The allele-based association test, comparing allele frequency difference between case and control groups, is locally most powerful. However, application of the classical allelic test is limited in practice, because the method is sensitive to the Hardy–Weinberg equilibrium (HWE) assumption, not applicable to continuous traits, and not easy to account for covariate effect or sample correlation. To develop a generalized robust allelic test, we propose a new allele-based regression model with individual allele as the response variable. We show that the score test statistic derived from this robust and unifying regression framework contains a correction factor that explicitly adjusts for potential departure from HWE and encompasses the classical allelic test as a special case. When the trait of interest is continuous, the corresponding allelic test evaluates a weighted difference between individual-level allele frequency estimate and sample estimate where the weight is proportional to an individual's trait value, and the test remains valid under Y-dependent sampling. Finally, the proposed allele-based method can analyze multiple (continuous or binary) phenotypes simultaneously and multiallelic genetic markers, while accounting for covariate effect, sample correlation, and population heterogeneity. To support our analytical findings, we provide empirical evidence from both simulation and application studies.

中文翻译：

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广义稳健的基于等位基因的遗传关联测试

基于等位基因的关联测试，比较病例组和对照组之间的等位基因频率差异，是当地最强大的。然而，经典等位基因检验在实践中的应用受到限制，因为该方法对哈迪-温伯格平衡（HWE）假设敏感，不适用于连续性状，且不易解释协变量效应或样本相关性。为了开发一个广义的稳健等位基因测试，我们提出了一个新的基于等位基因的回归模型，其中单个等位基因作为响应变量。我们表明，从这个稳健且统一的回归框架得出的分数测试统计包含一个修正因子，该修正因子明确调整了与 HWE 的潜在偏离，并将经典等位基因测试作为特例包含在内。当感兴趣的特征是连续的，Y相关采样。最后，所提出的基于等位基因的方法可以同时分析多个（连续或二元）表型和多等位基因标记，同时考虑协变量效应、样本相关性和群体异质性。为了支持我们的分析结果，我们提供了来自模拟和应用研究的经验证据。