Hi!

I am having some difficulty defining the correct contrast to test for synergy of two treatments A & B vs AB using the deseq2 results function.
Treatment has 4 levels *A*, *B*, combined *AB* and reference level *control.*

When I set up contrasts e.g. `( AB - control ) - [(A - control) + (B - control)]`

I end up with `AB - A - B + control`

! How can I get rid of the double counted control here? What am I missing?
My design is `~ donor + condition + treatment + treatment:condition`

Thanks in advance for your time.

Thanks for helping Michael, Condition has two levels. I want to test if the combined AB treatment is different from the additive A and B treatment (AB - A - B) within either conditions. First in the reference condition, later adding the interaction term to test within the hypoxia condition.

Easiest is to code this as colData with the columns: condition, A (ctrl/trt), and B (ctrl/trt).

Then your design is

`~condition + A + B + condition:A + condition:B + A:B + condition:A:B`

Not sure I fully understand, could you explain a bit more in detail? Did you note that I have 4 levels in my treatment column? (A, B, AB and control) As I read it now I would create extra dummy columns in colData consisting of ones and zeros, with column A having entries as ones for when treatment is control or treatment A, and column B having entries as ones for when treatment is control or B. On paper I would not be able to set up the correct contrast? I'd get this I think:

(A + control - B - AB) - (B + control - A - AB) so I still do not end up with A + B - AB.

The design I suggested will allow you to assess whether there is an interaction with A and B, and whether this is same or different across condition. As it’s a complex design, if you’re not certain about the terms and how to connect them to interpretations, I’d recommend you to collaborate with a local statistician.

I am trying to do a similar test for synergy between treatments with a somewhat simpler experimental design. I have data from 3 animals that were treated with hormone A, hormone B, or their combination. Each animal received each of the treatments, so my original model design includes blocking by individual: ~ Animal + Treatment.

I would like to test for synergy between treatments A and B. Can you please suggest a model design for this, as well as how to extract genes showing synergistic rather than additive effects using the results function?

colData: