This course will introduce students, researchers, and professionals to the complete process of conducting a Genome-Wide Association Study (GWAS). Participants will learn all the essential steps involved in a typical GWAS — from study design and data preparation to statistical analysis and interpretation of results, integrating them into a cohesive and efficient workflow — through a combination of lectures and hands-on practical sessions.

The course is organized into modules across five days. Each day begins with introductory lectures and interactive class discussions to cover key concepts. The rest of the day is dedicated to practical, hands-on sessions where you’ll first follow along with the instructors to learn new skills, then apply those skills independently through individual exercises. Throughout and after each exercise, we’ll interpret the results together and engage in group discussions to deepen understanding.

This course is designed for students, researchers, and professionals eager to learn the key steps involved in conducting a GWAS study. Whether you’re a beginner or have some experience, the course will provide valuable insights and practical skills. We’ll start by introducing fundamental GWAS concepts and gradually guide you through each step, integrating them into a cohesive and efficient workflow. A background in biology, especially genetics, is recommended, and prior exposure to GWAS is helpful but not required. The course combines lectures with hands-on exercises using R and the Linux command line tools. 

This course is designed for students, researchers, and professionals eager to learn the key steps involved in conducting a GWAS study. Whether you’re a beginner or have some experience, the course will provide valuable insights and practical skills. We’ll start by introducing fundamental GWAS concepts and gradually guide you through each step, integrating them into a cohesive and efficient workflow. A background in biology, especially genetics, is recommended, and prior exposure to GWAS is helpful but not required. The course combines lectures with hands-on exercises using R and the Linux command line tools. 

Course schedule: 2-8  pm Berlin time

Monday

• Lecture 0: General Introduction / Course Overview

• Lecture 1: Introduction to GWAS – Linkage Disequilibrium and Linear Regression

• Lecture 2: GWAS Case Studies / Examples from Literature

• Lab 2 Part 1: Basic Linux and R

• Lab 2 Part 2: Practicalities and Setup (Server, GitHub Repo, Conda Environments, etc.) + Dataset Overview

• Lab 2 Part 3: Basic Linux and R (Continued)

• Lab 3: GWAS Basic Models

• Lab 3 Demonstration: GWAS Basic Models (Linear & Logistic Regression, Population Structure, etc.)

Tuesday

• Lecture 4: Exploratory Data Analysis (EDA) Theory

• Lab 4: EDA Practice

• Lecture 5: Data Preprocessing Theory

• Lab 5: Data Preprocessing Practice

• Lecture 6: Imputation of Missing Genotypes – Theory

• Lab 6 Part 1: Imputation Practice (Beagle)

• Lab 7 Demonstration: KNNI Imputation

Wednesday

• Lecture 7: GWAS Full Model (All SNPs)

• Lab 9 Demonstration: Review of Past Steps (GenABEL)

• Lab 10: GWAS Stand-Alone Script(s) for the Full Model

• Lecture 8: GWAS Experimental Design and Statistical Power

• Lecture 9: The Multiple Testing Issue

• Lab 10: Revisiting GWAS Steps

Thursday

• Lecture 10: Bioinformatics Pipelines – A Super-Elementary Introduction

• Lab 11: Building a Pipeline with Snakemake

• Lab 12: GWAS Pipeline for Continuous Phenotypes

• Lab 13: GWAS Pipeline for Binary Phenotypes

• Lab 14: Introducing the Exercise (+ Intro to RMarkdown)

• Collaborative Exercise: Build Your Own GWAS Pipeline on New Data

• Discussion: Q&A on Building Pipelines for GWAS

Friday

• Lecture 11: GWAS Models for Categorical Traits (Primer)

• Lecture 12: GWAS Models for Longitudinal Data (Primer)

• Lecture 13: Introduction to Post-GWAS Analysis

• Lecture 14: Overview of ROH-Based Alternatives

• Kahoot Quiz: What We Learned About GWAS!

• Wrap-Up Discussion: GWAS

Cancellation Policy:

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.