Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression.
Details
Serval ID
serval:BIB_9B3CD4626BAA
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression.
Journal
Bioinformatics advances
ISSN
2635-0041 (Electronic)
ISSN-L
2635-0041
Publication state
Published
Issued date
03/2023
Peer-reviewed
Oui
Volume
3
Number
1
Pages
vbad021
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Publication Status: epublish
Abstract
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.
Source code and applications are available at https://github.com/rwk-unil/parallel_pbwt.
Supplementary data are available at Bioinformatics Advances online.
Pubmed
Open Access
Yes
Create date
20/03/2023 10:52
Last modification date
23/01/2024 7:31