Diceplot: a package for high dimensional categorical data visualization

Note

This project is under active development.

Displaying multidimensional categorical data often poses a challenge in life sciences to get a comprehensive overview of the underlying data. This is not limited to but holds in particular for pathway analysis across multiple conditions. Here we developed a visualization concept to create easy to understand and intuitive representation of such data. We provide the implementation as python as well as R package to ensure easy access and application.

Features

• Visualize Complex Data: Easily create plots for datasets with multiple categorical variables.

• Dice Plot: Create dice plots for datasets with more than two categorical variables.

• Dominoplot: Visualize gene expression data for different cell types and contrasts.

• R and python: Implementations in both R and python to ensure easy access and application.

• Customization: Customize plots with titles, labels, and themes.

• Integration with ggplot2: Leverages the power of ggplot2 for advanced plotting capabilities.

• Interactive Plots: Create interactive plots for easy exploration of your data using the plotly backend.

Diceplot

You can find the R Source Code on github.

• R - Diceplot
  • Requirements and installation
    • Install DicePlot from Files
    • Load the Package
  • Example Usage of DicePlot v0.1.2
    • Loading Necessary Libraries
    • Defining Variables
    • Creating and Plotting Dice Plots
  • Example Usage v0.1.1
  • Dominoplot
    • Example Usage

pyDiceplot

You can find the python Source Code on github.

• Python - pyDiceplot
  • Requirements and installation
    • Using Conda
    • Installation via pip
  • Diceplot
    • Example Usage
  • Dominoplot
    • Example Usage

Contributing

We welcome contributions from the community! If you’d like to contribute:

1. Fork the repository on GitHub.

2. Create a new branch for your feature or bug fix.

3. Submit a pull request with a detailed description of your changes.

Contact

If you have any questions, suggestions, or issues, please open an issue on GitHub.

Citation

If you use this code or the R and Python packages for your own work, please cite Diceplot as:

M. Flotho, P. Flotho, A. Keller, “Diceplot: A package for high dimensional categorical data visualization,” arxiv, 2024. doi:10.48550/arXiv.2410.23897 <https://doi.org/10.48550/arXiv.2410.23897>

BibTeX entry:

@article{flotea2024,
    author = {Flotho, M. and Flotho, P. and Keller, A.},
    title = {Diceplot: A package for high dimensional categorical data visualization},
    year = {2024},
    journal = {arXiv preprint},
    doi = {https://doi.org/10.48550/arXiv.2410.23897}
}