Faster Maximal Exact Matches with Lazy LCP Evaluation

Goga, Adrián; Depuydt, Lore; Brown, Nathaniel K.; Fostier, Jan; Gagie, Travis; Navarro, Gonzalo

doi:10.1109/dcc58796.2024.00020

Cited by 2 publications

(1 citation statement)

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“…Note that the additional memory usage required to support locating can still be decreased by applying the subsampling technique [8, 15].…”

Section: Resultsmentioning

confidence: 99%

b-move: faster bidirectional character extensions in a run-length compressed index

Depuydt,

Renders,

Van de Vyver

et al. 2024

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Due to the increasing availability of high-quality genome sequences, pan-genomes are gradually replacing single consensus reference genomes in many bioinformatics pipelines to better capture genetic diversity. Traditional bioinformatics tools using the FM-index face memory limitations with such large genome collections. Recent advancements in run-length compressed indices like Gagie et al.’s r-index and Nishimoto and Tabei’s move structure, alleviate memory constraints but focus primarily on backward search for MEM-finding. Arakawa et al.’s br-index initiates complete approximate pattern matching using bidirectional search in run-length compressed space, but with significant computational overhead due to complex memory access patterns. We introduce b-move, a novel bidirectional extension of the move structure, enabling fast, cache-efficient bidirectional character extensions in run-length compressed space. It achieves bidirectional character extensions up to 8 times faster than the br-index, closing the performance gap with FM-index-based alternatives, while maintaining the br-index’s favorable memory characteristics. For example, all available completeE. coligenomes on NCBI’s RefSeq collection can be compiled into a b-move index that fits into the RAM of a typical laptop. Thus, b-move proves practical and scalable for pan-genome indexing and querying. We provide a C++ implementation of b-move, supporting efficient lossless approximate pattern matching including locate functionality, available athttps://github.com/biointec/b-moveunder the AGPL-3.0 license.FundingLore Depuydt: PhD Fellowship FR (1117322N), Research Foundation – Flanders (FWO)Luca Renders: PhD Fellowship SB (1SE7822N), Research Foundation – Flanders (FWO)Travis Gagie: NSERC Discovery Grant RGPIN-07185-2020 to Travis Gagie and NIH grant R01HG011392 to Ben Langmead

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“…Note that the additional memory usage required to support locating can still be decreased by applying the subsampling technique [8, 15].…”

Section: Resultsmentioning

confidence: 99%