Hi everyone,

I’m working on an RNA-seq dataset with three different drug treatments (let’s call them C, D, and E) and I’m trying to understand whether drug C acts differently from the other two, and if so, in what way.

I’m using a standard limma-voom pipeline and I’m a bit unsure about the best strategy to define contrasts for this question.

Current approaches I’m considering:

1. Pairwise contrasts + intersection

• C vs D
• C vs E Then:
• identify DE genes in each contrast
• take the intersection (possibly also requiring same direction of logFC)

The idea would be that genes consistently different in both contrasts represent a “C-specific signature”.

2. Combined contrast

• C − (D + E) / 2

This would directly test whether C differs from the average effect of D and E.

From a statistical and biological interpretation standpoint, which approach is more appropriate for identifying C-specific effects?

Any advice or references would be really appreciated.

Thanks in advance!