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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Can Deep Learning Improve Genomic Prediction of Complex Human Traits
TL;DR: It is suggested that more research is needed to adapt CNN methodology, originally motivated by image analysis, to genetic-based problems in order for CNNs to be competitive with linear models.
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Detecting Polygenic Evolution: Problems, Pitfalls, and Promises
TL;DR: Traditional approaches used for identifying the molecular basis of phenotypic traits are reviewed, to highlight the inherent problems and pitfalls that bias them towards the detection of large-effect loci.
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Non-additive Effects in Genomic Selection
TL;DR: This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection.
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Genomic Prediction of Gene Bank Wheat Landraces
José Crossa,Diego Jarquin,Jorge Franco,Paulino Pérez-Rodríguez,Juan Burgueño,Carolina Saint-Pierre,Phrashant Vikram,Carolina Sansaloni,Cesar Petroli,Deniz Akdemir,Clay Sneller,Matthew P. Reynolds,Maria Tattaris,Thomas Payne,Carlos Guzmán,Roberto J. Peña,Peter Wenzl,Sukhwinder Singh +17 more
TL;DR: In this paper, the authors examined genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian accessions stored in gene banks and evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM).
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Factors Affecting the Accuracy of Genotype Imputation in Populations from Several Maize Breeding Programs
TL;DR: The objective of this paper was to quantify the accuracy of imputation in a maize (Zea mays L.) data set and explore some of the factors that affect it and the design of an information nucleus that incorporates imputation for the purposes of implementing genomic selection and association mapping in small independent breeding programs.
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.