Evidence map›Paper›PMID 42312341›Full record

ArticleBioinformatics (Oxford, England)2026

Movi 2: fast and space-efficient queries on pangenomes.

Mohsen Zakeri, Nathaniel K Brown, Travis Gagie, Ben Langmead

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Bounding the Average Move Structure Query for Faster and Smaller RLBWT Permutations.LIPIcs : Leibniz international proceedings in informatics · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Mohsen ZakeriDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, United States.ORCID 0000-0002-9856-719X
Nathaniel K BrownDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, United States.
Travis GagieFaculty of Computer Science, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada.ORCID 0000-0003-3689-327X
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, United States.

Funding

Efficient and scalable pangenomes with the move structureR21HG013433 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2024 to 2025
$399k
NHGRI NIH HHS R21 HG013433NHGRI NIH HHS R21HG013433
6 · The paper itself

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.

Indexed as

GenomicsSoftwareAlgorithmsHaplotypesHumans

Identifiers

PMID42312341
PMCPMC13379629

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.