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Open Access Highly Accessed Research article

Detection of recurrent rearrangement breakpoints from copy number data

Anna Ritz1*, Pamela L Paris2, Michael M Ittmann3, Colin Collins4 and Benjamin J Raphael15*

Author Affiliations

1 Department of Computer Science, Brown University, Providence, RI, USA

2 Department of Urology, University of California at San Francisco, San Francisco, CA, USA

3 Department of Pathology, Baylor College of Medicine, Houston, TX, USA

4 Vancouver Prostate Centre, Vancouver, BC, Canada

5 Center for Computational Molecular Biology, Brown University, Providence, RI, USA

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BMC Bioinformatics 2011, 12:114  doi:10.1186/1471-2105-12-114

Published: 21 April 2011

Additional files

Additional File 1:

The Appendix includes full derivations of the segmentation model, comparisons to other segmentation algorithms, and data aquisition and implementation details.

Format: PDF Size: 344KB Download file

This file can be viewed with: Adobe Acrobat Reader

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Additional File 2:

Tables of all the breakpoints and pairs of breakpoints predicted for the prostate dataset and the GBM dataset. Note that the values reported for the prostate dataset (e.g. the RMS difference) are log base 10, while the values reported for the GBM dataset are log base 2.

Format: XLS Size: 55KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data