Benchmarking of ASV clustering tools.

<p>a. Precision vs. recall for each run of the different tools. Colors correspond to the different runs and the legend shows the settings used: ‘sw’ is the difference cutoff in Swarm, ‘op’ the distance cutoff in OptiClust, and ‘db’ the distance and abundance cutoffs in dbOTU3. The diamond symb...

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Bibliographic Details
Main Author:	John Sundh (4486429) (author)
Other Authors:	Emma Granqvist (22582298) (author), Ela Iwaszkiewicz-Eggebrecht (21236594) (author), Lokeshwaran Manoharan (10693472) (author), Laura J. A. van Dijk (4639210) (author), Robert Goodsell (22582301) (author), Nerivania N. Godeiro (22582304) (author), Bruno C. Bellini (12844121) (author), Johanna Orsholm (22582307) (author), Piotr Łukasik (3319233) (author), Andreia Miraldo (3245715) (author), Tomas Roslin (425902) (author), Ayco J. M. Tack (2921256) (author), Anders F. Andersson (6628826) (author), Fredrik Ronquist (167458) (author)
Published:	2025
Subjects:	Genetics Evolutionary Biology Marine Biology Biological Sciences not elsewhere classified Information Systems not elsewhere classified signals across samples integrates &# 8216 echo &# 8217 best performing tools scale metabarcoding data deep metabarcoding data enabling efficient analysis noisy data taxonomic annotation sequencing errors reproducible approach parameter settings otu clustering novel algorithm insects demonstrate extensive datasets chimera removal biodiversity monitoring accuracy pipeline
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Benchmarking of ASV clustering tools.

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