Statistical Genetics and Bioinformatics

Statistical Genetics and Bioinformatics has three main themes.

  • The Statistical Genetics theme (Professor Chris Holmes, Professor Jonathan Marchini and Professor Simon Myers) is building a new and fundamental understanding of genetically-related conditions through multi-disciplinary research. Research has lately shifted towards medical applications. There are close connections to the Wellcome Trust Centre for Human Genetics where Professor Peter Donnelly is based.
  • Evolutionary Bioinformatics Group, led by Professor Jotun Hein.  Research includes sequence alignment and annotation, and integrative genomics and data fusion, leading to functional characterization of individual mutations.
  • Oxford Protein Informatics Group (OPIG), led by Professor Charlotte Deane, researches protein structure prediction and protein interaction networks, combining empirical research with theoretical work in collaboration with Professor Gesine Reinert.

Highlights include:

  • the Myers’ group published work (Nature Genetics 2008, Science 2010, Nature 2011) on the biology of recombination implementing new statistical algorithms and enabling them to understand genetic differences among human populations at unprecedented fine scales (PLoS Genetics 2008, 2012)
  • Professor Deane and her collaborators demonstration that protein interactions are not conserved between species (PLoS Computational Biology 2012) 
  • Professor Holmes’ new statistical methodology for the analysis of genetic copy number variation (JRSSB 2011, Nature 2010)
  • Professor Marchini’s papers on genotype imputation (PLoS Genetics 2009, Nature Reviews Genetics 2010, G3 2011, Nature Genetics 2012) and widely used software IMPUTE2 underpin analysis in the 1000 Genomes Project (Nature 2010 and 2012) 
  • Professor Donnelly, Professor Gil McVean and Professor Myers developed computational statistical methods and applied these to large surveys of human genetic variation to characterise over 30,000 human recombination hotspots

Research Groups