I need some feedback for defining contrasts in edgeR.
We are using sequencing to count shRNAs in a screen aiming to understand the effect of drug treatment in one cell line. We work with two time points (t0 and t1) and four drug treatment levels (untreated, solvent, drug1 and drug2). The experimental setup grouped all time points and treatments in four groups (three replicates per group): t0_untreated, t1_solvent, t1_drug1 and t1_drug2. Solvent is the media used to dissolve the drugs for t1_drug1 and t1_drug2.
The rows of our count table are all shRNAs and 12 columns corresponding to 4 groups * 3 replicates so that my design matrix used to estimate common dispersion and fit a negative binomial GLM looks as follows:
t0_untreated t1_solvent t1_drug1 t1_drug2
t0_untreated_1 1 0 0 0
t0_untreated_2 1 0 0 0
t0_untreated_3 1 0 0 0
t1_solvent_1 0 1 0 0
t1_solvent_2 0 1 0 0
t1_solvent_3 0 1 0 0
t1_drug1_1 0 0 1 0
t1_drug1_2 0 0 1 0
t1_drug1_3 0 0 1 0
t1_drug2_1 0 0 0 1
t1_drug2_2 0 0 0 1
t1_drug2_3 0 0 0 1
We want to find the following:
(a) shRNAs specific to the t1_drug1 and t1_drug2 groups individually in comparison to t0_untreated and t1_solvent.
(b) shRNAs overlapping between t1_drug1 and t1_drug2 groups when compared to t0_untreated and t1_solvent.
So far I have used makeContrasts to define three contrasts:
contrast1 = t1_solvent - t0_untreated
contrast2 = t1_drug1 - t0_untreated
contrast3 = t1_drug2 - t0_untreated
Then used glmLRT for each contrast individually, then topTags fixing a FDR threshold (e.g. 10^(-3)), which would give me shRNAs for questions (a) and (b) above. E.g. drug1 specific shRNAs would be obtained from the hits in for contrast2 excluding shared hits with contrast1 and contrast3 at the same FDR threshold.
However I am wondering whether it would be possible to define other contrasts in order to answer (a) and (b) directly. Here are some ideas, would any of the following make sense for you?
One option for (a): specific shRNAs for drug1 and drug2 respectively:
contrast4 = (t1_drug1 - t0_untreated) - (t1_drug2 - t0_untreated) - (t1_solvent - t0_untreated)
contrast5 = (t1_drug2 - t0_untreated) - (t1_drug1 - t0_untreated) - (t1_solvent - t0_untreated)
A second option for (a):
contrast6 = t1_drug1 - 1/3*t1_drug2 - 1/3*t1_solvent - 1/3*t0_untreated
contrast7 = t1_drug2 - 1/3*t1_drug1 - 1/3*t1_solvent - 1/3*t0_untreated
In the same line of thought, for (b):
contrast8 = t1_drug1 + t1_drug2 - t1_solvent - t0_untreated
Any ideas will be useful.