Estimating effects and making predictions from genome-wide marker data

DOI10.1214/09-STS306zbMath1329.62423arXiv1010.4710WikidataQ57242433 ScholiaQ57242433MaRDI QIDQ908132

Peter M. Visscher, Michael E. Goddard, Klara Verbyla, Naomi R. Wray

Publication date: 3 February 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1010.4710

zbMATH Keywords

predictionestimationgenome-wide association study

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10)

Related Items (1)

Methodological issues in multistage genome-wide association studies

Cites Work

• Unnamed Item
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• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• A random model approach for the LASSO
• Likelihood, Bayesian, and MCMC methods in quantitative genetics
• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• Incorporating LASSO effects into a mixed model for quantitative trait loci detection
• Sire Evaluation
• Best Linear Unbiased Estimation and Prediction under a Selection Model

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