Bayesian Hierarchical Model for Estimating Gene Expression Intensity Using Multiple Scanned Microarrays. (12th December 2007)

• Record Type: Journal Article
• Authors: Gupta, Rashi; Arjas, Elja; Kulathinal, Sangita; Thomas, Andrew; Auvinen, Petri
• Other Names: Huang Yufei Academic Editor.
• Is Part Of: EURASIP journal on bioinformatics and systems biology. Volume 2008(2008)
• Publication Date: 2007-12-12
• Subjects: Bioinformatics -- Periodicals; Systems biology -- Periodicals; Systems Biology; Signal Processing, Computer-Assisted; Bio-informatique; Biologie systémique; Bioinformatics; Systems biology; Systems Biology; Bioinformatics; Electronic journals; Periodical; Fulltext; Internet Resources; Periodicals; Periodicals; 570.285
• DOI: 10.1155/2008/231950
• Languages: English
• ISSNs: 1687-4145

Abstract

Abstract : We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sen-sitivities. 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.