Publications by Statistical Genetics and Epidemiology

Our research spans areas of statistical genetics, in particular the development of powerful statistical approaches to analyse genetic data, as well as studying infectious diseases.

Ganjgahi, H. et al. (2025) “AI-driven reclassification of multiple sclerosis progression”, Nature Medicine, pp. 1–11.

Ignatieva, A. et al. (2025) “The length of haplotype blocks and signals of structural variation in reconstructed genealogies”, Molecular Biology and Evolution, p. msaf190.

Lehmann, B. et al. (2025) “Methodological opportunities in genomic data analysis to advance health equity”, Nature Reviews Genetics, pp. 1–15.

Freni-Sterrantino, A. et al. (2025) “Assessments and developments in constructing a National Health Index for policy-making, in the UK”, Journal of the Royal Statistical Society. Series A: Statistics in Society, 188(2), pp. 491–514.

Hu, S. et al. (2025) “Fine-scale population structure and widespread conservation of genetic effect sizes between human groups across traits”, Nature Genetics, 57(2), pp. 379–389.

Hayes, S. et al. (2025) “Understanding reservoirs of multi-host pathogens: a One Health approach to rabies in Tanzania”, One Health Cases [Preprint].

Fawkes, J. et al. (2025) “Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition”, in Proceedings of Machine Learning Research, pp. 1423–1431.

Wang, Z. and Holmes, C. (2025) “On Subjective Uncertainty Quantification and Calibration in Natural Language Generation”, in Proceedings of Machine Learning Research, pp. 3799–3807.

Ter-Minassian, L. et al. (2025) “Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation”, in Proceedings of Machine Learning Research, pp. 1900–1908.

Bajaj, S. et al. (2024) “COVID-19 testing and reporting behaviours in England across different sociodemographic groups: a population-based study using testing data and data from community prevalence surveillance surveys”, The Lancet Digital Health, 6(11), pp. e778 - e790.