Are interaction terms symetrical with regard to the designation of main and secondary effect?
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kieran.mace ▴ 40
@kieranmace-11647
Last seen 6.3 years ago

Lets say I have a design that is ~ drugTreatment + environmentalCondition + drugTreatment:environmentalCondition

with factors with the following levels:

drugTreatment:

  1. control
  2. A
  3. B

environmentalCondition:

  1. standard
  2. heat
  3. osmotic

For the interaction term drugTreatmentA:environmentalConditionheat, one could it interpret its meaning as:

The difference in effect of that drugTreatmentA has when the environment is environmentalConditionheat compared to drugTreatmentAs main effect (on base level environment).

BUT:

I could also interpret the same interaction term as:

The difference in effect of that environmentalConditionheat has when the drug is drugTreatmentA compared to environmentalConditionheats main effect (base level drug).

Is this line of reasoning correct? Intuitivly I feel as if these values could be different.

In terms of design, I guess my question is:

for Design 1: ~ drugTreatment + environmentalCondition + drugTreatment:environmentalCondition

and Design 2: ~ environmentalCondition + drugTreatment + environmentalCondition:drugTreatment

are the interaction terms drugTreatmentA:environmentalConditionheat and environmentalConditionheat:drugTreatmentA the same?

If so, can someone please help me understand why this is the case?

In example 3 of the man page of ?results it makes reference to "the main effect", in my case, I don't know if the environmnet, or the drug is the main effect.

To make my question clearer, I created a diagram, I'd like to understand why the pink and red arrows are the same.

https://imgur.com/a/XshRM

deseq2 • 824 views
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I guess my confusion is coming from my base assumption. Which is that the the two effects on gene expression are not parallel, but rather sequential. For example, If gene 1 is completely silenced in the standard condition, then the drug has no chance of effecting that gene, even if it is a true target. Is it possible for me to figure out the sequential nature of regulation?

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kieran.mace ▴ 40
@kieranmace-11647
Last seen 6.3 years ago

I think I may have graphically answered my own question.

The interaction term in the design stated in my question is actually testing something different from what I originally thought. See new updated image below.

https://imgur.com/8twNdmn

If you wanted to test the coeficients I was talking about before, one would use ~environmentalCondition + environmentalCondition:drugTreatment and ~drugTreatment + drugTreatment:environmentalCondition

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The second interaction term is not meaningful. If I call the variables x and y, R's model.matrix() will ignore y:x if you already have a design of ~x + y + x:y, recognizing that you've already added the interaction between x and y. Since interaction terms are products between columns of the design matrix, and multiplication is commutative, there is no difference.

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Hi Michael, please can you expand on what you mean by the term not being meaningful, is this in response to the question's design? or my attempt at an answer?
In example 3, of the results man page, you use the same design that I use in my question:

dds <- makeExampleDESeqDataSet(n=100,m=18)
dds$genotype <- factor(rep(rep(c("I","II","III"),each=3),2))
design(dds) <- ~ genotype + condition + genotype:condition
dds <- DESeq(dds)
resultsNames(dds)
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Oops, I didn’t see the second line had it’s own tilde, I thought you had ~x + x:y + y + y:x. My mistake.

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