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Matchtigs: minimum plain text representation of k-mer sets

We propose a polynomial algorithm computing a minimum plain-text representation of k-mer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to...

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Autores principales: Schmidt, Sebastian, Khan, Shahbaz, Alanko, Jarno N., Pibiri, Giulio E., Tomescu, Alexandru I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251615/
https://www.ncbi.nlm.nih.gov/pubmed/37296461
http://dx.doi.org/10.1186/s13059-023-02968-z
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author Schmidt, Sebastian
Khan, Shahbaz
Alanko, Jarno N.
Pibiri, Giulio E.
Tomescu, Alexandru I.
author_facet Schmidt, Sebastian
Khan, Shahbaz
Alanko, Jarno N.
Pibiri, Giulio E.
Tomescu, Alexandru I.
author_sort Schmidt, Sebastian
collection PubMed
description We propose a polynomial algorithm computing a minimum plain-text representation of k-mer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 59% over unitigs and 26% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 90% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26× over unitigs and 2.10× over previous work. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02968-z.
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spelling pubmed-102516152023-06-10 Matchtigs: minimum plain text representation of k-mer sets Schmidt, Sebastian Khan, Shahbaz Alanko, Jarno N. Pibiri, Giulio E. Tomescu, Alexandru I. Genome Biol Method We propose a polynomial algorithm computing a minimum plain-text representation of k-mer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 59% over unitigs and 26% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 90% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26× over unitigs and 2.10× over previous work. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02968-z. BioMed Central 2023-06-09 /pmc/articles/PMC10251615/ /pubmed/37296461 http://dx.doi.org/10.1186/s13059-023-02968-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Schmidt, Sebastian
Khan, Shahbaz
Alanko, Jarno N.
Pibiri, Giulio E.
Tomescu, Alexandru I.
Matchtigs: minimum plain text representation of k-mer sets
title Matchtigs: minimum plain text representation of k-mer sets
title_full Matchtigs: minimum plain text representation of k-mer sets
title_fullStr Matchtigs: minimum plain text representation of k-mer sets
title_full_unstemmed Matchtigs: minimum plain text representation of k-mer sets
title_short Matchtigs: minimum plain text representation of k-mer sets
title_sort matchtigs: minimum plain text representation of k-mer sets
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10251615/
https://www.ncbi.nlm.nih.gov/pubmed/37296461
http://dx.doi.org/10.1186/s13059-023-02968-z
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