When I use WGCNA, I usually have matched microarray data and clinical data, which means for each patient and each time point, the microarray data and clinical data are matched. However, some of the clinical data are coming out later, like the antibody, usually, Ab will be tested after 1 or 2 months, but the microarray data only have 1-2 weeks time points. I wonder, in this case, could you still use WGCNA to make the co-expression network. Match the patient, but not for the time point. I’m not sure if that’s correct.
And, for the module number, usually, how many modules do make sense? When I plot the relationship between module eigengenes, some of them have correlation higher than 0.8, does that mean I can merge them into one module? I do not sure how to determine the cutoff value for merging the modules.
You can build the co-expression network and match it with the data you want. What will be harder is the interpretation of the data.
Depending what do you want to do you can merge the modules or not. Why would you want to merge modules which are tightly correlated but have different pattern of co-expression?