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An Alternative Model of Type A Dependence in a Gene Set of Correlated Genes

Author

Listed:
  • Lim Johan

    (Seoul National University)

  • Kim Jayeon

    (Yonsei University)

  • Kim Byung Soo

    (Yonsei University)

Abstract

Klebanov et al. (2006) proposed a new type of stochastic dependence, Type A dependence, between gene expression levels. They estimated the abundance of Type A pairs by testing the correlation coefficients of gene pairs. We propose a new model, hidden regulator dependence, as an alternative to Type A dependence. We show that the correlation based procedure proposed by Klebanov et al. (2006) fails to differentiate hidden regulator dependence from Type A dependence, although their probabilistic structures are quite different.

Suggested Citation

  • Lim Johan & Kim Jayeon & Kim Byung Soo, 2010. "An Alternative Model of Type A Dependence in a Gene Set of Correlated Genes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-12, January.
    • Handle: RePEc:bpj:sagmbi:v:9:y:2010:i:1:n:12
    DOI: 10.2202/1544-6115.1525
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    References listed on IDEAS

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    1. Thilakarathne Pushpike J & Verbeke Geert & Engelen Kristof & Marchal Kathleen, 2009. "A Nonlinear Mixed-Effects Model for Estimating Calibration Intervals for Unknown Concentrations in Two-Color Microarray Data with Spike-Ins," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-25, January.
    2. Qiu Xing & Klebanov Lev & Yakovlev Andrei, 2005. "Correlation Between Gene Expression Levels and Limitations of the Empirical Bayes Methodology for Finding Differentially Expressed Genes," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-32, November.
    3. Klebanov Lev & Jordan Craig & Yakovlev Andrei, 2006. "A New Type of Stochastic Dependence Revealed in Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-24, March.
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