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Dear all
As I just started using WGCNA, it's not entirely clear for me what's the difference between "signed" and "signed hybrid" networks. Can anyone clarify, please?
Many thanks in advance!
7
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In practical terms, the difference is negligible.
In a signed network, the similarity is defined as (1+cor)/2; in a signed hybrid the similarity equals the correlation if the correlation is positive and zero otherwise (it is called hybrid because it is a hybrid of weighted and unweighted networks). The similarity is raised to a power which is usually twice as big in signed networks than it is in hybrid networks. For correlations near 1, ( (1+cor)/2 )^(2*beta) approximately equals cor^beta, and for low correlations both adjacencies are near zero.
Peter
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Dear Dr. Langfelder
Many thanks for your quick response! As the difference between signed and signed hybrid is neglibigle, is there a difference in their applications? For instance, do you recommend one of both when analyzing data in relation to a binary trait? Many thanks for your answer.
I usually use signed hybrid since I like to have adjacencies for negative correlations exactly zero and I find the formula cor^beta "cleaner", but as I said, these are more "cosmetic" rather than fundamental reasons.