Hello all,

I'm trying to understand concepts on the linear model and the best way to design my experiment. I have RNAseq data and my design is 2 groups (H and C) and 2 conditions (E and S). To check for the main effects and the interactions what would be the best design:

dds..........design= ~ Condition + Exercise + Condition:Exercise dds <- DESeq(dds)

or

dds........design_ full: ~ Condition + Exercise + Condition:Exercise; reduced: ~ Condition + Exercise dds <- DESeq(dds, test="LRT", reduced=~Condition + Exercise)

Both I get

resultsNames(dds) [1] "Intercept" "ConditionCPvsHealthy" "ExerciseYesvsNo"
[4] "ConditionCP.ExerciseYes"

I'm trying to understand the differences in both models and any insight would be much appreciated.