Plot Histograms of Region Statistics

plotRegionStats() takes a set of regions from getRegions(), generates histograms of region characteristics, and saves it as a pdf. Region-level statistics include width, number of CpGs, minimum coverage, mean coverage, mean methylation, and methylation standard deviation.

Usage

plotRegionStats(
  regions,
  maxQuantile = 1,
  bins = 30,
  histCol = "#132B43",
  lineCol = "red",
  nBreaks = 4,
  save = TRUE,
  file = "Region_Plots.pdf",
  width = 11,
  height = 8.5,
  verbose = TRUE
)

Arguments

regions

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

maxQuantile

A numeric(1) giving the maximum quantile of each feature to plot.

bins

A numeric(1) specifying the number of bins in each histogram.

histCol

A character(1) giving the color of the histogram.

lineCol

A character(1) giving the color of the vertical median line.

nBreaks

A numeric(1) specifying the number of breaks for the x-axis.

save

A logical(1) indicating whether to save the plot.

file

A character(1) giving the file name (.pdf) for the plot.

width

A numeric(1) specifying the width in inches of the saved plot.

height

A numeric(1) specifying the height in inches of the saved plot.

verbose

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

Value

A ggplot object.

Details

It's recommended to examine region characteristics before and after filtering. The vertical line on each histogram indicates the median value for that feature. A ggplot object is produced and can be edited outside of this function if desired.

See also

• getRegions() to generate the set of regions.

• plotSDstats(), getRegionTotals(), 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")
}