Hi,

I am using limma to analyze a barcode sequencing dataset. The raw data are counts, similar to RNA-seq. I am using edgeR::calcNormFactors followed by voom to normalize and transform the count data. I am interested in plotting normalized data for a specific single gene. I have looked around and found plotCounts function from DESeq2. Is there a similar function in limma? If not, is there another package that provides such a function for EList or ExpressionSet objects?

Thanks.

Yury

Well, assuming your DGEList or count matrix is y, grouping is a factor indicating which group each library belongs to, and gene is an integer/string specifying the gene of interest, you could do:

norm <- edgeR::cpm(y) # to get normalized expression values.
plot(jitter(as.integer(grouping)), norm[gene,], ylab="CPM", xaxt="n",
    xlab="", xlim=c(0.5, nlevels(grouping)+0.5))
axis(side=1, at=seq_len(nlevels(grouping)), label=levels(grouping))

Admittedly, it's not a nice easy function, but you can customize this to your heart's content. I usually end up writing all my own plotting code anyway to get publication-quality figures I'm satisfied with.