I am studying only one co-expression network utilizing WGCNA.
I would like to validate that the modules identified by WGCNA are significantly above randomly generated modules.
1. What would be the best way to do it?
2. Is there a way to utilize the modulePreservation function to study preservation of modules only in one network?
It looks like the modulePreservation function was designed to do more complicated analysis. To study preservation of modules between two (or more) networks. It also uses randomized data to asses the significance of the results. Maybe there is a way to use it only for one network?
Thank you!
1 answer
I was advised by an expert in this field that it is possible to use modulePreservation with a single data set. Single set can be supplied both as reference, and as a test set. In the results, one should focus on module quality.
See significance in: Zsummary.qual. Read more about statistics in: "Is my network module preserved and reproducible?" PloS Comp Biol. 7(1):e1001057
Hi David,
Suggestion was derived from Personal correspondence with WGCNA. You can also read the module preservation article (http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1001057).
One can see related works in: https://academic.oup.com/mbe/article/30/6/1384/1143158 https://www.nature.com/articles/s41398-021-01435-2?proof=tNature
Arik
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Hi. I am also facing the same issue. It would be great if you could help me out if you found a method to overcome this problem.
Hi,
right off the bat, I would generate a 'random' correlation matrix and use this as test in the
modulePreservationfunction. This is just an idea, I would like to have an opinion from an expert.I was advised by an expert in this field that it is possible to use modulePreservation with a single data set. Single set can be supplied both as reference, and as a test set. In the results, one should focus on module quality.
See significance in: Zsummary.qual. Read more about statistics in: "Is my network module preserved and reproducible?" PloS Comp Biol. 7(1):e1001057