Open ghost opened 7 years ago
Hey timmo,
Late reply, but in case you're still interested, you can simply use rowMeans()/rowMedians() on the expression matrix, subsetting its columns by cells of a given cell type/cluster. Something like:
cds$clust1.mean <- rowMeans(cds[,which(cds$cluster == "1")])
This will then be stored in pData(cds) for you. You could also use this approach for a bunch of other summary statistics: rowMedians(), rowVars(), rowMins(), rowMaxs(), etc.
in your documents about differential expression you mention "We could also simply compute summary statistics such as mean or median expression level on a per-CellType basis"...
This would be really useful for my objectives, would you mind sharing a way to do this.
Thanks for your time.
Andrew