title: Matching strategies for genetic association studies in structured populations.
abstract: Association studies in populations that are genetically heterogeneous can yield large numbers of spurious associations if population subgroups are unequally represented among cases and controls. This problem is particularly acute for studies involving pooled genotyping of very large numbers of single-nucleotide-polymorphism (SNP) markers, because most methods for analysis of association in structured populations require individual genotyping data. In this study, we present several strategies for matching case and control pools to have similar genetic compositions, based on ancestry information inferred from genotype data for approximately 300 SNPs tiled on an oligonucleotide-based genotyping array. We also discuss methods for measuring the impact of population stratification on an association study. Results for an admixed population and a phenotype strongly confounded with ancestry show that these simple matching strategies can effectively mitigate the impact of population stratification.
authors.affiliation: Perlegen Sciences, Mountain View, CA, 94043, USA. David_Hinds@perlegen.com
authors.forename: David A
authors.initials: DA
authors.lastname: Hinds
authors.forename: Renee P
authors.initials: RP
authors.lastname: Stokowski
authors.forename: Nila
authors.initials: N
authors.lastname: Patil
authors.forename: Karel
authors.initials: K
authors.lastname: Konvicka
authors.forename: David
authors.initials: D
authors.lastname: Kershenobich
authors.forename: David R
authors.initials: DR
authors.lastname: Cox
authors.forename: Dennis G
authors.initials: DG
authors.lastname: Ballinger
mesh_terms: D016022:Case-Control Studies; D005828:Genetics, Population; D009693:Nucleic Acid Hybridization; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide