Lecture takes place in Basel. ***ATTENTION: Starting with the lecture on March 20, the Single Cell Technologies lecture will be broadcasted using a Zoom videoconference. The lecturer will inform the students about the URL to participate in the online course***
Single-cell sequencing and imaging technologies are being applied to primary human organs and to engineered cells and tissues to understand cell states that emerge in these systems at unparalleled resolution. These technologies require sophisticated experimental and computational methods, which we will discuss in practical detail in this course.
Learning objective
To understand the history and current state of the art of single-cell sequencing and imaging methods, gain experimental experience in the implementation of these methods, and to learn data analytical techniques to extract biological insight from the high-information content data.
Content
This course will include lecture sessions and paper discussion seminars, along with wet lab single-cell genomic experiments, followed by computational data analysis sessions based in R. In the lecture, I will cover the molecular biology and technical aspects underlying popular single-cell sequencing methods, as well as methods to spatially localize cell states within tissues or other multi-cellular systems. We will also cover the experimental aspects of light sheet microscopy and other microscopy methods as a tool to analyze cellular dynamics within complex tissues. We will read recent, seminal manuscripts in the single-cell genomics field and discuss the papers in detail as a group.
In the lab, we will select an exciting biological phenomena to explore using single-cell sequencing and each student will get hands on experience in designing and executing the experiment, going through the steps of tissue dissociation, isolating cells, capturing and labeling nucleic acid, generating and sequencing libraries. We will then go through each step of sequencing read processing and quality control analysis, followed by sessions on data exploration (cell composition, marker gene detection, trajectory reconstruction, differential gene expression analysis, etc.)
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course