In this course participants will learn the critical steps that need to be taken before performing any genetic analysis. This includes the process of genotyping, setting up all necessary quality control steps and learning how to properly prepare data. Additionally, this course offers a deep dive into the world of Genome-Wide Association Studies (GWAS), polygenic risk scores, next- generation sequencing and network analysis.
Modules
In the first of this seminar series, you will learn about crucial steps before performing any genetic analysis. This module outlines the process of genotyping and provides the necessary quality control steps you need to follow to clean your data at a sample and variant level. Navigate through this practical demonstration and learn the code to perform your own genotyping quality control.
Have you ever wondered how to impute your data against different population panels? Watch this video for a clear and straightforward explanation of imputation. Learn how to prepare your data, how to carry out this process in the Michigan Imputation Server, and how to generate softcall and hardcall data for further analyses.
Enter the fascinating world of Genome-Wide Association Studies (GWAS). This module will walk you through this topic in an easy manner. You will learn how to prepare and run your own GWAS for PD risk and onset, how to generate summary statistics and data visualizations (including scree, QQ and manhattan plots), and how to navigate through the FUMA online tool to annotate and interpret GWAS results.
Gain practical insight into polygenic risk scores, and understand their utility, challenges and limitations. This module will allow you to explore hands-on examples to implement polygenic risk scores for PD risk and onset, how to estimate the specificity and sensitivity of your model, and finally how to interpret and visualize your results.
Interested in next-generation sequencing? This module provides an overview of this widely used technology, highlighting the challenges and limitations in translational applications. Learn the bioinformatic sequencing process and implement practically the concepts of variant filtering, annotation and prioritization.
Ever wondered about network analysis? Gain knowledge on this systems biology approach used in the translation of genetic data into the disease context, along with practical demonstrations of its application. Learn about common challenges in interpreting genetic data for complex neurodegenerative conditions, and more.
