I am a noob statistician and I am trying to build a gene co-expression network using pearson's correlation as a distance metric in my data. As I was doing this I caculated the correlation matrix which has values from [-1,1] and then squared this to make it [0,1] and then applied a threshold of 0.7 (totally arbitrary) and built a network.
When I was researching, I came across the package "coexnet" which does this in one-step. However when i compared the results they are varying. When I tried to look into the source code - I found this line.
simil <- abs(cor(t(difexp),use = "pairwise.complete.obs")) # line nbr 82 in the internalFunctions.R file
The author seems to have taken an absolute value.
What is the advice in this instance? Do we take the abs or square it? To me the negative values of r matrix means they are dissimilar which is now low when we do an abs.
Thanks in advance!