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Activity Number:
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254
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #303262 |
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Title:
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Functional Structural Equation Models for Deciphering the Path from Genomic Information to Phenotypic Variation
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Author(s):
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Li Luo*+ and Momiao Xiong
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Companies:
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The University of Texas School of Public Health and The University of Texas Health Science Center at Houston
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Address:
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1200 Herman Pressler St, Houston, TX, 77030,
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Keywords:
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structural functional equations ; quantitative traits ; complex diseases ; sequence variation ; association ; network
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Abstract:
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Current methods for uncovering the path from genomic information to phenotypic variation have serious limitations. Paradigm shift from traditional single marker approach to comprehensive system approach and from common allele approach to entire spectrum of DNA variation approach is urgently needed. We propose functional structural equation models as a general framework for unraveling the path from genomic information to phenotypic variation in which quantitative trait is taken as curve of sequence variations at different genome positions and a network model for multiple traits are assumed. We use structural equations to model the relations among multiple quantitative traits and genomic variations. The statistical methods for parameter estimation and inferences in functional structural equation models will be proposed which will be applied to Dallas heart study data set.
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