I have a scRNA-Seq dataset for which I would like to regress out the effects of cell cycle and then perform a differential expression analysis. I believe cell cycle genes are dominating and masking interesting gene expression patterns which would otherwise be present in the diff expression output.
Seurat can be used to regress out cell cycle genes via their ScaleData() function. However, the generally accepted method to perform differential expression is to use raw counts (certainly for DESeq2) and I will therefore lose any effect of my cell cycle regression.
So my question is - can I somehow use my scaled data to perform differential expression after cell cycle regression?