OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action

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• dc.contributor.author Schroeder, Michael Philipp, 1986-ca
• dc.contributor.author Rubio Pérez, Carlota, 1990-ca
• dc.contributor.author Tamborero Noguera, Davidca
• dc.contributor.author González-Pérez, Abelca
• dc.contributor.author López Bigas, Núriaca
• dc.date.accessioned 2015-09-28T11:47:03Z
• dc.date.available 2015-09-28T11:47:03Z
• dc.date.issued 2014ca
• dc.description.abstract MOTIVATION: Several computational methods have been developed to identify cancer drivers genes-genes responsible for cancer development upon specific alterations. These alterations can cause the loss of function (LoF) of the gene product, for instance, in tumor suppressors, or increase or change its activity or function, if it is an oncogene. Distinguishing between these two classes is important to understand tumorigenesis in patients and has implications for therapy decision making. Here, we assess the capacity of multiple gene features related to the pattern of genomic alterations across tumors to distinguish between activating and LoF cancer genes, and we present an automated approach to aid the classification of novel cancer drivers according to their role. RESULT: /nOncodriveROLE is a machine learning-based approach that classifies driver genes according to their role, using several properties related to the pattern of alterations across tumors. The method shows an accuracy of 0.93 and Matthew's correlation coefficient of 0.84 classifying genes in the Cancer Gene Census. The OncodriveROLE classifier, its results when applied to two lists of predicted cancer drivers and TCGA-derived mutation and copy number features used by the classifier are available at http://bg.upf.edu/oncodrive-role. AVAILABILITY AND IMPLEMENTATION: The R implementation of the OncodriveROLE classifier is available at http://bg.upf.edu/oncodrive-role. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
• dc.description.sponsorship This work was supported by the Spanish Ministry of Economy and Competitivity (grant number SAF2012-36199) and the Spanish National Institute of Bioinformatics (INB). M.P.S. and C.R.-P. are supported by FPI fellowships
• dc.format.mimetype application/pdfca
• dc.identifier.citation Schroeder MP, Rubio-Perez C, Tamborero D, Gonzalez-Perez A, Lopez-Bigas N./nOncodriveROLE classifies cancer driver genes in loss of function and activating mode of action. Bioinformatics. 2014 Sep 1;30(17):549-55. DOI: 10.1093/bioinformatics/btu467ca
• dc.identifier.doi http://dx.doi.org/10.1093/bioinformatics/btu467
• dc.identifier.issn 1367-4803ca
• dc.identifier.uri http://hdl.handle.net/10230/24768
• dc.language.iso engca
• dc.publisher Oxford University Press
• dc.relation.ispartof Bioinformatics. 2014 Sep 1;30(17):549-55
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SAF2012-36199
• dc.rights © 2014 Michael Philipp Schroeder et al. Published by Oxford University Press. This is an Open Access article distributed under the terms of a Creative Commons Attribution Licenseca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.other Intel·ligència artificial
• dc.subject.other Tumors
• dc.subject.other Oncogens
• dc.subject.other Genètica
• dc.title OncodriveROLE classifies cancer driver genes in loss of function and activating mode of actionca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca