MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Journal of Proteome Research Pub Date : 2025-01-21 DOI:10.1021/acs.jproteome.4c00650
David J Degnan, Daniel M Claborne, Rachel E Richardson, Clayton W Strauch, Evan C Glasscock, Dusan Veličković, Kristin E Burnum-Johnson, Bobbie-Jo M Webb-Robertson, Kelly G Stratton, Lisa M Bramer
{"title":"MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.","authors":"David J Degnan, Daniel M Claborne, Rachel E Richardson, Clayton W Strauch, Evan C Glasscock, Dusan Veličković, Kristin E Burnum-Johnson, Bobbie-Jo M Webb-Robertson, Kelly G Stratton, Lisa M Bramer","doi":"10.1021/acs.jproteome.4c00650","DOIUrl":null,"url":null,"abstract":"<p><p>Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as \"omics\") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.4c00650","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as "omics") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

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
MODE:用于组学数据交互可视化和探索的Web应用程序。
生成转录组学、蛋白质组学、脂质组学和代谢组学(通俗地称为“组学”)数据的研究使研究人员能够通过识别实验条件下生物分子丰度和表达的变化来发现生物标志物或分子靶点,或了解复杂的生物结构和功能。组学数据是多维的,通常使用诸如主成分分析(PCA)之类的汇总技术来识别数据中的高级模式。虽然有用,但这些总结不允许探索组学数据中可能具有生物学相关性的详细模式。使用带有图表的交互式HTML显示使研究人员能够在详细的层面上与组学数据进行交互,但是构建这些显示需要大量的编码专业知识。为了克服这一障碍,我们开发了软件MODE,使用户能够构建自己的交互式HTML显示,以支持科学发现。这些显示很容易共享,不依赖于特定的操作系统,并允许用户通过称为元的分类或数值变量对图进行排序和筛选。MODE允许用户建立和共享这些显示与几个选项的情节设计和元选择。MODE web应用程序及其功能被展示,然后在叶片损伤研究的脂质组学数据上进行演示。
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
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
期刊最新文献
MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics. Cysteine-Directed Isobaric Labeling Combined with GeLC-FAIMS-MS for Quantitative Top-Down Proteomics. OpenMS WebApps: Building User-Friendly Solutions for MS Analysis. Proteomic Analysis of Unicellular Cyanobacterium Crocosphaera subtropica ATCC 51142 under Extended Light or Dark Growth. Investigation of Immunoreactivity Profiles and Epitope Landscape in Divergent COVID-19 Trajectories and SARS-CoV-2 Variants.
×
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