squidpy.gr.co_occurrence

squidpy.gr.co_occurrence(adata, cluster_key, spatial_key='spatial', interval=50, copy=False, *, table_key=None)

Compute co-occurrence probability of clusters.

Parameters:

• adata (AnnData | SpatialData) – Annotated data object.

• table_key (str | None) – Key in spatialdata.SpatialData.tables where the table is stored. Required when adata is a spatialdata.SpatialData object and ignored otherwise.

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

• spatial_key (str) – Key in anndata.AnnData.obsm where spatial coordinates are stored.

• interval (int | ndarray[tuple[Any, ...], dtype[Any]]) – Distances interval at which co-occurrence is computed. If int, uniformly spaced interval of the given size will be used.

• copy (bool) – If True, return the result, otherwise save it to the adata object.

Return type:

tuple[ndarray[tuple[Any, ...], dtype[Any]], ndarray[tuple[Any, ...], dtype[Any]]] | None

Returns:

If copy = True, returns the co-occurrence probability and the distance thresholds intervals.

Otherwise, modifies the adata with the following keys:

• anndata.AnnData.uns ['{cluster_key}_co_occurrence']['occ'] - the co-occurrence probabilities across interval thresholds.

• anndata.AnnData.uns ['{cluster_key}_co_occurrence']['interval'] - the distance thresholds computed at interval.