Variance components analysis for genetic linkage of time to onset for disease.
We compared two variance components methods for detecting genes that influence time to onset for a complex disease using simulated data. We first divided the extended families into nuclear families. The first method fitted variance components to the martingale residuals, which were obtained from first fitting a proportional hazards model to the time to onset data for the trait, allowing for the quantitative traits Q1-Q5, sex, age, and the environmental factor. The second method treated time to onset among the affected individuals as a quantitative trait adjusting for the same factors as in the first method. Power of these analyses were similar for either approach. However, we found an excess of false-positive results when fitting the martingale residual model or the affected-only model to identify genetic factors linked to chromosome 6. Applying a power transformation to the martingale residuals decreased the type I error rate and increased the power of tests for genetic linkage. We also found that robust variance correction lead to test with a slightly lower type I error rate, perhaps because the robust variance correction adjusts for the fact that we did not specifically model the effects of the mitochondrial factor in our analysis.
Amos
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Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd., Box 189, Houston, TX 77030, USA.
Shete
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D000704:Analysis of Variance; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D002896:Chromosomes, Human, Pair 6; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005820:Genetic Testing; D005838:Genotype; D006801:Humans; D008126:Lod Score; D008957:Models, Genetic; D016016:Proportional Hazards Models; D019655:Quantitative Trait, Heritable; D016019:Survival Analysis
D005819:Genetic Markers