the dmpFinder function in minfi is great. But the next question is how do I control for co-variates that clearly effect DNA methylation. For instance, it's well known that smoking effects DNA methylation.
Say I'm determining differences in CpG methylation between schizophrenia patients (who are known to be heavy smokers) and healthy controls. If I collect some arbitrary smoking score from all subjects, how can I incorporate and control for smoking score when I calculate differences in CpG methylation between the two groups?
Attempting to answer my own question, it looks like limma can help me. But I don't see any clear workflows/pipelines online that explain how to incorporate and control for co-variates in design matricies created for limma.
Can someone point me to a pipeline that can offer me guidance for what I want to do? if not, any general suggestions or tips would be MUCH appreciated.
NOTE: A cross-package Bioconductor workflow for analysing methylation array data by Maksimovic did not really help as she explained paired analysis with methylation data in limma which is not what I want.
**Im a novice to bioconductor btw. I'd say I'm well versed with minfi, but now that I'm trying to figure out how to build models to answer more complex questions I've hit the wall (despite all the time I've spent reading limma documentations and user guides)