:py:mod:`deeprvat.deeprvat.evaluate` ==================================== .. py:module:: deeprvat.deeprvat.evaluate .. autodoc2-docstring:: deeprvat.deeprvat.evaluate :allowtitles: Module Contents --------------- Functions ~~~~~~~~~ .. list-table:: :class: autosummary longtable :align: left * - :py:obj:`count_unique ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.count_unique :summary: * - :py:obj:`get_baseline ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_baseline :summary: * - :py:obj:`get_baseline_results ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_baseline_results :summary: * - :py:obj:`combine_results ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.combine_results :summary: * - :py:obj:`get_pvals ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_pvals :summary: * - :py:obj:`min_Bonferroni_aggregate ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.min_Bonferroni_aggregate :summary: * - :py:obj:`aggregate_pvals_per_gene ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.aggregate_pvals_per_gene :summary: * - :py:obj:`process_results ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.process_results :summary: * - :py:obj:`evaluate_ ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.evaluate_ :summary: * - :py:obj:`evaluate ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.evaluate :summary: Data ~~~~ .. list-table:: :class: autosummary longtable :align: left * - :py:obj:`logger ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.logger :summary: * - :py:obj:`BASELINE_GROUPS ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.BASELINE_GROUPS :summary: * - :py:obj:`BURDEN_SKAT_RENAME ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.BURDEN_SKAT_RENAME :summary: * - :py:obj:`VARIANT_TYPE_RENAME ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.VARIANT_TYPE_RENAME :summary: * - :py:obj:`METHOD_NAMES ` - .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.METHOD_NAMES :summary: API ~~~ .. py:data:: logger :canonical: deeprvat.deeprvat.evaluate.logger :value: 'getLogger(...)' .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.logger .. py:data:: BASELINE_GROUPS :canonical: deeprvat.deeprvat.evaluate.BASELINE_GROUPS :value: None .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.BASELINE_GROUPS .. py:data:: BURDEN_SKAT_RENAME :canonical: deeprvat.deeprvat.evaluate.BURDEN_SKAT_RENAME :value: None .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.BURDEN_SKAT_RENAME .. py:data:: VARIANT_TYPE_RENAME :canonical: deeprvat.deeprvat.evaluate.VARIANT_TYPE_RENAME :value: None .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.VARIANT_TYPE_RENAME .. py:data:: METHOD_NAMES :canonical: deeprvat.deeprvat.evaluate.METHOD_NAMES :value: None .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.METHOD_NAMES .. py:function:: count_unique(result: pandas.DataFrame, query: str) :canonical: deeprvat.deeprvat.evaluate.count_unique .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.count_unique .. py:function:: get_baseline(paths, experiment_name, deeprvat_genes, phenotype=None, min_eaf=50, alpha: float = 0.05, correction_method: str = 'Bonferroni') -> pandas.DataFrame :canonical: deeprvat.deeprvat.evaluate.get_baseline .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_baseline .. py:function:: get_baseline_results(config: typing.Dict, pheno, deeprvat_genes: numpy.ndarray, alpha: float = 0.05, correction_method: str = 'Bonferroni') :canonical: deeprvat.deeprvat.evaluate.get_baseline_results .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_baseline_results .. py:function:: combine_results(deeprvat_results: pandas.DataFrame, baseline_results: pandas.DataFrame, correction_method: str = 'Bonferroni', alpha: float = 0.05, combine_pval: str = 'Bonferroni') :canonical: deeprvat.deeprvat.evaluate.combine_results .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.combine_results .. py:function:: get_pvals(results, method_mapping=None, phenotype_mapping={}) :canonical: deeprvat.deeprvat.evaluate.get_pvals .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.get_pvals .. py:function:: min_Bonferroni_aggregate(pvals) :canonical: deeprvat.deeprvat.evaluate.min_Bonferroni_aggregate .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.min_Bonferroni_aggregate .. py:function:: aggregate_pvals_per_gene(df, agg_method) :canonical: deeprvat.deeprvat.evaluate.aggregate_pvals_per_gene .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.aggregate_pvals_per_gene .. py:function:: process_results(results: pandas.DataFrame, alpha: float = 0.05, correction_method: str = 'Bonferroni', combine_pval: str = 'Bonferroni') -> typing.Tuple[pandas.DataFrame, pandas.DataFrame] :canonical: deeprvat.deeprvat.evaluate.process_results .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.process_results .. py:function:: evaluate_(associations: pandas.DataFrame, alpha: float, baseline_results: typing.Optional[pandas.DataFrame] = None, debug: bool = False, correction_method: str = 'Bonferroni', combine_pval: str = 'Bonferroni') :canonical: deeprvat.deeprvat.evaluate.evaluate_ .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.evaluate_ .. py:function:: evaluate(debug: bool, phenotype: typing.Optional[str], use_baseline_results: bool, association_files: typing.Tuple[str], config_file: str, out_dir: str, combine_pval) :canonical: deeprvat.deeprvat.evaluate.evaluate .. autodoc2-docstring:: deeprvat.deeprvat.evaluate.evaluate