Methods in Molecular Biology

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

Nolwenn Le Meur1,2,*, Robert Gentleman2

∗ Corresponding author (nlemeur@irisa.fr)

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

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

Abstract

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.

Keywords

graph, random graph, network, statistic, systems biology

Downloads

Dataset.

Files used to build the dataset.

R commands used to run the analyses.

Fred Hutchinson Cancer Research Center