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Open Access Methodology article

Using expression arrays for copy number detection: an example from E. coli

Dmitriy Skvortsov12, Diana Abdueva13*, Michael E Stitzer14, Steven E Finkel1 and Simon Tavaré15

Author Affiliations

1 Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA

2 Department of Human Genetics, UCLA School of Medicine, University of California, Los Angeles, USA

3 Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, USA

4 Mount Sinai School of Medicine, New York, NY 10029, USA

5 Department of Oncology, University of Cambridge, Cambridge, UK

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BMC Bioinformatics 2007, 8:203  doi:10.1186/1471-2105-8-203

Published: 14 June 2007

Abstract

Background

The sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible. Microarray-based comparative genomic hybridization (array CGH) has enabled the high-resolution detection of DNA copy number aberrations. While many of the methods and algorithms developed for the analysis microarrays have focused on expression analysis, the same technology can be used to detect genetic alterations, using for example standard commercial Affymetrix arrays. Due to the nature of the resultant data, standard techniques for processing GeneChip expression experiments are inapplicable.

Results

We have developed a robust and flexible methodology for high-resolution analysis of DNA copy number of whole genomes, using Affymetrix high-density expression oligonucleotide microarrays. Copy number is obtained from fluorescence signals after processing with novel normalization, spatial artifact correction, data transformation and deletion/duplication detection. We applied our approach to identify deleted and amplified regions in E. coli mutants obtained after prolonged starvation.

Conclusion

The availability of Affymetrix expression chips for a wide variety of organisms makes the proposed array CGH methodology useful more generally.