1.

Simulated data for genomic selection and genome-wide association studies using a combination of coalescent and gene drop methods

An approach is described for simulating data sequence, genotype, and phenotype data to study genomic selection and genome-wide association studies (GWAS). The simulation method, implemented in a software package called AlphaDrop, can be used to simul

COBISS.SI-ID: 3034248

2.

An imputation strategy which results in an alternative parameterization of the single stage genomic evaluation

A method is presented for imputing genotypes in pedigreed populations based on long-range phasing, haplotype libraries, recombination modelling and segragation analysis. In two very different data sets, one a pig data set comparising animals from a s

COBISS.SI-ID: 3028872

3.

Accuracy of genomic prediction for protein yield using different models in Slovenian Brown bulls

Use of genomic (SNP) information enables more accurate inference of breeding values (BV), especially for young animals. The objective of this study was to compare the correlation between progeny based and genomically based evaluation for protein yiel

COBISS.SI-ID: 3093384

4.

Reliability of breeding values in selected populations

Selection reduces genetic variance in population. However, this is not taken into account when reliabilities are computed from prediction error variance (PEV) and base population additive genetic variance. Results of simulations confirmed that when s

5.

Accuracy of genomic prediction for milk traits with different approaches in Slovenian Brown bulls

Use of genome-wide single nucleotide polymorphism (SNP) marker information enables more accurate inference of breeding values (EBV), especially for young animals. The objective of this study was to compare the accuracy of genomic and progeny based ev