Hi all, I'm wondering how to interpret the logFC of an interaction term correctly. As an example, in the limma user guide section 9.5. (Interaction Models: 2 × 2 Factorial Designs), sub-section 9.5.2 (Analysing as for a Single Factor), a contrast matrix is generated as follows:
> cont.matrix <- makeContrasts(
+ SvsUinWT=WT.S-WT.U,
+ SvsUinMu=Mu.S-Mu.U,
+ Diff=(Mu.S-Mu.U)-(WT.S-WT.U),
+ levels=design)
> fit2 <- contrasts.fit(fit, cont.matrix)
> fit2 <- eBayes(fit2)
(abbreviations: Mu=mutated, WT=wild-type, S=stimulated, U=unstimulated)
So the interaction contrast Diff=(Mu.S-Mu.U)-(WT.S-WT.U) can be used to identify genes that respond to stimulation differently between mutant and wild-type samples, i.e. two factors (genotype and treatment) are combined.
Now suppose we use topTable for this "Diff" contrast, returning a log2-fold-change of 1.58 (= 3-fold upregulation) for a certain gene. Would that logFC value refer to genotype (3-fold upregulation in mutant vs. wt), or refer to treatment (3-fold upregulation in stimulated vs. unstimulated), or to both (upregulation in mutant-vs-wt AND stimulated-vs-unstimulated)?
Thank you James for the explanation and the visualization suggestions! I already plotted some heatmaps, and will try kmeans as well.