ORBIT: Annotation-Aware Empirical Enrichment and Semantic Reranking for Interpretable Functional-Class Recovery

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Gene-set interpretation tools often yield lengthy, redundant results, necessitating extensive manual curation.
• Efficient summarization of transcriptomic and proteomic data is crucial for biological insight.

Purpose of the Study:

• To develop and evaluate ORBIT (Ontology-Ranked Biological Interpretation Tool), an advanced workflow for functional interpretation of gene sets.
• To improve the prioritization and clarity of biological summaries derived from gene-set enrichment analyses.

Main Methods:

• ORBIT integrates empirical enrichment, semantic reranking, and redundancy-aware term selection.
• Evaluation involved a benchmark of human functional-class gene sets and case studies in GPCRs and transcriptomics.
• Statistical validation included bootstrap confidence intervals and permutation testing.

Main Results:

• ORBIT semantic demonstrated superior expected-class recovery compared to Enrichr and PANTHER Gene Ontology baselines on a core benchmark.
• The tool effectively compressed redundant terms into semantically representative neighborhoods, facilitating biological interpretation.
• ORBIT successfully condensed complex signatures from single-cell markers, interferon stimulation, and cancer subtypes into prioritized functional summaries.

Conclusions:

• ORBIT enhances the transition from ranked enrichment terms to structured biological interpretation.
• The tool preserves the evidence trail from input genes to functional summaries, improving data reviewability.
• ORBIT offers a robust solution for summarizing complex biological data from transcriptomic and proteomic experiments.