SynthesisNature genetics2023
CARMA is a new Bayesian model for fine-mapping in genome-wide association meta-analyses.
Synthesis in Nature genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 5 of them syntheses that pooled it.
What it found
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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
63 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Pooled it
- Multi-ancestry genome-wide association analyses of refractive error augment genetic discovery and polygenic prediction.Nature genetics · 2026Pooled it
- Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation.Nature communications · 2025Pooled it
- Cross-Phenotype Genome-Wide Association Study on the Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.Arthritis & rheumatology (Hoboken, N.J.) · 2025Pooled it
- Gene-level analysis reveals the genetic aetiology and therapeutic targets of schizophrenia.Nature human behaviour · 2025Pooled it
- Genetic evidence and cross-species functional characterization implicateProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Genome-wide association study of sarcopenia index reveals sex-stratified genetic architecture.Biology of sex differences · 2026Article
- Molecular regulatory mechanisms of schizophrenia-associated functional non-coding variants.Molecular psychiatry · 2026Article
- From GWAS Signals to Molecular Mechanisms: Explainable AI for Causal Gene Prioritization and Biomolecular Target Interpretation.Biomolecules · 2026Review
- CIT-Lasso: a scalable approach beyond guilty by association for identifying causal variants from genome-wide summary statistics.Genome biology · 2026Article
- Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage.Journal of the American Statistical Association · 2026Article
- Article
- Common Coronary Artery Disease Risk Variants in Endothelial Regulatory Elements Modulate Tetraspanin 14 Expression and Notch Signaling.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- Leveraging cell-type specificity and similarity improves single-cell eQTL fine-mapping.Nature communications · 2026Article
- Genome-wide fine-mapping improves identification of causal variants.Nature genetics · 2026Article
- Genome-Wide Discovery Reveals Adipose-Specific and Systemic Regulators of Insulin Resistance.medRxiv : the preprint server for health sciences · 2026Article
- Decoding Complex Traits in Goats Through Genome-Wide Association Studies: Progress, Challenges, and Perspectives.International journal of molecular sciences · 2026Review
- Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
3 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
9 authors.
Funding
Abstract
Fine-mapping is commonly used to identify putative causal variants at genome-wide significant loci. Here we propose a Bayesian model for fine-mapping that has several advantages over existing methods, including flexible specification of the prior distribution of effect sizes, joint modeling of summary statistics and functional annotations and accounting for discrepancies between summary statistics and external linkage disequilibrium in meta-analyses. Using simulations, we compare performance with commonly used fine-mapping methods and show that the proposed model has higher power and lower false discovery rate (FDR) when including functional annotations, and higher power, lower FDR and higher coverage for credible sets in meta-analyses. We further illustrate our approach by applying it to a meta-analysis of Alzheimer's disease genome-wide association studies where we prioritize putatively causal variants and genes.
Indexed as
Identifiers
37169873What 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.