Find DE in single cell RNA sequencing
I follow the protocol which made by Satija lab. but it didnt' work when I'm doing this part(**)
pseudo_harmony <- AggregateExpression(obj_Harmony, assays = "RNA", return.seurat = T, group.by = c("type","predicted.celltype.l2"))
pseudo_harmony$celltype.WAT <- paste(pseudo_harmony$predicted.celltype.l2, pseudo_harmony$type, sep = "_")
Idents(pseudo_harmony) <- "orig.ident"
View(GetAssayData(pseudo_harmony, slot = "counts", assay = "RNA"))
**bulk.mac.de <- FindMarkers(object = pseudo_harmony,
ident.1 = "Old_hASPC2",
ident.2 = "Young_hASPC2",
test.use = "DESeq2")
It says
Error in ValidateCellGroups(object = object, cells.1 = cells.1, cells.2 = cells.2, : Cell group 1 has fewer than 3 cells
I think they consider one cell type as a one cell. but don't know which process go wrong.
I want to compare old sample and young sample by cell type.
Thank you!!
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Hi, the problem here is that you are using
AggregateExpressionfirst, converting your data into a pseudo-bulk.FindMarkersrequires a normal single cell dataset (not pseudo-bulk), try running it on theobj_Harmonyobject instead.I want to try both pseudobulk and regular Seurat data to compare the markers identified from each method.