topGO

topGO performs Gene Ontology (GO) enrichment analysis of gene lists from microarray and other gene expression experiments by leveraging GO graph topology to improve detection of biologically meaningful processes.

Key Features:

• Integration of GO Graph Topology: Incorporates relationships between GO terms by leveraging the underlying topology of the GO graph to improve scoring of functional gene groups.
• Novel Algorithms for Enhanced Scoring: Implements two algorithms to refine statistical significance calculations for GO term groupings and to address dependencies among terms.
• Local Dependency Handling: Recognizes and eliminates local dependencies between GO terms to reduce confounding effects in enrichment results.
• Evaluation and Validation: Algorithms were evaluated on real and simulated gene expression datasets with comparative studies showing improved detection of relevant GO terms over existing approaches.

Scientific Applications:

• Gene expression enrichment analysis: Applied to microarray and similar gene expression datasets to identify enriched GO terms from lists of differentially expressed genes.
• Biological interpretation: Facilitates identification of significant biological processes, gene regulation mechanisms, disease mechanisms, and potential therapeutic targets.

Methodology:

Incorporates GO graph topology into enrichment scoring via two algorithms that refine statistical significance and detect/eliminate local dependencies between GO terms; performance was evaluated on real and simulated gene expression datasets and compared to other methods.