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Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities

Lookup NU author(s): Dr Ian Wilson


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We develop a flexible class of Metropolisā€“Hastings algorithms for drawing inferences about population histories and mutation rates from deoxyribonucleic acid (DNA) sequence data. Match probabilities for use in forensic identification are also obtained, which is particularly useful for mitochondrial DNA profiles. Our data augmentation approach, in which the ancestral DNA data are inferred at each node of the genealogical tree, simplifies likelihood calculations and permits a wide class of mutation models to be employed, so that many different types of DNA sequence data can be analysed within our framework. Moreover, simpler likelihood calculations imply greater freedom for generating tree proposals, so that algorithms with good mixing properties can be implemented. We incorporate the effects of demography by means of simple mechanisms for changes in population size and structure, and we estimate the corresponding demographic parameters, but we do not here allow for the effects of either recombination or selection. We illustrate our methods by application to four human DNA data sets, consisting of DNA sequences, short tandem repeat loci, single-nucleotide polymorphism sites and insertion sites. Two of the data sets are drawn from the male-specific Y-chromosome, one from maternally inherited mitochondrial DNA and one from the Ī²-globin locus on chromosome 11.

Publication metadata

Author(s): Wilson IJ; Weale ME; Balding DJ

Publication type: Article

Publication status: Published

Journal: Journal of the Royal Statistical Society, Series A: Statistics in Society

Year: 2003

Volume: 166

Issue: 2

Pages: 155-188

ISSN (print): 0964-1998

ISSN (electronic): 1467-985X

Publisher: Wiley-Blackwell Publishing Ltd.


DOI: 10.1111/1467-985X.00264


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