3.0

credits

Average Course Rating

Covers two parts: Part I (taught by Dr. Wang) and Part II (taught by Dr. Chatterjee). Part I: Covers various topics for analyzing prospective and case-control data, and for evaluating the performance of biomarkers to predict risk of clinical or disease outcome. Specific topics include concepts and methods for relative risk, absolute risk, odds/hazards ratio, and ROC/AUC biomarker inference for binary and failure time outcomes. Part II: Covers methods for building absolute risk models and incorporating polygenic risk score (PRS) into such models together with non-genetic factors. Specific topics include a) Absolute risk and components of underlying models b) Integration of Data from various sources for building absolute risk models c) Concept of heritability and its relationship with predictive performance of PRS d) Methods for building PRS from existing genome-wide association studies e) Evaluating statistical validity and clinical utility of risk-prediction models.