Array rank order regression analysis for the detection of gene copy-number changes in human cancer

被引:19
作者
Cheng, C
Kimmel, R
Neiman, P
Zhao, LP
机构
[1] Fred Hutchinson Canc Res Ctr, Div Publ Hlth Sci, Seattle, WA 98109 USA
[2] Fred Hutchinson Canc Res Ctr, Div Basic Sci, Seattle, WA 98109 USA
关键词
CHG; microarray technology; rank order; regression analysis; statistics;
D O I
10.1016/S0888-7543(03)00122-8
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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. (C) 2003 Elsevier Science (USA). All rights reserved.
引用
收藏
页码:122 / 129
页数:8
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