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Generate Regions from CpGs

Source: R/Get_and_Filter_Regions.R
getRegions.Rd

getRegions() generates a set of regions and some statistics based on the CpGs in a BSseq object and then saves it as a tab-delimited text file. Regions can be defined based on CpG locations (for CpG clusters), built-in genomic annotations from annotatr, or a custom genomic annotation.

Usage

getRegions(
  bs,
  annotation = NULL,
  genome = c("hg38", "hg19", "mm10", "mm9", "rn6", "rn5", "rn4", "dm6", "dm3",
    "galGal5"),
  upstream = 5000,
  downstream = 1000,
  custom = NULL,
  maxGap = 150,
  n = 3,
  save = TRUE,
  file = "Unfiltered_Regions.txt",
  verbose = TRUE
)

Arguments

bs

A BSseq object.

annotation

A character(1) giving the built-in genomic annotation to use for defining regions. Shortcuts are available for genes, promoters, and transcripts. Get the entire list of possible annotations with annotatr::builtin_annotations(), which also includes CpG islands, enhancers, and chromatin states.

genome

A character(1) with the genome build to use for built-in annotations. Available builds include hg38, hg19, mm10, mm9, rn6, rn5, rn4, dm6, dm3, and galGal5.

upstream

A numeric(1) giving the number of bases upstream of a transcription start site to specify a promoter. Used for the promoters built-in annotation.

downstream

A numeric(1) giving the number of bases downstream of a transcription start site to specify a promoter. Used for the promoters built-in annotation.

custom

A GRanges object with a custom genomic annotation for defining regions. Construct this using GenomicRanges::GRanges().

maxGap

A numeric(1) specifying the maximum number of bases between CpGs to be included in the same CpG cluster.

n

A numeric(1) giving the minimum number of CpGs for a region to be returned. This applies to CpG clusters, built-in, and custom, annotations.

save

A logical(1) indicating whether to save the data.frame.

file

A character(1) giving the file name (.txt) for the saved data.frame.

verbose

A logical(1) indicating whether messages should be printed.

Value

A data.frame with the region genomic locations along with some statistics, including number of CpGs, coverage minimum, mean, and standard deviation, and methylation mean and standard deviation.

Details

These regions still need to be filtered for minimum coverage and methylation standard deviation.

See also

Examples

if (FALSE) {

# Call Regions
regions <- getRegions(bs, file = "Unfiltered_Regions.txt")
plotRegionStats(regions, maxQuantile = 0.99,
                file = "Unfiltered_Region_Plots.pdf")
plotSDstats(regions, maxQuantile = 0.99,
            file = "Unfiltered_SD_Plots.pdf")

# Examine Region Totals at Different Cutoffs
regionTotals <- getRegionTotals(regions, file = "Region_Totals.txt")
plotRegionTotals(regionTotals, file = "Region_Totals.pdf")

# Filter Regions
regions <- filterRegions(regions, covMin = 10, methSD = 0.05,
                         file = "Filtered_Regions.txt")
plotRegionStats(regions, maxQuantile = 0.99,
                file = "Filtered_Region_Plots.pdf")
plotSDstats(regions, maxQuantile = 0.99,
            file = "Filtered_SD_Plots.pdf")
}