300164 UE Advanced bioinformatic analysis of single-cell data (2024S)
Continuous assessment of course work
Labels
ON-SITE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Th 08.02.2024 14:00 to Th 22.02.2024 18:00
- Deregistration possible until Fr 15.03.2024 18:00
Details
max. 8 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
The first course date will also serve as the date for the preliminary discussion (Vorbesprechung).
Monday
04.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Tuesday
05.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Wednesday
06.03.
09:45 - 14:45
Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
Thursday
07.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Friday
08.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Monday
11.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Thursday
14.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Friday
15.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Monday
18.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Tuesday
19.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Wednesday
20.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Thursday
21.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Friday
22.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Wednesday
03.04.
08:00 - 14:00
Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
Thursday
04.04.
08:00 - 14:00
Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
Information
Aims, contents and method of the course
Single-cell RNA-sequencing has significantly advanced our understanding of biological systems. It has highlighted unexpected transcriptional heterogeneity in cell populations that were thought to be uniform, discovered hitherto unknown rare cell types, and allowed us to predict cell fates in differentiation. Extracting biological meaning from the sequencing data requires involved in-silico analysis.This course will use publicly available datasets to attack advanced topics in single-cell RNA-seq analysis, such as cell type theory, actionable clustering, dataset integration, cross-species comparison, and advanced visualisation. Recent literature will be used as reference material and discussed in class.
Assessment and permitted materials
Doesn’t require any previous knowledge in programming or single-cell transcriptomics analysis, though it is strongly recommended. Basic knowledge of molecular biology and a general interest in the field is expected from the students. Knowledge in mathematics and statistics is welcome.Previous students have indicated that the following courses have been helpful:- 300106 UE Analyses of single cell transcriptome data
- 300357 UE Mathematical Basics for Quantitative BiologActive participation in the exercises and discussions during the course is required. For final evaluation, students will be asked to repeat the analysis steps on previously unseen data (open book). A short report including the code will be turned in and evaluated. The grade will be determined to 50% by participation, 20% by presentations during the course, and 30% by the final evaluation. For a passing grade all three partial evaluations must be at least passing.
- 300357 UE Mathematical Basics for Quantitative BiologActive participation in the exercises and discussions during the course is required. For final evaluation, students will be asked to repeat the analysis steps on previously unseen data (open book). A short report including the code will be turned in and evaluated. The grade will be determined to 50% by participation, 20% by presentations during the course, and 30% by the final evaluation. For a passing grade all three partial evaluations must be at least passing.
Minimum requirements and assessment criteria
Active participation in the exercises and discussions during the course is required. For final evaluation, students will be asked to repeat the analysis steps on previously unseen data (open book). A short report including the code will be turned in and evaluated. The grade will be determined to 50% by participation, 20% by presentations during the course, and 30% by the final evaluation. For a passing grade all three partial evaluations must be at least passing.
Examination topics
Reading list
Previous students have been asked to provide feedback and advice for future course attendees. Here are some quotes:- "Best advice for me would be: make sure you have time! Mainly just to make sure to have time after class to review the concepts and codes gone through the day because with this block course format everything piles up pretty quickly."
- "Be prepared for the theory and the philosophy behind the different steps [...]"
- "Be sure to have at least some basic knowledge of coding as it will help very much."
- "Take your time to really understand the fundamental concepts & take your time playing around with the homework."
- "Be prepared for the theory and the philosophy behind the different steps [...]"
- "Be sure to have at least some basic knowledge of coding as it will help very much."
- "Take your time to really understand the fundamental concepts & take your time playing around with the homework."
Association in the course directory
MZO W3, MZO4, MBO 7, MEC-9, MZO2, MES5
Last modified: Tu 02.04.2024 11:46