ArticleBMC bioinformatics2019
Multi-allelic positional Burrows-Wheeler transform.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- TS-IBD: An efficient ancestral recombination graph-based identity by descent segment detection method.Human population genetics and genomics · 2026Article
- Flexible read-aware genotype imputation from sequence using biobank sized reference panels.Nature communications · 2025Article
- Haplotype Matching with GBWT for Pangenome Graphs.bioRxiv : the preprint server for biology · 2025Article
- Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank.eLife · 2024Article
- Minimal positional substring cover is a haplotype threading alternative to Li and Stephens model.Genome research · 2023Article
- Minimal Positional Substring Cover: A Haplotype Threading Alternative to Li & Stephens Model.bioRxiv : the preprint server for biology · 2023Article
- Syllable-PBWT for space-efficient haplotype long-match query.Bioinformatics (Oxford, England) · 2023Article
- Haplotype Threading Using the Positional Burrows-Wheeler Transform.Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop) · 2022Article
- Computational graph pangenomics: a tutorial on data structures and their applications.Natural computing · 2022Article
- d-PBWT: dynamic positional Burrows-Wheeler transform.Bioinformatics (Oxford, England) · 2021Article
- Discovery of runs-of-homozygosity diplotype clusters and their associations with diseases in UK Biobank.medRxiv : the preprint server for health sciences · 2020Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundRecent advances in whole-genome sequencing and SNP array technology have led to the generation of a large amount of genotype data. Large volumes of genotype data will require faster and more efficient methods for storing and searching the data. Positional Burrows-Wheeler Transform (PBWT) provides an appropriate data structure for bi-allelic data. With the increasing sample sizes, more multi-allelic sites are expected to be observed. Hence, there is a necessity to handle multi-allelic genotype data.
resultsIn this paper, we introduce a multi-allelic version of the Positional Burrows-Wheeler Transform (mPBWT) based on the bi-allelic version for compression and searching. The time-complexity for constructing the data structure and searching within a panel containing t-allelic sites increases by a factor of t.
conclusionConsidering the small value for the possible alleles t, the time increase for the multi-allelic PBWT will be negligible and comparable to the bi-allelic version of PBWT.
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