Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation

This dataset contains supplemental tables and tracks for the study entitled: "Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation".

• Files
  • PMDs_CGIs.zip
    • The included files contain
    • Genome positions of detected PMDs with their mean methylation (weighted mean, see Methods)
    • Genome positions of CpG islands with their mean methylation (weighted mean)
    • The "Brinkman" directory contains files from breast cancer data produced in this study
    • The "normals" directory contains files from normal tissues (external data) analyzed in this study
    • The "tumors" directory contains files from tumors (external data) analyzed in this study
    • All genome positions are based on GRCh37/hg19 
    • All files are TAB-delimited text files (.tsv)
  • DNAme_bigwigs.zip
    • The included files are BIGWIG files (http://genome.ucsc.edu/goldenPath/help/bigWig.html) for viewing the DNA methylation profiles in a genome browser such as UCSC (http://genome.ucsc.edu). Each file represents a whole-Genome Bisulfite Sequencing (WGBS) DNA methylation profile from one tumor used in this study. The used genome build was GRCh37/hg19. For every CpG with a coverage of at least 4 reads, the DNA methylation value (range: 0-1) is included.
• Methods
  • Detection of partially methylated domains (PMDs) in all whole-genome bisulfite sequencing (WGBS) methylation profiles throughout this study was done using the MethylSeekR package for R (1). Before PMD calling, CpGs overlapping common SNPs (dbSNP build 137) were removed. The alpha distribution (1) was used to determine whether PMDs were present at all, along with visual inspection of WGBS profiles. After PMD calling, the resulting PMDs were further filtered by removing regions overlapping with centromers (undetermined sequence content).
  • Mean methylation values from WGBS inside CGIs were calculated using the ‘weighted methylation level’ (2).
  • Mean methylation values from WGBS inside PMDs were calculated using the ‘weighted methylation level’ (2). Calculation of mean methylation within PMDs involved removing all CpGs overlapping with CpG island(-shores) and promoters, as the high CpG densities within these elements yield unbalanced mean methylation values, not representative of PMD methylation. 
• References
  • (1) Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. Identification of active regulatory regions from DNA methylation data. Nucleic Acids Research 41, (2013).
  • (2) Schultz, M. D., Schmitz, R. J. & Ecker, J. R. ’Leveling’ the playing field for analyses of single-base resolution DNA methylomes. Trends in Genetics 28, 583–585 (2012).