ArticleGenomics, proteomics & bioinformatics2023
simplifyEnrichment: A Bioconductor Package for Clustering and Visualizing Functional Enrichment Results.
Article in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 172 papers, 4 of them syntheses that pooled it.
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Who cites it
172 citing papers in PubMed, 4 syntheses or guidelines pooled it.
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- Meta-analysis towards FSHD reveals misregulation of neuromuscular junction, nuclear envelope, and spliceosome.Communications biology · 2024Pooled it
- Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans.BMC microbiology · 2024Pooled it
- Faster and smaller: Heterochronic shift in gene expression leads to larval onset of spermatogenesis and miniaturized males.iScience · 2026Article
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
- Transposable elements as evolutionary catalysts of ant macrodiversity.Science advances · 2026Article
- MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi-Omics Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Proteome analyses reveal endoplasmic reticulum stress-induced changes in protein abundance associated with Ube2j2 deficiency in human cell culture.G3 (Bethesda, Md.) · 2026Article
- Multimodal protective and susceptibility clusters in paediatric atopic dermatitis: A machine learning-based, data-driven observational study.PLoS medicine · 2026Observational
- Blood-derived microRNA signatures associated with hippocampal structure and atrophy rate: findings from the Rhineland Study.Molecular psychiatry · 2026Article
- Neuroinflammation as molecular landscape of post-operative delirium revealed by live human brain multi-omics profiling.Molecular psychiatry · 2026Article
- Neuroinflammatory suppression of astrocytic BMAL1 defines a selective reactive astrocyte program.Journal of neuroinflammation · 2026Article
- ClusterGVis: An Advanced Visualization and Clustering Tool for Gene Expression Analysis.Genomics, proteomics & bioinformatics · 2026Article
- Spatial architecture of autism pathogenesis reveals mosaic structural disarray during early development.Nature communications · 2026Article
- Recent Polygenic Adaptation in Heavily Fished Malawi Cichlids.Molecular ecology · 2026Article
- NAT10 maintains stem cell homeostasis by mitigating mRNA decay through an acNature cell biology · 2026Article
- Distinct epigenetic alterations and accelerated mitotic aging define second primary breast cancers.Scientific reports · 2026Article
- Integrated lipidome and miRNome analyses reveal sex-based differences in circulating extracellular vesicles of alcohol use disorder patients.Cell biology and toxicology · 2026Article
- H3K9me3 controls epidermis morphogenesis by regulating RNA Pol II dynamics at developmental promoters and enhancers.Nature communications · 2026Article
112 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Functional enrichment analysis or gene set enrichment analysis is a basic bioinformatics method that evaluates the biological importance of a list of genes of interest. However, it may produce a long list of significant terms with highly redundant information that is difficult to summarize. Current tools to simplify enrichment results by clustering them into groups either still produce redundancy between clusters or do not retain consistent term similarities within clusters. We propose a new method named binary cut for clustering similarity matrices of functional terms. Through comprehensive benchmarks on both simulated and real-world datasets, we demonstrated that binary cut could efficiently cluster functional terms into groups where terms showed consistent similarities within groups and were mutually exclusive between groups. We compared binary cut clustering on the similarity matrices obtained from different similarity measures and found that semantic similarity worked well with binary cut, while similarity matrices based on gene overlap showed less consistent patterns. We implemented the binary cut algorithm in the R package simplifyEnrichment, which additionally provides functionalities for visualizing, summarizing, and comparing the clustering. The simplifyEnrichment package and the documentation are available at https://bioconductor.org/packages/simplifyEnrichment/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.