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.

Blake, I. and Donnelly, C. (2014) “A Simple Incidence-Based Method to Avoid Misinterpretation of Bovine Tuberculosis Incidence Trends in Great Britain”, PLOS Currents, 6(Outbreaks), p. ecurrents.outbreaks.6fd216fc24317f2ce04a7c5705a30c69.

Mouradov, D. et al. (2013) “Survival in stage II/III colorectal cancer is independently predicted by chromosomal and microsatellite instability, but not by specific driver mutations”, The American Journal of Gastroenterology, 108(11), pp. 1785 – 1785.

Mouradov, D. et al. (2013) “Survival in stage II/III colorectal cancer is independently predicted by chromosomal and microsatellite instability, but not by specific driver mutations”, American Journal of Gastroenterology, 108(11), pp. 1785–1793.

Godfray, H. et al. (2013) “A restatement of the natural science evidence base relevant to the control of bovine tuberculosis in Great Britain†”, Proceedings of the Royal Society B, 280(1768), p. 20131634.

Wang, W. et al. (2013) “Integrative network-based Bayesian analysis of diverse genomics data”, BMC Bioinformatics, 14.

Yau, C. and Holmes, C. (2013) “A decision-theoretic approach for segmental classification”, The Annals of Applied Statistics, 7(3), pp. 1814–1835.

Wills, Q. et al. (2013) “Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments”, Nature Biotechnology, 31(8), pp. 748–752.

Myers, S. et al. (2013) “Microsurgery Training for the Twenty-First Century”, Archives of plastic surgery, 40(04), pp. 302–303.

Prado-Martinez, J. et al. (2013) “Great ape genetic diversity and population history”, Nature, 499(7459), pp. 471–475.

Palamara, P. and Pe’er, I. (2013) “Inference of historical migration rates via haplotype sharing”, Bioinformatics, 29(13), pp. i180 - i188.