Dear Community,

My RNA-Seq experiment has three factors: A, B and C. A and B are random effects while C is fixed effect. I would like to fit a mixed model including all of the main effects and interaction terms, i.e.,

model=A  + B + C  + A x B   + A x C  + B x C + A x B x C 

Can DESeq2 or edgeR fit the mixed model? Thanks.

When I searched "DESeq/DESeq2/edgeR random effect", I found this post: http://seqanswers.com/forums/archive/index.php/t-16539.html

Simon mentioned that uses shrinkage for random effect, and DESeq2 has already considered the shrinkage for dispersion and coefficient.

My Question is: how to use shrinkage in DESeq2 modeling so that I can fit the mixed model mentioned above.

Thanks.

Yanzhu

While DESeq2 does have moderation on the log2 fold changes between conditions, I would not call it a random effects model.

DESeq2 is a strictly fixed effects model, and we apply a zero-centered Gaussian prior to these effects, and report maximum a posteriori estimates as the final log2 fold changes.

A related point I would make is that limma has a function duplicateCorrelation, which allows you to inform that model of the correlation between sets of samples.