GSAn

GSAn applies semantic similarity measures to refine Gene Ontology (GO) term annotations for gene sets, reducing redundant terms while maximizing inclusion of annotated genes to improve interpretation of omics-derived genotype–phenotype relationships.

Key Features:

• Semantic similarity refinement: Employs semantic similarity measures to refine Gene Ontology (GO) terms associated with gene sets.
• Redundancy reduction: Reduces the number of redundant GO terms to simplify annotation output.
• Maximized gene coverage: Balances term reduction with maximization of inclusion of related annotated genes within gene sets.
• Alternative to enrichment analysis: Provides a complementary approach to statistical enrichment analysis that can broaden annotation beyond well-studied genes.

Scientific Applications:

• Interpretation of omics data: Enhances interpretation of omics datasets in studies of genotype–phenotype relationships.
• Annotation of less-studied genes: Facilitates inclusion and analysis of less-studied genes within gene sets.
• Characterization of biological processes and pathways: Improves identification and summarization of GO-based biological processes and pathways from gene sets.
• Complementary functional analysis: Serves as a complementary method to conventional statistical enrichment for functional annotation of gene sets.

Methodology:

Uses semantic similarity measures to refine Gene Ontology (GO) terms, reduce redundant GO terms, and maximize inclusion of related annotated genes within gene sets.