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Faster Maximal Exact Matches with Lazy LCP Evaluation.

Authors :
Goga A
Depuydt L
Brown NK
Fostier J
Gagie T
Navarro G
Source :
Proceedings. Data Compression Conference [Proc Data Compress Conf] 2024 Mar; Vol. 2024, pp. 123-132. Date of Electronic Publication: 2024 May 21.
Publication Year :
2024

Abstract

MONI (Rossi et al., 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.

Details

Language :
English
ISSN :
2375-0383
Volume :
2024
Database :
MEDLINE
Journal :
Proceedings. Data Compression Conference
Publication Type :
Academic Journal
Accession number :
39157794
Full Text :
https://doi.org/10.1109/dcc58796.2024.00020