ArticleBioinformatics (Oxford, England)2026
Movi 2: fast and space-efficient queries on pangenomes.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Building genomic data structures from compressed representations using prefix-free parsing.Genome research · 2026Review
- Bounding the Average Move Structure Query for Faster and Smaller RLBWT Permutations.LIPIcs : Leibniz international proceedings in informatics · 2026Article
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Abstract
summarySpace-efficient compressed indexing methods are critical for pangenomics and for avoiding reference bias. In the Movi study, we implemented the move-structure index, highlighting its locality-of-reference and speed. However, Movi had a high memory footprint compared to other compressed indexes. Here, we introduce Movi 2 and describe new methods that greatly reduce size and memory footprint of move structure-based indexes. The most compressed version of Movi 2 reduces the Movi index's space footprint more than five-fold. We also introduce sampling approaches that enable trade-offs between query and space efficiency. To demonstrate, we show that Movi 2 achieves advantageous time and space tradeoffs when applied to large pangenome collections, including both the first and second releases of the Human Pangenome Reference Consortium (HPRC) collection, the latter of which spans over 460 human haplotypes. We show that Movi 2 dominates prior methods on both speed and memory footprint, including both r-index-based and our previous move-structure-based method. AVAILABILITY AND IMPLEMENTATION: The methods we developed for Movi 2 are publicly available at https://github.com/mohsenzakeri/Movi.
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