Estimation of transformation parameters for microarray data

Blythe Durbin; David M Rocke

doi:10.1093/bioinformatics/btg178

Estimation of transformation parameters for microarray data

Blythe Durbin, David M Rocke

Public Health Sciences

Research output: Contribution to journal › Article › peer-review

51 Scopus citations

Abstract

Motivation and Results: Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.

Original language	English (US)
Pages (from-to)	1360-1367
Number of pages	8
Journal	Bioinformatics
Volume	19
Issue number	11
DOIs	https://doi.org/10.1093/bioinformatics/btg178
State	Published - Jul 22 2003

ASJC Scopus subject areas

Clinical Biochemistry
Computer Science Applications
Computational Theory and Mathematics

Access to Document

10.1093/bioinformatics/btg178

Fingerprint Dive into the research topics of 'Estimation of transformation parameters for microarray data'. Together they form a unique fingerprint.

Cite this

@article{328c3ef75f444614b0668b26a135e2fb,

title = "Estimation of transformation parameters for microarray data",

abstract = "Motivation and Results: Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.",

author = "Blythe Durbin and Rocke, {David M}",

year = "2003",

month = jul,

day = "22",

doi = "10.1093/bioinformatics/btg178",

language = "English (US)",

volume = "19",

pages = "1360--1367",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

number = "11",

}

TY - JOUR

T1 - Estimation of transformation parameters for microarray data

AU - Durbin, Blythe

AU - Rocke, David M

PY - 2003/7/22

Y1 - 2003/7/22

N2 - Motivation and Results: Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.

AB - Motivation and Results: Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency.

UR - http://www.scopus.com/inward/record.url?scp=0042594496&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0042594496&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/btg178

DO - 10.1093/bioinformatics/btg178

M3 - Article

C2 - 12874047

AN - SCOPUS:0042594496

VL - 19

SP - 1360

EP - 1367

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 11

ER -

Estimation of transformation parameters for microarray data

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this