qualPlot-methods {qrqc} | R Documentation |
basePlot
plots quality statistics by position. Optionally, it
adds a smoothed curve through the qualities, which is fit with data
randomly drawn from the distribution of qualities at each position.
The grey lines indicate the range of the 10% and 90% quantiles, the orange lines indicate the range of the 25% and 75% quartiles, the blue point is the mean. Optionally, one can plot the median as well.
qualPlot(x, smooth=TRUE, extreme.color="grey", quartile.color="orange", mean.color="blue", median.color=NULL)
x |
an S4 object of class |
smooth |
a logical value indicating whether to add a smooth curve. |
extreme.color |
a character value indicating the color to use for
the extreme values (the 10% and 90% quantiles). If |
quartile.color |
a character value indicating the color to use
for the quartiles. If |
mean.color |
a character value indicating the color to use for
the mean. If |
median.color |
a character value indicating the color to use for
the median. If |
signature(x = "FASTQSummary")
qualPlot
will plot the qualities for a single object of class FASTQSummary
.
signature(x = "list")
qualPlot
will plot the qualities for each of the
FASTQSummary
items in the list and display them in a series of
panels.
Vince Buffalo <vsbuffalo@ucdavis.edu>
## Load a FASTQ file s.fastq <- readSeqFile(system.file('extdata', 'test.fastq', package='qrqc')) ## Plot qualities qualPlot(s.fastq) ## Combine with ggplot2 to produce custom graphics p <- qualPlot(s.fastq, smooth=FALSE) p <- p + geom_smooth(aes(x=position, y=quality), data=getMCQual(s.fastq), method="lm", color="green", se=FALSE) p <- p + theme_bw() p ## Plot multiple quality plots s.trimmed.fastq <- readSeqFile(system.file('extdata', 'test-trimmed.fastq', package='qrqc')) qualPlot(list("not trimmed"=s.fastq, "trimmed"=s.trimmed.fastq))