Treffer: GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis.
Title:
GeNePi: a graphics processing unit enhanced next-generation bioinformatics pipeline for whole-genome sequencing analysis.
Authors:
Marangoni S; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Furia F; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Charrance D; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Fant A; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Di Dio S; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Trova S; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Spirito G; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Musacchia F; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Coppe A; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Gustincich S; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Human Technology, Via Morego 30, 16152 Genova, Italy., Vecchi M; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Non-coding RNAs and RNA-based therapeutics, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Landuzzi F; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy., Cavalli A; Computational and Chemical Biology, Italian Institute of Technology (IIT), CMP3VdA, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Clinical and Computational Genomics, Via Lavoratori - Vittime del Col du Mont 28, 11100 Aosta, Italy.; Computational and Chemical Biology, Italian Institute of Technology (IIT), Center for Human Technology, Via Morego 30, 16152 Genova, Italy.; Centre Européen de Calcul Atomique et Moléculaire (CECAM), Ecole Polytechnique Fédérale de Lausanne, 1015 Lousanne, Switzerland.
Source:
Briefings in bioinformatics [Brief Bioinform] 2026 Jan 07; Vol. 27 (1).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 100912837 Publication Model: Print Cited Medium: Internet ISSN: 1477-4054 (Electronic) Linking ISSN: 14675463 NLM ISO Abbreviation: Brief Bioinform Subsets: MEDLINE
Imprint Name(s):
Publication: Oxford : Oxford University Press
Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000-
Original Publication: London ; Birmingham, AL : H. Stewart Publications, [2000-
MeSH Terms:
References:
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F1000Res. 2020 Jan 29;9:63. (PMID: 32269765)
Ann Oncol. 2023 Jan;34(1):33-47. (PMID: 36307055)
Nat Biotechnol. 2020 Mar;38(3):276-278. (PMID: 32055031)
NPJ Parkinsons Dis. 2024 Jul 23;10(1):134. (PMID: 39043730)
Am J Hum Genet. 2017 Feb 2;100(2):267-280. (PMID: 28132688)
Genet Med. 2013 Sep;15(9):733-47. (PMID: 23887774)
Gigascience. 2019 Apr 1;8(4):. (PMID: 31222198)
Genome Res. 2018 Apr;28(4):581-591. (PMID: 29535149)
Proc Natl Acad Sci U S A. 2012 Jul 24;109(30):11920-7. (PMID: 22797899)
Nat Rev Cancer. 2007 Apr;7(4):233-45. (PMID: 17361217)
Nat Biotechnol. 2023 Dec;41(12):1709-1715. (PMID: 37845570)
Nature. 2019 May;569(7757):503-508. (PMID: 31068700)
Bioinformatics. 2012 Sep 15;28(18):i333-i339. (PMID: 22962449)
Nucleic Acids Res. 2019 Jan 8;47(D1):D941-D947. (PMID: 30371878)
Nat Methods. 2009 Sep;6(9):677-81. (PMID: 19668202)
Cell Genom. 2022 May;2(5):. (PMID: 36452119)
Nat Biotechnol. 2020 Nov;38(11):1347-1355. (PMID: 32541955)
Nat Rev Cancer. 2018 Nov;18(11):696-705. (PMID: 30293088)
Genome Res. 2017 Nov;27(11):1916-1929. (PMID: 28855259)
Genome Res. 2010 Sep;20(9):1297-303. (PMID: 20644199)
Genome Biol. 2014 Jun 26;15(6):R84. (PMID: 24970577)
Nat Rev Genet. 2016 Aug 16;17(9):507-22. (PMID: 27528417)
Nucleic Acids Res. 2010 Sep;38(16):e164. (PMID: 20601685)
