Faster Maximal Exact Matches with Lazy LCP Evaluation
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. © 2024 IEEE.
Más información
| Título según WOS: | Faster Maximal Exact Matches with Lazy LCP Evaluation |
| Título según SCOPUS: | Faster Maximal Exact Matches with Lazy LCP Evaluation |
| Título de la Revista: | Proceedings of the Data Compression Conference |
| Editorial: | Institute of Electrical and Electronics Engineers Inc. |
| Fecha de publicación: | 2024 |
| Página de inicio: | 123 |
| Página final: | 132 |
| Idioma: | English |
| DOI: |
10.1109/DCC58796.2024.00020 |
| Notas: | ISI, SCOPUS |