MUFFINN: cancer gene discovery via network analysis of somatic mutation data

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• dc.contributor.author Cho, Araca
• dc.contributor.author Shim, Jungca
• dc.contributor.author Kim, Eiruca
• dc.contributor.author Supek, Franca
• dc.contributor.author Lehner, Ben, 1978-ca
• dc.contributor.author Lee, Insukca
• dc.date.accessioned 2016-11-28T16:32:56Z
• dc.date.available 2016-11-28T16:32:56Z
• dc.date.issued 2016ca
• dc.description.abstract A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.
• dc.description.sponsorship This research was partly supported by grants from the National Research Foundation of Korea (2012M3A9B4028641, 2012M3A9C7050151, 2015R1A2A1A15055859), Brain Korea 21 (BK21) PLUS program to I.L., Global PH.D Fellowship Program through the National Research Foundation of Korea (2011-0008548) to A.C., the European Research Council (Consolidator grant IR-DC, 616434), the Spanish Ministry of Economy and Competitiveness (BFU2011-26206 and SEV-2012-0208), the AXA Research Fund, and AGAUR to B.L., the FP7 FET grant MAESTRA (ICT-2013-612944) and Marie Curie Actions to F.S.
• dc.format.mimetype application/pdfca
• dc.identifier.citation Cho A, Shim J, Kim E, Supek F, Lehner B, Lee I. MUFFINN: cancer gene discovery via network analysis of somatic mutation data. Genome Biology. 2016; 17:129. DOI: 10.1186/s13059-016-0989-xca
• dc.identifier.doi http://dx.doi.org/10.1186/s13059-016-0989-x
• dc.identifier.issn 1474-760Xca
• dc.identifier.uri http://hdl.handle.net/10230/27623
• dc.language.iso engca
• dc.publisher BioMed Centralca
• dc.relation.ispartof Genome Biology. 2016;17:129
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/612944ca
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BFU2011-26206
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SEV2012-0208
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/612944
• dc.rights © 2016 The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.ca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Cancer gene prediction
• dc.subject.keyword Cancer somatic mutation
• dc.subject.keyword Cancer genomes
• dc.subject.keyword Mutation frequency
• dc.subject.keyword Functional gene network
• dc.subject.keyword Pathway-centric analysis
• dc.title MUFFINN: cancer gene discovery via network analysis of somatic mutation dataca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca