Recently Taught Courses

Instat 2026 - Advanced Statistical Methods for Genetic Association Studies

This seminar presents advanced statistical methods for genetic association research, synthesizing theoretical foundations with applied workflows. It addresses the analytical challenges that arise in large-scale genome-wide association studies (GWAS), molecular QTL mapping, co-localization, Mendelian Randomization (MR), and transcriptome-wide association studies (TWAS), and it explains why rigorous statistical treatment for reliable inference is essential in genetics.

  • Session 1: GWAS Fundamentals and Data Preparation
  • Session 2: Advanced Association Models and Fine-Mapping
  • Session 3: Polygenic Risk Scores
  • Session 4: Molecular QTL Mapping and Covariate Control
  • Session 5: Co-Localization Theory and Practice
  • Session 6: Integrating Molecular QTL with GWAS Results by Mendelian Randomization
  • Session 7: TWAS/PWAS and Integrative Reproducible Pipelines
  • Session 8: TWAS/PWAS Using Summary-Level xQTL and GWAS Data
  • Session 9: Fine-Mapping TWAS/PWAS Results

SISG 2025 - Gene Regulation Modules

  1. Introduction to TWAS
  2. TWAS with Summary xQTL Data and Finemapping
  3. TWAS and Mendelian Randomization
  4. ChIP-seq Analysis Pipeline
  5. Analysis with Functions of Noncoding Variants

BIOS-770 - Advanced Statistical Genetics: GWAS

  1. Genotype Imputation, Single Variant GWAS
  2. QC, Population Stratification, LMM
  3. Finemap, Bayesian Functional GWAS
  4. Rare Variant Test, Pleiotropy, Mendelian Randomization

IBS-519 - Data Analysis using R

  1. Linear Regression
  2. ANOVA
  3. Power Analysis
  4. Permutation Test
  5. Introductions to Machine Learning

IBS-538 - Data Science

  1. Multivariate Analysis with Application to RNAseq Differential Gene Expression Analysis

High Performance and Cloud Computing Cluster

HGCC

RHPC

HyPER-C3

Emory Amazon Web Service (AWS)

Other Resources

Bioinformatics

  1. Bioinformatics workshop documentations by UCDAVIS Bioinformatics Core with the following Covered Topics:
    • Bioinformatics Prerequisites (Command Line and R)
    • Single-Cell RNA-Seq Analysis
    • RNA-seq Analysis
    • Microbial Community Analysis (Amplicon)
    • Variant Analysis (Variant calling with GATK, Variant Annotation)
  2. Analysis of single cell RNA-seq data by Hemberg lab, Welcome Sanger Institute, UK

  3. ENAR 2021 short course on single cell RNA-seq analysis by Hao Wu, Emory University, and Ziyi Li, MD Anderson Cancer Center

  4. Bioinformatics Training at the Harvard Chan Bioinformatics Core

Linux

R

Coursera Python Courses

Scientific Writing and Presentations

Scientific Writing

Scientific Presentations

Poster Presentations

Oral Scientific Presentations