title: Defining the power limits of genome-wide association scan meta-analyses.
abstract: Large-scale meta-analyses of genome-wide association scans (GWAS) have been successful in discovering common risk variants with modest and small effects. The detection of lower frequency signals will undoubtedly require concerted efforts of at least similar scale. We investigate the sample size-dictated power limits of GWAS meta-analyses, in the presence and absence of modest levels of heterogeneity and across a range of different allelic architectures. We find that data combination through large-scale collaboration is vital in the quest for complex trait susceptibility loci, but that effect size heterogeneity across meta-analyzed studies drawn from similar populations does not appear to have a profound effect on sample size requirements.
authors.affiliation: Wellcome Trust Centre for Human Genetics, Roosevelt Drive, University of Oxford, Oxford, United Kingdom.
authors.forename: Kay
authors.initials: K
authors.lastname: Chapman
authors.forename: Teresa
authors.initials: T
authors.lastname: Ferreira
authors.forename: Andrew
authors.initials: A
authors.lastname: Morris
authors.forename: Jennifer
authors.initials: J
authors.lastname: Asimit
authors.forename: Eleftheria
authors.initials: E
authors.lastname: Zeggini
mesh_terms: D005787:Gene Frequency; D018740:Genetic Heterogeneity; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015201:Meta-Analysis as Topic; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D018401:Sample Size