Hello all,

I have two experimental conditions and one control, I want to compare the difference of these effects in reference to the control. A simple way to do this would to get the gene sets that result from comparing each experimental level to the control separately, and then take the difference of these sets. However, this might miss where the difference in effects is direction or magnitude. 

However, I am wondering if this can also be legitimately done using an interaction term? One would duplicate the control condition so that the setup would look like so (ignoring replicates here):

design(dds) <- ~Condition * Experimental_Condition

Note that the second control is just a duplicate of the first. 

The resulting genes from the interaction term, conditionExperimental.Experimental_Conditioncond2, would be where the effect was significantly different between the condition effects in reference to the control. I realize this is similar to the LRT test, where we would be looking to see if there are any differences at all between all the levels. But, we will still not get only the genes where the effect is different. Please correct me if I'm wrong. 

I also realize that this might mess with the dispersion estimates, as there is now a pseudo replicate.

Thanks,

-R

"Note that the second control is just a duplicate of the first. "

You mean, the identical samples? So the columns of counts are identical?

Note the following re-arrangement of terms:

(X-Z) - (Y-Z) = X-Y

If you want to compare condition 2 to condition 1, and they share the identical control, then it drops out of the numerator and denominator of the fold change. Am I reading your question correctly?