ReviewNature reviews. Genetics2025
Towards improved fine-mapping of candidate causal variants.
Review in Nature reviews. Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Integrative post-GWAS analysis prioritizes immune regulatory pathways and candidate effector signals in systemic lupus erythematosus.Journal of translational autoimmunity · 2026Article
- Identification and evaluation of 41 risk loci for juvenile idiopathic arthritis informs precision medicine: mechanistic implications of DNA topology and an HLA-A*02:01-ERAP2 interaction.medRxiv : the preprint server for health sciences · 2026Article
- Enhancing detection of polygenic adaptation: a comparative study of machine learning and statistical approaches using simulated evolve-and-resequence data.BMC genomics · 2026Article
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Bridging precision agriculture and human medicine through comparative genetics.Nature reviews. Genetics · 2026Review
- Genetic influences on haematopoiesis.Nature reviews. Genetics · 2026Review
- Multi-ancestry colocalization approaches.PLoS genetics · 2026Article
- Fine-Mapping-Based Variant Prioritization and Genomic Prediction Enhance Genetic Analyses of Teat Traits in Pigs.Animals : an open access journal from MDPI · 2026Article
- Ultra-fast genetic colocalisation across millions of association signals.PLoS genetics · 2026Article
- Urbanisation Drives Microevolution in the Egyptian Fruit Bat (Evolutionary applications · 2026Article
- Decoding Complex Traits in Goats Through Genome-Wide Association Studies: Progress, Challenges, and Perspectives.International journal of molecular sciences · 2026Review
- Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain.bioRxiv : the preprint server for biology · 2026Article
- Article
- ProteoNexus: an integrative database to characterize genetic architecture, estimate mediation effects, and construct and evaluate prediction models of the plasma proteome.Nucleic acids research · 2026Article
- Integrative analysis of GWAS, Bayesian fine-mapping, Mendelian randomization and colocalization reveals genetic determinants underlying milk-related traits in dairy cattle.Genetics, selection, evolution : GSE · 2026Article
- Evolving computational paradigms for noncoding variant pathogenicity prediction.Frontiers in molecular biosciences · 2026Review
- Psoriasis risk allele function in activated Th1/17 cells with "memory" to antigen exposure.PloS one · 2026Article
- Translating Osteoarthritis Genetic Risk Into Biomarkers: Opportunities, Pitfalls, and Implementation Considerations.Human mutation · 2026Review
- Multimodal analysis definesbioRxiv : the preprint server for biology · 2025Article
- Common and rare variant genetic contributions in African Americans with autism.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Fine-mapping in genome-wide association studies aims to identify potentially causal genetic variants among a set of candidate variants that are often highly correlated with each other owing to linkage disequilibrium. A variety of statistical approaches are used in fine-mapping, almost all of which are based on a multiple regression framework to model the relationship between genotype and phenotype, while accommodating specific assumptions about the distribution of variant effect sizes and using different inference algorithms. Owing to their modelling flexibility and the ease of making inferential statements, these approaches are predominantly Bayesian in nature. Recently, these approaches have been improved by refining modelling assumptions, integrating additional information, accommodating summary statistics, and developing scalable computational algorithms that improve computation efficiency and fine-mapping resolution.
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.