Course Description:
Every week a topic of RNA seq. data analysis will be covered, followed by hands-on R coding exercise.

Topics Covered (and the tentative syllabus):
Week 1. Introduction to next generation sequencing technology and its applications in biomedical sciences.
Week 2. Introduction to R
Week 3. Data exploration and quality control
Week 4. Data transformation and clustering
Week 5&6. Matrix operation and PCA
Week 7-9. Generalized linear regression and hypothesis testing
Week 10. Mid-term examination
Week 11&12. Functional and gene set analysis
Week 13. Introduction to single cell RNA sequencing technology
Week 14&15. scRNA sequencing analysis with Seurat
Week 16 Final examination

Evaluation:
Attendance：10%
Homework: 20%
Midterm：30%
Final: 40%

AI rules:
Conditionally open; please specify how generative AI will be used in course output.