Bioinformatics Advance Access originally published online on January 22, 2004
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Bioinformatics 20(5) © Oxford University Press 2004; all rights reserved.
Variance-stabilizing transformations for two-color microarrays
1 Center for Image Processing and Integrated Computing and 2 Department of Applied Science, University of California, Davis, CA 95616, USA
Received on August 20, 2003
; accepted on October 2, 2003
Motivation: Authors of several recent papers have independently introduced a family of transformations (the generalized-log family), which stabilizes the variance of microarray data up to the first order. However, for data from two-color arrays, tests for differential expression may require that the variance of the difference of transformed observations be constant, rather than that of the transformed observations themselves.
Results: We introduce a transformation within the generalized-log family which stabilizes, to the first order, the variance of the difference of transformed observations. We also introduce transformations from the ‘started-log’ and log-linear-hybrid families which provide good approximate variance stabilization of differences. Examples using control–control data show that any of these transformations may provide sufficient variance stabilization for practical applications, and all perform well compared to log ratios.
Contact: bpdurbin{at}ucdavis.edu
* To whom correspondence should be addressed.
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