Hi all

As the newbie I am, I would really appreciate your help!

I would like to apply a similar approach to WGCNA, but taking into account more than one omics data types, so I cannot use WGCNA itself (I think).

I was considering doing the following:

- Instead of the co-expression measure, I will create a matrix where I will add up the correlation values that resulted in three independent correlation tests in each of the data type.
- Convert the above matrix into an adjacency matrix, if the summed correlations are over a threshold (I was considering a cut off of 0.7 considering that for some of the data types I am using most of the correlations are low).
- Use WGCNA´s functions for the rest of the analysis.

Would that be a reasonable thing to do with respect to the first steps? I have not found any similar approaches, or cases where they have used WGCNA to something other than co-expression.

Thanks you in advance.

R.