Hi, I am looking for a way to compare module connectivity between two networks created for two different behavioral phenotypes. Some background:
I am not using genes, but activated cells in different brain regions. Both networks have the same number and identity of regions (~500). I have 27 samples in network A and 25 in network B. The power threshold is the same for both networks (8) as is the min mod size (15 region; smaller than what is used since I only have 500 regions). I was thinking of using the color labels from one of my networks (A) and apply them to the second network (B). I was thinking that I could then use Fisher's Z-transform on the values for each region and then compare.
Is this a "good" way of going about this? If not, are there any other ideas?
Thanks,
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WGCNA has a set of tutorial to assess module preservation across indipendent datasets: link; check the tutorial number 3
However, I do not know if this analysis can be applied to your data
Yes, I just found this prior to your post. It is definitely applicable and is what I was looking for. Thanks