Day 2

Morning

• Lecture: What is a count matrix and how is it represented in Seurat/Scanpy?
• Lecture: Quality Control for scRNA-Seq data
• Practical work: Importing the scRNA-Seq example dataset and performing first QC steps
  • Download the example dataset from the course github. This is a subset of the 10x Genomics v3 10k PBMC dataset (“10k PBMCs from a Healthy Donor (v3 chemistry)”; https://www.10xgenomics.com/datasets/10-k-pbm-cs-from-a-healthy-donor-v-3-chemistry-3-standard-3-0-0). Cell numbers were reduced while keeping the individual cells’ sequencing depth the same. Only some cell types in the original dataset were kept. A number of empty droplets and low-quality cells are also included.
  • basic scRNA-Seq workflow exercises - python
  • basic scRNA-Seq workflow exercises - R

Afternoon

• Lecture: Data preprocessing
• Lecture: Dimensionality reduction 1 - Principal Component Analysis
• Practical work: Data preprocessing (comparison of standard log norm approach and Pearson residuals) and PCA, preliminary cell type analysis
  • (uses the same notebooks as the morning exercise, see above)