I am a novice working on a 450k methylation array analysis. I have a very simple design which is to see the differentially methylated genes b/w smoking (1) vs non-smoking (0). This is the following I did.
# using smoking_primary as the factor in interest design <- model.matrix(~0 + smoking_primary) # Make contrasts 0 is the control and 1 is the test contrast <- makeContrasts(smoking_primary0 - smoking_primary1, levels = design) # fit to methyaltion set fit <- lmFit(m_norm_qc, design) fit2 <- contrasts.fit(fit, contrast) fit2 <- eBayes(fit2) ## Add the annotations to the results ann450kSub <- ann450k[match(rownames(m_norm_qc),ann450k$Name), c(1:4,12:19,24:ncol(ann450k))] DMPs <- topTable(fit2, num=Inf, coef=1, genelist = ann450kSub)
Could you please review this and tell me if it is the correct way to do the analysis?
In addition, how should I approach adding covariates to my design? If you could point me to the resource where I could get more info that would be very helpful. I checked the limma manual but it seems a little confusing for a simple design like mine.
Thank you for your time on this post.