This may be a naive question, but I am wondering which, glmFit/glmLRT or glmQLFit/glmQLFTest, I should use for DE gene analysis in paired designs using edgeR. In the edgeR Users Guide (rev 20.4.2016),  glmFit/glmLRT is used in Chapter 3.4.1 and 4.1 for paired designs, whereas glmQLFit/glmQLFTest is recommended over glmFit/glmLRT in general in Chapter 2.10.3. I checked a chapter published in Methods Mol Biol (vol 1418, pp391-416, 2016) about Quasi-likelihood methods in edgeR, but there was no mention paired designs in the paper. Is glmFit/glmLRT still preferred for paired designs?

Check out some previous posts on this topic:

EdgeR glmLRT vs glmQLFTest

EDGE-R exact test vs QL F-test

The experimental design doesn't determine the choice of glmLRT vs glmQLFTest. Rather, it's got to do with type I error control, for which the QL methods are better; or cases involving low counts and/or large dispersions, where the LRT is better. I use the QL methods for my routine analyses, but both of them should do the job well. The case studies were originally written using glmLRT and we've just left them as they are (I mean, it's pretty easy to swap out glmFit and glmLRT for the corresponding QL-based functions).