troutpy.tl.calculate_target_cells

troutpy.tl.calculate_target_cells#

troutpy.tl.calculate_target_cells(sdata, layer='transcripts', xcoord='x', ycoord='y', xcellcoord='x_centroid', ycellcoord='y_centroid', celltype_key='cell type', gene_id_key='gene', copy=False)#

Find the nearest cell to each transcript and annotate it with that cell’s ID, type, and distance.

Parameters:

  • sdata (spatialdata.SpatialData) – SpatialData object containing spatial and transcript data.

  • layer (str, optional) – The layer in sdata.points containing transcript data. Defaults to "transcripts".

  • xcoord (str, optional) – Column name for the x-coordinate of transcripts. Defaults to "x".

  • ycoord (str, optional) – Column name for the y-coordinate of transcripts. Defaults to "y".

  • xcellcoord (str, optional) – Column name for the x-coordinate of cell centroids. Defaults to "x_centroid".

  • ycellcoord (str, optional) – Column name for the y-coordinate of cell centroids. Defaults to "y_centroid".

  • celltype_key (str, optional) – Column name in adata.obs that contains cell type annotations. Defaults to "cell type".

  • gene_id_key (str, optional) – Column name in sdata.points[layer] that contains gene identity. Defaults to "gene".

  • copy (bool, optional) – If True, returns a copy of the modified SpatialData object. Defaults to False.

Return type:

SpatialData | None

Returns:

spatialdata.SpatialData or None Modified SpatialData object with updated transcript annotations if copy=True; otherwise updates are made in place and None is returned.

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