Skip to main content

SEMINAR: Statistical genomics approaches to bacterial transmission

Date: 17 June 2013 | Time: 12.30pm-1.30pm | Venue: GLT3, WMS


Dr Xavier Didelot, School of Public Health, Imperial College London


Understanding how human infectious diseases spread from person to person is essential to decide which containment measures will effectively limit their burden on public health. A new genomic methodology to study transmission is starting to emerge which holds great promise to complement traditional epidemiological approaches.

Because mutations accumulate at a relatively low and constant rate on the genome of a pathogen, if a person infected another, the genomes they carry are expected to be highly similar. This simple principle can be inverted, in order to assess the probability of transmission between two individuals given the similarity of the genomes infecting them. We will show how this method can be applied to investigate the transmission of Clostridium difficile in UK hospitals as well as Helicobacter pylori in a rural South African setting.


Xavier Didelot obtained his doctorate in Statistical Genetics from the University of Oxford in 2007. He spent three years as a research fellow at the University of Warwick before moving back to Oxford in 2010. He took his current appointment as Lecturer at Imperial College London in 2012. He is the author of ClonalFrame, a computer software that infers the relationships between a sample of bacteria while accounting for the disruptive effect of recombination. His primary research interests are in developing new methods that can be used to analyse whole microbial genome sequences. Such data is becoming increasingly available thanks to the advent of high-throughput sequencing technologies, and has great potential to lead to new insights into the evolution, ecology and epidemiology of many microbes.


Xavier Didelot