Generation of methylation profiles of cell line genomic DNA isolated using ethanol precipitation was performed at the Erasmus MC Department of Pathology molecular diagnostics lab according to the Illumina protocols (EPIC). Copy number alterations were resolved using the Conumee package (Hovestadt V, Zapatka M. conumee: Enhanced copy-number variation analysis using Illumina DNA methylation arrays. R package version 1.6.0. https://www.bioconductororg/packages/conumee/ . 2015). Differential methylation was identified using the RnBeads package (https://rnbeads.org ) using “SWAN” for normalization [28 (link)].
Dna methylation arrays
Manufactured by Illumina
DNA methylation arrays are a type of lab equipment used to measure DNA methylation patterns across the genome. They provide a comprehensive analysis of DNA methylation levels at specific genomic locations. The core function of these arrays is to enable researchers to interrogate the epigenetic landscape of cells and tissues.
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Lab products found in correlation
4 protocols using dna methylation arrays
1
Methylation Profiling and Copy Number Analysis
2
Copy Number Variation Analysis
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Analyses were performed as previously described.13 (link),14 (link) In brief, copy number analyses were performed using the conumee package (Hovestadt V, Zapatka M. conumee: Enhanced copy number variation analysis using Illumina DNA methylation arrays. R package version 1.9.0).15 Data were generated for bins with at least 25 probes. Other settings were default. The reference set was composed of 64 normal male samples from an in-house set (n = 14) and from the German Cancer Research Center (n = 50, DKFZ, Heidelberg, obtained from Dr Martin Sill).
3
Comprehensive Methylome Profiling of Blood and Tissues
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Normalized DNA methylation beta values for 450 K sites included in Illumina DNA methylation arrays for a total of 11,636 samples from healthy blood, normal tissues, cancer tissues and noncancer-associated tissues NAT were downloaded from TCGA and GEO sites as listed in Table 1 .
We first generated a list of 47981 CpG positions that were hypomethylated in 17 different somatic tissues (beta = <0.1 and median <0.02) using Illumina 450 K array data in GSE50192. We then generated a list of 68260 unmethylated CpG positions in blood DNA in each of the 312 individuals in GSE61496. To increase the robustness of the list and to exclude sites with residual variation in methylation across individuals that are derived from sex or age differences, we overlapped this list with a list of 55959 of unmethylated CpGs in blood DNA in all 656 individuals, males and females aged from 19 to 101 years (GSE40279). We got the list of 41622 CpGs of unmethylated CpGs in blood DNA from both dataset GSE61496 and GSE40279 in all 968 individuals.
We then overlapped the two lists (unmethylated in blood and in tissue) to obtain a list of 28,775 CpGs that are unmethylated in every single individual in both blood datasets and 17 somatic tissues.
We first generated a list of 47981 CpG positions that were hypomethylated in 17 different somatic tissues (beta = <0.1 and median <0.02) using Illumina 450 K array data in GSE50192. We then generated a list of 68260 unmethylated CpG positions in blood DNA in each of the 312 individuals in GSE61496. To increase the robustness of the list and to exclude sites with residual variation in methylation across individuals that are derived from sex or age differences, we overlapped this list with a list of 55959 of unmethylated CpGs in blood DNA in all 656 individuals, males and females aged from 19 to 101 years (GSE40279). We got the list of 41622 CpGs of unmethylated CpGs in blood DNA from both dataset GSE61496 and GSE40279 in all 968 individuals.
We then overlapped the two lists (unmethylated in blood and in tissue) to obtain a list of 28,775 CpGs that are unmethylated in every single individual in both blood datasets and 17 somatic tissues.
4
DNA Methylation Profiling of Tissues
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Normalized DNA methylation beta values for 450K sites included in Illumina DNA methylation arrays for a total of 11,636 samples from healthy blood, normal tissues, cancer tissues and noncancer associated tissues NAT were downloaded from TGCA and GEO sites as listed in table 1. DNA methylation differences at speci c CG positions between the groups were computed using t statistics adjusted by Bonferroni corrections for 450K multiple tests.
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