Cargando…
Pitfalls and Remedies for Cross Validation with Multi-trait Genomic Prediction Methods
Incorporating measurements on correlated traits into genomic prediction models can increase prediction accuracy and selection gain. However, multi-trait genomic prediction models are complex and prone to overfitting which may result in a loss of prediction accuracy relative to single-trait genomic p...
Autores principales: | Runcie, Daniel, Cheng, Hao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829121/ https://www.ncbi.nlm.nih.gov/pubmed/31511297 http://dx.doi.org/10.1534/g3.119.400598 |
Ejemplares similares
-
Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits
por: Montesinos-López, Osval A., et al.
Publicado: (2018) -
Multi-trait Improvement by Predicting Genetic Correlations in Breeding Crosses
por: Neyhart, Jeffrey L., et al.
Publicado: (2019) -
Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture
por: Montesinos-López, Abelardo, et al.
Publicado: (2018) -
Multi-trait Genomic Prediction Model Increased the Predictive Ability for Agronomic and Malting Quality Traits in Barley (Hordeum vulgare L.)
por: Bhatta, Madhav, et al.
Publicado: (2020) -
Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome
por: Karaman, Emre, et al.
Publicado: (2018)