Computational approaches to identify functional genetic variants in cancer genomes Journal Article


Authors: Gonzalez-Perez, A.; Mustonen, V.; Reva, B.; Ritchie, G. R. S.; Creixell, P.; Karchin, R.; Vazquez, M.; Fink, J. L.; Kassahn, K. S.; Pearson, J. V.; Bader, G. D.; Boutros, P. C.; Muthuswamy, L.; Ouellette, B. F. F.; Reimand, J.; Linding, R.; Shibata, T.; Valencia, A.; Butler, A.; Dronov, S.; Flicek, P.; Shannon, N. B.; Carter, H.; Li, D.; Sander, C.; Stuart, J. M.; Stein, L. D.; Lopez-Bigas, N.
Article Title: Computational approaches to identify functional genetic variants in cancer genomes
Abstract: The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. © 2013 Nature America, Inc. All rights reserved.
Journal Title: Nature Methods
Volume: 10
Issue: 8
ISSN: 1548-7091
Publisher: Nature Publishing Group  
Date Published: 2013-07-30
Start Page: 723
End Page: 729
Language: English
DOI: 10.1038/nmeth.2562
PROVIDER: scopus
PUBMED: 23900255
PMCID: PMC3919555
DOI/URL:
Notes: --- - "Export Date: 4 September 2013" - "Source: Scopus"
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  1. Boris A Reva
    36 Reva
  2. Chris Sander
    210 Sander