Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays
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Research Article Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays Rashi Gupta,1, 2 Elja Arjas,1, 3 Sangita Kulathinal,1 Andrew Thomas,1 and Petri Auvinen2 1 Department
of Mathematics and Statistics, University of Helsinki, P.O. Box 68, 00014 Helsinki, Finland of Biotechnology, University of Helsinki, P.O.Box 56, 00014 Helsinki, Finland 3 National Public Health Institute (KTL), Mannerheimintie 166, 00300 Helsinki, Finland 2 Institute
Correspondence should be addressed to Rashi Gupta, [email protected] Received 7 July 2007; Accepted 28 November 2007 Recommended by Yufei Huang We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sensitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at which expressions can be measured in all ranges and extends the dynamic range of measured gene expression at the high end. Our method is generic and can be applied to data from any organism, for imaging with any scanner that allows varying the laser power, and for extraction with any image analysis software. Results from a self-self hybridization data set illustrate an improved precision in the estimation of the expression of genes compared to what can be achieved by applying standard methods and using only a single scan. Copyright © 2008 Rashi Gupta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction DNA microarray technology is used to study simultaneously the expression profile of a large number of distinct genes [1]. Several factors contribute to the accuracy with which these genes and their expressions (also referred here as intensities) can be determined. In particular, very low or very high intensities may lead to poor estimation of the ratio between the two samples and thus to an incorrect identification of differentially expressed genes. Low intensities tend to be noisy and lead to highly variable ratio estimates, whereas very high intensities are saturated from above and hence give biased results. One of the objectives of microarray experiments is to identify a subset of genes that are differentially expressed between the samples of interest. The relative intensity between the samples at a spot (also referred here as gene) is extracted by applying suitable image processing methods to the images produced by scanning the microarray slides on which the two samples have been hybridized. Errors occurring during image acquisition affect all further analyses and, therefore, the process of generation of these digital images is crucial.
Photomultiplier tube (PMT), laser power (LP), and analog to digital converter (ADC), are the main components of an acquisition device, the scanner, which controls the formation of digital images. Each spot on the hybridized slide ha
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