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Multi-trait analysis of rare-variant association summary statistics using MTAR

机译:使用MTAR的稀有变异关联摘要统计的多特征分析

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摘要

In this illustration, the number of variants is  = 10 and the number of traits is  = 5. The degree of heterogeneity of among-variant effects is controlled by . MTAR methods are robust to various patterns of genetic effects across variants by combining variance-component test -values from different specifications of . The degree of heterogeneity of among-trait effects is controlled by . By changing the value of , the degree of heterogeneity of among-trait effects can be weakly, moderately, or strongly dictated by genetic correlation . By setting  = 0, iMTAR and cMTAR structures assume genetic effects become completely heterogeneous and homogeneous, respectively. MTAR methods are robust to various patterns of genetic effects across traits by combining variance-component test -values from different specifications of . The cctP that combines the single-trait burden and SKAT tests -values is particularly powerful when only a small number of traits are associated with the set of rare variants. The omnibus test MTAR-O that combines iMTAR, cMTAR, and cctP is robust to all the aforementioned patterns of genetic effects across traits and variants.
机译:在该图中,变体的数量为= 10,性状的数量为= 5,变体间效应的异质度由来控制。 MTAR方法通过组合来自不同规格的方差分量检验值,对跨变体的多种遗传效应模式具有鲁棒性。性状间效应的异质性程度由来控制。通过改变的值,性状间效应的异质性程度可以由遗传相关性弱,中或强地决定。通过设置= 0,iMTAR和cMTAR结构假定遗传效应分别变得完全异质和同质。 MTAR方法通过组合来自不同规格的方差成分检验值,对各种性状的遗传效应模式均具有鲁棒性。当只有少部分性状与稀有变种集相关联时,将单性状负担和SKAT检验值结合在一起的cctP尤其强大。结合了iMTAR,cMTAR和cctP的综合测试MTAR-O对上述所有跨越性状和变体的遗传效应模式均具有强大的抵抗力。

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