PAFway: pairwise associations between functional annotations in biological networks and pathways

Area of Science:

• Bioinformatics
• Systems Biology
• Computational Biology

Background:

• Biological networks are often dense and challenging to interpret biologically.
• Understanding gene regulatory relationships is crucial for biological insights.

Purpose of the Study:

• To introduce PAFway, a novel computational package for analyzing functional associations in biological networks.
• To address the question of whether genes with specific functions tend to regulate genes with different specific functions.

Main Methods:

• PAFway estimates pairwise associations between functional annotations within biological networks and pathways.
• The package visualizes results as heatmaps or networks of biological functions.
• Applied to an Arabidopsis thaliana gene network to identify functional associations.

Main Results:

• Revealed significant pairwise associations between functional annotations in the Arabidopsis thaliana gene network.
• Demonstrated the utility of PAFway in uncovering biologically meaningful relationships within gene networks.
• Provided visualized outputs (heatmap, network) for easier interpretation of functional links.

Conclusions:

• PAFway offers a valuable method for interpreting complex gene networks by identifying functional associations.
• The tool facilitates a deeper understanding of gene regulation and biological pathways.
• PAFway is available on CRAN and GitHub for broader scientific use.