Literature DB >> 11712970

A sampling method for estimating the accuracy of predicted breeding values in genetic evaluation.

M N Fouilloux1, D Laloë.   

Abstract

A sampling-based method for estimating the accuracy of estimated breeding values using an animal model is presented. Empirical variances of true and estimated breeding values were estimated from a simulated n-sample. The method was validated using a small data set from the Parthenaise breed with the estimated coefficient of determination converging to the true values. It was applied to the French Salers data file used for the 2000 on-farm evaluation (IBOVAL) of muscle development score. A drawback of the method is its computational demand. Consequently, convergence can not be achieved in a reasonable time for very large data files. Two advantages of the method are that a) it is applicable to any model (animal, sire, multivariate, maternal effects...) and b) it supplies off-diagonal coefficients of the inverse of the mixed model equations and can therefore be the basis of connectedness studies.

Entities:  

Mesh:

Year:  2001        PMID: 11712970      PMCID: PMC2705400          DOI: 10.1186/1297-9686-33-5-473

Source DB:  PubMed          Journal:  Genet Sel Evol        ISSN: 0999-193X            Impact factor:   4.297


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  3 in total

1.  Connectedness among herds of beef cattle bred under natural service.

Authors:  Joaquim Tarrés; Marta Fina; Jesús Piedrafita
Journal:  Genet Sel Evol       Date:  2010-02-25       Impact factor: 4.297

2.  Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance.

Authors:  John M Hickey; Roel F Veerkamp; Mario P L Calus; Han A Mulder; Robin Thompson
Journal:  Genet Sel Evol       Date:  2009-02-09       Impact factor: 4.297

3.  An assessment of genomic connectedness measures in Nellore cattle.

Authors:  Sabrina T Amorim; Haipeng Yu; Mehdi Momen; Lúcia Galvão de Albuquerque; Angélica S Cravo Pereira; Fernando Baldi; Gota Morota
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

  3 in total

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