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Efficient Algorithms for Pangenome Personalization

Authors Denys Andrukhovskyi , Martin Madzin , Luca Denti , Tomáš Vinař , Broňa Brejová

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Subject Classification

ACM Subject Classification
  • Applied computing → Computational genomics
  • Theory of computation → Design and analysis of algorithms
Keywords
  • pangenome graph
  • approximation algorithm
  • network flow

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Abstract

A pangenome graph is a representation of the genomes of multiple individuals of the same species. Using a pangenome graph reference instead of a single linear reference genome can increase accuracy of read mapping and downstream tasks, e.g., variant calling, but can also lead to increasing computational demands and false positives. In 2024, Sirén et al. proposed to select only parts of the pangenome mostly likely to match a studied individual, introducing the so-called personalized pangenome reference. Their algorithm is based on greedily selecting sections of paths representing individual haplotypes comprising the pangenome. In this article, we formulate the problem of pangenome personalization purely in terms of pangenome vertices and edges, as finding two paths using vertices supported by sequencing data. We provide several algorithms for solving the problem, ranging from a simple linear-time greedy algorithm with approximation ratio analysis, through dynamic programming and application of minimum-cost flow. Our implementation misses only a small percentage of vertices belonging to the studied individual and improves the sensitivity of read mapping compared to the linear reference.

Cite As Get BibTex

Denys Andrukhovskyi, Martin Madzin, Luca Denti, Tomáš Vinař, and Broňa Brejová. Efficient Algorithms for Pangenome Personalization. In 26th International Conference on Algorithms for Bioinformatics (WABI 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 390, pp. 8:1-8:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.WABI.2026.8

Author Details

Denys Andrukhovskyi
  • Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia
Martin Madzin
  • Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia
Luca Denti
  • Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia
Tomáš Vinař
  • Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia
Broňa Brejová
  • Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia

Funding

  • Denti, Luca: This research work has received funding from the European Union’s Horizon programme under the Horizon Europe grant agreement (ASVA-CGR No. 101180581).
  • Vinař, Tomáš: This research was supported in part by the Slovak Grant Agency VEGA grant 1/0567/26.
  • Brejová, Broňa: This research was supported in part by the Slovak Grant Agency VEGA grant 1/0140/25.

Supplementary Materials

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