Question: DESeq2: paired samples + controls
0
gravatar for guidobarzaghi
5 months ago by
University of Copenhagen
guidobarzaghi20 wrote:

Hi fellow DESeq'ers!

I am trying to figure out how to model a DEA with n paired samples (so n conditions + n controls, where the two sample sets come from the same individuals) plus two unrelated controls. So overall I am dealing with n condition + n+2 controls.

From the DESeq2 Vignette I could read that a paired experiment should be modeled as ~subject+condition, but I am wondering if this could work in my case as well.

Many many thanks in advance!

deseq2 • 135 views
ADD COMMENTlink modified 5 months ago by Michael Love24k • written 5 months ago by guidobarzaghi20
Answer: DESeq2: paired samples + controls
0
gravatar for Michael Love
5 months ago by
Michael Love24k
United States
Michael Love24k wrote:

In DESeq2 which uses fixed effects, the unpaired samples do not contribute to more information about the condition effect, because they do not have a corresponding treatment sample. So you can leave them out.

There is another method in limma-voom, called duplicateCorrelation(), which allows you to include them, as it does some extra modeling on the degree of correlation between the paired samples.

ADD COMMENTlink written 5 months ago by Michael Love24k

Wow, that was quick (thanks a lot for that).

I am only unsure about the meaning of "fixed effects", could you briefly elaborate on that?

ADD REPLYlink written 5 months ago by guidobarzaghi20

Maybe that's not very useful for me to have added, but I mean it to contrast against random or mixed effects modeling which can be more flexible for dealing with correlations among units.

https://en.wikipedia.org/wiki/Mixed_model

ADD REPLYlink written 5 months ago by Michael Love24k

Perfect, I think I got my head around this concept a bit more.

My final doubt then is whether adding those two external controls would somehow mislead the analysis or would it just add no information.

ADD REPLYlink written 5 months ago by guidobarzaghi20

In this design it just adds no information. I don’t think it produces any problem for the inference. I know this is the case for linear modeling at least.

ADD REPLYlink written 5 months ago by Michael Love24k

Alright, thanks a lot for you help!

ADD REPLYlink written 5 months ago by guidobarzaghi20
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