About Course

This course introduces GWAS and TWAS methods for identifying genetic biomarkers using statistical association methods, SNP analysis, haplotype blocks, linkage disequilibrium, and transcriptome-wide association pipelines.

Course abbreviation: GWAS

Workload: 12 lectures, 3 hours each. Total workload: 42 hours: 36 hours of lectures and tutorials and 6 hours of self studies.

Entrance requirements: Basic knowledge of bioinformatics.

Used media: PowerPoint presentation

Objectives

  • Understand GWAS analysis and genetic biomarkers
  • Preprocess and examine GWAS data using R, Haploview, and PLINK
  • Postprocess GWAS results using R
  • Apply TWAS using the FUSION pipeline

Competences to be Developed

  • Overview of GWAS analysis
  • Preprocessing GWAS data using R
  • Examining GWAS data using Haploview and PLINK
  • Postprocessing GWAS results using R
  • Applying TWAS using FUSION pipeline

Assessment

  • Finalize a research project applying learned methods
  • Compile project outcomes into a high-quality research article ready for peer-review submission
  • Present and scientifically review all projects in the last lecture
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What Will You Learn?

  • Understand GWAS analysis and genetic biomarkers
  • Preprocess and examine GWAS data using R, Haploview, and PLINK
  • Postprocess GWAS results using R
  • Apply TWAS using the FUSION pipeline
  • Overview of GWAS analysis
  • Preprocessing GWAS data using R
  • Examining GWAS data using Haploview and PLINK
  • Postprocessing GWAS results using R

Course Content

Lecture 1: Single Nucleotide Polymorphisms

  • Single Nucleotide Polymorphisms
    00:00

Lecture 2: Genetic Association Studies

Lecture 3: Direct and Indirect Association Studies

Lecture 4: Population-based Association Studies

Lecture 5: GWAS

Lecture 6: Haplotype Blocks

Lecture 7: Haplotype Blocks Partitioning Methods

Lecture 8: GWAS Application 1

Lecture 9: GWAS Application 2

Lecture 10: TWAS 1

Lecture 11: TWAS 2

Lecture 12: Projects Discussion and Closure

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