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Computational approaches to identify functional genetic variants in cancer genomes
- Gonzalez-Perez, Abel;
- Mustonen, Ville;
- Reva, Boris;
- Ritchie, Graham RS;
- Creixell, Pau;
- Karchin, Rachel;
- Vazquez, Miguel;
- Fink, J Lynn;
- Kassahn, Karin S;
- Pearson, John V;
- Bader, Gary D;
- Boutros, Paul C;
- Muthuswamy, Lakshmi;
- Ouellette, BF Francis;
- Reimand, Jueri;
- Linding, Rune;
- Shibata, Tatsuhiro;
- Valencia, Alfonso;
- Butler, Adam;
- Dronov, Serge;
- Flicek, Paul;
- Shannon, Nick B;
- Carter, Hannah;
- Ding, Li;
- Sander, Chris;
- Stuart, Josh M;
- Stein, Lincoln D;
- Lopez-Bigas, Nuria
- et al.
Published Web Location
https://doi.org/10.1038/nmeth.2562Abstract
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.
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