Single-Cell Omics

(3 Credits)

This course will provide an overview of the principles and applications of single-cell data analysis with a focus on single-cell RNA-seq libraries. Topics to be covered in the course will include, but not limited to: an overview of single-cell platforms, experimental design, quality control, filtering, normalization, batch correction, dimensionality reduction, clustering, cell annotation, differential expression, and cell ordering. Through a combination of lectures, hands-on laboratory exercises, and discussions, students will gain the knowledge and skills necessary to harness the power of single-cell techniques for a wide range of research applications. Basic knowledge of the programming language R is a prerequisite for participation in the course.