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WaveRead: automatic measurement of relative gene expression levels from microarrays using wavelet analysis.

TitleWaveRead: automatic measurement of relative gene expression levels from microarrays using wavelet analysis.
Publication TypeJournal Article
Year of Publication2006
AuthorsBidaut, G, Manion, FJ, Garcia, C, Ochs, MF
JournalJ Biomed Inform
Volume39
Issue4
Pagination379-88
Date Published2006 Aug
ISSN1532-0480
KeywordsAlgorithms, Artificial Intelligence, Gene Expression, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis, Pattern Recognition, Automated, Software
Abstract

Gene expression microarrays monitor the expression levels of thousands of genes in an experiment simultaneously. To utilize the information generated, each of the thousands of spots on a microarray image must be properly quantified, including background correction. Most present methods require manual alignment of grids to the image data, and still often require additional minor adjustments on a spot by spot basis to correct for spotting irregularities. Such intervention is time consuming and also introduces inconsistency in the handling of data. A fully automatic, tested system would increase throughput and reliability in this field. In this paper, we describe WaveRead, a fully automated, standalone, open-source system for quantifying gene expression array images. Through the use of wavelet analysis to identify the spot locations and diameters, the system is able to automatically grid the image and quantify signal intensities and background corrections without any user intervention. The ability of WaveRead to perform proper quantification is demonstrated by analysis of both simulated images containing spots with donut shapes, elliptical shapes, and Gaussian intensity distributions, as well as of standard images from the National Cancer Institute.

DOI10.1016/j.jbi.2005.10.001
Alternate JournalJ Biomed Inform
PubMed ID16298556
Grant ListCA06927 / CA / NCI NIH HHS / United States
P50 CA83638 / CA / NCI NIH HHS / United States
People: 
Frank Manion
University of Michigan Rogel Cancer Center at North Campus Research Complex
1600 Huron Parkway, Bldg 100, Rm 1004 
Mailing Address: 2800 Plymouth Rd, NCRC 100-1004
Ann Arbor, MI 48109-2800 

Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592. The content is solely the responsibility
of the authors and does not necessarily represent the official views of the
National Institutes of Health.

Research reported in this publication was supported by the National Cancer Institutes of
Health under Award Number P30CA046592 by the use of the following Cancer Center
Shared Resource(s): Biostatistics, Analytics & Bioinformatics; Flow Cytometry;
Transgenic Animal Models; Tissue and Molecular Pathology; Structure & Drug
Screening; Cell & Tissue Imaging; Experimental Irradiation; Preclinical
Imaging & Computational Analysis; Health Communications; Immune Monitoring;
Pharmacokinetics)

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