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dc.contributor.authorDaneshjou, Roxana
dc.contributor.authorWang, Yanran
dc.contributor.authorBromberg, Yana
dc.contributor.authorBovo, Samuele
dc.contributor.authorMartelli, Pier L
dc.contributor.authorBabbi, Giulia
dc.contributor.authorDi Lena, Pietro
dc.contributor.authorCasadio, Rita
dc.contributor.authorEdwards, Matthew D
dc.contributor.authorGifford, David K
dc.contributor.authorJones, David T
dc.contributor.authorSundaram, Laksshman
dc.contributor.authorBhat, Rajendra
dc.contributor.authorLi, Xiaolin
dc.contributor.authorPal, Lipika R.
dc.contributor.authorKundu, Kunal
dc.contributor.authorYin, Yizhou
dc.contributor.authorMoult, John
dc.contributor.authorJiang, Yuxiang
dc.contributor.authorPejaver, Vikas
dc.contributor.authorPagel, Kymberleigh A.
dc.contributor.authorLi, Biao
dc.contributor.authorMooney, Sean D.
dc.contributor.authorRadivojac, Predrag
dc.contributor.authorShah, Sohela
dc.contributor.authorCarraro, Marco
dc.contributor.authorGasparini, Alessandra
dc.contributor.authorLeonardi, Emanuela
dc.contributor.authorGiollo, Manuel
dc.contributor.authorFerrari, Carlo
dc.contributor.authorTosatto, Silvio C E
dc.contributor.authorBachar, Eran
dc.contributor.authorAzaria, Johnathan R.
dc.contributor.authorOfran, Yanay
dc.contributor.authorUnger, Ron
dc.contributor.authorNiroula, Abhishek
dc.contributor.authorVihinen, Mauno
dc.contributor.authorChang, Billy
dc.contributor.authorWang, Maggie H
dc.contributor.authorFranke, Andre
dc.contributor.authorPetersen, Britt-Sabina
dc.contributor.authorPirooznia, Mehdi
dc.contributor.authorZandi, Peter
dc.contributor.authorMcCombie, Richard
dc.contributor.authorPotash, James B
dc.contributor.authorAltman, Russ
dc.contributor.authorKlein, Teri E.
dc.contributor.authorHoskins, Roger
dc.contributor.authorRepo, Susanna
dc.contributor.authorBrenner, Steve E
dc.contributor.authorMorgan, Alexander A
dc.date.accessioned2021-01-13T22:47:51Z
dc.date.available2021-01-13T22:47:51Z
dc.date.issued2017-08
dc.date.submitted2017-06
dc.identifier.issn1098-1004
dc.identifier.urihttps://hdl.handle.net/1721.1/129418
dc.description.abstractPrecision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype–phenotype relationships.en_US
dc.language.isoen
dc.publisherWileyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/HUMU.23280en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleWorking toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challengesen_US
dc.typeArticleen_US
dc.identifier.citationDaneshjou, Roxana et al. "Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges." Human Mutation 38, 9 (September 2017): 1182-1192 © 2017 Wiley Periodicals, Inc.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalHuman Mutationen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-05-29T14:24:16Z
dspace.date.submission2019-05-29T14:24:17Z
mit.journal.volume38en_US
mit.journal.issue9en_US
mit.metadata.statusComplete


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