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Activity Number:
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244
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #308405 |
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Title:
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A Bayesian Method for the Detection of Epistasis in Quantitative Trait Loci
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Author(s):
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Edward Boone*+
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Companies:
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Virginia Commonwealth University
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Address:
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Department of SSOR, Richmond, VA, 23284,
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Keywords:
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Bayesian Statistics ; Quantitative Trait Loci ; Markov Chain Monte Carlo Model Composition ; Genetics
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Abstract:
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Epistasis or the interaction between loci on a genome is of great interest to geneticists. However, this problem is complicated by the actual definition of interaction and the number of loci and interactions versus the number of observations. Often researchers find there simply isn't enough data to sort through a large number of loci on a genome and then compound that with the interaction effects. This presentation discusses the definition of interaction in Recombinant Inbred Lines (RIL) and proposes a method to search for the loci as well as the interaction (epistasis) effects. This Bayesian method utilizes a Markov Chain Monte Carlo Model Composition approach using restricted sample spaces. The method is illustrated with the Arabidopsis thaliana plant considering cotyledon opening against 38 loci using 158 lines.
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