Legacy Function to plot variant metrics — plot_variant

This function works with CW_mgatk.read and Vfilter_v3 This allows you to plot the mito mutation metrics This legacy function is useful to look at all threadhold simultaneous For each category(stringency), p1: Variant allele frequency(VAF); p2: Heteroplasmy histogram p3: CellN(Number of caells that carry the variants) VS maxcts( The number of variant counts in the highest cell) p4: Histogram to show the distribution of the number of variant per cell

Usage

plot_variant_legacy(
  GTSummary,
  feature.list,
  depth,
  cat = c("Total", "VerySensitive", "Sensitive", "Specific"),
  p4xlim = 50,
  QualifyCellCut = 10
)

Arguments

GTSummary: GTSummary from CW_mgatk.read
feature.list: feature.list from Vfilter_v3
cat: The catogories, it can be cat = c("Total", "VerySensitive", "Sensitive", "Specific") or a subset
p4xlim: the p4 xlim(number of variant per cell), default is 50
QualifyCellCut: median coverage for qualified cells, default is 10

Value

no returns, directly plot

Examples

if (FALSE) {
plot_variant_legacy(DN1CD34_1.VariantsGTSummary, DN1CD34_1.Variants.feature.lst,
  depth = DN1CD34_1.depth, cat = c("Total", "VerySensitive", "Sensitive", "Specific"),
  p4xlim = 30)
}