Evidence map›Paper›PMID 36908398›Full record

ArticleBioinformatics advances2023

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

Rick Wertenbroek, Ioannis Xenarios, Yann Thoma, Olivier Delaneau

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Article in Bioinformatics advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Haplotype-based Parallel PBWT for Biobank Scale Data.IEEE ... International Conference on Computational Advances in Bio and Medical Sciences : [proceedings]. IEEE International Conference on Computational Advances in Bio and Medical Sciences · 2026
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rick WertenbroekSchool of Engineering and Management Vaud (HEIG-VD), HES-SO University of Applied Sciences and Arts Western Switzerland, Yverdon-les-Bains 1401, Switzerland.ORCID https://orcid.org/0000-0003-4114-6615
Ioannis XenariosDepartment of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.ORCID https://orcid.org/0000-0002-3413-6841
Yann ThomaSchool of Engineering and Management Vaud (HEIG-VD), HES-SO University of Applied Sciences and Arts Western Switzerland, Yverdon-les-Bains 1401, Switzerland.
Olivier DelaneauDepartment of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

Identifiers

PMID36908398
PMCPMC10005600

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.