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Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/73830

Type: Journal article
Title: Estimating Bayesian networks for high-demensional data with complex mean structure and random effects
Author: Kasza, Jessica Eleonore
Glonek, Garique Francis Vladimir
Solomon, Patricia Joy
Citation: Australian & New Zealand Journal of Statistics, 2012; 54(2):169-187
Publisher: Wiley-Blackwell Publishing Asia
Issue Date: 2012
ISSN: 1467-842X
School/Discipline: School of Mathematical Sciences
Statement of
Responsibility: 
Jessica Kasza, Gary Glonek and Patty Solomon
Abstract: The estimation of Bayesian networks given high-dimensional data, in particular gene expression data, has been the focus of much recent research. Whilst there are several methods available for the estimation of such networks, these typically assume that the data consist of independent and identically distributed samples. It is often the case, however, that the available data have a more complex mean structure, plus additional components of variance, which must then be accounted for in the estimation of a Bayesian network. In this paper, score metrics that take account of such complexities are proposed for use in conjunction with score-based methods for the estimation of Bayesian networks. We propose first, a fully Bayesian score metric, and second, a metric inspired by the notion of restricted maximum likelihood. We demonstrate the performance of these new metrics for the estimation of Bayesian networks using simulated data with known complex mean structures. We then present the analysis of expression levels of grape-berry genes adjusting for exogenous variables believed to affect the expression levels of the genes. Demonstrable biological effects can be inferred from the estimated conditional independence relationships and correlations amongst the grape-berry genes.
Keywords: Bayesian network; exogenous variable; grape-berry gene expression; regulatory network; score-based metric; variance components
Rights: © 2012 Australian Statistical Publishing Association Inc.
RMID: 0020122346
DOI: 10.1111/j.1467-842X.2012.00662.x
Appears in Collections:Mathematical Sciences publications
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