Array rank order regression analysis for the detection of gene copy-number changes in human cancer |
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Authors: | Cheng Chun Kimmel Robert Neiman Paul Zhao Lue Ping |
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Affiliation: | Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA. |
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Abstract: | cDNA microarray technology has been applied to the detection of DNA copy-number changes in malignant tumors. Test and control genomic DNA samples are differentially labeled and cohybridized to a spotted cDNA microarray. The ratio of test to control fluorescence intensities for each spot reflects relative gene copy number. The low signal-to-noise ratios of this assay and the variable levels of gene amplification and deletion among tumors hamper the detection of deviations from the diploid complement. We describe a regression-based statistical method to test for altered copy number on each gene and apply the technique to copy-number profiles in 10 thyroid tumors. We show that a novel transformation of fluorescence ratios into array rank order efficiently normalizes the heterogeneity among copy-number profiles and improves the reproducibility of the results. Array rank order regression analysis enhances the detection of consistent changes in gene copy number in solid tumors by cDNA microarray-based comparative genome hybridization. |
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