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). A program of the course is below.

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.



Program 2023 (Feb 20- 24 )


Methods and Tool for Genomic Predictions and GWAS in Breeding Programs


Day 1: Mehdi

1.     Introduction to Genomic data

a.      History of the use of genomic data

b.     Genomic markers

c.      Statistics of genomic data

d.     Genomic files

e.      Quality control of SNP data

2.     Simulation of genomic data

a.      Simulated vs. real data

b.     QMSim for genomic data simulation


3.     Introduction to Unix environment and tools

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

manipulation and statistics


Slides Day1 Simulation

Unix Commands

Exercise Day 1 QMSim

Lab 1 Data


Day 2: Mehdi

1.     Introduction to imputation

a)     Implications of missing genomic data

b)     Methods for imputation to medium and large density

c)     State-of-the-art in imputation

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

Slides Day 2 Imputation

Exercise Day2 FImpute


Day 3: Daniela

1.     Introduction of BLUPF90 family of programs for the analyses of mixed models

including single and multiple traits, maternal effects, and repeatability models

a)     Renumbering datasets: renumf90

b)     Estimation of breeding values and VCE: blupf90+

c)     Estimation of breeding values and VCE - Bayesian: gibbsf90+

2.     Exercise: use of BLUPF90 programs with real data for single and multiple trait models


Slides Day 3 BLUPF90

Exercise Day 3 BLUPF90

Lab3 Data


Day 4: Daniela

1.     Introduction to Genomic Selection

2.     Theory of Single-step GBLUP (ssGBLUP)

3.     Creation and handling of genomic relationship matrices with preGSf90

4.     Quality control for genomic and pedigree relationships

a)     Calling rate

b)     Parental exclusions

c)     Distributions of diagonals and off-diagonals of G

d)     Differences between matched G and A22

e)     Eigenvalues/eigenvectors – population stratification

5.     Validation techniques for testing genomic models

6.     Exercises: Application of quality control and use of single-step with BLUPF90

programs in simulated data sets


Slides 1 Day 4 Genomics

Slides 2 Day 4 Accuracy

Slides 3 Day 4 Best Practice BLUPF90

Exercise Day 4 SSGBLUP

Lab 4 Data

Lab 4 Scripts



Day 5:

1.     Base allele frequencies from Gengler’s method

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

7.     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


Slides 1 Day 5 SNP effects

Slides 2 Day 5 GWAS

Slides 3 Day 5 Metafounders

Exercise Day 5 (Indirect SNP effects, GWAS)

Lab 5 Data

Lab 5 Scripts

Exercise Day 5 (Metafounders)

Lab 5 Data (Metafounders)

Lab 5 Scripts (Metafounders)








Download photo here








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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