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. 2010 Feb;34(2):188-93.
doi: 10.1002/gepi.20450.

An evaluation of statistical approaches to rare variant analysis in genetic association studies

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Free PMC article

An evaluation of statistical approaches to rare variant analysis in genetic association studies

Andrew P Morris et al. Genet Epidemiol. 2010 Feb.
Free PMC article

Abstract

Genome-wide association (GWA) studies have proved to be extremely successful in identifying novel common polymorphisms contributing effects to the genetic component underlying complex traits. Nevertheless, one source of, as yet, undiscovered genetic determinants of complex traits are those mediated through the effects of rare variants. With the increasing availability of large-scale re-sequencing data for rare variant discovery, we have developed a novel statistical method for the detection of complex trait associations with these loci, based on searching for accumulations of minor alleles within the same functional unit. We have undertaken simulations to evaluate strategies for the identification of rare variant associations in population-based genetic studies when data are available from re-sequencing discovery efforts or from commercially available GWA chips. Our results demonstrate that methods based on accumulations of rare variants discovered through re-sequencing offer substantially greater power than conventional analysis of GWA data, and thus provide an exciting opportunity for future discovery of genetic determinants of complex traits.

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Figures

Fig. 1
Fig. 1
Power of six tests of rare variant association with a quantitative trait as a function of the percentage of phenotypic variation explained by causal variants in a 50 kb region, assuming the trait mean is determined by the presence or absence of minor alleles at any of the causal variants. Results for two models are presented, both assuming a total MAF of 5% for all causal variants in the region: (a) the maximum MAF of any individual causal variant is 0.5% and (b) the maximum MAF of any individual causal variant is 2%. Power is estimated at a 5% significance level over 10,000 replicates of data. Re-sequencing RVT1: test of phenotype association with the proportion of rare variants, discovered through re-sequencing, at which individuals carry minor alleles. Re-sequencing RVT2: test of phenotype association with the presence/absence of minor alleles in individuals at any rare variant discovered through re-sequencing. GWA <5% RVT1: test of phenotype association with the proportion of low-frequency variants on the GWA chip at which individuals carry minor alleles. GWA <5% RVT2: test of phenotype association with the presence/absence of minor alleles at any low-frequency variant on the GWA chip. GWA single SNP: standard trend test of quantitative trait association with each SNP on the GWA chip, with Bonferroni correction for multiple testing. GWA SNP haplotypes: haplotype trend test of association with the quantitative trait across all SNPs on the GWA chip.

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