ArticleHeredity2019
Statistical power in genome-wide association studies and quantitative trait locus mapping.
Article in Heredity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 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.
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Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it, 96 citations in OpenAlex.
- Genome-Wide Association Study Meta-Analysis Elucidates Genetic Structure and Identifies Candidate Genes of Teat Number Traits in Pigs.International journal of molecular sciences · 2023Pooled it
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- Genomic loci associated with Fusarium stalk rot resistance and related agronomic traits in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Expanded chromatin accessibility mapping explains genetic variation associated with complex traits in liver.American journal of human genetics · 2026Article
- Review
- Robust replication of associations across patient-mediated and provider-sourced EHR data in thenpj digital public health · 2026Article
- Expanded Chromatin Accessibility Mapping Explains Genetic Variation Associated with Complex Traits in Liver.medRxiv : the preprint server for health sciences · 2025Article
- Mitochondrial Gene Regulation and Pain Susceptibility: A Multi-Omics Causal Inference Study.International journal of molecular sciences · 2025Article
- Merging traditional practices and modern technology through computational plant breeding.Plant physiology · 2025Review
- H3K27me3-mediated epigenetic regulation of TET1 in the eutopic endometrium of women with endometriosis and infertility.Scientific reports · 2025Article
- Review
- Crop wild relative populations of Beta vulgaris as source for genome-wide association mapping of complex traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genome-Wide Association Study for Weight-Related Traits inAnimals : an open access journal from MDPI · 2025Article
- Development of a cost-effective high-throughput mid-density 5K genotyping assay for germplasm characterization and breeding in groundnut.The plant genome · 2025Article
- PlasmaCancer biology & medicine · 2025Article
- Genomic Selection for Pea Grain Yield and Protein Content in Italian Environments for Target and Non-Target Genetic Bases.International journal of molecular sciences · 2025Article
- Optimizing core collections for genetic studies: a worldwide flax germplasm case study.Frontiers in plant science · 2025Article
- Genetic Determinants of Endurance: A Narrative Review on Elite Athlete Status and Performance.International journal of molecular sciences · 2024Review
- Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Power calculation prior to a genetic experiment can help investigators choose the optimal sample size to detect a quantitative trait locus (QTL). Without the guidance of power analysis, an experiment may be underpowered or overpowered. Either way will result in wasted resource. QTL mapping and genome-wide association studies (GWAS) are often conducted using a linear mixed model (LMM) with controls of population structure and polygenic background using markers of the whole genome. Power analysis for such a mixed model is often conducted via Monte Carlo simulations. In this study, we derived a non-centrality parameter for the Wald test statistic for association, which allows analytical power analysis. We show that large samples are not necessary to detect a biologically meaningful QTL, say explaining 5% of the phenotypic variance. Several R functions are provided so that users can perform power analysis to determine the minimum sample size required to detect a given QTL with a certain statistical power or calculate the statistical power with given sample size and known values of other population parameters.
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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 Socratic graph.