Does metagenomeSeq handle mixed models including random effects? If yes, how can I incorporate those random effects in the model?Thanks!

Random effects metagenomeSeq

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Does metagenomeSeq handle mixed models including random effects? If yes, how can I incorporate those random effects in the model?Thanks!

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Short answer: Currently, no.

Long answer:

The `fitZig` function outputs a MArrayM object which can then be used to run limma's duplicatedCorrelation function.

This is implemented in metagenomeSeq using the duplicateCorrelation function when the option useMixedModel==TRUE, but is still considered in development.

See the instructions in limma's manual for how the function should be called.

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Hello,

I also have a question about use of random effects with fitZig. I am currently trying to run the following model:

design = model.matrix(~0+var1+var2+var3)

dup <- duplicateCorrelation(MRcounts(MRexp),block=subject, design= design)

model = fitZig(obj = MRexp, mod = design, control = settings, useCSSoffset=FALSE, useMixedModel=dup$consensus)

This is what I understand to be correct from limma's user manual. However, when I then call res$dupcor, I get "NULL" -- as if that part of the model wasn't called.

In addition, the results of the above model are exactly the same when I don't call "useMixedModel".

My conclusion is that fitZig isn't incorporating the "useMixedModel" statement. Is this correct, or is something wrong with my model statement?

I am using metagenomeSeq version 1.12.0.

Thank you in advance for any help you can provide!

Noelle

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