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Statistical Applications in Genetics and Molecular Biology

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Combining Multiple Laser Scans of Spotted Microarrays by Means of a Two-Way ANOVA Model

Jérôme Ambroise / Bertrand Bearzatto / Annie Robert / Benoit Macq / Jean-Luc Gala
Published Online: 2012-02-27 | DOI: https://doi.org/10.1515/1544-6115.1738

Motivation: Assessment of gene expression on spotted microarrays is based on measurement of fluorescence intensity emitted by hybridized spots. Unfortunately, quantifying fluorescence intensity from hybridized spots does not always correctly reflect gene expression level. Low gene expression levels produce low fluorescence intensities which tend to be confounded with the local background while high gene expression levels produce high fluorescence intensities which rapidly reach the saturation level. Most algorithms that combine data acquired at different voltages of the photomultiplier tube (PMT) assume that a change in scanner setting transforms the intensity measurements by a multiplicative constant.Methods and Results: In this paper we introduce a new model of spot foreground intensity which integrates a PMT voltage independent scanner optical bias. This new model is used to implement a ”Combining Multiple Scan using a Two-way ANOVA” (CMS2A) method, which is based on a maximum likelihood estimation of the scanner optical bias. After having computed scanner bias, coefficients of the two-way ANOVA model are used for correcting the saturated spots intensities obtained at high PMT voltage by using their counterpart values at lower PMT voltages. The method was compared to state-of-the-art multiple scan algorithms, using data generated from the MAQC study. CMS2A produced fold-changes that were highly correlated with qPCR fold-changes. As the scanner optical bias is accurately estimated within CMS2A, this method allows also avoiding fold-change compression biases whatever the value of this optical bias.

Keywords: microarray; saturation; multiscan

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Published Online: 2012-02-27

Citation Information: Statistical Applications in Genetics and Molecular Biology, ISSN (Online) 1544-6115, DOI: https://doi.org/10.1515/1544-6115.1738.

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©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston. Copyright Clearance Center

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