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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Detalles Bibliográficos
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
Descripción
Sumario: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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