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Practical considerations of computing additive and dominance relationships using the genomic relationship matrix are discussed.
GEBVs were estimated by a Bayesian model averaging approach (BayesB) and an animal model using the genomic relationship matrix (G-BLUP).
2) GBLUP - reduced animal model using the genomic relationship matrix estimated by the method in [ 9], with allele frequencies based on the full data set.
The estimates of trait heritability when using the genomic relationship matrix was comparable but slightly higher than the equivalent model using the pedigree relationships (~ 0.6 vs ~ 0.5).
Genomic BLUP (G-BLUP) EBVs of both training and validation bulls were obtained by mixed-model equations using the genomic relationship matrix, whereas pedigree-based BLUP (P-BLUP) EBVs were obtained by using the numerator relationship matrix [ 24, 25].
The two additive genetic variances were also estimated by fitting each separately: the additive genetic animal variance using the pedigree-based relationship matrix (σ a 0 2 ) and the additive genetic variance using the genomic relationship matrix (σ g 0 2 ).
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Compared to estimates obtained with A, most of the additive variance estimates using the genomic relationships in the smaller dataset were inflated.
SM-GBLUP uses the genomic relationship matrix G T, and variance components were estimated within the data (since the variance components in Table 1 do not apply to DYD).
In the presence of sparse genotype information, we used the genomic relationship matrix G for this, i.e. the MCG method.
Using the genomic information, the relationship between these primary breast tumors and the breast cancer cell lines was explored.
Accounting for individual relationships is automatic with inversion [ 19] or can be approximated without inversion using elements of the genomic relationship matrix [ 4, 26].
More suggestions(15)
using the genomic distance
using the full relationship
using the empirical relationship
using the following relationship
using the genomic primer
using the genomic relatedness
using the evolutionary relationship
using the temporal relationship
using the standard relationship
using the recursive relationship
using the genomic segmentation
using the stratigraphic relationship
using the logarithmic relationship
using the genomic rescue
using the geometric relationship
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