Literature DB >> 24241353

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

Michael C Wu1, Bonnie R Joubert2, Pei-fen Kuan3, Siri E Håberg4, Wenche Nystad4, Shyamal D Peddada2, Stephanie J London2.   

Abstract

The Illumina Infinium HumanMethylation450 BeadChip has emerged as one of the most popular platforms for genome wide profiling of DNA methylation. While the technology is wide-spread, systematic technical biases are believed to be present in the data. For example, this array incorporates two different chemical assays, i.e., Type I and Type II probes, which exhibit different technical characteristics and potentially complicate the computational and statistical analysis. Several normalization methods have been introduced recently to adjust for possible biases. However, there is considerable debate within the field on which normalization procedure should be used and indeed whether normalization is even necessary. Yet despite the importance of the question, there has been little comprehensive comparison of normalization methods. We sought to systematically compare several popular normalization approaches using the Norwegian Mother and Child Cohort Study (MoBa) methylation data set and the technical replicates analyzed with it as a case study. We assessed both the reproducibility between technical replicates following normalization and the effect of normalization on association analysis. Results indicate that the raw data are already highly reproducible, some normalization approaches can slightly improve reproducibility, but other normalization approaches may introduce more variability into the data. Results also suggest that differences in association analysis after applying different normalizations are not large when the signal is strong, but when the signal is more modest, different normalizations can yield very different numbers of findings that meet a weaker statistical significance threshold. Overall, our work provides useful, objective assessment of the effectiveness of key normalization methods.

Entities:  

Keywords:  association testing; cotinine exposure; genome wide methylation profiling; normalization; reproducibility

Mesh:

Year:  2013        PMID: 24241353      PMCID: PMC3962542          DOI: 10.4161/epi.27119

Source DB:  PubMed          Journal:  Epigenetics        ISSN: 1559-2294            Impact factor:   4.528


  21 in total

1.  Cohort profile: the Norwegian Mother and Child Cohort Study (MoBa).

Authors:  Per Magnus; Lorentz M Irgens; Kjell Haug; Wenche Nystad; Rolv Skjaerven; Camilla Stoltenberg
Journal:  Int J Epidemiol       Date:  2006-08-22       Impact factor: 7.196

2.  High density DNA methylation array with single CpG site resolution.

Authors:  Marina Bibikova; Bret Barnes; Chan Tsan; Vincent Ho; Brandy Klotzle; Jennie M Le; David Delano; Lu Zhang; Gary P Schroth; Kevin L Gunderson; Jian-Bing Fan; Richard Shen
Journal:  Genomics       Date:  2011-08-02       Impact factor: 5.736

3.  Cigarette smoking increases copy number alterations in nonsmall-cell lung cancer.

Authors:  Yen-Tsung Huang; Xihong Lin; Yan Liu; Lucian R Chirieac; Ray McGovern; John Wain; Rebecca Heist; Vidar Skaug; Shanbeh Zienolddiny; Aage Haugen; Li Su; Edward A Fox; Kwok-Kin Wong; David C Christiani
Journal:  Proc Natl Acad Sci U S A       Date:  2011-09-12       Impact factor: 11.205

4.  Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome.

Authors:  Juan Sandoval; Holger Heyn; Sebastian Moran; Jordi Serra-Musach; Miguel A Pujana; Marina Bibikova; Manel Esteller
Journal:  Epigenetics       Date:  2011-06-01       Impact factor: 4.528

5.  Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 BeadChips.

Authors:  Jing Shen; Shuang Wang; Yu-Jing Zhang; Hui-Chen Wu; Muhammad G Kibriya; Farzana Jasmine; Habibul Ahsan; David P H Wu; Abby B Siegel; Helen Remotti; Regina M Santella
Journal:  Epigenetics       Date:  2012-12-03       Impact factor: 4.528

6.  Self-selection and bias in a large prospective pregnancy cohort in Norway.

Authors:  Roy M Nilsen; Stein Emil Vollset; Håkon K Gjessing; Rolv Skjaerven; Kari K Melve; Patricia Schreuder; Elin R Alsaker; Kjell Haug; Anne Kjersti Daltveit; Per Magnus
Journal:  Paediatr Perinat Epidemiol       Date:  2009-11       Impact factor: 3.980

7.  Bioconductor: open software development for computational biology and bioinformatics.

Authors:  Robert C Gentleman; Vincent J Carey; Douglas M Bates; Ben Bolstad; Marcel Dettling; Sandrine Dudoit; Byron Ellis; Laurent Gautier; Yongchao Ge; Jeff Gentry; Kurt Hornik; Torsten Hothorn; Wolfgang Huber; Stefano Iacus; Rafael Irizarry; Friedrich Leisch; Cheng Li; Martin Maechler; Anthony J Rossini; Gunther Sawitzki; Colin Smith; Gordon Smyth; Luke Tierney; Jean Y H Yang; Jianhua Zhang
Journal:  Genome Biol       Date:  2004-09-15       Impact factor: 13.583

8.  The allure of the epigenome.

Authors:  Naomi Attar
Journal:  Genome Biol       Date:  2012-10-23       Impact factor: 13.583

9.  450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy.

