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.

Getting started

Package details

AuthorAtsushi Fukushima, Kozo Nishida
MaintainerAtsushi Fukushima <atsushi.fukushima@riken.jp>
LicenseGPL (> 3)
Package repositoryView on CRAN
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DiffCorr documentation built on May 2, 2019, 3:46 p.m.