Illumina MethylationEPIC Repeatability dataset
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ABSTRACT:
PROVIDER: EGAD00010002501 | EGA |
REPOSITORIES: EGA
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Project description:We performed a critical evaluation of the new Infinium MethylationEPIC BeadChip microarray. EPIC covers over 850,000 CpG sites, including >90% of the CpGs from the HumanMethylation450 (HM450) BeadChip and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58% of FANTOM5 enhancers, only 7% distal and 27% proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and whole-genome bisulphite sequencing data (WGBS) show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform.
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Project description:We performed a critical evaluation of the new Infinium MethylationEPIC BeadChip microarray. EPIC covers over 850,000 CpG sites, including >90% of the CpGs from the HumanMethylation450 (HM450) BeadChip and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58% of FANTOM5 enhancers, only 7% distal and 27% proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and whole-genome bisulphite sequencing data (WGBS) show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform.
2016-09-12 | GSE86831 | GEO
Project description:We performed a critical evaluation of the new Infinium MethylationEPIC BeadChip microarray. EPIC covers over 850,000 CpG sites, including >90% of the CpGs from the HumanMethylation450 (HM450) BeadChip and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58% of FANTOM5 enhancers, only 7% distal and 27% proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and whole-genome bisulphite sequencing data (WGBS) show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform.
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Project description:DNA methylation microarray analysis was performed on human donor whole blood samples from patients with and without AMD. A total of 30 patient samples including 16 Normal, 3 AREDS grade 2 (early AMD) and 11 AREDS grade 3 (intermediate AMD) (AMD total, n = 14) were selected. Samples were obtained from individuals phenotyped according to the Age-Related Eye Disease Study (AREDS) classification. DNAm levels were measured using the EPIC-array (Illumina Inc., San Diego, CA, USA). Samples run on the EPIC-array were randomized and balanced for disease status and smoking status to minimise chip and row specific effects. The EPIC-array incorporated technical controls into the experimental design. In total, 500 ng (50 ng/μL) total peripheral whole blood-derived gDNA was bisulfite converted using the EZ-96 DNA methylation kit (Zymo Research, Irvine, CA, USA) and hybridised to the EPIC-array according to the manufacturer’s instructions. Quality control analysis was performed using GenomeStudio (v2011.1). Raw IDAT files were then read into R (version 3.31) using the read.metharray.exp function within the minfi package. DNA methylation microarray data was collected in order to assess the estimated DNA methylation age using the Horvath multi-tissue, Hannum and Skin & Blood epigenetic clocks and to identify loci of differential methylation between the experimental groups.
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Project description:DNA methylation assessments of peripheral blood DNA can be used to accurately estimate the relative proportions of underlying leukocyte subtypes. Such cell deconvolution analysis relies on libraries of discriminating differentially methylated regions that are developed for each specific cell type measured. The relationship between estimated cell type proportions can then be tested for their association with phenotypes, disease states, and subject outcomes, or used in multivariable models as terms for adjustment in epigenome-wide association studies (EWAS). We obtained purified neutrophils, monocytes, B-lymphocytes, natural killer (NK) cells, CD4+ T-cells, and CD8+ T-cells from healthy subjects and measured DNA methylation with the Illumina HumanMethylationEPIC array platform. In addition, we measured DNA methylation with the EPIC array in two sets of artificial DNA mixtures comprising the above cell types. We compared three separate approaches to select reference differentially methylated region libraries (DMR library), for cell type proportion inference. The IDOL algorithm identified an optimal DMR library consisting of 450 CpG sites for inferring leukocyte subtype proportions (average R2=99.2). Importantly, the majority of CpG sites (69%) in the IDOL DMR library were unique to the new EPIC methylation array, in that they were not present on the 450K array. Our new reference DMR library is available as a Bioconductor package, has the potential to reduce any unintended technical differences arising from the combination of different generations of array platforms, and may be helpful in generating larger DMR libraries that include novel cell subtypes. A dataset of six whole blood samples were FACS sorted and the DNA was processed as a validation dataset.
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Project description:DNA methylation microarrays have become a widely used tool for investigating epigenetic modifications in various aspects of biomedical research. However, technical variability in methylation data poses challenges for downstream applications such as predictive modeling of health and disease. In this study, we measure the impact of common sources of technical variability in Illumina DNA methylation microarray data, with a specific focus on positional biases inherent within the microarray technology. By utilizing a dataset comprised of multiple, highly similar technical replicates, we identified a chamber number bias, with different chambers of the microarray exhibiting systematic differences in fluorescence intensities and their derived methylation beta values, which are only partially corrected for by existing preprocessing methods, and demonstrate that this positional bias can lead to false positive results during differential methylation testing. Additionally, our investigation identified outliers in low-level fluorescence data which might play a role in contributing to predictive error in computational models of health-relevant traits such as age.
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