scirpy.pl.clonal_expansion

scirpy.pl.clonal_expansion#

scirpy.pl.clonal_expansion(adata, groupby, *, target_col='clone_id', expanded_in=None, breakpoints=(1, 2), clip_at=None, summarize_by='cell', normalize=True, show_nonexpanded=True, viztype='bar', airr_mod='airr', **kwargs)#

Visualize clonal expansion.
`

Visualize clonal expansion.

Plots the fraction of cells that belong to an expanded Clonotype by a categorical variable.

If summarize_by is set to “clone_id” it plots the fraction of clonotypes instead of the fraction of cells.

Removes all entries with NaN in target_col prior to plotting.

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

  • groupby (str) – Group by this categorical variable in adata.obs.

  • target_col (str (default: 'clone_id')) – Column in adata.obs containing the clonotype information.

  • expanded_in (Optional[str] (default: None)) – Calculate clonal expansion within groups. To calculate expansion within patients, set this to the column containing patient annotation. If set to None, a clonotype counts as expanded if there’s any cell of the same clonotype across the entire dataset. See also Public clonotype.

  • breakpoints (Sequence[int] (default: (1, 2))) –

    summarize clonotypes with a size smaller or equal than the specified numbers into groups. For instance, if this is (1, 2, 5), there will be four categories:

    • all clonotypes with a size of 1 (singletons)

    • all clonotypes with a size of 2

    • all clonotypes with a size between 3 and 5 (inclusive)

    • all clonotypes with a size > 5

  • clip_at (Optional[int] (default: None)) – This argument is superseded by breakpoints and is only kept for backwards-compatibility. Specifying a value of clip_at = N equals to specifying breakpoints = (1, 2, 3, ..., N) Specifying both clip_at overrides breakpoints.

  • summarize_by (Literal['cell', 'clone_id'] (default: 'cell')) – Can be either cell to count cells belonging to a clonotype (the default), or clone_id to count clonotypes. The former leads to a over-representation of expanded clonotypes but better represents the fraction of expanded cells.

  • normalize (bool (default: True)) – If True, compute fractions rather than reporting abosolute numbers.

  • show_nonexpanded (bool (default: True)) – Whether or not to show the fraction of non-expanded cells/clonotypes

  • viztype (Literal['bar', 'barh'] (default: 'bar')) – bar for bars, barh for horizontal bars.

  • airr_mod (str (default: 'airr')) – 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.

  • **kwargs – Additional arguments passed to scirpy.pl.base.bar()