We study variance estimation and associated confidence intervals for parameters characterizing genetic effects from genome-wide association studies (GWAS) misspecified mixed model analysis. Previous studies have shown that, in spite of the model misspecification, certain quantities of genetic interests are estimable, and consistent estimators of these quantities can be obtained using the restricted maximum likelihood (REML) method under a misspecified linear mixed model. However, the asymptotic variance of such a REML estimator is complicated and not ready to be implemented for practical use. In this paper, we develop practical and computationally convenient methods for estimating such asymptotic variances and constructing the associated confidence intervals. Performance of the proposed methods is evaluated empirically based on Monte-Carlo simulations and real-data application.
翻译:我们研究整个基因组协会研究(GWAS)错误描述的混合模型分析的遗传影响特征参数的差异估计和相关信任期,以前的研究显示,尽管模型有误,某些遗传利益的数量是可估量的,在错误描述的线性混合模型下,可以使用限量最大可能性(REML)方法取得这些数量一致的估算数据,但是,这种REML估计值的无现时差异很复杂,无法实际使用。我们在本文件中开发了实际和计算上方便的方法,用于估计例如物质差异和构建相关的信任期。根据蒙特-卡洛模拟和实际数据应用,对拟议方法的绩效进行了经验评估。