Dear Biostars,

I've a RNAseq counts dataset of 32 samples belonging to two groups: group1 (16 samples) and group2 (16 samples). Each group contains 2 subgroups: subgroup1 (8 samples), and subgroup2 (8 samples). Now, by using glmLRT test I want to find deferentially expressed genes between subgroups inside group1, and do the same inside group2. What I've tried so far is the following:

condition <-factor(c(rep("group1subgroup1", 8), 
                   rep("group1subgroup2", 8), 
                   rep("group2subgroup1", 8), 
                   rep("group2subgroup2", 8)))

design <- model.matrix(~ 0 + condition)

colnames(design) <- levels(condition)

# make contrasts
contrasts <- makeContrasts(gp1sub1.vs.gp1sub2 = group1subgroup1 - group1subgroup2,
                           gp2sub1.vs.gp2sub2 = group2subgroup1 - group2subgroup2,
                           levels = design)

 # define dge list
 dge <- DGEList(counts=rnaseq.counts)
 disp <- estimateGLMCommonDisp(dge, design)
 disp <- estimateGLMTrendedDisp(disp, design)
 disp <- estimateGLMTagwiseDisp(disp, design)

# fit the model
 fit <- glmFit(disp, design)

 # LRT test for contrast 1: between subgroup1 and subgroup2 inside group1
 lrt.1 <- glmLRT(fit, contrast = contrasts[,1])

I've obtained positive and negative log2 FC for the genes.

Interpretation: A gene with a positive log2FC means that gene is over-expressed in subgroup2, and a gene with a negative log2FC means the gene is under-expressed in subgroup2.

Am I right?