Anderson, Paul E., Smith, J. Q., 1953-, Edwards, Kieron D. and Millar, A. J. (Andrew J.) (2006) Guided conjugate Bayesian clustering for uncovering rhythmically expressed genes. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. (Working papers).

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Abstract

Background: An increasing number of microarray experiments produce time series of expression levels for many genes. Some recent clustering algorithms respect the time ordering of the data and are, importantly, extremely fast. The focus of this paper is the development of such an algorithm on a microarray data set consisting of 22,810 genes of the plant Arabidopsis thaliana measured at 13 time points over two days. Circadian rhythms control the timing of various physiological and metabolic processes and are regulated by genes acting in feedback loops. The aim is to cluster and classify the expression profiles in order to identify genes potentially involved in, and regulated by, the circadian clock. Results: A greedy search over time series of expression levels (where series are compared pairwise, the two most similar put in the same cluster and so forth) will get a fast result but will only explore a very limited number of the possible partitions of the profiles. We propose an improved, deterministic method based on a multi-step application of a conjugate Bayesian clustering algorithm. It allows the entire space to be searched more fully and intelligently. The values of the summary statistics are used to not only score clusters of genes, but also to guide the search of the vast partition space. By following this procedure, we are able to cluster genes that are known to be rhythmically expressed with genes of previously unknown function; thus suggesting potentially interesting targets for future experiments.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Arabidopsis thaliana -- Genetics -- Mathematical models, Time-series analysis, Cluster analysis, Circadian rhythms -- Mathematical models
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Date:	2006
Volume:	Vol.2006
Number:	No.7
Number of Pages:	37
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), BioSim
Grant number:	G19886 (BBSRC)
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URI:	http://wrap.warwick.ac.uk/id/eprint/35566

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