title: Practical considerations regarding the use of genotype and pedigree data to model relatedness in the context of genome-wide association studies.
abstract: Genome-wide association studies of complex traits often are complicated by relatedness among individuals. Ignoring or inappropriately accounting for relatedness often results in inflated type I error rates. Either genotype or pedigree data can be used to estimate relatedness for use in mixed-models when undertaking quantitative trait locus mapping. We performed simulations to investigate methods for controlling type I error and optimizing power considering both full and partial pedigrees and, similarly, both sparse and dense marker coverage; we also examined real data sets. (1) When marker density was low, estimating relatedness by genotype data alone failed to control the type I error rate; (2) this was resolved by combining both genotype and pedigree data. (3) When sufficiently dense marker data were used to estimate relatedness, type I error was well controlled and power increased; however, (4) this was only true when the relatedness was estimated using genotype data that excluded genotypes on the chromosome currently being scanned for a quantitative trait locus.
authors: Department of Human Genetics, The University of Chicago, Illinois 60637.
authors: Riyan
authors: R
authors: Cheng
authors: Clarissa C
authors: CC
authors: Parker
authors: Mark
authors: M
authors: Abney
authors: Abraham A
authors: AA
authors: Palmer
mesh_terms: D000818:Animals; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D010375:Pedigree; D040641:Quantitative Trait Loci
keywords: quantitative trait locus (QTL); relatedness; statistical power; type I error rate
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