Extract clusters of CpG probes located closely

WriteCloseByAllRegions(
  fileName,
  regions,
  genome = c("hg19", "hg38"),
  arrayType = c("450k", "EPIC"),
  ignoreStrand = TRUE,
  maxGap = 200,
  minCpGs = 3,
  ...
)

Arguments

fileName: Name of the RDS file where the output genomic regions will be saved.
regions: GRanges of input genomic regions
genome: Human genome of reference: hg19 or hg38
arrayType: Type of array: "450k" or "EPIC"
ignoreStrand: Whether strand can be ignored, default is TRUE
maxGap: an integer, genomic locations within maxGap from each other are placed into the same cluster
minCpGs: an integer, minimum number of CpGs for each resulting region
...: Dots for internal arguments. Currently unused.

Value

Nothing. Instead, file with the genomic regions containing CpGs located closely within each inputting pre-defined genomic region will be written to the disk

Details

For maxGap = 200 and minCpGs = 3, we have already calculated the clusters of CpGs. They are saved in folder /inst/extdata/.

Examples


regions <- GenomicRanges::GRanges(
  seqnames = c("chr4", "chr6", "chr16", "chr16", "chr22", "chr19"),
  ranges = c(
    "174202697-174203520", "28226203-28227482", "89572934-89574634",
    "67232460-67234167", "38244199-38245362", "39402823-39403373"
  )
)

# Uncomment out the example code below:
# WriteCloseByAllRegions(
#   regions = regions,
#   arrayType = "EPIC",
#   maxGap = 50,
#   minCpGs = 3,
#   fileName = "closeByRegions.rds"
# )