DGSEA

DGSEA compares the relative enrichment of two gene sets in transcriptomic datasets to quantify differential pathway activity.

Key Features:

• R package implementation: Implemented as an R package for analysis of transcriptomic datasets.
• Differential comparison of gene sets: Quantifies and compares relative enrichment between two gene sets or pathways, extending Gene Set Enrichment Analysis (GSEA).
• Statistical methodology: Provides a robust statistical methodology to quantify and compare differential enrichment between gene sets.
• Validation on synthetic data: Validated using synthetic data to assess accuracy and reliability.
• Detection of coordinated pathway regulation: Captures hypoxia-induced coordinated upregulation of glycolysis alongside downregulation of oxidative phosphorylation.
• Metabolic phenotype prediction: Demonstrated improved prediction of metabolic states in cancer cell lines, including lactate secretion and intracellular concentrations of lactate and AMP.
• Application to senescence: Enables generation of hypotheses about differential metabolic pathway activities during cellular senescence.
• Transcriptomic focus: Designed for use with transcriptomic datasets for gene set enrichment comparisons.

Scientific Applications:

• Comparative pathway analysis: Compare enrichment between pathways (for example, glycolysis versus oxidative phosphorylation) under specific conditions such as hypoxia.
• Metabolic state inference in cancer: Predict lactate secretion and intracellular metabolite concentrations (lactate, AMP) in cancer cell lines from transcriptomic data.
• Hypoxia response characterization: Dissect coordinated transcriptional regulation induced by hypoxia.
• Cellular senescence studies: Generate hypotheses about differential metabolic pathway activities during cellular senescence.

Methodology:

Implemented as an R package that quantifies and compares relative enrichment between two gene sets using a statistical methodology and validated on synthetic data.