Please note that this is a competence-enhancing course for PhD students and other scientists.
The course is of 1.5 ECTS and is organised by Sreten Andonov, PhD, Swedish University of Agricultural Sciences.
This is a course on implementing genomic selection, where polygenic prediction using genome-wide SNPs provides high prediction accuracy for complex traits. The course will be given by prof Ignacy Misztal, PhD and Daniela Lourenco, PhD, from UGA, USA, and Sreten Andonov, PhD, SLU.
The course will include sections on: a) BLUPF90 family of programs: animal and maternal model, multiple trait and genomic model; b) Introduction to genomic selection, basis of SNP data, simulation of genomic data, data manipulation and bash scripting in Linux; c) Methods based on SNP estimation (SNP_BLUP, BayesX), methods based on genomic relationships, creation and handling of genomic relationship matrices with preGSf90, GBLUP, GREML and GGIBBBS; d) Theory of single-step GBLUP, single-step for populations under selection: bias, inflation, accuracy, forming single-step equations, quality control for G, validation methods, predictability for animals with records, cross-validation when few genotyped animals with records e.g. mortality or disease resistance; e) Estimating SNP effects for GBLUP-based methods, weighted GBLUP and ssGBLUP, linear weights, nonlinear A weights, genome-wide association (GWA) and p-values with postGSf90, experiences and future with ssGBLUP. Exercises: use of programs for data sets with single and multiple traits; data simulation and manipulation; use of programs with simulated data; single-step with simulated data set; application of weighted ssGBLUP and GWA. Literature will be delivered before the course.
The course is characterized by a very strong connection to the breeding programs and population investigations. The course will last for 5 days. Each day there will be 5 hours of lectures: theoretical, demonstrations and case studies, followed by 3 hours computer exercises. From the exercises, each participant will learn how to apply the method explained before in real analysis. Additionally, it is expected each attendant will spend 1-hour on independent work after the classes. A short explanatory course (offered also online) will be given to participants a week before in order to set up their laptops to run programs on a Linux server.
Prof. Ignacy Misztal, PhD, University of Georgia – Athens, USA
Assist. prof. Daniela Lourenco, PhD, University of Georgia – Athens, USA
Please find more information on the course and on how to apply here: