Imperial College London

DrThibautJombart

Faculty of MedicineSchool of Public Health

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 3658t.jombart Website

 
 
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Location

 

UG11Norfolk PlaceSt Mary's Campus

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Summary

 

Summary

I am a biometrician working on statistical genetics of pathogen populations. I am currently working as a research associate with Neil Ferguson, Christophe Fraser and Simon Cauchemez. My work aims to develop novel statistical approaches for extracting information from pathogen genomes and gain insights into the spatio-temporal dynamics of infectious diseases. The methodological approaches I use include multivariate analysis, Bayesian statisticsspatial statisticsgraph theory, and phylogenetics. I am also interested in using simulations to understand which and how biological processes shape the genetic diversity observed in biological populations.

 

I am also extensively involved with the development of free software for the analysis of genetic and epidemiological data. I have recently organized a R hackathon on disease outbreak modelling using molecular data, hosted by the MRC Center for Outbreak Analysis and Modelling in January 2013

I am author or contributor for the following R packages:

- adegenet (author): multivariate analysis for genetic/genomic data

- adephylo (author): tools for testing and describing the  phylogenetic signal

- geoGraph (author): large-scale modelling of spatial data

- ade4 (contributor): multivariate analysis, graphics, spatial statistics

phylobase (contributor): handling and analyses of phylogenetic comparative data

- sedaR (contributor): spatial statistics for ecological data

- outbreaker (author): Bayesian reconstruction of disease outbreaks using genomic data

- epibase (author): basic tools for the disease outbreak analysis

 

 

More information is available from my  webpage.

Publications

Journals

Cori A, Nouvellet P, Garske T, et al., A graph-based evidence synthesis approach to detecting outbreak clusters: an application to dog rabies, Plos Computational Biology, ISSN:1553-734X

Moraga P, Dorigatti I, Kamvar Z, et al., 2018, epiflows : an R package for risk assessment of travel- related spread of disease [version 1; referees: 2 approved with reservations], F1000research, Vol:7, ISSN:2046-1402

Nagraj VP, Randhawa N, Campbell F, et al., 2018, epicontacts: Handling, visualisation and analysis of epidemiological contacts

Beugin M-P, Gayet T, Pontier D, et al., 2018, A fast likelihood solution to the genetic clustering problem, Methods in Ecology and Evolution, Vol:9, ISSN:2041-210X, Pages:1006-1016

Dupuis JR, Bremer FT, Jombart T, et al., 2018, mvmapper: Interactive spatial mapping of genetic structures, Molecular Ecology Resources, Vol:18, ISSN:1755-098X, Pages:362-367

More Publications