mkt.databases.cbioportal

cBioPortal API client and extraction of missense kinase mutations, treatments, and panels.

Builds on cBioPortal/cBioPortalQuery to pull study, mutation, treatment, and gene-panel data; KinaseMissenseMutations extracts missense mutations restricted to kinase genes.

Classes

`Clinical`([bool_prefix, list_col_explode, ...])	Class to get clinical information from a cBioPortal study.
`ClinicalPatient`([bool_prefix, ...])	Class to get patient-level clinical information from a cBioPortal study.
`ClinicalSample`([bool_prefix, ...])	Class to get sample-level clinical information from a cBioPortal study.
`GenePanel`([bool_prefix, list_col_explode, ...])	Class to get gene panel information from a cBioPortal study.
`KinaseMissenseMutations`(bool_prefix, ...)	Class to get kinase mutations from a cBioPortal study.
`Mutations`([bool_prefix, list_col_explode, ...])	Class to get mutations from a cBioPortal study.
`PanelData`([bool_prefix, list_col_explode, ...])	Class to get gene panel information from a cBioPortal instance.
`StudyData`([bool_prefix, list_col_explode, ...])	Class to get mutations from a cBioPortal study.
`Treatment`(bool_prefix, list_col_explode, ...)	Class to get treatment information from a cBioPortal study.
`cBioPortal`()	Class to interact with the cBioPortal API.
`cBioPortalQuery`([bool_prefix, ...])	Class to get data from a cBioPortal instance.

class mkt.databases.cbioportal.Clinical(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str, bool_sample: bool)[source]

Bases: StudyData

Class to get clinical information from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str, bool_sample: bool) → None

bool_sample: bool: If True, return sample-level clinical data; if False, return patient-level clinical data.

query_sub_api() → list | None[source]

Get clinical info cBioPortal data.

Returns:

list | None –

cBioPortal data as list of Abstract Base Classes
objects if successful, otherwise None.
bool_sample (bool) – If True, return sample-level clinical data; if False, return patient-level clinical data

class mkt.databases.cbioportal.ClinicalPatient(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str)[source]

Bases: Clinical

Class to get patient-level clinical information from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str) → None

bool_sample: bool = False: If True, return sample-level clinical data; if False, return patient-level clinical data

class mkt.databases.cbioportal.ClinicalSample(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str)[source]

Bases: Clinical

Class to get sample-level clinical information from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str) → None

bool_sample: bool = True: If True, return sample-level clinical data; if False, return patient-level clinical data

class mkt.databases.cbioportal.GenePanel(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, panel_id: str)[source]

Bases: PanelData

Class to get gene panel information from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, panel_id: str) → None

query_sub_api() → list | None[source]

Get gene panel genes cBioPortal data.

Returns:

cBioPortal data as list of Abstract Base Classes: objects if successful, otherwise None.

Return type:

list | None

class mkt.databases.cbioportal.KinaseMissenseMutations(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, dict_replace: dict[str, str] = <factory>, str_blosom: str = 'BLOSUM80', pathfile_filter: str | None = None, *, study_id: str)[source]

Bases: Mutations

Class to get kinase mutations from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, dict_replace: dict[str, str] = <factory>, str_blosom: str = 'BLOSUM80', pathfile_filter: str | None = None, *, study_id: str) → None

annotate_kinase_regions(df: DataFrame, dict_in: dict) → DataFrame[source]

Annotate kinase regions in a DataFrame of mutations.

Parameters:

df (pd.DataFrame) – DataFrame of mutations
dict_in (dict) – Dictionary of HGNC gene names to KinaseInfo objects

Returns:

DataFrame of mutations with kinase regions annotated

Return type:

pd.DataFrame

Convert a value to log10 and truncate if necessary.

Parameters:

x (int | float | str) – Value to convert to log10
bool_truncate (bool) – Truncate the value to max_value if True; default is True
max_value (int) – Maximum value to truncate to if bool_truncate is True; default is 1.5

Returns:

Log10 converted value if numeric, otherwise original value; truncated to max_value if bool_truncate is True

Return type:

int | float | str

dict_replace: dict[str, str]

“WHR1”}.

Type:: Dictionary mapping cBioPortal to mkt gene names for mismatches; default is {“STK19”

filter_single_aa_missense_mutations(df: DataFrame) → DataFrame[source]

Filter DataFrame for single amino acid missense mutations.

Parameters:: df (pd.DataFrame) – DataFrame of mutations
Returns:: DataFrame of single amino acid missense mutations
Return type:: pd.DataFrame

generate_pivot_table(colname: str, bool_onehot: bool, bool_log10: bool, max_value: int | None) → DataFrame[source]

Generate a pivot table of missense mutation counts by KLIFS region.

Parameters:

colname (str) – Column name to pivot on; default is “klifs_region”
bool_onehot (bool) –

Column name to pivot on; default is “klifs_region” (just counts);

if “blosum_penalty”, the mean BLOSUM penalty is used instead;
if starts with “_”, it is treated as a one-hot encoded column
bool_log10 (bool) – Convert counts to log10 if True; default is True
max_value (int | None) –

Maximum value to truncate the log10 counts to if bool_log10 is True;
if None, no truncation is applied; default is None

Returns:

Pivot table of missense mutation counts by KLIFS region

Return type:

pd.DataFrame

get_kinase_missense_mutations(bool_save=False) → None | DataFrame[source]

Get cBioPortal kinase mutations and optionally save as a CSV file.

Parameters:: bool_save (bool) – Save cBioPortal kinase mutations as a CSV file if True
Returns:: DataFrame of kinase mutations if successful, otherwise None
Return type:: pd.DataFrame | None

pathfile_filter: str | None = None: Path to CSV file for filtered kinase missense mutations; default is None.

query_hgnc_gene_names(list_hgnc: list[str], dict_kinase: dict[str, object]) → dict[str, str | None][source]

Query HGNC gene names from a DataFrame of mutations.

