Hello everyone, I am working on scRNA-Seq data analysis and I have a technical question. We can combine different scRNA-Seq experiments with batch correction methods such as MNN or CCA. As I know, while doing differential expression analysis we should consider batch effect like Scater/Scran package provided a block parameter to do analysis with batch.
But the point is, if out data sets comes from different conditions (let's say healthy and disease) and real source of batch effect is the condition and we want to compare the transcriptomes of specific cell types between conditions, what should we do? We cannot block or do correction for batch since we want to see the effect of batch to specific conditions.
I identified cell types of clusters of each data seperately. Now I have 2 data sets from 2 conditions and I know which cluster is which cell type and I want to compare specific cell types in these 2 different conditions.
Treating scRNA-Seq data as bulk RNA-Seq data and use raw-counts (after deletion of non-expressed genes of course) with methods such as DESeq2 or edgeR, would it be okay?
Thank you in advance.