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)

Adds a column to obs recording which clonotypes are expanded.

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

Parameters

adata : AnnData

Annoated data matrix

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 results will be added to obs.

inplace : bool (default: True)

If True, adds a column to obs. Otherwise returns an array with the clipped counts.

Return type

None | ndarrayOptional[ndarray]

Returns

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