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https://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. |
DOI: | 10.1038/nmeth.2562 |
Published version: | http://dx.doi.org/10.1038/nmeth.2562 |
Appears in Collections: | Aurora harvest 3 Genetics publications |
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