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Bioinformatics Vol. 19 no. 16 2003
pages 2031-2038
© 2003 Oxford University Press

A novel strategy for microarray quality control using Bayesian networks

Sampsa Hautaniemi 1,*,§, Henrik Edgren 2,3,§, Petri Vesanen 1,§, Maija Wolf 3, Anna-Kaarina Järvinen 2, Olli Yli-Harja 1, Jaakko Astola 1, Olli Kallioniemi 3 and Outi Monni 2

1 Institute of Signal Processing, Tampere University of Technology, PO Box 553, 33101 Tampere, Finland, 2 Biomedicum Biochip Center, PO Box 63, 00014 University of Helsinki, Helsinki, Finland and 3 Medical Biotechnology Group, VTT Technical Research Centre of Finland and University of Turku, PO Box 106, 20521 Turku, Finland

Received on December 3, 2002 ; revised on March 3, 2003 ; accepted on April 18, 2003

Motivation: High-throughput microarray technologies enable measurements of the expression levels of thousands of genes in parallel. However, microarray printing, hybridization and washing may create substantial variability in the quality of the data. As erroneous measurements may have a drastic impact on the results by disturbing the normalization schemes and by introducing expression patterns that lead to incorrect conclusions, it is crucial to discard low quality observations in the early phases of a microarray experiment. A typical microarray experiment consists of tens of thousands of spots on a microarray, making manual extraction of poor quality spots impossible. Thus, there is a need for a reliable and general microarray spot quality control strategy.

Results: We suggest a novel strategy for spot quality control by using Bayesian networks, which contain many appealing properties in the spot quality control context. We illustrate how a non-linear least squares based Gaussian fitting procedure can be used in order to extract features for a spot on a microarray. The features we used in this study are: spot intensity, size of the spot, roundness of the spot, alignment error, background intensity, background noise, and bleeding. We conclude that Bayesian networks are a reliable and useful model for microarray spot quality assessment.

Supplementary information: http://sigwww.cs.tut.fi/TICSP/SpotQuality/

Contact: sampsa.hautaniemi{at}tut.fi

* To whom correspondence should be addressed.

§ The authors wish it to be known that, in their opinion, the first two authors contributed equally to this work.


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