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 casecontrol
association studies. It is an extension of the popular
multifactor ...»»»»
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 casecontrol
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.^^^^