Good morning, I am analyzing Methylation EPIC BeadChip Data, comparing cases and controls. After the preprocessing and normalization of my data, I used the limma package to find differentially methylated probes/positions (DMPs) assuming a linear model where the M values of each probe were used as quantitative dependent variables in all analyses, and I add some covariates in the model such as cell composition, age, and gender. After running the linear model, I applied the statistical analysis using an empirical Bayes method to moderate standard errors. I found a lot of statistical differentially methylated positions, and I would like now to see the inflation factor of p.value distribution. Which is the best method to do it?

Hi, if I understand correctly you want to find out the variance inflation factor from this data right? Isn't there a function in limma like the

`camera`

and`cameraPR`

that provides are`data.frame`

with all these statistics? It also provides you a column with variance inflation factor (vif). Have you tried that out?