Table 2 The comparison of the applied approaches used by participants for estimation of genomic breeding value of quantitative trait.
From: Comparison of analyses of the QTLMAS XIV common dataset. I: genomic selection
Approach no. | Authors | Method | Acc. | Reg. Coef. | MSD | Shared (%) | Loss (%) | ||
|---|---|---|---|---|---|---|---|---|---|
|  |  |  | ♂ | ♀ | ♂ | ♀ |  |  |  |
1 | Calus et al.[10]* | BayesA bivariate | 0.85 | 0.84 | 1.06 | 0.91 | 45.4 | 17 | 14 |
2 | Calus et al. [10] | BayeaA univariate | 0.84 | 0.83 | 1.05 | 0.90 | 46.9 | 58 | 18 |
3 | Calus et al. [10] | BayesC bivariate | 0.87 | 0.89 | 1.01 | 0.88 | 42.4 | 71 | 10 |
4 | Calus et al. [10] | BayesC univariate | 0.86 | 0.87 | 1.01 | 0.89 | 44.1 | 68 | 12 |
5 | Calus et al. [10] | GBLUP bivariate | 0.83 | 0.81 | 1.07 | 0.90 | 47.8 | 57 | 19 |
6 | Calus et al. [10] | GBLUP univariate | 0.83 | 0.80 | 1.10 | 0.90 | 48.9 | 54 | 22 |
7 | Calus et al. [10] | Pedigree-BLUP univariate | 0.49 | 0.46 | 0.88 | 0.71 | 66.4 | 17 | 79 |
8 | Calus et al. [10] | Pedigree-BLUP bivariate | 0.50 | 0.47 | 0.88 | 0.72 | 66.8 | 23 | 62 |
9 | Cleveland et al. [11] | BayesA_all 1 | 0.85 | 0.86 | 1.13 | 0.96 | 45.0 | 70 | 12 |
10 | Cleveland et al. [11] | BayesA_s12 | 0.49 | 0.52 | 0.94 | 0.91 | 63.4 | 26 | 63 |
11 | Cleveland et al. [11] | BayesA_s22 | 0.67 | 0.66 | 0.94 | 0.84 | 56.5 | 54 | 33 |
12 | Coster and Calus[12] | PLSR3 | 0.76 | 0.73 | 9.05 | 7.31 | 76.4 | 16 | 83 |
13 | Nadaf et al. [13] | BayesB | 0.89 | 0.89 | 1.04 | 0.91 | 41.7 | 77 | 8 |
14 | Nadaf et al. [13] | BayesB + Pedigree information | 0.88 | 0.88 | 1.02 | 0.90 | 42.2 | 71 | 9 |
15 | Nadaf et al. [13] | GBLUP + Pedigree information | 0.81 | 0.80 | 1.09 | 0.92 | 49.2 | 56 | 21 |
16 | Nadaf et al. [13] | GBLUP | 0.82 | 0.80 | 1.12 | 0.92 | 49.1 | 71 | 23 |
17 | Ogutu et al. [8] | Boosting | 0.47 | 0.38 | 0.19 | 0.15 | 280.7 | 29 | 65 |
18 | Ogutu et al. [8] | Support vector | 0.69 | 0.63 | 1.54 | 1.20 | 48.3 | 49 | 36 |
19 | Schulz-Streeck et al. [14] | Ridge regression | 0.85 | 0.84 | 1.02 | 0.86 | 59.6 | 59 | 19 |
20 | Schulz-Streeck et al. [14] | Spatial regression | 0.83 | 0.81 | 1.08 | 0.88 | 46.4 | 63 | 19 |
21 | Shen et al. [15] | DHGLM4 | 0.82 | 0.80 | 1.03 | 0.84 | 49.9 | 58 | 15 |
22 | Sun et al. [16] | BayesCpi | 0.89 | 0.89 | 1.05 | 0.91 | 41.6 | 77 | 8 |
23 | Zhang et al. [17] | BayesB | 0.89 | 0.89 | 1.05 | 0.91 | 42.0 | 74 | 8 |
24 | Zhang et al. [17] | TA–BLUP–sub5 | 0.89 | 0.89 | 1.03 | 0.90 | 42.2 | 73 | 9 |
25 | Zhang et al. [17] | TA–BLUP–all6 | 0.89 | 0.89 | 1.06 | 0.92 | 41.9 | 72 | 9 |
26 | Zukowski et al. | GBLUP | 0.58 | 0.59 | 1.12 | 0.96 | 87.0 | 41 | 38 |