8 months ago by
Applying the shrinkage definitely changes the result, otherwise what would be the point of doing it in the first place. As Grant has pointed out, DESeq2 is mostly trying to address the problem that lowly expressed genes tend to have high relatively levels of variability and they try to alleviate this.
The goal of a garden-variety RNA-seq experiment is usually to discover genes that show significant changes. DESeq2 and the other tools have been tuned to do exactly that in a fairly reproducible and reliable manner. Yes, they also give an estimate of the (log2) fold change, but they make it very clear that this an estimate either way.
Even without that clear language that can be found in the respective manuals, I wouldn't bet a single penny on a fold change value stemming from an RNA-seq analysis to be taken at face value. There are so many factors that will influence it, including the library prep.
Trying to compare these values precisely to qPCR measurements is not appropriate either because qPCR typically measures one (!) very short fragment of a transcript whereas RNA-seq often covers the entire transcript. EDIT: and thousands different other ones, too!
In short, I don't think you need to worry about a difference of an extremely high fold change (if that's a log2FC, we're talking about more than thousand fold difference, which is definitely in the ballpark of the qPCR, no?). The important thing is that the general message between RNA-seq and qPCR is consistent, i.e. the gene should change in the same direction, and if the ranking fits (i.e., the gene changes quite strongly compared to many other genes), then that's even better.
modified 8 months ago
8 months ago by
Friederike ♦ 4.2k