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Bioinformatics. 2003 Jul 22;19(11):1360-7.

Estimation of transformation parameters for microarray data.

Author information

1
Department of Statistics, UC Davis, Davis, CA 95616, USA. bpdurbin@ucdavis.edu

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.

AVAILABILITY:

R and Matlab code and test data are available from the authors on request.

PMID:
12874047
DOI:
10.1093/bioinformatics/btg178
[Indexed for MEDLINE]

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