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Methods in Molecular Biology

Analyzing biological data using R: methods for graphs and networks.

Nolwenn Le Meur1,2,*, Robert Gentleman2

∗ Corresponding author (

1 IRSET EA SeRAIC 4427 - IRISA - Equipe Symbiose, Université de Rennes I Campus de Beaulieu, 35042 Rennes cedex, France. E-mail:

2 Fred Hutchinson Cancer Research Center, Program in Computational Biology, M2-B876, P.O. Box 19024, Seattle, WA 98109, USA. E-mail:


R is a powerful language and widely used software tool for the analysis and visualization of data. Its core capabilities can be extended through many different add-on packages. Among the many packages are some which offer a broad range of facilities for analyzing statistical properties of graphs. This chapter will provide a practical tutorial covering the use of R methods for graphs and networks to examine biological data and analyze their topological and statistical properties.


graph, random graph, network, statistic, systems biology



Files used to build the dataset.

R commands used to run the analyses.