Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/111878
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Type: Journal article
Title: Computational approaches to identify functional genetic variants in cancer genomes
Author: Gonzalez-Perez, A.
Mustonen, V.
Reva, B.
Ritchie, G.
Creixell, P.
Karchin, R.
Vazquez, M.
Fink, J.
Kassahn, K.
Pearson, J.
Bader, G.
Boutros, P.
Muthuswamy, L.
Ouellette, B.
Reimand, J.
Linding, R.
Shibata, T.
Valencia, A.
Butler, A.
Dronov, S.
et al.
Citation: Nature Methods, 2013; 10(8):723-729
Publisher: Springer Nature
Issue Date: 2013
ISSN: 1548-7091
1548-7105
Statement of
Responsibility: 
Abel Gonzalez-Perez, Ville Mustonen, Boris Reva, Graham RS Ritchie, Pau Creixell, Rachel Karchin, Miguel Vazquez, J Lynn Fink, Karin S Kassahn, John V Pearson, Gary D Bader, Paul C Boutros, Lakshmi Muthuswamy, BF Francis Ouellette, Jüri Reimand, Rune Linding, Tatsuhiro Shibata, Alfonso Valencia, Adam Butler, Serge Dronov, Paul Flicek, Nick B Shannon, Hannah Carter, Li Ding, Chris Sander, Josh M Stuart, Lincoln D Stein and Nuria Lopez-Bigas, for the International Cancer Genome Consortium Mutation Pathways and Consequences Subgroup of the Bioinformatics Analyses Working Group
Abstract: The International Cancer Genome Consortium (ICICGC) 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 ICICGC 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.
Rights: © 2013 Nature America, Inc. All rights reserved.
RMID: 0030035708
DOI: 10.1038/nmeth.2562
Appears in Collections:Genetics publications

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