Area of Research: Statistical genomics in immune mediated diseases
Chris Wallace is a Wellcome Trust Senior Research Fellow at the University of Cambridge and joined the MRC BSU as an honorary Programme Leader in February 2016. Prior to this, she held fellowships from the Wellcome Trust and the British Heart Foundation at other institutes in Cambridge and Queen Mary University of London, where she worked on various aspects of statistical genomics. Her focus is on the twin goals of using genomic analysis to make meaningful contributions to the understanding of human autoimmune disease and the development of statistical methodology to enable these contributions.
BSU Research Overview
Chris Wallace’s research programme has three complementary aims. First, to develop the statistical tools needed to identify genetic associations with disease, then robustly and empirically link each genetic association with a gene, cell type, stimulatory condition and ultimately a biological pathway. Specifically, this requires methods for:
- horizontal integration of different layers of omics data
- mapping the variants which regulate gene expression
- “fine mapping” causal genetic variants from amongst associated variants in genetic association data, typically using sparse variable selection
- “fine mapping” regulatory contacts in 3D maps of folded DNA from technologies such as promoter capture Hi-C
While the methods are broadly applicable across a range of common complex diseases, Chris’s second aim is to use the methods to understand the causes of autoimmune diseases, the links between different diseases, and identify pharmaceutical targets and opportunities for pharmaceutical re-purposing. Finally, a third strand of research aims to build upon what we have learnt about mechanisms underlying to disease to make stronger inference about the relationship of omics biomarkers and treatment outcomes in childhood arthritis, in order to aid treatment decisions.
For further details of my group’s research, including papers and code, see chr1swallace.github.io.
Selected PapersEijsbouts C, Burren O, Newcombe P, Wallace C. (2019)Fine mapping chromatin contacts in capture Hi-C data.
BMC genomics :
Fortune M, Wallace C. (2018)simGWAS: a fast method for simulation of large scale case-control GWAS summary statistics
Burren OS, Rubio García A, Javierre BM, Rainbow DB, Cairns J, Cooper NJ, Lambourne JJ, Schofield E, Castro Dopico X, Ferreira RC, Coulson R, Burden F, Rowlston SP, Downes K, Wingett SW, Frontini M, Ouwehand WH, Fraser P, Spivakov M, Todd JA, Wicker LS, Cutler AJ, Wallace C. (2017)Chromosome contacts in activated T cells identify autoimmune disease candidate genes
Genome Biology 18:165:
Javierre BM*, Burren OS*, Wilder SP*, Kreuzhuber R*, Hill SM, Sewitz S, Cairns J, Wingett SW, Várnai C, Thiecke MJ, Burden F, Farrow S, Cutler AJ, Rehnström K, Downes K, Grassi L, Kostadima M, Freire-Pritchett P, Wang F, Stunnenberg HG, Todd JA, Zerbino DR, Stegle O, Ouwehand WH, Frontini M#, Wallace C#, Spivakov M#, Fraser P#. (2016)Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters
Cell vol. 167, no. 5, pp: 1369-1384
Liley J, Todd JA, Wallace C. (2017)A genetic test for differential causative pathology in disease subgroups
Nature Genetics 49(2): 310-316
Fortune MD, Guo H, Burren O, Schofield E, Walker NM, Ban M, Sawcer SJ, Bowes J, Worthington J, Barton A, Eyre S, Todd JA, Wallace C. (2015)Statistical colocalization of genetic risk variants for related autoimmune diseases in the context of common controls
Nature Genetics 47(7): 839-846
Liley J, Wallace C. (2015)A Pleiotropy-Informed Bayesian False Discovery Rate Adapted to a Shared Control Design Finds New Disease Associations From GWAS Summary Statistics.
PLoS genetics vol. 11, no. 2, pp. e1004926.: