ReviewAmerican journal of human genetics2010
Prioritizing GWAS results: A review of statistical methods and recommendations for their application.
Review in American journal of human genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 334 papers, 8 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
334 citing papers in PubMed, 8 syntheses or guidelines pooled it.
- Evidence for penetrance in patients without a family history of disease: a systematic review.European journal of human genetics : EJHG · 2020Pooled it
- Design and methodology challenges of environment-wide association studies: A systematic review.Environmental research · 2020Pooled it
- A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis.Nature communications · 2019Pooled it
- Mitochondrial DNA variants and pulmonary function in older persons.Experimental gerontology · 2019Pooled it
- Meta-analysis identifies mitochondrial DNA sequence variants associated with walking speed.GeroScience · 2018Pooled it
- Genome-wide association study meta-analysis identifies five new loci for systemic lupus erythematosus.Arthritis research & therapy · 2018Pooled it
- A meta-analytic framework for detection of genetic interactions.Genetic epidemiology · 2016Pooled it
- Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers.Brain imaging and behavior · 2014Pooled it
- Turbocharging crop breeding with integrated biotechnology for a climate-resilient future.Journal of integrative plant biology · 2026Review
- SNPWay: streamlined SNP-to-function and pathway over-representation analysis.bioRxiv : the preprint server for biology · 2026Article
- Genome-wide association study and pathway analysis of healthy aging in Super Seniors.GeroScience · 2026Article
- From SNPs to pathways: a genome-wide benchmark of annotation discrepancies and their impact on protein- and pathway-level inference.BMC genomics · 2026Article
- From SNPs to Pathways: A genome-wide benchmark of annotation discrepancies and their impact on protein- and pathway-level inference.bioRxiv : the preprint server for biology · 2026Article
- A resource of "bottom-line" variant associations for 1,281 complex traits by integrating data across published genome-wide association studies.Research square · 2026Article
- PROVGEN: A Privacy-Preserving Approach for Outcome Validation in Genomic Research.Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium · 2026Article
- Refining mechanistic models of hallucinations for enhanced translatability.Translational psychiatry · 2025Review
- Super-silencers are crucial for development and carcinogenesis in B cells.Nature communications · 2025Article
- Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample.Drug and alcohol dependence · 2025Article
- Review
- Challenges and opportunities for omics-based precision medicine in chronic low back pain.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Review
274 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
3 authors.
Funding
Abstract
Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the GWAS provide preliminary genetic information that is available for additional analysis by statistical procedures that accumulate evidence, and that these secondary analyses are very likely to provide valuable information that will help prioritize the strongest constellations of results. We review and discuss three analytic methods to combine preliminary GWAS statistics to identify genes, alleles, and pathways for deeper investigations. Meta-analysis seeks to pool information from multiple GWAS to increase the chances of finding true positives among the false positives and provides a way to combine associations across GWAS, even when the original data are unavailable. Testing for epistasis within a single GWAS study can identify the stronger results that are revealed when genes interact. Pathway analysis of GWAS results is used to prioritize genes and pathways within a biological context. Following a GWAS, association results can be assigned to pathways and tested in aggregate with computational tools and pathway databases. Reviews of published methods with recommendations for their application are provided within the framework for each approach.
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.