WriteCloseByAllRegions: Extract clusters of CpG probes located closely

In TransBioInfoLab/coMethDMR: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies

Extract clusters of CpG probes located closely

Description

Extract clusters of CpG probes located closely

Usage

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.

Details

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

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

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"
# )

TransBioInfoLab/coMethDMR documentation built on Sept. 14, 2022, 7:09 p.m.