V-pipe

V-pipe analyzes NGS data from intra-host viral populations to generate high-quality read alignments, call low-frequency single-nucleotide variants, and infer viral haplotypes for studies of genetic diversity, transmission, and genomic surveillance.


Key Features:

  • Quality Control and Read Mapping: Integrates quality control and read mapping for NGS reads using configurable aligners and statistical models.
  • ngshmmalign (Novel Alignment Methodology): Implements profile hidden Markov models tailored to small, highly diverse viral genomes to improve alignment quality.
  • Low-Frequency Mutation Calling and Haplotype Inference: Detects low-frequency mutations and performs viral haplotype inference to characterize intra-host genetic diversity.
  • Benchmarking Functionality: Provides a standardized benchmarking environment to compare read aligners (Bowtie 2, BWA MEM, ngshmmalign) and variant callers (LoFreq, ShoRAH) for single-nucleotide variant calling performance.
  • Modular Implementation: Uses a modular architecture that enables substitution and configuration of pipeline components and benchmarking setups.

Scientific Applications:

  • Genomic Surveillance: Analyzes whole genome sequences to monitor variants such as SARS-CoV-2 B.1.1.7 and to estimate transmission fitness advantages and effective reproductive numbers.
  • One-Health Context Studies: Supports investigation of zoonotic transmissions, including SARS-CoV-2 infections in domestic cats.
  • Quantifying Genetic Diversity: Measures within-host genetic diversity to inform studies of disease progression, treatment outcomes, drug resistance, cell tropism, and transmission risks.

Methodology:

Performs quality control and read mapping; uses ngshmmalign (profile hidden Markov models) and supports Bowtie 2 and BWA MEM; applies variant callers LoFreq and ShoRAH; conducts haplotype inference and benchmarking of configurations.

Topics

Collections

Details

License:
Apache-2.0
Maturity:
Mature
Cost:
Free of charge
Tool Type:
command-line tool, workflow
Operating Systems:
Linux, Mac
Programming Languages:
Shell, Python
Added:
2/2/2018
Last Updated:
11/24/2024

Operations

Publications

Carlisle LA, Turk T, Kusejko K, Metzner KJ, Leemann C, Schenkel CD, Bachmann N, Posada S, Beerenwinkel N, Böni J, Yerly S, Klimkait T, Perreau M, Braun DL, Rauch A, Calmy A, Cavassini M, Battegay M, Vernazza P, Bernasconi E, Günthard HF, Kouyos RD, Anagnostopoulos A, Battegay M, Bernasconi E, Böni J, Braun DL, Bucher HC, Calmy A, Cavassini M, Ciuffi A, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Günthard HF, Haerry D, Hasse B, Hirsch HH, Hoffmann M, Hösli I, Huber M, Kahlert C, Kaiser L, Keiser O, Klimkait T, Kouyos RD, Kovari H, Ledergerber B, Martinetti G, Martinez de Tejada B, Marzolini C, Metzner KJ, Müller N, Nicca D, Paioni P, Pantaleo G, Perreau M, Rauch A, Rudin C, Scherrer AU, Schmid P, Speck R, Stöckle M, Tarr P, Trkola A, Vernazza P, Wandeler G, Weber R, Yerly S. Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection. The Journal of Infectious Diseases. 2019;220(2):254-265. doi:10.1093/infdis/jiz094. PMID:30835266.

PMID: 30835266
Funding: - Swiss National Science Foundation: 148522, 179571, BSSGI0_155851

Posada-Céspedes S, Seifert D, Topolsky I, Jablonski KP, Metzner KJ, Beerenwinkel N. V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data. Bioinformatics. 2021;37(12):1673-1680. doi:10.1093/bioinformatics/btab015. PMID:33471068. PMCID:PMC8289377.

Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A, Baumbach J, Beerenwinkel N, Brandt C, Cacciabue M, Chuguransky S, Drechsel O, Finn RD, Fritz A, Fuchs S, Hattab G, Hauschild A, Heider D, Hoffmann M, Hölzer M, Hoops S, Kaderali L, Kalvari I, von Kleist M, Kmiecinski R, Kühnert D, Lasso G, Libin P, List M, Löchel HF, Martin MJ, Martin R, Matschinske J, McHardy AC, Mendes P, Mistry J, Navratil V, Nawrocki E, O'Toole ÁN, Palacios-Ontiveros N, Petrov AI, Rangel-Piñeros G, Redaschi N, Reimering S, Reinert K, Reyes A, Richardson L, Robertson DL, Sadegh S, Singer JB, Theys K, Upton C, Welzel M, Williams L, Marz M. Computational Strategies to Combat COVID-19: Useful Tools to Accelerate SARS-CoV-2 and Coronavirus Research. Unknown Journal. 2020. doi:10.20944/preprints202005.0376.v1.

Posada-Cespedes S, Seifert D, Beerenwinkel N. Recent advances in inferring viral diversity from high-throughput sequencing data. Virus Research. 2017;239:17-32. doi:10.1016/j.virusres.2016.09.016. PMID:27693290.

Ibrahim B, Arkhipova K, Andeweg A, Posada-Céspedes S, Enault F, Gruber A, Koonin E, Kupczok A, Lemey P, McHardy A, McMahon D, Pickett B, Robertson D, Scheuermann R, Zhernakova A, Zwart M, Schönhuth A, Dutilh B, Marz M. Bioinformatics Meets Virology: The European Virus Bioinformatics Center’s Second Annual Meeting. Viruses. 2018;10(5):256. doi:10.3390/v10050256. PMID:29757994. PMCID:PMC5977249.

