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dc.contributor.authorWolf, F Alexanderen
dc.contributor.authorHamey, Fiona Ken
dc.contributor.authorPlass, Mireyaen
dc.contributor.authorSolana, Jordien
dc.contributor.authorDahlin, Joakim Sen
dc.contributor.authorGottgens, Bertholden
dc.contributor.authorRajewsky, Nikolausen
dc.contributor.authorSimon, Lukasen
dc.contributor.authorTheis, Fabian Jen
dc.date.accessioned2019-02-19T00:31:12Z
dc.date.available2019-02-19T00:31:12Z
dc.date.issued2019-03-19en
dc.identifier.issn1474-7596
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/289622
dc.description.abstractSingle-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graphlike map of the arising data manifold, based on estimating connectivity of manifold partitions (https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at di erent resolutions and result in much higher computational e ciency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.
dc.description.sponsorshipWellcome Trust, MRC, CRUK, Bloodwise, Swedish Research Council, Helmholtz Association, German Center for Cardiovascular Research, German Research Foundation
dc.format.mediumElectronicen
dc.languageengen
dc.publisherBioMed Central
dc.subjectHematopoietic Stem Cellsen
dc.subjectEmbryo, Nonmammalianen
dc.subjectAnimalsen
dc.subjectZebrafishen
dc.subjectHumansen
dc.subjectPlanariansen
dc.subjectSequence Analysis, RNAen
dc.subjectComputational Biologyen
dc.subjectGene Expression Regulation, Developmentalen
dc.subjectAlgorithmsen
dc.subjectReference Standardsen
dc.subjectComputer Graphicsen
dc.subjectSoftwareen
dc.subjectSingle-Cell Analysisen
dc.subjectHigh-Throughput Nucleotide Sequencingen
dc.titlePAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells.en
dc.typeArticle
prism.issueIdentifier1en
prism.publicationDate2019en
prism.publicationNameGenome biologyen
prism.startingPage59
prism.volume20en
dc.identifier.doi10.17863/CAM.36871
dcterms.dateAccepted2019-02-26en
rioxxterms.versionofrecord10.1186/s13059-019-1663-xen
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-03-19en
dc.contributor.orcidWolf, F Alexander [0000-0002-8760-7838]
dc.contributor.orcidHamey, Fiona K [0000-0001-7299-2860]
dc.contributor.orcidPlass, Mireya [0000-0002-9891-2723]
dc.contributor.orcidDahlin, Joakim S [0000-0003-3007-9875]
dc.contributor.orcidGottgens, Berthold [0000-0001-6302-5705]
dc.contributor.orcidRajewsky, Nikolaus [0000-0002-4785-4332]
dc.contributor.orcidSimon, Lukas [0000-0001-6148-8861]
dc.identifier.eissn1474-760X
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idLeukaemia & Lymphoma Research (12029)
pubs.funder-project-idNational Institutes of Health (NIH) (via Pennsylvania State University) (R24DK106766)
pubs.funder-project-idWellcome Trust (206328/Z/17/Z)
pubs.funder-project-idWellcome Trust (203151/Z/16/Z)
pubs.funder-project-idWellcome Trust (079895/Z/06/Z)
pubs.funder-project-idMRC (MC_PC_12009)
cam.orpheus.successMon Jun 08 08:19:01 BST 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2022-02-18


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