GS01 1041 Computational Approaches for Single-Cell Data Analysis
- Course Coordinator(s): Ken Chen, Nicholas Navin, and Wenyi Wang
- Semester: Spring and Fall
- Frequency: Annually
- Credit Hours: 1
- Grading System: Pass/Fail
- Prerequisites: None
Chen, Ken; Navin, Nicholas; Wang, Wenyi. One semester hour. Spring and Fall annually. Grading System: Pass/Fail. Prerequisite: None. Audit permitted.
This course aims to provide the central concepts and background knowledge required for experimental design and analysis of single-cell studies. The format combines journal club and seminar series formats, with an organized reading of landmark papers in single-cell omics technologies, high-dimensional data analysis (including transformation, visualization, and clustering), statistical inference, statistical modeling, and phylogenetics, among other possible topics. There will be participant presentations and discussion sessions. At the end of the course, students will be able to think critically about single-cell studies and understand their applications in cancer research and other disciplines.
Schedule can be found here.