Department of Statistics, North Carolina State University, Raleigh NC 27695, USA.
BioData Min. 2011 Aug 16;4(1):24. doi: 10.1186/1756-0381-4-24.
A breadth of high-dimensional data is now available with unprecedented numbers of genetic markers and data-mining approaches to variable selection are increasingly being utilized to uncover associations, including potential gene-gene and gene-environment interactions. One of the most commonly used data-mining methods for case-control data is Multifactor Dimensionality Reduction (MDR), which has displayed success in both simulations and real data applications. Additional software applications in alternative programming languages can improve the availability and usefulness of the method for a broader range of users.
We introduce a package for the R statistical language to implement the Multifactor Dimensionality Reduction (MDR) method for nonparametric variable selection of interactions. This package is designed to provide an alternative implementation for R users, with great flexibility and utility for both data analysis and research. The 'MDR' package is freely available online at http://www.r-project.org/. We also provide data examples to illustrate the use and functionality of the package.
MDR is a frequently-used data-mining method to identify potential gene-gene interactions, and alternative implementations will further increase this usage. We introduce a flexible software package for R users.
现在有大量的高维数据，利用遗传标记和数据挖掘方法进行变量选择的情况越来越多，以揭示关联，包括潜在的基因-基因和基因-环境相互作用。用于病例对照数据的最常用的数据挖掘方法之一是多因子降维（MDR），它在模拟和真实数据应用中都取得了成功。替代编程语言中的其他软件应用程序可以提高该方法对更广泛用户的可用性和实用性。
我们为 R 统计语言引入了一个软件包，以实现用于交互的非参数变量选择的多因子降维（MDR）方法。该软件包旨在为 R 用户提供替代实现，具有数据分析和研究的极大灵活性和实用性。“MDR”软件包可在 http://www.r-project.org/ 在线获得。我们还提供了数据示例，以说明软件包的使用和功能。
MDR 是一种常用的数据挖掘方法，用于识别潜在的基因-基因相互作用，替代实现将进一步增加这种使用。我们为 R 用户引入了一个灵活的软件包。
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