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Bioinformatics Advance Access published online on October 10, 2006
Bioinformatics, 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
Received July 21, 2006
Revised September 13, 2006
Accepted September 30, 2006

Article

Evaluating the performance of microarray segmentation algorithms

Antti Lehmussola 1 *, Pekka Ruusuvuori 1, and Olli Yli-Harja 1

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

* To whom correspondence should be addressed.
Antti Lehmussola, E-mail: antti.lehmussola{at}tut.fi


  Abstract

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 identifying 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/.

Associate Editor: Joaquin Dopazo
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