PLoS Comput Biol. 2016 Apr 21;12(4):e1004873. (PMID: 27100738)
Bioinformatics. 2016 Apr 15;32(8):1220-2. (PMID: 26647377)
Genomics Inform. 2020 Mar;18(1):e10. (PMID: 32224843)
Cell. 2011 Jan 7;144(1):27-40. (PMID: 21215367)
BMC Bioinformatics. 2022 Nov 16;23(1):490. (PMID: 36384437)
Bioinformatics. 2021 Jul 27;37(13):1785-1795. (PMID: 34037688)
Fly (Austin). 2012 Apr-Jun;6(2):80-92. (PMID: 22728672)
Genome Biol. 2022 Dec 27;23(1):271. (PMID: 36575487)
J Cancer Res Clin Oncol. 1987;113(3):253-9. (PMID: 2438285)
Bioinformatics. 2019 Nov 1;35(21):4442-4444. (PMID: 31116378)
Nat Commun. 2017 Jan 24;8:14061. (PMID: 28117401)
Genome Biol. 2019 Nov 20;20(1):246. (PMID: 31747936)
Sci Rep. 2022 Dec 13;12(1):21502. (PMID: 36513709)
Genome Biol. 2021 May 25;22(1):161. (PMID: 34034781)
Curr Genet Med Rep. 2017 Dec;5(4):183-190. (PMID: 29732242)
Sci Data. 2016 Jun 07;3:160025. (PMID: 27271295)
Genome Res. 2011 Jun;21(6):974-84. (PMID: 21324876)
Brief Bioinform. 2019 Sep 27;20(5):1795-1811. (PMID: 30084865)
Cell. 2022 Aug 4;185(16):3041-3055.e25. (PMID: 35917817)
Bioinformatics. 2018 Oct 15;34(20):3572-3574. (PMID: 29669011)
Nat Neurosci. 2022 Apr;25(4):504-514. (PMID: 35288716)
Grant Information:
FESR CUP B68H19005520007 Fondo Europeo di Sviluppo Regionale; ESF CUP B65F19001200009 European Social Fund; ESF+ CUP J51B24000170002 Fondo sociale europeo plus; CUP: J33C22001180001 NextGenerationEU
Contributed Indexing:
Keywords: GPU-accelerated algorithm; Nextflow; Nvidia Clara Parabricks; bioinformatics pipeline; genomic variants; next-generation sequencing; whole-genome sequencing analyses
Entry Date(s):
Date Created: 20260125 Date Completed: 20260125 Latest Revision: 20260128
Update Code:
20260128
PubMed Central ID:
PMC12832024
DOI:
10.1093/bib/bbag001
PMID:
41581117
Database:
MEDLINE
Weitere Informationen
Next-generation sequencing (NGS) has revolutionized genome biology by enabling rapid whole-genome sequencing (WGS) and driving its adoption in research and clinical settings. However, the high-throughput nature of NGS and the complexity of downstream analyses demand robust computational solutions. We present GeNePi, a modular bioinformatic pipeline for efficient and accurate analysis of WGS short paired-end reads. GeNePi is a genomics analysis pipeline built on the Nextflow framework, integrating graphics processing unit (GPU)-accelerated algorithms from NVIDIA Clara Parabricks to enable high-performance variant discovery. The pipeline supports multiple workflow configurations and automates the detection of a broad range of genomic variants, including single-nucleotide variants and small insertions/deletions via GPU-accelerated HaplotypeCaller, copy number variants (CNVs) using CNVkit, and structural variants through a consensus approach combining Manta, Lumpy, BreakDancer, and CNVnator. Additionally, GeNePi incorporates MELT for the detection of mobile element insertions, providing a comprehensive framework for variant discovery and characterization. Benchmarking on synthetic and real datasets demonstrates high accuracy and performance comparable to state-of-the-art tools such as Genome Analysis ToolKit (GATK), establishing GeNePi as a scalable solution for comprehensive WGS analysis. These features make GeNePi a valuable instrument for large-scale analyses in both research and clinical contexts, representing a key step towards the establishment of National Centers for Computational and Technological Medicine.
(© The Author(s) 2026. Published by Oxford University Press.)