bento.tl.coloc_quotient

bento.tl.coloc_quotient(sdata, points_key='transcripts', instance_key='cell_boundaries', feature_key='feature_name', shapes=['cell_boundaries'], radius=20, min_points=10, min_cells=0, num_workers=1)

Calculate pairwise gene colocalization quotient in each cell.

Parameters:

• sdata (SpatialData) – SpatialData object.

• points_key (str, default “transcripts”) – Key that specifies transcript points in sdata.

• instance_key (str, default “cell_boundaries”) – Key that specifies cell_boundaries instance in sdata.

• feature_key (str, default “feature_name”) – Key that specifies genes in sdata.

• shapes (List[str], default [“cell_boundaries”]) – Specify which shapes to compute colocalization separately.

• radius (int, default 20) – Unit distance to count neighbors.

• min_points (int, default 10) – Minimum number of points for sample to be considered for colocalization.

• min_cells (int, default 0) – Minimum number of cells for gene to be considered for colocalization.

• num_workers (int, default 1) – Number of workers to use for parallel processing.

Returns:

Updated SpatialData object with: - .tables[“table”].uns[‘clq’]: Pairwise gene colocalization similarity within each cell formatted as a long dataframe.

Return type:

SpatialData