Statistics Group
The group specialises in statistical methods for genetic epidemiology, including association and linkage analysis. We have a diverse program of work in this area including the following main strands:
Genetic Epidemiology of Cancer
We work closely with Tim Bishop and Julia Newton Bishop on genetic epidemiological studies of melanoma, bowel and testicular cancer, using both family-and population-based approaches.
Statistical Methodology for Genetic Epidemiology Studies
We carry out methodological research into improved methods of design and analysis for genetic epideimiology. Current research interests include gene-environment interactions, family-based association studies and genome-wide association studies and their follow-up.
Statistical Analysis of Mass Spectrometry Proteomic Data
In collaboration with Roz Banks' group, we are working in experimental design, statistical analysis and classification algorithms for clinical proteomic studies.
Other Research
We collaborate with researchers from other clinical areas within the Faculty working on the genetic epidemiology of complex diseases, in particular rheumatoid arthritis (with Ann Morgan). We are involved in pharmacogenetic projects investigating molecular predictors of response to treatment in melanoma and other cancers.
Book chapter on Linkage Analysis
Files are available for download for use in conjunction with the book chapter Linkage Analysis, Jennifer H Barrett and M Dawn Teare, in Methods in Molecular Biology: In Silico Tools for Gene Discovery, edited by B Yu and MJ Hinchcliffe, Humana Press, 2010.
The link below asks users to download a ZIP file.
Figure 1.Manhattan plot from genome-wide association study of melanoma
Figure 2.Forest plot showing the effect of SNP in CASP8 region on melanoma risk
Barrett JH, Iles MM, Harland M, Taylor JC, Aitken JF, Andresen PA, Akslen LA, Armstrong BK, Avril M-F, Azizi E, Bakker B, Bergman W, Bianchi-Scarrà G, Bressac-de Paillerets B, Calista D, Cannon-Albright LA, Corda E, Cust AE, Dębniak T, Duffy D, Dunning A, Easton DF, Friedman E, Galan P, Ghiorzo P, Giles GG, Hansson J, Hocevar M, Höiom V, Hopper JL, Ingvar C, Janssen B, Jenkins MA, Jönsson G, Kefford RF, Landi G, Landi MT, Lang J, Lubiński J, Mackie R, Malvehy J, Martin NG, Molven A, Montgomery GW, van Nieuwpoort FA, Novakovic S, Olsson H, Pastorino L, Puig S, Puig-Butille JA, Randerson-Moor J, Snowden H, Tuominen R, Van Belle P, van der Stoep N, Whiteman D.C., Zelenika D., Han J., Fang S., Lee JE, Wei Q, Lathrop GM, Gillanders EM, Brown KM, Goldstein AM, Kanetsky PA, Mann GJ, MacGregor S, Elder DE, Amos CI, Hayward NK, Gruis NA, Demenais F, Newton Bishop JA, Bishop DT on behalf of the GenoMEL Consortium. Novel melanoma loci show no evidence of association with pigmentation and nevus phenotype. Nature Genetics, epub ahead of print, 9 October 2011.
Newton-Bishop JA, Chang Y-M, Elliott F, Chan M, Leake S, Karpavicius B, Haynes S, Fitzgibbon E, Kukalizch K, Randerson-Moor J, Elder DE, Bishop DT and Barrett JH. Relationship between sun exposure and melanoma risk for tumours in different body sites in a large case-control study in a temperate climate. European Journal of Cancer 2011; 47:732-741.
Iles MM. The impact of incomplete linkage disequilibrium and genetic model choice on the analysis and interpretation of genome-wide association studies. Annals of Human Genetics 2010; 74:375-9.