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bayesian methods for quantifying levels of adaptive divergence between populations from gene frequency data
Reference
BBS/B/12776
Principal Investigator / Supervisor
Professor Mark Beaumont
Co-Investigators /
Co-Supervisors
Dr Kevin Dawson
Institution
University of Reading
Department
Animal and Microbial Sciences
Funding type
Research
Value (£)
160,451
Status
Completed
Type
Research Grant
Start date
01/02/2004
End date
29/02/2008
Duration
49 months
Abstract
The identification of signatures of natural selection in genomic surveys is currently an area of intense research. The objectives of this project are to extend a hierarchical Bayesian modelling approach, currently being developed by the applicants, that allows computation of the posterior probability that a locus is influenced by selection. The extensions will allow for a number of different demographic models and types of molecular marker. The methods developed in this project will enable genomic data to be used to test hypotheses about speciation, and to determine the adaptive uniqueness of populations, which will help to inform decisions in conservation and management.
Summary
unavailable
Committee
Closed Committee - Genes & Developmental Biology (GDB)
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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