Research

LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present


Reference:

Barral, S., Haynes, C., Stone, M. and Gordon, D., 2006. LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present. Bmc Genetics, 7.

Related documents:

This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below.

Abstract

Background: In the field of statistical genetics, phenotype and genotype misclassification errors can substantially reduce power to detect association with genetic case/control studies. Misclassification also can bias population frequency parameters such as genotype, haplotype, or multi-locus genotype frequencies. These problems are of particular concern in case/control designs because, short of repeated sampling, there is no way to detect misclassification errors. We developed a double-sampling procedure for case/control genetic association using a likelihood ratio test framework. Different approaches have been proposed to deal with misclassification errors. We have chosen the likelihood framework because of the ease with which misclassification probabilities may be incorporated into in the statistical framework and hypothesis testing. The statistic is called the Likelihood Ratio Test allowing for errors ( LRTae) and is freely available via software download. Results: We applied our procedure to 10,000 replicates of simulated case/control data in which we introduced phenotype misclassification errors. The phenotype considered is Ankylosing Spondylitis ( AS). The LRTae method power was always greater than LRTstd power for the significance levels considered ( 5%, 1%, 0.1%, 0.01%). Power gains for the LRTae method over the LRTstd method increased as the significance level became more stringent. Multi-locus genotype frequency estimates using LRTae method were more accurate than estimates using LRTstd method. Conclusion: The LRTae method can be applied to single-locus genotypes, multi-locus genotypes, or multi-locus haplotypes in a case/control framework and can be more powerful to detect association in case/control studies when both genotype and/or phenotype errors are present. Furthermore, the LRTae method provides asymptotically unbiased estimates of case and control genotype frequencies, as well as estimates of phenotype and/or genotype misclassification rates.

Details

Item Type Articles
CreatorsBarral, S., Haynes, C., Stone, M. and Gordon, D.
DOI10.1186/1471-2156-7-24
DepartmentsFaculty of Humanities & Social Sciences > Health
Faculty of Science > Pharmacy & Pharmacology
RefereedYes
StatusPublished
ID Code6467
Additional InformationID number: ISI:000237846300001

Export

Actions (login required)

View Item