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Bioinformatics Advance Access originally published online on October 10, 2006
Bioinformatics 2006 22(23):2910-2917; doi:10.1093/bioinformatics/btl502
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Evaluating the performance of microarray segmentation algorithms

Antti Lehmussola *, Pekka Ruusuvuori and Olli Yli-Harja

Institute of Signal Processing, Tampere University of Technology PO Box 553, 33101 Tampere, Finland

*To whom correspondence should be addressed.

Motivation: Although numerous algorithms have been developed for microarray segmentation, extensive comparisons between the algorithms have acquired far less attention. In this study, we evaluate the performance of nine microarray segmentation algorithms. Using both simulated and real microarray experiments, we overcome the challenges in performance evaluation, arising from the lack of ground-truth information. The usage of simulated experiments allows us to analyze the segmentation accuracy on a single pixel level as is commonly done in traditional image processing studies. With real experiments, we indirectly measure the segmentation performance, identify significant differences between the algorithms, and study the characteristics of the resulting gene expression data.

Results: Overall, our results show clear differences between the algorithms. The results demonstrate how the segmentation performance depends on the image quality, which algorithms operate on significantly different performance levels, and how the selection of a segmentation algorithm affects the identification of differentially expressed genes.

Availability: Supplementary results and the microarray images used in this study are available at the companion web site http://www.cs.tut.fi/sgn/csb/spotseg/

Contact: antti.lehmussola@tut.fi

Received on July 21, 2006; revised on September 13, 2006; accepted on September 30, 2006

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