RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Area of Science:

• Bioinformatics
• Computational Biology
• Systems Biology

Background:

• Biological networks are crucial for understanding complex biological systems.
• Analyzing large and intricate networks requires specialized computational tools.
• Existing tools may lack the flexibility for custom datasets or high-throughput analysis.

Purpose of the Study:

• Introduce RWRtoolkit, a novel package for R and command-line users.
• Provide efficient tools for generating, exploring, and statistically analyzing multiplex biological networks.
• Facilitate the analysis of custom and public biological datasets across species.

Main Methods:

• Development of a software package (RWRtoolkit) for R and command-line environments.
• Implementation of functions for topological distance calculation, relationship determination, and statistical evaluation within networks.
• Design of a command-line interface for parallelization and high-throughput analysis, including permutation testing.
• Integration of selected tools into the KBase web application for reproducible workflows.

Main Results:

• RWRtoolkit enables efficient exploration of large, complex biological networks.
• The package provides functions to analyze topological distances and relationships within biological entities.
• Statistical evaluation of relationships within and between sets of interest is supported.
• The command-line interface facilitates high-throughput analyses on cluster systems.

Conclusions:

• RWRtoolkit offers a comprehensive solution for biological network analysis.
• The package enhances the ability to uncover relationships and evaluate network properties.
• Its design supports both custom data exploration and reproducible research workflows.