an object of class DNAcopy resulting from analyzing
data from copy number array experiments.
plot.type
the type of plot.
xmaploc
logical flag to indicate that the X axis is the maploc
position rather than the index. Since the segments are rearranged
the plateau plot does not use maploc position.
altcol
logical flag to indicate if chromosomes should be
plotted in alternating colors in the whole genome plot.
sbyc.layout
layout settings for the multifigure grid layout
for the ‘samplebychrom’ type. It should be specified as a vector of
two integers which are the number of rows and columns. The default
values are chosen based on the number of chromosomes to produce a
near square graph. For normal genome it is 4x6 (24 chromosomes)
plotted by rows.
cbys.layout
layout settings for the multifigure grid layout
for the ‘chrombysample’ type. As above it should be specified as
number of rows and columns and the default chosen based on the
number of samples.
cbys.nchrom
the number of chromosomes per page in the layout.
The default is 1.
include.means
logical flag to indicate whether segment means
are to be drawn.
zeroline
logical flag to indicate whether a horizontal line at
y=0 is to be drawn.
pt.pch
the plotting character used for plotting the log-ratio
values (default is ".").
pt.cex
the size of plotting character used for the log-ratio
values (default is 3).
pt.cols
the color list for the points. The colors alternate
between chromosomes. If missing the point colors are black and green.
segcol
the color of the lines indicating the segment means. If
missing the line color is set to be red.
zlcol
the color of the zeroline. If missing it is set to be grey.
ylim
this argument is present to override the default limits
which is the range of symmetrized log-ratios.
lwd
line weight of lines for segment mean and zeroline. If
missing it is set to 3.
...
other arguments which will be passed to plot
commands.
Details
There are four possible plot types. For the type ‘whole’ the data
are plotted for the entire genome. For the ‘samplebychrom’ type a
graph with each chromosome (of a given sample) is drawn in a separate
figure on a multi-figure grid. For the ‘plateau’ type the graph
is drawn with the chromosome segments re-ordered by the segment means.
For the ‘chrombysample’ type the samples for a given chromosome are
drawn in a 4x6 multi-figure grid in multiples of 24. By default the
segments means are drawn. For multisample data each sample or
chromosome is drawn on a separate sheet. When invoked interactively
the user is prompted before advancing to the next sample.
Examples
#Read in two examples from Snijders et al.
data(coriell)
#Combine into one CNA object to prepare for analysis on Chromosomes 1-23
CNA.object <- CNA(cbind(coriell$Coriell.05296,coriell$Coriell.13330),
coriell$Chromosome,coriell$Position,
data.type="logratio",sampleid=c("c05296","c13330"))
#We generally recommend smoothing single point outliers before analysis
#Make sure to check that the smoothing is proper
smoothed.CNA.object <- smooth.CNA(CNA.object)
#Segmentation at default parameters
segment.smoothed.CNA.object <- segment(smoothed.CNA.object, verbose=1)
#Plot whole studies
plot(segment.smoothed.CNA.object, plot.type="w")
#Plot each study by chromosome
plot(segment.smoothed.CNA.object, plot.type="s")
#Plot each chromosome across studies (6 per page)
plot(segment.smoothed.CNA.object, plot.type="c", cbys.layout=c(2,1), cbys.nchrom=6)
#Plot by plateaus
plot(segment.smoothed.CNA.object, plot.type="p")
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(DNAcopy)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/DNAcopy/plot.DNAcopy.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.DNAcopy
> ### Title: Plot the data and results from segment of a CNA object
> ### Aliases: plot.DNAcopy
> ### Keywords: nonparametric
>
> ### ** Examples
>
>
> #Read in two examples from Snijders et al.
>
> data(coriell)
>
> #Combine into one CNA object to prepare for analysis on Chromosomes 1-23
>
> CNA.object <- CNA(cbind(coriell$Coriell.05296,coriell$Coriell.13330),
+ coriell$Chromosome,coriell$Position,
+ data.type="logratio",sampleid=c("c05296","c13330"))
Warning message:
In CNA(cbind(coriell$Coriell.05296, coriell$Coriell.13330), coriell$Chromosome, :
array has repeated maploc positions
>
> #We generally recommend smoothing single point outliers before analysis
> #Make sure to check that the smoothing is proper
>
> smoothed.CNA.object <- smooth.CNA(CNA.object)
>
> #Segmentation at default parameters
>
> segment.smoothed.CNA.object <- segment(smoothed.CNA.object, verbose=1)
Analyzing: c05296
Analyzing: c13330
>
> #Plot whole studies
>
> plot(segment.smoothed.CNA.object, plot.type="w")
>
> #Plot each study by chromosome
>
> plot(segment.smoothed.CNA.object, plot.type="s")
Setting multi-figure configuration
>
> #Plot each chromosome across studies (6 per page)
>
> plot(segment.smoothed.CNA.object, plot.type="c", cbys.layout=c(2,1), cbys.nchrom=6)
Setting multi-figure configuration
>
> #Plot by plateaus
>
> plot(segment.smoothed.CNA.object, plot.type="p")
>
>
>
>
>
>
> dev.off()
null device
1
>