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Nucleic Acids Research Advance Access published online on June 5, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp481
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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.

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Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies

Ignacio Medina1,2, David Montaner1,3, Nuria Bonifaci4,5, Miguel Angel Pujana4,5, José Carbonell1, Joaquin Tarraga1,3, Fatima Al-Shahrour1 and Joaquin Dopazo1,2,3,*

1Department of Bioinformatics and Genomics, CIPF, 2CIBER de Enfermedades Raras (CIBERER), 3Functional Genomics Node (INB) at CIPF, Valencia, 4Bioinformatics and Biostatistics Unit and 5Translational Research Laboratory, IDIBELL, Barcelona, Spain

*To whom correspondence should be addressed. Tel: +34 963289680; Fax: +34 963289701; Email: jdopazo{at}cipf.es

Received February 7, 2009. Revised May 1, 2009. Accepted May 19, 2009.

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/


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