Andrés Legarra

The paper develops a model to quantify social genetic effects on feed intake in pigs by analyzing feeding visit intervals and transforming variance components into aggregated traits.

The paper develops a method to model substitution effect correlations across populations and generations considering non-additive gene action, using variance components and genetic distances.

This paper develops a statistical model to detect buffering loci in genome-wide association studies and identifies loci with significant epistatic effects but no additive effects in bovine data.

The paper implements exact p-values for GWAS within the SSGBLUP framework, demonstrating its efficiency and application to a large beef cattle dataset.

This paper introduces metafounders as pseudo-individuals to reduce bias in genomic evaluations by incorporating ancestral relationships estimated from marker genotypes and pedigrees.