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Computational approaches to identify functional genetic variants in cancer genomes

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the International Cancer Genome Consortium Mutation Pathways and Consequences Subgroup of the Bioinformatics Analyses Working Group·2013·Nature Methods
DOI 10.1038/nmeth.2562
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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.

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Metadata

Authors
the International Cancer Genome Consortium Mutation Pathways and Consequences Subgroup of the Bioinformatics Analyses Working Group
Venue
Nature Methods
Publisher
Springer Science and Business Media LLC
Published
2013-07-30
Volume
10
Issue
8
Pages
723-729
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
DOI
10.1038/nmeth.2562
OpenAlex
W2012673284
Cited by
171
References
14
FWCI
8.07
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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CoChat. (2026). Citation check: Computational approaches to identify functional genetic variants in cancer genomes. https://app.cochat.ai/papers/10.1038/nmeth.2562
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the International Cancer Genome Consortium Mutation Pathways and Consequences Subgroup of the Bioinformatics Analyses Working Group. (2013). Computational approaches to identify functional genetic variants in cancer genomes. Nature Methods. https://doi.org/10.1038/nmeth.2562

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