title: Variance-stabilizing transformations for two-color microarrays.
abstract: BACKGROUND
  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.
authors.affiliation: Center for Image Processing and Integrated Computing, University of California, Davis 95616, USA. bpdurbin@ucdavis.edu
authors.forename: Blythe P
authors.initials: BP
authors.lastname: Durbin
authors.forename: David M
authors.initials: DM
authors.lastname: Rocke
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D003116:Color; D005456:Fluorescent Dyes; D020869:Gene Expression Profiling / Q000379:methods*; D014644:Genetic Variation / Q000235:genetics; D008856:Microscopy, Fluorescence / Q000379:methods; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D005456:Fluorescent Dyes