Gene Set Enrichment Analysis

Written by Stephanie J. Spielman to supercede previous analyses in ssgsea-hallmark. Primary goals include:

1. Score hallmark pathways based on expression data using GSVA analysis, using a strategy that produces Gaussian-distributed scores.
2. Analyze scores for highly significant differences among tumor classifications
3. [Pending] generate heatmaps and templates for boxplot figures

Folder Content

• 01-conduct-gsea-analysis.R performs the GSVA analysis using RSEM FPKM expression data for both stranded and polyA data. Results are saved in results/ TSV files.

• 02-model-gsea.Rmd performs ANOVA and Tukey tests on GSVA scores to evaluate, for each hallmark pathway, differences in GSVA across groups (e.g. short histology or disease type).

• FORTHCOMING: 03-visualize-gsea.Rmd will create heatmaps and boxplots to visualize scores.

• results/gsva_scores_stranded.tsv represents GSVA scores calculated from pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds (data release v12)

  • File created with: Rscript --vanilla 01-conduct-gsea-analysis.R --input pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds --output gsva_scores_stranded.tsv

• results/gsva_scores_polya.tsv represents GSVA scores calculated from pbta-gene-expression-rsem-fpkm-collapsed.polya.rds (data release v12)

  • File created with: Rscript --vanilla 01-conduct-gsea-analysis.R --input pbta-gene-expression-rsem-fpkm-collapsed.polya.rds --output gsva_scores_stranded.tsv

• Eight files named as results/gsva_<tukey/anova>_<stranded/polya>_<disease_type_new/short_histology>.tsv represent results from modeling

  • Files created with: Rscript --vanilla 02-model-gsea.R
  • Assumes results/gsva_scores_stranded.tsv and results/gsva_scores_polya.tsv exist