Polygenic Prediction: Part 4 Bayesian methods for PGS prediction

This video introduces Bayesian methods in statistical genetics, focusing on how prior information can be combined with observed data to make inferences about genetic effects. It explains key concepts such as prior distributions, likelihood, and posterior estimation, along with how Bayesian approaches differ from conventional methods. The lecture also discusses practical applications of Bayesian modeling in genetic analyses and their advantages in handling uncertainty and complex models.