gpsea.analysis.temporal package

The gpsea.analysis.temporal package implements comparison of survivals between genotype groups.

See Survival analysis for an example.

class gpsea.analysis.temporal.Endpoint[source]

Bases: ContinuousPartitioning

Endpoint computes survival for the analyzed individual.

An example endpoint includes death(), disease_onset(), or onset of a phenotypic feature (hpo_onset()).

abstract compute_survival(patient: Patient) → Survival | None[source]

Compute a survival for a given patient or None if the patient lacks the required data (e.g. age of death or age at last investigation).

class gpsea.analysis.temporal.SurvivalAnalysis(statistic: SurvivalStatistic)[source]

Bases: object

SurvivalAnalysis compares the survivals of genotype groups with respect to an Endpoint.

The cohort is partitioned into groups using a genotype predicate and survival is computed for each cohort member. The difference between survivals is tested with selected SurvivalStatistic.

compare_genotype_vs_survival(cohort: Iterable[Patient], gt_predicate: GenotypePolyPredicate, endpoint: Endpoint) → SurvivalAnalysisResult[source]

Execute the survival analysis on a given cohort.

class gpsea.analysis.temporal.SurvivalAnalysisResult(gt_predicate: GenotypePolyPredicate, endpoint: Endpoint, statistic: SurvivalStatistic, data: DataFrame, pval: float)[source]

Bases: MonoPhenotypeAnalysisResult

SurvivalAnalysisResult includes the results of a SurvivalAnalysis.

The genotype categories and survival are reported in the data data frame with the following structure:

patient_id

genotype

phenotype

patient_1

0

Survival(value=123.4, is_censored=False)

patient_2

0

None

patient_3

None

Survival(value=456.7, is_censored=True)

patient_4

1

None

…

…

…

The index includes the individual IDs (patient_id), and then there are 2 columns with the genotype group id (cat_id) and the phenotype with the survival represented as Survival object.

A genotype value may be missing (None) if the individual cannot be assigned into a genotype category. Similarly, a survival is None if computing the survival for an individual is impossible.

property endpoint: Endpoint

Get the endpoint used to compute the survival of the individuals.

plot_kaplan_meier_curves(ax)[source]

Plot genotype group survivals on the provided axes.

The axes includes legend. However, if no survival is available for a genotype group, the group name will be missing from the legend.

Parameters:

ax – a Matplotlib Axes to draw on.

class gpsea.analysis.temporal.Survival(value: float, is_censored: bool)[source]

Bases: object

Information regarding individual’s survival.

value: float

The survival value, expressed as a float.

The value must be finite and non-NaN.

is_censored: bool

True if the survival has been censored and False otherwise.

Subpackages