Alm E, Broberg EK, Connor T, Hodcroft EB, Komissarov AB, Maurer-Stroh S, Melidou A, Neher RA, O’Toole Á, Pereyaslov D. Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020. Eurosurveillance. 2020;25(32). doi:10.2807/1560-7917.es.2020.25.32.2001410. PMID:32794443. PMCID:PMC7427299.

Kuipers J, Batavia AA, Jablonski KP, Bayer F, Borgsmüller N, Dondi A, Drăgan M, Ferreira P, Jahn K, Lamberti L, Pirkl M, Posada-Céspedes S, Topolsky I, Nissen I, Santacroce N, Burcklen E, Schär T, Capece V, Beckmann C, Kobel O, Noppen C, Redondo M, Nadeau S, Seidel S, Santamaria de Souza N, Beisel C, Stadler T, Beerenwinkel N. Within-patient genetic diversity of SARS-CoV-2. Unknown Journal. 2020. doi:10.1101/2020.10.12.335919.

Nadeau S, Beckmann C, Topolsky I, Vaughan T, Hodcroft E, Schär T, Nissen I, Santacroce N, Burcklen E, Ferreira P, Jablonski KP, Posada-Céspedes S, Capece V, Seidel S, de Souza NS, Martinez-Gomez JM, Cheng P, Bosshard PP, Levesque MP, Kufner V, Schmutz S, Zaheri M, Huber M, Trkola A, Cordey S, Laubscher F, Gonçalves AR, Leuzinger K, Stange M, Mari A, Roloff T, Seth-Smith H, Hirsch HH, Egli A, Redondo M, Kobel O, Noppen C, Beerenwinkel N, Neher RA, Beisel C, Stadler T. Quantifying SARS-CoV-2 spread in Switzerland based on genomic sequencing data. Unknown Journal. 2020. doi:10.1101/2020.10.14.20212621.

Jahn K, Dreifuss D, Topolsky I, Kull A, Ganesanandamoorthy P, Fernandez-Cassi X, Bänziger C, Devaux AJ, Stachler E, Caduff L, Cariti F, Corzón AT, Fuhrmann L, Chen C, Jablonski KP, Nadeau S, Feldkamp M, Beisel C, Aquino C, Stadler T, Ort C, Kohn T, Julian TR, Beerenwinkel N. Detection and surveillance of SARS-CoV-2 genomic variants in wastewater. Unknown Journal. 2021. doi:10.1101/2021.01.08.21249379.

Chen C, Nadeau SA, Topolsky I, Manceau M, Huisman JS, Jablonski KP, Fuhrmann L, Dreifuss D, Jahn K, Beckmann C, Redondo M, Noppen C, Risch L, Risch M, Wohlwend N, Kas S, Bodmer T, Roloff T, Stange M, Egli A, Eckerle I, Kaiser L, Denes R, Feldkamp M, Nissen I, Santacroce N, Burcklen E, Aquino C, de Gouvea AC, Moccia MD, Grüter S, Sykes T, Opitz L, White G, Neff L, Popovic D, Patrignani A, Tracy J, Schlapbach R, Dermitzakis ET, Harshman K, Xenarios I, Pegeot H, Cerutti L, Penet D, Blin A, Elies M, Althaus CL, Beisel C, Beerenwinkel N, Ackermann M, Stadler T. Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland. Epidemics. 2021;37:100480. doi:10.1016/j.epidem.2021.100480. PMID:34488035. PMCID:PMC8452947.

Klaus J, Meli M, Willi B, Nadeau S, Beisel C, Stadler T, Egberink H, Zhao S, Lutz H, Riond B, Rösinger N, Stalder H, Renzullo S, Hofmann-Lehmann R. Detection and Genome Sequencing of SARS-CoV-2 in a Domestic Cat with Respiratory Signs in Switzerland. Viruses. 2021;13(3):496. doi:10.3390/v13030496. PMID:33802899. PMCID:PMC8002591.

PMID: 33802899
PMCID: PMC8002591
Funding: - Universität Zürich: G-53420-01-01 - Bundesamt für Lebensmittelsicherheit und Veterinärwesen: 0714001572, 0714001626

Fuhrmann L, Jablonski KP, Beerenwinkel N. Quantitative measures of within-host viral genetic diversity. Current Opinion in Virology. 2021;49:157-163. doi:10.1016/j.coviro.2021.06.002. PMID:34153841.

PMID: 34153841
Funding: - Horizon 2020 Marie Skłodowska-Curie Actions: 955974

Documentation

Training material
https://youtu.be/qHEUVJZsgE4
Video introduction to V-pipe
Training material
https://cbg-ethz.github.io/V-pipe/tutorial/sars-cov2/
Tutorial: how to use V-pipe (specifically for SARS-CoV-2 data).
Training material
https://youtu.be/pIby1UooK94
Webinar: Applying V-pipe to SARS-Coronavirus-2 data

Downloads

Links

Issue tracker
https://github.com/cbg-ethz/V-pipe/issues
(GitHub issue tracker)
Mailing list
https://sympa.ethz.ch/sympa/info/v-pipe-users
(Sympa ETHZ mailing list)
Repository
https://github.com/cbg-ethz/V-pipe
(GitHub repository)
Software catalogue
https://www.expasy.org/resources/v-pipe
(ExPASy - SIB Bioinformatics Resource Portal)
Software catalogue
https://workflowhub.eu/workflows/301
(WorkflowHub)

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