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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido

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Volume 12, Issue 6


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Volume 1 (2002)

A new variance stabilizing transformation for gene expression data analysis

Diana M. Kelmansky / Elena J. Martínez / Víctor Leiva
  • Corresponding author
  • Departamento de Estadística, Universidad de Valparaíso, Avda. Gran Bretaña 1111, Playa Ancha, Valparaíso, Chile
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Published Online: 2013-10-16 | DOI: https://doi.org/10.1515/sagmb-2012-0030


In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

Keywords: classical and robust estimators; linear models; microarrays; Monte Carlo method; power transformations; R software; regression methods


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About the article

Corresponding author: Víctor Leiva, Departamento de Estadística, Universidad de Valparaíso, Avda. Gran Bretaña 1111, Playa Ancha, Valparaíso, Chile, URL: www.deuv.cl/leiva, e-mail:

Published Online: 2013-10-16

Published in Print: 2013-12-01

Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 12, Issue 6, Pages 653–666, ISSN (Online) 1544-6115, ISSN (Print) 2194-6302, DOI: https://doi.org/10.1515/sagmb-2012-0030.

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