SimpleViz: A user-friendly, web-based tool for publication-ready data visualization in bioinformatics

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.

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Publication Details

Journal
Molecules and Cells
Published
2025-05-08
DOI
https://doi.org/10.1016/j.mocell.2025.100222
Citations
1
Primary Topic
Genetics, Bioinformatics, and Biomedical Research
Type
article
Field-Weighted Citation Impact
0.81
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article

SimpleViz: A user-friendly, web-based tool for publication-ready data visualization in bioinformatics

Minjung Kwon, Jaehun Bang, Yong‐Joon Cho, Kwang Jun Lee et al.
1 citations
Molecules and Cells
Genetics, Bioinformatics, and Biomedical Research
0.81
article

SimpleViz: A user-friendly, web-based tool for publication-ready data visualization in bioinformatics

Minjung Kwon, Jaehun Bang, Yong‐Joon Cho, Kwang Jun Lee, Eun-Jin Lee, Juhee Kim, B. Oh
article en
1 citations

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.

Molecules and CellsVol. 48(7)
Kangwon National University (KR), Korea University (KR), Korea National Institute of Health (KR)
Openalex Percentile: Top 28%
Genetics, Bioinformatics, and Biomedical Research
0.81
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