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Kelmansky, D.M.; Martínez, E.J.; Leiva, V. "A new variance stabilizing transformation for gene expression data analysis" (2013) Statistical Applications in Genetics and Molecular Biology. 12(6):653-666
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Abstract:

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.

Registro:

Documento: Artículo
Título:A new variance stabilizing transformation for gene expression data analysis
Autor:Kelmansky, D.M.; Martínez, E.J.; Leiva, V.
Filiación:Departamento de Estadística, Universidad de Valparaíso, Avda. Gran Bretaña 1111, Playa Ancha, Valparaíso, Chile
Instituto de Cálculo, FCEN, Universidad de Buenos Aires, Argentina
Palabras clave:Classical and robust estimators; Linear models; Microarrays; Monte Carlo method; Power transformations; R software; Regression methods; article; contamination; data analysis; family; gene expression; genetic transformation; genomics; human; human genome; methodology; microarray analysis; Monte Carlo method; statistical model; variance; Algorithms; Computer Simulation; Data Interpretation, Statistical; Gene Expression Profiling; Humans; Linear Models; Models, Genetic; Monte Carlo Method; Oligonucleotide Array Sequence Analysis; Software
Año:2013
Volumen:12
Número:6
Página de inicio:653
Página de fin:666
DOI: http://dx.doi.org/10.1515/sagmb-2012-0030
Título revista:Statistical Applications in Genetics and Molecular Biology
Título revista abreviado:Stat. Appl. Genet. Mol. Biol.
ISSN:15446115
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_15446115_v12_n6_p653_Kelmansky

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Citas:

---------- APA ----------
Kelmansky, D.M., Martínez, E.J. & Leiva, V. (2013) . A new variance stabilizing transformation for gene expression data analysis. Statistical Applications in Genetics and Molecular Biology, 12(6), 653-666.
http://dx.doi.org/10.1515/sagmb-2012-0030
---------- CHICAGO ----------
Kelmansky, D.M., Martínez, E.J., Leiva, V. "A new variance stabilizing transformation for gene expression data analysis" . Statistical Applications in Genetics and Molecular Biology 12, no. 6 (2013) : 653-666.
http://dx.doi.org/10.1515/sagmb-2012-0030
---------- MLA ----------
Kelmansky, D.M., Martínez, E.J., Leiva, V. "A new variance stabilizing transformation for gene expression data analysis" . Statistical Applications in Genetics and Molecular Biology, vol. 12, no. 6, 2013, pp. 653-666.
http://dx.doi.org/10.1515/sagmb-2012-0030
---------- VANCOUVER ----------
Kelmansky, D.M., Martínez, E.J., Leiva, V. A new variance stabilizing transformation for gene expression data analysis. Stat. Appl. Genet. Mol. Biol. 2013;12(6):653-666.
http://dx.doi.org/10.1515/sagmb-2012-0030