GSEA

Overview

Gene Set Enrichment Analysis (GSEA) is a computational method for determining whether a predefined gene set (e.g., a biological pathway, GO term, or curated gene signature) shows statistically significant, concordant differences between two biological states. It uses a ranked gene list (by differential expression, correlation, or other metric) and calculates an enrichment score for each gene set, testing for nonrandom distribution of the set’s genes within the ranked list. GSEA is widely used for pathway-level interpretation of transcriptomic data and for cross-dataset comparison of gene expression programs.

Used by

  • GSEA of 486 fulvestrant-responsive differentially expressed genes in Nf1Indel rat mammary tumors showed significant enrichment of genes induced by neoadjuvant letrozole (GSE5462) and fulvestrant (GSE71791) in patient datasets; 58-gene overlap included PGR, AREG, SGK3, and other ER-response genes, validating cross-species transcriptome concordance. PMID:26437033
  • Used to compare gene expression between long-fusion (breakpoint after exon 11) and short-fusion (exons 8/9) MYBL1/MYB ACC subsets; identified 19 gene sets enriched in long fusions (RNA processing/translation) and 5 in short fusions (tissue development) PMID:26631609.
  • Used (alongside GSVA) with MSigDB C2/C6/C7 gene sets to identify the IPRES co-enriched transcriptional resistance program in anti-PD-1-treated metastatic melanoma PMID:26997480
  • Used to evaluate enrichment of a YAP/TAZ transcriptional signature in NF2-loss vs NF2-WT uRCC, confirming Hippo pathway dysregulation in the NF2-loss subset. PMID:27713405
  • Applied over REACTOME pathways to identify clonal enrichment in post-chemotherapy urothelial carcinoma tumours; highlighted L1CAM (OR=1.9, FDR=0.12) and integrin signaling (OR=2.8, FDR=0.02) as candidate resistance pathways. PMID:27749842
  • Applied to CCA methylation data showing both Cluster 1 and Cluster 4 hypermethylation target PRC2 pathway gene sets (at CpG islands vs CpG shores respectively), and to transcriptome data for immune-pathway characterization across the four clusters PMID:28667006
  • Applied to TCGA PRAD ranked by NOL10 expression; E2F targets and G2M checkpoint ranked as top hallmarks. Also applied to RNA-seq of NOL10-knockdown LNCaP, identifying 71 downregulated genes enriched in cell-cycle processes PMID:28927585
  • GSEA used with IPA for pathway analysis of DEGs between on-therapy responders and non-responders in 45 melanoma RNA-seq samples; enriched pathways included PD-1 signaling, IFN-γ, IL-2, and TCR signaling PMID:29033130
  • GSEA of PBAF-complex-perturbed A704 CCRCC cells and PBRM1-LOF tumors revealed enrichment of IL6/JAK-STAT3, TNF-α/NF-κB, hypoxia, and cytokine-cytokine receptor gene sets (top hit FWER q=0.002) PMID:29301960
  • GSEA against MSigDB Hallmark gene sets used to correlate arm-level aneuploidy with expression programs; revealed positive enrichment for E2F targets, G2M checkpoint, and mitotic spindle hallmarks, and negative enrichment for immune signatures after controlling for leukocyte fraction PMID:29622463

Notes

  • Standard GSEA uses a Kolmogorov-Smirnov-like statistic with permutation-based FDR correction (Subramanian et al. 2005).
  • MSigDB (Molecular Signatures Database) is the primary curated gene set library used with GSEA.
  • Pre-ranked GSEA (fgsea/GSEA Preranked) is commonly used when the ranked list is derived from an external statistic (e.g., DESeq2 Wald statistic).

Sources

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This page was processed by entity-page-writer on 2026-05-15. - PMID:27713405

This page was processed by entity-page-writer on 2026-05-15. - PMID:27749842

This page was processed by entity-page-writer on 2026-05-15. - PMID:28667006

This page was processed by entity-page-writer on 2026-05-15. - PMID:28927585

This page was processed by entity-page-writer on 2026-05-15. - PMID:29033130

This page was processed by entity-page-writer on 2026-05-15. - PMID:29301960

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