Module Number

BIOINF4250 (entspricht BIO-4250) 		Module Title

Computational Single Cell Biology 		Lecture Type(s)

Practical Course
ECTS 3
Work load
- Contact time
- Self study
Workload:
90 h
Class time:
30 h / 2 SWS
Self study:
60 h
Duration 1 Semester
Frequency Irregular
Language of instruction English
Type of Exam

A written report is to be submitted after the course. Performance during the course will also be integrated into the final grade.
Content

The basics of processing and automatically interpreting single-cell datasets are conveyed and applied on concrete examples in this practical course. The course tasks will be implemented in the scripting language Python and R. Specifically this course covers preprocessing, quality control of single-cell transcriptomic data and reconstruction of dynamic processes via RNA velocity analyses, trajectory inference and different dynamic models.
Objectives

(1)The students learn how to perform quality control and normalization of single-cell RNA sequencing data.
(2) They learn how to visualize high dimensional single-cell data.
(3) They learn how to perform RNA velocity analyses.
(4) They learn how to establish dynamic models from RNA velocity fields.
Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Claassen
Literature

Will be supplied during the course.
Last offered Wintersemester 2022
Planned for currently not planned
Assigned Study Areas BIO-PRAK