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Heumos, S.* ; Heuer, M.L.* ; Hanssen, F.* ; Heumos, L. ; Guarracino, A.* ; Heringer, P.* ; Ehmele, P. ; Prins, P.* ; Garrison, E.* ; Nahnsen, S.*

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

Bioinformatics 40:btae609 (2024)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
MOTIVATION: Pangenome 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. RESULTS: To 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 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 E. coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. AVAILABILITY: 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/1.1.2/docs/usage. SUPPLEMENTARY: Supplementary data are available at Bioinformatics online.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
e-ISSN 1367-4811
Zeitschrift Bioinformatics
Quellenangaben Band: 40, Heft: 11, Seiten: , Artikelnummer: btae609 Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of Lung Health and Immunity (LHI)
POF Topic(s) 30205 - Bioengineering and Digital Health
30202 - Environmental Health
Forschungsfeld(er) Enabling and Novel Technologies
Lung Research
PSP-Element(e) G-503800-001
G-501693-001
Förderungen CITG
BMBF
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy
NIH/NIDA
NIH/NIGMS
NSF PPoSS Award
Central Innovation Programme (ZIM) for SMEs of the Federal Ministry for Economic Affairs and Energy of Germany
DOI 10.1093/bioinformatics/btae609
WOS ID 001374659300001
Scopus ID 85209647392
PubMed ID 39400346
Erfassungsdatum 2024-11-11
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