I've been having some trouble with getting my pipeline to execute what I want. Below is my ColData, and what I would like to look at is the following. First I would like to look at the main effect of treatment. I tried Design = Clone + Treatment and did a contrast of VPA vs Unt, but the results were way higher then they should've been, so something isn't right.

Then, I would like to look at the interaction effect, which I believe can be done with Design= Disease + Treatment, but I am not sure if I am executing things correctly, and I don't believe my resultsName(dds)- is showing me what I would like...but basically would like to look at SMS-VPA vs SMS-Unt, Cont-VPA vs Con-Unt etc etc

Any advice or help with be greatly appreciated

    Clone Disease Treatment Age
AT.1    A1  SMS   VPA       Y
AT.2    A2  SMS   VPA       Y
AT.3    A3  SMS   VPA       Y
AU.1    A1  SMS   Unt       Y
AU.2    A2  SMS   Unt       Y
AU.3    A3  SMS   Unt       Y
OT.1    O1  Con   VPA       Y
OT.2    O2  Con   VPA       O
OT.3    O3  Con   VPA       O
OU.1    O1  Con   Unt       Y
OU.2    O2  Con   Unt       O
OU.3    O3  Con   Unt       O

Have you done PCA on your samples to see how they look compared to each other?

To do a simple comparison of one subset of samples to another subset of samples, make a new column in ColData that is the disease concatenated to the treatment, and make that your design.

Take a look at the vignette section on interactions first.

Secondly, if you want to do some exploration, use plotCounts on the top genes to understand why they are identified as DE.