ArticleBioinformatics (Oxford, England)2022
ViReMaShiny: an interactive application for analysis of viral recombination data.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- SARS-CoV-2 EndoU-ribonuclease regulates RNA recombination and impacts viral fitness.Nature communications · 2025Article
- Review
- Characterization of SARS-CoV-2 intrahost genetic evolution in vaccinated and non-vaccinated patients from the Kenyan population.Journal of virology · 2025Article
- Genomic characteristics of human respiratory syncytial virus from children in China during 2017-2020.Archives of virology · 2024Article
- ViReMa: a virus recombination mapper of next-generation sequencing data characterizes diverse recombinant viral nucleic acids.GigaScience · 2023Article
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Authors and funding
2 authors.
Funding
Abstract
motivationRecombination is an essential driver of virus evolution and adaption, giving rise to new chimeric viruses, structural variants, sub-genomic RNAs and defective RNAs. Next-generation sequencing (NGS) of virus samples, either from experimental or clinical settings, has revealed a complex distribution of recombination events that contributes to intrahost diversity. We and others have previously developed alignment tools to discover and map these diverse recombination events in NGS data. However, there is no standard for data visualization to contextualize events of interest, and downstream analysis often requires bespoke coding.
resultsWe present ViReMaShiny, a web-based application built using the R Shiny framework to allow interactive exploration and point-and-click visualization of viral recombination data provided in BED format generated by computational pipelines such as ViReMa (Viral-Recombination-Mapper). AVAILABILITY AND IMPLEMENTATION: The application is hosted at https://routhlab.shinyapps.io/ViReMaShiny/ with associated documentation at https://jayeung12.github.io/. Code is available at https://github.com/routhlab/ViReMaShiny. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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