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RnBeads

Methylome Resource: Comprehensive RnBeads analyses of large-scale reference epigenome datasets

The Methylome Resource was established by applying RnBeads to some of the largest public datasets that are currently available for whole genome bisulfite sequencing (WGBS), for reduced representation bisulfite sequencing (RRBS) and for the Illumina Infinium HumanMethylation450 assay. This resource provides a reference for large-scale DNA methylation analyses that can be used in complementary ways:

Resource Data Source Preprocessed Data Archive Sample Annotation Files RnBeads Configuration
Genome-scale RRBS data for
216 tissues and cell lines
Encode Project Website data.zip (3 GB) samples.csv (all samples) analysis.xml
samples.csv (17 untreated samples)
Genome-wide WGBS data for
41 tissues and cell lines
Gene Expression Omnibus data.zip (11 GB) samples.csv (all 41 samples) analysis.xml
samples.csv (10 adult primary tissues)
Infinium 450k data for
4034 cancer and normal samples
TCGA data portal data.zip (35 GB) samples.csv (all samples) analysis.xml
samples.csv (40 samples from 10 primary tumors)

Resource 1: Genome-scale RRBS data for 216 tissues and cell lines

In the context of the ENCODE project, Varley et al. established genome-scale DNA methylation maps for various tissue sample and cell lines using reduced representation bisulfite sequencing (RRBS). This RnBeads analysis of 216 samples shows that cells from different germ layers are clearly distinguished by their DNA methylation profiles, and it identifies characteristic loci that can be used for classifying samples according to their tissue type. Including parts or all of this dataset in custom RnBeads analyses provides a useful reference for quality control, analysis and interpretation of user-generated DNA methylation datasets.


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Resource 2: Genome-wide WGBS data for 41 tissues and cell lines

Ziller et al. recently compiled whole genome bisulfite sequencing (WGBS) data for 41 tissues and cell lines comprising data from the Roadmap Epigenomics Project and other sources. The RnBeads analysis identified clear grouping of samples according to tissue types. Furthermore, sample type is strongly correlated with the laboratory performing the experiment. Outliers in terms of experimental quality as well as long term cell culturing are identified. This analysis illustrates how this methylome resource can be used for identifying both technical and biological outliers in large-scale DNA methylation datasets.


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Resource 3: Infinium 450k data for 4034 cancer samples

In the context of The Cancer Genome Atlas (TCGA) researchers have generated a large collection of cancer methylomes using the Infinium 450k assay. While an integrative analysis of the full dataset has not been published yet, Weisenberger recently summarized and reviewed the activities that led to creating this dataset. This RnBeads analysis of 4034 blood, breast, intestinal and brain cancer samples provides an extensive and interactively browsable analysis of this dataset, which can be used as a starting point for more targeted investigation and hypothesis testing, but also as a reference for interpreting DNA methylation aberrations observed in other cancer cohorts.


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Resource 4: Analysis of BLUEPRINT methylomes (WGBS)

In the context of the BLUEPRINT project, whole genome bisulfite sequencing data have been generated for 81 blood related samples. Among others primary monocyte and neutrophil cell samples from healthy donors were profiled. The RnBeads analysis shows similar methylomes between these two closely related cell types, but also significant DNA methylation differences enriched for important biological processes of the immune system.


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Resource 5: DNA methylation reprogramming in memory formation of human T cells (WGBS, NOMe-seq)

In the context of the DEEP project, whole genome bisulfite sequencing and NOMe-seq data have been generated for multiple stages during the process of memory formation in human CD4+ T cells (Durek et al., 2016). The data was anlyzed in RnBeads. The results show a progressive loss of DNA methylation during memory formation, particularly in putative regulatory regions of the genome. Two technologies (WGBS and NOMe-seq) were employed to assess CpG methylation levels. Overall, the agreement between both methods is high.


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The Methylome Resource will be extended further based on large-scale methylome maps that are currently being generated as part of the International Human Epigenome Consortium's (IHEC) efforts to establish comprehensive reference epigenomes for more than 1,000 human cell types.