gravatar for calen.p.ryan

3 hours ago by

I am running regressions using limma on 450k array DNA methylation data.

I'm interested in the relationship between circulating levels of a hormone and DNAm in ~144,000 CpG sites I've preselected based on variability (non variable sites likely won't tell us anything about our variable of interest).

I run regressions using limma, and plot the p-values, but they don't look uniform at all. The odd thing is that this is exactly the same for all 3 hormone measurements. I tried to remove covariates in case there is collinearity going on, many different versions of these models look exactly the same.


or here if that link isn't working.

What would explain this kind of distribution - sparse at high and low p-values, but uniform across the rest?

Is there some way I can 'fix' this? More robust tests I can run etc. to see if there is a relationship between my hormones and DNAm?

Source link