Bioinformatics Advance Access originally published online on May 18, 2006
Bioinformatics 2006 22(14):1737-1744; doi:10.1093/bioinformatics/btl184
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Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset
1 Department of Environmental Health, University of Cincinnati 3223 Eden Avenue ML 56, Cincinnati OH 45267, USA
2 Division of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation Cincinnati, OH 45229, USA
3 Mathematical Sciences Department, University of Cincinnati Cincinnati, OH 45221, USA
4 Department of Microbiology, University of Washington Seattle, WA 98195, USA
*To whom correspondence should be addressed.
Motivation: Identifying groups of co-regulated genes by monitoring their expression over various experimental conditions is complicated by the fact that such co-regulation is condition-specific. Ignoring the context-specific nature of co-regulation significantly reduces the ability of clustering procedures to detect co-expressed genes due to additional ‘noise’ introduced by non-informative measurements.
Results: We have developed a novel Bayesian hierarchical model and corresponding computational algorithms for clustering gene expression profiles across diverse experimental conditions and studies that accounts for context-specificity of gene expression patterns. The model is based on the Bayesian infinite mixtures framework and does not require a priori specification of the number of clusters. We demonstrate that explicit modeling of context-specificity results in increased accuracy of the cluster analysis by examining the specificity and sensitivity of clusters in microarray data. We also demonstrate that probabilities of co-expression derived from the posterior distribution of clusterings are valid estimates of statistical significance of created clusters.
Availability: The open-source package gimm is available at http://eh3.uc.edu/gimm
Contact: Mario.Medvedovic{at}uc.edu
Supplementary information: http://eh3.uc.edu/gimm/csimm
Received on March 6, 2006; revised on April 18, 2006; accepted on May 8, 2006
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