New course SEMESTER TWO 2017.

Course Overview:

This course teaches the why and how of statistical methods - and their computer applications - to analyse genome-wide genetic data and phenotypes on large numbers of individuals. Genetic data sets are usually large, comprising thousands of individuals. Examples of typical genetic data sets include phenotypic records with a recorded pedigree structure of relationships between individuals or disease cases and controls with DNA polymorphisms measured at millions of locations in the genome. A key feature of genetic data is the massive correlation structure between random effects. Major topics include: Linear mixed models for estimation and prediction; Genome-wide association studies; Multiple trait analyses. The course focuses on applications in human and agricultural genetics and genomics. There is a strong element of hands-on analyses of real-world datasets using R and GCTA


Researchers at UQ are internationally recognised for their research in analysis of genetic data of complex traits. Complex traits are underpinned by many genetic factors and many non-genetic factors and include quantitative traits of importance in our society, from production yields of wheat, to milk production in dairy cattle, to body mass index in humans. Common human diseases are also complex genetic traits underpinned by thousands of genetic risk loci: diseases such as cancers, immune disorders, heart disease, diabetes, neurological disorders, psychiatric disorders. Advances in technology in the last ten years mean that there is an explosion of data, allowing researchers to answers questions that were previously impossible to address. The course is built upon content taught by our experienced lecturers in workshops presented around the world.

Lecturers Include:

Professor Peter Visscher, IMB/QBI, teaches quantitative genetics and works on understanding genetic architecture of complex traits
Dr Allan McRae, IMB teaches genome-wide association analysis and specialises in analysis of DNA methylation data
Professor Ben Hayes, QAAFI, teaches Best Linear Unbiased Prediction and works in agricultural genomics
Professor Jian Yang, IMB/QBI teaches Restricted Maximum Likelihood (REML), develops new methodology and author of the software GCTA
Professor David Evans, UQDI, teaches detection of causality via Mendelian Randomisation and works on genomics of immune disorders
Professor Naomi Wray, IMB/QBI, teaches quantitative genetics of disease and works on genomics of brain disorders

IMB: Institute for Molecular Bioscience; QBI: Queensland Brain Institute; UQDI: University of Queensland Diamantina Institute. QAAFI: Queensland Alliance for Agriculture and Food Industries


This course was developed recognising that the skills taught are in demand in agricultural industries, health industries and research.
This course is primarily targeted at third year students majoring in statistics, Honours students, and Masters level students working at the interface of biology and quantitation. Other students with a demonstrated talent in quantitative skills should contact the course advisor to see if they have the necessary pre-requisites to enrol:

Dr Florian Rohart
Dr Ian Wood

The course is available as a single study unit to non-award students: