Calibration data EPIC array: Mouse and Rat
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PROVIDER: PRJNA730557 | ENA |
REPOSITORIES: ENA
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Project description:Illumina Infinium HumanMethylation850 BeadChip (also known as Illumina EPIC array, GPL23976) was used to generate DNA methylation data from synthetic DNA from 3 species. The DNA samples from each species were enzymatically manipulated so that they would exhibit 0%, 25%, 50%, 75% and 100% percent methylation at each CpG location, respectively. The variable “ProportionMethylated” (with ordinal values 0, 0.25, 0.5, 0.75, 1) can be interpreted as a benchmark for each CpG that maps to the respective genome. Thus, the DNA methylation levels of each CpG are expected to have a high positive correlation with ProportionMethylated across the arrays measurement for the human species. The human EPIC array was applied to calibration data from mouse (n=15 EPIC arrays, 3 per methylation level) and rat (n=10, 2 per methylation level). The EPIC array data were normalized using the noob method (R function preprocessNoob in minfi).
2021-08-27 | GSE174568 | GEO
Project description:Calibration data mammalian array: Human, Mouse, Rat
| PRJNA730555 | ENA
Project description:Calibration array used to assess probe specific binding behaviour across eight different amounts of DNA starting material. This calibration step was performed to select one best out of three probes per gene based on probe responsiveness on increasing DNA staring material. It was further used to calibrate a subsequent microarray experiment to account for probe specific binding behaviour as part of the normalization process (see also Dennenmoser et al. 2017 Copy number increases of transposable elements and protein coding genes in an invasive fish of hybrid origin).
2017-07-01 | GSE93063 | GEO
Project description:An Infinium microarray platform (GPL28271, HorvathMammalMethylChip40) was used to generate DNA methylation data from synthetic DNA from 3 species. The DNA samples from each species were enzymatically manipulated so that they would exhibit 0%, 25%, 50%, 75% and 100% percent methylation at each CpG location, respectively. The variable “ProportionMethylated” (with ordinal values 0, 0.25, 0.5, 0.75, 1) can be interpreted as a benchmark for each CpG that maps to the respective genome. Thus, the DNA methylation levels of each CpG are expected to have a high positive correlation with ProportionMethylated across the arrays measurement from a given species. The mammalian array was applied to synthetic DNA data from 3 species: human (n=10 mammalian arrays, 2 per methylation level), mouse (n=20, 4 per methylation level), and rat (n=15, 3 per methylation level).
2021-08-27 | GSE174567 | GEO
Project description:Background: Epigenome-wide association studies (EWAS) have been widely applied to identify methylation CpG sites associated with human disease. To date, the Infinium Methylation EPIC array (EPIC) is commonly used for high-throughput DNA methylation profiling. However, the EPIC array covers only 30% of the human methylome. Methylation Capture bisulfite sequencing (MC-seq) captures target regions of methylome and has advantages of extensive coverage in the methylome at an affordable price. Methods: Epigenome-wide DNA methylation in four peripheral blood mononuclear cell samples was profiled by using SureSelectXT Methyl-Seq for MC-seq and EPIC platforms separately. CpG site-based reproducibility of MC-seq was assessed with DNA sample inputs ranging in quantity of high (> 1000ng), medium (300-1000ng), and low (150ng-300ng). To compare the performance of MC-seq and the EPIC arrays, we conducted a Pearson correlation and methylation value difference at each CpG site that was detected by both MC-seq and EPIC. We compared the percentage and counts in each CpG island and gene annotation between MC-seq and the EPIC array. Results: After quality control, an average of 3,708,550 CpG sites per sample was detected by MC-seq with DNA quantity >1000ng. Reproducibility of MC-seq detected CpG sites was high with strong correlation estimates for CpG methylation among samples with high, medium, and low DNA inputs (r > 0.96). The EPIC array captured an average of 846,464 CpG sites per sample. Compared with the EPIC array, MC-seq detected more CpGs in coding regions and CpG islands. Among the 472,540 CpG sites captured by both platforms, methylation of a majority of CpG sites was highly correlated in the same sample (r: 0.98~0.99). However, methylation for a small proportion of CpGs (N=235) differed significantly between the two platforms, with differences in beta values of greater than 0.5. Conclusions: Our results show that MC-seq is an efficient and reliable platform for methylome profiling with a broader coverage of the methylome than the array-based platform. Although methylation measurements in majority of CpGs are highly correlated, a number of CpG sites show large discrepancy between the two platforms, which warrants further investigation and needs cautious interpretation.
2020-06-11 | GSE152245 | GEO
Project description:Comparison of Methylation Capture Sequencing and Infinium EPIC Methylation Array in Peripheral Blood Mononuclear Cells [EPIC array]
| PRJNA638699 | ENA
Project description:DNA methylation analysis in oropharyngeal cancer [EPIC array]
| PRJNA512879 | ENA
Project description:EPIC Methylation array profiling of MCF-7 cells
| PRJNA727848 | ENA
Project description:Picky is an optimal microarray design software which designed the NSF Rice 45K Array. A series of microarray experiments using a one-chip version of this array were conducted to validate as well as to develop a calibration method for Picky designed microarrays. Synthesized samples with known content were used in the validation. PICKY designed microarrays were found to be highly reliable. The PICKY predicted closest nontarget information was used to quantitatively calibrate the best microarray hybridization conditions using the same microarrays and synthesized samples. Because this method works under most microarray protocols, it is generally applicable in any lab that uses PICKY as their microarray design tool. The associate publication provides more details about the experiment design and discussions about its results. Keywords: Microarray Calibration
2009-10-22 | GSE14717 | GEO