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A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distr...

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Autores principales: Teschendorff, Andrew E., Marabita, Francesco, Lechner, Matthias, Bartlett, Thomas, Tegner, Jesper, Gomez-Cabrero, David, Beck, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546795/
https://www.ncbi.nlm.nih.gov/pubmed/23175756
http://dx.doi.org/10.1093/bioinformatics/bts680
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author Teschendorff, Andrew E.
Marabita, Francesco
Lechner, Matthias
Bartlett, Thomas
Tegner, Jesper
Gomez-Cabrero, David
Beck, Stephan
author_facet Teschendorff, Andrew E.
Marabita, Francesco
Lechner, Matthias
Bartlett, Thomas
Tegner, Jesper
Gomez-Cabrero, David
Beck, Stephan
author_sort Teschendorff, Andrew E.
collection PubMed
description Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online
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spelling pubmed-35467952013-01-16 A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data Teschendorff, Andrew E. Marabita, Francesco Lechner, Matthias Bartlett, Thomas Tegner, Jesper Gomez-Cabrero, David Beck, Stephan Bioinformatics Original Papers Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online Oxford University Press 2013-01-15 2012-11-21 /pmc/articles/PMC3546795/ /pubmed/23175756 http://dx.doi.org/10.1093/bioinformatics/bts680 Text en © The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Teschendorff, Andrew E.
Marabita, Francesco
Lechner, Matthias
Bartlett, Thomas
Tegner, Jesper
Gomez-Cabrero, David
Beck, Stephan
A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title_full A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title_fullStr A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title_full_unstemmed A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title_short A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
title_sort beta-mixture quantile normalization method for correcting probe design bias in illumina infinium 450 k dna methylation data
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546795/
https://www.ncbi.nlm.nih.gov/pubmed/23175756
http://dx.doi.org/10.1093/bioinformatics/bts680
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