Prediction of complex human traits using the genomic best linear unbiased predictor. [PDF]
Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be
Gustavo de Los Campos +4 more
doaj +8 more sources
Approximation of reliabilities for random-regression single-step genomic best linear unbiased predictor models [PDF]
Random-regression models (RRM) are used in national genetic evaluations for longitudinal traits. The outputs of RRM are an index based on random-regression coefficients and its reliability.
M. Bermann +6 more
doaj +4 more sources
Multivariate best linear unbiased predictor as a tool to improve multi-trait selection in sugarcane [PDF]
: The objective of this work was to evaluate the use of the multivariate best linear unbiased predictor (BLUP) method for multi-trait selection, to estimate the genetic parameters in sugarcane (Saccharum officinarum) genotypes. The experiment was carried
Ivan Ricardo Carvalho +9 more
doaj +6 more sources
Breeding value reliabilities for multiple-trait single-step genomic best linear unbiased predictor
: Approximate multistep methods to calculate reliabilities for estimated breeding values in large genetic evaluations were developed for single-trait (ST-R2A) and multitrait (MT-R2A) single-step genomic BLUP (ssGBLUP) models.
Hafedh Ben Zaabza +5 more
doaj +5 more sources
Multi-Trait, Multi-Environment Genomic Prediction of Durum Wheat With Genomic Best Linear Unbiased Predictor and Deep Learning Methods [PDF]
Although durum wheat (Triticum turgidum var. durum Desf.) is a minor cereal crop representing just 5–7% of the world’s total wheat crop, it is a staple food in Mediterranean countries, where it is used to produce pasta, couscous, bulgur and bread.
Osval A. Montesinos-López +6 more
doaj +2 more sources
Comparing algorithms to approximate accuracies for single-step genomic best linear unbiased predictor. [PDF]
Abstract The exact accuracy of estimated breeding values can be calculated based on the prediction error variances obtained from the diagonal of the inverse of the left-hand side (LHS) of the mixed model equations (MME). However, inverting the LHS is not computationally feasible for large datasets, especially if genomic information is ...
Ramos P +7 more
europepmc +3 more sources
Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 Challenge [PDF]
We ranked third in the Predictive Analytics Competition (PAC) 2019 challenge by achieving a mean absolute error (MAE) of 3.33 years in predicting age from T1-weighted MRI brain images.
Baptiste Couvy-Duchesne +51 more
doaj +2 more sources
Weighted single-step genomic best linear unbiased predictor enhances the genomic prediction accuracy for milk citrate predicted by milk mid-infrared spectra of Holstein cows in early lactation [PDF]
Previous studies have shown that milk citrate predicted by milk mid-infrared (MIR) spectra is strongly affected by a few genomic regions. This study aimed to explore the effect of weighted single-step GBLUP on the accuracy of genomic prediction (GP) for ...
Y. Chen +3 more
doaj +2 more sources
: The US dairy cattle genetic evaluation is currently a multistep process, including multibreed traditional BLUP estimations followed by single-breed SNP effects estimation. Single-step GBLUP (ssGBLUP) combines pedigree and genomic data for all breeds in
J.M. Tabet +7 more
doaj +5 more sources
: The validation of estimated breeding values from single-step genomic BLUP (ssGBLUP) is an important topic, as more and more countries and animal populations are currently changing their genomic prediction to single-step.
Judith Himmelbauer +3 more
doaj +1 more source

