COMPASS enables cohort-independent digital biomarker discovery and pathway quantification

Reproducible and clinically transferable quantification of pathway activity remains a major barrier in precision medicine, where biomarker performance often depends on cohort composition and normalization strategies. Here, we introduce COMPASS ( COMP osite A ctivity S coring S ystem), a deterministic threshold-based framework that converts gene expression into quantitative pathway activity scores without reliance on reference cohorts. COMPASS derives gene-specific activation thresholds directly from data, standardizes deviations from thresholds, and integrates directionally opposing genes into a single composite score. This enabled transparent activity scoring, statistical comparisons, and survival analyses without coding. Across diverse biological and clinical datasets, COMPASS robustly quantified cellular states, benchmarked the humanness and disease relevance of new approach methodologies, and stratified outcomes. Compared to GSVA and ssGSEA, COMPASS demonstrated greater consistency across datasets and improved robustness in bootstrap analyses, particularly for bidirectional programs, including regulatory-approved sepsis gene signatures. COMPASS therefore addresses a critical unmet need for exact, interpretable, and clinically transferable biomarker discovery and outcome modeling across diverse biological and clinical settings.