期刊
BIOINFORMATICS
卷 26, 期 17, 页码 2198-2199出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btq352
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资金
- Ministerio de Educacion y Ciencia (Spain) [MTM2008-06747-C02-02]
- La Marato de TV3 Foundation [050831]
- Generalitat de Catalunya [2009SGR-581]
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.
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