Gene‐based analysis of bi‐variate survival traits via functional regressions with applications to eye diseases

Gene‐based analysis of bi‐variate survival traits via functional regressions with applications to eye diseases
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通过功能回归对双变量生存特征进行基于基因的分析并应用于眼部疾病

DOI:
10.1002/gepi.22381
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发表时间:
2021
影响因子:
2.1
通讯作者:
Fan, Ruzong
Fan, Ruzong
中科院分区:
医学4区
文献类型:
--
作者:
Zhang, Bingsong;Chiu, Chi‐Yang;Yuan, Fang;Sang, Tian;Cook, Richard J;Wilson, Alexander F.;Bailey‐Wilson, Joan E.;Chew, Emily Y.;Xiong, Momiao;Fan, Ruzong

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对多效性基因的两个相关生存结果的遗传学研究很常见,但很少开发出分析它们的统计模型。为了分析测序数据,我们通过功能回归提出了混合效应 Cox 比例风险模型,对我们正在进行的实际研究所激发的两个生存特征进行基于基因的联合关联分析。这些模型通过将多变量生存特征的变化和相关性纳入模型中,扩展了单变量生存特征的固定效应 Cox 模型。通过似然比检验统计来检验遗传变异和两种生存特征之间的关联。大量的仿真研究表明,I 类错误率得到了很好的控制,功率性能也很稳定。所提出的模型用于分析年龄相关性黄斑变性进展中左眼和右眼的双变量生存特征。
Genetic studies of two related survival outcomes of a pleiotropic gene are commonly encountered but statistical models to analyze them are rarely developed. To analyze sequencing data, we propose mixed effect Cox proportional hazard models by functional regressions to perform gene‐based joint association analysis of two survival traits motivated by our ongoing real studies. These models extend fixed effect Cox models of univariate survival traits by incorporating variations and correlation of multivariate survival traits into the models. The associations between genetic variants and two survival traits are tested by likelihood ratio test statistics. Extensive simulation studies suggest that type I error rates are well controlled and power performances are stable. The proposed models are applied to analyze bivariate survival traits of left and right eyes in the age‐related macular degeneration progression.
基于区域的关联测试,用于生存特征测序数据
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