You can use (log)CPMs from edgeR starting from a count matrix, it is a one-liner, see Basic normalization, batch correction and visualization of RNA-seq data.
Don't use any of these naive metrics that only scale by library size, it is typically not sufficient as it fails to correct for library composition.
edgeR has a
rpkm function though, which is simply its normalized counts divided by gene length, but I would not use this since in the differential testing you do not consider gene length and the MA-plot is actually meant to visualize the DE results, so just use
cpm() as described in the lined post.