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Fast Set Operations for Compact k-mer Sets

Authors Jarno N. Alanko , Lore Depuydt , Camille Marchet , Simon J. Puglisi

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ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Data Structures
  • efficient Algorithms

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Abstract

The k-mer spectrum of a set of sequences is the set of k-length substrings the sequences contain. This lossy representation of sequence content pervades modern genomics. Recently, the spectral Burrows-Wheeler transform (SBWT) has emerged as a space-efficient representation of k-spectra that also supports efficient k-mer lookup queries and, more generally, easy navigation of the de Bruijn graph of the k-spectrum. In this paper, we examine primitive set operations, such as intersection, union, and set difference, on SBWT-encoded k-spectra and show that these operations can be supported efficiently. Moreover, efficient merging leads directly to a new memory-efficient algorithm for SBWT construction, which was able to build the SBWT for the 661K bacterial dataset containing 88 billion distinct k-mers in 50 hours using 186 GiB of RAM and 112 GiB of disk space. Given the pervasiveness of k-mer sets in genomics and the continued rapid growth of genomic databases, our work opens the door to a wide array of future applications that manipulate and reason about genomic data by dealing directly with simultaneously compact and searchable k-mer set representations offered by the SBWT.

Cite As Get BibTex

Jarno N. Alanko, Lore Depuydt, Camille Marchet, and Simon J. Puglisi. Fast Set Operations for Compact k-mer Sets. In 26th International Conference on Algorithms for Bioinformatics (WABI 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 390, pp. 18:1-18:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.WABI.2026.18

Author Details

Jarno N. Alanko
  • Department of Computer Science, University of Helsinki, Finland
Lore Depuydt
  • Univ. Lille, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France
Camille Marchet
  • Univ. Lille, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France
Simon J. Puglisi
  • Department of Computer Science, University of Helsinki, Finland

Funding

This work has benefited from funding from the French State under the France 2030 program, reference ANR-21-IDES-0006. The European Metropolis of Lille and the University of Lille are also acknowledged for their funding and support of the project WILL-CHAIRES-25-001-BOSSA.

Supplementary Materials

References

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    Software Heritage Logo archived version
    full metadata available at: https://doi.org/10.4230/artifacts.27674
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