Genomic Control of Human Complex Trait Variation. This project aims to address knowledge gaps in our understanding of the genetic and environmental control of complex human trait variation. This project will use innovative approaches that combine molecular genomic information with data from large biobank sized cohorts to generate new knowledge of the mechanisms underlying ancestral and sex differences in humans. Expected outcomes include the development of novel methods for the integrative analy ....Genomic Control of Human Complex Trait Variation. This project aims to address knowledge gaps in our understanding of the genetic and environmental control of complex human trait variation. This project will use innovative approaches that combine molecular genomic information with data from large biobank sized cohorts to generate new knowledge of the mechanisms underlying ancestral and sex differences in humans. Expected outcomes include the development of novel methods for the integrative analysis of genomic data and building Australia’s capacity in a highly demanded field, ensuring the capability to realise the translation of this knowledge to positively impact society and human well-being.Read moreRead less
Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, populat ....Complex trait analyses based on genome-wide approaches. This project aims to develop whole genome approaches that can improve the estimation and prediction power by using information from the dynamic genetic architecture of complex traits (i.e. the changes of genetic characteristics and effects when varying effective population size and genetic backgrounds). The project intends to deliver advanced statistical models, efficient algorithms and design by combining data from close relatives, population samples or from different populations (e.g. multi-ethnicities or multi-breeds). The expected outcome is to better understand the dynamic architecture of complex traits and develop methods with improved power, precision and accuracy in genomic analyses.Read moreRead less