Posters: Statistical Methods - Linear and Nonlinear Models (Group 1)

Friday, August 22, 2014: 3:00 PM-3:30 PM
Posters (The Westin Bayshore)
Moderator:
Marco C.A.M. Bink
686
Simultaneous Estimation of Spatial and Genetic Effects Using Hierarchical Generalized Linear Models
Lars Rönnegård, SLU; Majbritt Felleki, SLU; Moudud Alam, Dalarna University; Xia Shen, Division of Computational Genetics, Department of Clinical Sciences, Swedish University of Agricultural Sciences
687
Properties of Mendelian Residuals when regressing Breeding Values using a Genomic Covariance Matrix
Rodolfo J.C. Cantet, Department of Animal Science, University of Buenos Aires; Zulma G. Vitezica, Unite Mixte ENSAT- INRA
688
Can a model with genetic groups for Mendelian sampling deviations correct for pre-selection bias?
Freddy Fikse, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences
689
Aggregation of methods for genetic prediction
Clement Carre, IMT Université Paul Sabatier; Llibertat Tusell, INRA; Selma Forni, Genus Plc; Fabrice Gamboa, IMT Université Paul Sabatier; Daniel Gianola, University of Wisconsin - Madison; Eduardo Manfredi, INRA
690
Bayesian analysis of heterogeneous residual variance in canine behaviour
Stéphanie M van den Berg, University of Twente; Inga Schwabe, University of Twente; Freddy Fikse, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences; Henri CM Heuven, University of Utrecht; Cees AW Glas, University of Twente
691
Influence of Family Structure on Variance Decomposition
Stefan M Edwards, Center of Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Pernille M Sarup, Center of Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Peter Sørensen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University
692
A Bayesian Modeling Framework to Integrate Genetics and Epidemiology in Field Disease Data
M. Nath, Biomathematics and Statistics Scotland; C. M. Pooley, The Roslin Institute and R(D)SVS, University of Edinburgh; S. C. Bishop, The Roslin Institute and R(D)SVS, University of Edinburgh; G. Marion, Biomathematics and Statistics Scotland
693
Variational Bayesian Method to Estimate Variance Components
Aisaku Arakawa, National Institute of Agrobiological Sciences; Masaaki Taniguchi, National Institute of Agrobiological Sciences; Takeshi Hayashi, NARO Institute of Agricultural Research Center; Satoshi Mikawa, National Institute of Agrobiological Sciences
694
Parallel Computing to Speed up Whole-Genome Analyses Using Independent Metropolis-Hastings Sampling
Hao Cheng, Iowa State Univeristy; Rohan L Fernando, Iowa State University; Dorian J. Garrick, Iowa State University
695
Results of Genome Wide Association Studies Improve the Accuracy of Genomic Selection
Zhe Zhang, South China Agricultural University; Jinlong He, South China Agricultural University; Hao Zhang, South China Agricultural University; Ping Gao, South China Agricultural University; Malena Erbe, Georg-August University; Henner Simianer, Georg-August University; Jiaqi Li, South China Agricultural University
696
Estimation of genetic parameters and breeding values in honey bees
Evert W Brascamp, Animal Breeding and Genomics Centre, Wageningen University; Roel F. Veerkamp, Animal Breeding and Genomics Centre, Wageningen University; Piter Bijma, Animal Breeding and Genomics Centre, Wageningen University
697
Genetic variance components when fluctuating imprinting patterns are present
Inga Blunk, Leibniz Institute for Farm Animal Biology; Norbert Reinsch, Leibniz Institute for Farm Animal Biology
698
Approximation of Standard Errors of Estimates as a By-Product for MC EM REML Analysis
Kaarina Matilainen, MTT Agrifood Research Finland, Biotechnology and Food Research; Ismo Strandén, MTT Agrifood Research Finland, Biotechnology and Food Research; Esa A. Mäntysaari, MTT Agrifood Research Finland, Biotechnology and Food Research
699
DMU - A Package for Analyzing Multivariate Mixed Models in quantitative Genetics and Genomics
Per Madsen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Just Jensen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Rodrigo Labouriau, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Ole Fredslund Christensen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Goutam Sahana, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University
700
A New Nonparametric Approach to Delineating Spatial Population Genomic Variation
Zhiqiu Hu, University of Alberta; Rong-Cai Yang, Alberta Agriculture and Rural Development
701
Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster
Fabio Morgante, Department of Biological Sciences, North Carolina State University; Daniel A Sorensen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Peter Sørensen, Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University; Christian Maltecca, North Carolina State University; Trudy FC Mackay, Department of Biological Sciences, North Carolina State University
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