A new study published in Nature Genetics and involving researchers from the Universities of Oxford, Bristol, UCL and Regeneron has revealed that genetic mutations have remarkably consistent effects across populations. The work shows that most biological factors operate similarly in all of us.

The University of Oxford (OU), the University of Copenhagen (KU), and Aarhus University (AU) are delighted to announce the launch of the recently established Pioneer Centre for Statistical and Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed) This Centre will become a vital international partner for data-driven medical research.

Dr. Samvida Venkatesh is one of the fifteen fellows joining the University of Oxford.

We have received the fantastic news of the Engineering and Physical Science Research Council (EPSRC) investing £1 Billion into Centres of Doctoral Training (CDTs). Included in the list of centres receiving funding is our own CDT in Statistics and Machine Learning.

The OxUSC team developed a 5-day course as well as a 10-day course covering all key statistical approaches for application in the field of Psychiatry. Graduate students gained a thorough understanding of foundational statistics and probability, hypothesis testing, linear regression to more advanced topics including generalised linear models, as well as multilevel models and models for longitudinal data. Emphasis was placed on the interpretation and reporting of statistical outputs. The participants also learned to perform data wrangling, analysis and visualisation tasks using the statistical software R. Statistics training has also been delivered to other audiences, including as part of the UNIQ+ scheme providing students from under-represented and disadvantaged backgrounds a chance to enhance their research skills and experience some of what Oxford offers its postgraduate students.

A company in the international pharmaceutical sector is currently exploring options to address unmet needs of vulnerable patients. These are patients who might experience periods of lack of resources and either forego treatment or compensate for spending on drugs and treatment with savings on other basic needs. OUSC has provided feedback and advice on data requirements and appropriate statistical models to measure treatment affordability, identify groups to target for additional support and measure changes in affordability over time. We have also provided ad-hoc inputs on the predictive modelling of the appearance of symptoms of a disease, using frequentist statistical methods as well as machine learning approaches.

OxUSC has implemented the statistical analysis for several clinical studies conducted by a company that has developed and is testing a novel in vitro leucocyte blood test device across a range of sectors (cross-over trials, data with biological and technical replicates). The analyses included trials with Sepsis patients, COVID-19 patients, and healthy control groups, as well as a study on healthy participants assessing the link between leucocyte readings and stress. Findings from the descriptive and multivariable and mixed-effects regression analyses are feeding into academic journal publications and providing insights into the further development of the test device.

Find out more about IMPUTE,  a powerful new statistical tool for identifying ‘disease genes’

Read about the animation that Prof Christl Donnelly and DPhil student Emmanuelle Dankwa produced around research into Covid-19 transmission.