scirpy.tl.clonal_expansion

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 (Union[AnnData, MuData, DataHandler]) – AnnData or MuData object that contains AIRR information.

  • target_col (str (default: 'clone_id')) – Column containing the clontype annoataion

  • expanded_in (Optional[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:

Optional[Series]

Returns:

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

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