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Activity Number:
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143
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #308299 |
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Title:
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Statistical Framework for Integrative Analysis of Multiple Gene Expression
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Author(s):
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Chien-Cheng Tseng*+
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Companies:
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University of Pittsburgh
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Address:
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130 Desoto Street, Pittsburgh, PA, 15218,
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Keywords:
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meta-analysis ; microarray ; expression profile
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Abstract:
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With the availability of tons of expression profiles on the web, the needs of meta-analyses to enhance different types of microarray analyses are obvious. For detection of differentially expressed genes, most of the current efforts are focused on comparing and evaluating gene lists obtained from each dataset and a real sense of information integration is rarely performed. In this paper, we propose a general framework of statistical integration by a weighted averaged statistics when multiple biologically relevant data sets are available and a permutation analysis is applied to control the false discovery rate. A subset of differentially expressed genes identified in the integrative analysis are otherwise ignored in each individual analysis. We will show the advantage of combining information from multiple data sets through simulation and real data of lung and prostate cancer.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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