I am a statistician who works with biological datasets to understand the mechanisms underlying human disease and identify possible treatments. Such work is only possible with close collaboration with biologists, and I moved to the Cambridge Institute for Medical Research in 2009 to pursue these collaborations, most closely with the Diabetes and Inflammation Laboratory. During the GWAS era, we, and others, identified many genetic polymorphisms that alter risk of human diseases such as type 1 diabetes and hypertension. My focus has now mostly shifted towards understanding the cell specific mechanism through which these variants affect risk of different immune mediated diseases and intermediate biological traits such as gene expression.
Statistically, my current work is focused on variable selection, Bayesian model averaging and empirical Bayes false discovery rates, applied to integrated analysis of multiple related datasets.
My aim for my group is that, by integrating detailed biological understanding with excellent statistical inference we will make a meaningful contribution to the understanding of autoimmune diseases.
In Feburary 2016 I moved to the Department of Medicine as a PI with the aim of establishing new collaborations. I am funded by the Wellcome Trust as a Senior Research Fellow and hold an honorary Programme Leader position at the MRC Biostatistics Unit.
- 2009-2016 :: Wellcome Trust Career Development Fellow in the Diabetes and Inflammation Laboratory (and head of the DIL stats group from 2012)
- 2003-2008 :: Research Fellow working with the BRIGHT study into the genetics of hypertension.
- 1999-2003 :: PhD: Genetic Susceptibility to leprosy: methodological issues in a linkage analysis of extended pedigrees from Karonga District, Malawi, LSHTM, part of the Karonga Prevention Study.
- 1997-1999 :: Statistical programmer, Imperial.
Jenn Asimit is a senior investigator statistician with an interest in statistical methodology development for the analysis of multiple traits, as well as fine-mapping and rare variant association approaches. She recently held a MRC Methodology Research fellowship at the Sanger institute and has developed several methods and software for rare variant association analyses and the overlap analysis of traits.
Olly Burren is undertaking a PhD, researching methods to integrate genomic and genetic datasets to better understand autoimmune disease mechanisms. He was previously head of Genome Informatics in the Diabetes and Inflammation Laboratory where he was responsible for the creation and smooth running of the ImmunoBase, T1DBase and CHiCP web resources which collate data and summary information from genomic, GWAS and ImmunoChip analyses of autoimmune diseases. He continues to maintain CHiCP as a means of visualizing Capture Hi-C datasets.
Alessandra Cabassi is a PhD student at the MRC Biostatistics Unit, jointly supervised by Paul Kirk. She is working on Bayesian nonparametric approaches for integrative modelling of genomic “big data”.
Nastasiya Grinberg is a Wellcome Trust funded postdoctoral researcher. Her research interests revolve around applications of machine learning and data mining techniques to GWAS data and in bioinformatics. She also has a special interest in scientific computing.
James Liley is a NIHR/BRC funded student on the Wellcome Trust four-year PhD programme in Mathematical Genomics and Medicine. He is working on analysis of GWAS and similar data across multiple diseases and in disease subtypes.
Elena obtained her PhD in immunology at the University of Barcelona, Spain, and worked for several years on gene regulation on the immune system at the Babraham Institute, UK. She then trained in epidemiology and now works on developing statistical and computational methods for modelling genetic regulation through transcriptomic datasets.
Loes Rutten-Jacobs is a British Heart Foundation Immediate Research Fellow in the Stroke Research Group of the Department of Clinical Neurosciences, University of Cambridge and is visiting our group until December 2018. In her research she aims to identify novel pathophysiological mechanisms underlying cerebral small vessel disease, using genetic and epidemiologic approaches.
Chris Eijsbouts (2016-2017)
Chris Eijsbouts first joined the group as an MPhil student in Computational Biology for a 3 month summer project. He stayed on afterwards as a research assistant, to continue his work on the interpretation of Capture Hi-C data. The goal of this project was to develop a method for improved identification of chromatin contacts which regulate gene expression, thereby facilitating the interpretation of GWAS studies. He will start a PhD in Oxford in Autumn 2017.
Steven Kiddle (2014-2017)
Steven Kiddle held an MRC Career Development Fellow in Biostatistics based at King’s College London, on which Chris Wallace was a statistical mentor. He visited our group in Cambridge from 2015-6, working on clustering approaches for time series and biomarkers of Alzheimer’s Disease.
He now holds a new MRC Career Development Fellowship and is based in the MRC Biostatistics Unit.
Mary Fortune (2013-2017)
Mary Fortune worked as a Wellcome Trust PhD student in the Mathematical Genomics and Medicine programme on colocalisation analysis in dependent datasets and methods for fitting models of genetic causality to summary GWAS data. She stayed on in the group to complete papers arising from her PhD work and has now moved to the MRC Biostatistics Unit.
Lucia Cilloni (Summer 2015)
Lucia did her BSc in Mathematics at the University of Newcastle Upon Tyne and her MPhil in Computational Biology at Cambridge University. She did her summer project in the Wallace group on eQTL-GWAS colocalisation analysis to identify causal genes for Type 1 Diabetes. She is now studying for a PhD in Epidemiology at Imperial College London.
Hui Guo (2010-2014)
Hui worked as a post doctoral researcher on gene expression data, and led the analysis of our study relating gene expression in PBMCs from children at risk of type 1 diabetes to autoantibody positivity. She is now a lecturer in biostatistics at University of Manchester.
Xin Yang (2011-2014)
Xin’s PhD focused on analysis of all kinds of next gen sequencing data - pooled DNA, RNA seq, and bisulfite seq. She had a special interest in modelling the extra binomial variation induced by pooling.
She moved to KCL in 2014, and from there to the CTTV project at Sanger/GSK.
Nikolas Pontikos (2011-2014)
During Niko’s PhD he worked on automated analysis of flow cytometry data and applying clustering methods to call and impute genotypes in the KIR locus.
He moved to UCL in 2014 and maintains notes about his current work.