Hello All,

Our lab is getting some interesting results whereby we have modules that have both positive and negative kme values in a signed network. If a higher power is used this goes away but the lower power already surpasses the R2 and k.means thresholds.  Any insight would be helpful.

Best,  
Duc
Thanks Kevin and all who have looked at this issue-- Peter Langfelder suggested bypassing use of TOM for the dissimilarity metric used to cluster, which can disagree sometimes substantially with expected module membership based on kME table (based on the experience with this and similar large multi-batch, batch-corrected, data).  The batch variance removal prior to WGCNA blockwiseModules() may/may not play a role, which begame the focus of the above post. Regardless, adding the parameter to bypass TOM and use the adjacency matrix instead, TOMType="none" seems to have handled all abnormal assignments in a kME table of a similar network, and I suspect it will work for these data.  Cf. [interactions on the bioconductor forum][1] for more of Peter's response.

Practical solution found -- I recommend Duc close this thread!

  [1]: https://support.bioconductor.org/p/119506/#119531