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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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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. |
format | Online Article Text |
id | pubmed-10493178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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