Topic outline

• 

  Single-cell Transcriptomics

  Streamed, 2 - 4 March 2021

  This page is addressed to registered participants. To access the course description and the application form, please click here.

  For any assistance, please contact training@sib.swiss.

  • Feedback for Single-cell Transcriptomics March 2021
• Schedule
  

  Schedule

  Schedule

  First day

  Introduction to scRNAseq:

  • Technologies
  • Experimental design
  • R versus GUI-based tools
    

  Quality control

  • Dropouts - Doublets
  • Doublet removal using simulation
    
  • Ribosomal / mitochondrial RNAs
  • Cell cycling
    

  Normalization and scalability

  • Feature selection
  • Log scaling
  • Confounding factors removal

  Second day

  Dimentionality reduction and cell type clustering 

  • PCA
  • tSNE
  • UMAP
  • Clustering methods (Hierarchical, K-means and Graph-based)
  • Data integration of complex experimental designs
    

  Cell type identification and marker identification

  • Methods and applications

  Differential expression analysis

  • Methods overview

  Third day

  Differential expression analysis- continued
  

  • DE between clusters 
  • DE between samples (involving data-integration)
  • Gene set enrichment analysis
    

  Pseudotime analysis

  • Methods and applications
• Materials
  

  Materials

  • First Day

  • Practicals Day 1 Folder

    Scripts, source data and information for practicals performed on day 1
    

  • Second Day

  • Practicals Day 2 Folder
  • Third Day

  • Practicals Day 3 Folder

    Scripts to perform DEG analysis and trajectory analysis.

    Link to data:

    https://single-cell-transcriptomics.s3.eu-central-1.amazonaws.com/scRNAseq.tar.gz