Differential Gene Set Enrichment Analysis: A Statistical Approach to Quantify the Relative Enrichment of Two Gene Sets

Gene Set Enrichment Analysis (GSEA) is an algorithm widely used to identify enrichments of individual gene sets in transcriptomic data. However, statistical methods are needed to accurately measure how two gene sets or pathways are coordinately regulated with respect to each other. Here we present Differential Gene Set Enrichment Analysis (DGSEA), an adaptation of GSEA that assesses the relative enrichment of two gene sets. Using the metabolic pathways glycolysis and oxidative phosphorylation as an example, we demonstrate that DGSEA accurately captures the hypoxia-induced shift towards glycolysis. We also show that DGSEA is more predictive than GSEA of the metabolic state of cancer cell lines, including lactate secretion and intracellular concentrations of lactate and AMP. Furthermore, we demonstrate that DGSEA identifies novel metabolic dependencies not found by GSEA in cancer cell lines. Together, these data demonstrate that DGSEA is a novel tool to examine the relative enrichment of two gene sets. DGSEA is available as an R package at https://github.com/JamesJoly/DGSEA and can be readily applied to analyze gene expression data.