Faster Maximal Exact Matches with Lazy LCP Evaluation
Data Structures and Algorithms
2023-11-09 v1
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.
Cite
@article{arxiv.2311.04538,
title = {Faster Maximal Exact Matches with Lazy LCP Evaluation},
author = {Adrián Goga and Lore Depuydt and Nathaniel K. Brown and Jan Fostier and Travis Gagie and Gonzalo Navarro},
journal= {arXiv preprint arXiv:2311.04538},
year = {2023}
}