ReviewBriefings in bioinformatics2022
On the influence of several factors on pathway enrichment analysis.
Review in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
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- Cross-Omic Comparative Analysis Identifies Transcriptomic Signatures and Exploratory Gene Set-Level Signals in Sporadic Creutzfeldt-Jakob Disease.International journal of molecular sciences · 2026Article
- Analytical Methods and Application of Single-Cell and Single-Nucleus Transcriptomics in the Study of Ischemic Stroke.Biomolecules · 2026Review
- In silico analysis of gene expression signatures and drug repurposing associated with metastatic progression in melanoma (skin cancer).Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Review
- Blood-based proteomic signature of amyloidosis: identification of novel regulators of amyloid load.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Continuous multi-omics pathway enrichment analysis resolves hidden functional heterogeneity.Briefings in bioinformatics · 2026Article
- A Ponatinib-Associated Transcriptomic Signature: Implications for Cardiovascular Toxicity.International journal of molecular sciences · 2026Article
- The complexome contextualizes proteomics data to fingerprint biological states and highlight perturbed functional modules in disease.NPJ systems biology and applications · 2026Article
- Ten common mistakes that could ruin your enrichment analysis.PLoS computational biology · 2026Article
- Preliminary insights into methylation patterns in Agent Orange exposed thyroid cancers: a pilot study.Environmental pollution (Barking, Essex : 1987) · 2026Article
- Shared genetic architecture between Parkinson's disease and self-reported sleep-related traits implicates theSleep advances : a journal of the Sleep Research Society · 2026Article
- SeqExpressionAnalyser: An R Package for Automated End-to-End RNA-Seq Analysis From Reads to Differential Expression.Bioinformatics and biology insights · 2026Article
- Hemispheric Asymmetry in the Genetic Overlap between Schizophrenia and White Matter Microstructure.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- A dual approach to evaluate the performance of RNA-Seq data analysis pipelines with weak signals.Bioinformatics advances · 2026Article
- Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics.Bioactive materials · 2025Review
- Synaptic proteome diversity is shaped by the levels of glutamate receptors and their regulatory proteins.Nature communications · 2025Article
- Optimized murine sample sizes for RNA sequencing studies revealed from large scale comparative analysis.Nature communications · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathway enrichment analysis has become a widely used knowledge-based approach for the interpretation of biomedical data. Its popularity has led to an explosion of both enrichment methods and pathway databases. While the elegance of pathway enrichment lies in its simplicity, multiple factors can impact the results of such an analysis, which may not be accounted for. Researchers may fail to give influential aspects their due, resorting instead to popular methods and gene set collections, or default settings. Despite ongoing efforts to establish set guidelines, meaningful results are still hampered by a lack of consensus or gold standards around how enrichment analysis should be conducted. Nonetheless, such concerns have prompted a series of benchmark studies specifically focused on evaluating the influence of various factors on pathway enrichment results. In this review, we organize and summarize the findings of these benchmarks to provide a comprehensive overview on the influence of these factors. Our work covers a broad spectrum of factors, spanning from methodological assumptions to those related to prior biological knowledge, such as pathway definitions and database choice. In doing so, we aim to shed light on how these aspects can lead to insignificant, uninteresting or even contradictory results. Finally, we conclude the review by proposing future benchmarks as well as solutions to overcome some of the challenges, which originate from the outlined factors.
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