You can run the labs either in a Singularity container on Uppmax (recommended during course) or using Docker locally on your system. Instructions on running the labs are provided here
A short description of the data used in the tutorials is provided here.
Tip
We perform the same steps with all three toolkits, but there are some small differences as all methods are not implemented everywhere. It’s up to you which toolkit you want to work with. To download file, Right click > Save Link As….
| Topic | Seurat | Bioconductor | Scanpy |
|---|---|---|---|
| 1 Quality Control | |||
| 2 Dimensionality reduction | |||
| 3 Data integration | |||
| 4 Clustering | |||
| 5 Differential expression | |||
| 6 Celltype prediction | |||
| 7 Trajectory inference |
Caution
This topics below are not covered in the workshop and are therefore optional. These topics also require separate containers. See instructions on running labs for more info.
| Optional Topic | Seurat | Bioconductor | Scanpy |
|---|---|---|---|
| 8 Spatial transcriptomics |
Useful resources
- The github repository for this course
- Pre-recorded videos of lectures (from 2022) are available on Youtube
- Single Cell Glossary
- Single cell RNA-seq course at from Hemberg lab
- Single cell RNA-seq course in Python
- Single cell RNA-seq course at Broad
- Repository listing many scRNA-seq tools
- SingleCellExperiment objects for many datasets
- Conquer datasets - many different datasets based on a salmon pipeline
- The Human Cell Atlas project