mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits
mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits
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DOI：
10.1093/bioinformatics/btq352
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发表时间：
2010-09-01
期刊：
影响因子：
5.8
通讯作者：
Van Steen, Kristel
中科院分区：
文献类型：
--
作者：
Luz Calle, M.;Urrea, Victor;Van Steen, Kristel
描述了一个用于实现基于模型的多因素降维(MB-MDR)方法的R包MBMDR。MB-MDR是由Calle等人提出的。作为病例对照关联研究中探索基因基因交互作用的降维方法。它是Ritchie等人流行的多因素降维(MDR)方法的推广。允许对风险单元进行更灵活的定义。在MB-MDR中，风险类别是使用回归模型定义的，该模型允许对协变量和主要影响进行调整，除了经典的低风险和高风险类别外，MB-MDR还考虑了第三类不确定或不提供信息的单元。与Calle等人的原始MB-MDR公式相比，对当前的MBMDR算法增加了一项重要改进。也是对经典的MDR方法的扩展，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针对二元性状提出的，但MBMDR软件包提供了分析无关个体的二元或数量性状的选项。
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.