coverage.GC: Bait coverage versus GC content plot
In hummelma/TEQC: Quality control for target capture experiments

Description Usage Arguments Details Value Author(s) References See Also Examples

Calculates and plots average normalized coverage per hybridization probe versus GC content of the respective probe. A smoothing spline is added to the scatter plot.

1	coverage.GC(coverageAll, baits, returnBaitValues = FALSE, linecol = "darkred", lwd, xlab, ylab, pch, col, cex, ...)

`coverageAll`	`RleList` containing `Rle` vectors of per-base coverages for each chromosome, i.e. `coverageAll` output of `coverage.target`
`baits`	A `RangedData` table holding the hybridization probe ("bait") positions and sequences, i.e. output of`get.baits`
`returnBaitValues`	if `TRUE`, average coverage, average normalized coverage and GC content per bait are returned
`linecol, lwd`	color and width of spline curve
`xlab, ylab`	x- and y-axis labels
`pch`	plotting character
`col, cex`	color and size of plotting character
`...`	further graphical parameters passed to `plot`

The function calculates average normalized coverages for each bait: the average coverage over all bases within a bait is divided by the average coverage over all bait-covered bases. Normalized coverages are not dependent on the absolute quantity of reads and are hence better comparable between different samples or even different experiments.

A scatterplot with normalized per-bait coverages on the y-axis and GC content of respective baits on the x-axis. A smoothing spline is added to the plot.

If returnBaitValues = TRUE average coverage, average normalized coverage and GC content per bait are returned as 'values' columns of the baits input RangedData table

Manuela Hummel m.hummel@dkfz.de

Tewhey R, Nakano M, Wang X, Pabon-Pena C, Novak B, Giuffre A, Lin E, Happe S, Roberts DN, LeProust EM, Topol EJ, Harismendy O, Frazer KA. Enrichment of sequencing targets from the human genome by solution hybridization. Genome Biol. 2009; 10(10): R116.

coverage.target, covered.k, coverage.hist, coverage.plot, coverage.uniformity, coverage.targetlength.plot

## get reads and targets
exptPath <- system.file("extdata", package="TEQC")
readsfile <- file.path(exptPath, "ExampleSet_Reads.bed")
reads <- get.reads(readsfile, idcol=4, skip=0)
targetsfile <- file.path(exptPath, "ExampleSet_Targets.bed")
targets <- get.targets(targetsfile, skip=0)

## calculate per-base coverages
Coverage <- coverage.target(reads, targets, perBase=TRUE)

## get bait positions and sequences
baitsfile <- file.path(exptPath, "ExampleSet_Baits.txt")
baits <- get.baits(baitsfile, chrcol=3, startcol=4, endcol=5, seqcol=2)

## do coverage vs GC plot
coverage.GC(Coverage$coverageAll, baits)