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Bioinformatics Vol. 19 no. 11 2003
Pages 1360-1367
© 2003 Oxford University Press

Estimation of transformation parameters for microarray data

Blythe Durbin 1,* and David M. Rocke 2

1 Department of Statistics
2 Department of Applied Science, UC Davis, Davis, CA 95616, USA

Received on September 9, 2002 ; revised on February 19, 2003 ; accepted on February 21, 2003

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.

Contact: bpdurbin{at}ucdavis.edu

* To whom correspondence should be addressed.


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