Literature DB >> 22690668

Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

Nizar Touleimat1, Jörg Tost.   

Abstract

BACKGROUND: Huge progress has been made in the development of array- or sequencing-based technologies for DNA methylation analysis. The Illumina Infinium(®) Human Methylation 450K BeadChip (Illumina Inc., CA, USA) allows the simultaneous quantitative monitoring of more than 480,000 CpG positions, enabling large-scale epigenotyping studies. However, the assay combines two different assay chemistries, which may cause a bias in the analysis if all signals are merged as a unique source of methylation measurement. MATERIALS &
METHODS: We confirm in three 450K data sets that Infinium I signals are more stable and cover a wider dynamic range of methylation values than Infinium II signals. We evaluated the methylation profile of Infinium I and II probes obtained with different normalization protocols and compared these results with the methylation values of a subset of CpGs analyzed by pyrosequencing.
RESULTS: We developed a subset quantile normalization approach for the processing of 450K BeadChips. The Infinium I signals were used as 'anchors' to normalize Infinium II signals at the level of probe coverage categories. Our normalization approach outperformed alternative normalization or correction approaches in terms of bias correction and methylation signal estimation. We further implemented a complete preprocessing protocol that solves most of the issues currently raised by 450K array users.
CONCLUSION: We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.

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Year:  2012        PMID: 22690668     DOI: 10.2217/epi.12.21

Source DB:  PubMed          Journal:  Epigenomics        ISSN: 1750-192X            Impact factor:   4.778


  221 in total

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3.  Identification, Heritability, and Relation With Gene Expression of Novel DNA Methylation Loci for Blood Pressure.

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Journal:  Hypertension       Date:  2020-06-10       Impact factor: 10.190

4.  ChAMP: 450k Chip Analysis Methylation Pipeline.

Authors:  Tiffany J Morris; Lee M Butcher; Andrew Feber; Andrew E Teschendorff; Ankur R Chakravarthy; Tomasz K Wojdacz; Stephan Beck
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5.  A-clustering: a novel method for the detection of co-regulated methylation regions, and regions associated with exposure.

Authors:  Tamar Sofer; Elizabeth D Schifano; Jane A Hoppin; Lifang Hou; Andrea A Baccarelli
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6.  Considerations for normalization of DNA methylation data by Illumina 450K BeadChip assay in population studies.

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Journal:  Epigenetics       Date:  2013-08-19       Impact factor: 4.528

7.  A systematic assessment of normalization approaches for the Infinium 450K methylation platform.

Authors:  Michael C Wu; Bonnie R Joubert; Pei-fen Kuan; Siri E Håberg; Wenche Nystad; Shyamal D Peddada; Stephanie J London
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8.  ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip.

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Journal:  Nucleic Acids Res       Date:  2015-09-17       Impact factor: 16.971

9.  DNA methylation and childhood asthma in the inner city.

Authors:  Ivana V Yang; Brent S Pedersen; Andrew Liu; George T O'Connor; Stephen J Teach; Meyer Kattan; Rana Tawil Misiak; Rebecca Gruchalla; Suzanne F Steinbach; Stanley J Szefler; Michelle A Gill; Agustin Calatroni; Gloria David; Corinne E Hennessy; Elizabeth J Davidson; Weiming Zhang; Peter Gergen; Alkis Togias; William W Busse; David A Schwartz
Journal:  J Allergy Clin Immunol       Date:  2015-03-11       Impact factor: 10.793

10.  Influence of donor age on induced pluripotent stem cells.

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