As leipinji said, you shoudln't use rRNA as normalizers because library construction usually includes a step that either select mRNA or deplete rRNA. The efficiency of this step can vary, therefore rRNA levels can be very different between libraries (especially if you used ribodepletion).
However, in the case of ribodepleted datasets, you could try to normalize on snoRNAs. With DEseq2, its pretty simple :
1) get read count per gene/exons (with HTseq-counts or featureCounts for instance)
2) Perform differential analysis using DEseq2. Follow procedure described in the documentation except that you will estimate the size factor (= how you will normalize your libraries) only on read counts from snoRNA genes :
cds = newCountDataSet(CountTable, Design$condition )
sizeFactors( cds )
head(counts( cds, normalized=TRUE))
Hope that helps !
modified 3.6 years ago
3.6 years ago by
Carlo Yague • 4.4k