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

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.