Jiang Xiaohan, Putz Austin, Huang Wen, Steibel Juan P
Bioinformatic and Computational Biology Program, Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
Hendrix Genetics, Boxmeer, 5831CK, The Netherlands.
J Anim Sci. 2025 Jan 4;103. doi: 10.1093/jas/skaf083.
Recent advancements in genotyping technologies have revolutionized our ability to estimate breed composition in pigs. The classical compositional regression used for this purpose requires a multibreed panel to detect crossbreeding and its application is limited to breeds in the panel. Some breed entities may not have access to the multibreed panel but may have access to a single breed panel. We present crossbreeding detection methods based on semi-supervised anomaly detection techniques that use a single-breed genotype panel from purebred animals of interest. By utilizing these methods, we identified and assessed breed outliers within large pig genotype panels.
基因分型技术的最新进展彻底改变了我们估计猪品种组成的能力。用于此目的的经典成分回归需要一个多品种面板来检测杂交，并且其应用仅限于面板中的品种。一些品种实体可能无法获得多品种面板，但可能可以获得单一品种面板。我们提出了基于半监督异常检测技术的杂交检测方法，该技术使用来自感兴趣的纯种动物的单一品种基因型面板。通过使用这些方法，我们在大型猪基因型面板中识别并评估了品种异常值。
