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

09/25/2014
PeerJ

Type

Article dans des revues

Authors

Mahé Frédéric
Rognes Torbjorn
Quince Christopher
De Vargas Colomban
Dunthorn Micah

Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarmwas 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.

Publications topics

biodiversity
bioinformatics
ecology
microbiology
molecular biology
environmental diversity
barcoding
molecular operational taxonomic units