GATE: an efficient procedure in study of pleiotropic genetic associations.
GATE: an efficient procedure in study of pleiotropic genetic associations.
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GATE：多效性遗传关联研究的有效程序
DOI：
10.1186/s12864-017-3928-7
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发表时间：
2017-07-21
期刊：
影响因子：
4.4
通讯作者：
Li Q
中科院分区：
文献类型：
--
作者：
Zhang W;Yang L;Tang LL;Liu A;Mills JL;Sun Y;Li Q
背景毫无疑问，对人类复杂性状的关联研究有利于识别有害的遗传标记。与单性状分析相比，多性状分析可以更好地利用性状和标记的信息，从而显着提高关联检验的统计功效。主成分分析 (PCA) 是多变量分析中众所周知的有用工具，可以应用于此任务。一般来说，首先对所有性状进行PCA，然后选择一定数量的解释大部分性状变异的顶级主成分（PC）来构建检验统计量。然而，在某些情况下，仅使用这些顶级 PC 会导致废弃 PC 中重要证据的丢失，从而使性能受到影响。方法为了克服这一缺点，同时保持使用顶级 PC 的优势，我们提出了一种群体累积测试证据（GATE）程序。 GATE通过将根据相应特征值降序排列的PC分为几组，在组级别上整合性状信息。结果仿真研究表明，该方法在统计功效方面优于现有的几种方法。有时，功率的增幅可达25%。使用从定量全基因组关联研究中收集的异质种小鼠数据进一步说明了这些方法。结论总体而言，GATE 为多效性遗传关联提供了强大的测试。
BackgroundThe association studies on human complex traits are admittedly propitious to identify deleterious genetic markers. Compared to single-trait analyses, multiple-trait analyses can arguably make better use of the information on both traits and markers, and thus improve statistical power of association tests prominently. Principal component analysis (PCA) is a well-known useful tool in multivariate analysis and can be applied to this task. Generally, PCA is first performed on all traits and then a certain number of top principal components (PCs) that explain most of the trait variations are selected to construct the test statistics. However, under some situations, only utilizing these top PCs would lead to a loss of important evidences from discarded PCs and thus makes the capability compromised.MethodsTo overcome this drawback while keeping the advantages of using the top PCs, we propose a group accumulated test evidence (GATE) procedure. By dividing the PCs which is sorted in the descending order according to the corresponding eigenvalues into a few groups, GATE integrates the information of traits at the group level.ResultsSimulation studies demonstrate the superiority of the proposed approach over several existing methods in terms of statistical power. Sometimes, the increase of power can reach 25%. These methods are further illustrated using the Heterogeneous Stock Mice data which is collected from a quantitative genome-wide association study.ConclusionsOverall, GATE provides a powerful test for pleiotropic genetic associations.
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