Armidale Animal Breeding Summer Course 2023

Venue: University of New England, Armidale, NSW Australia

Course Audience: Postgraduate students and other professionals




Methods and Tool for Genomic Predictions and GWAS in Breeding Programs



Dr Daniela Lourenco              University of Georgia, USA

Dr Mehdi Sargolzaei              Select Sires Inc., USA


Dates:     Monday – Friday     20 -24 February 2023

Course Description:  

This course encompasses the background needed to perform genomic analyses used in Animal Breeding and Genetics. It involves simulation of genomic data using QMSim (Sargolzaei and Schenkel, 2009), imputation of missing SNP using FImpute (Sargolzaei et al., 2014), and overall genomic analyses using BLUPF90 programs (Misztal et al., 2014).

Intended Audience

The intended audience is advanced graduate students, postdocs, and faculty with an interest in breeding programs and the use of genomic information in prediction of genetic merit or risk.

Background required

 Knowledge of quantitative genetics and linear models at a postgraduate level, some basic knowledge of working with Linux.


Program 2023 (Feb 20- 24 )


Day 1:

1.         Introduction to Genomic data

a)         History of the use of genomic data

b)         Genetic markers

c)         Statistics of genomic data

d)         Genomic files

2.         Simulation of genomic data

a)         Simulated vs. real data

b)         QMSim for genomic data simulation in livestock

3.         Introduction to Unix environment and tools

4.         Exercise: Simulate a genomic dataset with QMSim and use Unix tools for data manipulation and statistics


Day 2:

1.         Introduction to imputation

a)         Implications of missing genomic data

b)         Methods for imputation

c)         Population structure and its implications for imputation using different SNP panel densities

d)         State-of-the-art in imputation in livestock

2.         Imputation

a)         Best practices before and after imputation

b)         FImpute for imputation

c)         Accuracy of imputation

3.         Exercise: Impute missing genotypes with and without pedigree information, and compute imputation accuracy


Day 3:

1.         History and theory of genomic selection

2.         Quality control of SNP data

3.         Genomic relationship matrix (G)

4.         Creation and handling of genomic relationship matrices with preGSf90

5.         GBLUP, GREML, and GGIBBBS using BLUPF90 programs

6.         Exercise: use of genomic programs with real data


Day 4:

1.         Theory of Single-step GBLUP (ssGBLUP)

2.         Forming Single-step equations

3.         Quality control for genomic and pedigree relationships

1.         Calling rate

2.         Parental exclusions

3.         Distributions of diagonals and off-diagonals of G

4.         Differences between matched G and A22

5.         Eigenvalues/eigenvectors – population stratification

4.         Validation techniques for testing genomic models

5.         Exercises: Application of quality control and use of single-step with BLUPF90 programs in simulated data sets


Day 5:

1.         Accounting for unknown relationships in ssGBLUP (UPG and metafounders)

2.         Estimating SNP effects from GBLUP-based models

3.         Indirect predictions using SNP effects

4.         Weighted GBLUP and ssGBLUP

5.         Genome-wide association studies (GWAS)

6.         Exercises: Compute SNP effects from ssGBLUP, run indirect predictions for young animals, and do ssGWAS (variance explained by SNP and p-values) with BLUPF90 programs







Photos from 2020  (click on photo to download)














Material of previous years:


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 2005    Materials
·         Breeding Objectives: Gibson, Van der Werf, Kinghorn
·         Scientific Writing:          David Lindsay
·         ASReml:           Arthur Gilmour
Armidale Animal Breeding Summer Course 2004    Materials
·         Bayesian for Beginners               Kerrie Mengersen
·         Bayesian Models for QTL analysis        Michel Perez-Enciso
·         Bioinformatics   John McEwan

Armidale Animal Breeding Summer Course 2003    Materials

·         Scientific Writing:  David Lindsay
·         Linear Models for animal breeding:   Julius van der Werf, Mike Goddard
·         QTL mapping for practitioners, from linkage to gene: Ben Hayes, Julius van der Werf
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