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Faster Maximal Exact Matches with Lazy LCP Evaluation

2023/11/08 by Adrián Goga, Goga, Adrián, Lore Depuydt +9
Biochemistry, Genetics and Molecular Biology · Computer Science · #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Genomics and Phylogenetic Studies #Natural Language Processing Techniques

paper · pdf · doi:10.48550/arxiv.2311.04538

openalex publication_date 2023/11/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

MONI (Rossi et al., \it JCB 2022) is a BWT-based compressed index for computing the matching statistics and maximal exact matches (MEMs) of a pattern (usually a DNA read) with respect to a highly repetitive text (usually a database of genomes) using two operations: LF-steps and longest common extension (LCE) queries on a grammar-compressed representation of the text. In practice, most of the operations are constant-time LF-steps but most of the time is spent evaluating LCE queries. In this paper we show how (a variant of) the latter can be evaluated lazily, so as to bound the total time MONI needs to process the pattern in terms of the number of MEMs between the pattern and the text, while maintaining logarithmic latency.

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