dc.date.accessioned | 2018-02-14T17:38:22Z | |
dc.date.available | 2018-02-14T17:38:22Z | |
dc.date.created | 2014-09-27T17:12:21Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Mahé, Frédéric Rognes, Torbjørn Quince, Christopher de Vargas, Colomban Dunthorn, Micah . Swarm: robust and fast clustering method for amplicon-based studies. PeerJ. 2014, 2014(1) | |
dc.identifier.uri | http://hdl.handle.net/10852/60103 | |
dc.description.abstract | Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. | |
dc.description.abstract | Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. | |
dc.language | EN | |
dc.publisher | PeerJ Inc. | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.title | Swarm: robust and fast clustering method for amplicon-based studies | |
dc.type | Journal article | |
dc.creator.author | Mahé, Frédéric | |
dc.creator.author | Rognes, Torbjørn | |
dc.creator.author | Quince, Christopher | |
dc.creator.author | de Vargas, Colomban | |
dc.creator.author | Dunthorn, Micah | |
cristin.unitcode | 185,15,5,35 | |
cristin.unitname | Forskningsgruppen for biomedisinsk informatikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 1158902 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=PeerJ&rft.volume=2014&rft.spage=&rft.date=2014 | |
dc.identifier.jtitle | PeerJ | |
dc.identifier.volume | 2014 | |
dc.identifier.issue | 1 | |
dc.identifier.pagecount | 13 | |
dc.identifier.doi | http://dx.doi.org/10.7717/peerj.593 | |
dc.identifier.urn | URN:NBN:no-62777 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 2167-8359 | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/60103/1/2014%2BMah%25C3%25A9-PeerJ.pdf | |
dc.type.version | PublishedVersion | |
cristin.articleid | e593 | |