troutpy.tl.compute_target_score

troutpy.tl.compute_target_score#

troutpy.tl.compute_target_score(sdata, layer='transcripts', gene_key='gene', coords_key=None, lambda_decay=0.1, copy=False, celltype_key='cell type', k_neighbors=50, batch_size=100000)#

Computes scores for each extracellular transcript targeting specific cell types using spatial proximity.

Parameters:

  • sdata (spatialdata.SpatialData) – The input spatial data object.

  • layer (str) – The layer in sdata.points containing transcript data. Default is ‘transcripts’.

  • gene_key (str) – Column name in the transcript data representing gene identifiers.

  • coords_key (list) – Column names for spatial coordinates of transcripts and cell centroids.

  • lambda_decay (float) – The exponential decay factor for distances.

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

  • celltype_key (str) – Key for cell type annotations in the cell table.

  • k_neighbors (int) – Number of nearest cells to consider per transcript.

  • batch_size (int) – Number of transcripts to process per batch to limit memory usage.

Returns:

-sdata (SpatialData) SpatialData object with target score table added.

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