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MONI Can Find k-MEMs

Authors Igor Tatarnikov , Ardavan Shahrabi Farahani, Sana Kashgouli, Travis Gagie

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Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • Compact data structures
  • Burrows-Wheeler Transform
  • run-length compression
  • maximal exact matches

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Abstract

Suppose we are asked to index a text T [0..n - 1] such that, given a pattern P [0..m - 1], we can quickly report the maximal substrings of P that each occur in T at least k times. We first show how we can add O (r log n) bits to Rossi et al.’s recent MONI index, where r is the number of runs in the Burrows-Wheeler Transform of T, such that it supports such queries in O (k m log n) time. We then show how, if we are given k at construction time, we can reduce the query time to O (m log n).

Cite As Get BibTex

Igor Tatarnikov, Ardavan Shahrabi Farahani, Sana Kashgouli, and Travis Gagie. MONI Can Find k-MEMs. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 26:1-26:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.CPM.2023.26

Author Details

Igor Tatarnikov
  • Dalhousie University, Halifax, Canada
Ardavan Shahrabi Farahani
  • Dalhousie University, Halifax, Canada
Sana Kashgouli
  • Dalhousie University, Halifax, Canada
Travis Gagie
  • Dalhousie University, Halifax, Canada

Funding

This research was supported by National Institutes of Health (NIH) NIAID (grant no. HG011392), the National Science Foundation NSF IIBR (grant no. 2029552), a Natural Science and Engineering Research Council (NSERC) Discovery Grant (grant no. RGPIN-07185-2020) and the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) through the Centre for Biotechnology and Bioengineering (grant CeBiB FB0001).

Acknowledgements

The authors thank Christina Boucher, Ben Langmead, Manuel Mattheisen and Massimiliano Rossi for helpful discussions.

References

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