Love et al (2014) state that when interactions are present, shrinkage is disabled for main effects to prevent false positive calls of significance for interactions. I don't understand why it is necessary given that the interaction betas are shrunk as well. Why do they assume that the main effects will be shrunk too much relative to the interaction terms?
That "interaction rule" results in obtaining two different answers to the same question. E.g., I can present 2*3 design with interaction as 1-way with 6 treatments and no interaction. Statistically they are equivalent, but DESeq2 will generate different fits because for 2*3 design the main effects are not shrunk. Why was it so necessary to introduce the "interaction rule"?