Abstract
BackgroundGenome-wide association studies are a promising new tool for deciphering the genetics of complex diseases. To choose the proper sample size and genotyping platform for such studies, power calculations that take into account genetic model, tag SNP selection, and the population of interest are required.ResultsThe power of genome-wide association studies can be computed using a set of tag SNPs and a large number of genotyped SNPs in a representative population, such as available through the HapMap project. As expected, power increases with increasing sample size and effect size. Power also depends on the tag SNPs selected. In some cases, more power is obtained by genotyping more individuals at fewer SNPs than fewer individuals at more SNPs.ConclusionGenome-wide association studies should be designed thoughtfully, with the choice of genotyping platform and sample size being determined from careful power calculations.
Highlights
Genome-wide association studies are a promising new tool for deciphering the genetics of complex diseases
It has been proposed that population-based association studies will be more powerful than traditional family-based linkage methods in identifying such high-frequency, low-penetrance alleles [1]. Such studies require the genotypes a large number of polymorphisms across the genome, each of which is tested for association with the phenotype of interest
This would be a direct test of association, in which the functional mutation is presumed to be genotyped
Summary
Genome-wide association studies are a promising new tool for deciphering the genetics of complex diseases. It has been proposed that population-based association studies will be more powerful than traditional family-based linkage methods in identifying such high-frequency, low-penetrance alleles [1]. Such studies require the genotypes a large number of polymorphisms (usually single nucleotide polymorphisms [SNPs]) across the genome, each of which is tested for association with the phenotype of interest. An alternate approach to association studies takes advantage of the correlation between SNPs, called linkage disequilibrium (LD), that can occur due to the genealogical history of the polymorphisms [2]. Recent advances in genotyping technology make such studies feasible [4,5] and the first results of such studies are being published [6,7,8,9,10]
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