R2 Tutorials
stable
1. Preface
2. Using Datasets
3. One Gene View
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 and Creating genesets 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. Adapting R2 to your needs
23. Exporting data
24. R2 Dataset Addition
25. Concepts of R2: did you know..?
R2 Tutorials
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