Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression.
Fiche du document
- doi: 10.1093/bioadv/vbad021
- issn: 2635-0041
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1093/bioadv/vbad021
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/36908398
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/2635-0041
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_9B3CD4626BAA2
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
Sujets proches
Algorism Biological informatics Bio-informaticsCiter ce document
R. Wertenbroek et al., « Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression. », Serveur académique Lausannois, ID : 10.1093/bioadv/vbad021
Métriques
Partage / Export
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. Source code and applications are available at https://github.com/rwk-unil/parallel_pbwt. Supplementary data are available at Bioinformatics Advances online.
