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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 - #308995 |
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Title:
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Statistical Model for Detecting Multiple eQTLs
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Author(s):
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Wei Zhang*+ and Jun S. Liu and Jun Zhu
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Companies:
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Harvard University and Harvard University and Rosetta Inpharmatics, LLC
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Address:
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1 Oxford St, Cambridge, MA, 02138,
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Keywords:
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eQTL ; gene module ; epistasis ; pleiotropy ; MCMC
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Abstract:
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Treating mRNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been studied in many organisms. Due to the large number of gene expression values and genetic markers, it is still a challenging question to researchers where these associations are and how eQTLs affect expression levels. We will present a statistical model to describe the associations between gene expression and genetic markers. Unlike tradition eQTL analysis, our method treats genes with similar expression values and linked with similar markers as a module. It searches for the module and its linked markers simultaneously. The linkage is defined in a statistical way such that marker interactions are automatically considered. Simulation studies and real data examples will be presented to illustrate the method.
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