DOI QR코드

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효모 마이크로어레이 유전자 발현 데이터에 대한 유전자 선별 및 군집분석

Gene Screening and Clustering of Yeast Microarray Gene Expression Data

  • 이경아 (덕성여자대학교 정보통계학과) ;
  • 김태훈 (덕성여자대학교 PrePharmMed학과) ;
  • 김재희 (덕성여자대학교 정보통계학과)
  • Lee, Kyung-A (Department of Statistics, Duksung Women's University) ;
  • Kim, Tae-Houn (Department of PrePharmMed Duksung Women's University) ;
  • Kim, Jae-Hee (Department of Statistics, Duksung Women's University)
  • 투고 : 20110900
  • 심사 : 20111100
  • 발행 : 2011.12.31

초록

마이크로어레이 유전자 발현 데이터인 yeast cdc15에 대해 시계열 데이터의 특성을 반영한 푸리에 계수를 이용한 검정통계량과 FDR 다중비교법을 이용하여 차별화된 유전자를 선별한 후 선별된 유전자들에 대해 모형기반 군집방법, K-평균법, PAM, SOM, 계층적 Ward 군집방법과 Fuzzy 군집방법을 실시하였다. 군집방법에 따른 특성을 알아보고 군집화 결과와 내부유효성 측도로 연결성 측도, Dunn 지수와 실루엣 값을 살펴본다. 또한 GO분석을 통한 생물학적 의미도 파악해본다.

We accomplish clustering analyses for yeast cell cycle microarray expression data. To reflect the characteristics of a time-course data, we screen the genes using the test statistics with Fourier coefficients applying a FDR procedure. We compare the results done by model-based clustering, K-means, PAM, SOM, hierarchical Ward method and Fuzzy method with the yeast data. As the validity measure for clustering results, connectivity, Dunn index and silhouette values are computed and compared. A biological interpretation with GO analysis is also included.

키워드

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피인용 문헌

  1. Screening and Clustering for Time-course Yeast Microarray Gene Expression Data using Gaussian Process Regression vol.26, pp.3, 2013, https://doi.org/10.5351/KJAS.2013.26.3.389