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一个名为“VariABEL”的 R 包,用于通过测试基因型方差异质性来进行全基因组潜在相互作用基因座的搜索。

An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity.

机构信息

Department of Epidemiology, Erasmus MC, Rotterdam, 3000 CA, The Netherlands.

出版信息

BMC Genet. 2012 Jan 24;13:4. doi: 10.1186/1471-2156-13-4.

DOI:10.1186/1471-2156-13-4
PMID:22272569
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3398297/
Abstract

BACKGROUND

Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties.We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants.

RESULTS

In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests.

CONCLUSIONS

Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.

摘要

背景

通过对人类特征的全基因组关联研究,已经发现了数百个新的基因座。这些研究主要集中在单基因座与特征之间的关联上。基因之间以及基因与环境因素之间的相互作用很有趣,因为它们可以帮助我们更好地理解复杂特征的遗传背景。全基因组复杂遗传模型的测试是一项计算密集型任务。此外,此类模型的测试会导致多重比较问题,从而降低新发现的可能性。假设复杂特征的遗传模型可以包含数百个基因和环境因素,那么在全基因组关联研究中对这些模型进行测试将面临很大的困难。我们和 Pare 及其同事(2010 年)开发了一种方法,可以克服这些困难。该方法基于这样一个事实,即参与相互作用的基因座可以显示特征的基因型方差异质性。对这种异质性进行全基因组测试可以是一种快速扫描方法,可以指出相互作用的遗传变异。

结果

在这项工作中,我们提出了一种新的方法 SVLM,用于分析遗传变异的方差异质性。研究了这种检验的Ⅰ型错误和功效,并与 Levene 检验的Ⅰ型错误和功效进行了比较。我们还介绍了一个 R 包 VariABEL,实现了现有和新开发的检验。

结论

方差异质性分析是检测潜在相互作用基因座的一种很有前途的方法。这项工作中开发的新方法和软件包将有助于在全基因组范围内进行这种分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6216/3398297/fd31ff28b581/1471-2156-13-4-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6216/3398297/ce1254009778/1471-2156-13-4-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6216/3398297/fd31ff28b581/1471-2156-13-4-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6216/3398297/ce1254009778/1471-2156-13-4-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6216/3398297/fd31ff28b581/1471-2156-13-4-2.jpg

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