Coverage and power in genomewide association studies.

Eric Jorgenson; John S Witte

doi:10.1086/503751

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PubMed · 16642443

Coverage and power in genomewide association studies.

Eric Jorgenson·John S Witte

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Abstract

The ability of genomewide association studies to decipher genetic traits is driven in part by how well the measured single-nucleotide polymorphisms "cover" the unmeasured causal variants. Estimates of coverage based on standard linkage-disequilibrium measures, such as the average maximum squared correlation coefficient (r2), can lead to inaccurate and inflated estimates of the power of genomewide association studies. In contrast, use of the "cumulative r2 adjusted power" measure presented here gives more-accurate estimates of power for genomewide association studies.

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Chromosome Mapping Genetic Variation Genome, Human Humans Linkage Disequilibrium Models, Statistical Polymorphism, Single Nucleotide Quantitative Trait, Heritable Journal Article Research Support, N.I.H., Extramural

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Eric Jorgenson, John S Witte. 2006-03-17. Coverage and power in genomewide association studies.. https://doi.org/10.1086/503751

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