I am currently planning a scRNA-seq analysis and I would like to have some feedback from this community. As this is a Drop-seq run, I will be using the Seurat package to identify clusters of cells. However, the program does not perform differential expression among experimental conditions (only among populations of cells).
From what I gathered, bulk RNA-seq methods have been shown to perform well (DESeq2, EdgeR), along with scRNA methods like MAST. Recently, Seurat has included DESeq2 and MAST as part of the tests of expression for cell clusters. I am leaning towards DESeq2 for my approach as I like how the design can be constructed, however, I wanted to see if this sounds reasonable among users in here. As a further question, Seurat performs global normalization in the data, which confuses me a bit in the need to re-normalize in DESeq2 (although I think it is necessary as it normalizes for sequencing depth - thoughts?).
Thanks for the input.