This module highlights some of the downstream analyses that can be used to understand the biology underlying associations observed in a GWAS datasets, and map disease-associated genetic variants to genes and drugs. The module
will introduce statistical methods for molecular QTL (quantitative trait loci) studies and integrative omics analysis that combine GWAS summary statistics with omic datasets. Methods and resources that will be covered in this module include transcriptome-wide QTL analysis, Mendelian Randomisation, SMR, and Connectivity Map.

Prerequisite: This module assumes a basic understanding of GWAS. If you are not familiar with GWAS, we highly recommend attending Module 1 Genetic Mapping in advance. A basic knowledge of statistics and programming in R and Linux is required for this module.

Goal: By the end of the module, you will acquire the skills to follow up GWAS results to identify relevant biology and candidate drugs that could be investigated further. You will learn how to combine different omic datasets with GWAS data, as well as learn some of the caveats of these datasets that need to be considered when interpreting the data.

Primary instructor:
Dr Sonia Shah
Dr Sonia Shah leads the Genomics in Health Group at the Institute for Molecular Bioscience. She is a National Heart Foundation Future Leader Fellow with a research focus on pharmacogenomics and using genomic data to improve understanding, prevention and treatment of cardiovascular disease.

Co-instructors:
Dr Clara Jiang
Dr Clara Jiang is a post-doctoral research fellow at the Institute for Molecular Bioscience, the University of Queensland. Dr Jiang research focuses on using genomic and transcriptomic analysis to explore potential opportunities for drug repurposing, as well as using statistical genomic approaches to investigate the sex differences in cardiovascular diseases.

Dr Gagandeep Singh
Dr Gagandeep Singh is a Postdoctoral researcher at the Institute for Molecular Bioscience (IMB), University of Queensland (UQ), St. Lucia. His research focus is to identify the signature genes associated with diseases from different ancestries to develop Drug repurposing pipeline by exploring various datasets (Genomics and transcriptomics).

Dr Zhihong Zhu
Dr Zhihong Zhu is a statistical geneticist and a Senior Researcher at the National Centre for Register-based Research, Aarhus University, Denmark. He is a visiting scientist at the Institute for Molecular Bioscience, the University of Queensland. His research aims to provide insight into the biology and the determinants of human complex diseases. His current research focuses on the development of statistical methodologies to integrate large multi-omics datasets (including gene expression and protein abundance data) and to incorporate multilayer risk factors in response to exposure to environmental factors. He applies these techniques to the study of psychiatric disorders and risk factors (including both genetic and environmental factors).

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