Cancer	16	NaN	NaN

df2a = cd.get_all_clinical_data_in_study("acc_tcga", clinical_data_type="PATIENT")
df2a

	uniquePatientKey	patientId	studyId	clinicalAttributeId	value
0	VENHQS1PUi1BNUoxOmFjY190Y2dh	TCGA-OR-A5J1	acc_tcga	AGE	58
1	VENHQS1PUi1BNUoxOmFjY190Y2dh	TCGA-OR-A5J1	acc_tcga	AJCC_PATHOLOGIC_TUMOR_STAGE	Stage II
2	VENHQS1PUi1BNUoxOmFjY190Y2dh	TCGA-OR-A5J1	acc_tcga	ATYPICAL_MITOTIC_FIGURES	Atypical Mitotic Figures Absent
3	VENHQS1PUi1BNUoxOmFjY190Y2dh	TCGA-OR-A5J1	acc_tcga	CAPSULAR_INVASION	Invasion of Tumor Capsule Absent
4	VENHQS1PUi1BNUoxOmFjY190Y2dh	TCGA-OR-A5J1	acc_tcga	CLIN_M_STAGE	M0
...	...	...	...	...	...
4729	VENHQS1QSy1BNUhDOmFjY190Y2dh	TCGA-PK-A5HC	acc_tcga	SITE_OF_TUMOR_TISSUE	Adrenal
4730	VENHQS1QSy1BNUhDOmFjY190Y2dh	TCGA-PK-A5HC	acc_tcga	TISSUE_SOURCE_SITE	PK
4731	VENHQS1QSy1BNUhDOmFjY190Y2dh	TCGA-PK-A5HC	acc_tcga	TREATMENT_OUTCOME_FIRST_COURSE	Complete Remission/Response
4732	VENHQS1QSy1BNUhDOmFjY190Y2dh	TCGA-PK-A5HC	acc_tcga	TUMOR_STATUS	WITH TUMOR
4733	VENHQS1QSy1BNUhDOmFjY190Y2dh	TCGA-PK-A5HC	acc_tcga	WEISS_VENOUS_INVASION	Venous Invasion Present

4734 rows × 5 columns

df2b = cd.get_all_clinical_data_in_study("brca_tcga", attribute_id="MUTATION_COUNT")
df2b

	uniqueSampleKey	uniquePatientKey	sampleId	patientId	studyId	clinicalAttributeId	value
0	VENHQS1BUi1BMUFSLTAxOmJyY2FfdGNnYQ	VENHQS1BUi1BMUFSOmJyY2FfdGNnYQ	TCGA-AR-A1AR-01	TCGA-AR-A1AR	brca_tcga	MUTATION_COUNT	40
1	VENHQS1CSC1BMUVPLTAxOmJyY2FfdGNnYQ	VENHQS1CSC1BMUVPOmJyY2FfdGNnYQ	TCGA-BH-A1EO-01	TCGA-BH-A1EO	brca_tcga	MUTATION_COUNT	27
2	VENHQS1CSC1BMUVTLTAxOmJyY2FfdGNnYQ	VENHQS1CSC1BMUVTOmJyY2FfdGNnYQ	TCGA-BH-A1ES-01	TCGA-BH-A1ES	brca_tcga	MUTATION_COUNT	15
3	VENHQS1CSC1BMUVTLTA2OmJyY2FfdGNnYQ	VENHQS1CSC1BMUVTOmJyY2FfdGNnYQ	TCGA-BH-A1ES-06	TCGA-BH-A1ES	brca_tcga	MUTATION_COUNT	23
4	VENHQS1CSC1BMUVULTAxOmJyY2FfdGNnYQ	VENHQS1CSC1BMUVUOmJyY2FfdGNnYQ	TCGA-BH-A1ET-01	TCGA-BH-A1ET	brca_tcga	MUTATION_COUNT	16
...	...	...	...	...	...	...	...
977	VENHQS1FMi1BMUI0LTAxOmJyY2FfdGNnYQ	VENHQS1FMi1BMUI0OmJyY2FfdGNnYQ	TCGA-E2-A1B4-01	TCGA-E2-A1B4	brca_tcga	MUTATION_COUNT	27
978	VENHQS1FMi1BMUI1LTAxOmJyY2FfdGNnYQ	VENHQS1FMi1BMUI1OmJyY2FfdGNnYQ	TCGA-E2-A1B5-01	TCGA-E2-A1B5	brca_tcga	MUTATION_COUNT	12
979	VENHQS1FMi1BMUI2LTAxOmJyY2FfdGNnYQ	VENHQS1FMi1BMUI2OmJyY2FfdGNnYQ	TCGA-E2-A1B6-01	TCGA-E2-A1B6	brca_tcga	MUTATION_COUNT	7
980	VENHQS1FMi1BMUJDLTAxOmJyY2FfdGNnYQ	VENHQS1FMi1BMUJDOmJyY2FfdGNnYQ	TCGA-E2-A1BC-01	TCGA-E2-A1BC	brca_tcga	MUTATION_COUNT	24
981	VENHQS1FMi1BMUJELTAxOmJyY2FfdGNnYQ	VENHQS1FMi1BMUJEOmJyY2FfdGNnYQ	TCGA-E2-A1BD-01	TCGA-E2-A1BD	brca_tcga	MUTATION_COUNT	23

