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

Morris AP, Zeggini E - Genet. Epidemiol. (2010)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom. amorris@well.ox.ac.uk

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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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fig01: 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.

Mentions: Figure 1 shows the power of each of the tests of association as a function of the percentage of phenotypic variation explained by causal variants in the 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 here, each 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%. Model (b) incorporates fewer and, on average, more common causal variants than does (a), and thus represents a lower degree of allelic heterogeneity. Supplementary Figures 1 and 2 present power for a wider range of association models encompassing intermediate levels of allelic heterogeneity, where trait means are determined by the presence or absence of minor alleles at any causal variant, and by the proportion of causal variants at which a minor allele is present, respectively.


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

Morris AP, Zeggini E - Genet. Epidemiol. (2010)

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.
© Copyright Policy - open-access
Related In: Results  -  Collection

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fig01: 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.
Mentions: Figure 1 shows the power of each of the tests of association as a function of the percentage of phenotypic variation explained by causal variants in the 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 here, each 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%. Model (b) incorporates fewer and, on average, more common causal variants than does (a), and thus represents a lower degree of allelic heterogeneity. Supplementary Figures 1 and 2 present power for a wider range of association models encompassing intermediate levels of allelic heterogeneity, where trait means are determined by the presence or absence of minor alleles at any causal variant, and by the proportion of causal variants at which a minor allele is present, respectively.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom. amorris@well.ox.ac.uk

Show MeSH
Related in: MedlinePlus