Simulating variance heterogeneity in quantitative genome wide association studies.

Simulating variance heterogeneity in quantitative genome wide association studies.
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DOI:
10.1186/s12859-018-2061-1
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发表时间:
2018-03-21
期刊:
影响因子:
3
通讯作者:
Datta A
Datta A
中科院分区:
生物学4区
文献类型:
--
作者:
Al Kawam A;Alshawaqfeh M;Cai JJ;Serpedin E;Datta A

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全基因组关联研究中的方差异质性分析(vGWAS)是一种新兴的检测基因-基因和基因-环境相互作用的遗传位点的方法。vGWAS分析检测跨基因型的表型值的变异性,这与检测平均表型值的变异的典型GWAS分析相反。最近在文献中引入了一些vGWAS分析方法。然而,很少有工作已经做了评估这些方法。为了开发更好的vGWAS分析方法,这项工作提出了第一个定量vGWAS模拟程序。为此,我们描述了从基因型谱生成定量vGWAS表型数据的数学框架和算法。我们的模拟模型考虑了不同显性模式下的单倍体和二倍体基因型。我们的模型也能够模拟任何数量的遗传位点造成的均值和方差异质性。我们通过生成各种遗传位点类型来评估常见的GWAS和vGWAS分析方法,展示了我们的模拟程序的实用性。该评估的结果突出了当前工具在检测GWAS和vGWAS基因座方面面临的挑战。
Analyzing Variance heterogeneity in genome wide association studies (vGWAS) is an emerging approach for detecting genetic loci involved in gene-gene and gene-environment interactions. vGWAS analysis detects variability in phenotype values across genotypes, as opposed to typical GWAS analysis, which detects variations in the mean phenotype value. A handful of vGWAS analysis methods have been recently introduced in the literature. However, very little work has been done for evaluating these methods. To enable the development of better vGWAS analysis methods, this work presents the first quantitative vGWAS simulation procedure. To that end, we describe the mathematical framework and algorithm for generating quantitative vGWAS phenotype data from genotype profiles. Our simulation model accounts for both haploid and diploid genotypes under different modes of dominance. Our model is also able to simulate any number of genetic loci causing mean and variance heterogeneity. We demonstrate the utility of our simulation procedure through generating a variety of genetic loci types to evaluate common GWAS and vGWAS analysis methods. The results of this evaluation highlight the challenges current tools face in detecting GWAS and vGWAS loci.
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