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We observe that the two methods using a marker-based relationship matrix perform better than the method using the pedigree based relationship matrix, but as expected the one-step method performs the best.
The first method (ped) computes traditional EBVs using the pedigree based relationship matrix (without using markers).
For comparison, the prediction using the pedigree based relationship matrix (ped method) and the genomic prediction using (10) based on genotyped animals (two-step) are also shown.
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Method one-step is the method advocated in this paper, method ped uses the pedigree based relationship matrix, and method two-step is the genomic prediction method using only genotyped animals (note that parameter estimates for this method cannot be compared to parameter estimates from the other two methods).
Allele frequencies were calculated using the pedigree base population, that is, the 1020 individuals in the pedigree with unknown parents.
Partitioning the genetic variance into additive and nonadditive (uncorrelated) components using the pedigree-based relationship matrix significantly increased the log likelihood of the mixed model for ABS from the base model to second model (Table 3).
Statistical analyses were performed to account for the influence of environmental factors and the genetic heritability of the phenotypes was calculated using the pedigree-based variance components model.
We also estimated C miss 2 using the pedigree-based estimate of genetic variance.
Additive polygenic random effects were fitted using the pedigree-based relationship matrix.
Thus, this observation suggests that using the pedigree-based estimated breeding values as proxy for "true" breeding values has no significant impact on the estimation of prediction accuracies.
Breeding values of selection candidates in the pedigree sub-line were estimated using the pedigree-based multi-trait BLUP that is used for routine evaluation in the Hy-Line International breeding programs.
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