Dataset Information

The correlation of methylation levels measured using Illumina 450K and EPIC BeadChips in blood samples.

ABSTRACT:

Aim

We examined concordance of methylation levels across the Illumina Infinium HumanMethylation450 BeadChip and the Infinium MethylationEPIC BeadChip.

Methods

We computed the correlation for 145 whole blood DNA samples at each of the 422,524 CpG sites measured by both chips.

Results

The correlation at some sites was high (up to r = 0.95), but many sites had low correlation (55% had r < 0.20). The low correspondence between 450K and EPIC measured methylation values at many loci was largely due to the low variability in methylation values for the majority of the CpG sites in blood.

Conclusion

Filtering out probes based on the observed correlation or low variability may increase reproducibility of BeadChip-based epidemiological studies.

SUBMITTER: Logue MW

PROVIDER: S-EPMC5967357 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Publications

The correlation of methylation levels measured using Illumina 450K and EPIC BeadChips in blood samples.

Logue Mark W MW Smith Alicia K AK Wolf Erika J EJ Maniates Hannah H Stone Annjanette A Schichman Steven A SA McGlinchey Regina E RE Milberg William W Miller Mark W MW

Epigenomics 20170815 11

<h4>Aim</h4>We examined concordance of methylation levels across the Illumina Infinium HumanMethylation450 BeadChip and the Infinium MethylationEPIC BeadChip.<h4>Methods</h4>We computed the correlation for 145 whole blood DNA samples at each of the 422,524 CpG sites measured by both chips.<h4>Results</h4>The correlation at some sites was high (up to r = 0.95), but many sites had low correlation (55% had r < 0.20). The low correspondence between 450K and EPIC measured methylation values at many l ...[more]

PMID: 28809127

Similar Datasets

Project description:BackgroundAs the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets.ResultsThe standard index of DNA methylation at any specific CpG site is ? = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (?s) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive.ConclusionsCareful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.

Dataset Information

The correlation of methylation levels measured using Illumina 450K and EPIC BeadChips in blood samples.

Aim

Methods

Results

Conclusion

Publications

The correlation of methylation levels measured using Illumina 450K and EPIC BeadChips in blood samples.

Similar Datasets

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