I'm currently analysing an experiment of single cell RNA-seq consisting of two populations of cells both consisting predominantly of the same 3 cell types. When plotted on a UMAP/tSNE there is a clear separation between the two populations which can mostly be removed via batch correction, however the nature of our experiment means that we would like to identify the differences between the two populations as one is effectively a model of the other. We would thus like to identify the differences between our model population and the wild type population.
I've performed basic analyses such as differential expression between identical cells types across the two populations, however are there any options for further detailed analysis that I might consider?
Thank you for the suggestion, however in my case I do not have replicates in my study design meaning I do not think that this (or other similar methods such as muscat) are appropriate here. I think in my case a standard DE analysis would suffice. I'm really looking for other methods than differential expression.
I suppose you could give GSEA or similar pathway enrichment methods a shot.
fgseais quick and easy to run from your DE results if you want to look for higher-level changes that are sometimes easier to interpret than individual genes.