Repitools (version 1.18.0)

GCbiasPlots: Plot GC content vs. Read Counts Before Normalising, and GC content vs. Copy Estimates After Normalising.

Description

Two plots on the same plotting page are made for each sample. The top plot has estimates of copy number separated by GC content before any GC correction was applied. The bottom plot shows the copy number estimates after GC correction was applied.

Usage

"GCbiasPlots"(copy, y.max = NULL, pch = 19, cex = 0.2, pch.col = "black", line.col = "red", lty = 1, lwd = 2, verbose = TRUE)

Arguments

copy

A CopyEstimate object.

y.max

The maximum value of the y-axis of the scatter plots.

pch

Style of points in the scatter plots.

cex

Size of the points in the scatter plots.

pch.col

Colour of points in the scatter plots.

line.col

Colour of regression line in each scatter plot.

lty

Line type of plotted regression line.

lwd

Line width of plotted regression line.

verbose

Whether to print the progess of processing.

Value

A number of pages of scatterplots equal to the number of samples described by copy. The output should, therefore, be sent to a PDF device.

Details

See absoluteCN or relativeCN for how to do the GC adjusted copy number estimates. The line plotted through the scatterplots is a lowess line fit to the data points.

Examples

  ## Not run: 
#     library(BSgenome.Hsapiens.UCSC.hg18)
#     library(BSgenome.Hsapiens36bp.UCSC.hg18mappability)
#     load("inputsReads.RData")
#     windows <- genomeBlocks(Hsapiens, chrs = paste("chr", c(1:22, 'X', 'Y'), sep = ''),
#                             width = 20000)
#     counts <- annotationBlocksCounts(inputsReads, anno = windows, seq.len = 300)
# 
#     gc.par <- GCAdjustParams(genome = Hsapiens, mappability = Hsapiens36bp,
#                              min.mappability = 50, n.bins = 10, min.bin.size = 10,
#                              poly.degree = 4, ploidy = c(2, 4))
#     abs.cn <- absoluteCN(input.windows = windows, input.counts = counts, gc.params = gc.par)
# 
#     pdf("bias.pdf")
#     GCbiasPlots(abs.cn, y.max = 8)
#     dev.off()
#   ## End(Not run)