Get Region Totals at Different Cutoffs

getRegionTotals() calculates the total number of regions, as well as the total width and number of CpGs remaining in a region set after filtering at different covMin and methSD cutoffs and then saves it as a tab-delimited text file.

Usage

getRegionTotals(
  regions,
  covMin = seq(0, 20, 2),
  methSD = seq(0, 0.1, 0.01),
  save = TRUE,
  file = "Region_Totals.txt",
  verbose = TRUE
)

Arguments

regions

A data.frame output from getRegions() giving the set of regions and statistics for each region.

covMin

A numeric specifying the minimum number of reads at CpGs in a region in any sample for that region to be included in the total.

methSD

A numeric specifying the minimum methylation standard deviation for that region to be included in the total.

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 giving the total number of regions, width, and number of CpGs at all combinations of covMin and methSD.

Details

The purpose of this function is to help balance cutoffs for minimum coverage and methylation standard deviation and identify a robust set of variably methylated regions. It's recommended to input multiple covMin and methSD cutoffs for comparison. Computational resources are also a consideration for network construction, with region sets of 250K or less generally performing well.

See also

• getRegions() to generate the set of regions.

• plotRegionStats(), plotSDstats(), and plotRegionTotals() for more help visualizing region characteristics and setting cutoffs for filtering.

• filterRegions() for filtering regions by minimum coverage and methylation standard deviation.

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")
}