Correction of fluorescence bias on Affymetrix genotyping microarrays

Ralph Rippe; JJ Meulman; Paul Eilers

doi:10.1002/cem.2436

Correction of fluorescence bias on Affymetrix genotyping microarrays

Ralph Rippe, JJ Meulman, Paul Eilers

Epidemiology

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

Abstract

Fluorescence signals obtained from microarrays for single nucleotide polymorphism genotyping show systematic strong variations in the levels for single nucleotide polymorphisms and arrays as well as genotypes. Linear models that take all three effects into account fit very well. Once the model parameters have been estimated for a set of reference arrays, they can be used to calibrate new arrays in a simple way, thereby improving genotyping and analysis of copy number variations and allelic imbalance. Copyright (c) 2012 John Wiley & Sons, Ltd.

Original language	Undefined/Unknown
Pages (from-to)	191-196
Number of pages	6
Journal	Journal of Chemometrics
Volume	26
Issue number	5
DOIs	https://doi.org/10.1002/cem.2436
Publication status	Published - 2012

Research programs

EMC NIHES-01-66-01

Access to Document

10.1002/cem.2436

http://hdl.handle.net/1765/74105

Cite this

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title = "Correction of fluorescence bias on Affymetrix genotyping microarrays",

abstract = "Fluorescence signals obtained from microarrays for single nucleotide polymorphism genotyping show systematic strong variations in the levels for single nucleotide polymorphisms and arrays as well as genotypes. Linear models that take all three effects into account fit very well. Once the model parameters have been estimated for a set of reference arrays, they can be used to calibrate new arrays in a simple way, thereby improving genotyping and analysis of copy number variations and allelic imbalance. Copyright (c) 2012 John Wiley & Sons, Ltd.",

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AB - Fluorescence signals obtained from microarrays for single nucleotide polymorphism genotyping show systematic strong variations in the levels for single nucleotide polymorphisms and arrays as well as genotypes. Linear models that take all three effects into account fit very well. Once the model parameters have been estimated for a set of reference arrays, they can be used to calibrate new arrays in a simple way, thereby improving genotyping and analysis of copy number variations and allelic imbalance. Copyright (c) 2012 John Wiley & Sons, Ltd.

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DO - 10.1002/cem.2436

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