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CGH data analysis

Part 4. Bioinformatics

4.5. Computational Methods for High-throughput Genetic Analysis: Expression Profiling

Short Specialist Review

  1. Adam A. Margolin1,2,
  2. Joel Greshock2,
  3. Barbara L. Weber2

Published Online: 15 NOV 2005

DOI: 10.1002/047001153X.g405314

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Margolin, A. A., Greshock, J. and Weber, B. L. 2005. CGH data analysis. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.5:58.

Author Information

  1. 1

    Columbia University, New York, NY, USA

  2. 2

    University of Pennsylvania, Philadelphia, PA, USA

Publication History

  1. Published Online: 15 NOV 2005

Abstract

Array comparative genomic hybridization (aCGH) is an emerging technology for measuring genome-wide DNA copy number. aCGH has been demonstrated as an effective tool in gene discovery and disease classification in cancer and other genetic disorders. This review describes recently employed analysis techniques for genomic copy number profiling using aCGH with a particular focus on how established gene expression array analysis techniques can be adapted for analysis of aCGH data. We intend this review to propose a framework to guide ongoing and future research in aCGH data analysis.

Keywords:

  • comparative genomic hybridization;
  • microarray;
  • cancer;
  • CGH;
  • data analysis