mmcci.an.lr_interaction_clustering

mmcci.an.lr_interaction_clustering(sample, resolution=0.5, cluster_palette='Dark2_r', cell_type_palette='tab20', cell_colors=None, spot_size=1.5, spatial_plot=True, proportion_plot=True, return_adata=False, **kwargs)[source]

Clustering of spatial LR interaction scores on AnnData objects processed through stLearn.

Parameters:

  • sample (AnnData) – An AnnData object that has been run through stLearn.

  • resolution (float) (optional) – The resolution to use for the clustering. Defaults to 0.5.

  • cluster_palette (str) (optional) – Name of matplotlib colormap to use for clusters. Defaults to ‘Dark2_r’.

  • cell_type_palette (str) (optional) – Name of matplotlib colormap to use for cell types. Defaults to ‘tab20’.

  • cell_colors (dict) (optional) – Dictionary mapping cell types to colors. If not provided, colors will be generated from cell_type_palette. Defaults to None.

  • spot_size (float) (optional) – The size of the spots in the spatial plot. Defaults to 1.5.

  • spatial_plot (bool) (optional) – Whether to show the spatial plot. Defaults to True.

  • proportion_plot (bool) (optional) – Whether to show the proportion plot. Defaults to True.

  • return_adata (bool) (optional) – Whether to return the AnnData object with the clustering results. Defaults to False.

  • **kwargs – Additional keyword arguments to pass to the scanpy spatial plot function.

Returns:

An AnnData object with the clustering results.

Return type:

AnnData