title: Power considerations for λ inflation factor in meta-analyses of genome-wide association studies.
abstract: The genomic control (GC) approach is extensively used to effectively control false positive signals due to population stratification in genome-wide association studies (GWAS). However, GC affects the statistical power of GWAS. The loss of power depends on the magnitude of the inflation factor (λ) that is used for GC. We simulated meta-analyses of different GWAS. Minor allele frequency (MAF) ranged from 0·001 to 0·5 and λ was sampled from two scenarios: (i) random scenario (empirically-derived distribution of real λ values) and (ii) selected scenario from simulation parameter modification. Adjustment for λ was considered under single correction (within study corrected standard errors) and double correction (additional λ corrected summary estimate). MAF was a pivotal determinant of observed power. In random λ scenario, double correction induced a symmetric power reduction in comparison to single correction. For MAF 1·2 and MAF >5%. Our results provide a quick but detailed index for power considerations of future meta-analyses of GWAS that enables a more flexible design from early steps based on the number of studies accumulated in different groups and the λ values observed in the single studies.
authors.affiliation: Department of Therapeutics,University of Athens,Alexandra Hospital,80 Vas. Sofias Ave,GR-11528,Athens,Greece.
authors.forename: Georgios
authors.initials: G
authors.lastname: Georgiopoulos
authors.affiliation: Department of Hygiene and Epidemiology,University of Ioannina Medical School,Ioannina,Greece.
authors.forename: Evangelos
authors.initials: E
authors.lastname: Evangelou
mesh_terms: D005787:Gene Frequency; D016678:Genome; D055106:Genome-Wide Association Study / Q000379:methods* / Q000706:statistics & numerical data; D005838:Genotype; D006801:Humans; D008432:Mathematical Computing; D015201:Meta-Analysis as Topic; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide