scirpy.tl.clonal_expansion

scirpy.tl.clonal_expansion(adata, *, target_col='clone_id', expanded_in=None, clip_at=3, key_added='clonal_expansion', inplace=True, **kwargs)

Adds a column to obs recording which clonotypes are expanded.

nan`s in the clonotype column remain `nan in the output.

Parameters

adata : AnnData | MuData | DataHandlerUnion[AnnData, MuData, DataHandler]

AnnData or MuData object that contains AIRR information.

target_col : str (default: 'clone_id')

Column containing the clontype annoataion

expanded_in : str | NoneOptional[str] (default: None)

Calculate clonal expansion within groups. Usually makes sense to set this to the column containing sample annotation. If set to None, a clonotype counts as expanded if there’s any cell of the same clonotype across the entire dataset.

clip_at : int (default: 3)

All clonotypes with more than clip_at clones will be summarized into a single category

key_added : str (default: 'clonal_expansion')

Key under which the result will be stored in obs, if inplace is True. When the function is running on MuData, the result will be written to both mdata.obs["{airr_mod}:{key_added}"] and mdata.mod[airr_mod].obs[key_added].

inplace : bool (default: True)

If True, a column with the result will be stored in obs. Otherwise the result will be returned.

airr_mod

Name of the modality with AIRR information is stored in the MuData object. if an AnnData object is passed to the function, this parameter is ignored.

Return type

None | SeriesOptional[Series]

Returns

Depending on the value of inplace, adds a column to adata or returns a Series with the clipped count per cell.