Nguyen Tran Nam Tien, Nguyen Quang Thu, Dong Hyun Kim, Seongoh Park, Nguyen Phuoc Long
{"title":"EasyPubPlot: A Shiny Web Application for Rapid Omics Data Exploration and Visualization.","authors":"Nguyen Tran Nam Tien, Nguyen Quang Thu, Dong Hyun Kim, Seongoh Park, Nguyen Phuoc Long","doi":"10.1021/acs.jproteome.4c01068","DOIUrl":null,"url":null,"abstract":"<p><p>Computational toolkits for data exploration and visualization from widely used omics platforms often lack flexibility and customization. While many tools generate standardized output, advanced programming skills are necessary to create high-quality visualizations. Therefore, user-friendly tools that simplify this crucial, yet time-consuming, step are essential. We developed EasyPubPlot (Easy Publishable Plotting), a straightforward, easy-to-use, no-coding, user experience-oriented, open-source, and shiny web application along with its associated R package to streamline data exploration and visualization for functional omics-empowered research. EasyPubPlot generates publishable scores plots, volcano plots, heatmaps, box plots, dot plots, and bubble plots with minimal necessary steps. The tool was designed to guide new users to accurate and efficient navigation. Step-by-step tutorials for each type of plot are also provided. Herein, we demonstrated EasyPubPlot's competent functionality and versatility by showcasing metabolomics, proteomics, and transcriptomics data. Collectively, EasyPubPlot reduces the gap between data analysis and stunning visualization, thereby diminishing friction and focusing on science. The app can be downloaded and installed locally (https://github.com/Pharmaco-OmicsLab/EasyPubPlot) or used through a web application (https://pharmaco-omicslab.shinyapps.io/EasyPubPlot).</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-03-07","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.4c01068","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
Computational toolkits for data exploration and visualization from widely used omics platforms often lack flexibility and customization. While many tools generate standardized output, advanced programming skills are necessary to create high-quality visualizations. Therefore, user-friendly tools that simplify this crucial, yet time-consuming, step are essential. We developed EasyPubPlot (Easy Publishable Plotting), a straightforward, easy-to-use, no-coding, user experience-oriented, open-source, and shiny web application along with its associated R package to streamline data exploration and visualization for functional omics-empowered research. EasyPubPlot generates publishable scores plots, volcano plots, heatmaps, box plots, dot plots, and bubble plots with minimal necessary steps. The tool was designed to guide new users to accurate and efficient navigation. Step-by-step tutorials for each type of plot are also provided. Herein, we demonstrated EasyPubPlot's competent functionality and versatility by showcasing metabolomics, proteomics, and transcriptomics data. Collectively, EasyPubPlot reduces the gap between data analysis and stunning visualization, thereby diminishing friction and focusing on science. The app can be downloaded and installed locally (https://github.com/Pharmaco-OmicsLab/EasyPubPlot) or used through a web application (https://pharmaco-omicslab.shinyapps.io/EasyPubPlot).
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".