ArticleCommunications biology2024
GOAT: efficient and robust identification of gene set enrichment.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
- Integrated network pharmacology, transcriptomics and proteomics unveils the mechanisms of Forsythiae Fructus against acute lung injury.Die Naturwissenschaften · 2026Article
- Proteomics of post mortem brains in early- and late-onset Alzheimer's disease: Unraveling differential Aβ effects and potential AD biomarkers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- GOATEA: gene set enrichment analysis in R with shiny interactive visualizations.BMC bioinformatics · 2026Article
- Article
- Spatial Gene Set Enrichment Analysis with Applications to Spatially Resolved Transcriptomic Data.bioRxiv : the preprint server for biology · 2026Article
- RCDRank: a web server to prioritize regulated cell death modalities.BMC bioinformatics · 2026Article
- Proinflammatory and cytotoxic CD38American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2026Article
- Human brain prefrontal cortex proteomics identifies compromised energy metabolism and neuronal function in Schizophrenia.Nature communications · 2026Article
- Multi-Component Synergy in Hepatic Trauma Repair: Network Pharmacology and Molecular Docking Decipher Panax Notoginseng's PI3K-Akt Pathway Activation.Current pharmaceutical design · 2026Article
- One-step induction of human GABAergic neurons promotes presynaptic development & synapse maturation.bioRxiv : the preprint server for biology · 2025Article
- TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool.Briefings in bioinformatics · 2025Article
- GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis.BMC bioinformatics · 2025Article
- Uterine sarcoma with KAT6B/A::KANSL1 fusion: a molecular and clinicopathological study on 9 cases.Virchows Archiv : an international journal of pathology · 2025Article
- Molecular profiling of skin cells identifies distinct cellular signatures in radiation-induced skin injury across various stages in the murine dataset.Experimental hematology & oncology · 2025Article
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1 author.
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Abstract
Gene set enrichment analysis is foundational to the interpretation of high throughput biology. Identifying enriched Gene Ontology (GO) terms or disease-associated gene sets within a list of gene effect sizes that represent experimental outcomes is an everyday task in life science that crucially depends on robust and sensitive statistical tools. We here present GOAT, a parameter-free algorithm for gene set enrichment analysis of preranked gene lists. The algorithm can precompute null distributions from standardized gene scores, enabling enrichment testing of the GO database in one second. Validations using synthetic data show that estimated gene set p-values are well calibrated under the null hypothesis and invariant to gene list length and gene set size. Application to various real-world proteomics and gene expression studies demonstrates that GOAT identifies more significant GO terms as compared to current methods. GOAT is freely available as an R package and user-friendly online tool for gene set enrichment analyses that includes interactive data visualizations: https://ftwkoopmans.github.io/goat .
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