Armidale Genetics Summer Course 2026
Venue:
University of New England, Armidale, NSW Australia
Course Audience:
Postgraduate students and other professionals
In collaboration with the
Quantitative
Genetics, Prediction and Selection Theory
Teachers: Professor Agustín Blasco
Universitat Politècnica de
València
Dates: Monday
2 February 2026 (9am) - Friday 6
February 2026 (4pm)
Across
a week of lectures and practical sessions, participants will develop a strong
understanding of:
- Prediction of breeding values
using BLUP, including mixed models, sources
of information, accuracy, and the use of pedigree and genomic data.
- Bayesian methods for genetic
evaluation, covering priors, shrinkage,
Gibbs sampling, Bayesian regression, and how Bayesian prediction compares
to classical BLUP.
- Selection theory,
designing indices that combine multiple traits and economic weighting,
predicted vs realised
The
course is aimed at postgraduate students, researchers, and industry
professionals looking to build or refresh skills in quantitative genetic theory
and genetic evaluation.
Course
program (more detail)
SELECTION
INDICES
1.
Selection indices for one trait
Indices with information from relatives
Indices with information from several traits
2.
Selection indices for multiple traits
Economic weights
Indices for multiple traits with individual information
Interlude:
Changes in genetic parameters with selection.
The Bulmer effect
Indices for multiple traits with information from relatives
3.
Some important features of selection indices
More Selection Index Questions
Selection index calculator -single trait
(spreadsheet)
Selection index calculator -multiple trait (spreadsheet)
BLUP
& REML
1.
The linear model
The fixed effects model
Interlude:
Fixed effects and random effects
The mixed model
2.
BLUP
The mixed model equations
Genetic trends
Other models
BLUP Properties
3.
Estimation of genetic parameters
The maximum likelihood method
REML
Genetic parameters estimation
Practical Selection Index vs BLUP
Slides on mixed model UNE example
Properties of BLUP UNE example
BAYESIAN
METHODS
1.
Bayesian inference
Bayes' theorem
Prior probability
Probability density functions
2.
The mixed model in Bayesian inference
Predicting additive values and estimating genetic parameters
Marginalization
Interlude:
MCMC
BLUP and REML considered as Bayesian methods
Interlude: Inference on breeding values and genetic
parameters under selection
3.
The multitrait model
Traits having the same model
Data augmentation
Slides on Bayesian Inference Part 1
Slides on Bayesian Inference Part 2
Link
to Rabbit R program: https://github.com/marinamartinezalvaro/RabbitR
Pdf for Rabbit program (in Spanish)
GENOMIC
SELECTION
1.
The model with molecular markers
2.
Genomic selection with the infinitesimal model
RR-BLUP
G-BLUP
Single step G-BLUP
3.
Gene detection
GWAS
The Bayesian alphabet: Bayes A, B, C, Cπ, L, R
Material of previous years:
Armidale Genetics Summer Course 2024 Materials
Theory and Tools for
Designing Breeding Programs
of Animals and Plants
Armidale Genetics Summer Course 2023 Materials
·
Methods and Tool for
Genomic Predictions and GWAS in Breeding Programs Daniela Lourenco and Mehdi
Sargolzaei
- COVID
break -
Armidale Genetics Summer Course 2020 Materials
·
The Search for Selection:
Bruce Walsh and Michael Morrissey
Armidale Genetics Summer Course 2019 Materials
·
Introduction to Graphical
Models with Applications to Quantitative Genetics and Genomics: Guilherme Rosa and Francisco
Peñagaricano
Armidale Genetics Summer Course 2018 Materials
·
Mathematical modeling of
infection dynamics in genetically diverse livestock populations: Andrea
Doeschl-Wilson and Osvaldo Anacleto
Armidale Genetics Summer Course 2017 Materials
·
Genotype by environment
interaction in breeding programs: Piter Bijma and Han Mulder
Armidale Genetics Summer Course 2016 Materials
Investigating the Genetic Architecture of Complex Traits &
Prediction of Phenotype
from Genome-wide SNPs - Doug Speed and David Balding
Armidale Animal Breeding
Summer Course 2015 Materials
•
Primer to genomic
analysis using R:
Cedric Gondro
•
From Sequence Data to
Genomic Prediction: Ben Hayes
and Hans Daetwyler
Armidale Animal Breeding
Summer Course 2014 Materials
Breeding Program Design
with Genomic Selection: Jack Dekkers, Julius van der Werf
Armidale Animal Breeding
Summer Course 2012 Materials
Statistical Methods for
Genome-Enabled Selection:
Daniel Gianola, Gustavo de los Campos
Armidale Animal Breeding
Summer Course 2011 Materials
·
Statistical
methods and design in plant breeding and genomics: Ian Mackay
·
IBD
inference in genome association studies: Elizabeth Thompson
Armidale Animal Breeding
Summer Course 2010 Materials
·
Application of
evolutionary algorithms to solve complex problems in quantitative genetics
and
bioinformatics: Brian Kinghorn, Cedric Gondro
·
Bayesian methods in genome association studies: Dorian Garrick, Rohan
Fernando
Armidale Animal Breeding
Summer Course 2009 Materials
·
Quantitative
Genetic Theory and Analysis- Selection
Theory: Bruce
Walsh
·
Quantitative
Genetic Models for social interaction and inherited variability: Piter
Bijma
Armidale Animal Breeding Summer Course
2008 Materials
·
Genomic
Selection: Ben Hayes
Armidale Animal Breeding Summer Course
2007 Materials
·
Generalized Linear Mixed Models:
Steve Kachman
Armidale Animal Breeding Summer Course
2006 Materials
·
Gene Expression:
Toni Reverter
·
Breeding Program Design:
Graser, James, Van der Werf
Armidale Animal Breeding Summer Course
2003 Materials