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Cambridge Immunology Network



The research programme proposes to develop a range of improved statistical techniques and algorithms for finding important combinations of features in large genetic and genomics datasets that characterise or predict health outcomes and for carrying out integrative analyses to characterise heterogeneous disease processes. The new methods will be accompanied by the development of freely available software and will be used in a number of collaborative projects to improve understanding of the regulation of genes and immunological response, to study gene-environment interactions and to develop biomarker-based prognostic signatures.


Key publications: 

Bottolo, L., Chadeau-Hyam, M. coll. & Richardson, S. (2013). GUESS-ing polygenic associations with multiple phenotypes using a GPU-based Evolutionary Stochastic Search algorithm. PLOS Genetics. In press.

Papathomas, M., Molitor, J., Hoggart, C., Hastie, D. & Richardson, S. (2012). Exploring Data from Genetic Association Studies Using Bayesian Variable Selection and the Dirichlet Process: Application to Searching for Gene × Gene Patterns. Genetic Epidemiology. 36: 663-674.

Bottolo, L., Chadeau-Hyam, M., Hastie, D.I., Langley, S.R., Petretto, E., Tiret, L., Tregouet, D. & Richardson, S. (2011). ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration. Bioinformatics, 27: 587-588.

Bottolo, L., Petretto, E., Blankenberg, S., Cambien, F., Cook, S.A., Tiret, L. & Richardson, S. (2011). Bayesian detection of expression quantitative trait loci hot spots. Genetics. 189:1449-1459.

Turro, E., Su, S-Y., Goncalves, A., Coin, L.J.M., Richardson, S. & Lewin, A. (2011). Haplotype and isoform specic expression estimation using multi-mapping RNA-seq reads. Genome Biology, 12: R13.

Petretto, E., Bottolo, L., Langley, S. R., Heining, M., McDermott-Roe, C., Sarwar, R., Pravenec, M., Hübner, N., Aitman, T. J., Cook, S. A. & Richardson, S. (2010). New Insights into the Genetic Control of Gene Expression using a Bayesian Multi-tissue Approach. PLoS Comput Biol  6(4): e1000737.

Bottolo, L. & Richardson, S. (2010). Evolutionary Stochastic Search for Bayesian model exploration. Bayesian Analysis, 5(3), 583—618.

Ratmann, O., Andrieu, C., Wiuf, C. & Richardson, S. (2009). Model criticism based on likelihood-free inference, with an application to protein network evolution. Proc Natl Acad Sci USA. 106:10576-10581.

Lewin, A., Richardson, S., Marshall, C., Glazier, A. & Aitman, T. (2006). Bayesian modelling of differential gene expression. Biometrics, 62:1-9.

Other Professional Activities

Public Involvement/Engagement

Evidence given to the Lords Science and Technology Committee - UK Science, Research and Technology Capability and Influence in Global Disease Outbreaks   Aired live on Parliament TV:

Seminar for All-Party Parliamentary Group, Parliamentary and Scientific Committee on Statistics and COVID-19:

The Observer: ‘Coronavirus statistics: what can we trust and what should we ignore?’

Significance magazine: ‘A perspective on real-time epidemic surveillance for Covid-19’

Professor Sylvia  Richardson
Not available for consultancy


Person keywords: 
multiphenotype analysis
Dirichlet Process modelling
high dimensional data
biomarker based signatures
integrative genomics
network modelling
information synthesis
Bayesian inference
population MCMC
eQTL analysis
Gaussian processes
differential equations
sparse regression
gene-environment interactions
model uncertainty
penalised regression
gene regulation
structural equation models