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June 2010 Bayesian meta-analysis for identifying periodically expressed genes in fission yeast cell cycle
Xiaodan Fan, Saumyadipta Pyne, Jun S. Liu
Ann. Appl. Stat. 4(2): 988-1013 (June 2010). DOI: 10.1214/09-AOAS300


The effort to identify genes with periodic expression during the cell cycle from genome-wide microarray time series data has been ongoing for a decade. However, the lack of rigorous modeling of periodic expression as well as the lack of a comprehensive model for integrating information across genes and experiments has impaired the effort for the accurate identification of periodically expressed genes. To address the problem, we introduce a Bayesian model to integrate multiple independent microarray data sets from three recent genome-wide cell cycle studies on fission yeast. A hierarchical model was used for data integration. In order to facilitate an efficient Monte Carlo sampling from the joint posterior distribution, we develop a novel Metropolis–Hastings group move. A surprising finding from our integrated analysis is that more than 40% of the genes in fission yeast are significantly periodically expressed, greatly enhancing the reported 10–15% of the genes in the current literature. It calls for a reconsideration of the periodically expressed gene detection problem.


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Xiaodan Fan. Saumyadipta Pyne. Jun S. Liu. "Bayesian meta-analysis for identifying periodically expressed genes in fission yeast cell cycle." Ann. Appl. Stat. 4 (2) 988 - 1013, June 2010.


Published: June 2010
First available in Project Euclid: 3 August 2010

zbMATH: 1194.62020
MathSciNet: MR2758430
Digital Object Identifier: 10.1214/09-AOAS300

Keywords: cell cycle , fission yeast , Markov chain Monte Carlo , Meta-analysis , microarray time series , periodically expressed gene , Schizosaccharomyces pombe

Rights: Copyright © 2010 Institute of Mathematical Statistics

Vol.4 • No. 2 • June 2010
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