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.
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