Authors:  Bonnie R Joubert; Siri E Håberg; Roy M Nilsen; Xuting Wang; Stein E Vollset; Susan K Murphy; Zhiqing Huang; Cathrine Hoyo; Øivind Midttun; Lea A Cupul-Uicab; Per M Ueland; Michael C Wu; Wenche Nystad; Douglas A Bell; Shyamal D Peddada; Stephanie J London
Journal:  Environ Health Perspect       Date:  2012-07-31       Impact factor: 9.031

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

Authors:  Andrew E Teschendorff; Francesco Marabita; Matthias Lechner; Thomas Bartlett; Jesper Tegner; David Gomez-Cabrero; Stephan Beck
Journal:  Bioinformatics       Date:  2012-11-21       Impact factor: 6.937

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  34 in total

Review 1.  Characterising the epigenome as a key component of the fetal exposome in evaluating in utero exposures and childhood cancer risk.

Authors:  Akram Ghantous; Hector Hernandez-Vargas; Graham Byrnes; Terence Dwyer; Zdenko Herceg
Journal:  Mutagenesis       Date:  2015-02-26       Impact factor: 3.000

2.  Epigenome-wide association study (EWAS) of BMI, BMI change and waist circumference in African American adults identifies multiple replicated loci.

Authors:  Ellen W Demerath; Weihua Guan; Megan L Grove; Stella Aslibekyan; Michael Mendelson; Yi-Hui Zhou; Åsa K Hedman; Johanna K Sandling; Li-An Li; Marguerite R Irvin; Degui Zhi; Panos Deloukas; Liming Liang; Chunyu Liu; Jan Bressler; Tim D Spector; Kari North; Yun Li; Devin M Absher; Daniel Levy; Donna K Arnett; Myriam Fornage; James S Pankow; Eric Boerwinkle
Journal:  Hum Mol Genet       Date:  2015-05-01       Impact factor: 6.150

3.  Type 2 diabetes and leucocyte DNA methylation: an epigenome-wide association study in over 1,500 older adults.

Authors:  Ines Florath; Katja Butterbach; Jonathan Heiss; Melanie Bewerunge-Hudler; Yan Zhang; Ben Schöttker; Hermann Brenner
Journal:  Diabetologia       Date:  2015-10-03       Impact factor: 10.122

4.  Statistical challenges in analyzing methylation and long-range chromosomal interaction data.

Authors:  Zhaohui Qin; Ben Li; Karen N Conneely; Hao Wu; Ming Hu; Deepak Ayyala; Yongseok Park; Victor X Jin; Fangyuan Zhang; Han Zhang; Li Li; Shili Lin
Journal:  Stat Biosci       Date:  2016-03-07

5.  DNA methylation modifies urine biomarker levels in 1,6-hexamethylene diisocyanate exposed workers: a pilot study.

Authors:  Leena A Nylander-French; Michael C Wu; John E French; Jayne C Boyer; Lisa Smeester; Alison P Sanders; Rebecca C Fry
Journal:  Toxicol Lett       Date:  2014-10-22       Impact factor: 4.372

6.  Expanding epigenomics to archived FFPE tissues: an evaluation of DNA repair methodologies.

Authors:  Erin M Siegel; Anders E Berglund; Bridget M Riggs; Steven A Eschrich; Ryan M Putney; Abidemi O Ajidahun; Domenico Coppola; David Shibata
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-12       Impact factor: 4.254

7.  A cross-package Bioconductor workflow for analysing methylation array data.

Authors:  Jovana Maksimovic; Belinda Phipson; Alicia Oshlack
Journal:  F1000Res       Date:  2016-06-08

8.  Maternal smoking and DNA methylation in newborns: in utero effect or epigenetic inheritance?

Authors:  Bonnie R Joubert; Siri E Håberg; Douglas A Bell; Roy M Nilsen; Stein Emil Vollset; Oivind Midttun; Per Magne Ueland; Michael C Wu; Wenche Nystad; Shyamal D Peddada; Stephanie J London
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-04-16       Impact factor: 4.254

Review 9.  The Role of DNA Methylation in Cardiovascular Risk and Disease: Methodological Aspects, Study Design, and Data Analysis for Epidemiological Studies.

Authors:  Jia Zhong; Golareh Agha; Andrea A Baccarelli
Journal:  Circ Res       Date:  2016-01-07       Impact factor: 17.367

10.  Methylome-wide association study of central adiposity implicates genes involved in immune and endocrine systems.

Authors:  Anne E Justice; Geetha Chittoor; Rahul Gondalia; Phillip E Melton; Elise Lim; Megan L Grove; Eric A Whitsel; Ching-Ti Liu; L Adrienne Cupples; Lindsay Fernandez-Rhodes; Weihua Guan; Jan Bressler; Myriam Fornage; Eric Boerwinkle; Yun Li; Ellen Demerath; Nancy Heard-Costa; Dan Levy; James D Stewart; Andrea Baccarelli; Lifang Hou; Karen Conneely; Trevor A Mori; Lawrence J Beilin; Rae-Chi Huang; Penny Gordon-Larsen; Annie Green Howard; Kari E North
Journal:  Epigenomics       Date:  2020-09-09       Impact factor: 4.778

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