I'm using ChAMP for the analysis of my DNA methylation data obtained with EPIC. I have samples from a set of participants in two time points. I would like to identify the differentially methylated positions between the two time points. The values of Sample_Group are "first" and "second" (standing for first visit and second visit). So the appropriate command would be:
myDMP<-champ.DMP(beta = myCombat,pheno = myLoad$pd$Sample_Group,adjPVal = 0.05,adjust.method = "BH",compare.group = NULL,arraytype = "EPIC")
right? Moreover, from the champ.SVD analysis I have seen that some of the control probes and the proportions of cells types are correlated with methylation levels, even after correcting for batch effects (champ.runCombat). At that point, I would like to clarify something: in the ChAMP package pipeline when it is mentioned in the champ.SVD part that "the darker the color is, the more significant your deconvoluted components are correlated with your phenotype", the "phenotype" describes the methylation levels, right?
Is there any option to include this information in the champ.DMP command and use these variables as covariates in the statistical model?