afukushima/DiffCorr: Analyzing and Visualizing Differential Correlation Networks in Biological Data

A method for identifying pattern changes between 2 experimental conditions in correlation networks (e.g., gene co-expression networks), which builds on a commonly used association measure, such as Pearson's correlation coefficient. This package includes functions to calculate correlation matrices for high-dimensional dataset and to test differential correlation, which means the changes in the correlation relationship among variables (e.g., genes and metabolites) between 2 experimental conditions.

install.packages("remotes")
remotes::install_github("afukushima/DiffCorr")