Evidence map›Paper›PMID 39347649›Full record

ArticleGigaScience2024

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation.

Lara Fuhrmann, Kim Philipp Jablonski, Ivan Topolsky, Aashil A Batavia, Nico Borgsmüller, Pelin Icer Baykal, Matteo Carrara, Chaoran Chen, Arthur Dondi, Monica Dragan and 9 more

Abstract read
In one paragraph

Article in GigaScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

19 authors.

Lara FuhrmannDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0001-6405-0654
Kim Philipp JablonskiDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-4166-4343
Ivan TopolskyDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-7561-0810
Aashil A BataviaDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-5201-5816
Nico BorgsmüllerDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0003-4073-3877
Pelin Icer BaykalDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-9542-5292
Matteo CarraraSIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.ORCID 0000-0002-8559-8296
Chaoran ChenDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-8763-2937
Arthur DondiDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0003-3234-2550
Monica DraganDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-7719-5892
David DreifussDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-5827-5387
Anika JohnDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0009-0000-0902-2183
Benjamin LangerDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.
Michal OkoniewskiScientific IT Services, ETH Zurich, Zurich 8092, Switzerland.ORCID 0000-0003-4722-4506
Louis du PlessisDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0003-0352-6289
Uwe SchmittScientific IT Services, ETH Zurich, Zurich 8092, Switzerland.ORCID 0000-0002-4658-0616
Franziska SingerNEXUS Personalized Health Technologies, ETH Zurich, Basel 4058, Switzerland.ORCID 0000-0002-6017-1595
Tanja StadlerDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0001-6431-535X
Niko BeerenwinkelDepartment of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland.ORCID 0000-0002-0573-6119

Funding

Horizon 2020 Framework Programme 955974
6 · The paper itself

Abstract

The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, scaling to large sample sizes, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting 2 large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

Indexed as

Genetic VariationGenome, ViralHigh-Throughput Nucleotide SequencingSoftwareComputational BiologyGenomicsHumansVirusesbenchmarkglobal haplotype reconstructionnext-generation sequencingNGS data processingsustainable data analysis workflowviral genetic diversity

Identifiers

PMID39347649
PMCPMC11440432

What OpenQuestion holds

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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.