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用于多因素降维和(探索性)数量性状位点分析的R包GenomicTools。

The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.

作者信息

Fischer Daniel

机构信息

Natural Resources Institute Finland (Luke), Myllytie 1, Jokioinen, Finland; University of Tampere, School of Health Sciences, Tampere, Finland. Electronic address: http://genomictools.danielfischer.name.

出版信息

Comput Methods Programs Biomed. 2017 Nov;151:171-177. doi: 10.1016/j.cmpb.2017.08.012. Epub 2017 Aug 30.

Abstract

BACKGROUND AND OBJECTIVES

We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (exploratory) Quantitative Trait Loci analysis that overcomes some of the limitations of other popular (e)QTL approaches. Popular (e)QTL approaches that use linear models or ANOVA are often based on over-simplified models that have weak statistical properties and which are not robust against outlying observations.

METHOD

The algorithm to calculate the MDR is well established. To speed up its calculation in R, we implemented it in C++. Further, our implementation also supports the combination of several MDR results to an MDR ensemble classifier. The (e)QTL test procedure is based on a generalized Mann-Whitney test that is tailored for directional alternatives, as they are present in an (e)QTL analysis.

RESULTS

Our package GenomicTools provides functions to determine SNP combinations that have the highest accuracy for a MDR classification problem. It also provides functions to combine the best MDR results to a joined ensemble classifier for improved classification results. Further, the (e)QTL analysis is based on a solid statistical theory. In addition, informative visualizations of the results are provided.

CONCLUSION

The here presented new class of tests and methods have an easy to apply syntax, so that also researchers inexperienced in R are able to apply our proposed methods and implementations. The package creates publication ready Figures and hence could be a valuable tool for genomic data analysis.

摘要

背景与目的

我们引入了R包GenomicTools,用于执行多因素降维分析(MDR)等操作,以识别单核苷酸多态性(SNP)-SNP相互作用。该包还为(探索性)数量性状基因座分析提供了一类新的测试方法,克服了其他常用的(表达数量性状基因座,eQTL)方法的一些局限性。使用线性模型或方差分析的常用eQTL方法通常基于过度简化的模型,这些模型的统计特性较弱,并且对异常观测值不稳健。

方法

计算MDR的算法已经很成熟。为了在R中加快其计算速度,我们用C++实现了它。此外,我们的实现还支持将多个MDR结果组合成一个MDR集成分类器。eQTL测试程序基于一种广义的曼-惠特尼检验,该检验是为eQTL分析中存在的方向性备择假设量身定制的。

结果

我们的GenomicTools包提供了一些函数,用于确定在MDR分类问题中具有最高准确性的SNP组合。它还提供了一些函数,用于将最佳的MDR结果组合成一个联合的集成分类器,以提高分类结果。此外,eQTL分析基于坚实的统计理论。另外,还提供了结果的信息可视化。

结论

这里介绍的新的测试方法和类具有易于应用的语法,因此即使是没有R经验的研究人员也能够应用我们提出的方法和实现。该包可以生成可供发表的图表,因此可能是基因组数据分析的一个有价值的工具。

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