Literature DB >> 26384415

ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip.

Zongli Xu1, Liang Niu2, Leping Li3, Jack A Taylor4.   

Abstract

The Illumina HumanMethylation450 BeadChip is increasingly utilized in epigenome-wide association studies, however, this array-based measurement of DNA methylation is subject to measurement variation. Appropriate data preprocessing to remove background noise is important for detecting the small changes that may be associated with disease. We developed a novel background correction method, ENmix, that uses a mixture of exponential and truncated normal distributions to flexibly model signal intensity and uses a truncated normal distribution to model background noise. Depending on data availability, we employ three approaches to estimate background normal distribution parameters using (i) internal chip negative controls, (ii) out-of-band Infinium I probe intensities or (iii) combined methylated and unmethylated intensities. We evaluate ENmix against other available methods for both reproducibility among duplicate samples and accuracy of methylation measurement among laboratory control samples. ENmix out-performed other background correction methods for both these measures and substantially reduced the probe-design type bias between Infinium I and II probes. In reanalysis of existing EWAS data we show that ENmix can identify additional CpGs, and results in smaller P-value estimates for previously-validated CpGs. We incorporated the method into R package ENmix, which is freely available from Bioconductor website.
© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2015        PMID: 26384415      PMCID: PMC4756845          DOI: 10.1093/nar/gkv907

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  18 in total

1.  Exploration, normalization, and summaries of high density oligonucleotide array probe level data.

Authors:  Rafael A Irizarry; Bridget Hobbs; Francois Collin; Yasmin D Beazer-Barclay; Kristen J Antonellis; Uwe Scherf; Terence P Speed
Journal:  Biostatistics       Date:  2003-04       Impact factor: 5.899

2.  Evaluation of the Infinium Methylation 450K technology.

Authors:  Sarah Dedeurwaerder; Matthieu Defrance; Emilie Calonne; Hélène Denis; Christos Sotiriou; François Fuks
Journal:  Epigenomics       Date:  2011-12       Impact factor: 4.778

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

Authors:  Nizar Touleimat; Jörg Tost
Journal:  Epigenomics       Date:  2012-06       Impact factor: 4.778

4.  Adjusting batch effects in microarray expression data using empirical Bayes methods.

Authors:  W Evan Johnson; Cheng Li; Ariel Rabinovic
Journal:  Biostatistics       Date:  2006-04-21       Impact factor: 5.899

5.  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

Review 6.  DNA methylation: an introduction to the biology and the disease-associated changes of a promising biomarker.

Authors:  Jörg Tost
Journal:  Mol Biotechnol       Date:  2010-01       Impact factor: 2.695

7.  SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips.

Authors:  Jovana Maksimovic; Lavinia Gordon; Alicia Oshlack
Journal:  Genome Biol       Date:  2012-06-15       Impact factor: 13.583

8.  An epigenetic signature in peripheral blood predicts active ovarian cancer.

Authors:  Andrew E Teschendorff; Usha Menon; Aleksandra Gentry-Maharaj; Susan J Ramus; Simon A Gayther; Sophia Apostolidou; Allison Jones; Matthias Lechner; Stephan Beck; Ian J Jacobs; Martin Widschwendter
Journal:  PLoS One       Date:  2009-12-18       Impact factor: 3.240

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.  DNA methylation arrays as surrogate measures of cell mixture distribution.

Authors:  Eugene Andres Houseman; William P Accomando; Devin C Koestler; Brock C Christensen; Carmen J Marsit; Heather H Nelson; John K Wiencke; Karl T Kelsey
Journal:  BMC Bioinformatics       Date:  2012-05-08       Impact factor: 3.169

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  127 in total

1.  Alcohol and DNA Methylation: An Epigenome-Wide Association Study in Blood and Normal Breast Tissue.

Authors:  Lauren E Wilson; Zongli Xu; Sophia Harlid; Alexandra J White; Melissa A Troester; Dale P Sandler; Jack A Taylor
Journal:  Am J Epidemiol       Date:  2019-06-01       Impact factor: 4.897

2.  Methylomic profiles reveal sex-specific differences in leukocyte composition associated with post-traumatic stress disorder.

Authors:  Grace S Kim; Alicia K Smith; Fei Xue; Vasiliki Michopoulos; Adriana Lori; Don L Armstrong; Allison E Aiello; Karestan C Koenen; Sandro Galea; Derek E Wildman; Monica Uddin
Journal:  Brain Behav Immun       Date:  2019-06-19       Impact factor: 7.217

3.  Maternal swimming pool exposure during pregnancy in relation to birth outcomes and cord blood DNA methylation among private well users.

Authors:  Lucas A Salas; Emily R Baker; Mark J Nieuwenhuijsen; Carmen J Marsit; Brock C Christensen; Margaret R Karagas
Journal:  Environ Int       Date:  2019-01-05       Impact factor: 9.621

4.  Wavelet Screening identifies regions highly enriched for differentially methylated loci for orofacial clefts.

Authors:  William R P Denault; Julia Romanowska; Øystein A Haaland; Robert Lyle; Jack A Taylor; Zongli Xu; Rolv T Lie; Håkon K Gjessing; Astanand Jugessur
Journal:  NAR Genom Bioinform       Date:  2021-05-03

5.  PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.

Authors:  Joshua J Levy; Alexander J Titus; Lucas A Salas; Brock C Christensen
Journal:  Bioinformatics       Date:  2019-12-15       Impact factor: 6.937

6.  Comparison of Illumina 450K and EPIC arrays in placental DNA methylation.

Authors:  Nora Fernandez-Jimenez; Catherine Allard; Luigi Bouchard; Patrice Perron; Mariona Bustamante; Jose Ramon Bilbao; Marie-France Hivert
Journal:  Epigenetics       Date:  2019-06-28       Impact factor: 4.528

7.  Shift work, DNA methylation and epigenetic age.

Authors:  Alexandra J White; Jacob K Kresovich; Zongli Xu; Dale P Sandler; Jack A Taylor
Journal:  Int J Epidemiol       Date:  2019-10-01       Impact factor: 7.196

8.  DNA methylation profiling reveals the presence of population-specific signatures correlating with phenotypic characteristics.

Authors:  Anil K Giri; Soham Bharadwaj; Priyanka Banerjee; Shraddha Chakraborty; Vaisak Parekatt; Donaka Rajashekar; Abhishek Tomar; Aarthi Ravindran; Analabha Basu; Nikhil Tandon; Dwaipayan Bharadwaj
Journal:  Mol Genet Genomics       Date:  2017-03-07       Impact factor: 3.291

9.  Ca:Mg Ratio, APOE Cytosine Modifications, and Cognitive Function: Results from a Randomized Trial.

Authors:  Xiangzhu Zhu; Amy R Borenstein; Yinan Zheng; Wei Zhang; Douglas L Seidner; Reid Ness; Harvey J Murff; Bingshan Li; Martha J Shrubsole; Chang Yu; Lifang Hou; Qi Dai
Journal:  J Alzheimers Dis       Date:  2020       Impact factor: 4.472

10.  oxBS-MLE: an efficient method to estimate 5-methylcytosine and 5-hydroxymethylcytosine in paired bisulfite and oxidative bisulfite treated DNA.

Authors:  Zongli Xu; Jack A Taylor; Yuet-Kin Leung; Shuk-Mei Ho; Liang Niu
Journal:  Bioinformatics       Date:  2016-08-13       Impact factor: 6.937

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