Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Power of Expanded Multifactor Dimensionality Reduction with CART Algorithm

CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 검정력 평가

  • Received : 20100600
  • Accepted : 20100700
  • Published : 2010.09.30
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Abstract

It is important to detect the gene-gene interaction in GWAS(Genome-Wide Association Study). There are many studies about detecting gene-gene interaction. The one is Multifactor dimensionality reduction method. But MDR method is not applied continuous data and expanded multifactor dimensionality reduction(E-MDR) method is suggested. The goal of this study is to evaluate the power of E-MDR for identifying gene-gene interaction by simulation. Also we applied the method on the identify interaction e ects of single nucleotid polymorphisms(SNPs) responsible for economic traits in a Korean cattle population (real data).

인간의 유전자 상호작용을 분석하기 위해 제시된 다중인자 차원축소방법은 연속형자료에는 적용할 수 없다. 그래서 이를 보완한 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법이 제안되었다. 하지만 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 검정력이 밝혀지지 않았다. 따라서 본 연구에서는 모의실험을 통하여 CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 우수한 검정력을 평가하고, 확인된 검정력을 바탕으로 실제 한우 데이터에 적용하여 한우의 경제형질에 영향을 주는 우수 유전자조합을 규명하였다.

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References

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