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dc.contributor.authorRoss, Edith Men
dc.contributor.authorMarkowetz, Florianen
dc.date.accessioned2016-04-13T10:09:13Z
dc.date.available2016-04-13T10:09:13Z
dc.date.issued2016-04-15en
dc.identifier.citationGenome Biology 2016en
dc.identifier.issn1474-7596
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/254951
dc.description.abstractSingle-cell sequencing promises a high resolution view of genetic heterogeneity and clonal evolution in cancer. However, methods to infer tumour evolution from single-cell sequencing data lag behind methods developed for bulk-sequencing data. Here, we present oncoNEM, a probabilistic method for inferring intra-tumour evolutionary lineage trees from somatic single-nucleotide variants of single cells. OncoNEM identifies homogeneous cellular subpopulations and infers their genotypes as well as a tree describing their evolutionary relationships. In simulation studies, we assess oncoNEM’s robustness and benchmark its performance against competing methods. Finally, we show its applicability in case studies of muscle-invasive bladder cancer and essential thrombocythemia.
dc.description.sponsorshipThe authors would like to acknowledge the support of the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. This work was funded by CRUK core grant C14303/A17197.
dc.languageEnglishen
dc.language.isoenen
dc.publisherBioMed Central
dc.rightsAttribution 4.0 International
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjecttumour evolutionen
dc.subjectcancer evolutionen
dc.subjecttumour heterogeneityen
dc.subjectsingle-cell sequencingen
dc.subjectphylogenetic treeen
dc.titleOncoNEM: Inferring tumour evolution from single-cell sequencing dataen
dc.typeArticle
dc.provenanceOA-8116
dc.description.versionThis is the final version of the article. It first appeared from BioMed Central via https://doi.org/10.1186/s13059-016-0929-9en
prism.publicationDate2016en
prism.publicationNameGenome Biologyen
prism.volume17en
dc.rioxxterms.funderCRUK
dc.rioxxterms.projectidC14303/A17197
dcterms.dateAccepted2016-03-30en
rioxxterms.versionofrecord10.1186/s13059-016-0929-9en
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2016-04-15en
dc.contributor.orcidMarkowetz, Florian [0000-0002-2784-5308]
dc.identifier.eissn1474-760X
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idCancer Research UK (C14303_do not transfer)
pubs.funder-project-idCancer Research UK (CB4320)
cam.orpheus.successThu Jan 30 12:54:12 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International