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Unpublished Paper
Linear Models for Microarray Data Analysis: Hidden Similarities and Differences
UW Biostatistics Working Paper Series
  • M. Kathleen Kerr, University of Washington
Date of this Version
5-16-2003
Comments
This paper will appear in the Journal of Computational Biology.
Abstract
In the past several years many linear models have been proposed for analyzing two-color microarray data. As presented in the literature, many of these models appear dramatically different. However, many of these models are reformulations of the same basic approach to analyzing microarray data. This paper demonstrates the equivalence of some of these models. Attention is directed at choices in microarray data analysis that have a larger impact on the results than the choice of linear model.
Citation Information
M. Kathleen Kerr. "Linear Models for Microarray Data Analysis: Hidden Similarities and Differences" (2003)
Available at: http://works.bepress.com/kathleen_kerr/3/