I have a dataset with 3 different populations in it ("BCM", "BMCM", "BMR1") that have been integrated and clustered by Seurat. Because of the large overlap, cells of different populations will often cluster together, which is fine, as I still have the metadata to find the cells back.
Now, I would like to find differentially expressed genes between a group of cells within a certain cluster and all other clusters. Or another specific group from another cluster. E.g all BCM cells from cluster 0 vs all BMR1 cells from cluster 1.
I tried to use the subset.ident option of the FindMarkers function like this:
test.cluster <- FindMarkers(pbmc, ident.1 = "BCM", group.by = 'type', subset.ident = "0")
However, from what I understand it is used to get the genes from a specific group of cells within one cluster and the rest of the same cluster, which is not what I am aiming for.
Thank you for your time.
Usually I will do it manually by a customized code. Since for each cell barcode, you have the information of which cluster it belongs and which population it comes from, it won't be too difficult get your interested cell barcode list.