Efficient Methods to Compute Genomic Predictions
Agricultural Research Service · Beltsville Agricultural Research Center
Abstract
Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously. Algorithms were derived and computer programs tested with simulated data for 2,967 bulls and 50,000 markers distributed randomly across 30 chromosomes. Estimation of genomic inbreeding coefficients required accurate estimates of allele frequencies in the base population. Linear model predictions of breeding values were computed by 3 equivalent methods: 1) iteration for individual allele effects followed by summation across loci to obtain estimated breeding values, 2) selection index including a genomic relationship matrix, and 3) mixed…
Citation impact
- FWCI
- 31.94
- Percentile
- 100%
- References
- 24
Authors
1Topics & keywords
- Linkage disequilibrium
- Genomic selection
- Statistics
- Linkage (software)
- Selection (genetic algorithm)
- Population
- Genotyping
- Allele frequency