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KMID : 1132720180160040037
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Genomics & Informatics
2018 Volume.16 No. 4 p.37 ~ p.37
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EFMDR-Fast: An Application of Empirical Fuzzy Multifactor Dimensionality Reduction for Fast Execution
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Leem Sang-Seob
Park Tae-Sung
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Abstract
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Gene-gene interaction is a key factor to explain the missing heritability. Many methods have been proposed to identify gene-gene interactions. Multi-factor dimensionality reduction (MDR) is a well-known method for gene-gene interaction detection by reduction from genotypes of SNP combination to a binary variable with a value of high risk or low risk. This method is widely expanded to own a specific objective. Among those expansions, fuzzy-MDR used the fuzzy-set theory for the membership of high risk or low risk and increase the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as 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 implement 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.
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KEYWORD
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gene-gene interaction, MDR, Fuzzy-MDR, EFMDR, RCPP
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