Title: Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data

Abstract

Background: Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. Results: Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. Conclusion: Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of qualitymore » control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring.« less

Authors:

Timlin, Jerilyn A. ^[1]; Haaland, David M. ^[1]; Sinclair, Michael B. ^[1]; Aragon, Anthony D. ^[2]; Martinez, M. Juanita ^[2]; Werner-Washburne, Margaret ^[2]

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+ Show Author Affiliations

1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Lovelace Respiratory Research Inst., Albuquerque, NM (United States)

Publication Date:

Wed May 11 00:00:00 EDT 2005

Research Org.:

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

OSTI Identifier:

1626446

Grant/Contract Number:  

NA0003525

Resource Type:

Accepted Manuscript

Journal Name:

BMC Genomics

Additional Journal Information:

Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 1471-2164

Publisher:

Springer

Country of Publication:

United States

Language:

English

Subject:

59 BASIC BIOLOGICAL SCIENCES; Biotechnology & Applied Microbiology; Genetics & Heredity