Dataset of methylation data from whole blood DNA
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00010001593 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:DNA methylation analysis was perfomed using Infinium EPIC Methylation BeadChip platform on 65 PFA ependymoma patient samples. Resulting .idat files were then uploaded to the molecularneuropathology.org classifier to obtain molecular subgroup and copy number variance. Idat files were batch normalized and background corrected using default settings of the R package ChAMP to obtain GpG methylation beta values for analysis of differentially methylated GpG regions.
2023-06-01 | GSE226895 | GEO
Project description:DNA methylation analysis was perfomed using Infinium 450K Methylation BeadChip platform on 140 PFA ependymoma patient samples. Resulting .idat files were then uploaded to the molecularneuropathology.org classifier to obtain molecular subgroup and copy number variance. Idat files were batch normalized and background corrected using default settings of the R package ChAMP to obtain GpG methylation beta values for analysis of differentially methylated GpG regions.
2023-06-01 | GSE226960 | GEO
Project description:In summary, our study demonstrated the methylation sites of SFRP1 gene promoter in patients with colorectal cancer and adenoma and found SFRP1_16_17_18 CpG site was good performance as a diagnostic marker of colorectal cancer.
| 2401959 | ecrin-mdr-crc
Project description:Background: As 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 characterised. 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 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. Results: The standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities. Betas calculated from raw signal intensities (the default GenomeStudio behaviour) 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. Conclusions: Careful selection of preprocessing steps can minimise 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 an R software package called wateRmelon, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilise the same normalization methods and data quality tests on 450K data.
2013-01-24 | GSE43414 | GEO
Project description:To identify target genes of C/EBPepsilon in differentiated granulocytes, total RNA were purified from sorted Gr-1intermediate/Mac-1+ and Gr-1hi/Mac-1+ cells of C/EBPepsilon knock out and C57BL/6 wild type mice using RNeasy Mini Kit (Qiagen). The differences of their expression pattern were compared with Illumina Mouse WG-6v2 Expression Chip platform. Raw Illumina BeadArray data in IDAT format were preprocessed using the open-source Bioconductor package illuminaio with the Illumina array design formation BGX file downloaded from NCBI, GEO accession: GPL6887. Following the preprocessing, the expression data were normalized by applying control background correction, log transformation and inter-quantile normalization using the neqc function from the limma bioconductor package. This allowed us to compare the transcriptomic consequences of C/EBPepsilon in two independent populations.
2017-06-02 | GSE73835 | GEO
Project description:Epigenomics is developing a colon cancer screening assay based on differential methylation of specific CpG sites for the detection of early stage disease. A genome-wide methylation analysis and oligonucleotide array study using DNA from various stages of colon cancer and normal tissue have been completed to obtain candidate CpG markers. Based on results obtained in the above studies, Epigenomics has moved to the final stages of feasibility with a specific, highly sensitive real-time marker assay that is able to detect colon cancer DNA in blood plasma.
| 2056787 | ecrin-mdr-crc
Project description:In view of the roles played by miRNAs in cancer progression, we performed a microarray analysis aimed at identifying miR-135b target genes in breast cancer cells. Detection of transcripts affected by silencing of mir-135b was done using a time course at 24, 48 and 72 h both transfecting cell with mir-135b specific miRIDIAN microRNA Hairpin Inhibitor or miRIDIAN microRNA Hairpin Inhibitor negative control. Each experimental condition was repeated three times and analysed on on MOUSEREF-8 V2 Illumina bead chips. Genome studio was used to generate raw intensity signal without normalization. Data log2 transformation and loess normalization was performed with oneChannelGUI. Data were filtered using an IQR filter (i.e. only genes characterized by an IQR > 0.25, were retained for further analysis). Detection of differentially expressed transcripts was also performed with oneChannelGUI, using masigpro package with default parameters. Data were visualized by hierarchical clustering, as log2 ratio between anti-miR135b and the negative control using TMEV software. The subset of transcripts characterized by an increase in expression as consequence of a reduction of expression of miR135b were selected. MicroRNA target data for mir135b were retrieved from miranda database (microRNAsmiranda.mouse_predictions_S_C_aug2010.txt, http://www.microrna.org/microrna/home.do). Miranda data and transcripts increasing their expression upon silencing of miR135b were intersected to find the genes in common.
2013-12-01 | GSE28949 | GEO
Project description:Background: As 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 characterised. 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 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. Results: The 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. Betas calculated from raw signal intensities (the default GenomeStudio behaviour) 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. Conclusions: Careful selection of preprocessing steps can minimise 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 an R software package called wateRmelon, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilise the same normalization methods and data quality tests on 450K data. Bisulfite converted DNA from the 11 cohorts (N=695, including 36 technical replicates) were hybridised to the Illumina Infinium 450k Human Methylation Beadchip v1.2
2013-01-24 | E-GEOD-43414 | biostudies-arrayexpress
Project description:DNA methylation profiling of cancer and control samples. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across 1,505 CpG sites CpGs distributed across 807 genes in blood DNA specimens. DNA samples were extracted from blood specimens, bisulfite treated and subsequently used for GoldenGate Methylation Cancer Panel I Array (Illumina) according to manufacturer’s protocol together with normalization methylated, hemimethylated and unmethylated DNA controls (Qiagen).
2012-11-01 | E-GEOD-33614 | biostudies-arrayexpress
Project description:To determine whether differences between background strains or housing conditions altered the hepatic methylome, We report the generation and analysis of genome-wide DNA methylation profiles at nucleotide resolution in mouse liver from two male mice on a mixed background (mixed-1, mixed-2) and two males on a pure Black-6 (B6-1, B62) background. Using Enhanced high-throughput Reduced Representation Bisulfite Sequencing (ERRBS), we enriched CpG islands in mouse liver, and covered a representative sampling of conserved non-coding elements, transposons and other genomic features, for mouse liver. We found that the total CpG methylation of each methylome was strikingly similar among the 4 mouse liver samples from two different genetic backgrounds. Analysis of all CpG sites with at least 10x coverage showed a bimodal distribution of methylation, with all samples having 25% of hypermethylated CpG sites and 60% as hypomethylated CpG sites. Given the high percent of genome coverage and robust depth at single nucleotide level, these datasets provide a resource for investigation into changes in DNA methylation patterns in liver disease, tumorigenesis and regeneration. Ehanced reduced representation bisulfite sequencing (MspI 70~320bp size fraction) of liver tissue
2016-06-13 | E-GEOD-80761 | biostudies-arrayexpress