{"title":"EasyOmics:用于群体规模 omics 数据关联、整合和可视化的图形界面。","authors":"Yu Han, Qiao Du, Yifei Dai, Shaobo Gu, Mengyu Lei, Wei Liu, Wenjia Zhang, Mingjia Zhu, Landi Feng, Huan Si, Jianquan Liu, Yanjun Zan","doi":"10.1016/j.xplc.2025.101293","DOIUrl":null,"url":null,"abstract":"<p><p>The rapid growth of population-scale whole genome resequencing, RNA sequencing, bisulfate sequencing, metabolomics and proteomic profiling has led quantitative genetics into a big omics data era. Performing omics data association analysis, such as genome, transcriptome, proteome and methylome wide association analysis, and integrative analysis on multiple omics datasets requires various bioinformatics tools that rely on advanced programming skills and command-line tools, which are challenging for wet-lab biologists. Here, we present EasyOmics a stand-alone R Shiny application with a user-friendly interface for wet-lab biologists to perform population-scale omics data association, integration and visualization. The toolkit incorporates multiple functions designed to meet the increasing demand for population-scale omics data analyses, ranging from data quality control, heritability estimation, genome-wide association analysis, conditional association analysis, omics quantitative trait locus mapping, omics-wide association analysis, omics data integration and visualization etc. A wide range of publication quality graphs can be prepared in EasyOmics with point-and-click. EasyOmics is a platform-independent software that can be run under all operating systems with a docker container for quick installation. It is freely available to non-commercial users at docker hub https://hub.docker.com/r/yuhan2000/easyomics.</p>","PeriodicalId":52373,"journal":{"name":"Plant Communications","volume":" ","pages":"101293"},"PeriodicalIF":9.4000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"EasyOmics: A graphical interface for population-scale omics data association, integration and visualization.\",\"authors\":\"Yu Han, Qiao Du, Yifei Dai, Shaobo Gu, Mengyu Lei, Wei Liu, Wenjia Zhang, Mingjia Zhu, Landi Feng, Huan Si, Jianquan Liu, Yanjun Zan\",\"doi\":\"10.1016/j.xplc.2025.101293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The rapid growth of population-scale whole genome resequencing, RNA sequencing, bisulfate sequencing, metabolomics and proteomic profiling has led quantitative genetics into a big omics data era. Performing omics data association analysis, such as genome, transcriptome, proteome and methylome wide association analysis, and integrative analysis on multiple omics datasets requires various bioinformatics tools that rely on advanced programming skills and command-line tools, which are challenging for wet-lab biologists. Here, we present EasyOmics a stand-alone R Shiny application with a user-friendly interface for wet-lab biologists to perform population-scale omics data association, integration and visualization. The toolkit incorporates multiple functions designed to meet the increasing demand for population-scale omics data analyses, ranging from data quality control, heritability estimation, genome-wide association analysis, conditional association analysis, omics quantitative trait locus mapping, omics-wide association analysis, omics data integration and visualization etc. A wide range of publication quality graphs can be prepared in EasyOmics with point-and-click. EasyOmics is a platform-independent software that can be run under all operating systems with a docker container for quick installation. It is freely available to non-commercial users at docker hub https://hub.docker.com/r/yuhan2000/easyomics.</p>\",\"PeriodicalId\":52373,\"journal\":{\"name\":\"Plant Communications\",\"volume\":\" \",\"pages\":\"101293\"},\"PeriodicalIF\":9.4000,\"publicationDate\":\"2025-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plant Communications\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xplc.2025.101293\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Communications","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.xplc.2025.101293","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
EasyOmics: A graphical interface for population-scale omics data association, integration and visualization.
The rapid growth of population-scale whole genome resequencing, RNA sequencing, bisulfate sequencing, metabolomics and proteomic profiling has led quantitative genetics into a big omics data era. Performing omics data association analysis, such as genome, transcriptome, proteome and methylome wide association analysis, and integrative analysis on multiple omics datasets requires various bioinformatics tools that rely on advanced programming skills and command-line tools, which are challenging for wet-lab biologists. Here, we present EasyOmics a stand-alone R Shiny application with a user-friendly interface for wet-lab biologists to perform population-scale omics data association, integration and visualization. The toolkit incorporates multiple functions designed to meet the increasing demand for population-scale omics data analyses, ranging from data quality control, heritability estimation, genome-wide association analysis, conditional association analysis, omics quantitative trait locus mapping, omics-wide association analysis, omics data integration and visualization etc. A wide range of publication quality graphs can be prepared in EasyOmics with point-and-click. EasyOmics is a platform-independent software that can be run under all operating systems with a docker container for quick installation. It is freely available to non-commercial users at docker hub https://hub.docker.com/r/yuhan2000/easyomics.
期刊介绍:
Plant Communications is an open access publishing platform that supports the global plant science community. It publishes original research, review articles, technical advances, and research resources in various areas of plant sciences. The scope of topics includes evolution, ecology, physiology, biochemistry, development, reproduction, metabolism, molecular and cellular biology, genetics, genomics, environmental interactions, biotechnology, breeding of higher and lower plants, and their interactions with other organisms. The goal of Plant Communications is to provide a high-quality platform for the dissemination of plant science research.