Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
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RCTD method's cell type weights doesn't sum to 1 #193
I'm using the RCTD method for cell type deconvolution. When I apply RCTD in both full and doublet modes, the results, which include the cell type weights for each pixel, don't sum up to 1. I thought these weights represent the cell type proportions for each spot (pixel), and so, shouldn't they add up to 1 for each pixel?
For further clarification, I have attached a screenshot of the output I obtained using the same codes and data provided by the vignette. In the below output, we can see that the proportions don't add to 1. I hope you can help me clarify this matter.
Don't know enough to know exactly how to interpret differences in weight sums, but just note that this is mentioned in their vignette where they run the normalize_weights() function, which just seems to rescale each spot to sum to 1 with weight / sum(weights).
Hi,
I'm using the RCTD method for cell type deconvolution. When I apply RCTD in both full and doublet modes, the results, which include the cell type weights for each pixel, don't sum up to 1. I thought these weights represent the cell type proportions for each spot (pixel), and so, shouldn't they add up to 1 for each pixel?
For further clarification, I have attached a screenshot of the output I obtained using the same codes and data provided by the vignette. In the below output, we can see that the proportions don't add to 1. I hope you can help me clarify this matter.