@article {IgnacioMedina07012009,
	title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies},
	journal = {Nucl. Acids Res.},
	volume = {37},
	number = {suppl_2},
	year = {2009},
	pages = {W340-344},
	abstract = {<p>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/</p>},
	keywords = {babelomics, gene set, GESBAP, pathway-based analysis, SNP},
	doi = {10.1093/nar/gkp481},
	url = {http://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W340},
	author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Fatima Al-Shahrour and Dopazo, Joaquin}
}
@article {583,
	title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.},
	journal = {Nucleic Acids Res},
	volume = {37},
	year = {2009},
	month = {2009 Jul},
	pages = {W340-4},
	abstract = {<p>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/.</p>},
	keywords = {Biological Phenomena, Breast Neoplasms, Female, Genes, Genetic Variation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Software, User-Computer Interface},
	issn = {1362-4962},
	doi = {10.1093/nar/gkp481},
	author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin}
}
