Genomics Inform.  2018 Dec;16(4):e37. 10.5808/GI.2018.16.4.e37.

EFMDR-Fast: An Application of Empirical Fuzzy Multifactor Dimensionality Reduction for Fast Execution

• Leem S
• Park T

• KMID: 2439227
• DOI: http://doi.org/10.5808/GI.2018.16.4.e37

Abstract

Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP (c++ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

Keyword

EFMDR; Fuzzy-MDR; gene-gene interaction; multi-factor dimensionality reduction; RCPP

MeSH Terms

Genotype
Methods
Multifactor Dimensionality Reduction*