I have scRNA-seq data for 4 groups Treatment 1, Control 1, Treatment 2, Control 2.
My goal is to compare gene expression in each cell type between Treatment 1 and Control 1, between Treatment 2 and Control 2, and between Treatment 1 and Treatment 2.
Should I perform QC, Normalization, and clustering on the combined 4 scRNA-seq datasets and then do DE analysis in each identified cluster?
Any suggestions?
Thank you for your prompt reply, ATpoint. What do you mean by "DE analysis between clusters based on the unintegrated dataset with the clusters defined with the integrated dataset"? I'm interested in the DE analysis between treatment groups and control groups in the same cluster. I don't care about the comparison between different clusters except when I'm identifying cluster marker genes.
Sorry, misread the question. The point is the same though. You have to use the unintegrated values for DE analysis, not the ones that the integration produces, see https://osca.bioconductor.org/multi-sample-comparisons.html#sacrificing-differences
Thank you, my friend. That was helpful. I'm reading it now.