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Phasing Data from Genotype Queries via the μ-PBWT

Authors Davide Cozzi , Paola Bonizzoni , Christina Boucher , Ben Langmead , Yuri Pirola

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ACM Subject Classification
  • Theory of computation → Data structures design and analysis
Keywords
  • Positional Burrows-Wheeler Transform
  • r-index
  • minimal position substring cover
  • set-maximal exact matches
  • genotype phasing

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Abstract

Genotype phasing - the process of reconstructing haplotypes from genotype data - is a fundamental problem in genomics with applications in ancestry inference, imputation, and disease association. Traditional phasing methods rely on statistical models or combinatorial approaches which can be computationally expensive, particularly when applied to large-scale reference panels.
In this paper, we present a first exploration of using the μ-PBWT (a run-length encoded Positional Burrows-Wheeler Transform) to solve the genotype phasing problem with a reference panel. Leveraging our previous results on positional substrings, we propose an approach that can explain a query genotype if the corresponding haplotype pair exists in the input panel. Moreover, our method is extended to cases where such a pair does not exist, even though some regions should remain unphased if they cannot be explicitly explained using the reference panel.
We implemented this method and compared it against Beagle, a state-of-the-art phasing tool, demonstrating that, in the absence of mutations and recombinations, our approach correctly identifies the haplotype pair that explains a genotype query while using seven times less memory than Beagle. However, we also observe that as mutation rates increase, the quality of the phasing decreases as a result of the growing difficulty of identifying consistent haplotype pairs in the presence of sequence variation.
These findings highlight the potential of μ-PBWT as an efficient alternative for genotype phasing, particularly in settings where computational resources are limited. The source code is publicly available at https://github.com/dlcgold/muPBWT/tree/phase.

Cite As Get BibTex

Davide Cozzi, Paola Bonizzoni, Christina Boucher, Ben Langmead, and Yuri Pirola. Phasing Data from Genotype Queries via the μ-PBWT. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 10:1-10:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.Manzini.10

Author Details

Davide Cozzi
  • Department of Computer Science, University of Milano-Bicocca, Italy
Paola Bonizzoni
  • Department of Computer Science, University of Milano-Bicocca, Italy
Christina Boucher
  • Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA
Ben Langmead
  • Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
Yuri Pirola
  • Department of Computer Science, University of Milano-Bicocca, Italy

Funding

P.B., Y.P., and D.C. have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement PANGAIA No. 872539. P.B. is also supported by the grant MIUR 2022YRB97K, PINC, Pangenome Informatics: from Theory to Applications, funded by the EU, Next-Generation EU, Mission 4 and ITN ALPACA N.956229. C.B. was supported by NIH/NIAID (Grant No. R01AI14180) and NSF:SCH:INT (Grant No. 2013998). C.B. and B.L were supported by NIH:NHGRI: (Grant No. R56HG013865).

Supplementary Materials

References

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