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Thesis

Statistical methods for mapping complex traits

Abstract:

The first section of this thesis addresses the problem of simultaneously identifying multiple loci that are associated with a trait, using a Bayesian Markov Chain Monte Carlo method. It is applicable to both case/control and quantitative data. I present simulations comparing the methods to standard frequentist methods in human case/control and mouse QTL datasets, and show that in the case/control simulations the standard frequentist method out performs my model for all but the highest ef...

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Institution:
University of Oxford
Division:
MSD
Oxford college:
Lincoln College
Role:
Author

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Role:
Supervisor
Role:
Supervisor
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Funding agency for:
Allchin, L
Grant:
086787/Z/08/Z
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:65f392ba-1b64-4b00-8871-7cee98809ce1
Local pid:
ora:8982
Deposit date:
2014-09-26

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