Dear all,

I computed enrichment scores for 64 cell types with xCELL from my bulk RNAseq samples. Now I would like to detect differential expression across 3 groups (control, case1, case2) but adjusting for the different cell type compositions (continuous variables). I was thinking of taking only the most variable cell types across samples (<10). I was wondering if it is really necessary to cut the continuous variables into smaller bins as DESeq2 FAQ says.

would this model be enough?

model.matrix(~group+cell_type1+cell_type2+cell_type_n)

Thanks,

Ok Ryan, thanks!