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你得靠运气:覆盖率与难以捉摸的基因-基因相互作用。

You've gotta be lucky: Coverage and the elusive gene-gene interaction.

作者信息

Reimherr Matthew, Nicolae Dan L

机构信息

Department of Statistics, The University of Chicago, IL 60637, USA.

出版信息

Ann Hum Genet. 2011 Jan;75(1):105-11. doi: 10.1111/j.1469-1809.2010.00615.x. Epub 2010 Oct 26.

Abstract

Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting.

摘要

全基因组关联研究(GWAS)已经产生了大量单核苷酸多态性(SNP)关联研究结果,但到目前为止,尚未有研究发现可重复的基因-基因相互作用。在本文中,我们探讨了缺乏相关研究结果的一些可能原因,并认为因果变异的覆盖率不仅对检验效能的损失有很大影响,而且这种影响比单SNP分析中的影响更大。我们表明,因果SNP与检验SNP之间的连锁不平衡度量r²的乘积,很好地近似了由导致相似检验效能的样本量之比所定义的效率损失。我们还证明,除了巨大的搜索空间外,使用市售平台时由于覆盖率导致的检验效能损失,使得寻找基因-基因相互作用变得令人生畏。

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Evaluating coverage of genome-wide association studies.评估全基因组关联研究的覆盖范围。
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