Evidence map›Paper›PMID 39607778›Full record

ArticleBioinformatics (Oxford, England)2024

BWT construction and search at the terabase scale.

Heng Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Movi 2: fast and space-efficient queries on pangenomes.Bioinformatics (Oxford, England) · 2026
    Article
  5. Article
  6. Lossless pangenome indexing using tag arrays.Algorithms for molecular biology : AMB · 2026
    Article
  7. Finding low-complexity DNA sequences with longdust.Bioinformatics (Oxford, England) · 2026
    Article
  8. Article
  9. Article
  10. Prefix-free parsing for merging big BWTs.International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium) · 2026
    Article
  11. An Efficient Dynamic Data Structure for Haplotype Matching and Compression on Biobank-Scale Data.Journal of computational biology : a journal of computational molecular cell biology · 2026
    Article
  12. Article
  13. KeBaB:International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium) · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Movi 2: Fast and Space-Efficient Queries on Pangenomes.bioRxiv : the preprint server for biology · 2025
    Article
  18. Article
  19. DynamicbioRxiv : the preprint server for biology · 2025
    Article
  20. Haplotype Matching with GBWT for Pangenome Graphs.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Heng LiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, United States.ORCID 0000-0003-4874-2874

Funding

The WashU-UCSC-EBI Human Genome Reference Center."U41HG010972 · NHGRI · WASHINGTON UNIVERSITY · PI Ting Wang · 2019 to 2026
$24.9M
Dockstore: The Community Platform for Reproducible Biomedical Workflows and ApplicationsU24HG011853 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Jonathan Lawson, Benedict Paten · 2021 to 2026
$5.7M
Advanced computational methods in analyzing high-throughput sequencing dataR01HG010040 · NHGRI · DANA-FARBER CANCER INST · PI Heng Li · 2018 to 2026
$3.7M
The construction and utility of reference pan-genome graphsU01HG010961 · NHGRI · DANA-FARBER CANCER INST · PI LI, HENG, PATEN, BENEDICT · 2020 to 2023
$3.2M
Tools for comprehensive variant characterization using the pangenomeU01HG013748 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI LI, HENG, MARSCHALL, TOBIAS · 2024 to 2024
$1.7M
National Institute of Health R01HG010040NHGRI NIH HHS R01 HG010040NHGRI NIH HHS U01 HG010961NHGRI NIH HHS U01 HG013748NHGRI NIH HHS U24 HG011853
6 · The paper itself

Abstract

motivationBurrows-Wheeler Transform (BWT) is a common component in full-text indices. Initially developed for data compression, it is particularly powerful for encoding redundant sequences such as pangenome data. However, BWT construction is resource intensive and hard to be parallelized, and many methods for querying large full-text indices only report exact matches or their simple extensions. These limitations have hampered the biological applications of full-text indices.

resultsWe developed ropebwt3 for efficient BWT construction and query. Ropebwt3 indexed 320 assembled human genomes in 65 h and indexed 7.3 terabases of commonly studied bacterial assemblies in 26 days. This was achieved using up to 170 gigabytes of memory at the peak without working disk space. Ropebwt3 can find maximal exact matches and inexact alignments under affine-gap penalties, and can retrieve similar local haplotypes matching a query sequence. It demonstrates the feasibility of full-text indexing at the terabase scale. AVAILABILITY AND IMPLEMENTATION: https://github.com/lh3/ropebwt3.

Indexed as

SoftwareAlgorithmsGenome, BacterialGenome, HumanGenomicsHumansSequence Alignment

Identifiers

PMID39607778
PMCPMC11646566

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.