下一代测序会生成通常以变异调用格式（VCF）文件记录的变异。然而，对于缺乏生物信息学和编程专业知识的研究人员来说，全面检查VCF文件中的变异信息可能面临重大挑战。为了解决这个问题，我们引入了VCFshiny，这是一个R包，具有用户友好的Web界面，可实现对存储在VCF文件中的变异信息进行交互式注释、解释和可视化。VCFshiny提供两种注释方法，Annovar和VariantAnnotation，用于添加注释，例如基因或功能影响。注释后的VCF文件被视为可接受的输入，以便进行变异信息的汇总和可视化。这包括变异的总数、样本复制品间的重叠、单个核苷酸的碱基改变、插入和删除（indels）的长度分布、高频突变基因、基因组中的变异分布和基因组特征、癌症驱动基因中的变异以及癌症突变特征。VCFshiny通过提供交互式Web界面来增强VCF文件的可理解性，用于分析和可视化。源代码在https://github.com/123xiaochen/VCFshiny下以MIT开源许可证公开，文档在https://123xiaochen.github.io/VCFshiny提供。© 作者2023年发表于牛津大学出版社。

Next-generation sequencing generates variants that are typically documented in variant call format (VCF) files. However, comprehensively examining variant information from VCF files can pose a significant challenge for researchers lacking bioinformatics and programming expertise. To address this issue, we introduce VCFshiny, an R package that features a user-friendly web interface enabling interactive annotation, interpretation, and visualization of variant information stored in VCF files. VCFshiny offers two annotation methods, Annovar and VariantAnnotation, to add annotations such as genes or functional impact. Annotated VCF files are deemed acceptable inputs for the purpose of summarizing and visualizing variant information. This includes the total number of variants, overlaps across sample replicates, base alterations of single nucleotides, length distributions of insertions and deletions (indels), high-frequency mutated genes, variant distribution in the genome and of genome features, variants in cancer driver genes, and cancer mutational signatures. VCFshiny serves to enhance the intelligibility of VCF files by offering an interactive web interface for analysis and visualization.The source code is available under an MIT open source license at https://github.com/123xiaochen/VCFshiny with documentation at https://123xiaochen.github.io/VCFshiny.© The Author(s) 2023. Published by Oxford University Press.