Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation

dc.citation.articleNumberbtad512
dc.citation.issueNumber9
dc.citation.journalTitleBioinformatics
dc.citation.volumeNumber39
dc.contributor.authorKille, Bryce
dc.contributor.authorGarrison, Erik
dc.contributor.authorTreangen, Todd J
dc.contributor.authorPhillippy, Adam M
dc.date.accessioned2024-05-08T18:56:12Z
dc.date.available2024-05-08T18:56:12Z
dc.date.issued2023
dc.description.abstractThe Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates.To address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications.MashMap3 is available at https://github.com/marbl/MashMap.
dc.identifier.citationKille, B., Garrison, E., Treangen, T. J., & Phillippy, A. M. (2023). Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation. Bioinformatics, 39(9), btad512. https://doi.org/10.1093/bioinformatics/btad512
dc.identifier.digitalbtad512
dc.identifier.doihttps://doi.org/10.1093/bioinformatics/btad512
dc.identifier.urihttps://hdl.handle.net/1911/115693
dc.language.isoeng
dc.publisherOxford University Press
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleMinmers are a generalization of minimizers that enable unbiased local Jaccard estimation
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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