ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip

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 chang...

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Vydáno v:Nucleic acids research Ročník 44; číslo 3; s. e20
Hlavní autoři: Xu, Zongli, Niu, Liang, Li, Leping, Taylor, Jack A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Oxford University Press 18.02.2016
Témata:
DNA Methylation
DNA Probes
Epigenesis, Genetic
Genome-Wide Association Study
Humans
Methods Online
Oligonucleotide Array Sequence Analysis - methods
Reproducibility of Results
ISSN:0305-1048, 1362-4962, 1362-4962
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Shrnutí: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.
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ISSN:0305-1048
1362-4962
1362-4962
DOI:10.1093/nar/gkv907