Usually, when I use WGCNA to make co-expression network and associated with correspond bench data. For example, A sample has -1, -2 -3 time point microarray data, and also -1, -2, -3 time point bench data(clinical data), it's usually WGCNA doing. However, some of the clinical data aren't matched with microarray data, as A sample has -1, -2 -3 time point microarray data, but has -1, -4, -5 time point bench data(clinical data). I wonder, in this case, could you still use WGCNA to make the investigate the association.
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.