Is their a way to compare two gene co-expression networks or correlation matrizes of the same genes? My idea was to just compare the pearson correlation values of the gene pairs eg. check for differences in the correlation matrix. But a pearson correlation of 0.7 could mean something different in the first data compared to the second, so maybe there is a way to normalize a correlation matrix?
You can test whether the difference between the two correlation matrices is statistically significant using Jennrich's test implemented in R in the psych package in function cortest.jennrich(). Alternatively, an idea for comparing two networks would be to compare the transition matrices of the random walks on these networks.