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Bioinformatics Advance Access originally published online on March 23, 2009
Bioinformatics 2009 25(11):1470-1471; doi:10.1093/bioinformatics/btp167
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor

Jitao David Zhang * and Stefan Wiemann

Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), INF 580, 69120 Heidelberg, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: KEGG PATHWAY is a service of Kyoto Encyclopedia of Genes and Genomes (KEGG), constructing manually curated pathway maps that represent current knowledge on biological networks in graph models. While valuable graph tools have been implemented in R/Bioconductor, to our knowledge there is currently no software package to parse and analyze KEGG pathways with graph theory.

Results: We introduce the software package KEGGgraph in R and Bioconductor, an interface between KEGG pathways and graph models as well as a collection of tools for these graphs. Superior to existing approaches, KEGGgraph captures the pathway topology and allows further analysis or dissection of pathway graphs. We demonstrate the use of the package by the case study of analyzing human pancreatic cancer pathway.

Availability:KEGGgraph is freely available at the Bioconductor web site (http://www.bioconductor.org). KGML files can be downloaded from KEGG FTP site (ftp://ftp.genome.jp/pub/kegg/xml).

Contact: j.zhang{at}dkfz-heidelberg.de

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Thomas Lengauer

Received on December 15, 2008; revised on February 23, 2009; accepted on March 19, 2009

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