ShatterProof: operational detection and quantification of chromothripsis

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• 作者：Shaylan K Govind (10)
  Amin Zia (10)
  Pablo H Hennings-Yeomans (10)
  John D Watson (10)
  Michael Fraser (13)
  Catalina Anghel (10)
  Alexander W Wyatt (11)
  Theodorus van der Kwast (15)
  Colin C Collins (11)
  John D McPherson (10) (14)
  Robert G Bristow (12) (13) (14)
  Paul C Boutros (10) (14) (16)
  
  10. Ontario Institute for Cancer Research ; M5G 0A3 ; Toronto ; Canada
  13. Radiation Medicine Program ; Ontario Cancer Institute ; Toronto ; Ontario ; Canada
  11. Vancouver Prostate Centre and Department of Urologic Sciences ; University of British Columbia ; Vancouver ; BC ; Canada
  15. Department of Pathology ; University Health Network ; Toronto ; Ontario ; Canada
  14. Department of Medical Biophysics ; University of Toronto ; Toronto ; Ontario ; Canada
  12. STTARR Innovation Program ; Toronto ; Ontario ; Canada
  16. Department of Pharmocology and Toxicology ; University of Toronto ; Toronto ; Ontario ; Canada
  
• 关键词：Chromothripsis ; Complex genomic rearrangement ; Next generation sequencing ; High throughput sequencing ; Perl ; Bioinformatics
• 刊名：BMC Bioinformatics
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：15
• 期：1
• 全文大小：782 KB
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• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

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.