## Abstract Errors in genotyping can greatly affect family‐based association studies. If a mendelian inconsistency is detected, the family is usually removed from the analysis. This reduces power, and may introduce bias. In addition, a large proportion of genotyping errors remain undetected, and th
Testing for association with a case-parents design in the presence of genotyping errors
✍ Scribed by Richard W. Morris; Norman L. Kaplan
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 160 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Genotyping errors can create a problem for the analysis of case‐parents data because some families will exhibit genotypes that are inconsistent with Mendelian inheritance. The problem with correcting Mendelian inconsistent genotype errors by regenotyping or removing families in which they occur is that the remaining unidentified genotype errors can produce excess type I (false positive) error for some family‐based tests for association. We address this problem by developing a likelihood ratio test (LRT) for association in a case‐parents design that incorporates nuisance parameters for a general genotype error model. We extend the likelihood approach for a single SNP to include short haplotypes consisting of 2 or 3 SNPs. The extension to haplotypes is based on assumptions of random mating, multiplicative penetrances, and at most a single genotype error per family. For a single SNP, we found, using Monte Carlo simulation, that type I error rate can be controlled for a number of genotype error models at different error rates. Simulation results suggest the same is true for 2 and 3 SNPs. In all cases, power declined with increasing genotyping error rates. In the absence of genotyping errors, power was similar whether nuisance parameters for genotype error were included in the LRT or not. The LRT developed here does not require prior specification of a particular model for genotype errors and it can be readily computed using the EM algorithm. Consequently, this test may be generally useful as a test of association with case‐parents data in which Mendelian inconsistent families are observed. Genet Epidemiol 26:142–154, 2004. Published 2004 Wiley‐Liss, Inc.
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