Literature DB >> 15376909

A novel approach for high-quality microarray processing using third-dye array visualization technology.

Xujing Wang1, Nan Jiang, Xin Feng, Yizhou Xie, Peter J Tonellato, Soumitra Ghosh, Martin J Hessner.   

Abstract

Historically, microarray image processing has been technically challenging in obtaining quality gene expression data. After hybridization of Cy3- and Cy5-labeled samples, images are collected and processed to obtain gene expression ratio measurements for each of the elements on the array. The hybridization process often brings in contaminating noise, which can make correct identification of the signal difficult. In addition, spot intensity levels are highly variable due to the expression differences of different genes, and weak spots are often difficult to detect. These conditions are further complicated by inherent irregularities in spot position, shape, and size commonly found on high-density microarrays, making image processing an often labor-intensive task that is difficult to reliably automate. We previously reported a novel third-dye array visualization (TDAV) technology that allows prehybridization visualization and quality control of printed arrays. Here, we present a new microarray image processing approach utilizing TDAV. By incorporating the third-dye image, we show that overall quality of the microarray data is significantly improved, and automation of processing is feasible and reliable. Furthermore, we demonstrate use of the third-dye image to better quality control microarray image analysis. Both the principle and implementation of the approach are presented in detail, with experimental results.

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Year:  2003        PMID: 15376909     DOI: 10.1109/tnb.2003.816233

Source DB:  PubMed          Journal:  IEEE Trans Nanobioscience        ISSN: 1536-1241            Impact factor:   2.935


  5 in total

1.  Quality Weighted Mean and T-test in Microarray Analysis Lead to Improved Accuracy in Gene Expression Measurements and Reduced Type I and II Errors in Differential Expression Detection.

Authors:  Shouguo Gao; Shuang Jia; Martin Hessner; Xujing Wang
Journal:  J Comput Sci Syst Biol       Date:  2008-12-26

2.  Comprehensive quality control utilizing the prehybridization third-dye image leads to accurate gene expression measurements by cDNA microarrays.

Authors:  Xujing Wang; Shuang Jia; Lisa Meyer; Bixia Xiang; Li-Yen Chen; Nan Jiang; Carol Moreno; Howard J Jacob; Soumitra Ghosh; Martin J Hessner
Journal:  BMC Bioinformatics       Date:  2006-08-14       Impact factor: 3.169

3.  Quantitative measurement of pathogen-specific human memory T cell repertoire diversity using a CDR3 beta-specific microarray.

Authors:  Xujing Wang; Shuang Jia; Lisa Meyer; Maryam B Yassai; Yuri N Naumov; Jack Gorski; Martin J Hessner
Journal:  BMC Genomics       Date:  2007-09-19       Impact factor: 3.969

4.  Utilization of a labeled tracking oligonucleotide for visualization and quality control of spotted 70-mer arrays.

Authors:  Martin J Hessner; Vineet K Singh; Xujing Wang; Shehnaz Khan; Michael R Tschannen; Thomas C Zahrt
Journal:  BMC Genomics       Date:  2004-02-09       Impact factor: 3.969

5.  Immobilized probe and glass surface chemistry as variables in microarray fabrication.

Authors:  Martin J Hessner; Lisa Meyer; Jennifer Tackes; Sanaa Muheisen; Xujing Wang
Journal:  BMC Genomics       Date:  2004-08-04       Impact factor: 3.969

  5 in total

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