SNP Data Quality Control in the Uruguayan Sheep Breeding Program Database

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.