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Nat Methods. 2015 Jul;12(7):623-30. doi: 10.1038/nmeth.3407. Epub 2015 May 18.

Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection.

Author information

1
1] Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, California, USA. [2] Mater Research Institute, University of Queensland, Woolloongabba, Queensland, Australia.
2
Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
3
Sage Bionetworks, Seattle, Washington, USA.
4
Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, California, USA.
5
IBM Computational Biology Center, T.J. Watson Research Center, Yorktown Heights, New York, USA.
6
1] Sage Bionetworks, Seattle, Washington, USA. [2] Computational Biology Program, Oregon Health &Science University, Portland, Oregon, USA. [3] Department of Biomedical Engineering, Oregon Health &Science University, Portland, Oregon, USA.
7
1] Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada. [2] Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada. [3] Department of Pharmacology &Toxicology, University of Toronto, Toronto, Ontario, Canada.

Abstract

The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. Benchmarking is needed for tool assessment and improvement but is complicated by a lack of gold standards, by extensive resource requirements and by difficulties in sharing personal genomic information. To resolve these issues, we launched the ICGC-TCGA DREAM Somatic Mutation Calling Challenge, a crowdsourced benchmark of somatic mutation detection algorithms. Here we report the BAMSurgeon tool for simulating cancer genomes and the results of 248 analyses of three in silico tumors created with it. Different algorithms exhibit characteristic error profiles, and, intriguingly, false positives show a trinucleotide profile very similar to one found in human tumors. Although the three simulated tumors differ in sequence contamination (deviation from normal cell sequence) and in subclonality, an ensemble of pipelines outperforms the best individual pipeline in all cases. BAMSurgeon is available at https://github.com/adamewing/bamsurgeon/.

PMID:
25984700
PMCID:
PMC4856034
DOI:
10.1038/nmeth.3407
[Indexed for MEDLINE]
Free PMC Article

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