Oh Byeong Seob, Kim Juhee, Kwon Minjeong, Bang Jiwon, Lee Kwang-Jun, Lee Eun-Jin, Cho Yong-Joon
Multidimensional Genomics Research Center, Kangwon National University, Chuncheon, Republic of Korea.
Department of Integrative Molecular and Biomedical Sciences, College of Biomedical Sciences, Kangwon National University, Chuncheon, Republic of Korea.
Mol Cells. 2025 Jul;48(7):100222. doi: 10.1016/j.mocell.2025.100222. Epub 2025 May 8.
Large-scale datasets are central to bioinformatics research, creating a demand for intuitive visualization tools that transform complex data into accessible graphics. Existing visualization software often comes with high costs or requires coding expertise, limiting accessibility for many researchers. To address this gap, we introduce SimpleViz, a free, web-based platform that enables the creation of professional-quality figures without the need for programming skills. SimpleViz offers gene-level analysis of RNA-seq data and core visualization types such as box/violin/dot plots, volcano plots, principal component analysis plots, and heatmaps, with extensive customization options for detailed adjustments and built-in statistical comparisons. Developed on a Shiny interface, SimpleViz simplifies the process of data upload, visualization generation, and customization, ensuring that users can produce tailored visuals suited for publication. With plans for continuous improvement based on user feedback, SimpleViz provides an adaptable, accessible solution that meets evolving data analysis needs in biomedical research.
大规模数据集是生物信息学研究的核心，这就催生了对直观可视化工具的需求，这些工具能将复杂数据转化为易懂的图形。现有的可视化软件通常成本高昂或需要编码专业知识，限制了许多研究人员的使用。为了弥补这一差距，我们推出了SimpleViz，这是一个基于网络的免费平台，无需编程技能就能创建专业水准的图形。SimpleViz提供RNA测序数据的基因水平分析以及核心可视化类型，如箱线图/小提琴图/点图、火山图、主成分分析图和热图，并具有广泛的定制选项，可进行详细调整和内置统计比较。基于Shiny界面开发的SimpleViz简化了数据上传、可视化生成和定制过程，确保用户能够制作出适合发表的定制化视觉效果。基于用户反馈，SimpleViz计划持续改进，提供一个适应性强、易于使用的解决方案，以满足生物医学研究中不断变化的数据分析需求。
