ArticleGenetic epidemiology2011
Defining the power limits of genome-wide association scan meta-analyses.
Article in Genetic epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genetic Influences on Patient-Oriented Outcomes in Traumatic Brain Injury: A Living Systematic Review of Non-Apolipoprotein E Single-Nucleotide Polymorphisms.Journal of neurotrauma · 2021Pooled it
- How do stochastic processes and genetic threshold effects explain incomplete penetrance and inform causal disease mechanisms?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Meta-analysis of genome-wide association studies reveal common loci controlling agronomic and quality traits in a wide range of normal and heat stressed environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Sport and exercise genomics: the FIMS 2019 consensus statement update.British journal of sports medicine · 2020Article
- Genome-wide association analysis identifies a meningioma risk locus at 11p15.5.Neuro-oncology · 2018Article
- Common polygenic variation and risk for childhood-onset schizophrenia.Molecular psychiatry · 2016Article
- Statistical and Computational Methods for Genetic Diseases: An Overview.Computational and mathematical methods in medicine · 2015Review
- Detecting a weak association by testing its multiple perturbations: a data mining approach.Scientific reports · 2014Article
- Meta-analysis methods for genome-wide association studies and beyond.Nature reviews. Genetics · 2013Review
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
Large-scale meta-analyses of genome-wide association scans (GWAS) have been successful in discovering common risk variants with modest and small effects. The detection of lower frequency signals will undoubtedly require concerted efforts of at least similar scale. We investigate the sample size-dictated power limits of GWAS meta-analyses, in the presence and absence of modest levels of heterogeneity and across a range of different allelic architectures. We find that data combination through large-scale collaboration is vital in the quest for complex trait susceptibility loci, but that effect size heterogeneity across meta-analyzed studies drawn from similar populations does not appear to have a profound effect on sample size requirements.
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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.