GScluster

GScluster performs network-weighted clustering of gene sets by combining gene-set overlap and protein-protein interaction (PPI) networks to improve functional interpretation of gene-set analysis (GSA) results from omics data such as microarray gene expression, GWAS summary statistics, and RNA-sequencing.

Key Features:

• Network-weighted gene-set clustering: Clusters gene-sets using both gene overlap and PPI network information to prioritize functionally connected groups.
• Enhanced functional relevance: Increases PPI density within clusters to favor biologically coherent functions and pathways.
• Diverse visualization functions: Provides visualizations for gene-sets and PPI networks to support analysis and interpretation.
• Cross-omics applicability: Applicable to microarray gene expression, GWAS summary statistics, and RNA-sequencing datasets.
• Comparative gene-set distance analysis: Includes functionality to compare distinct properties of various gene-set distance measures.

Scientific Applications:

• GSA result interpretation: Improves interpretability of large lists of significant pathways or functions derived from gene-set analysis.
• Pathway and interaction discovery: Aids identification of biologically significant pathways and protein interactions that may be overlooked by overlap-only approaches.
• Cross-dataset analysis: Enables network-informed clustering across different omics data types such as microarray, GWAS, and RNA-seq.

Methodology:

Integrates gene-set overlap and protein-protein interaction (PPI) network information to perform network-weighted clustering that yields clusters with increased PPI density; includes comparison of gene-set distance measures.