title: Coverage and power in genomewide association studies.
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.
authors.affiliation: Department of Epidemiology and Biostatistics and Center for Human Genetics, University of California-San Francisco, San Francisco. Electronic address: jorg@itsa.ucsf.edu.
authors.forename: Eric
authors.initials: E
authors.lastname: Jorgenson
authors.affiliation: Department of Epidemiology and Biostatistics and Center for Human Genetics, University of California-San Francisco, San Francisco.
authors.forename: John S
authors.initials: JS
authors.lastname: Witte
mesh_terms: D002874:Chromosome Mapping; D014644:Genetic Variation; D015894:Genome, Human; D006801:Humans; D015810:Linkage Disequilibrium; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable