plotWin: Plot the Proportion of + Stranded Reads
In strandCheckR: Calculate strandness information of a bam file

Description Usage Arguments Details Value See Also Examples

Plot the number of reads vs the proportion of '+' stranded reads.

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plotWin(windows, split = c(10, 100, 1000), threshold = c(0.6, 0.7, 0.8,
0.9), save = FALSE, file = "win.pdf", group_by = NULL,
useCoverage = FALSE, ...)

`windows`	data frame containing the strand information of the sliding windows. Windows should be obtained using the function `getWinFromBamFile` to ensure the correct data structure.
`split`	an integer vector that specifies how you want to partition the windows based on coverage. By default `split` = c(10,100,1000), partition windows into 4 groups based on these values.
`threshold`	a `numeric` vector between 0.5 & 1 that specifies which threshold lines to draw on the plot. The positive windows above the threshold line (or negative windows below the threshold line) will be kept when using `filterDNA`.
`save`	if TRUE, then the plot will be save into the file given by `file` parameter
`file`	the file name to save to plot
`group_by`	colnames of `windows` which will be used to split the plot
`useCoverage`	if TRUE then plot the coverage strand information, otherwise plot the number of reads strand information. FALSE by default
`...`	used to pass parameters to facet_wrap during plotting

This function will plot the proportion of '+' stranded reads for each window, against the number of reads in each window. The threshold lines indicate the hypothetical boundary where windows will contain reads to kept or discarded using the filtering methods of filterDNA. Any plot can be easily modified using standard ggplot2 syntax (see Examples)

The plot will be returned as a standard ggplot2 object

getWinFromBamFile, plotHist

bamfilein = system.file('extdata','s2.sorted.bam',package = 'strandCheckR')
windows <- getWinFromBamFile(file = bamfilein,sequences = '10')
plotWin(windows)

# Change point colour using ggplot2
library(ggplot2)
plotWin(windows) + 
scale_colour_manual(values = rgb(seq(0, 1, length.out = 4), 0, 0))