How to calculate differentially spliced genes in single cell?

Question

[zeina]

I have generated single cell RNA sequencing data then calculated the spliced and unspliced counts using veloctyo for my mice composed of 2 conditions(disease and control).These counts come in a loom file which can be imported to the adata by scvelo. I would like to find the differentially spliced genes between the 2 conditions and the top spliced genes per each cell type. I have read the beta binomial regression might be used. I have also come across paper where they used wilcoxin to find the spliced DEGs. I just do not know how to apply this. Any specific packages? I would appreciate it if someone can guide me.

Answer 1

[ATpoint]

To me this sounds like a normal differential analysis, just that you use the spliced counts as input. So any package for DEG analysis will do. Do pseudobulk aggregation if you can. If not, consider going through https://www.nature.com/articles/nmeth.4612 to learn on how different methods might perform. Important points in this paper are the prefiltering they recommend for a minimal percent per group of cells that express the gene above a certain cutoff.