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Genes 2015, 6(2), 238-251; doi:10.3390/genes6020238

JAG: A Computational Tool to Evaluate the Role of Gene-Sets in Complex Traits

1
Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University & VU Medical Center, Amsterdam 1081HV, The Netherlands
2
Netherlands Bioinformatics Centre, Geert de Grooteplein 28, Nijmegen 6525 GA, The Netherlands
3
Delft Bioinformatics Lab, Delft University of Technology, Delft 2600GA, The Netherlands
4
Radboud University Nijmegen, Nijmegen 6525EC, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editor: J. Peter W. Young
Received: 20 November 2014 / Accepted: 27 April 2015 / Published: 14 May 2015
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Abstract

Gene-set analysis has been proposed as a powerful tool to deal with the highly polygenic architecture of complex traits, as well as with the small effect sizes typically found in GWAS studies for complex traits. We developed a tool, Joint Association of Genetic variants (JAG), which can be applied to Genome Wide Association (GWA) data and tests for the joint effect of all single nucleotide polymorphisms (SNPs) located in a user-specified set of genes or biological pathway. JAG assigns SNPs to genes and incorporates self-contained and/or competitive tests for gene-set analysis. JAG uses permutation to evaluate gene-set significance, which implicitly controls for linkage disequilibrium, sample size, gene size, the number of SNPs per gene and the number of genes in the gene-set. We conducted a power analysis using the Wellcome Trust Case Control Consortium (WTCCC) Crohn’s disease data set and show that JAG correctly identifies validated gene-sets for Crohn’s disease and has more power than currently available tools for gene-set analysis. JAG is a powerful, novel tool for gene-set analysis, and can be freely downloaded from the CTG Lab website. View Full-Text
Keywords: gene-set analysis; pathway analysis; biological pathway; genetic association; GWAS gene-set analysis; pathway analysis; biological pathway; genetic association; GWAS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lips, E.S.; Kooyman, M.; de Leeuw, C.; Posthuma, D. JAG: A Computational Tool to Evaluate the Role of Gene-Sets in Complex Traits. Genes 2015, 6, 238-251.

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