Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes

dc.contributor.author Skibbe, David
dc.contributor.author Wang, Xiujuan
dc.contributor.author Zhao, Xuefeng
dc.contributor.author Borsuk, Lisa
dc.contributor.author Nettleton, Dan
dc.contributor.author Schnable, Patrick
dc.contributor.author Nettleton, Dan
dc.contributor.department Statistics
dc.contributor.department Agronomy
dc.contributor.department Genetics, Development and Cell Biology
dc.contributor.department Bioinformatics and Computational Biology
dc.contributor.department Genetics and Genomics
dc.contributor.department Bioinformatics and Computational Biology
dc.contributor.department Baker Center for Bioinformatics and Biological Statistics
dc.contributor.department Center for Plant Genomics
dc.date 2019-08-25T02:45:47.000
dc.date.accessioned 2020-07-02T06:57:13Z
dc.date.available 2020-07-02T06:57:13Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2006
dc.date.issued 2006-08-01
dc.description.abstract <p><strong>Motivation:</strong> Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed.</p> <p><strong>Results:</strong> Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from any one scan amounted to <70% of the total number of genes identified in at least one scan. The average signal intensity of genes that exhibited statistically significant changes in expression was highest for the low-intensity scan and lowest for the high-intensity scan, suggesting that low-intensity scans may be best for detecting expression differences in high-signal genes, while high-intensity scans may be best for detecting expression differences in low-signal genes. Comparison of the differentially expressed genes identified in the multiple scan and linear regression approaches revealed that the multiple scan approach effectively identifies a subset of statistically significant genes that linear regression approach is unable to identify. Quantitative RT–PCR (qRT–PCR) tests demonstrated that statistically significant differences identified at all three scan intensities can be verified.</p>
dc.description.comments <p>This article is published as Skibbe, David S., Xiujuan Wang, Xuefeng Zhao, Lisa A. Borsuk, Dan Nettleton, and Patrick S. Schnable. "Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes." <em>Bioinformatics</em> 22, no. 15 (2006): 1863-1870. doi: <a href="https://doi.org/10.1093/bioinformatics/btl270">10.1093/bioinformatics/btl270</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/212/
dc.identifier.articleid 1216
dc.identifier.contextkey 14861150
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/212
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90524
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/212/2006_Nettleton_ScanningMicroarrays.pdf|||Fri Jan 14 22:35:38 UTC 2022
dc.source.uri 10.1093/bioinformatics/btl270
dc.subject.disciplines Agronomy and Crop Sciences
dc.subject.disciplines Bioinformatics
dc.subject.disciplines Cell and Developmental Biology
dc.subject.disciplines Genetics and Genomics
dc.subject.disciplines Microarrays
dc.title Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes
dc.type article
dc.type.genre article
dspace.entity.type Publication
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