Additional file 1: Figure S1. Prediction accuracy of sorghum phenotypes. Prediction accuracy (measured as mean R2) of sorghum phenotypes as a function of the number of SNPs used for the model (presented as logarithmic values) on the Φ data
Table S1 displays the effect of training set size on prediction ability when performing cross-valida...
Description of the SNP position and SNP features on the sorghum chromosomes and validation of the bi...
In the last years, a series of methods for genomic prediction (GP) have been established, and the ad...
Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the...
Two tables containing unbiasedness of genomic prediction of three traits in Germany cattle populatio...
Key message: The use of a kinship matrix integrating pedigree- and marker-based relationships optimi...
Key messageWe compare genomic selection methods that use correlated traits to help predict biomass y...
Certain agronomic crop traits are complex and thus governed by many small-effect loci. Statistical m...
Figure S1: Comparison of prediction accuracies of different prediction types. (A) SNP, (B) mRNA, (C)...
Additional file 2: Fig. S2. The comparison of the accuracy of wmssBLUP and GBLUP in different popula...
Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorg...
Mean and standard deviation of predictive ability across increasing numbers of SNPs, statistical met...
Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorg...
Average predictive abilities estimated using SNP sets located in different genomic regions. (DOCX 82...
In the last years, a series of methods for genomic prediction (GP) have been established, and the ad...
Table S1 displays the effect of training set size on prediction ability when performing cross-valida...
Description of the SNP position and SNP features on the sorghum chromosomes and validation of the bi...
In the last years, a series of methods for genomic prediction (GP) have been established, and the ad...
Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the...
Two tables containing unbiasedness of genomic prediction of three traits in Germany cattle populatio...
Key message: The use of a kinship matrix integrating pedigree- and marker-based relationships optimi...
Key messageWe compare genomic selection methods that use correlated traits to help predict biomass y...
Certain agronomic crop traits are complex and thus governed by many small-effect loci. Statistical m...
Figure S1: Comparison of prediction accuracies of different prediction types. (A) SNP, (B) mRNA, (C)...
Additional file 2: Fig. S2. The comparison of the accuracy of wmssBLUP and GBLUP in different popula...
Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorg...
Mean and standard deviation of predictive ability across increasing numbers of SNPs, statistical met...
Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorg...
Average predictive abilities estimated using SNP sets located in different genomic regions. (DOCX 82...
In the last years, a series of methods for genomic prediction (GP) have been established, and the ad...
Table S1 displays the effect of training set size on prediction ability when performing cross-valida...
Description of the SNP position and SNP features on the sorghum chromosomes and validation of the bi...
In the last years, a series of methods for genomic prediction (GP) have been established, and the ad...