R2 Tutorials Logo
2026-03-12
  • 1. Preface
  • 2. Using Datasets
  • 3. View a Gene
  • 4. Multiple Genes View
  • 5. Annotation analyses
  • 6. Differential expression of genes in your dataset
  • 7. Find genes correlating with your gene of interest
  • 8. Working with Kaplan Meier
  • 9. Pathway Finder
  • 10. Multiple datasets overview with Megasampler
  • 11. K-means clustering in R2
  • 12. Using signatures
  • 13. Analysing Time Series
  • 14. Using genesets and creating heatmaps in R2
  • 15. Principle Components Analysis in R2
  • 16. Sample maps: t-SNE / UMAP, high dimensionality reduction in R2
  • 17. Using the R2-Genome browser
  • 18. DataScopes
  • 19. Integrative analysis: ChIP-seq data
  • 20. Integrative Analysis : Across Platforms
  • 21. Integrative Analysis : WGS/NGS data
  • 22. Target Actionability Literature Reviews : TAR
  • 23. Adapting R2 to your needs
  • 24. Exporting data
  • 25. R2 Dataset Addition
  • 26. Graphs: Adjustable Settings menu versus Repsonsive Settings
  • 27. Concepts of R2: did you know..?
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