DivBrowse-interactive visualization and exploratory data analysis of variant call matrices.

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES GigaScience Pub Date : 2022-12-28 Epub Date: 2023-04-21 DOI:10.1093/gigascience/giad025
Patrick König, Sebastian Beier, Martin Mascher, Nils Stein, Matthias Lange, Uwe Scholz
{"title":"DivBrowse-interactive visualization and exploratory data analysis of variant call matrices.","authors":"Patrick König, Sebastian Beier, Martin Mascher, Nils Stein, Matthias Lange, Uwe Scholz","doi":"10.1093/gigascience/giad025","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community.</p><p><strong>Findings: </strong>We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files.</p><p><strong>Conclusion: </strong>DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":null,"pages":null},"PeriodicalIF":11.8000,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120423/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GigaScience","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/gigascience/giad025","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/4/21 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Background: The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community.

Findings: We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files.

Conclusion: DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
DivBrowse - 变体调用矩阵的交互式可视化和探索性数据分析。
背景:全基因组测序的价格越来越低廉。在此背景下,大规模测序项目正在产生越来越大的物种基因组多样性数据集。因此,越来越多的基因组数据需要便于科学界获取和分析:我们介绍的 DivBrowse 是一种网络应用程序,用于对存储在任何大小的变异调用格式(VCF)文件中的基因组多样性数据进行交互式可视化和探索性分析。通过将 BLAST 作为切入点与交互式数据分析功能(如主成分分析)无缝结合到一个图形用户界面中,DivBrowse 为基因组生物多样性数据集提供了一套新颖独特的探索性数据分析功能。DivBrowse 可以集成到现有的网络应用程序中,支持不同网络应用程序之间的互操作性。内置的交互式主成分分析计算功能允许用户根据基因和外显子等特定遗传元素对种群结构进行特别分析。以 VCF 和通用特征格式 3 文件导出基因组多样性数据的功能支持数据互操作性:DivBrowse 通过交互式计算变异频率和主成分分析等功能,为基因组多样性数据和可选基因注释数据的交互式可视化和分析提供了一种新方法。数据输入使用既定的标准文件格式,支持互操作性和基于既定生物信息学管道数据输出的应用实例的无缝部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
期刊最新文献
IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants An effective strategy for assembling the sex-limited chromosome Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1