Parameters:

list_hgnc (list[str]) – List of HGNC gene names to query
dict_kinase (dict[str, object]) – Dictionary mapping kinase names to KinaseInfo objects

Returns:

Dictionary mapping HGNC gene names from cBioPortal to Uniprot IDs

Return type:

dict

remove_mismatched_uniprot_mutations(df: DataFrame, dict_in: dict) → DataFrame[source]

Remove mutations with mismatches to canonical Uniprot sequence.

Parameters:

df (pd.DataFrame) – DataFrame of mutations
dict_in (dict) – Dictionary of HGNC gene names to Uniprot IDs

Returns:

DataFrame of mutations with mismatched Uniprot IDs removed

Return type:

pd.DataFrame

str_blosom: str = 'BLOSUM80': BLOSUM matrix to use for mutation analysis; default is “BLOSUM80”.

static try_except_middle_int(str_in)[source]

Try to convert string [1:-1] characters to integer.

Parameters:: str_in (str) – String to convert to integer
Returns:: Integer if successful, otherwise None
Return type:: int | None

class mkt.databases.cbioportal.Mutations(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str)[source]

Bases: StudyData

Class to get mutations from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str) → None

query_sub_api() → list | None[source]

Get mutations cBioPortal data.

Returns:

cBioPortal data as list of Abstract Base Classes: objects if successful, otherwise None.

Return type:

list | None

class mkt.databases.cbioportal.PanelData(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, panel_id: str)[source]

Bases: cBioPortalQuery

Class to get gene panel information from a cBioPortal instance.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, panel_id: str) → None

check_entity_id() → bool[source]

Check if the panel ID is valid.

Returns:: True if the panel ID is valid, False otherwise
Return type:: bool

get_entity_id()[source]: Get cBioPortal panel ID.

panel_id: str: cBioPortal panel ID.

class mkt.databases.cbioportal.StudyData(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str)[source]

Bases: cBioPortalQuery

Class to get mutations from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None, *, study_id: str) → None

check_entity_id() → bool[source]

Check if the study ID is valid.

Returns:: True if the study ID is valid, False otherwise
Return type:: bool

get_entity_id()[source]: Get cBioPortal study ID.

study_id: str: cBioPortal study ID.

class mkt.databases.cbioportal.Treatment(bool_prefix: bool = True, list_col_explode: list[str] | None = <factory>, pathfile: str | None = None, *, study_id: str)[source]

Bases: StudyData

Class to get treatment information from a cBioPortal study.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = <factory>, pathfile: str | None = None, *, study_id: str) → None

query_sub_api() → list | None[source]

Get mutations cBioPortal data.

Returns:

cBioPortal data as list of Abstract Base Classes: objects if successful, otherwise None.

Return type:

list | None

class mkt.databases.cbioportal.cBioPortal[source]

Bases: APIKeySwaggerClient

Class to interact with the cBioPortal API.

__init__() → None

get_cbioportal()[source]: Get cBioPortal API object.

get_instance()[source]: Get cBioPortal instance.

get_url()[source]: Get cBioPortal API URL.

instance: str = '': cBioPortal instance.

maybe_get_token()[source]

Get API token, if available.

Returns:: API token if available; None otherwise
Return type:: str | None

query_api()[source]

Query a Swagger API and return result.

Parameters:: url (str) – API URL
Returns:: API response
Return type:: SwaggerClient

url: str = '': cBioPortal API URL.

class mkt.databases.cbioportal.cBioPortalQuery(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None)[source]

Bases: cBioPortal

Class to get data from a cBioPortal instance.

__init__(bool_prefix: bool = True, list_col_explode: list[str] | None = None, pathfile: str | None = None) → None

bool_prefix: bool = True: Add prefix to ABC column names if True; default is True.

abstract check_entity_id() → bool[source]

Check if the entity ID is valid.

Returns:: True if the entity ID is valid, False otherwise
Return type:: bool

convert_api_query_to_dataframe() → DataFrame | None[source]

Convert API to query to a dataframe.

Returns:: DataFrame of API query if successful, otherwise None
Return type:: pd.DataFrame | None

get_data()[source]: Get cBioPortal data.

get_df()[source]: Get DataFrame of cBioPortal data in dataframe.

abstract get_entity_id()[source]

Get the entity ID (study_id or panel_id).

Returns:: Entity ID
Return type:: str

list_col_explode: list[str] | None = None: List of columns to explode in convert_api_query_to_dataframe; None if no columns to explode (post-init).

load_from_csv(str_path: str | None = None) → DataFrame | None[source]

Load DataFrame from CSV file.

Parameters:: str_path (str | None) – Path to CSV file; if None, use self.pathfile
Returns:: DataFrame loaded from CSV file if successful, otherwise None
Return type:: pd.DataFrame | None

pathfile: str | None = None: Path to load dataframe from CSV file; if None, regenerate (post-init).

abstract query_sub_api()[source]

Query a sub-API of cBioPortal and return result.

Returns:: API response
Return type:: SwaggerClient

regenerate_dataframe() → DataFrame | None[source]

Regenerate DataFrame from API query.

Returns:: DataFrame of API query if successful, otherwise None
Return type:: pd.DataFrame | None

return_adjusted_colname(colname: str, prefix: str = 'gene') → str[source]

Return adjusted column name based on bool_prefix.

Parameters:

colname (str) – Column name to adjust
prefix (str) – Prefix to add to the column name if bool_prefix is True; default is “gene”

Returns:

Adjusted column name

Return type:

str