ViSEAGO

ViSEAGO performs Gene Ontology (GO) functional analysis to mine biological functions and assess functional coherence across large-scale, multi-comparison gene-level datasets.

Key Features:

• R implementation: Implemented as an R package for programmatic analysis workflows.
• GO annotation sources: Retrieves GO annotations from NCBI EntrezGene, Ensembl, and UniProt for multiple species.
• Enrichment analysis: Conducts GO enrichment analyses to identify overrepresented biological terms.
• Semantic similarity: Computes semantic similarity measures between GO terms to evaluate functional coherence.
• Aggregation of themes: Aggregates closely related GO terms into coherent biological themes for synthesis and summarization.
• Multi-dataset and multi-comparison support: Handles large-scale datasets with multiple comparisons and enables collective analysis of multiple datasets.
• GO-structure-aware visualization: Produces visualizations that respect the GO graph structure and offer both synthetic and detailed views.
• Integration of existing methods: Leverages existing R packages and incorporates novel developments to extend traditional GO analysis.

Scientific Applications:

• Functional mining: Mining biological functions and establishing connections between genes within complex experimental designs.
• Comparative analyses: Comparative GO analysis across multiple datasets, conditions, and species to highlight shared and distinct functional signals.
• Interpretability enhancement: Improving interpretability of GO results by aggregating related terms and assessing functional coherence.

Methodology:

Implemented in R, ViSEAGO retrieves GO annotations from NCBI EntrezGene, Ensembl, and UniProt, performs GO enrichment analysis and semantic similarity calculations to aggregate related GO terms, visualizes results while respecting the GO graph structure, and handles multiple comparisons across datasets.