ArticleBioData mining2018
Gene set analysis methods: a systematic comparison.
Article in BioData mining, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis 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
57 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-Thermal Effects of Terahertz Radiation on Gene Expression: Systematic Review and Meta-Analysis.Genes · 2024Pooled it
- Cell type-specific contextualisation of the human phenome: towards the systematic treatment of all rare diseases.Genome medicine · 2026Article
- Helminth infection induces RELMα-dependent adipose tissue transcriptional reprogramming and protection against diet-induced obesity.bioRxiv : the preprint server for biology · 2026Article
- Donor-dependent immunomodulatory effects of human dental pulp stem cells on macrophages.Frontiers in immunology · 2026Article
- Bone matrix-mimetic multi-ion doped hydroxyapatite nanorod arrays for enhanced immuno-osteogenesis and prevention of aseptic loosening.Bioactive materials · 2026Article
- mLeveraging genetic correlations to prioritize drug groups for repurposing in type 2 diabetes.The pharmacogenomics journal · 2025Article
- Host Transcriptomics Reveal Reduction in Defence-Reproduction Trade-Offs During Coinfection.Molecular ecology · 2025Article
- Red-Wine Gene Networks Linked to Exceptional Longevity in Humans.Biomolecules · 2025Review
- Revealing genetic drivers of ovarian cancer and chemoresistance: insights from whole-genome CRISPR-knockout library screens.Cellular oncology (Dordrecht, Netherlands) · 2025Review
- Article
- Analysis of the cross-study replicability of tuberculosis gene signatures using 49 curated human transcriptomic datasets.Tuberculosis (Edinburgh, Scotland) · 2025Article
- Statistical properties of functional connectivity MRI enrichment analysis in school-age autism research.Developmental cognitive neuroscience · 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
- Transcriptomic Analysis of Blood Collagen-Induced Arthritis Mice Exposed to 0.1 THz Reveals Inhibition of Genes and Pathways Involved in Rheumatoid Arthritis.International journal of molecular sciences · 2024Article
- Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.iScience · 2024Article
- Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics.NeuroImage · 2024Article
- Article
- Tiny Guides, Big Impact: Focus on the Opportunities and Challenges of miR-Based Treatments for ARDS.International journal of molecular sciences · 2024Review
- Robustness evaluations of pathway activity inference methods on gene expression data.BMC bioinformatics · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundGene set analysis is a valuable tool to summarize high-dimensional gene expression data in terms of biologically relevant sets. This is an active area of research and numerous gene set analysis methods have been developed. Despite this popularity, systematic comparative studies have been limited in scope.
methodsIn this study we present a semi-synthetic simulation study using real datasets in order to test and compare commonly used methods.
resultsA software pipeline, Flexible Algorithm for Novel Gene set Simulation (FANGS) develops simulated data based on a prostate cancer dataset where the KRAS and TGF-β pathways were differentially expressed. The FANGS software is compatible with other datasets and pathways. Comparisons of gene set analysis methods are presented for Gene Set Enrichment Analysis (GSEA), Significance Analysis of Function and Expression (SAFE), sigPathway, and Correlation Adjusted Mean RAnk (CAMERA) methods. All gene set analysis methods are tested using gene sets from the MSigDB knowledge base. The false positive rate and power are estimated and presented for comparison. Recommendations are made for the utility of the default settings of methods and each method's sensitivity towards various effect sizes.
conclusionsThe results of this study provide empirical guidance to users of gene set analysis methods. The FANGS software is available for researchers for continued methods comparisons.
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.