Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression

SUMMARY: The positional Burrows–Wheeler transform (PBWT) data structure allows for efficient haplotype data matching and compression. Its performance makes it a powerful tool for bioinformatics. However, existing algorithms do not exploit parallelism due to inner dependencies. We introduce a new met...

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Autores principales: Wertenbroek, Rick, Xenarios, Ioannis, Thoma, Yann, Delaneau, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Application Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005600/
https://www.ncbi.nlm.nih.gov/pubmed/36908398
http://dx.doi.org/10.1093/bioadv/vbad021
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author Wertenbroek, Rick
Xenarios, Ioannis
Thoma, Yann
Delaneau, Olivier
author_facet Wertenbroek, Rick
Xenarios, Ioannis
Thoma, Yann
Delaneau, Olivier
author_sort Wertenbroek, Rick
collection PubMed
description SUMMARY: The positional Burrows–Wheeler transform (PBWT) data structure allows for efficient haplotype data matching and compression. Its performance makes it a powerful tool for bioinformatics. However, existing algorithms do not exploit parallelism due to inner dependencies. We introduce a new method to break the dependencies and show how to fully exploit modern multi-core processors. AVAILABILITY AND IMPLEMENTATION: Source code and applications are available at https://github.com/rwk-unil/parallel_pbwt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.
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spelling pubmed-100056002023-03-11 Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression Wertenbroek, Rick Xenarios, Ioannis Thoma, Yann Delaneau, Olivier Bioinform Adv Application Note SUMMARY: The positional Burrows–Wheeler transform (PBWT) data structure allows for efficient haplotype data matching and compression. Its performance makes it a powerful tool for bioinformatics. However, existing algorithms do not exploit parallelism due to inner dependencies. We introduce a new method to break the dependencies and show how to fully exploit modern multi-core processors. AVAILABILITY AND IMPLEMENTATION: Source code and applications are available at https://github.com/rwk-unil/parallel_pbwt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2023-03-02 /pmc/articles/PMC10005600/ /pubmed/36908398 http://dx.doi.org/10.1093/bioadv/vbad021 Text en © The Author(s) 2023. 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 Application Note
Wertenbroek, Rick
Xenarios, Ioannis
Thoma, Yann
Delaneau, Olivier
Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title_full Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title_fullStr Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title_full_unstemmed Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title_short Exploiting parallelization in positional Burrows–Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
title_sort exploiting parallelization in positional burrows–wheeler transform (pbwt) algorithms for efficient haplotype matching and compression
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005600/
https://www.ncbi.nlm.nih.gov/pubmed/36908398
http://dx.doi.org/10.1093/bioadv/vbad021
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