FeatureStat Studio

Version: v1.0

FeatureStat Studio is a Python desktop application for grouped statistical analysis, publication-ready plots, histograms, univariate ROC biomarker evaluation, and multi-feature batch visualization.

It is designed for researchers working with biomedical, pathology, imaging, or experimental datasets who need a lightweight graphical workflow for comparing groups, evaluating candidate features or biomarkers, and exporting reproducible analysis outputs.

Main features

• Load CSV, TSV, TXT, Excel files, or pasted spreadsheet data.
• Support for wide-format and long-format datasets.
• Prepare, rename, include/exclude, and style analysis groups.
• Pairwise statistical testing with multiple-comparison correction.
• Individual-value plots, bar plots, box plots, and violin plots.
• Histogram visualization with automatic or manual bin settings.
• Univariate ROC analysis with AUC, cutoff, sensitivity, specificity, and Youden index.
• Multi-feature batch workflow with preview pages and exportable figures.
• Export PNG, SVG, PDF, CSV, JSON parameters, validation reports, and project snapshots.
• Save and load project files for reproducible analysis.

Repository structure

FeatureStat_Studio/
├── FeatureStat_Studio.py              # Main application
├── README.md                          # Project documentation
├── LICENSE                            # MIT license
├── CITATION.cff                       # Citation metadata for GitHub/Zenodo
├── .zenodo.json                       # Zenodo metadata for DOI generation
├── requirements.txt                   # Runtime dependencies
├── requirements-dev.txt               # Build/development dependencies
├── VERSION                            # Current release version
├── CHANGELOG.md                       # Release notes
├── .gitignore                         # Git ignore rules
├── .github/workflows/                 # GitHub Actions builds
├── packaging/pyinstaller/             # PyInstaller spec files
├── scripts/                           # Local build scripts
├── docs/                              # Build and release documentation
├── examples/                          # Example input data
└── assets/icons/                      # Optional icon location

Installation from source

Clone the repository:

git clone https://github.com/Juaco2r/FeatureStat_Studio.git
cd FeatureStat_Studio

Create and activate a virtual environment.

Windows PowerShell:

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
pip install -r requirements.txt

Linux/macOS:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -r requirements.txt

Run the app:

python FeatureStat_Studio.py

Build executable files locally

FeatureStat Studio uses PyInstaller for local executable builds.

Install development/build dependencies first:

pip install -r requirements.txt -r requirements-dev.txt

Then run the script for your operating system.

Windows:

scripts\build_windows.bat

Linux:

bash scripts/build_linux.sh

macOS:

bash scripts/build_macos.sh

The generated files will appear in the dist/ folder.

GitHub Actions executable builds

This repository includes a GitHub Actions workflow at:

.github/workflows/build_executables.yml

When enabled, it builds artifacts for:

• Windows
• Linux
• macOS

You can run it manually from the GitHub Actions tab, or automatically on release tags such as:

git tag v1.0
git push origin v1.0

Example data

An example CSV is included at:

examples/example_long_format.csv

This file can be used to test long-format analysis and the multi-feature workflow.

Citation

If you use FeatureStat Studio in academic work, please cite the software. The repository includes CITATION.cff and .zenodo.json files so that GitHub and Zenodo can generate citation metadata and a DOI after release.

Suggested citation before DOI assignment:

Rodríguez-Rojas, J. (2026). FeatureStat Studio: a desktop application for grouped statistics, ROC biomarker analysis, and multi-feature visualization. Version v1.0. GitHub repository: https://github.com/Juaco2r/FeatureStat_Studio

After archiving the release in Zenodo, replace the repository link with the Zenodo DOI.

Zenodo DOI workflow

1. Create a GitHub release tagged v1.0.
2. Connect the GitHub repository to Zenodo.
3. Enable archiving for the repository in Zenodo.
4. Publish the GitHub release.
5. Zenodo will archive the release and assign a DOI.
6. Update this README and CITATION.cff with the DOI if desired.

See also:

docs/RELEASE_CHECKLIST.md
docs/ZENODO_NOTES.md

License

This project is distributed under the MIT License. See LICENSE for details.