Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees.
Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees.
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基于扩展谱系的结合印记效应的质量性状关联的广义不平衡检验
DOI：
10.1186/s12863-017-0560-0
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发表时间：
2017-10-16
期刊：
影响因子：
2.9
通讯作者：
Zhou JY
中科院分区：
文献类型：
--
作者：
Li JL;Wang P;Fung WK;Zhou JY
对于二分性状，具有方差矩估计的广义不平衡检验（GDT-ME）是一种强大的基于家族的关联方法。基因组印记是一种重要的表观遗传现象，目前，人们越来越关注结合印记来提高关联分析的测试能力。然而，GDT-ME没有考虑印迹效应，并且尚未研究当印迹效应确实存在时是否可以用于关联分析。在本文中，基于根据等位基因的父本或母本来源对基因型评分进行新的分解，我们提出了广义不平衡印记检验（GDTI），用于没有任何缺失基因型的完整谱系。然后，我们扩展 GDTI 和 GDT-ME 以适应不完整的谱系，其中一些谱系具有缺失的基因型，通过使用蒙特卡罗（MC）采样和估计方案来推断缺失的基因型（给定每个谱系中的可用基因型），分别由 MCGDTI 和 MCGDT-ME 表示。所提出的 GDTI 和 MCGDTI 方法评估谱系中所有不一致的亲属对（包括超出一级亲属对）的父本和母本等位基因评分的差异。通过各种模拟设置下的模拟研究以及在类风湿性关节炎数据集上的应用，证明了所提出的 GDTI 和 MCGDTI 检验统计量相对于现有方法的优势。仿真结果表明，所提出的测试在无关联的原假设下很好地控制了尺寸，并且在各种印迹效应模型下优于现有方法。即使存在印记效应，现有的 GDT-ME 和提出的 MCGDT-ME 也可用于测试关联。对于类风湿性关节炎数据的应用，与现有方法相比，MCGDTI 识别出更多与该疾病统计显着相关的位点。在完整和不完整印记效应模型下，我们提出的 GDTI 和 MCGDTI 方法，通过考虑印记效应信息和每个谱系内所有不一致的相对对，优于所有现有的测试统计数据，并且 MCGDTI 可以重新捕获大部分丢失的信息。因此，在实践中推荐使用MCGDTI。本文的在线版本 (10.1186/s12863-017-0560-0) 包含补充材料，可供授权用户使用。
For dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist. In this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease. Under complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice. The online version of this article (10.1186/s12863-017-0560-0) contains supplementary material, which is available to authorized users.
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