ReviewFrontiers in genetics2020
Gene Set Analysis: Challenges, Opportunities, and Future Research.
Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 151 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
151 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- A Cross-Species and Sex-Specific Meta-Analysis of Transcriptomic Studies of Pulmonary Hypertension.American journal of respiratory cell and molecular biology · 2025Pooled it
- A Practical Guideline for MicroRNA Sequencing Data Analysis in Chronic Lymphocytic Leukemia.Methods in molecular biology (Clifton, N.J.) · 2025Guideline
- Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets.Journal of human genetics · 2023Pooled it
- Genome-Wide Gene-Set Analysis Identifies Molecular Mechanisms Associated with ALS.International journal of molecular sciences · 2023Pooled it
- Random-effects meta-analysis of effect sizes as a unified framework for gene set analysis.PLoS computational biology · 2022Pooled it
- New Insights on the Regulatory Gene Network Disturbed in Central Areolar Choroidal Dystrophy-Beyond Classical Gene Candidates.Frontiers in genetics · 2022Pooled it
- Tumour microenvironment characterisation to stratify patients for hyperthermic intraperitoneal chemotherapy in high-grade serous ovarian cancer (OVHIPEC-1).British journal of cancer · 2024Trial
- Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.Molecular ecology · 2026Article
- Ephedrae Herba-Associated Adverse Events: A Disproportionality Analysis Integrated with Network Pharmacology.Pharmaceuticals (Basel, Switzerland) · 2026Article
- The molecular ICU: a primer on omics, informatics and the future of precision critical care.Critical care (London, England) · 2026Review
- BrainEnrich: Revealing Biological Insights for Imaging-Derived Phenotypes Through Transcriptomic Enrichment.Human brain mapping · 2026Article
- Cell type-specific contextualisation of the human phenome: towards the systematic treatment of all rare diseases.Genome medicine · 2026Article
- Multi-Bioinformatics Approach Reveals COX5B-Mediated Modulation of Oxidative Phosphorylation and ROS Levels by Water and Ethanol Extracts of Schisandrae Fructus in SW1783 Cells.Antioxidants (Basel, Switzerland) · 2026Article
- Spatial transcriptomics implicates the thalamus and cortex in autism and schizophrenia.bioRxiv : the preprint server for biology · 2026Article
- MEAST: a novel framework for analyzing gene set stability in single cell transcriptomics.Scientific reports · 2026Article
- Gain-of-function mutation inbioRxiv : the preprint server for biology · 2026Article
- From SNPs to pathways: a genome-wide benchmark of annotation discrepancies and their impact on protein- and pathway-level inference.BMC genomics · 2026Article
- Testing for Network Specificity in Brain-Behavior Associations Using Ordinal Dominance Curves.Human brain mapping · 2026Article
- ImmuSeeker: deep mining of immune-related gene family signatures through lineage reconstruction.Genome biology · 2026Article
- Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.iScience · 2026Article
91 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene set analysis methods are widely used to provide insight into high-throughput gene expression data. There are many gene set analysis methods available. These methods rely on various assumptions and have different requirements, strengths and weaknesses. In this paper, we classify gene set analysis methods based on their components, describe the underlying requirements and assumptions for each class, and provide directions for future research in developing and evaluating gene set analysis methods.
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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.