ArticleScientific reports2017
Comparing GWAS Results of Complex Traits Using Full Genetic Model and Additive Models for Revealing Genetic Architecture.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
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- Merging metabolomics and genomics provides a catalog of genetic factors that influence molecular phenotypes in pigs linking relevant metabolic pathways.Genetics, selection, evolution : GSE · 2025Article
- A novel application of data-consistent inversion to overcome spurious inference in genome-wide association studies.Genetic epidemiology · 2024Article
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- Significance of linkage disequilibrium and epistasis on genetic variances in noninbred and inbred populations.BMC genomics · 2022Article
- Accurate, ultra-low coverage genome reconstruction and association studies in Hybrid Swarm mapping populations.G3 (Bethesda, Md.) · 2021Article
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- On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids.PloS one · 2020Article
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- Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine.Acta pharmacologica Sinica · 2018Review
- The search for gene-gene interactions in genome-wide association studies: challenges in abundance of methods, practical considerations, and biological interpretation.Annals of translational medicine · 2018Article
- Dominance and Epistasis Interactions Revealed as Important Variants for Leaf Traits of Maize NAM Population.Frontiers in plant science · 2018Article
- Potential influence of κ-casein and β-lactoglobulin genes in genetic association studies of milk quality traits.Asian-Australasian journal of animal sciences · 2017Article
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2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits.
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