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Activity Number:
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137
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 7, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #306547 |
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Title:
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Bayesian Analysis of EST Data with Multiple Libraries and Multiple Types of Tissues
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Author(s):
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Fang Yu*+ and Ming-Hui Chen and Lynn Kuo and Peng Huang and Wanling Yang
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Companies:
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University of Connecticut and University of Connecticut and University of Connecticut and Medical University of South Carolina and The University of Hong Kong
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Address:
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Department of Statistics, Storrs, CT, 06269,
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Keywords:
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Dirichlet distribution ; gene expression ; mixture distributions ; multinomial distribution ; shrinkage estimators
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Abstract:
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ESTs (Expressed Sequence Tags) are usually a one-pass sequencing reading of cloned cDNAs derived from a certain tissue. The frequency of unique tags among different unbiased cDNA libraries is used to infer the relative expression level of each tag. In this paper, we consider a multinomial model with novel priors of nonlinear Dirichlet distributions for EST data with multiple libraries and/or multiple types of tissues. The properties of the priors and the implied posteriors are examined in detail. Gene selection algorithms are developed to detect the co-expression within the same type of tissue and the differential expression between different types of tissues. A real EST dataset is used to illustrate the proposed model.
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