ArticlePLoS computational biology2022
Urgent need for consistent standards in functional enrichment analysis.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.
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68 citing papers in PubMed.
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- Integrated network pharmacology, transcriptomics and proteomics unveils the mechanisms of Forsythiae Fructus against acute lung injury.Die Naturwissenschaften · 2026Article
- Proteome-Level Autophagy-Lysosome Remodelling Marks Ageing in Human Dermal Fibroblasts and Nominates Hydroxytyrosol as a Candidate Nutraceutical.International journal of molecular sciences · 2026Article
- Integrative proteogenomic analyses identify plasma proteins that impact the risk of ischemic stroke.Communications medicine · 2026Article
- Large-Scale Genomics Reveals Three-Source Ancestry and Layered Adaptation to High Altitude in Tibetan Chickens.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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- The dynamic expression pattern of signaling pathways involved in early embryo development.Cell communication and signaling : CCS · 2026Article
- A Ponatinib-Associated Transcriptomic Signature: Implications for Cardiovascular Toxicity.International journal of molecular sciences · 2026Article
- Confidence: a web app for cross-platform differential gene expression analysis, gene scoring, and enrichment analysis.Scientific reports · 2026Article
- Article
- Ten common mistakes that could ruin your enrichment analysis.PLoS computational biology · 2026Article
- RCDRank: a web server to prioritize regulated cell death modalities.BMC bioinformatics · 2026Article
- Functional Divergence of the Arg/N-Degron Pathway Between the CropPlant direct · 2026Article
- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- Concordant Shared Transcriptomic Signatures and Candidate Regulatory Features in Chronic Lymphocytic Leukemia and Multiple Myeloma.Oncology research · 2026Article
- Benchmarking multiple gene ontology enrichment tools reveals high biological significance, ranking, and stringency heterogeneity among datasets.Frontiers in bioinformatics · 2026Article
8 more citing papers are in PubMed but not listed here.
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene set enrichment tests (a.k.a. functional enrichment analysis) are among the most frequently used methods in computational biology. Despite this popularity, there are concerns that these methods are being applied incorrectly and the results of some peer-reviewed publications are unreliable. These problems include the use of inappropriate background gene lists, lack of false discovery rate correction and lack of methodological detail. To ascertain the frequency of these issues in the literature, we performed a screen of 186 open-access research articles describing functional enrichment results. We find that 95% of analyses using over-representation tests did not implement an appropriate background gene list or did not describe this in the methods. Failure to perform p-value correction for multiple tests was identified in 43% of analyses. Many studies lacked detail in the methods section about the tools and gene sets used. An extension of this survey showed that these problems are not associated with journal or article level bibliometrics. Using seven independent RNA-seq datasets, we show misuse of enrichment tools alters results substantially. In conclusion, most published functional enrichment studies suffered from one or more major flaws, highlighting the need for stronger standards for enrichment analysis.
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