Table 3.
Scenario | Cor all | Cor genotyped | PCG iterations | Sparsity of ) |
---|---|---|---|---|
NormalGa | 1 | 1 | 306 | 0.0 % |
Random10b | 0.995 | 0.977 | 377 | 80.1 % |
Unrelated10c | 0.982 | 0.954 | 492 | 79.9 % |
Offspring10d | 0.987 | 0.983 | 330 | 80.4 % |
OffspringRandom10e | 0.991 | 0.984 | 340 | 80.3 % |
Random30b | 0.997 | 0.996 | 346 | 48.4 % |
Random50b | 0.996 | 0.999 | 312 | 24.7 % |
Old10f | 0.944 | 0.936 | 463 | 80.1 % |
Young10g | 0.897 | 0.937 | 444 | 79.7 % |
NormalAh | 0.977 | 0.858 | 321 | – |
Correlations were calculated for all animals (Cor all) and genotyped animals (Cor genotyped)
Number of PCG iterations and sparsity of the matrix involved in the single step formula )
All correlations were significantly different from each other (p < 0.05)
aNormalG is the usual single-step procedure without sparse approximations
bRandom10, Random30, Random50 are the sparse single-step, where a random subset of animals (10, 30, 50 %) were treated as core
cUnrelated10 is 10 % animals chosen as core by minimizing the degree of relatedness between core animals
dOffspring10 is 10 % animals chosen based on the number of genotyped offspring
eOffspringRandom10 is, for old animals (excluding last year of birth) 10 % animals chosen based on the number of genotyped offspring, whereas for young animals (last year of birth) 10 % of the animals were chosen at random
fOld10 is the sparse single-step, where the 10 % oldest animals were treated as core
gYoung10 is the sparse single-step, where the 10 % youngest animals were treated as core
hNormalA is where genotypes are ignored completely