Session 11: RNA-seq Data Mining

Topics Covered

  • Data mining: gene fusion detection, differential expression, GSEA, pathway analysis

Practical

  • DESeq normalization
  • Principal Component Analysis (PCA)
  • Differential Expression (DE) Analysis
  • Plots to visualize DE results

  • Clustering and visualization of gene expression
  • Hierarchical clustering using the GenePattern module and R
  • Gene set and pathway enrichment analysis with GSEA and GSVA

  • Identification of gene fusion