An R package for Survival-based Gene Set Enrichment Analysis

Music City Center 

Functional enrichment analysis is often used to assess the effect of experimental differences. However, researchers sometimes want to understand the relationship between transcriptomic variation and health outcomes like survival. We propose Survival-based Gene Set Enrichment Analysis (SGSEA) to identify biological functions associated with a disease's survival. Despite the availability of this method, there are no standard tools or software to perform this analysis. We developed an R package and Shiny App called SGSEA and presented a study of kidney renal clear cell carcinoma (KIRC) to demonstrate the approach. Unlike traditional Gene Set Enrichment Analysis (GSEA), which uses log-fold change, SGSEA uses hazard ratios for gene ranking. Our study shows that pathways enriched with genes whose increased transcription is associated with mortality (NES > 0, adjusted p-value < 0.15) have previously been linked to KIRC survival, demonstrating the value of this approach. This method allows rapid identification of disease variant pathways and provides supplementary information to standard GSEA, all within a single R package or via the convenient app.

Gene Set Enrichment Analysis (GSEA)

R package Shiny App

Pathway enrichment analysis

Survival outcomes

Transcriptomic variation

Biological functions 

Section on Statistics in Genomics and Genetics