ArticleNature protocols2019
Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap.
Article in Nature protocols, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,208 papers, 4 of them syntheses that pooled it.
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Who cites it
1,208 citing papers in PubMed, 4 syntheses or guidelines pooled it.
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- Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review.Journal of translational medicine · 2025Pooled it
- Predictive enrichment using biomarkers in studies of critically-ill patients with sepsis: a systematic review.Critical care (London, England) · 2025Pooled it
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- Medicinal cannabis plant extract (NTI164) modifies epigenetic, ribosomal, and immune pathways in paediatric acute-onset neuropsychiatric syndrome.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Trial
- The molecular heterogeneity and clinical impact of genomic driver alterations in prostate cancer.Nature communications · 2026Article
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
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- MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi-Omics Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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- An NLRP3 inflammasome-anchored Astragalus mechanistic prior yields a mortality-associated transcriptomic signal in ICU sepsis: a secondary analysis with exploratory cross-cohort assessment.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Article
- Multi-omics integration uncovers epigenetic control of metabolic reprogramming in triple-negative breast cancer.Journal of the Egyptian National Cancer Institute · 2026Article
1,148 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
Pathway enrichment analysis helps researchers gain mechanistic insight into gene lists generated from genome-scale (omics) experiments. This method identifies biological pathways that are enriched in a gene list more than would be expected by chance. We explain the procedures of pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists resulting from RNA-seq and genome-sequencing experiments. The protocol comprises three major steps: definition of a gene list from omics data, determination of statistically enriched pathways, and visualization and interpretation of the results. We describe how to use this protocol with published examples of differentially expressed genes and mutated cancer genes; however, the principles can be applied to diverse types of omics data. The protocol describes innovative visualization techniques, provides comprehensive background and troubleshooting guidelines, and uses freely available and frequently updated software, including g:Profiler, Gene Set Enrichment Analysis (GSEA), Cytoscape and EnrichmentMap. The complete protocol can be performed in ~4.5 h and is designed for use by biologists with no prior bioinformatics training.
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