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Abstract：
Transcriptomic analysis has been widely used in comparative experiments to uncover biological mechanisms in various species. However, a simple tool is still lacking to optimize and integrate the features from multiple R packages. In this study, we developed TOmicsVis (Transcriptomics Visualization) (CRAN: https://cran.r-project.org/package=TOmicsVis, v2.0.0), an R package that provides a comprehensive solution for transcriptomics analysis and visualization. It utilizes 46 R packages to design 40 suitable functions for the streamlined analysis of multigroup transcriptomic projects, which covers six main categories: Sample Statistics, Traits Analysis, Differential Expression, Advanced Analysis, GO and KEGG Enrichment, and Table Operation. TOmicsVis can be performed either locally or online (https://shiny.hiplot.cn/tomicsvis-shiny/), which provides significant convenience for researchers without coding training. These user-friendly visualization functions and built-in analysis capabilities enable researchers to monitor experimental data dynamics promptly and explore transcriptomics data quickly.
摘要：
转录组学分析已广泛用于比较实验，以揭示各种物种的生物学机制。然而,仍然缺乏一个简单的工具来优化和集成来自多个R包的功能。在这项研究中,我们开发了TOmicsVis（转录组学可视化）（CRAN：https：//cran。r-project.org/package=TOmicsVis,v2.0.0),一个R包，为转录组学分析和可视化提供全面的解决方案。它利用46个R包来设计40个合适的函数，用于多组转录组项目的流线型分析，它涵盖六个主要类别：样本统计，性状分析,差异表达,高级分析,GO和KEGG浓缩，和表操作。TOmicsVis可以在本地或在线执行（https://shiny。hiplot。cn/tomicsvis-shiny/)，这为无需编码培训的研究人员提供了极大的便利。这些用户友好的可视化功能和内置的分析功能使研究人员能够及时监测实验数据动态并快速探索转录组学数据。
