Estimation of transformation parameters for microarray data.
other · Level V
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Abstract
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. R and Matlab code and test data are available from the authors on request.
Medical subject headings
- Algorithms
- Gene Expression Profiling
- Models, Genetic
- Models, Statistical
- Oligonucleotide Array Sequence Analysis