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隐性/显性模型:基于病例对照的全基因组关联研究的另一种选择。

Recessive/dominant model: Alternative choice in case-control-based genome-wide association studies.

机构信息

School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China.

出版信息

PLoS One. 2021 Jul 21;16(7):e0254947. doi: 10.1371/journal.pone.0254947. eCollection 2021.

Abstract

An additive genetic model is usually employed in case-control-based genome-wide association studies. The model usually encodes "AA", "Aa" and "aa" ("a" represents the minor allele) as three different numbers, implying the contribution of genotype "Aa" to the phenotype is different from "AA" and "aa". From the perspective of biological phenomena, the coding is reasonable since the phenotypes of lives are not "black and white". A case-control based study, however, has only two phenotypes, case and control, which means that the phenotypes are "black and white". It suggests that a recessive/dominant model may be an alternative to the additive model. In order to investigate whether the alternative is feasible, we conducted comparative experiments on several models used in those studies through chi-square test and logistic regression. Our simulation experiments demonstrate that a recessive model is better than the additive model. The area under the curve of the former has increased by 5% compared with the latter, the discrimination of identifying risk single nucleotide polymorphisms has been improved by 61%, and the precision has also reached 1.10 times that of the latter. Furthermore, the real data experiments show that the precision and area under the curve of the former are 16% and 20% higher than the latter respectively, and the area under the curve of dominant model of the former is 13% higher than the latter. The results indicate a recessive/dominant model may be an alternative to the additive model and suggest a new route for case-control-based studies.

摘要

基于病例对照的全基因组关联研究通常采用加性遗传模型。该模型通常将“AA”、“Aa”和“aa”(“a”代表次要等位基因)编码为三个不同的数字,这意味着基因型“Aa”对表型的贡献与“AA”和“aa”不同。从生物学现象的角度来看,这种编码是合理的,因为生物的表型不是“非黑即白”的。然而,基于病例对照的研究只有两种表型,病例和对照,这意味着表型是“非黑即白”的。这表明隐性/显性模型可能是加性模型的替代方案。为了研究替代方案是否可行,我们通过卡方检验和逻辑回归对这些研究中使用的几种模型进行了比较实验。我们的模拟实验表明,隐性模型优于加性模型。与后者相比,前者的曲线下面积增加了 5%,识别风险单核苷酸多态性的辨别力提高了 61%,精度也达到了后者的 1.10 倍。此外,真实数据实验表明,前者的精度和曲线下面积分别比后者高 16%和 20%,而前者的显性模型的曲线下面积比后者高 13%。结果表明,隐性/显性模型可能是加性模型的替代方案,并为基于病例对照的研究提供了新的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8806/8294554/2a6de0483d85/pone.0254947.g001.jpg

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