[R-sig-ME] Bayesian, MCMCglmm and multiple testing

Fiona Ingleby F.Ingleby at sussex.ac.uk
Thu Jul 23 09:39:06 CEST 2015

Hi everyone,

I’m working with gene expression data and am planning on running a mixed model with MCMCglmm for each gene in the dataset individually (>15000 models). 

With previous non-Bayesian approaches to this data, I have corrected results for multiple testing with the false discovery rate, and I’m wondering if there is a generally accepted way of correcting Bayesian results for multiple tests. I’ve had a look through some publications but I’m drawing a blank so would anyone be able to point me in the direction of some useful information? Either methods, or discussion about the consequences of multiple testing for Bayesian model results, would be really helpful.

It has been suggested to me to simply use the pseudo-p-values in the MCMCglmm output to adjust p-values, but to be honest I’ve always ignored the pMCMC values as I’ve found the intervals much more useful, so I’m not sure how good a solution this would be.

Thanks in advance for any help,


More information about the R-sig-mixed-models mailing list