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Swarm v2: highly-scalable and high-resolution amplicon clustering
Author(s) -
Frédéric Mahé,
Torbjørn Rognes,
Christopher Quince,
Colomban de Vargas,
Micah Dunthorn
Publication year - 2015
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.1420
Subject(s) - swarm behaviour , cluster analysis , computer science , scalability , amplicon , computation , data mining , biology , artificial intelligence , algorithm , database , genetics , polymerase chain reaction , gene
Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold ( d ), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

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