Newcastle University

Research Interests

Development of Statistical Methods for Population Genomic Data

My main research focuses on building models for statistical inference of the processes underlying genetic variation in large datasets of closely linked genetic markers. Publicly accessible datasets are now available that give detailed pictures of haplotype diversity from a sample of human populations. Genomic data of this form is likely to be increasingly important studying the genetic of disease: successful use of this data requires new statistical techniques. My main interest is in how we use known human evolutionary history to inform genetic studies of common human disease – such as type 1 and type II diabetes, hypertension and coronary artery disease.

I am developing models that describe genomic data and can be used to estimate genetic parameters from subdivided populations, and, more importantly, can sample from the conditional distribution of an unseen variant, conditional on genomic variation. A large number of population genomic problems can be described under this prediction-with-subdivision framework and problems of immediate interest can be made to conform such as fine-scale mapping for case-control studies of genetic variation, and the search for loci that have undergone different selective regimes in sampled subpopulations.

Recent work has focussed on methods for inferring human evolutionary history from worldwide DNA samples. Projects have concentrated on the X and Y chromosomes and mitochondrial DNA. I am the author of BATWING, which has been used extensively in inferring human history using the Y chromosome.

• How can we make best use of large databases of genetic variation?


• How do we use known human history to


• How can we best make use of complete genetic information?


• What approximations can be made so that calculations are feasible for thousands of SNPs at the same time?


• What evidence do we have for the genetic basis of difference between populations?


• What proportion of selected loci could one hope to find?


• How widespread are functional genetic variants between populations?

• Wilson IJ, Weale ME, Balding DJ. Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities. Journal of the Royal Statistical Society, Series A: Statistics in Society 2003, 166(2), 155-188.
• Wilson IJ. Approximate Likelihood Methods for SNP data with Genetic Correlations. 2012. In Preparation.
• Ermini L, Wilson IJ, Goodship THJ, Sheerin NS. Complement polymorphisms: Geographical distribution and relevance to disease. Immunobiology 2012, 217(2), 265-271.
• Soemedi R, Wilson IJ, Bentham J, Darlay R, Topf A, Zelenika D, Cosgrove C, Setchfield K, Thornborough C, Granados-Riveron J, Blue GM, Breckpot J, Hellens S, Zwolinski S, Glen E, Mamasoula C, Rahman TJ, Hall D, Rauch A, Devriendt K, Gewillig M, O'Sullivan J, Winlaw DS, Bu'Lock F, Brook F, Bhattacharya S, Lathrop M, Santibanez-Koref H, Cordell HJ, Goodship JA, Keavney BD. Contribution of Global Rare Copy Number Variants to the Risk of Sporadic Congenital Heart Disease. American Journal of Human Genetics 2012. Submitted.
• Soemedi R, Topf A, Wilson IJ, Darlay R, Rahman T, Glen E, Hall D, Huang N, Bentham J, Bhattacharya S, Cosgrove C, Brook JD, Granados-Riveron J, Setchfield K, Bu'lock F, Thornborough C, Devreindt K, Breckpot J, Hofbeck M, Lathrop M, Rauch A, Blue G, Winlaw D, Hurles M, Santibanez-Koref M, Cordell H, Goodship J, Keavney B. Phenotype-Specific Effect of Chromosome 1q21.1Rearrangements and GJA5 Duplications in 2437 CongenitalHeart Disease Patients and 6760 Controls. Human Molecular Genetics 2012, (epub ahead of print).
• Wilson IJ, Howey RAJ, Houniet DT, Santibanez-Koref M. Finding genes that influence quantitative traits with tree-based clustering. BMC Proceedings 2011, 5(s9), S98.
• Payne BAI, Wilson IJ, Hateley CA, Horvath R, Santibanez-Koref M, Samuels DC, Price DA, Chinnery PF. Mitochondrial aging is accelerated by anti-retroviral therapy through the clonal expansion of mtDNA mutations. Nature Genetics 2011, 43(8), 806-U121.
• Wilson IJ, Dawson KJ. A Markov chain Monte Carlo strategy for sampling from the joint posterior distribution of pedigrees and population parameters under a Fisher-Wright model with partial selfing. Theoretical Population Biology 2007, 72(3), 436-458.
• Santos-Lopes SS, Pereira RW, Wilson IJ, Pena SDJ. A worldwide phylogeography for the human X chromosome. PLoS ONE 2007, 2(6), e557.
• Vickers MA, McLeod E, Spector TD, Wilson IJ. Assessment of mechanism of acquired skewed X inactivation by analysis of twins. Blood 2001, 97(5), 1274-1281.
• Emery AM, Wilson IJ, Craig S, Boyle PR, Noble LR. Assignment of paternity groups without access to parental genotypes: multiple mating and developmental plasticity in squid. Molecular Ecology 2001, 10(5), 1265-1278.
• Estoup A, Wilson IJ, Sullivan C, Cornuet JM, Moritz C. Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus. Genetics 2001, 159(4), 1671-1687.
• Wilson I.J., and Balding D. J. Genealogical inference from microsatellite data.. Genetics, 1998, 150, 499-510.