Efficient Methods to Compute Genomic Predictions
TLDR
Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously, and a blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects.About:
This article is published in Journal of Dairy Science.The article was published on 2008-11-01 and is currently open access. It has received 4196 citations till now. The article focuses on the topics: Best linear unbiased prediction & Allele frequency.read more
Citations
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Software for Genome-Wide Association Studies in Autopolyploids and Its Application to Potato.
TL;DR: The results indicate that both marker density and population size were limiting factors for GWAS with the SolCAP panel, and the hypothesis that statistical power is higher when the assumed gene action in the GWAS model matches the gene action at unobserved quantitative trait loci is confirmed.
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Improving the Accuracy of Whole Genome Prediction for Complex Traits Using the Results of Genome Wide Association Studies
TL;DR: This is the first study incorporating public GWAS results formally into the standard GBLUP model and it is thought that the BLUP|GA approach deserves further investigations in animal breeding, plant breeding as well as human genetics.
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A SUPER powerful method for genome wide association study
TL;DR: A method to extract a small subset of SNPs and use them in FaST-LMM, which not only retains the computational advantage of FaST, but also remarkably increases statistical power even when compared to using the entire set ofSNPs.
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The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction
TL;DR: Reliabilities can be predicted accurately using empirically estimated Me and level of relationship with reference individuals has a much higher effect on the reliability than linkage disequilibrium per se, and accumulated length of shared haplotypes is more important in determining the reliability of genomic prediction than the individual shared haplotype length.
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Genome Properties and Prospects of Genomic Prediction of Hybrid Performance in a Breeding Program of Maize
Frank Technow,Tobias A. Schrag,Wolfgang Schipprack,Eva Bauer,Henner Simianer,Albrecht E. Melchinger +5 more
TL;DR: High consistency of linkage phases and large differences in allele frequencies between the Dent and Flint heterotic groups in pericentromeric regions are found and support the hypothesis of differential fixation of alleles due to pseudo-overdominance in these regions.
References
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Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps
TL;DR: It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.
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Coefficients of Inbreeding and Relationship
TL;DR: The importance of having a coefficient by means of which the degree of inbreeding may be expressed has been brought out by Pearl' in a number of papers published between 1913 and 1917.
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Strategy for applying genome-wide selection in dairy cattle.
TL;DR: Genome-wide selection may become a popular tool for genetic improvement in livestock after a strategy that utilizes these advantages was compared with a traditional progeny testing strategy under a typical Canadian-like dairy cattle situation.
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Derivation, calculation, and use of national animal model information.
Paul M. VanRaden,G.R. Wiggans +1 more
TL;DR: New terms and definitions were developed to explain national USDA genetic evaluations computed by an animal model, whereiability is the squared correlation of predicted and true transmitting ability.
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Accuracy of Genomic Selection Using Different Methods to Define Haplotypes
TL;DR: It was concluded that genomic selection is considerably more accurate than traditional selection, especially for a low-heritability trait.