Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Software

Visualization-based discovery and analysis of genomic aberrations in microarray data

Chad L Myers12, Xing Chen3 and Olga G Troyanskaya12*

Author Affiliations

1 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, NJ 08544, USA

2 Department of Computer Science, Princeton University, Princeton, NJ 08544, USA

3 Department of Computer Science, Stanford University, Stanford, CA 94305, USA

For all author emails, please log on.

BMC Bioinformatics 2005, 6:146  doi:10.1186/1471-2105-6-146

Published: 13 June 2005



Chromosomal copy number changes (aneuploidies) play a key role in cancer progression and molecular evolution. These copy number changes can be studied using microarray-based comparative genomic hybridization (array CGH) or gene expression microarrays. However, accurate identification of amplified or deleted regions requires a combination of visual and computational analysis of these microarray data.


We have developed ChARMView, a visualization and analysis system for guided discovery of chromosomal abnormalities from microarray data. Our system facilitates manual or automated discovery of aneuploidies through dynamic visualization and integrated statistical analysis. ChARMView can be used with array CGH and gene expression microarray data, and multiple experiments can be viewed and analyzed simultaneously.


ChARMView is an effective and accurate visualization and analysis system for recognizing even small aneuploidies or subtle expression biases, identifying recurring aberrations in sets of experiments, and pinpointing functionally relevant copy number changes. ChARMView is freely available under the GNU GPL at webcite.