risk-network 0.1.2

A Python package for scalable network analysis and high-quality visualization.

RISK

Regional Inference of Significant Kinships (RISK) is a next-generation tool for biological network annotation and visualization. It integrates community detection algorithms, rigorous overrepresentation analysis, and a modular framework for diverse network types. RISK identifies biologically coherent relationships within networks and generates publication-ready visualizations, making it a useful tool for biological and interdisciplinary network analysis.

For a full description of RISK and its applications, see:
Horecka, I., and Röst, H. (2026)
RISK: a next-generation tool for biological network annotation and visualization
Bioinformatics. https://doi.org/10.1093/bioinformatics/btaf669

Documentation and Tutorial

• Full Documentation: riskportal.github.io/risk-docs
• Try in Browser (Binder):
• Documentation Repository: github.com/riskportal/risk-docs

Installation

RISK is compatible with Python 3.8 or later and runs on all major operating systems. To install the latest version of RISK, run:

pip install risk-network --upgrade

Key Features of RISK

• Broad Data Compatibility: Accepts multiple network formats (Cytoscape, Cytoscape JSON, GPickle, NetworkX) and user-provided annotations formatted as term–to–gene membership tables (JSON, CSV, TSV, Excel, Python dictionaries).
• Flexible Clustering: Offers Louvain, Leiden, Markov Clustering, Greedy Modularity, Label Propagation, Spinglass, and Walktrap, with user-defined resolution parameters to detect both coarse and fine-grained modules.
• Statistical Testing: Provides permutation, hypergeometric, chi-squared, and binomial tests, balancing statistical rigor with speed.
• High-Resolution Visualization: Generates publication-ready figures with customizable node/edge properties, contour overlays, and export to SVG, PNG, or PDF.

Example Usage

We applied RISK to a Saccharomyces cerevisiae protein–protein interaction (PPI) network (Michaelis et al., 2023; 3,839 proteins, 30,955 interactions). RISK identified compact, functional modules overrepresented in Gene Ontology Biological Process (GO BP) terms (Ashburner et al., 2000), revealing biological organization including ribosomal assembly, mitochondrial organization, and RNA polymerase activity.

RISK workflow overview and analysis of the yeast PPI network. Clusters are color-coded by enriched GO Biological Process terms (p < 0.01).

Citation

Primary citation

Horecka, I., and Röst, H. (2026)
RISK: a next-generation tool for biological network annotation and visualization
Bioinformatics. https://doi.org/10.1093/bioinformatics/btaf669

Software archive

RISK software for the published manuscript.
Zenodo. https://doi.org/10.5281/zenodo.17257418

Contributing

We welcome contributions from the community:

• Issues Tracker
• Source Code

Support

If you encounter issues or have suggestions for new features, please use the Issues Tracker on GitHub.

License

RISK is open source under the GNU General Public License v3.0.