skip to primary navigationskip to content

Professor Sylvia Richardson

Research Interests

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.


clustering ; 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

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.