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Single-cell RNA-seq analysis using R

  • Overview
  • Search
  • Course content
  • Planning the experiment
    • Keynote: Cellular heterogeneity in liver and drivers of disease
    • Droplet-based library generation overview
    • Pipeline overview
    • Experimental design
  • Processing data
    • Getting set up: infrastructure terms
    • Raw reads to expression matrix
    • Cell atlases & interpretation
  • Analysing data
    • Designing your analysis
    • Pre-processing and dimensionality reduction
    • From UMAP to annotation
    • Online tools and follow-up
  • Technical help sheets
  • Trainers biographies
  • Further learning
  • Your feedback

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All materials are free cultural works licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, except where further licensing details are provided.

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Processing data

This section will repeat the course of analysis of scRNA-seq data from raw reads to cluster maps and show how to explore and interpret data using R as well as the Human Cell & Single Cell Expression Atlases.

  • Getting set up: infrastructure terms
  • Raw reads to expression matrix
  • Cell atlases & Interpretation

Proceed through this section to view materials on all these topics or select a specific session from the above list to jump ahead.

  • page navigation-left-circle-1_1 Experimental design
  • pageGetting set up: infrastructure terms navigation-right-circle-1_1