troutpy.tl.spatial_colocalization

troutpy.tl.spatial_colocalization#

troutpy.tl.spatial_colocalization(sdata, coord_keys=None, gene_key='gene', resolution=1000, square_size=20, n_threads=1, threshold_colocalized=1, copy=False)#

Computes spatial variability of extracellular RNA using Moran’s I.

Parameters:

  • sdata (SpatialData) – The spatial transcriptomics dataset in SpatialData format.

  • coord_keys (Optional[list] (default: None)) – The keys for spatial coordinates in the dataset (default: [‘x’, ‘y’]).

  • gene_key (str (default: 'gene')) – The key for gene identifiers in the dataset (default: ‘gene’).

  • n_neighbors – Number of neighbors to use for computing spatial neighbors (default: 10).

  • resolution (int (default: 1000)) – The resolution for kernel density estimation (default: 1000).

  • square_size (int (default: 20)) – The square_size for kernel density estimation (default: 20).

  • n_threads (int (default: 1)) – The number of threads for LazyKDE processing (default: 1).

  • method – The mode for spatial autocorrelation computation (default: “moran”).

  • threshold_colocalized (int (default: 1)) – Minimum expression of two genes to consider them as colocalized if expressed together

Returns:

sdata: spatialdata.SpatialData A spatialdata object containing Moran’s I values for each gene, in sdata.xrna_metadata.var, indexed by gene names.

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