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Activity Number:
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154
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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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ENAR
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| Abstract - #309776 |
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Title:
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A Novel Method of Identifying Differentially Expressed Genes Based on Probe-Level Data for GeneChip Arrays
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Author(s):
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Zhongxue Chen*+ and Monnie McGee and Qingzhong Liu and Megan Kong and Richard Scheuermann
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Companies:
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Southern Methodist University and Southern Methodist University and New Mexico Institute of Mining and Technology and The University of Texas Southwestern Medical Center at Dallas and The University of Texas Southwestern Medical Center at Dallas
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Address:
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3225 Daniels Ave Statistical Science Dep, Dallas, TX, 75275,
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Keywords:
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Differentially Expressed Gene ; Microarray ; False Positive Rate ; Receiver Operating Characteristic ; spike-in ; GeneChip
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Abstract:
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Current gene selection methods suffer from the -multiple comparisons problem due to the large number of significance tests that must be performed. Methods that control false discovery rate (FDR) are difficult to estimate the number of true negatives and are limited to the application for real data. We propose a novel method for identifying differentially expressed genes (DEGs), probe level identification of differentially expressed genes (PLIDEG). With the extra information provided by probe level data, PLIDEG can not only control type I error but also increase the power of detecting DEGs simultaneously. Therefore, PLIDEG can efficiently separate differentially expressed genes and non-DEGs without requiring estimation of the number of non-DEGs. Based on theoretical analysis and real microarray data, we show that PLIDEG has better performance than other methods.
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