GUST

"GUST" (Genes Under Selection in Tumors) is a computational method to identify oncogenes (OGs) and tumor-suppressor genes (TSGs) in a cancer-type specific manner. Recognizing the substantial variability in the functions of cancer driver genes across different tissues and organs, GUST offers a solution to distinguish between passenger genes, OGs, and TSGs, thereby facilitating a deeper understanding of tumor biology and aiding in identifying clinically actionable targets.

Key Features and Functionalities:

- Cancer-Type Specific Analysis: GUST is developed to discover OGs and TSGs with high tissue specificity, addressing the need for context-aware classifications of cancer driver genes.

- Differentiation of Mutation Patterns: The method is based on the observation that the direction and magnitude of somatic selection for protein-coding mutations significantly differ among passenger genes, OGs, and TSGs. This insight allows for accurate differentiation of these gene categories.

High Accuracy: When evaluated through strict cross-validation procedures, GUST demonstrates high accuracy (92%) in identifying OGs and TSGs, underscoring its reliability and effectiveness.