squidpy.pl.nhood_enrichment

squidpy.pl.nhood_enrichment(adata, cluster_key, mode='zscore', annotate=False, method=None, title=None, cmap='viridis', palette=None, cbar_kwargs=mappingproxy({}), figsize=None, dpi=None, save=None, ax=None, **kwargs)

Plot neighborhood enrichment.

The enrichment is computed by squidpy.gr.nhood_enrichment().

Parameters:

• adata (AnnData) – Annotated data object.

• cluster_key (str) – Key in anndata.AnnData.obs where clustering is stored.

• mode (Literal['zscore', 'count']) –

  Which squidpy.gr.nhood_enrichment() result to plot. Valid options are:

  • ’zscore’ - z-score values of enrichment statistic.

  • ’count’ - enrichment count.

• annotate (bool) – Whether to annotate the cells of the heatmap.

• method (str | None) – The linkage method to be used for dendrogram/clustering, see scipy.cluster.hierarchy.linkage().

• title (str | None) – The title of the plot.

• cmap (str) – Continuous colormap to use.

• cbar_kwargs (Mapping[str, Any]) – Keyword arguments for matplotlib.figure.Figure.colorbar().

• palette (str | ListedColormap | None) – Categorical colormap for the clusters. If None, use anndata.AnnData.uns ['{cluster_key}_colors'], if available.

• figsize (tuple[float, float] | None) – Size of the figure in inches.

• dpi (int | None) – Dots per inch.

• save (str | Path | None) – Whether to save the plot.

• ax (Axes | None) – Axes, matplotlib.axes.Axes.

• kwargs (Any) – Keyword arguments for matplotlib.pyplot.text().

Return type:

None

Returns:

Nothing, just plots the figure and optionally saves the plot.