A class of Bayesian methods to combine large numbers of genotyped and non-genotyped animals for whole-genome analyses.
about
Metafounders are related to F st fixation indices and reduce bias in single-step genomic evaluationsTag SNP selection for prediction of tick resistance in Brazilian Braford and Hereford cattle breeds using Bayesian methodsA computationally efficient algorithm for genomic prediction using a Bayesian model.Genome-wide Association Study (GWAS) and Its Application for Improving the Genomic Estimated Breeding Values (GEBV) of the Berkshire Pork Quality Traits.Inexpensive Computation of the Inverse of the Genomic Relationship Matrix in Populations with Small Effective Population Size.An efficient exact method to obtain GBLUP and single-step GBLUP when the genomic relationship matrix is singular.Computational strategies for alternative single-step Bayesian regression models with large numbers of genotyped and non-genotyped animals.Comparison of alternative approaches to single-trait genomic prediction using genotyped and non-genotyped Hanwoo beef cattle.Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture.Single-step SNP-BLUP with on-the-fly imputed genotypes and residual polygenic effects.Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictionsThe Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection.Incorporating single-step strategy into random regression model to enhance genomic prediction of longitudinal trait.Invited review: efficient computation strategies in genomic selection.Genetic evaluation with major genes and polygenic inheritance when some animals are not genotyped using gene content multiple-trait BLUP.Transcriptomic investigation of meat tenderness in two Italian cattle breeds.Incorporation of causative quantitative trait nucleotides in single-step GBLUP.Factors affecting GEBV accuracy with single-step Bayesian models.Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.The effect of the H-1 scaling factors τ and ω on the structure of H in the single-step procedure.A nested mixture model for genomic prediction using whole-genome SNP genotypes.Genomic selection in the German Landrace population of the Bavarian herdbook.Non-additive Effects in Genomic Selection.Deflated preconditioned conjugate gradient method for solving single-step BLUP models efficientlyEstimates of genetic trend for single-step genomic evaluationsStatistical and Computational Challenges in Whole Genome Prediction and Genome-Wide Association Analyses for Plant and Animal Breeding
P2860
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P2860
A class of Bayesian methods to combine large numbers of genotyped and non-genotyped animals for whole-genome analyses.
description
2014 nî lūn-bûn
@nan
2014 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
A class of Bayesian methods to ...... als for whole-genome analyses.
@ast
A class of Bayesian methods to ...... als for whole-genome analyses.
@en
A class of Bayesian methods to ...... als for whole-genome analyses.
@nl
type
label
A class of Bayesian methods to ...... als for whole-genome analyses.
@ast
A class of Bayesian methods to ...... als for whole-genome analyses.
@en
A class of Bayesian methods to ...... als for whole-genome analyses.
@nl
prefLabel
A class of Bayesian methods to ...... als for whole-genome analyses.
@ast
A class of Bayesian methods to ...... als for whole-genome analyses.
@en
A class of Bayesian methods to ...... als for whole-genome analyses.
@nl
P2860
P356
P1476
A class of Bayesian methods to ...... mals for whole-genome analyses
@en
P2093
Jack Cm Dekkers
Rohan L Fernando
P2860
P2888
P356
10.1186/1297-9686-46-50
P577
2014-09-22T00:00:00Z
P5875
P6179
1009045375