dcGOR

dcGOR performs ontology-based analysis of protein domain annotations by integrating the dcGO database and ontologies such as the Gene Ontology (GO) to support enrichment, semantic similarity, and network analyses.

Key Features:

• Data structures and R integration: Provides R data structures representing domains, ontologies, annotations, and analysis outputs and integrates with the dcGO database.
• Domain-based enrichment analysis: Performs enrichment analysis to assess functional, phenotypic, and disease-related associations of protein domains.
• Visualization: Produces visualization outputs for enrichment results and network relationships.
• Semantic similarity networks: Constructs semantic similarity networks from ontology annotations to investigate domain relationships at the network level.
• Significance analysis: Conducts statistical significance testing for contact and network data.
• Custom ontology and annotation import: Supports importing user-defined ontologies and annotations from SCOP, Pfam, InterPro, and Rfam.
• Parallel computing: Supports high-performance parallel computing to accelerate analyses.

Scientific Applications:

• Functional interpretation of domains: Maps protein domain annotations to ontologies to interpret biological roles and functions.
• Phenotype and disease association analysis: Identifies associations between protein domains and phenotypes or diseases.
• Network-level domain analysis: Explores domain relationships and organizational patterns via semantic similarity networks.
• Therapeutic target prioritization: Aids in prioritizing candidate therapeutic targets based on domain-disease associations.

Methodology:

dcGOR processes input lists of protein domains to perform enrichment analysis, construct semantic similarity networks, and conduct statistical significance testing while allowing integration of user-defined ontologies and annotations.