Genomic Prediction with Golden Helix SNP & Variation Suite
Predicting phenotypic traits from genotypes is a key focus in agrigenomics, as researchers work to increase crop yields and meat production to satisfy the needs of a growing population. Genomic prediction allows these scientists to identify the plants or animals with the best breeding potential for desirable traits without having to endure lengthy and expensive field trials.
The Golden Helix SNP and Variation Suite (SVS) now offers two methods for genomic prediction: Bayes C-pi and Genomic Best Linear Unbiased Predictors (GBLUP). This webcast will discuss the principles of genomic prediction, describe and compare the methods available in SVS, and include an interactive demonstration of how SVS can be used to predict phenotypes for both plant and animal species.
About the Presenter
Dr. Bryce Christensen fills two roles at Golden Helix as he is both the Director of Services as well as a Statistical Geneticist. Bryce joined GHI in 2009 from the University of Utah where he earned his PhD in Genetic Epidemiology and Biomedical Informatics. Before undertaking his graduate studies, Bryce worked for 2 years as a data analyst at Mayo Clinic in the Division of Biostatistics.