EPIC PDX
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ABSTRACT:
PROVIDER: EGAD00010001872 | EGA |
REPOSITORIES: EGA
Similar Datasets
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:Infinium® HumanMethylation450 BeadChip and EPIC arrays were run with the aim of using the methylation profiles (n=986 in total) for sarcoma subtype classification (Paper: Lyskjær et al, 2021, DNA methylation-based profiling of bone and soft tissue tumours: a validation study of the ‘DKFZ sarcoma Classifier’ ). 500ng of DNA from fresh frozen (FT) or formalin-fixed paraffin-embedded (FFPE) tumour samples were bisulfite converted using the Zymo EZ DNA methylation Gold kit (Zymo Research Corp. Irvine, USA) before hybridisation to the Infinium HumanMethylation450 or EPIC beadchip arrays (Illumina, San Diego, CA) by UCL Genomics. All bisulfite-converted FFPE samples were restored with the Infinium FFPE DNA Restore kit (Illumina).
2021-05-01 | E-MTAB-9875 | biostudies-arrayexpress
Project description:DNA methylation alterations are a universal feature of cancer. In prostate cancer, site specific DNA methylation changes have been suggested as driver in disease initial and progression. Here we provide a comprehensive assessment of DNA methylation changes in prostate cancer patient derived xenograft (PDX) models. We delineate patterns of both site specific and global methylation changes and nominate novel candidates for biomarker development. Genome wide DNA methylation profiling of prostate cancer patient derived xenograft and cell line models using Infinium EPIC arrays
2023-12-31 | GSE227814 | GEO
Project description:DNA methylation alterations are a universal feature of cancer. In prostate cancer, site specific DNA methylation changes have been suggested as driver in disease initial and progression. Here we provide a comprehensive assessment of DNA methylation changes in prostate cancer patient derived xenograft (PDX) models. We delineate patterns of both site specific and global methylation changes and nominate novel candidates for biomarker development. Genome wide DNA methylation profiling of prostate cancer patient derived xenograft and cell line models using Infinium EPIC arrays
2023-12-31 | GSE227695 | 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:Epic methylation arrays of DNMT1 inhibitor treated AML cell lines
| PRJNA557724 | ENA
Project description:EPIC methylation array from liver DNA obtained from liver tissue preserved in paraffin, from individuals with or without HEPATOPULMONARY SYNDROME (HPS)
2020-12-26 | GSE162984 | GEO
Project description:DNA methylation is the most studied epigenetic modification due to its role in regulating gene expression and aberrations in methylation involved in the pathogenesis of cancer and several diseases. The method of choice to evaluate genome-wide methylation has been the Illumina HumanMethylation450 BeadChip (450K), but it was recently replaced with the MethylationEPIC BeadChip (EPIC). We therefore sought to validate the EPIC array in comparison to the 450K array for both fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) pediatric brain tumors. We also performed analysis on the EPIC array with paired FF and FFPE samples, to adapt to a clinical setting where FFPE is routinely used. Further, we compared two restoration methods, REPLI-g and Infinium, for FFPE-derived DNA on the EPIC array.
2017-04-01 | GSE92579 | 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.
2020-06-22 | GSE152922 | GEO