Hello Biocconductor community,

I have been wondering this for some time (and I think I can finally articulate it, somewhat, well enough to have an idea of what to ask)

How would I interpret DESeq2's padj after setting lfcThreshold and the log2FC is greater than lfcThreshold?

An example:

So if the results() I use within DESeq2 looks like this:

res <- results(dds, 
              contrast=c("Group", second_compar, first_compar),
              independentFiltering=TRUE, 
              alpha=0.05, 
              pAdjustMethod="BH", 
              lfcThreshold=1, 
              altHypothesis="greaterAbs")

This would mean:

Fold Change = (second_compar/first_compar)

so:

log2(FC) = log2(second_compar/first_compar)

Then, as above, if I set the lfcThreshold=1 (so an FC equal to 2 in log2(FC)=... so lfcThreshold=1 would mean the cut-off I am setting is log2(2)=1 ) and then an alpha=0.05. This means that the padj value for a given differentially expressed & significant gene as defined by a log2(2) =1 and an alpha=0.05.

For everything above, I am somewhat okay in my understanding...

Ambiguous territory:

This is where it gets into "ambiguous territory" for me. Could someone help clear my understanding of what happens when with the "cut-offs" set above, if Gene X that has for example a log2(10) = 3.321928 but I am using the cut-off of log2(2)=1 and alpha=0.05?

And then to bring it to the actual example above, for hopefully the sake of simplicity, if first_compar in the Fold Change above had a value of 1 and second_compar had a value of 10, so that log2(FC) = log2(second_compar/first_compar) = log2(10/1) = log2(10) = 3.321928 and then let me just give a padj=0.001 for this Gene X comparison.

If you're still with me after reading all that. Thank you : ) Pratik

It's not a "cutoff" per se, but it is used in computing the p-value, this is described in the 2014 paper.