Case-control genetic association study is an efficient tool to search for the deleterious genetic variants predispose to human complex diseases, where the additive mode of inheritance is commonly assumed. However, how the genetic variants influence the occurrence of a certain disease is impossible to know beforehand. We show numerically that the existing procedures using the Hardy-Weinberg equilibrium test to choose the genetic model might be inconsistent. We propose a new method to choose the genetic model by adopting co-dominant code for risk allele and logistic regression model. Extensive computer simulation results demonstrate superiorities of the new method. Applications to six single nucleotide polymorphisms (SNPs) for breast cancer and eight SNPs for Type 2 Diabetes further show good performances of proposed method. In order to specify a genetic model for an allele, our method has some merits and is consistent as sample size is large. We propose to apply our method in related fields.

中文翻译：

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在病例对照研究中估算遗传遗传

病例对照遗传关联研究是寻找易患人类复杂疾病的有害遗传变异的有效工具，在人类复杂疾病中，通常假定遗传的累加方式。但是，遗传变异如何影响某种疾病的发生尚无法事先知道。我们用数字显示，使用Hardy-Weinberg平衡检验选择遗传模型的现有程序可能不一致。我们提出了一种采用风险等位基因和逻辑回归模型的共主导代码选择遗传模型的新方法。大量的计算机仿真结果证明了该新方法的优越性。乳腺癌的六个单核苷酸多态性（SNP）和2型糖尿病的八个SNP的应用进一步显示了所提出方法的良好性能。为了指定等位基因的遗传模型，我们的方法有一些优点，并且由于样本量较大，因此是一致的。我们建议将我们的方法应用于相关领域。