PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysis

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• dc.contributor.author Ng, Samca
• dc.contributor.author Collisson, Eric A.ca
• dc.contributor.author Sokolov, Artemca
• dc.contributor.author Goldstein, Theodoreca
• dc.contributor.author González-Pérez, Abelca
• dc.contributor.author López Bigas, Núriaca
• dc.contributor.author Benz, Christopherca
• dc.contributor.author Haussler, Davidca
• dc.contributor.author Stuart, Joshua M.ca
• dc.date.accessioned 2015-12-07T17:23:14Z
• dc.date.available 2015-12-07T17:23:14Z
• dc.date.issued 2012
• dc.description.abstract MOTIVATION: A current challenge in understanding cancer processes is to pinpoint which mutations influence the onset and progression of disease. Toward this goal, we describe a method called PARADIGM-SHIFT that can predict whether a mutational event is neutral, gain-or loss-of-function in a tumor sample. The method uses a belief-propagation algorithm to infer gene activity from gene expression and copy number data in the context of a set of pathway interactions. RESULTS: The method was found to be both sensitive and specific on a set of positive and negative controls for multiple cancers for which pathway information was available. Application to the Cancer Genome Atlas glioblastoma, ovarian and lung squamous cancer datasets revealed several novel mutations with predicted high impact including several genes mutated at low frequency suggesting the approach will be complementary to current approaches that rely on the prevalence of events to reach statistical significance. AVAILABILITY: All source code is available at the github repository http:github.org/paradigmshift. CONTACT: jstuart@soe.ucsc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.ca
• dc.format.mimetype application/pdfca
• dc.identifier.citation Ng S, Collisson EA, Sokolov A, Goldstein T, Gonzalez-Perez A, Lopez-Bigas N et al. PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysis. Bioinformatics. 2012;28(18):i640-i646. DOI: 10.1093/bioinformatics/bts402ca
• dc.identifier.doi http://dx.doi.org/10.1093/bioinformatics/bts402
• dc.identifier.issn 1367-4803
• dc.identifier.uri http://hdl.handle.net/10230/25345
• dc.language.iso engca
• dc.publisher Oxford University Pressca
• dc.relation.ispartof Bioinformatics. 2012;28(18):i640-i646
• dc.rights © 2012 Ng S et al. 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/3.0ca
• dc.subject.other Expressió gènicaca
• dc.title PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysisca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca