Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
Wertenbroek, Rick; Xenarios, Ioannis; Thoma, Yann; Delaneau, Olivier
2023

Résumé

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.

Détails

Titre Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression
Auteur(s)/ trice(s) Wertenbroek, Rick (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland ; Univeristy of Lausanne, Lausanne, Switzerland)
Xenarios, Ioannis (University of Lausanne, Lausanne, Switzerland)
Thoma, Yann (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Delaneau, Olivier (University of Lausanne, Lausanne, Switzerland)
Date 2023-03
Publié dans Bioinformatics Advances
Volume 2023, vol. 3, no. 1
Pagination 4 p.
DOI https://doi.org/10.1093/bioadv/vbad021
ISSN 2635-0041
Type d'article scientifique
Domaine Ingénierie et Architecture
Ecole HEIG-VD
Institut ReDS - Reconfigurable & embedded Digital Systems
Le document apparaît dans Articles scientifiques
Global

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