Generic Assays#
The module generic_assays provides functions related to Generic Assays section of
cBioPortal Web Public API.
- pybioportal.generic_assays.fetch_generic_assay_meta(generic_assay_stable_ids=None, molecular_profile_ids=None, projection='SUMMARY')#
Fetch meta data for generic assays based on a filter.
- Parameters:
generic_assay_stable_ids (list of str) – List of Stable IDs (e.g., [“TULP4_pS563”, “TEP1_pS397”, “ALAD_214_215_1_1_S215”]).
molecular_profile_ids (list of str) – List of Molecular Profile IDs (e.g., [“brca_tcga_phosphoprotein_quantification”,”brain_cptac_2020_phosphoprotein”]).
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).
- Returns:
A DataFrame containing meta data for the generic assays matching the filter criteria.
- Return type:
pandas.DataFrame
- pybioportal.generic_assays.get_generic_assay_meta_by_id(generic_assay_stable_id, projection='SUMMARY')#
Fetch meta data for a generic assay by its ID.
- Parameters:
generic_assay_stable_id (str) – The stable ID of the generic assay.
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).
- Returns:
A DataFrame containing the fetched meta data for the generic assay.
- Return type:
pandas.DataFrame
- pybioportal.generic_assays.get_generic_assay_meta_by_molecular_profile_id(molecular_profile_id, projection='SUMMARY')#
Fetch meta data for a generic assay by molecular profile ID.
- Parameters:
molecular_profile_id (str) – Molecular Profile ID.
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).
- Returns:
A DataFrame containing the fetched meta data for the generic assay in the specified molecular profile.
- Return type:
pandas.DataFrame
Examples#
from pybioportal import generic_assays as ga
df1a = ga.fetch_generic_assay_meta(generic_assay_stable_ids=["TULP4_pS563", "TEP1_pS397", "ALAD_214_215_1_1_S215"])
df1a
| stableId | entityType | genericEntityMetaProperties_GENE_SYMBOL | genericEntityMetaProperties_PHOSPHOSITE | genericEntityMetaProperties_DESCRIPTION | genericEntityMetaProperties_NAME | |
|---|---|---|---|---|---|---|
| 0 | TEP1_pS397 | GENERIC_ASSAY | TEP1 | pS397 | NaN | NaN |
| 1 | TULP4_pS563 | GENERIC_ASSAY | TULP4 | pS563 | NaN | NaN |
| 2 | ALAD_214_215_1_1_S215 | GENERIC_ASSAY | NaN | NaN | NP_000022.3 | ALAD S215 214-215 1_1 |
df1b = ga.fetch_generic_assay_meta(molecular_profile_ids=["brca_tcga_phosphoprotein_quantification",
"brain_cptac_2020_phosphoprotein"])
df1b
| stableId | entityType | genericEntityMetaProperties_GENE_SYMBOL | genericEntityMetaProperties_PHOSPHOSITE | genericEntityMetaProperties_DESCRIPTION | genericEntityMetaProperties_NAME | |
|---|---|---|---|---|---|---|
| 0 | FSCN1_pS328 | GENERIC_ASSAY | FSCN1 | pS328 | NaN | NaN |
| 1 | YWHAZ_pS230 | GENERIC_ASSAY | YWHAZ | pS230 | NaN | NaN |
| 2 | GMPPB_pS246 | GENERIC_ASSAY | GMPPB | pS246 | NaN | NaN |
| 3 | EPN3_pS503 | GENERIC_ASSAY | EPN3 | pS503 | NaN | NaN |
| 4 | C19orf47_pS395 | GENERIC_ASSAY | C19orf47 | pS395 | NaN | NaN |
| ... | ... | ... | ... | ... | ... | ... |
| 76663 | DIS3L2_133_154_1_1_S139 | GENERIC_ASSAY | NaN | NaN | NP_689596.4 | DIS3L2 S139 133-154 1_1 |
| 76664 | CRYBG3_442_457_1_1_S457 | GENERIC_ASSAY | NaN | NaN | NP_705833.3 | CRYBG3 S457 442-457 1_1 |
| 76665 | RASAL2_1005_1006_1_1_S1005 | GENERIC_ASSAY | NaN | NaN | NP_733793.2 | RASAL2 S1005 1005-1006 1_1 |
| 76666 | CAMK2B_338_343_1_1_T342 | GENERIC_ASSAY | NaN | NaN | NP_742078.1 | CAMK2B T342 338-343 1_1 |
| 76667 | EXOC1_453_458_1_1_S455 | GENERIC_ASSAY | NaN | NaN | NP_839955.1 | EXOC1 S455 453-458 1_1 |
76668 rows × 6 columns
df2 = ga.get_generic_assay_meta_by_molecular_profile_id("brca_tcga_phosphoprotein_quantification")
df2
| stableId | entityType | genericEntityMetaProperties_GENE_SYMBOL | genericEntityMetaProperties_PHOSPHOSITE | |
|---|---|---|---|---|
| 0 | FSCN1_pS328 | GENERIC_ASSAY | FSCN1 | pS328 |
| 1 | YWHAZ_pS230 | GENERIC_ASSAY | YWHAZ | pS230 |
| 2 | GMPPB_pS246 | GENERIC_ASSAY | GMPPB | pS246 |
| 3 | EPN3_pS503 | GENERIC_ASSAY | EPN3 | pS503 |
| 4 | C19orf47_pS395 | GENERIC_ASSAY | C19orf47 | pS395 |
| ... | ... | ... | ... | ... |
| 72115 | CIC_pS902_S904 | GENERIC_ASSAY | CIC | pS902_S904 |
| 72116 | MAGI1_pT1336 | GENERIC_ASSAY | MAGI1 | pT1336 |
| 72117 | PRKD2_pT211_S214 | GENERIC_ASSAY | PRKD2 | pT211_S214 |
| 72118 | PDCD11_pT1012 | GENERIC_ASSAY | PDCD11 | pT1012 |
| 72119 | PKN2_pT958 | GENERIC_ASSAY | PKN2 | pT958 |
72120 rows × 4 columns
df3 = ga.get_generic_assay_meta_by_id("TULP4_pS563")
df3
| stableId | entityType | genericEntityMetaProperties_GENE_SYMBOL | genericEntityMetaProperties_PHOSPHOSITE | |
|---|---|---|---|---|
| 0 | TULP4_pS563 | GENERIC_ASSAY | TULP4 | pS563 |