Award details

Development of statistical tools to infer demographic history using linked microsatellite markers

Reference	E13397
Principal Investigator / Supervisor	Professor Mark Beaumont
Co-Investigators / Co-Supervisors	Professor David Balding
Institution	University of Reading
Department	Animal and Microbial Sciences
Funding type	Research
Value (£)	122,972
Status	Completed
Type	Research Grant
Start date	01/12/2000
End date	31/12/2004
Duration	49 months

Abstract

A new method of statistical analysis previously developed by the applicants to infer past population growth and decline using unlinked or completely linked microsatellite markers will be extended to the case of linked markers. This method uses Markov Chain Monte Carlo techniques with the theory of gene genealogies (coalescent theory) to perform Bayesian inference on parameters specifying the evolutionary history of populations. Software enabling this to be carried out will be made available to researchers in fields such as statistical genetics, human genetics, and evolutionary biology. This study will contribute to our understanding of high dimensional MCMC problems, linkage disequilibrium mapping of disease genes, and the evolutionary history of populations of biological or conservation interest.

Summary

unavailable

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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