Communications for Statistical Applications and Methods

  • 제17권5호
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  • Pages.667-678
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  • 2010
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 검정력 평가

Power of Expanded Multifactor Dimensionality Reduction with CART Algorithm

  • 투고 : 20100600
  • 심사 : 20100700
  • 발행 : 2010.09.30
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초록

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.

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).

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참고문헌

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