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

Table 2.

Accuracies for genotyped individuals using single- and multi-trait models in scenario G9

Trait1 Region size2 Single-trait3 Multi-trait
BayesN0 ssSNPB1 ssBayesN0 ssSNPB2 BayesN0 ssSNPB1 ssBayesN0 ssSNPB2
L4 1 SNP ab0.349e ab0.452cd ab0.470d ab0.478c b0.437d b0.536b b0.554b a0.574a
100 SNPs a0.365d a0.460c a0.478c a0.479c a0.481c a0.559b a0.590a a0.590a
1 Chr b0.335c b0.434b bc0.444b bc0.445b b0.402b c0.493a c0.497a b0.499a
WG b0.335d b0.433b c0.433bc c0.433b c0.362cd d0.461ab d0.472a c0.473a
H 1 SNP b0.587g b0.683e b0.689de b0.700bc b0.593f b0.688cd b0.699b a0.712a
100 SNPs a0.611f a0.698d a0.716b a0.716b a0.622e a0.707c a0.725a a0.725a
1 Chr c0.552e c0.650bd c0.651cd c0.651abcd c0.558e c0.655ac c0.657ab b0.657ab
WG d0.538d c0.642c c0.642bc c0.643bc d0.543d d0.644abc d0.646ab c0.646a

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