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Activity Number:
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572
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #305121 |
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Title:
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A Rank Approach to Identify Outlier Tissue
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Author(s):
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Dung-Tsa Chen*+ and Lin-An Chen
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Companies:
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Moffitt Cancer Center & Research Institute and National Chiao-Tung University
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Address:
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12902 Magnolia Drive, Tampa, FL, 33612,
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Keywords:
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outlier gene ; outlier tissue ; COPA ; outlier sum
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Abstract:
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Microarray analysis has been advanced to identify outlier genes which are over-expressed only in a small number of disease samples (outlier tissues). There are several studies developing various "outlier" approaches in microarray research to identify "outlier" genes, such as cancer outlier profile analysis (COPA), outlier sums statistics, and outlier robust t statistics. These approaches focus on identifying "outlier" genes, but have limitations to extend to identify "outlier" tissue. In this study, we propose a rank approach to identify outlier tissues. The rank approach includes two steps. The first step is to select differentially expressed (DE) genes by the SAM method. The 2nd step is to rank DE genes to identify outlier tissues. Sensitivity analysis is performed to evaluate the rank approach and to compare its performance with the COPA and the outlier sum methods.
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