Hi all,
I work on a scRNA-seq dataset. I computed a module score (AddModuleScore of Seurat) and I want to test if the difference in this score is statistically significant between two conditions.
I have three batches and each contain the two conditions (KO_batch1, WT_batch1, KO_batch2, WT_batch2, KO_batch3, WT_batch3).
I would normally use a Wilcoxon or t-test between condition 1 and condition 2, but doing so I wouldn't account for the batches. It would be testing all cells independently while they're not independent and therefore I would get really low p-values while I shouldn't. I could aggregate the scores, average them per batch and then test if the difference in batches is significant. But I would have a very low power as I would test only three differences somehow (3 batches: module score in condition2 vs. condition1).
So I wonder what is the best to do here? I've heard about linear mixed effect model but I am confused about what they are and how to use them and if they're suited here.
A big thank you for your help:)
Are the batches biological replicates?