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Bioinformatics Advance Access published online on March 7, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm072
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

codelink: An R package for analysis of GE Healthcare Gene Expression Bioarrays

Diego Diez 1,2,*, Rebeca Alvarez 3 and Ana Dopazo 3

1Instituto de Investigaciones Biomédicas Alberto Sols, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, Arturo Duperier 4, 28029 Madrid, Spain, 2Current address: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611–0011, Japan and 3Genomics Unit, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, 28029 Madrid, Spain

*To whom correspondence should be addressed. Dr. Diego Diez, E-mail: diez{at}kuicr.kyoto-u.ac.jp


  Abstract

Motivation: Microarray based expression profiles have become a standard methodology in any high throughput analysis. Several commercial platforms are available, each with its strengths and weaknesses. The R platform for statistical analysis and graphics (Team, 2005) is a powerful environment for the analysis of microarray data, because it has many integrated statistical methods available as well as the specialized microarray analysis project Bioconductor (Gentleman, et al., 2004). Many packages have been added in the last few years increasing the range of possible analysis. Here we report the availability of a package for reading and analyzing data from GE Healthcare Gene Expression Bioarrays within the R environment.

Availability: The software is implemented in the R language, is open source and available for download free of charge through the Bioconductor (http://www.bioconductor.org) project.

Associate Editor: Dr. Joaquin Dopazo

Received on January 30, 2007; revised on February 21, 2007; accepted on February 22, 2007

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