V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation
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Author / Producer
Date
2024
Publication Type
Journal Article
ETH Bibliography
yes
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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.
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published
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Journal / series
Volume
13
Pages / Article No.
Publisher
Oxford University Press
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Software
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Subject
next-generation sequencing; NGS data processing; sustainable data analysis workflow; benchmark; global haplotype reconstruction; viral genetic diversity
Organisational unit
02892 - NEXUS Personalized Health / NEXUS Personalized Health
09490 - Stadler, Tanja / Stadler, Tanja
03790 - Beerenwinkel, Niko / Beerenwinkel, Niko
Notes
Funding
955974 - Understanding (harmful) virus-host interactions by linking virology and bioinformatics (EC)
Related publications and datasets
Is new version of: https://doi.org/10.3929/ethz-b-000653083