Prediction

Overview

Summary

From fundamentals to cutting‑edge methods, this session explores how polygenic scores are constructed, evaluated, and improved using conventional and Bayesian approaches, including MCMC and functional genomic annotations.

  • Originally presented: June 8, 2026
  • Lead: Jian Zeng
  • Topics: prediction theory, polygenic risk scores, SBayesRC

Lectures

This series of lectures can be viewed as a YouTube playlist.

Part 1 Fundamentals

Slides

Part 2 Evaluation, visualization, and pitfalls of polygenic prediction

Slides

Part 3 Conventional methods for PGS prediction

Slides

Part 4 Bayesian methods for PGS prediction

Slides

Part 5 (Optional) Markov chain Monte Carlo (MCMC) for polygenic prediction

Slides

Part 6 SBayesRC: Polygenic prediction incorporating functional annotations

Slides

Practicals