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Pangenome Graph Indexing via the Multidollar-BWT

Authors Davide Cozzi , Brian Riccardi , Luca Denti , Simone Ciccolella , Kunihiko Sadakane , Paola Bonizzoni

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ACM Subject Classification
  • Theory of computation → Data structures design and analysis
Keywords
  • Multidollar-BWT
  • Graph Index
  • Graph Pattern Matching
  • Pangenome Graph

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Abstract

Indexing pangenome graphs is a major algorithmic challenge in computational pangenomics, a recent and active research field that seeks to use graphs as representations of multiple genomes. Since these graphs are constructed from whole genome sequences of a species population, they can become very large, making indexing one of the most challenging problems.
In this paper, we propose gindex, a novel indexing approach to solve the Graph Pattern Matching Problem based on the multidollar-BWT. Specifically, gindex aims to find all occurrences of a pattern in a sequence-labeled graph by overcoming two main limitations of GCSA2, one of the most widely used graph indexes: handling queries of arbitrary length and scaling to large graphs without pruning any complex regions. Moreover, we show how a smart preprocessing step can optimize the use of multidollar-BWT to skip small redundant sub-patterns and enhance gindex’s querying capabilities.
We demonstrate the effectiveness of our approach by comparing it to GCSA2 in terms of index construction and query time, using different preprocessing modes on three pangenome graphs: one built from Drosophila genomes and two produced by the Human Pangenome Reference Consortium.
The results show that gindex can scale on human pangenome graphs - which GCSA2 cannot index using large amounts of RAM - with acceptable memory and time requirements. Moreover, gindex achieves fast query times, although not as fast as GCSA2, which may produce false positives.

Cite As Get BibTex

Davide Cozzi, Brian Riccardi, Luca Denti, Simone Ciccolella, Kunihiko Sadakane, and Paola Bonizzoni. Pangenome Graph Indexing via the Multidollar-BWT. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 13:1-13:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.SEA.2025.13

Author Details

Davide Cozzi
  • University of Milano-Bicocca, Milan, Italy
Brian Riccardi
  • University of Milano-Bicocca, Milan, Italy
Luca Denti
  • Comenius University, Bratislava, Slovakia
Simone Ciccolella
  • University of Milano-Bicocca, Milan, Italy
Kunihiko Sadakane
  • University of Tokyo, Japan
Paola Bonizzoni
  • University of Milano-Bicocca, Milan, Italy

Funding

This research work was initially developed in collaboration with S.K. during a secondment of P.B, B.R. and D. C. at the University of Tokyo in June 2024, under the project PANGAIA. L. D. has received funding from the European Union’s Horizon programme under the Horizon Europe grant agreement (ASVA-CGR No. 101180581). P.B., B.R, D.C. and S.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. and ITN ALPACA N.956229. 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. This work was supported by project 101160008 (FORGENOM II) funded by the Horizon Europe program.

Supplementary Materials

References

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