982 rows × 7 columns

df3a = cd.fetch_all_clinical_data_in_study(study_id="brca_tcga",
                                           attribute_ids=["SEX", "RACE"],
                                           ids=["TCGA-5T-A9QA", "TCGA-A1-A0SB"],
                                           clinical_data_type="PATIENT", ret_format="LONG")
df3a

	uniquePatientKey	patientId	studyId	clinicalAttributeId	value
0	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB	brca_tcga	RACE	WHITE
1	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB	brca_tcga	SEX	Female
2	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	RACE	BLACK OR AFRICAN AMERICAN
3	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	SEX	Female

df3b = cd.fetch_all_clinical_data_in_study(study_id="brca_tcga",
                                           ids=["TCGA-5T-A9QA", "TCGA-A1-A0SB"],
                                           clinical_data_type="PATIENT", ret_format="WIDE")
df3b

clinicalAttributeId	uniquePatientKey	patientId	studyId	AGE	AJCC_METASTASIS_PATHOLOGIC_PM	AJCC_NODES_PATHOLOGIC_PN	AJCC_PATHOLOGIC_TUMOR_STAGE	AJCC_STAGING_EDITION	AJCC_TUMOR_PATHOLOGIC_PT	DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS	...	PR_STATUS_BY_IHC	RACE	RETROSPECTIVE_COLLECTION	SAMPLE_COUNT	SEX	SITE_OF_TUMOR_TISSUE	STAGING_SYSTEM	SURGICAL_PROCEDURE_FIRST	TISSUE_SOURCE_SITE	TUMOR_STATUS
0	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	52	MX	NX	Stage IIA	7th	T2	0	...	Negative	BLACK OR AFRICAN AMERICAN	NO	1	Female	Breast	No axillary staging	NaN	5T	NaN
1	VENHQS1BMS1BMFNCOmJyY2FfdGNnYQ	TCGA-A1-A0SB	brca_tcga	70	M0	N0	Stage I	6th	T1c	0	...	Negative	WHITE	YES	1	Female	Breast	Sentinel node biopsy alone	Lumpectomy	A1	TUMOR FREE

2 rows × 54 columns

df3c = cd.fetch_all_clinical_data_in_study(study_id="msk_met_2021",
                                           attribute_ids=["CANCER_TYPE", "MUTATION_COUNT"],
                                           ids=["P-0000004-T01-IM3", "P-0000950-T01-IM3"],
                                           clinical_data_type="SAMPLE", ret_format="WIDE")
df3c

clinicalAttributeId	uniqueSampleKey	uniquePatientKey	sampleId	patientId	studyId	CANCER_TYPE	MUTATION_COUNT
0	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	Breast Cancer	4
1	UC0wMDAwOTUwLVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwOTUwOm1za19tZXRfMjAyMQ	P-0000950-T01-IM3	P-0000950	msk_met_2021	Small Bowel Cancer	12

df4 = cd.get_all_clinical_data_of_patient_in_study(study_id="brca_tcga", patient_id="TCGA-5T-A9QA")
df4

