Abstract
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.
| Original language | English |
|---|---|
| Article number | 100222 |
| Journal | Molecules and cells |
| Volume | 48 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2025 Jul |
Bibliographical note
Publisher Copyright:© 2025 The Authors
Keywords
- Bar/violin/dot plot
- Data visualization
- Principal component analysis plot
- Volcano plot
ASJC Scopus subject areas
- Molecular Biology
- Cell Biology
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