Hello, I am working through the vignettes and examples for DESeq2 ?results. I had a question(s) regarding lfcshrinkage. Looking at Example 2:

 ## Example 2: two conditions, two genotypes, with an interaction term

 dds <- makeExampleDESeqDataSet(n=100,m=12)
 dds$genotype <- factor(rep(rep(c("I","II"),each=3),2))

 design(dds) <- ~ genotype + condition + genotype:condition
 dds <- DESeq(dds)
 resultsNames(dds)

 # Note: design with interactions terms by default have betaPrior=FALSE

 # the condition effect for genotype I (the main effect)
 results(dds, contrast=c("condition","B","A"))

 # the condition effect for genotype II
 # this is, by definition, the main effect *plus* the interaction term
 # (the extra condition effect in genotype II compared to genotype I).
 results(dds, list( c("condition_B_vs_A","genotypeII.conditionB") ))

 # the interaction term, answering: is the condition effect *different* across genotypes?
 results(dds, name="genotypeII.conditionB")

How would you use the lfcShrink() function in those three cases (in particular with 'apeglm', which won't work with contrast in the second results() call)? Are you supposed to apply shrinkage to the interaction term? How would you specify a different alpha (0.05)?

Have you seen the extended section on shrinkage methods in the vignette? apeglm only can be used for individual terms however we show some examples for how to rearrange terms to apply apeglm. Alternatively you can use ashr. You can change alpha by running results() first and supplying res=res.