Dr Kevin Dawson | Staff Scientist

Dawson, Kevin

My PhD and early research was on evolutionary processes in which statistical associations among genes (linkage disequilibria) play a decisive role. (For example, the evolution of mutation rates.) I also investigated the population genetic foundations of the classical infinitesimal model of quantitative genetics, and related models. After that, my research interests shifted towards statistical inference problems in population genetics, and developing Bayesian computation methods. I now apply these methods to statistical problems in cancer biology.


  • Linkage disequilibrium and the infinitesimal limit.

    Dawson KJ

    Theoretical population biology 1997;52;2;137-54

  • Evolutionarily stable mutation rates.

    Dawson KJ

    Journal of theoretical biology 1998;194;1;143-57

  • The dynamics of infinitesimally rare alleles, applied to the evolution of mutation rates and the expression of deleterious mutations.

    Dawson KJ

    Theoretical population biology 1999;55;1;1-22

  • The decay of linkage disequilibrium under random union of gametes: how to calculate Bennett's principal components.

    Dawson KJ

    Theoretical population biology 2000;58;1;1-20

  • A Bayesian approach to the identification of panmictic populations and the assignment of individuals.

    Dawson KJ and Belkhir K

    Genetical research 2001;78;1;59-77

  • Interpretation of variation across marker loci as evidence of selection.

    Vitalis R, Dawson K and Boursot P

    Genetics 2001;158;4;1811-23

  • DetSel 1.0: a computer program to detect markers responding to selection.

    Vitalis R, Dawson K, Boursot P and Belkhir K

    The Journal of heredity 2003;94;5;429-31

  • A comparison of rarefaction and bayesian methods for predicting the allelic richness of future samples on the basis of currently available samples.

    Belkhir K, Dawson KJ and Bonhomme F

    The Journal of heredity 2006;97;5;483-92

  • 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.

    Wilson IJ and Dawson KJ

    Theoretical population biology 2007;72;3;436-58

  • An agglomerative hierarchical approach to visualization in Bayesian clustering problems.

    Dawson KJ and Belkhir K

    Heredity 2009;103;1;32-45

  • Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model.

    Bazin E, Dawson KJ and Beaumont MA

    Genetics 2010;185;2;587-602

  • Detecting and measuring selection from gene frequency data.

    Vitalis R, Gautier M, Dawson KJ and Beaumont MA

    Genetics 2014;196;3;799-817

  • Heterogeneity of genomic evolution and mutational profiles in multiple myeloma.

    Bolli N, Avet-Loiseau H, Wedge DC, Van Loo P, Alexandrov LB et al.

    Nature communications 2014;5;2997

  • Fast randomization of large genomic datasets while preserving alteration counts.

    Gobbi A, Iorio F, Dawson KJ, Wedge DC, Tamborero D et al.

    Bioinformatics (Oxford, England) 2014;30;17;i617-23

  • The evolutionary history of lethal metastatic prostate cancer.

    Gundem G, Van Loo P, Kremeyer B, Alexandrov LB, Tubio JMC et al.

    Nature 2015;520;7547;353-357

Dawson, Kevin