Bagos Pantelis G
University of Central Greece.
Stat Appl Genet Mol Biol. 2008;7(1):Article31. doi: 10.2202/1544-6115.1408. Epub 2008 Oct 24.
Methods for multivariate meta-analysis of genetic association studies are reviewed, summarized and presented in a unified framework. Modifications of standard models are described in detail in order to be applied in genetic association studies. The model based on summary data is uniformly defined for both discrete and continuous outcomes and analytical expressions for the covariance of the two jointly modeled outcomes are derived for both cases. The models based on the binary nature of the data are fitted using both prospective and retrospective likelihood. Furthermore, formal tests for assessing the genetic model of inheritance are developed based on standard normal theory. The general model is compared to the recently proposed genetic model-free bivariate approach (either using summary or binary data), and it is clearly shown that the estimates provided by this approach are nearly identical to the estimates derived by the general bivariate model using the aforementioned tests for the genetic model. The methods developed here as well as the tests, are easily implemented in all major statistical packages, escaping the need of self written software. The methods are applied in several already published meta-analyses of genetic association studies (with both discrete and continuous outcomes) and the results are compared against the widely used univariate approach as well as against the genetic model free approaches. Illustrative examples of code in Stata are given in the appendix. It is anticipated that the methods developed in this work will be widely applied in the meta-analysis of genetic association studies.
对基因关联研究的多变量荟萃分析方法进行了回顾、总结，并在一个统一的框架中呈现。详细描述了标准模型的修改，以便应用于基因关联研究。基于汇总数据的模型针对离散和连续结果进行了统一定义，并针对这两种情况推导了两个联合建模结果协方差的解析表达式。基于数据二元性的模型使用前瞻性和回顾性似然进行拟合。此外，基于标准正态理论开发了用于评估遗传遗传模型的正式检验。将通用模型与最近提出的无遗传模型双变量方法（使用汇总数据或二元数据）进行比较，结果清楚地表明，该方法提供的估计值与使用上述遗传模型检验的通用双变量模型得出的估计值几乎相同。本文开发的方法以及检验在所有主要统计软件包中都易于实现，无需自行编写软件。这些方法应用于已发表的多项基因关联研究荟萃分析（包括离散和连续结果），并将结果与广泛使用的单变量方法以及无遗传模型方法进行比较。附录中给出了Stata代码的示例。预计这项工作中开发的方法将在基因关联研究的荟萃分析中得到广泛应用。
