Table 1 Methods used by the participants to the XVth QTLMAS workshop
From: Comparison of analyses of the XVth QTLMAS common dataset III: Genomic Estimations of Breeding Values
First author | Label | Method | Description |
|---|---|---|---|
Shariati | BayesS_1 | 2 steps (all SNP) | First step: a GBLUP giving estimation of SNP effects. Groups of size 150, 75 (SPNa) or 50 (SNPb) are made assembling SNP of similar effect. Second step: BayesA with all or a limited (1500 or 450) number of SNP and a unique SNP effect variance per group. |
BayesS_2 | 2 steps (1500 SNP) | ||
BayesS_3 | 2 steps-Bayes (450 SNPa) | ||
BayesS_4 | 2 steps-Bayes (450 SNPb) | ||
Ogutu | RR | Ridge regression | |
GBLUP_O | GBLUP | Qualified Ridge Regression BLUP by the authors | |
LASSO_O | LASSO | ||
LASSO_ad | Adaptative LASSO | Following Zou [21], data-driven weights are added to the penalty to force LASSO to be consistent | |
EN | Elastic net | ||
EN_ad | Adaptative EN | Mixture of adaptative lasso and EN | |
Wang | BayesA_W | BayesA | |
BayesB_W | BayesB | ||
BayesCπ_W | BayesCπ | ||
TABLUP | TABLUP | In the genomic matrix, loci IBD probability estimations are weighted by their effect variance estimated from BayesB [11] | |
GBLUP_W | GBLUP | ||
Mucha | AM | Animal model | All models are estimating haplotypes effects. Haplotypes are obtained using the PHASE software [18]. RM1 and RM2 differ by the estimation of the haplotype effect variance |
FM | Fixed effect | ||
RM1 | Random model 1 | ||
RM2 | Random model 2 | ||
Zeng | GBLUPa_Z | GBLUP1 | Additive effect only |
GBLUPd_Z | GBLUP2 | Additive and dominance effect | |
BayesB _W | BayesB | ||
BayesCπ_W | BayesCπ | ||
Usai | LASSO_Uc | LASSO-LARS classic | The penalty is describes as ∑|β j |≤t. In the LASSO-LARS classic, the t parameter is the average number of active SNP in 1000 simulations. In strategy 1, the number which occurred more than 5% of the times and in strategy 2, which minimized a selection criteria |
LASSO_Uc1 | LASSO-LARS strategy 1 | ||
LASSO_Uc2 | LASSO-LARS strategy 2 | ||
Schurink | BayesZ | BayesZ | Similar to BayesCπ, with a Bernoulli prior for π |