Project Description:Through large cohort studies based at QIMR Berghofer Medical Research Institute, including the Queensland Study of Melanoma: Environmental and Genetic Associations (Q-MEGA), the Queensland Twin Registry (QTwin), and the QSkin skin cancer study (N ~ 20,000), and from large international datasets (e.g. UK Biobank, N > 500,000) we have a large body of data linking genetics to skin biology. Through this we are able to assess the genetics of skin cancers, including melanoma, skin ageing, pigmentation, and mole count.
These traits interact, and recent methods such as Multi-trait analysis of GWAS, MTAG, have shown that combining related traits can dramatically increase discovery of new genes. We wish to combine this data to greatly increase this data to improve our understanding of skin biology.
Through advanced statistical genetics techniques perform combined analysis of skin traits, identifying new genetic risks and generating improved prediction models.
The overlap of these traits will be explored to identify new genetic risks common to all traits. Prediction models will be developed from the combined data, and calibrated against datasets in hand.
Suitable background:The post is ideally suited to someone with an undergraduate or Masters degree in genetic epidemiology, epidemiology, statistics or bioinformatics. Experience in the analysis/manipulation of large datasets and a good knowledge of computing is desirable. Experience in cancer genetics and/or molecular biology advantageous but not essential. Non-statistical applicants must be able to demonstrate some knowledge of statistics. For statistical applicants, some knowledge of genetics is desirable.