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首页> 外文期刊>Annals of Human Genetics >Haplotype Misclassification Resulting from Statistical Reconstruction and Genotype Error, and Its Impact on Association Estimates
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Haplotype Misclassification Resulting from Statistical Reconstruction and Genotype Error, and Its Impact on Association Estimates

机译：统计重建和基因型错误导致的单倍型分类错误及其对关联估计的影响

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摘要

SummaryHaplotypes are an important concept for genetic association studies, but involve uncertainty due to statistical reconstruction from single nucleotide polymorphism (SNP) genotypes and genotype error. We developed a re-sampling approach to quantify haplotype misclassification probabilities and implemented the MC-SIMEX approach to tackle this as a 3 × 3 misclassification problem. Using a previously published approach as a benchmark for comparison, we evaluated the performance of our approach by simulations and exemplified it on real data from 15 SNPs of the APM1 gene. Misclassification due to reconstruction error was small for most, but notable for some, especially rarer haplotypes. Genotype error added misclassification to all haplotypes resulting in a non-negligible drop in sensitivity. In our real data example, the bias of association estimates due to reconstruction error alone reached −48.2% for a 1% genotype error, indicating that haplotype misclassification should not be ignored if high genotype error can be expected. Our 3 × 3 misclassification view of haplotype error adds a novel perspective to currently used methods based on genotype intensities and expected number of haplotype copies. Our findings give a sense of the impact of haplotype error under realistic scenarios and underscore the importance of high-quality genotyping, in which case the bias in haplotype association estimates is negligible.
机译：总结单体型是遗传关联研究的重要概念，但由于单核苷酸多态性（SNP）基因型和基因型错误的统计重建，因此存在不确定性。我们开发了一种重新采样方法来量化单元型错误分类的概率，并实施了MC-SIMEX方法来解决此问题，将其作为3×3错误分类问题。使用以前发布的方法作为比较的基准，我们通过模拟评估了该方法的性能，并以APM1基因的15个SNP的真实数据为例进行了举例说明。大多数情况下，由于重建错误造成的分类错误很小，但对于某些（尤其是较罕见的）单倍型却很明显。基因型错误增加了对所有单倍型的错误分类，导致敏感性不可忽略的下降。在我们的真实数据示例中，对于1％的基因型错误，仅由于重构错误而导致的关联估计偏差就达到了-48.2％，这表明如果可以预期到高的基因型错误，则不应忽略单倍型错误分类。我们基于单倍型错误的3×3错误分类视图为基于基因型强度和单倍型预期拷贝数的当前使用方法提供了新的视角。我们的发现提供了在实际情况下单倍型错误影响的感觉，并强调了高质量基因分型的重要性，在这种情况下，单倍型关联估计的偏差可以忽略不计。

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  • 来源
    《Annals of Human Genetics》 |2010年第5期|p.452-462|共11页
  • 作者

    Claudia Lamina; Helmut Küchenhoff; Jenny Chang-Claude; Bernhard Paulweber; H.-Erich Wichmann; Thomas Illig; Margret R. Hoehe; Florian Kronenberg; Iris M. Heid;

  • 作者单位

    Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany|Division of Genetic Epidemiology;

    Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria;

    Department of Statistics, Ludwig-Maximilians-Universitt München, Munich, Germany;

    Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany;

    First Department of Internal Medicine, Paracelsus Private Medical University Salzburg, Austria;

    Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany|Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universitt München, Munich, Germany|Klinikum Grosshadern, Munich, Germany;

    Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany;

    Max Planck Institute for Molecular Genetics, Berlin, Germany;

    Division of Genetic Epidemiology;

    Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria;

    Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany|Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Germany;

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  • 关键词

    Haplotypes; measurement error; genotyping error; association studies; misclassification;

    机译：单倍型;测量误差;基因分型误差;关联研究;分类错误;

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