H
Hans D. Daetwyler
Researcher at La Trobe University
Publications - 156
Citations - 8372
Hans D. Daetwyler is an academic researcher from La Trobe University. The author has contributed to research in topics: Population & Selection (genetic algorithm). The author has an hindex of 36, co-authored 137 publications receiving 6511 citations. Previous affiliations of Hans D. Daetwyler include Department of Environment and Primary Industries & Dow AgroSciences.
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Journal ArticleDOI
Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding
TL;DR: An overview of available methods for implementing parametric WGR models is provided, selected topics that emerge in applications are discussed, and a general discussion of lessons learned from simulation and empirical data analysis in the last decade are presented.
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Whole-genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle
Hans D. Daetwyler,Aurélien Capitan,Hubert Pausch,Paul Stothard,Rianne van Binsbergen,R.F. Brøndum,Xiaoping Liao,Anis Djari,Sabrina Rodriguez,Cécile Grohs,Diane Esquerre,Olivier Bouchez,Marie-Noelle Rossignol,Christophe Klopp,Dominique Rocha,Sébastien Fritz,André Eggen,Phil J. Bowman,David Coote,Amanda J. Chamberlain,Charlotte Anderson,Curt P VanTassell,Ina Hulsegge,Michael E. Goddard,Bernt Guldbrandtsen,M.S. Lund,Roel F. Veerkamp,Didier Boichard,Ruedi Fries,Ben J. Hayes +29 more
TL;DR: The 1000 bull genomes project supports the goal of accelerating the rates of genetic gain in domestic cattle while at the same time considering animal health and welfare by providing the annotated sequence variants and genotypes of key ancestor bulls.
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The Impact of Genetic Architecture on Genome-Wide Evaluation Methods
TL;DR: The relative accuracy of GBLUP and BayesB for a given number of records and heritability are highly dependent on Me, which is a property of the target genome, as well as the architecture of the trait (NQTL).
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Accuracy of predicting the genetic risk of disease using a genome-wide approach.
TL;DR: This study derived simple deterministic formulae to predict the accuracy of predicted genetic risk from population or case control studies using a genome-wide approach and assuming a dichotomous disease phenotype with an underlying continuous liability.
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Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting and Benchmarking
Hans D. Daetwyler,Mario P. L. Calus,Ricardo Pong-Wong,Gustavo de los Campos,John M. Hickey,John M. Hickey +5 more
TL;DR: Simulation procedures, validation and reporting of results, and apply benchmark procedures for a variety of genomic prediction methods in simulated and real example data are reviewed, concluding that no single method can serve as a benchmark for genomic prediction.