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mbmdr:一个用于探索与二项式或定量性状相关的基因-基因相互作用的 R 包。

mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits.

机构信息

Department of Systems Biology, Universitat de Vic.

出版信息

Bioinformatics. 2010 Sep 1;26(17):2198-9. doi: 10.1093/bioinformatics/btq352. Epub 2010 Jul 1.

Abstract

SUMMARY

We describe mbmdr, an R package for implementing the model-based multifactor dimensionality reduction (MB-MDR) method. MB-MDR has been proposed by Calle et al. as a dimension reduction method for exploring gene-gene interactions in case-control association studies. It is an extension of the popular multifactor dimensionality reduction (MDR) method of Ritchie et al. allowing a more flexible definition of risk cells. In MB-MDR, risk categories are defined using a regression model which allows adjustment for covariates and main effects and, in addition to the classical low risk and high risk categories, MB-MDR considers a third category of indeterminate or not informative cells. An important improvement added to the current mbmdr algorithm with respect to the original MB-MDR formulation in Calle et al. and also to the classical MDR approach, is the extension of the methodology to different outcome types. While MB-MDR was initially proposed for binary traits in the context of case-control studies, the mbmdr package provides options to analyze both binary or quantitative traits for unrelated individuals.

AVAILABILITY

http://cran.r-project.org/.

摘要

摘要

我们描述了 mbmdr,这是一个用于实现基于模型的多因子维度减少(MB-MDR)方法的 R 包。MB-MDR 是由 Calle 等人提出的,作为一种在病例对照关联研究中探索基因-基因相互作用的维度减少方法。它是 Ritchie 等人流行的多因子维度减少(MDR)方法的扩展,允许更灵活地定义风险细胞。在 MB-MDR 中,风险类别是使用回归模型定义的,该模型允许调整协变量和主效应,并且除了经典的低风险和高风险类别之外,MB-MDR 还考虑了第三类不确定或无信息的细胞。与 Calle 等人的原始 MB-MDR 公式以及经典的 MDR 方法相比,当前 mbmdr 算法的一个重要改进是将该方法扩展到不同的结果类型。虽然 MB-MDR 最初是在病例对照研究的背景下为二元特征提出的,但 mbmdr 包提供了用于分析无关个体的二元或定量特征的选项。

可用性

http://cran.r-project.org/。

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