Due to the COVID-19 outbreak, this course will be held online

This course will introduce students, researchers and professionals to the steps needed to build an analysis pipeline for Genome-Wide Association Studies (GWAS). The course will describe all the necessary steps involved in a typical GWAS study, which will then be used to build a reusable and reproducible bioinformatics pipeline.

The course is structured in modules over five days. Each day will include introductory lectures with class discussions of key concepts. The remainder of each day will consist of practical hands-on sessions. These sessions will involve a combination of both mirroring exercises with the instructors to demonstrate a skill as well as applying these skills on your own to complete individual exercises. After and during each exercise, results will be interpreted and discussed in group.

The course is aimed at students, researchers and professionals interested in learning the different steps involved in a GWAS study using them to build a structured pipeline for semi-automated and reproducibile GWAS analyses. It will include information useful for both beginners and more advanced users. We will start by introducing general concepts of GWAS and bioinformatics pipeline building, progressively describing all steps and putting there seamlessy together in a general workflow. Attendees should have a background in biology, specifically genetics; previous exposure to GWAS experiments would also be beneficial. There will be a mix of lectures and hands-on practical exercises using R, Linux command line and custom software. Some basic understanding of R programming and Unix will be advantageous. Attendees should also have some basic familiarity with genomic data such as those arising from NGS experiments.

• Understanding the different steps involved in a typical GWAS analysis and how to build them together in a general workflow / bioinformatics pipeline

Monday  2-8  pm Berlin time

 14:00    Lecture 0  General Introduction / Overview of the course

 14:30   Lecture 1   Introduction to GWAS: Linkage disequilibrium and Linear Regression

 15:30   Lecture 2   GWAS: case studies / examples from literature

 16:30  break

 17:00    Lab 2 - part 1  basic Linux and R

 18:00   Lab 2 - part 2  Practicalities and set-up (server, github repo, conda envs, etc) and description of datasets

 18:30   Lab 2 - part 3  basic Linux and R

 19:00   Lab 3     GWAS: basic models

 19:30   Lab 3 (demonstration) GWAS: basic models (linear and logistic regression, population structure, etc.)

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.