dae.pheno_tool package

Subpackages

Submodules

dae.pheno_tool.pheno_tool_adapter module

class dae.pheno_tool.pheno_tool_adapter.PhenoToolAdapter(pheno_tool: PhenoTool, pheno_tool_helper: PhenoToolHelper)[source]

Bases: PhenoToolAdapterBase

Adapter for PhenoTool class.

static align_na_results(results: list[dict[str, Any]]) → None[source]

Align NA results.

build_report_description(measure_id: str, normalize_by: Any) → str[source]
calc_by_effect(measure_id: str, effect: str, people_variants: Counter, person_ids: list[str] | None = None, family_ids: list[str] | None = None, normalize_by: list[dict[str, str]] | None = None) → dict[str, Any][source]
calc_variants(data: dict[str, Any], effect_groups: list[str]) → dict[str, Any][source]

Run pheno tool on given data.

get_result_by_sex(result: dict[str, PhenoResult], sex: str) → dict[str, Any][source]
class dae.pheno_tool.pheno_tool_adapter.PhenoToolAdapterBase[source]

Bases: object

Base class for pheno tool adapters.

calc_by_effect(measure_id: str, effect: str, people_variants: Counter, person_ids: list[str] | None = None, family_ids: list[str] | None = None, normalize_by: list[dict[str, str]] | None = None) → dict[str, Any][source]
calc_variants(data: dict[str, Any], effect_groups: list[str]) → dict[str, Any][source]

dae.pheno_tool.tool module

class dae.pheno_tool.tool.PhenoResult[source]

Bases: object

Represents a result of PhenoTool calculation.

set_negative_stats(n_count: int, n_mean: float, n_std: float) → None[source]
set_positive_stats(p_count: int, p_mean: float, p_std: float) → None[source]
class dae.pheno_tool.tool.PhenoTool(phenotype_data: PhenotypeData)[source]

Bases: object

Tool to estimate dependency between variants and phenotype measrues.

Arguments of the constructor are:

phenotype_data – an instance of PhenotypeData

measure_id – a phenotype measure ID

person_ids – an optional list of person IDs to filter the phenotype database with

normalize_by – list of continuous measure names. Default value is an empty list

calc(measure_id: str, variants: Counter, *, sex_split: bool = False, person_ids: list[str] | None = None, family_ids: list[str] | None = None, normalize_by: list[dict[str, str]] | None = None) → dict[str, PhenoResult] | PhenoResult[source]

Perform calculation.

variants – an instance of Counter, matching personIds to an amount of variants

sex_split – should we split the result by sex or not. Default is False.

create_df(measure_id: str, person_ids: list[str] | None = None, family_ids: list[str] | None = None, normalize_by: list[dict[str, str]] | None = None) → DataFrame[source]

Create dataframe for given measure.

get_normalize_measure_id(measure_id: str, normalize_measure: dict[str, str]) → str | None[source]
init_normalize_measures(measure_id: str, normalize_by: list[dict[str, str]]) → list[str][source]
static join_pheno_df_with_variants(pheno_df: DataFrame, variants: Counter) → DataFrame[source]

Join phenotype dataframe with variants.

class dae.pheno_tool.tool.PhenoToolHelper(genotype_data: GenotypeData, phenotype_data: PhenotypeData)[source]

Bases: object

Helper class for PhenoTool.

Collects variants and person ids from genotype data.

Arguments of the constructor are:

genotype_data – an instance of StudyWrapper

genotype_data_persons(family_ids: list[str] | None = None, roles: list[Role] | None = None) → set[str][source]

Collect person ids from genotype data.

genotype_data_variants(data: dict, effect_groups: list[str]) → dict[str, Counter][source]

Collect effect groups variants.

Module contents