Supporting data for "Expression-driven genetic dependency reveals targets for precision oncology"

This dataset supports the BEACON (Bayesian EvAluation of expression Correlation-driveN dependency) framework, which integrates global proteomic and transcriptomic profiles from 375 cancer cell lines across 22 tissue types with genetic dependency scores derived from CRISPR knockout screens. <br>The dataset includes gene expression-driven dependencies (GED) and protein expression-driven dependencies (PED) computed using Bayesian correlation analysis between gene/protein expression levels and cancer cell dependency data. Results are presented as both pan-cancer dependencies (common across multiple tissue types) and cancer-specific dependencies (unique to particular lineages), along with correlation coefficients (rho), standard deviations, z-scores, and multiple-testing adjusted p-values. <br>This comprehensive resource can be utilized to identify tissue-specific therapeutic vulnerabilities, discover genes with coordinated dependency profiles across cancer types, prioritize precision oncology targets, and enable comparative analysis of molecular dependencies at the transcriptomic and proteomic levels across diverse cancer cell lineages.