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

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

doi:10.1186/1471-2164-6-72

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

Journal Article · Wed May 11 00:00:00 EDT 2005 · BMC Genomics

DOI:https://doi.org/10.1186/1471-2164-6-72· OSTI ID:1626446

Timlin, Jerilyn A. ^[1]; Haaland, David M. ^[2]; Sinclair, Michael B. ^[2]; Aragon, Anthony D. ^[3]; Martinez, M. Juanita ^[3]; Werner-Washburne, Margaret ^[3]

Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); DOE/OSTI
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Lovelace Respiratory Research Inst., Albuquerque, NM (United States)

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 quality 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.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

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

Grant/Contract Number:: NA0003525

OSTI ID:: 1626446

Journal Information:: BMC Genomics, Journal Name: BMC Genomics Journal Issue: 1 Vol. 6; ISSN 1471-2164

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Hyperspectral Computed Tomographic Imaging Spectroscopy of Vascular Oxygen Gradients in the Rabbit Retina In Vivo Kashani, Amir H.; Kirkman, Erlinda; Martin, Gabriel PLoS ONE, Vol. 6, Issue 9 https://doi.org/10.1371/journal.pone.0024482	journal	September 2011
Spectral Flow Cytometry Nolan, John P.; Condello, Danilo Current Protocols in Cytometry, Vol. 63, Issue 1 https://doi.org/10.1002/0471142956.cy0127s63	journal	January 2013
Spectral imaging of the retina Mordant, D. J.; Al-Abboud, I.; Muyo, G. Eye, Vol. 25, Issue 3 https://doi.org/10.1038/eye.2010.222	journal	March 2011
In vivo hyperspectral confocal fluorescence imaging to determine pigment localization and distribution in cyanobacterial cells Vermaas, W. F. J.; Timlin, J. A.; Jones, H. D. T. Proceedings of the National Academy of Sciences, Vol. 105, Issue 10, p. 4050-4055 https://doi.org/10.1073/pnas.0708090105	journal	March 2008
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Multispectral Concurrent Detection of Multiple Proteins Chai, Jingwen; Song, Qing Nano LIFE, Vol. 02, Issue 03 https://doi.org/10.1142/s1793984412410048	journal	September 2012

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