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ShatterProof: operational detection and quantification of chromothripsis

Shaylan K Govind1, Amin Zia1, Pablo H Hennings-Yeomans1, John D Watson1, Michael Fraser4, Catalina Anghel1, Alexander W Wyatt2, Theodorus van der Kwast6, Colin C Collins2, John D McPherson15, Robert G Bristow345 and Paul C Boutros157*

Author Affiliations

1 Ontario Institute for Cancer Research, M5G 0A3, Toronto, Canada

2 Vancouver Prostate Centre and Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada

3 STTARR Innovation Program, Toronto, Ontario, Canada

4 Radiation Medicine Program, Ontario Cancer Institute, Toronto, Ontario, Canada

5 Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

6 Department of Pathology, University Health Network, Toronto, Ontario, Canada

7 Department of Pharmocology and Toxicology, University of Toronto, Toronto, Ontario, Canada

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BMC Bioinformatics 2014, 15:78  doi:10.1186/1471-2105-15-78

Published: 19 March 2014

Abstract

Background

Chromothripsis, a newly discovered type of complex genomic rearrangement, has been implicated in the evolution of several types of cancers. To date, it has been described in bone cancer, SHH-medulloblastoma and acute myeloid leukemia, amongst others, however there are still no formal or automated methods for detecting or annotating it in high throughput sequencing data. As such, findings of chromothripsis are difficult to compare and many cases likely escape detection altogether.

Results

We introduce ShatterProof, a software tool for detecting and quantifying chromothriptic events. ShatterProof takes structural variation calls (translocations, copy-number variations, short insertions and loss of heterozygosity) produced by any algorithm and using an operational definition of chromothripsis performs robust statistical tests to accurately predict the presence and location of chromothriptic events. Validation of our tool was conducted using clinical data sets including matched normal, prostate cancer samples in addition to the colorectal cancer and SCLC data sets used in the original description of chromothripsis.

Conclusions

ShatterProof is computationally efficient, having low memory requirements and near linear computation time. This allows it to become a standard component of sequencing analysis pipelines, enabling researchers to routinely and accurately assess samples for chromothripsis. Source code and documentation can be found at http://search.cpan.org/~sgovind/Shatterproof webcite.

Keywords:
Chromothripsis; Complex genomic rearrangement; Next generation sequencing; High throughput sequencing; Perl; Bioinformatics