Hi,

I have a gene expression dataset that is equivalent to Example 3 in your ?results help page: 3 temperatures (cold, room, warm) and 2 conditions (control, treatment).

I ran DESeq2 with the following design: ~temperature + condition + temperature:condition. I have three research questions:

(1) Which genes are differentially expressed between control samples of the three different temperatures?
(before editing: What is the effect of the temperature on the control?)

results(dds, name="temperature_cold_vs_room", alpha=0.05, pAdjustMethod="BH")   
results(dds, name="temperature_warm_vs_room", alpha=0.05, pAdjustMethod="BH")

(2) Which genes are differentially expressed between control and treatment samples in a given temperature?
(before editing: What is the effect of the treatment for each temperature?)

results(dds, name="condition_treatment_vs_control", alpha=0.05, pAdjustMethod="BH")  
results(dds, contrast=list(c("condition_treatment_vs_control", "temperaturecold.conditiontreatment")), alpha=0.05, pAdjustMethod="BH")   
results(dds, contrast=list(c("condition_treatment_vs_control", "temperaturewarm.conditiontreatment")), alpha=0.05, pAdjustMethod="BH")  

(3) The expression of which genes changes upon treatment, but changes differently depending on the temperature?
(before editing: What is the effect of the temperature on the treatment?)

results(dds, name="temperaturecold.conditiontreatment", alpha=0.05, pAdjustMethod="BH")  
results(dds, name="temperaturewarm.conditiontreatment", alpha=0.05, pAdjustMethod="BH")  

Could you confirm that what I am doing is correct? And finally, for question 1, I don't know yet how to extract the respective results for warm versus cold?

Many thanks in advance,
Katrin

-- Edit: I have edited the wording of my questions, trying to make the questions more concise.

I see it this way: if you absolutely want to do the interaction design, you need to acknowledge: the baseline is estimated on your reference level of the interaction term, from the deseq vignette: "the main condition effect only represents the effect of condition for the reference level of genotype (I, or whichever level was defined by the user as the reference level). The interaction terms genotypeII.conditionB and genotypeIII.conditionB give the difference between the condition effect for a given genotype and the condition effect for the reference genotype." (substitute temperature for genotype)

This impacts your final question (how to check warm vs cold) as well as the implications for your other questions. I think you can use the group_A_vs_B nomenclature as well as the c("group", "A", "B") for the former (as long as all are in resultsNames).

For the first question, you do not need the interaction design. The first rule is to make sure your data and approach are suited for answering your question. Optimally: no more, no less.

For answering the second question, I would also recommend using the concatenation approach. Did you compare the outcome of your interaction result with the concatenation result?

For (3), I am not sure the first premise (changes upon treatment) is correct; as above, the baseline is estimated based on the reference level of temperature, so it should not matter if the gene is differentially expressed (I assume you used RT as the reference level). The interaction term just tells you the difference between the temperature effect for the reference level and the effect for the other temperature (so the second premise, differently depending on temperature, is correct, as far as I can tell).

I think this will be far easier to do if you follow the suggestion in the vignette and not use interactions, but instead make a new column which concatenates temp and treatment, and use contrasts to compare the desired sub-groups.

The interaction design is useful for answering the question "Which genes change with treatment, but change differently depending on temperature?"