Published August 3, 2026
| Version 2.1.1
Software
Open
BIOSZEN
Authors/Creators
Description
BIOSZEN is an app for data analysis and visualization from an Excel file. It can generate boxplot, barplot, violin plot, stacked plots, heatmaps, and correlation plots between parameters. It includes metadata-based reproducibility, normalized-data workflows, downloadable graphics and workbooks, normality tests such as Shapiro-Wilk, Kolmogorov-Smirnov, and Anderson-Darling, and significance tests such as ANOVA, Kruskal-Wallis, t-test, and Wilcoxon. It also extracts microbial growth curve parameters (uMax, max_percap_time, doub_time, lag_time, ODmax, max_time, AUC, OD0).
Notes
Version 2.1.1 improves application stability, startup reliability, dependency management, data compatibility, and overall robustness. It also introduces vector-based PowerPoint (.pptx) export for individual plots and multi-plot composition panels. Exported figures remain editable in PowerPoint, allowing users to modify text, fonts, colors, axes, legends, annotations, graphical elements, and layouts directly.
Technical info
BIOSZEN is now available through R-universe, making it easier to install and update the package directly from R. The application can also be launched conveniently from the RStudio Addins menu, allowing users to access BIOSZEN without manually entering commands.
To install BIOSZEN, run:
install.packages(
"BIOSZEN",
repos = c(
"https://bioszen.r-universe.dev",
"https://cloud.r-project.org"
)
)After installation, launch the application with:
BIOSZEN::BIOSZEN()Files
README.md
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Additional details
Related works
- Is cited by
- Journal article: 10.1002/jimd.70214 (DOI)
- Preprint: 10.21203/rs.3.rs-10451293/v1 (DOI)
- Is derived from
- Software: https://github.com/bioszen/BIOSZEN (URL)
- Is documented by
- Software: https://bioszen.r-universe.dev/BIOSZEN (URL)
- Is referenced by
- Other: https://bio.tools/bioszen (URL)
Software
- Repository URL
- https://github.com/bioszen/BIOSZEN
- Programming language
- R
- Development Status
- Active
References
- R Core Team (2026). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://doi.org/10.32614/R.manuals
- Blazanin, M. (2024). gcplyr: an R package for microbial growth curve data analysis. BMC Bioinformatics, 25, 232. https://doi.org/10.1186/s12859-024-05817-3
- Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4. https://ggplot2.tidyverse.org
- Kassambara, A. (2025). rstatix: Pipe-Friendly Framework for Basic Statistical Tests. R package version 0.7.3. https://doi.org/10.32614/CRAN.package.rstatix
- Gross, J., & Ligges, U. (2015). nortest: Tests for Normality. R package version 1.0-4. https://doi.org/10.32614/CRAN.package.nortest
- Pohlert, T. (2024). PMCMRplus: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended. R package version 1.9.12. https://doi.org/10.32614/CRAN.package.PMCMRplus
- Signorell, A. (2025). DescTools: Tools for Descriptive Statistics. R package version 0.99.60. https://doi.org/10.32614/CRAN.package.DescTools