James H Joly1, William E Lowry2,3,4,5,6, Nicholas A Graham1,7. 1. Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA. 2. Department of Molecular, Cell, and Developmental Biology, Los Angeles, Los Angeles, CA 90095, USA. 3. Broad Center for Regenerative Medicine, Los Angeles, Los Angeles, CA 90095, USA. 4. Division of Dermatology, David Geffen School of Medicine, Los Angeles, Los Angeles, CA 90095, USA. 5. Molecular Biology Institute, Los Angeles, Los Angeles, CA 90095, USA. 6. Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA 90095, USA. 7. Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90089, USA.
Abstract
MOTIVATION: Gene Set Enrichment Analysis (GSEA) is an algorithm widely used to identify statistically enriched gene sets in transcriptomic data. However, GSEA cannot examine the enrichment of two gene sets or pathways relative to one another. Here we present Differential Gene Set Enrichment Analysis (DGSEA), an adaptation of GSEA that quantifies the relative enrichment of two gene sets. RESULTS: After validating the method using synthetic data, we demonstrate that DGSEA accurately captures the hypoxia-induced coordinated upregulation of glycolysis and downregulation of oxidative phosphorylation. 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. Finally, we demonstrate the application of DGSEA to generate hypotheses about differential metabolic pathway activity in cellular senescence. Together, these data demonstrate that DGSEA is a novel tool to examine the relative enrichment of gene sets in transcriptomic data. AVAILABILITY AND IMPLEMENTATION: DGSEA software and tutorials are available at https://jamesjoly.github.io/DGSEA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Gene Set Enrichment Analysis (GSEA) is an algorithm widely used to identify statistically enriched gene sets in transcriptomic data. However, GSEA cannot examine the enrichment of two gene sets or pathways relative to one another. Here we present Differential Gene Set Enrichment Analysis (DGSEA), an adaptation of GSEA that quantifies the relative enrichment of two gene sets. RESULTS: After validating the method using synthetic data, we demonstrate that DGSEA accurately captures the hypoxia-induced coordinated upregulation of glycolysis and downregulation of oxidative phosphorylation. 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. Finally, we demonstrate the application of DGSEA to generate hypotheses about differential metabolic pathway activity in cellular senescence. Together, these data demonstrate that DGSEA is a novel tool to examine the relative enrichment of gene sets in transcriptomic data. AVAILABILITY AND IMPLEMENTATION: DGSEA software and tutorials are available at https://jamesjoly.github.io/DGSEA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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