Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Major SNP Marker Identification with MDR and CART Application

  • Lee, Jea-Young (Department of Statistics, Yeungnam University) ;
  • Choi, Yu-Mi (Department of Statistics, Yeungnam University)
  • Published : 2008.03.30
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Abstract

It is commonly believed that diseases of human or economic traits of livestock are caused not by single genes acting alone, but multiple genes interacting with one another. This issue is difficult due to the limitations of parametric-statistic methods of gene effects. So we introduce multifactor-dimensionality reduction(MDR) as a methods for reducing the dimensionality of multilocus information. The MDR method is nonparametric (i. e., no hypothesis about the value of a statistical parameter is made), model free (i. e., it assumes no particular inheritance model) and is directly applicable to case-control studies. Application of the MDR method revealed the best model with an interaction effect between the SNPs, SNP1 and SNP3, while only one main effect of SNP1 was statistically significant for LMA (p < 0.01) under a general linear mixed model.

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References

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