title: Approximate variance-stabilizing transformations for gene-expression microarray data.
abstract: BACKGROUND
  A variance stabilizing transformation for microarray data was recently introduced independently by several research groups. This transformation has sometimes been called the generalized logarithm or glog transformation. In this paper, we derive several alternative approximate variance stabilizing transformations that may be easier to use in some applications.
  
  
  RESULTS
  We demonstrate that the started-log and the log-linear-hybrid transformation families can produce approximate variance stabilizing transformations for microarray data that are nearly as good as the generalized logarithm (glog) transformation. These transformations may be more convenient in some applications.
authors.affiliation: Department of Applied Science, University of California, Davis, Davis, CA 95616, USA. dmrocke@ucdavis.edu
authors.forename: David M
authors.initials: DM
authors.lastname: Rocke
authors.forename: Blythe
authors.initials: B
authors.lastname: Durbin
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D017422:Sequence Analysis, DNA / Q000379:methods*