Visualization-based discovery and analysis of genomic aberrations in microarray data
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Updated: Aug 17, 2026
Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Chad L Myers1, Xing Chen, Olga G Troyanskaya
1Lewis-Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, NJ 08544, USA. clmyers@princeton.edu
Background:
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.
Results:
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.
Conclusion:
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 http://function.princeton.edu/ChARMView.
