bioviz-kit 0.3.2

Framework-agnostic plotting utilities for biological and clinical data visualization

bioviz-kit

Framework-agnostic visualization library for publication-ready clinical and biological data plots.

Features

• Publication-ready styling – Clean, professional visualizations out of the box
• Framework-agnostic – Works with any data pipeline or analysis framework
• Customizable configurations – Extensive theming and layout options
• Clinical & bioinformatics focused – Specialized plot types for common analyses

Installation

bioviz-kit

Framework-agnostic visualization library for publication-ready clinical and biological data plots.

Features

• Publication-ready styling – Clean, professional visualizations out of the box
• Framework-agnostic – Works with any data pipeline or analysis framework
• Customizable configurations – Extensive theming and layout options
• Clinical & bioinformatics focused – Specialized plot types for common analyses

Installation

Install from PyPI:

pip install bioviz-kit

Or install in development mode:

pip install -e .

Requirements

• Python 3.11+
• pandas
• matplotlib
• seaborn
• adjustText

Usage

from bioviz import lineplot, oncoplot

# Generate styled plots with minimal configuration
fig = lineplot.generate_styled_lineplot(df, config)
fig = oncoplot.generate_styled_oncoplot(df, config)

See examples/ for complete usage examples.

Examples

• Example files live in the examples/ directory. Recommended practices:
  • Keep runnable .py scripts for quick CLI usage and reproducible examples.
  • Provide companion .ipynb notebooks for narrative tutorials and figures. Convert with jupytext or nbconvert if needed:

pip install jupytext
jupytext --to notebook examples/my_example.py -o examples/my_example.ipynb

- Name files with short, descriptive snake_case (optionally numeric prefixes for ordered tutorials, e.g. `01_quickstart.ipynb`).
- Add a short header comment or top-level README in `examples/` describing each example's purpose and required inputs.

Documentation and ReadTheDocs

TBD

Design Philosophy

• Lightweight DefaultStyle provided; easily extended with custom themes

Licensing

• bioviz-kit is released under the MIT License © 2025 Victoria Cheung.

Thanks

This package was spun out of internal tooling I wrote at Revolution Medicines. Many thanks to the team there for allowing the code to be open sourced.