Genomics

Content
 

The Sandbox Genomics course is a 4-day course designed to provide comprehensive training in Genome-Wide Association Studies (GWAS).

 

On the first day, participants will engage in lectures and discussions on foundational genetics concepts, setting the stage for the rest of the course. Attendees will then be guided through every step of a typical GWAS study, from data preprocessing and quality control to the interpretation of results.

A key feature of the course is a hands-on GWAS case study, where participants will work through the entire process from start to finish. This will include handling missing genotypes, performing linear regression analyses for association testing, and understanding linkage disequilibrium for fine-mapping and haplotype construction.

Throughout the course, participants will gain practical insights into the technical challenges and best practices for conducting GWAS using high-performance computing resources. In addition to real-world case studies and recent applications, the course will highlight common limitations and biases in GWAS studies that researchers should be aware of.

Learning Outcomes

A student who has met the objectives of the course will be able to:

  • Explain basic population genetics concepts and elaborate on them when analyzing data
  • Understand and apply in practice the basics of GWAS (Linkage disequilibrium and linear regression)
  • Perform and generalize approaches to data preprocessing and imputation of missing genotypes
  • Discuss and reproduce basic GWAS applications from literature
  • Interpret GWAS results and have a critical approach towards their limitations

Requirements

    The workshop is for researchers, professors, and PhD students at SUND who are interested in learning the different steps involved in a GWAS study and using them to build a structured pipeline for semi-automated GWAS analyses using high-performance computing resources. 

      Exercises will be run on an HPC platform, and participants will be expected to build on existing familiarity with bioinformatics tools and the scripting languages bash and R/Python.