graphite - a Bioconductor package to convert pathway topology to gene network

BMC Bioinformatics

Software

Gabriele Sales¹  Enrica Calura¹  Chiara Romualdi¹  Duccio Cavalieri² 

[1] Department of Biology, University of Padova, via U. Bassi 58/B, Padova, Italy;Department of Computational Biology, Istituto Agrario di San Michele all'Adige, Trento, Italy;

关键词: Acute Lymphocytic Leukemia;    Chronic Myeloid Leukemia;    Bioconductor Package;    Adult Acute Lymphocytic Leukemia;    Pathway Topology;   

DOI  :  10.1186/1471-2105-13-20

 received in 2011-09-30, accepted in 2012-01-31,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundGene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses.Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families.ResultsHere we present graphite, a Bioconductor package addressing these issues. Pathway information from four different databases is interpreted following specific biologically-driven rules that allow the reconstruction of gene-gene networks taking into account protein complexes, gene families and sensibly removing chemical compounds from the final graphs. The resulting networks represent a uniform resource for pathway analyses. Indeed, graphite provides easy access to three recently proposed topological methods. The graphite package is available as part of the Bioconductor software suite.Conclusionsgraphite is an innovative package able to gather and make easily available the contents of the four major pathway databases. In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements.

【 授权许可】

Unknown   
© Sales et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.