scholarly journals Genomic Bayesian Prediction Model for Count Data with Genotype × Environment Interaction

2016 ◽  
Vol 6 (5) ◽  
pp. 1165-1177 ◽  
Author(s):  
Abelardo Montesinos-López ◽  
Osval A. Montesinos-López ◽  
José Crossa ◽  
Juan Burgueño ◽  
Kent M. Eskridge ◽  
...  
Keyword(s):  
Prediction Model ◽  
Count Data ◽  
Bayesian Prediction ◽  
Environment Interaction ◽  
Genotype Environment Interaction

scholarly journals Genomic Bayesian Prediction Model for Count Data with Genotype × Environment Interaction

2015 ◽  
Author(s):  
Abelardo Montesinos-Lopez ◽  
Osval Montesinos-Lopez ◽  
Jose Crossa ◽  
Juan Burgueno ◽  
Kent Eskridge ◽  
...  
Keyword(s):  
Sample Size ◽  
Count Data ◽  
Genomic Prediction ◽  
Negative Binomial ◽  
Prediction Models ◽  
Simulated Data ◽  
Large Sample Size ◽  
Environment Interaction ◽  
Data Set ◽  
Genotype Environment Interaction

Genomic tools allow the study of the whole genome and are facilitating the study of genotype-environment combinations and their relationship with the phenotype. However, most genomic prediction models developed so far are appropriate for Gaussian phenotypes. For this reason, appropriate genomic prediction models are needed for count data, since the conventional regression models used on count data with a large sample size (n) and a small number of parameters (p) cannot be used for genomic-enabled prediction where the number of parameters (p) is larger than the sample size (n). Here we propose a Bayesian mixed negative binomial (BMNB) genomic regression model for counts that takes into account genotype by environment (G × E) interaction. We also provide all the full conditional distributions to implement a Gibbs sampler. We evaluated the proposed model using a simulated data set and a real wheat data set from the International Maize and Wheat Improvement Center (CIMMYT) and collaborators. Results indicate that our BMNB model is a viable alternative for analyzing count data.

scholarly journals Bayesian and Classical Prediction Models for Categorical and Count Data

2022 ◽  
pp. 209-249
Author(s):  
Osval Antonio Montesinos López ◽  
Abelardo Montesinos López ◽  
Jose Crossa
Keyword(s):  
Logistic Regression ◽  
Count Data ◽  
Poisson Regression ◽  
Prediction Models ◽  
Multinomial Logistic Regression ◽  
Bayesian Framework ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Interaction Term ◽  
Main Effects

AbstractIn this chapter, we explain, under a Bayesian framework, the fundamentals and practical issues for implementing genomic prediction models for categorical and count traits. First, we derive the Bayesian ordinal model and exemplify it with plant breeding data. These examples were implemented in the library BGLR. We also derive the ordinal logistic regression. The fundamentals and practical issues of penalized multinomial logistic regression and penalized Poisson regression are given including several examples illustrating the use of the glmnet library. All the examples include main effects of environments and genotypes as well as the genotype × environment interaction term.

scholarly journals A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction

2017 ◽  
Vol 7 (6) ◽  
pp. 1833-1853 ◽  
Author(s):  
Osval A. Montesinos-López ◽  
Abelardo Montesinos-López ◽  
José Crossa ◽  
José Cricelio Montesinos-López ◽  
Francisco Javier Luna-Vázquez ◽  
...  
Keyword(s):  
Prediction Model ◽  
Variational Bayes ◽  
Environment Interaction ◽  
Genotype Environment Interaction

Genotype-Environment Interaction in Calf Production. II. Live Measurements and Carcass Traits

1973 ◽  
Vol 36 (3) ◽  
pp. 471-475 ◽  
Author(s):  
T. R. Batra ◽  
W. R. Usborne ◽  
D. G. Grieve ◽  
E. B. Burnside
Keyword(s):  
Carcass Traits ◽  
Environment Interaction ◽  
Genotype Environment Interaction

METHODS FOR EVALUATING THE GENOTYPE-ENVIRONMENT INTERACTION IN BREEDING WINTER WHEAT FOR PRODUCTIVITY

2020 ◽  
Vol 15 (1) ◽  
pp. 56-64
Author(s):  
Irina Manukyan ◽  
◽  
Madina Basieva ◽  
Elena Miroshnikova ◽  
◽  
...  
Keyword(s):  
Winter Wheat ◽  
Environment Interaction ◽  
Genotype Environment Interaction
Sign in / Sign up

Export Citation Format

Share Document