This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data
Identification of genes associated with complex traits by testing the genetic dissimilarity between individuals
1 Department of Epidemiology, School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322, USA
2 Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA
3 Department of Statistics, University of Michigan, 439 West Hall, 1085 South University Avenue, Ann Arbor, MI 48109-1107, USA
BMC Proceedings 2011, 5(Suppl 9):S120 doi:10.1186/1753-6561-5-S9-S120Published: 29 November 2011
Using the exome sequencing data from 697 unrelated individuals and their simulated disease phenotypes from Genetic Analysis Workshop 17, we develop and apply a gene-based method to identify the relationship between a gene with multiple rare genetic variants and a phenotype. The method is based on the Mantel test, which assesses the correlation between two distance matrices using a permutation procedure. Using up to 100,000 permutations to estimate the statistical significance in 200 replicate data sets, we found that the method had 5.1% type I error at an α level of 0.05 and had various power to detect genes with simulated genetic associations. FLT1 and KDR had the most significant correlations with Q1 and were replicated 170 and 24 times, respectively, in 200 simulated data sets using a Bonferroni corrected p-value of 0.05 as a threshold. These results suggest that the distance correlation method can be used to identify genotype-phenotype association when multiple rare genetic variants in a gene are involved.