...
This is all great and I agree with Brig's approach as it is very intuitive and unassuming. However, now that I proceed with data analysis it is critical for me to figure out which probes are actually methylated and which are not. Especially because I don't have any control data. How should I approach it? With M value the methods have been developed for drawing a cutoff (because the data has a distinctive bimodal shape). Should I take unmethylated probes, process them similarly to the methylated probes, combine them to make M values and apply the existing method (described here) to figure out what is methylated and what is not? Also, Bin has built comethylation networks based on mb and mbc normalization. Should I rebuild them with a new M value? Something to think about.
Important to remember: I didn't adjust the data for age or stage/grade. In comethylation networks we need to see if there is any association with age/stage/grade (this is the only biology that is available to us). I would also like to see comethylation network built with only stage III patients because it is the largest group and I am not sure how many more novel information we are gaining by keeping a few stage I, II and IV outliers.