EFMDR-Fast: An Application of Empirical Fuzzy Multifactor Dimensionality Reduction for Fast Execution
- Author:
Sangseob LEEM
1
;
Taesung PARK
Author Information
- Publication Type:Note
- Keywords: EFMDR; Fuzzy-MDR; gene-gene interaction; multi-factor dimensionality reduction; RCPP
- MeSH: Genotype; Methods; Multifactor Dimensionality Reduction
- From:Genomics & Informatics 2018;16(4):e37-
- CountryRepublic of Korea
- Language:English
- 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.
