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. 2019 Oct 22;124(2):274–287. doi: 10.1038/s41437-019-0273-4

Table 4.

Accuracies for genotyped individuals using single- and multi-trait models in scenario N5

Trait1 Region size2 Single-trait3 Multi-trait
BayesN0 ssSNPB1 ssBayesN0 ssSNPB2 BayesN0 ssSNPB1 ssBayesN0 ssSNPB2
L4 1 SNP a0.314d a0.432b a0.432b a0.433b a0.362c a0.470a a0.469a a0.470a
100 SNPs a0.313e a0.428bc a0.434b ab0.429c a0.367d ab0.468a a0.475a a0.474a
1 Chr a0.309d b0.419c b0.420c b0.419c b0.341d c0.447abc b0.447b b0.450a
WG a0.314c a0.431ab ab0.430b a0.432a b0.342c bc0.447ab ab0.459ab ab0.460ab
H 1 SNP b0.545d a0.651c b0.654bc a0.658ab b0.548d a0.654bc b0.657b a0.662a
100 SNPs a0.554d a0.654c a0.663a a0.662ab a0.559d a0.657bc a0.666a a0.665a
1 Chr c0.537b b0.642a c0.645a b0.645a c0.540b b0.644a c0.646a b0.647a
WG c0.537b b0.644a c0.645a b0.646a c0.539b b0.645a c0.648a b0.648a

1L and H: low (0.1) and high (0.4) heritability traits, respectively

2Chr chromosome, WG whole genome

3ssSNPB1 and ssSNPB2: Single-step SNPBLUP, for which the variance components were obtained from BayesN0 and ssBayesN0, respectively

4Different alphabets mean significantly different values at a Type 1 error rate of 0.05 with Bonferroni correction. Subscripts and superscripts stand for comparisons within column and row, respectively, for each trait