Evidence map›Paper›PMID 39400346›Full record

ArticleBioinformatics (Oxford, England)2024

Cluster-efficient pangenome graph construction with nf-core/pangenome.

Simon Heumos, Michael L Heuer, Friederike Hanssen, Lukas Heumos, Andrea Guarracino, Peter Heringer, Philipp Ehmele, Pjotr Prins, Erik Garrison, Sven Nahnsen

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 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
  3. Approaches to Studying Viral Pangenome Variation Graphs.Genomics, proteomics & bioinformatics · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Early Detection of BothInternational journal of molecular sciences · 2024
    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

10 authors.

Simon HeumosQuantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany.ORCID 0000-0003-3326-817X
Michael L HeuerUniversity of California, Berkeley, Berkeley, CA 94720, United States.ORCID 0000-0002-9052-6000
Friederike HanssenQuantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany.ORCID 0009-0001-9875-5262
Lukas HeumosDepartment of Computational Health, Institute of Computational Biology, Helmholtz Munich, Munich, 85764, Germany.ORCID 0000-0002-8937-3457
Andrea GuarracinoDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States.ORCID 0000-0001-9744-131X
Peter HeringerQuantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany.ORCID 0009-0005-5985-2317
Philipp EhmeleDepartment of Computational Health, Institute of Computational Biology, Helmholtz Munich, Munich, 85764, Germany.ORCID 0000-0001-5945-7839
Pjotr PrinsDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States.ORCID 0000-0002-8021-9162
Erik GarrisonDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, United States.ORCID 0000-0003-3821-631X
Sven NahnsenQuantitative Biology Center (QBiC) Tübingen, University of Tübingen, Tübingen, 72076, Germany.ORCID 0000-0002-4375-0691

Funding

German Network for Bioinformatics Infrastructure 031A532B
6 · The paper itself

Abstract

motivationPangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time.

resultsTo overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core's best practices. Leveraging biocontainers ensures portability and seamless deployment in High-Performance Computing (HPC) environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 Escherichia coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. AVAILABILITY AND IMPLEMENTATION: nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/docs/usage.

Indexed as

Escherichia coliSoftwareAlgorithmsGenome, BacterialGenome, HumanGenomicsHaplotypesHumans

Identifiers

PMID39400346
PMCPMC11568064

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.