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Methods to efficiently analyse genetic data

  • Title:  Methods to efficiently analyse genetic data
  • AU project manager: Professor Doug Speed, Center for Quantitative Genetics and Genomics
  • Collaboration partners: Bioinformatics Research Centre
  • Project period: April 2018 - October 2023
  • Funding: 5,590,000 DKK

Project summary:

There is great promise in personalised medicine. For example, given an individual's genome, it should in theory be possible to accurately predict their risk of developing diabetes; or if the individual is diagnosed with epilepsy, we should be able to use their genetic information to determine best course of treatment. But despite the ever-increasing amounts of genetic data being produced, we currently lack statistical tools to efficiently analyse these data and make personalised medicine a reality. In this fellowship I will develop novel statistical methods for analysing genetic data, then apply these methods to large-scale datasets. I will tackle important problems in medical genetics, such as constructing models to predict disease susceptibility and severity, and classifying heterogeneous neurological diseases. Finally, I will make all my methods freely-available, so other researchers can apply them to their datasets.