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J Comput Biol. 2003;10(6):891-901.

Linear models for microarray data analysis: hidden similarities and differences.

Author information

1
Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA. katiek@u.washington.edu

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.

PMID:
14980016
DOI:
10.1089/106652703322756131
[Indexed for MEDLINE]

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