SynthesisPLoS computational biology2019
Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE).
Synthesis in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Immunogenomic classification reveals prognostic immune signatures in pediatric solid and hematological tumors.Scientific reports · 2026Article
- Metabolic reprogramming of the neovascular niche promotes regenerative angiogenesis in proliferative retinopathy.Nature communications · 2025Article
- Article
- Aberrant expression of collagen type X in solid tumor stroma is associated with EMT, immunosuppressive and pro-metastatic pathways, bone marrow stromal cell signatures, and poor survival prognosis.bioRxiv : the preprint server for biology · 2024Article
- Dissecting the Distinct Tumor Microenvironments of HRD and HRP Ovarian Cancer: Implications for Targeted Therapies to Overcome PARPi Resistance in HRD Tumors and Refractoriness in HRP Tumors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.Nucleic acids research · 2024Article
- APPLICATION OF QUANTILE DISCRETIZATION AND BAYESIAN NETWORK ANALYSIS TO PUBLICLY AVAILABLE CYSTIC FIBROSIS DATA SETS.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024Article
- Music compensates for altered gene expression in age-related cognitive disorders.Scientific reports · 2023Article
- Article
- Integrating spatial and single-nucleus transcriptomic data elucidates microglial-specific responses in female cynomolgus macaques with depressive-like behaviors.Nature neuroscience · 2023Article
- Tumor collagens predict genetic features and patient outcomes.NPJ genomic medicine · 2023Article
- Article
- TRIB1 regulates tumor growth via controlling tumor-associated macrophage phenotypes and is associated with breast cancer survival and treatment response.Theranostics · 2022Article
- Blood-derived mitochondrial DNA copy number is associated with gene expression across multiple tissues and is predictive for incident neurodegenerative disease.Genome research · 2021Article
- Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults.Journal of immunology (Baltimore, Md. : 1950) · 2020Article
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
Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies.
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.