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.

Wills, Q. et al. (2017) “The nature and nurture of cell heterogeneity: accounting for macrophage gene-environment interactions with single-cell RNA-Seq”, BMC Genomics, 18(1).

Salter-Townshend, M. and Myers, S. (2017) “Local Ancestry Inference in Non-Model Organisms”, in HUMAN HEREDITY, pp. 244–244.

Rukat, T. et al. (2017) “Bayesian boolean matrix factorisation”, in 34th International Conference on Machine Learning, ICML 2017, pp. 4539–4549.

Esperança, P., Aslett, L. and Holmes, C. (2017) “Encrypted accelerated least squares regression”, in Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017.

Nicholson, G. and Holmes, C. (2016) “A note on statistical repeatability and study design for high-throughput assays”, Statistics in Medicine, 36(5), pp. 790–798.

Filippi, S., Holmes, C. and Nieto Barajas, L. (2016) “Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures”, Electronic Journal of Statistics, 10(2), pp. 3338–3354.

Watson, J., Nieto-Barajas, L. and Holmes, C. (2016) “Characterizing variation of nonparametric random probability measures using the Kullback–Leibler divergence”, Statistics, 51(3), pp. 558–571.

Al Omran, Y. et al. (2016) “Effects of habitual physical activity on microsurgical performance”, British Journal of Oral and Maxillofacial Surgery, 54(9), pp. 1025–1027.

Taylor, A. et al. (2016) “Artemether-lumefantrine and dihydroartemisinin-piperaquine exert inverse selective pressure on Plasmodium Falciparum drug sensitivity-associated haplotypes in Uganda”, Open Forum Infect Dis, 4(1), p. ofw229.