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首页> 美国卫生研究院文献>American Journal of Human Genetics >Contrasting Linkage-Disequilibrium Patterns between Cases and Controls as a Novel Association-Mapping Method
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Contrasting Linkage-Disequilibrium Patterns between Cases and Controls as a Novel Association-Mapping Method

机译：案例和控件之间的对比链接不平衡模式作为一种新的关联映射方法

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Identification and description of genetic variation underlying disease susceptibility, efficacy, and adverse reactions to drugs remains a difficult problem. One of the important steps in the analysis of variation in a candidate region is the characterization of linkage disequilibrium (LD). In a region of genetic association, the extent of LD varies between the case and the control groups. Separate plots of pairwise standardized measures of LD (e.g., D′) for cases and controls are often presented for a candidate region, to graphically convey case-control differences in LD. However, the observed graphic differences lack statistical support. Therefore, we suggest the “LD contrast” test to compare whole matrices of disequilibrium between two samples. A common technique of assessing LD when the haplotype phase is unobserved is the expectation-maximization algorithm, with the likelihood incorporating the assumption of Hardy-Weinberg equilibrium (HWE). This approach presents a potential problem in that, in the region of genetic association, the HWE assumption may not hold when samples are selected on the basis of phenotypes. Here, we present a computationally feasible approach that does not assume HWE, along with graphic displays and a statistical comparison of pairwise matrices of LD between case and control samples. LD-contrast tests provide a useful addition to existing tools of finding and characterizing genetic associations. Although haplotype association tests are expected to provide superior power when susceptibilities are primarily determined by haplotypes, the LD-contrast tests demonstrate substantially higher power under certain haplotype-driven disease models.
机译：疾病易感性，功效和药物不良反应的遗传变异的鉴定和描述仍然是一个难题。分析候选区域变异的重要步骤之一是连锁不平衡（LD）的表征。在遗传关联的区域中，LD的程度在病例与对照组之间有所不同。通常会为候选区域提供LD和案例的成对标准化度量（例如D '）的单独图，以图形方式传达LD中案例控制的差异。但是，观察到的图形差异缺乏统计支持。因此，我们建议使用“ LD对比”测试来比较两个样本之间的整个不平衡矩阵。当单倍型阶段未观察到时，评估LD的一种常用技术是期望最大化算法，该算法结合了Hardy-Weinberg平衡（HWE）的假设。这种方法提出了一个潜在的问题，即在遗传关联的区域中，当根据表型选择样本时，HWE假设可能不成立。在这里，我们提出了一种不假设HWE的计算可行方法，以及图形显示和案例样本与对照样本之间LD的成对矩阵的统计比较。 LD对比测试为发现和表征遗传关联的现有工具提供了有用的补充。虽然当主要由单倍型确定药敏性时，单倍型关联测试有望提供更高的功效，但LD对比测试显示在某些单倍型驱动的疾病模型下，其功效显着提高。

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