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Nucleic Acids Res. 2016 Feb 18;44(3):e20. doi: 10.1093/nar/gkv907. Epub 2015 Sep 17.

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

Author information

1
Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA.
2
Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA Department of Environmental Health, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
3
Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA li3@niehs.nih.gov.
4
Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA taylor@niehs.nih.gov.

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.

PMID:
26384415
PMCID:
PMC4756845
DOI:
10.1093/nar/gkv907
[Indexed for MEDLINE]
Free PMC Article

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