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Single-cell RNA-seq and network analysis using Galaxy and Cytoscape

  • Overview
  • Search
  • Course content
  • Introduction to scRNA-seq technologies
    • Introduction to single-cell RNA-seq
    • Experimental design of single-cell studies
    • Library generation overview
    • Pipeline overview
  • Applying scRNA-seq in research
    • The local and systemic response to SARS-CoV-2 infection in children and adults
    • Understanding complex cellular interactions in senescence using single-cell seq approaches
  • Network analysis using Galaxy
    • Introduction to Galaxy
    • From fasta to matrix
    • Pre-processing and batch correction
    • From matrix to UMAP
    • Clustering, annotation and trajectory interference tools for scRNA-seq data: A quick guide
    • From UMAP to trajectories
  • Network analysis using Cytoscape
    • Network analysis using Cytoscape
    • Advanced network visualisation
    • Cytoscape single-cell analysis
  • Technical help sheet
  • 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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Network analysis using Galaxy

This section covers Galaxy pipelines, an online open-access resource that allows even the most computer-phobic bench scientists to analyse their biological data.

  • Introduction to Galaxy
  • From fasta to matrix
  • Pre-processing and batch correction
  • From matrix to UMAP
  • Clustering, annotation and trajectory interference tools for scRNA-seq data: A quick guide
  • From UMAP to trajectories

  • page navigation-left-circle-1_1 Understanding complex cellular interactions in senescence using single-cell seq approaches
  • pageIntroduction to Galaxy navigation-right-circle-1_1