Swarm: robust and fast clustering method for amplicon-based studies

Mahé, F., Rognes, T., Quince, C., de Vargas, C. and Dunthorn, M. (2014) Swarm: robust and fast clustering method for amplicon-based studies. PeerJ, 2(e593), (doi: 10.7717/peerj.593) (PMID:25276506)

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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.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Quince, Dr Christopher
Authors: Mahé, F., Rognes, T., Quince, C., de Vargas, C., and Dunthorn, M.
College/School:College of Science and Engineering > School of Engineering
Journal Name:PeerJ
Publisher:PeerJ
ISSN:2167-8359
ISSN (Online):2167-8359
Copyright Holders:Copyright © 2014 The Authors
First Published:First published in PeerJ 2:e593
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
503351Pioneering the genomics era of environmental microbiologyChristopher QuinceEngineering & Physical Sciences Research Council (EPSRC)EP/H003851/1ENG - ENGINEERING INFRASTRUCTURE & ENVIR