	uniquePatientKey	patientId	studyId	clinicalAttributeId	value
0	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AGE	52
1	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AJCC_METASTASIS_PATHOLOGIC_PM	MX
2	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AJCC_NODES_PATHOLOGIC_PN	NX
3	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AJCC_PATHOLOGIC_TUMOR_STAGE	Stage IIA
4	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AJCC_STAGING_EDITION	7th
5	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	AJCC_TUMOR_PATHOLOGIC_PT	T2
6	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS	0
7	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	DFS_MONTHS	9.95
8	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	DFS_STATUS	0:DiseaseFree
9	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ER_POSITIVITY_SCALE_USED	3 Point Scale
10	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ER_STATUS_BY_IHC	Positive
11	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ER_STATUS_IHC_PERCENT_POSITIVE	70-79%
12	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ETHNICITY	NOT HISPANIC OR LATINO
13	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	FORM_COMPLETION_DATE	12/23/13
14	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HER2_FISH_STATUS	Negative
15	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HER2_IHC_PERCENT_POSITIVE	10-19%
16	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HER2_IHC_SCORE	2
17	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HISTOLOGICAL_DIAGNOSIS	Other, specify
18	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HISTORY_NEOADJUVANT_TRTYN	No
19	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	HISTORY_OTHER_MALIGNANCY	No
20	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ICD_10	C50.9
21	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ICD_O_3_HISTOLOGY	8523/3
22	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	ICD_O_3_SITE	C50.9
23	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	IHC_HER2	Equivocal
24	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	IHC_SCORE	2
25	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	INFORMED_CONSENT_VERIFIED	YES
26	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	INITIAL_PATHOLOGIC_DX_YEAR	2013
27	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	LYMPH_NODES_EXAMINED	NO
28	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	METHOD_OF_INITIAL_SAMPLE_PROCUREMENT	Excisional Biopsy
29	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	MICROMET_DETECTION_BY_IHC	NO
30	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	NEW_TUMOR_EVENT_AFTER_INITIAL_TREATMENT	NO
31	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	OS_MONTHS	9.95
32	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	OS_STATUS	0:LIVING
33	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	OTHER_PATIENT_ID	2FD36838-5A83-433E-AC80-B1F77448E5AA
34	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	PRIMARY_SITE_PATIENT	Left
35	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	PROSPECTIVE_COLLECTION	YES
36	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	PR_STATUS_BY_IHC	Negative
37	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	RACE	BLACK OR AFRICAN AMERICAN
38	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	RETROSPECTIVE_COLLECTION	NO
39	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	SAMPLE_COUNT	1
40	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	SEX	Female
41	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	SITE_OF_TUMOR_TISSUE	Breast
42	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	STAGING_SYSTEM	No axillary staging
43	VENHQS01VC1BOVFBOmJyY2FfdGNnYQ	TCGA-5T-A9QA	brca_tcga	TISSUE_SOURCE_SITE	5T

df5 = cd.get_all_clinical_data_of_sample_in_study(study_id="msk_met_2021", sample_id="P-0000004-T01-IM3")
df5

	uniqueSampleKey	uniquePatientKey	sampleId	patientId	studyId	clinicalAttributeId	value
0	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	CANCER_TYPE	Breast Cancer
1	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	CANCER_TYPE_DETAILED	Breast Invasive Ductal Carcinoma
2	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_ADRENAL_GLAND	No
3	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_BILIARY_TRACT	No
4	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_BLADDER_UT	No
5	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_BONE	Yes
6	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_BOWEL	No
7	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_BREAST	No
8	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_CNS_BRAIN	No
9	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_DIST_LN	No
10	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_FEMALE_GENITAL	No
11	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_HEAD_NECK	No
12	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_INTRA_ABDOMINAL	No
13	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_KIDNEY	No
14	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_LIVER	Yes
15	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_LUNG	No
16	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_MALE_GENITAL	No
17	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_MEDIASTINUM	No
18	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_OVARY	No
19	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_PLEURA	No
20	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_PNS	No
21	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_SKIN	No
22	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	DMETS_DX_UNSPECIFIED	No
23	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	FGA	0.278
24	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	FRACTION_GENOME_ALTERED	0.2782
25	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	GENE_PANEL	IMPACT341
26	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	IS_DIST_MET_MAPPED	TRUE
27	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	MET_COUNT	2
28	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	MET_SITE_COUNT	2
29	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	MSI_SCORE	2.5
30	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	MSI_TYPE	Stable
31	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	MUTATION_COUNT	4
32	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	ONCOTREE_CODE	IDC
33	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	ORGAN_SYSTEM	Breast
34	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	PRIMARY_SITE	Breast
35	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	SAMPLE_COVERAGE	428
36	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	SAMPLE_TYPE	Primary
37	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	SUBTYPE	Breast Ductal HR+HER2-
38	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	SUBTYPE_ABBREVIATION	IDC HR+HER2-
39	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	TMB_NONSYNONYMOUS	4.43662120239
40	UC0wMDAwMDA0LVQwMS1JTTM6bXNrX21ldF8yMDIx	UC0wMDAwMDA0Om1za19tZXRfMjAyMQ	P-0000004-T01-IM3	P-0000004	msk_met_2021	TUMOR_PURITY	50