Efficient methods to compute genomic predictions.

By Paul M. Vanraden. Journal of Dairy Science, 2008

5,379 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bd6e45caed04286a115e1a20a0f8bce30fc9c451

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Citations in the corpus

Efficient Bayesian mixed model analysis increases association power in large cohorts (2014, methodology): “Instead, the approximation algorithm only requires solving linear systems of mixed model equations, which can be accomplished efficiently using conjugate gradient iteration 28,29 .”
Perspectives for Genomic Selection Applications and Research in Plants (2015, neutral): “frequency of the minor allele (VanRaden 2008).”
Genomic prediction when some animals are not genotyped (2010, methodology): “In VanRaden [3] it is assumed that all animals are genotyped, which is unlikely to be a common scenario.”
Genomic selection in forest tree breeding (2011, methodology): “However, practical applications (Hayes and Goddard 2008; VanRaden 2008) of the BLUP method in GS have shown similar efficiency as the more elaborated Bayesian methods.”
Genetic Gains in Grain Yield Through Genomic Selection in Eight Bi-parental Maize Populations under Drought Stress (2015, background): “Most studies have used different cross-validation designs and schemes that attempt to predict performance of untested individuals and environments (VanRaden, 2008; Hayes et al., 2009; Crossa et al., 2010, 2013, 2014; Pérez-Rodríguez et al., 2012; Poland et al., 2012; Dawson et al., 2013; Heslot et a”
Using Genetic Distance to Infer the Accuracy of Genomic Prediction (2015, methodology): “Kinship Coefficients and FST A common measure of kinship from marker data is average allelic correlation [24, 36], which is defined as K = [kij] with”
Research review: Polygenic methods and their application to psychiatric traits. (2014, methodology): “Therefore, other methods have been developed that analyse all SNPs simultaneously, first for quantitative traits (Fernando, 1998; Goddard, 2009; Habier, Fernando, & Dekkers, 2007; VanRaden, 2008; Yang et al., 2010), and later extended to disease traits (Lee, Wray, Goddard, & Visscher, 2011).”
Extension of the bayesian alphabet for genomic selection (2011, methodology): “An animal model with a genomic relationship matrix [13] was used to obtain GEBVs (GBLUP), which is equivalent to ridge-regression.”
Genomic Relationship Matrix for Correcting Pedigree Errors in Breeding Populations: Impact on Genetic Parameters and Genomic Selection Accuracy (2014, methodology): “Typically in GS prediction models, the BLUP-BVs are deregressed (Garrick et al., 2009) before regressing with the marker data, which is equivalent to single-step methodologies proposed by VanRaden (2008) and Misztal et al. (2009).”