Communications for Statistical Applications and Methods

  • 제14권3호
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  • Pages.687-698
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  • 2007
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Detection of Differentially Expressed Genes by Clustering Genes Using Class-Wise Averaged Data in Microarray Data

  • Kim, Seung-Gu (Department of Data & Information, Sangji University)
  • 발행 : 2007.12.31
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초록

A normal mixture model with which dependence between classes is incorporated is proposed in order to detect differentially expressed genes. Gene clustering approaches suffer from the high dimensional column of microarray expression data matrix which leads to the over-fit problem. Various methods are proposed to solve the problem. In this paper, use of simple averaging data within each class is proposed to overcome the various problems due to high dimensionality when the normal mixture model is fitted. Some experiments through simulated data set and real data set show its availability in actuality.

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참고문헌

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