Haplotype frequency estimation in the presence of genotyping errors.
Several statistical methods have been proposed to estimate haplotype frequencies, either based on unrelated individuals or based on families. These estimates may yield insights on population genetics as well as associations between candidate regions and disease of interest. One limitation of the existing methods is that all these methods make the implicit assumption that there are no genotyping errors. However, genotyping errors are unavoidable in practice. Numerous methods have been developed to incorporate genotyping errors in genetic studies, but none to date have addressed the issues of haplotype inference in the presence of genotyping errors. In this article, we develop statistical methods for haplotype inference incorporating genotyping errors. We describe how our methods can be applied to analyze unrelated individuals as well as nuclear families. Our simulation results show that the proposed methods perform well in the presence of genotyping errors.
Zou
Guohua
G
Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520-8034, USA.
Zhao
Hongyu
H
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005787:Gene Frequency; D005838:Genotype; D006239:Haplotypes; D006801:Humans