Estimation of transformation parameters for microarray data

Blythe Durbin, David M Rocke

Research output: Contribution to journalArticle

50 Citations (Scopus)

Abstract

Motivation and Results: Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.

Original languageEnglish (US)
Pages (from-to)1360-1367
Number of pages8
JournalBioinformatics
Volume19
Issue number11
DOIs
StatePublished - Jul 22 2003

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Microarrays
Microarray Data
Linear Models
Skewness
Linear Model
Model-based
First-order
Family

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Estimation of transformation parameters for microarray data. / Durbin, Blythe; Rocke, David M.

In: Bioinformatics, Vol. 19, No. 11, 22.07.2003, p. 1360-1367.

Research output: Contribution to journalArticle

Durbin, Blythe ; Rocke, David M. / Estimation of transformation parameters for microarray data. In: Bioinformatics. 2003 ; Vol. 19, No. 11. pp. 1360-1367.
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