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VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants

SUMMARY: 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...

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Autores principales: Chen, Tao, Tang, Chengcheng, Zheng, Wei, Qian, Yanan, Chen, Min, Zou, Qingjian, Jin, Yinge, Wang, Kepin, Zhou, Xiaoqing, Gou, Shixue, Lai, Liangxue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493178/
https://www.ncbi.nlm.nih.gov/pubmed/37701675
http://dx.doi.org/10.1093/bioadv/vbad107
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author Chen, Tao
Tang, Chengcheng
Zheng, Wei
Qian, Yanan
Chen, Min
Zou, Qingjian
Jin, Yinge
Wang, Kepin
Zhou, Xiaoqing
Gou, Shixue
Lai, Liangxue
author_facet Chen, Tao
Tang, Chengcheng
Zheng, Wei
Qian, Yanan
Chen, Min
Zou, Qingjian
Jin, Yinge
Wang, Kepin
Zhou, Xiaoqing
Gou, Shixue
Lai, Liangxue
author_sort Chen, Tao
collection PubMed
description SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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.
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spelling pubmed-104931782023-09-11 VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants Chen, Tao Tang, Chengcheng Zheng, Wei Qian, Yanan Chen, Min Zou, Qingjian Jin, Yinge Wang, Kepin Zhou, Xiaoqing Gou, Shixue Lai, Liangxue Bioinform Adv Application Note SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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. Oxford University Press 2023-08-26 /pmc/articles/PMC10493178/ /pubmed/37701675 http://dx.doi.org/10.1093/bioadv/vbad107 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Application Note
Chen, Tao
Tang, Chengcheng
Zheng, Wei
Qian, Yanan
Chen, Min
Zou, Qingjian
Jin, Yinge
Wang, Kepin
Zhou, Xiaoqing
Gou, Shixue
Lai, Liangxue
VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title_full VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title_fullStr VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title_full_unstemmed VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title_short VCFshiny: an R/Shiny application for interactively analyzing and visualizing genetic variants
title_sort vcfshiny: an r/shiny application for interactively analyzing and visualizing genetic variants
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493178/
https://www.ncbi.nlm.nih.gov/pubmed/37701675
http://dx.doi.org/10.1093/bioadv/vbad107
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