Movi: A fast and cache-efficient full-text pangenome index

Pangenome indexes are promising tools for many applications, including classification of nanopore sequencing reads. Move structure is a compressed-index data structure based on the Burrows-Wheeler Transform (BWT). It offers simultaneous O(1)-time queries and O(r) space, where r is the number of BWT runs (consecutive sequence of identical characters). We developed Movi based on the move structure for indexing and querying pangenomes. Movi scales very well for repetitive text as its size grows strictly by r. Movi computes sophisticated matching queries for classification such as pseudo-matching lengths and backward search up to 30 times faster than existing methods by minimizing the number of cache misses and using memory prefetching to attain a degree of latency hiding. Movi's fast constant-time query loop makes it well suited to real-time applications like adaptive sampling for nanopore sequencing, where decisions must be made in a small and predictable time interval.

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Publication Details

Journal
iScience
Published
2024-11-27
DOI
https://doi.org/10.1016/j.isci.2024.111464
Citations
28
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
9.73

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article

Movi: A fast and cache-efficient full-text pangenome index

Ben Langmead, Travis Gagie, Nathaniel K. Brown, Mohsen Zakeri et al.
28 citations
iScience
Algorithms and Data Compression
9.73
article

Movi: A fast and cache-efficient full-text pangenome index

Ben Langmead, Travis Gagie, Nathaniel K. Brown, Mohsen Zakeri, Omar Ahmed
article en
28 citations

Abstract

Pangenome indexes are promising tools for many applications, including classification of nanopore sequencing reads. Move structure is a compressed-index data structure based on the Burrows-Wheeler Transform (BWT). It offers simultaneous O(1)-time queries and O(r) space, where r is the number of BWT runs (consecutive sequence of identical characters). We developed Movi based on the move structure for indexing and querying pangenomes. Movi scales very well for repetitive text as its size grows strictly by r. Movi computes sophisticated matching queries for classification such as pseudo-matching lengths and backward search up to 30 times faster than existing methods by minimizing the number of cache misses and using memory prefetching to attain a degree of latency hiding. Movi's fast constant-time query loop makes it well suited to real-time applications like adaptive sampling for nanopore sequencing, where decisions must be made in a small and predictable time interval.

iScienceVol. 27(12)
Dalhousie University (CA), Johns Hopkins University (US), Johns Hopkins Medicine (US)
National Science Foundation, Johns Hopkins University, National Institutes of Health, Natural Sciences and Engineering Research Council of Canada
Climate action
Openalex Percentile: Top 2%
Algorithms and Data Compression
9.73
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Movi: A fast and cache-efficient full-text pangenome index — Ben Langmead, Travis Gagie, et al. · iScience (2024) | TGRS Research Map | TGRS