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I was wondering, get_mapping_scores() returns a table of all pairwise scores between cell types of different species, but sets scores within the same species to zero.
This may be a bit misleading, as if I wanted to try to do a downstream interpretation of the scores as a kind of distance metric, certainly, say Hs_Tcell1 and Hs_Tcell2 in the human have some relationship to each other, which may be similar to both of their relations to Mm_Tcell1 and Mm_Tcell2 in the mouse.
Is there any way to calculate mapping scores on the same scale as the cross-species scores for cell types within a data set, or is this simply impossible?
The text was updated successfully, but these errors were encountered:
The mapping scores are a relative measure of the connectivity between cells across species. It's not really comparable to the connectivity strength of cells within species. As SAMap is a graph-stitching method, it doesn't offer any sort of distance metric.
I was wondering, get_mapping_scores() returns a table of all pairwise scores between cell types of different species, but sets scores within the same species to zero.
This may be a bit misleading, as if I wanted to try to do a downstream interpretation of the scores as a kind of distance metric, certainly, say Hs_Tcell1 and Hs_Tcell2 in the human have some relationship to each other, which may be similar to both of their relations to Mm_Tcell1 and Mm_Tcell2 in the mouse.
Is there any way to calculate mapping scores on the same scale as the cross-species scores for cell types within a data set, or is this simply impossible?
The text was updated successfully, but these errors were encountered: