omicverse.pl.markers_dotplot

omicverse.pl.markers_dotplot(adata, groupby=None, key=None, n_genes=5, groups=None, standard_scale='var', cmap='Spectral_r', dendrogram=False, min_logfoldchange=None, use_raw=None, layer=None, figsize=None, show=None, save=None, return_fig=False, **kwds)[source]

Dot plot of marker genes — clean drop-in for rank_genes_groups_dotplot().

Wraps rank_genes_groups_dotplot() with more convenient defaults: standard_scale='var', cmap='Spectral_r', and dendrogram=False.

Parameters:

  • adata (AnnData) – Annotated data matrix.

  • groupby (str or None, default=None) – Key in adata.obs to group by. If None, uses adata.uns[key]['params']['groupby'].

  • key (str or None, default=None) – Key in adata.uns containing rank_genes_groups results.

  • n_genes (int, default=5) – Number of top marker genes shown per group.

  • groups (str or Sequence[str] or None, default=None) – Subset of groups to include.

  • standard_scale ({'var', 'group'} or None, default='var') – Standardization mode for color values.

  • cmap (Colormap or str or None, default='Spectral_r') – Colormap for mean expression.

  • dendrogram (bool, default=False) – Whether to include a dendrogram.

  • min_logfoldchange (float or None, default=None) – Minimum log-fold-change threshold for marker inclusion.

  • use_raw (bool or None, default=None) – Whether to use adata.raw values.

  • layer (str or None, default=None) – Layer used for expression values.

  • figsize (tuple[float, float] or None, default=None) – Figure size in inches.

  • show (bool or None, default=None) – Whether to display the figure.

  • save (str or bool or None, default=None) – Save option/path.

  • return_fig (bool, default=False) – Whether to return the generated plot object.

  • **kwds – Additional keyword arguments forwarded to dotplot().

  • Returns – Figure or axes object when return_fig=True or show=False; None otherwise.

  • Examples – 

    >>> import omicverse as ov
>>> ov.single.find_markers(adata, groupby='leiden', method='cosg')
>>> ov.pl.markers_dotplot(adata, groupby='leiden', n_genes=5)
>>> # Using wilcoxon results stored under a different key
>>> ov.single.find_markers(adata, groupby='leiden', method='wilcoxon',
...                        key_added='wilcoxon_markers')
>>> ov.pl.markers_dotplot(adata, groupby='leiden', key='wilcoxon_markers')

Return type:

Optional[Any]