ReviewHuman molecular genetics2015
Strategies for fine-mapping complex traits.
Review in Human molecular genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 papers, 4 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
128 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- Genetic risk of Spontaneous intracerebral hemorrhage: Systematic review and future directions.Journal of the neurological sciences · 2019Pooled it
- A fine-mapping study of central obesity loci incorporating functional annotation and imputation.European journal of human genetics : EJHG · 2018Pooled it
- Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution.Human molecular genetics · 2017Pooled it
- AI-Guided Long Non-Coding RNA Target Discovery for Precision Medicine: Integrating GWAS, Multi-Omics, Experimental Validation, and RNA Therapeutics.Biomedicines · 2026Review
- From GWAS Signals to Molecular Mechanisms: Explainable AI for Causal Gene Prioritization and Biomolecular Target Interpretation.Biomolecules · 2026Review
- A comparative approach for selecting orthologous candidate genes in genome-wide association studies across multiple species.Plant physiology · 2026Article
- Comparative fine-mapping of breast cancer susceptibility loci using summary statistics methods and multinomial regression.medRxiv : the preprint server for health sciences · 2026Article
- rs2357322 and rs17726078 Contribute to Breast Cancer Risk by Regulating DLX2 Expression.The breast journal · 2026Article
- Towards improved fine-mapping of candidate causal variants.Nature reviews. Genetics · 2025Review
- Fine-mapping methods for complex traits: essential adaptations for samples of related individuals.Briefings in bioinformatics · 2025Article
- fSuSiE enables fine-mapping of QTLs from genome-scale molecular profiles.bioRxiv : the preprint server for biology · 2025Article
- Genome-wide iterative fine-mapping for non-Gaussian phenotypes.Scientific reports · 2025Article
- Recent Advances in Experimental Functional Characterization of GWAS Candidate Genes in Osteoporosis.International journal of molecular sciences · 2025Review
- Performance of deep-learning-based approaches to improve polygenic scores.Nature communications · 2025Article
- Exploring the shared genetic landscape of diabetes and cardiovascular disease: findings and future implications.Diabetologia · 2025Review
- Beyond the Standard GWAS-A Guide for Plant Biologists.Plant & cell physiology · 2025Review
- Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele.Nature communications · 2025Article
- Multivariate Bayesian variable selection for multi-trait genetic fine mapping.Journal of the Royal Statistical Society. Series C, Applied statistics · 2025Article
- Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues.Human genomics · 2025Review
68 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
2 authors.
Funding
Abstract
Genome-wide association studies (GWAS) have identified thousands of robust and replicable genetic associations for complex disease. However, the identification of the causal variants that underlie these associations has been more difficult. This problem of fine-mapping association signals predates GWAS, but the last few years have seen a surge of studies aimed at pinpointing causal variants using both statistical evidence from large association data sets and functional annotations of genetic variants. Combining these two approaches can often determine not only the causal variant but also the target gene. Recent contributions include analyses of custom genotyping arrays, such as the Immunochip, statistical methods to identify credible sets of causal variants and the addition of functional genomic annotations for coding and non-coding variation to help prioritize variants and discern functional consequence and hence the biological basis of disease risk.
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.