pypath.utils.orthology.get_df

pypath.utils.orthology.get_df(target: str | int, source: str | int = 9606, id_type: str = 'uniprot', only_swissprot: bool = True, oma: bool | None = None, homologene: bool | None = None, ensembl: bool | None = None, oma_rel_type: set[Literal['1:1', '1:n', 'm:1', 'm:n']] | None = None, oma_score: float | None = None, ensembl_hc: bool = True, ensembl_types: list[Literal['one2one', 'one2many', 'many2many']] | None = None, full_records: bool = False, **kwargs) → DataFrame

Create a data frame for one source organism and ID type.

Parameters:

• target – Name or NCBI Taxonomy ID of the target organism.

• source – Name or NCBI Taxonomy ID of the source organism.

• id_type – The identifier type to use.

• only_swissprot – Use only SwissProt IDs.

• oma – Use orthology information from the Orthologous Matrix (OMA). Currently this is the recommended source for orthology data.

• homologene – Use orthology information from NCBI HomoloGene.

• ensembl – Use orthology information from Ensembl.

• oma_rel_type – Restrict relations to certain types.

• oma_score – Lower threshold for similarity metric.

• ensembl_hc – Use only the high confidence orthology relations from Ensembl.

• ensembl_types – Ensembl orthology relation types to use. Possible values are one2one, one2many and many2many. By default only one2one is used.

• full_records – Include not only the identifiers, but also some properties of the orthology relationships.

• kwargs – Ignored.

Returns:

A data frame with pairs of orthologous identifiers, in two columns: “source” and “target”.