Type I error rates in association versus joint linkage/association tests in related individuals.
Positional gene discovery on pedigree data typically involves initial gross localization by linkage analysis with subsequent finer localization by association analysis in areas that show evidence of linkage. We examine the effect of including linkage information when testing for association in the context of variance-components-based pedigree analysis. We present simulation experiments showing that, at least in the extreme case of a rare private allele, failing to include the linkage variance component in the association model results in excessive Type I error that increases with allele copy number and/or quantitative trait locus (QTL) effect size. Joint estimation of the linkage variance component in the association model reduces Type I error to nominal expectations. This holds whether allele-sharing probabilities are estimated from a polymorphic marker or from the very single-nucleotide polymorphism (SNP) being tested for association, although the latter provides much less power. These results support the idea that an appropriate association analysis must test both the random effect of shared marker alleles (linkage) and the mean effects of the marker genotypes (association).
Kent
Jack W
JW
Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78245-0549, USA. jkent@sfbrgenetics.org
Dyer
Thomas D
TD
Göring
Harald H H
HH
Blangero
John
J
D000483:Alleles; D003198:Computer Simulation; D005189:False Positive Reactions; D005260:Female; D018628:Gene Dosage; D005787:Gene Frequency; D005819:Genetic Markers; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium; D008126:Lod Score; D008297:Male; D008957:Models, Genetic; D009679:Nuclear Family; D010375:Pedigree; D019655:Quantitative Trait, Heritable; D011897:Random Allocation
D005819:Genetic Markers