ArticleBMC bioinformatics2017
Ranking metrics in gene set enrichment analysis: do they matter?
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 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
38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 80 citations in OpenAlex.
- Oligoprotein type I interferon signatures, but not TREX1 variants, increase risk of systemic lupus erythematosus in UK Biobank.Nature communications · 2026Pooled it
- Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae.NPJ systems biology and applications · 2022Pooled it
- Random-effects meta-analysis of effect sizes as a unified framework for gene set analysis.PLoS computational biology · 2022Pooled it
- Analytical Methods and Application of Single-Cell and Single-Nucleus Transcriptomics in the Study of Ischemic Stroke.Biomolecules · 2026Review
- SOPA and SIMPA: normalized single-sample integrated multiomics pathway analysis of tumor heterogeneity in solid cancers.Briefings in bioinformatics · 2026Article
- Acid Ceramidase Inhibition Disrupts Ceramide Homeostasis and Induces Mitochondrial Apoptosis in IDH1-Mutant Oligodendroglioma.Research square · 2026Article
- Proteomic Profile of Ischemic Heart Disease in Heart Failure: A Community Study.Mayo Clinic proceedings · 2025Article
- Replicability of bulk RNA-Seq differential expression and enrichment analysis results for small cohort sizes.PLoS computational biology · 2025Article
- Variable Gene Copy Number in Cancer-Related Pathways Is Associated With Cancer Prevalence Across Mammals.Molecular biology and evolution · 2025Article
- Gene Set Enrichment Analysis in Zebrafish Embryos Is Susceptible to False-Positive Results in the Absence of Differentially Expressed Genes.Bioinformatics and biology insights · 2025Article
- Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results.Nucleic acids research · 2024Article
- Clinical and CSF single-cell profiling of post-COVID-19 cognitive impairment.Cell reports. Medicine · 2024Article
- Generalized reporter score-based enrichment analysis for omics data.Briefings in bioinformatics · 2024Article
- Chromatin activity identifies differential gene regulation across human ancestries.Genome biology · 2024Article
- D-Allulose Ameliorates Dysregulated Macrophage Function and Mitochondrial NADH Homeostasis, Mitigating Obesity-Induced Insulin Resistance.Nutrients · 2023Article
- Expression-based subtypes define pathologic response to neoadjuvant immune-checkpoint inhibitors in muscle-invasive bladder cancer.Nature communications · 2023Article
- The hitchhikers' guide to RNA sequencing and functional analysis.Briefings in bioinformatics · 2023Article
- Delving into gene-set multiplex networks facilitated by a k-nearest neighbor-based measure of similarity.Computational and structural biotechnology journal · 2023Article
- Cellular stress promotes NOD1/2-dependent inflammation via the endogenous metabolite sphingosine-1-phosphate.The EMBO journal · 2021Article
- GeneWalk identifies relevant gene functions for a biological context using network representation learning.Genome biology · 2021Article
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 at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere exist many methods for describing the complex relation between changes of gene expression in molecular pathways or gene ontologies under different experimental conditions. Among them, Gene Set Enrichment Analysis seems to be one of the most commonly used (over 10,000 citations). An important parameter, which could affect the final result, is the choice of a metric for the ranking of genes. Applying a default ranking metric may lead to poor results. METHODS AND
resultsIn this work 28 benchmark data sets were used to evaluate the sensitivity and false positive rate of gene set analysis for 16 different ranking metrics including new proposals. Furthermore, the robustness of the chosen methods to sample size was tested. Using k-means clustering algorithm a group of four metrics with the highest performance in terms of overall sensitivity, overall false positive rate and computational load was established i.e. absolute value of Moderated Welch Test statistic, Minimum Significant Difference, absolute value of Signal-To-Noise ratio and Baumgartner-Weiss-Schindler test statistic. In case of false positive rate estimation, all selected ranking metrics were robust with respect to sample size. In case of sensitivity, the absolute value of Moderated Welch Test statistic and absolute value of Signal-To-Noise ratio gave stable results, while Baumgartner-Weiss-Schindler and Minimum Significant Difference showed better results for larger sample size. Finally, the Gene Set Enrichment Analysis method with all tested ranking metrics was parallelised and implemented in MATLAB, and is available at https://github.com/ZAEDPolSl/MrGSEA .
conclusionsChoosing a ranking metric in Gene Set Enrichment Analysis has critical impact on results of pathway enrichment analysis. The absolute value of Moderated Welch Test has the best overall sensitivity and Minimum Significant Difference has the best overall specificity of gene set analysis. When the number of non-normally distributed genes is high, using Baumgartner-Weiss-Schindler test statistic gives better outcomes. Also, it finds more enriched pathways than other tested metrics, which may induce new biological discoveries.
Indexed as
Identifiers
What OpenQuestion holds
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.