2026/05/27 by Beatriz Carracelas, Gabriel Ciappesoni, E.A. Navajas +1 · 1 voice
Biochemistry, Genetics and Molecular Biology · #Genetic Associations and Epidemiology #Genetic Mapping and Diversity in Plants and Animals #Genetic and phenotypic traits in livestock
paper · pdf · doi:10.31285/agro.30.1771
openalex publication_date 2026/05/27 · openalex created_date 2026/05/28 · openalex updated_date 2026/07/22
Genomic data provides enhanced accuracy to sheep genetic evaluations while speeding up genetic improvement and helping fix pedigree errors. Achieving these outcomes requires efficient data pipelines to automate quality control (QC) and optimize genotypic data analysis during routine genetic evaluations. Our pipeline includes three main steps: genotype QC, based on the per sample call rate; parentage verification against reported sires and dams, and animal QC, which detects duplicate entries and possible errors in sex and breed assignment. These QC procedures help detect sample mix-ups that occur because of laboratory or farm errors. This paper describes the design and implementation of the QC pipeline applied to the MGAdbSNP database, with the aim of supporting robust and accurate genomic evaluations in sheep.