ArticleHeredity2015
Evaluation of multi-locus models for genome-wide association studies: a case study in sugar beet.
Article in Heredity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Local and Bayesian Survival FDR Estimations to Identify Reliable Associations in Whole Genome of Bread Wheat.International journal of molecular sciences · 2023Article
- A novel genomic region on chromosome 11 associated with fearfulness in dogs.Translational psychiatry · 2020Article
- Scalable Nonparametric Prescreening Method for Searching Higher-Order Genetic Interactions Underlying Quantitative Traits.Genetics · 2019Article
- Genome-wide mapping of quantitative trait loci in admixed populations using mixed linear model and Bayesian multiple regression analysis.Genetics, selection, evolution : GSE · 2018Article
- Article
- Choice of models for QTL mapping with multiple families and design of the training set for prediction of Fusarium resistance traits in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2016Article
- Genetic control of plant height in European winter wheat cultivars.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2015Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
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Abstract
Association mapping has become a widely applied genomic approach to dissect the genetic architecture of complex traits. A major issue for association mapping is the need to control for the confounding effects of population structure, which is commonly done by mixed models incorporating kinship information. In this case study, we employed experimental data from a large sugar beet population to evaluate multi-locus models for association mapping. As in linkage mapping, markers are selected as cofactors to control for population structure and genetic background variation. We compared different biometric models with regard to important quantitative trait locus (QTL) mapping parameters like the false-positive rate, the QTL detection power and the predictive power for the proportion of explained genotypic variance. Employing different approaches we show that the multi-locus model, that is, incorporating cofactors, outperforms the other models, including the mixed model used as a reference model. Thus, multi-locus models are an attractive alternative for association mapping to efficiently detect QTL for knowledge-based breeding.
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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.