The data should just be any normalised dataset that has undergone the standard QC filtering and data processing for things like background noise (microarray), low count transcripts, etc. As WGCNA is fundamentally based on correlation, the data does not necessarily have to be logged or on the Z-scale. Just any normalised data is fine, and obviously it makes sense that all samples are processed in the same way.
WGCNA states not to use differentially expressed genes because it was designed as an unsupervised clustering procedure.
For other network methods, you'd have to check what respective data inputs are required.