# Efficient and scalable pangenomes with the move structure

> **NIH NIH R21** · JOHNS HOPKINS UNIVERSITY · 2024 · $198,495

## Abstract

PROJECT SUMMARY
Pangenome references and indexes have been shown to alleviate the reference bias problem. Computer
scientists recently described the novel “move structure,” which supports similar pattern-matching capabil-
ities as the more typical r-index or F M -index structures, but with radically improved locality of reference.
That is, move-structure algorithms access computer memory in a predictable way that minimizes cache
misses, or other kinds of pauses due to data movement. We will adapt the “move structure” to the problem
of pangenome indexing, enabling extremely and consistently fast pangenome queries. This will allow us
to leverage inclusive and bias-avoiding pangenomes in applications where (a) we must keep up with a
sequencer in real-time, e.g. nanopore sequencing, or (b) the index is so big that we must divide it across
many computers, e.g. BLAST-like sequence classification.

## Key facts

- **NIH application ID:** 10813518
- **Project number:** 1R21HG013433-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Benjamin Thomas Langmead
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $198,495
- **Award type:** 1
- **Project period:** 2024-02-01 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10813518

## Citation

> US National Institutes of Health, RePORTER application 10813518, Efficient and scalable pangenomes with the move structure (1R21HG013433-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10813518. Licensed CC0.

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