gene-set-enrichment-analysis

Gene Set Enrichment Analysis using GSVA

Written by Stephanie J. Spielman to supercede previous analyses in ssgsea-hallmark. Edited for R 4.4, GSVA 1.52.0, tidyR >1.0 by Jo Lynne Rokita

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

Usage:

Note that running this analyis on the full dataset requires > 16GB of memory. Run the bash script of this analysis module:

using OPENPBTA_BASE_SUBTYPING=1 to run this module using the pbta-histologies-base.tsv from data folder while running molecular-subtyping modules for release.

OPENPBTA_BASE_SUBTYPING=1 analyses/gene-set-enrichment-analysis/run-gsea.sh

OR by default uses histologies.tsv from data folder

bash analyses/gene-set-enrichment-analysis/run-gsea.sh

This command above assumes you are in the top directory, OpenPBTA-analysis

Folder Content

• 01-conduct-gsea-analysis.R performs the GSVA analysis using RSEM TPM expression data for both exome_capture, stranded and polyA data. Results are saved in results/ TSV files when run via run-gsea.sh.

• 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).

• results/gsva_scores.tsv represents GSVA scores calculated from gene-expression-rsem-tpm-collapsed.rds with Rscript --vanilla 01-conduct-gsea-analysis.R

• results/gsva_scores_polya.tsv represents GSVA scores calculated from pbta-gene-expression-rsem-fpkm-collapsed.polya.rds with with Rscript --vanilla 01-conduct-gsea-analysis.R

• Files named as results/gsva_<tukey/anova>_<all_possible_RNA_library>_<broad_histology/cancer_group)>.tsv represent results from modeling

  • Files created with: Rscript -e "rmarkdown::render('02-model-gsea.Rmd', clean = TRUE, params=list(is_ci = ${IS_CI}))"
  • Assumes results/gsva_scores.tsv