Developing And Applying Biologically Plausible Statistical Models For Normal And Non-normal Family Data
Funder
National Health and Medical Research Council
Funding Amount
$339,700.00
Summary
Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing ....Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing common diseases. This project aims to develop novel, biologically realistic statistical models for investigation of common, complex diseases, such as heart disease and cancer, in families. These models will incorporate both measured and unmeasured genetic and environmental factors, and will be applicable to both normally distributed and non-normally distributed traits. Model fitting will use computer-intensive simulation techniques. Application of the models to data from two large pre-existing studies of international renown, the Victorian Family Heart Study and the Australian Prostate Cancer Family Study, will enable a better understanding of the genetic and environmental factors influencing heart disease and cancer. The models will also be applicable to many other studies of diseases which use data from families, and allow more accurate and useful information to be obtained from data. Software will also be made freely available to other researchers. This will ultimately translate into better outcomes from familial genetic research, and eventually, better prevention, detection, and treatment of the diseases.Read moreRead less
Development And Evaluation Of Statistical Methods And Software For Analysis Of Complex Genetic Disease Data
Funder
National Health and Medical Research Council
Funding Amount
$1,250,371.00
Summary
What are the major factors underpinning complex genetic diseases like diabetes, bipolar disorder or cancer? To answer this question new tools are needed, including software for mining the human genome with interactions between the genome and environment being incorporated. This is our focus. It will form the basis of a superior understanding of the overall process leading to disease and hence better predictions with important ramifications for new treatments and health care planning.
Novel Statistical Methods For Genetic Epidemiology
Funder
National Health and Medical Research Council
Funding Amount
$481,505.00
Summary
We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic ep ....We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic epidemiology, genomics, and proteomics, there is a high demand for data analysis and statistical skills. WA has some world class expertise in statistical science, both in academia and in industry. However, this expertise has not yet been applied in a system way to genetic data analysis. We propose to undertake advanced methodological research in statistical genetics and bioinformatics, to produce easy-to-use and accessible software tools and resources that allow methodological advances to be accessed by the Australian research community, and to apply our new methods and tools both to specific disease research and to the developing human genome epidemiology (HuGE) enterprise in WA. These new initiatives in methodological research will draw together a number of currently separate research strands and will provide new tools and resources that will allow applied Australian programs to improve the efficiency of their research into the causes of important. Methodological development in both bioinformatics and statistical genetics are recognized international areas of need.Read moreRead less