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.

Padellini, T. et al. (2021) “Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: a space-time study.”, medRxiv [Preprint].

Tan, Y. et al. (2021) “Enhanced Recovery Pathways for Flap-Based Reconstruction: Systematic Review and Meta-Analysis”, Aesthetic Plastic Surgery, 45(5), pp. 2096–2115.

Nicholson, G. et al. (2021) “Interoperability of statistical models in pandemic preparedness: principles and reality”, arXiv.

Davies, B. et al. (2021) “Altering the binding properties of PRDM9 partially restores fertility across the species boundary”, Molecular Biology and Evolution, 38(12), pp. 5555–5562.

Jiang, X., Holmes, C. and McVean, G. (2021) “The impact of age on genetic risk for common diseases”, PLOS Genetics, 17(8).

Watson, J. et al. (2021) “Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision”, eLife, 10.

Wymant, C. et al. (2021) “The epidemiological impact of the NHS COVID-19 app”, Nature, 594(7863), pp. 408–412.

Speidel, L. et al. (2021) “Inferring population histories for ancient genomes using genome-wide genealogies”, Molecular Biology and Evolution, 38(9), pp. 3497–3511.

Davies, R. et al. (2021) “Rapid genotype imputation from sequence with reference panels”, Nature Genetics, 53(7), pp. 1104–1111.

Nicholson, G. et al. (2021) “Local prevalence of transmissible SARS-CoV-2 infection: an integrative causal model for debiasing fine-scale targeted testing data”, p. 2021.05.17.21256818.