I am working on methylation data and I want to use WGCNA on them. The data are the beta values of 400K CpG probes and ~30 samples which were transformed by log2(beta+1) (The data then have a nice scale-free topology profile when the soft threshold is calculated, I think it is a good sign? ). So, if someone already use WGCNA for this kind of data, I would have some questions: Firstly, are my data properly normalized? And secondly, how can I choose the maximal number of blocks for the blockWiseModule function ? I have access to a cluster, can I deduct the maxBlockSize when I know the available RAM?
Thanks in advance,
Have a nice day !