Statistical Genetics
The Statistical Genetics group focuses on the development of algorithms to perform statistical analysis to facilitate the mapping of human and murine (mouse) genes. We have collaborations with researchers and clinicians from around Australia, on mapping genes for both simple and complex human diseases such as deafness, muscular neuropathies, leukaemia and lymphomas, multiple sclerosis (MS), Leber's hereditary optical neuropathy, haemochromatosis and epilepsy. In particular we have a strong collaboration with the Menzies Research Institute, Hobart. We work together not only on mapping projects but also statistical and algorithmic development.
We also work closely with the Division of Molecular Medicine on the mapping and identification of ENU mutants and we have been able to help with the idenfication of several of the mutants. We also have a long association with the Australian Genome Research Facility (AGRF). This collaboration provides the important connection between the production of high quality genotyping data and its analysis, which is vital for the effective mapping of genes. Researchers also benefit substantially from this collaboration with our development of analysis methods and tools, especially for new genotyping technologies such as SNP chips.
We are always interested in new mapping projects and encourage clinician researchers to contact us to discuss potential projects. We have considerable experience in the use of both microsatellite and SNP chip mapping for both linkage and association studies.
Research projects are available for BSc and PhD students in Statistical Genetics. For further information on studies in Bioinformatics, visit the Bioinformatics web page. Projects involve analysis of DNA marker data from human pedigrees that display inherited disease patterns with mathematical and computational techniques to identify the responsible genetic loci. DNA marker data generated from crosses between mouse strains that show differences in genetically influenced traits are also analysed to identify genetic loci that contribute to these differences and also provide potential for Honours and PhD studies. Refer to the Prospective Students web page for further information on studying at the institute and contact Dr Melanie Bahlo (details at top of page) for further details on statistical genetics, in particular if you have specific questions or wish to discuss projects.
A family segregating deafness. The family’s DNA samples were used to identify a genomic region in the human genome that is likely to contain the faulty gene causing the deafness. Squares represent males, circles females. Shaded symbols indicate that the individual is deaf. Individuals in grey with a question mark may still become deaf with age.
We also work closely with the Division of Molecular Medicine on the mapping and identification of ENU mutants and we have been able to help with the idenfication of several of the mutants. We also have a long association with the Australian Genome Research Facility (AGRF). This collaboration provides the important connection between the production of high quality genotyping data and its analysis, which is vital for the effective mapping of genes. Researchers also benefit substantially from this collaboration with our development of analysis methods and tools, especially for new genotyping technologies such as SNP chips.
A plot of the genome wide scan results for the family shown in the pedigree above. A clear peak can be seen on chromosome 22 indicating that the faulty gene lies on this chromosome
We are always interested in new mapping projects and encourage clinician researchers to contact us to discuss potential projects. We have considerable experience in the use of both microsatellite and SNP chip mapping for both linkage and association studies.
Research projects are available for BSc and PhD students in Statistical Genetics. For further information on studies in Bioinformatics, visit the Bioinformatics web page. Projects involve analysis of DNA marker data from human pedigrees that display inherited disease patterns with mathematical and computational techniques to identify the responsible genetic loci. DNA marker data generated from crosses between mouse strains that show differences in genetically influenced traits are also analysed to identify genetic loci that contribute to these differences and also provide potential for Honours and PhD studies. Refer to the Prospective Students web page for further information on studying at the institute and contact Dr Melanie Bahlo (details at top of page) for further details on statistical genetics, in particular if you have specific questions or wish to discuss projects.