This is a support page about “Using the DiffCorr Package to Analyze and Visualize Differential Correlations in Biological Networks” - Book chapter in “Challenges of Computational Network Analysis with R”. Editors: Matthias Dehmer, Yongtang Shi, and Frank Emmert-Streib. WILEY.

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The R package DiffCorr affords users a simple and effective framework to detect differential correlations between 2 conditions in omics data. The approach is useful for the first step towards inferring causal relationships and detecting biomarker candidates.

We have used many R (and Bioconductor) packages in the book chapter, and those packages are updating day by day.

Here we keep you informed on those updates and additional instructions upsupported in the book chapter.

We will revise this page continually. If you have a question about this book and support page, feel free to contact us with the bottom comment system.

Important announcement

R code files

You can download the R scripts used in this book chapter.


Integrating R and Cytoscape

By adding cyREST app (, you can programmatically controll Cytoscape with R. You can reproduce the book chapter Figure 4.B and Figure 7.B with just running the R script in ( without controlling Cytoscape GUI manually.


Please feel free to contact us if you have any question.