k mdiff, large-scale and user-friendly differential k-mer analyses

SUMMARY: Genome wide association studies elucidate links between genotypes and phenotypes. Recent studies point out the interest of conducting such experiments using k-mers as the base signal instead of single-nucleotide polymorphisms. We propose a tool, kmdiff, that performs differential k-mer anal...

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Detalles Bibliográficos
Autores principales: Lemane, Téo, Chikhi, Rayan, Peterlongo, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750116/
https://www.ncbi.nlm.nih.gov/pubmed/36315078
http://dx.doi.org/10.1093/bioinformatics/btac689
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author Lemane, Téo
Chikhi, Rayan
Peterlongo, Pierre
author_facet Lemane, Téo
Chikhi, Rayan
Peterlongo, Pierre
author_sort Lemane, Téo
collection PubMed
description SUMMARY: Genome wide association studies elucidate links between genotypes and phenotypes. Recent studies point out the interest of conducting such experiments using k-mers as the base signal instead of single-nucleotide polymorphisms. We propose a tool, kmdiff, that performs differential k-mer analyses on large sequencing cohorts in an order of magnitude less time and memory than previously possible. AVAILABILITYAND IMPLEMENTATION: https://github.com/tlemane/kmdiff SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-97501162022-12-15 k mdiff, large-scale and user-friendly differential k-mer analyses Lemane, Téo Chikhi, Rayan Peterlongo, Pierre Bioinformatics Applications Note SUMMARY: Genome wide association studies elucidate links between genotypes and phenotypes. Recent studies point out the interest of conducting such experiments using k-mers as the base signal instead of single-nucleotide polymorphisms. We propose a tool, kmdiff, that performs differential k-mer analyses on large sequencing cohorts in an order of magnitude less time and memory than previously possible. AVAILABILITYAND IMPLEMENTATION: https://github.com/tlemane/kmdiff SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-10-31 /pmc/articles/PMC9750116/ /pubmed/36315078 http://dx.doi.org/10.1093/bioinformatics/btac689 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Lemane, Téo
Chikhi, Rayan
Peterlongo, Pierre
k mdiff, large-scale and user-friendly differential k-mer analyses
title k mdiff, large-scale and user-friendly differential k-mer analyses
title_full k mdiff, large-scale and user-friendly differential k-mer analyses
title_fullStr k mdiff, large-scale and user-friendly differential k-mer analyses
title_full_unstemmed k mdiff, large-scale and user-friendly differential k-mer analyses
title_short k mdiff, large-scale and user-friendly differential k-mer analyses
title_sort k mdiff, large-scale and user-friendly differential k-mer analyses
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750116/
https://www.ncbi.nlm.nih.gov/pubmed/36315078
http://dx.doi.org/10.1093/bioinformatics/btac689
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