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Comparison of algorithms for the detection of cancer drivers at subgene resolution

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dc.contributor.author Porta-Pardo, Eduard
dc.contributor.author Kamburov, Atanas
dc.contributor.author Tamborero Noguera, David
dc.contributor.author Pons, Tirso
dc.contributor.author Grases, Daniela
dc.contributor.author Valencia, Alfonso
dc.contributor.author López Bigas, Núria
dc.contributor.author Getz, Gad
dc.contributor.author Godzik, Adam
dc.date.accessioned 2018-11-13T09:56:54Z
dc.date.available 2018-11-13T09:56:54Z
dc.date.issued 2017
dc.identifier.citation Porta-Pardo E, Kamburov A, Tamborero D, Pons T, Grases D, Valencia A et al. Comparison of algorithms for the detection of cancer drivers at subgene resolution. Nat Methods. 2017 Aug;14(8):782-8. DOI: 10.1038/nmeth.4364
dc.identifier.issn 1548-7091
dc.identifier.uri http://hdl.handle.net/10230/35737
dc.description.abstract Understanding genetic events that lead to cancer initiation and progression remains one of the biggest challenges in cancer biology. Traditionally, most algorithms for cancer-driver identification look for genes that have more mutations than expected from the average background mutation rate. However, there is now a wide variety of methods that look for nonrandom distribution of mutations within proteins as a signal for the driving role of mutations in cancer. Here we classify and review such subgene-resolution algorithms, compare their findings on four distinct cancer data sets from The Cancer Genome Atlas and discuss how predictions from these algorithms can be interpreted in the emerging paradigms that challenge the simple dichotomy between driver and passenger genes.
dc.description.sponsorship E.P.-P. and A.G. acknowledge the support from the Cancer Center grants P30 CA030199 (to our institute) and R35 GM118187 (A.G.). A.K. was supported by startup funds of G.G. and by a collaboration with Bayer AG. D.T. is supported by project SAF2015-74072-JIN, which is funded by the Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER). N.L.-B. acknowledges funding from the European Research Council (consolidator grant 682398). A.V. and T.P. acknowledge funding by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 305444 (RD-Connect)
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Publishing Group
dc.relation.ispartof Nature Methods. 2017 Aug;14(8):782-8
dc.rights © Nature Publishing Group. http://dx.doi.org/10.1038/nmeth.4364
dc.subject.other Algorismes
dc.subject.other Carcinogènesi
dc.subject.other Cromosomes
dc.subject.other Tumors
dc.title Comparison of algorithms for the detection of cancer drivers at subgene resolution
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/nmeth.4364
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/682398
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/305444
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/SAF2015-74072-JIN
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion

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