Volume Methods and Tools: Statistical methods - linear and nonlinear models, Proceedings of the World Congress on Genetics Applied to Livestock Production


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H. Simianer, Ma, Y., and Qanbari, S., “Statistical Problems in Livestock Population Genomics”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 202, 2014. (761.1 KB)
A. Doeschl-Wilson, Lipschutz-Powell, D., Anacleto, O., García-Cortés, L. Alberto, Lough, G., Lengeling, A., Bergmann, S., and Woolliams, J. A., “New Methods for capturing unidentified genetic Variation underlying Infectious Disease in Livestock Populations”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 203, 2014. (19.6 KB)
J. Szyda, Fraszczak, M., Giannico, R., Kaminski, S., Mielczarek, M., Minozzi, G., Nicolazzi, E. L., Suchocki, T., Wojdak-Maksymiec, K., and Zarnecki, A., “My P value is lower than your P value! Beyond GWAS in livestock genomics”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 204, 2014. (311.29 KB)
M. Muñoz, Pong-Wong, R., Haley, C. S., and Tenesa, A., “Heritability of complex human diseases in the UK Biobank”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 205, 2014. (205.58 KB)
Y. Li, Kijas, J., Henshall, J. M., Lehnert, S. A., McCulloch, R., and Reverter-Gomez, A., “Using Random Forests (RF) To Prescreen Candidate Genes: A New Prospective for GWAS”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 206, 2014. (157.71 KB)
M. L. Bermingham, Pong-Wong, R., Spiliopoulou, A., Hayward, C., Rudan, I., Campbell, H., Wright, A. F., Wilson, J. F., Agakov, F. V., Navarro, P., and Haley, C. S., “Genomic prediction of health traits in humans: demonstrating the value of marker selection”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 207, 2014. (150.85 KB)
A. Ehret, Hochstuhl, D., and Thaller, G., “Extreme Learning Machine: A new approach for genomic prediction of complex traits”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 208, 2014. (214.39 KB)
X. Sun, Fernando, R. L., Garrick, D. J., and Dekkers, J. C. M., “Improved Accuracy of Genomic Prediction for Traits with Rare QTL by Fitting Haplotypes”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 209, 2014. (163.9 KB)
W. O. Burgos-Paz, Ramos-Onsins, S. E., Perez-Enciso, M., and Ferretti, L., “Correcting For Unequal Sampling in Principal Component Analysis of Genetic Data”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 210, 2014. (313.67 KB)
L. Wang, Edwards, D., and Janss, L., “Evaluation of antedependence model performance and genomic prediction for growth in Danish pigs”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 211, 2014. (251.6 KB)
D. Gianola, Morota, G., and Crossa, J., “Genome-enabled Prediction of Complex Traits with Kernel Methods: What Have We Learned?”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 212, 2014. (304.54 KB)
A. I. Vazquez, Wiener, H. W., Shrestha, S., Tiwari, H. K., and Campos, Gde los, “Integration of Multi-Layer Omic Data for Prediction of Disease Risk in Humans”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 213, 2014. (287.76 KB)
L. Janss, “Disentangling Pleiotropy along the Genome using Sparse Latent Variable Models”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 214, 2014. (340.23 KB)
C. - C. Schoen and Wimmer, V., “Efficiency of Variable Selection in Genome-Wide Prediction for Traits of Different Genetic Architecture”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 215, 2014. (417.33 KB)
D. Wittenburg and Reinsch, N., “Selective Shrinkage of Genomic Effects Using Synthetic Dependencies in Neighboring Chromosome Regions”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 216, 2014. (417.33 KB)
K. Meyer, “Improving REML estimates of genetic parameters through penalties on correlation matrices”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 217, 2014. (4.63 MB)
S. Boitard and Sochacki, S., “Inferring the ancestral dynamics of population size from genome wide molecular data: an ABC approach”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 218, 2014. (173.52 KB)
B. Dourado Valente, Morota, G., Rosa, G. J. M., Gianola, D., and Weigel, K. A., “Causal Meaning of Genomic Predictors: Implication on Genome-Enabled Selection Modeling”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 219, 2014. (173.52 KB)
M. S. Lopes, Bastiaansen, J. W. M., Janss, L., Bovenhuis, H., and Knol, E. F., “Using SNP Markers to Estimate Additive, Dominance and Imprinting Genetic Variance”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 220, 2014. (233.66 KB)
C. M. Pooley, Bishop, S. C., and Marion, G., “Estimation of single locus effects on susceptibility, infectivity and recovery rates in an epidemic using temporal data”, Proceedings of the World Congress on Genetics Applied to Livestock Production, vol. Methods and Tools: Statistical methods - linear and nonlinear models, p. 221, 2014. (411.07 KB)