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
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
Student Ratings & Reviews
No Review Yet

