JSM 2005 - Toronto

Abstract #304372

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 477
Type: Topic Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #304372
Title: Crossplatform Comparison of Microarray Gene Expression Intensities
Author(s): Kellie J. Archer*+ and Daniela Puiu and Catherine I. Dumur
Companies: Virginia Commonwealth University and Virginia Commonwealth University and Virginia Commonwealth University
Address: 14318 Beachmere Dr, Chester, VA, 23831, United States
Keywords: microarray ; cross-platform ; invariant ; errors-in-regression
Abstract:

Due to the growing number of microarray data repositories and the requirement on behalf of journals and granting institutions that data be made publicly available, it may be of interest to explore methods for merging microarray data across platforms for the purpose of performing statistical analyses. Therefore, this research investigated interlaboratory variability among RNA samples hybridized to three microarray platforms. Additionally, we explored the feasibility of combining intensities from three platforms for the purpose of conducting further analyses. Among a set of technical replicates, proportions of invariant features and the coefficient of variation were compared. For RNA extracted from breast and ovarian tumor samples, first platform-specific normalization methods were applied and then data were combined by scaling all arrays to a common baseline. Subsequent analyses were restricted to sequence-matched features. Because intensities resulting from each platform are subject to random measurement errors, errors-in-regression models were applied to compare the accuracy and consistency of gene expression measurements.


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Revised March 2005