You are here: Home / Publications / Linding Lab, BRIC & DTU [2011-present] / Computational approaches to identify functional genetic variants in cancer genomes.

Computational approaches to identify functional genetic variants in cancer genomes.

Nature Methods 2013 Jul 30;10(8):723-9.
Gonzalez-Perez A, Mustonen V, Reva B, Ritchie GR, Creixell P, Karchin R, Vazquez M, Fink JL, Kassahn KS, Pearson JV, Bader GD, Boutros PC, Muthuswamy L, Ouellette BF, Reimand J, Linding R, Shibata T, Valencia A, Butler A, Dronov S, Flicek P, Shannon NB, Carter H, Ding L, Sander C, Stuart JM, Stein LD, Lopez-Bigas N.

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.

 

[PDF]

[Publisher]

[Pubmed]

Document Actions

Navigation
« June 2017 »
June
SuMoTuWeThFrSa
123
45678910
11121314151617
18192021222324
252627282930