Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation
| dc.citation.articleNumber | btad512 | en_US |
| dc.citation.issueNumber | 9 | en_US |
| dc.citation.journalTitle | Bioinformatics | en_US |
| dc.citation.volumeNumber | 39 | en_US |
| dc.contributor.author | Kille, Bryce | en_US |
| dc.contributor.author | Garrison, Erik | en_US |
| dc.contributor.author | Treangen, Todd J | en_US |
| dc.contributor.author | Phillippy, Adam M | en_US |
| dc.date.accessioned | 2024-05-08T18:56:12Z | en_US |
| dc.date.available | 2024-05-08T18:56:12Z | en_US |
| dc.date.issued | 2023 | en_US |
| dc.description.abstract | The 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. | en_US |
| dc.identifier.citation | Kille, 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 | en_US |
| dc.identifier.digital | btad512 | en_US |
| dc.identifier.doi | https://doi.org/10.1093/bioinformatics/btad512 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/115693 | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Oxford University Press | en_US |
| dc.rights | Except 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. | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.title | Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation | en_US |
| dc.type | Journal article | en_US |
| dc.type.dcmi | Text | en_US |
| dc.type.publication | publisher version | en_US |
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