Analyzing and Visualizing Differential Correlation Networks in Biological Data
Hierarchical clustering of molecules
Export differential correlations between two conditions
Compare two correlation coefficients
Additional distance functions correlation distance (1-r)
Correlation Test
Differential correlations in omics datasets
Generating graph from data matrix
Getting graph from eigengene module list
Get eigen molecule
Getting local false discovery rate (lfdr)
Get minimum and maximum
Plot cluster molecules
Plot DiffCorr group
scalingMethods
Additional distance functions correlation distance (uncentered)
Calculating all pairwise distances using correlation distance
Writing modules into a text file
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.