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

Genes

Esther S. Lips²  Maarten Kooyman¹  Christiaan de Leeuw²  Danielle Posthuma² 

[1] Netherlands Bioinformatics Centre, Geert de Grooteplein 28, Nijmegen 6525 GA, The Netherlands; E-Mail:;Department of Complex Trait Genetics, Neuroscience Campus Amsterdam, VU University & VU Medical Center, Amsterdam 1081HV, The Netherlands; E-Mail:

关键词: gene-set analysis;    pathway analysis;    biological pathway;    genetic association;    GWAS;   

DOI  :  10.3390/genes6020238

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.