Evidence map›Paper›PMID 42412794›Full record

ArticleBioinformatics (Oxford, England)2026

Scalable computation of ultrabubbles in pangenomes by orienting bidirected graphs.

Juha Harviainen, Francisco Sena, Corentin Moumard, Aleksandr Politov, Sebastian Schmidt, Alexandru I Tomescu

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Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Juha HarviainenDepartment of Computer Science, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-4581-840X
Francisco SenaDepartment of Computer Science, University of Helsinki, Helsinki, Finland.
Corentin MoumardDepartment of Computer Science, University of Helsinki, Helsinki, Finland.
Aleksandr PolitovDepartment of Computer Science, University of Helsinki, Helsinki, Finland.
Sebastian SchmidtDepartment of Computer Science, University of Helsinki, Helsinki, Finland.ORCID 0000-0003-4878-2809
Alexandru I TomescuDepartment of Computer Science, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-5747-8350

Funding

European Union 101169716Helsinki Institute of Information TechnologyResearch Council of Finland 351156
6 · The paper itself

Abstract

motivationPangenome graphs are increasingly used in bioinformatics, ranging from environmental surveillance and crop improvement to the construction of population-scale human pangenomes. As these graphs grow in size, methods that scale efficiently become essential. A central task in pangenome analysis is the discovery of variation structures. In directed graphs, the most widely studied such structures, superbubbles, can be identified in linear time. Their canonical generalization to bidirected graphs, ultrabubbles, more accurately models DNA reverse complementarity. However, existing ultrabubble algorithms are quadratic in the worst case.

resultsWe show that all ultrabubbles in a bidirected graph containing at least one tip or one cutvertex-a common property of pangenome graphs-can be computed in linear time. Our key contribution is a new linear-time orientation algorithm that transforms such a bidirected graph into a directed graph of the same size, in practice. Orientation conflicts are resolved by introducing auxiliary source or sink vertices. We prove that ultrabubbles in the original bidirected graph correspond to weak superbubbles in the resulting directed graph, enabling the use of existing linear-time algorithms. Our approach achieves speedups of up to 25× over the ultrabubble implementation in vg, and of >200× over BubbleGun, enabling scalable pangenome analyses. For example, on the v2.0 pangenome graph constructed by the Human Pangenome Reference Consortium from 232 individuals, after reading the input, our method completes in under 3 min, while vg requires >1 hour, and four times more RAM. AVAILABILITY AND IMPLEMENTATION: Our method is implemented in the BubbleFinder tool github.com/algbio/BubbleFinder, via the new ultrabubbles subcommand.

Indexed as

AlgorithmsComputational BiologyGenomicsHumans

Identifiers

PMID42412794
PMCPMC13341124

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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.