Single Cell RNA Sequencing New
Mon 2 Mar, Mon 9 Mar, ... Mon 23 Mar 2020
Description
The course will outlay bioinformatic analysis of cell populations from single-cell RNA including visualisation, clustering and functional analysis of genes. This will be using the programming language R and packages such as Seurat. Participants are encouraged to bring their own laptop to follow along.
Lesson 1
- 4.00 - 4.45pm = Setting up
- 4.45 - 5.00pm = Break, questions
- 5.00 - 6.00pm = Introduction to scRNA-Seq
Lesson 2
- 1.00 - 1.45pm = QC, Normalising, Feature Selection
- 1.45 - 2.00pm = Break, questions
- 2.00 - 3.00pm = Scaling, Dimensionality reduction, Determining dimensionality of dataset
Lesson 3
- 1.00 - 1.45pm = Clustering, UMAP/t-SNE
- 1.45 - 2.00pm = Break, questions
- 2.00 - 3.00pm = Cluster biomarkers, Assigning cell type identity, Differential expression, Enrichment
Lesson 4
- 1.00 - 1.45pm = Work on dataset from Stanford/literature/own dataset
- 1.45 - 2.00pm = Break, questions
- 2.00 - 3.00pm = Work on dataset from Stanford/literature/own dataset
Target audience
- Chemistry Postgraduates
- Further details regarding eligibility criteria are available
Sessions
Number of sessions: 4
| # | Date | Time | Venue | Trainers |
|---|---|---|---|---|
| 1 | Mon 2 Mar 2020 16:00 - 18:00 | 16:00 - 18:00 | Unilever Lecture Theatre | Andrew Boardman, L. Hosseini-Gerami |
| 2 | Mon 9 Mar 2020 13:00 - 15:00 | 13:00 - 15:00 | Todd-Hamied | Andrew Boardman, L. Hosseini-Gerami |
| 3 | Mon 16 Mar 2020 13:00 - 15:00 | 13:00 - 15:00 | Todd-Hamied | Andrew Boardman, L. Hosseini-Gerami |
| 4 | Mon 23 Mar 2020 13:00 - 15:00 | 13:00 - 15:00 | Todd-Hamied | Andrew Boardman, L. Hosseini-Gerami |
Booking / availability