copynumber (version 1.12.0)

plotSample: Plot copy number data and/or segmentation results by sample

Description

Plot copy number data and/or segmentation results for each sample separately with chromosomes in different panels.

Usage

plotSample(data = NULL, segments = NULL, pos.unit = "bp", sample = NULL,
            chrom = NULL, assembly = "hg19", winsoutliers = NULL, xaxis = 
            "pos", layout = c(1,1), plot.ideo = TRUE, ...)

Arguments

data

a data frame with numeric or character chromosome numbers in the first column, numeric local probe positions in the second, and numeric copy number data for one or more samples in subsequent columns. The header of the copy number columns should be the sample IDs.

segments

a data frame or a list of data frames containing the segmentation results found by either pcf or multipcf.

pos.unit

the unit used to represent the probe positions. Allowed options are "mbp" (mega base pairs), "kbp" (kilo base pairs) or "bp" (base pairs). By default assumed to be "bp".

sample

a numeric vector indicating which sample(s) is (are) to be plotted. The number(s) should correspond to the sample's place (in order of appearance) in data, or in segments in case data is unspecified.

chrom

a numeric or character vector with chromosome number(s) to indicate which chromosome(s) is (are) to be plotted.

assembly

a string specifying which genome assembly version should be applied to define the chromosome ideogram. Allowed options are "hg19", "hg18", "hg17" and "hg16" (corresponding to the four latest human genome annotations in the UCSC genome browser).

winsoutliers

an optional data frame of the same size as data identifying observations classified as outliers by winsorize. If specified, outliers will be marked by a different color and symbol than the other observations (see wins.col and wins.pch).

xaxis

either "pos" or "index". The former implies that the xaxis will represent the genomic positions, whereas the latter implies that the xaxis will represent the probe index. Default is "pos".

layout

an integer vector of length two giving the number of rows and columns in the plot. Default is c(1,1).

plot.ideo

a logical value indicating whether the chromosome ideogram should be plotted. Only applicable when xaxis="pos".

...

other graphical parameters. These include the common plot arguments xlab, ylab, main, xlim, ylim, col (default is "grey"), pch (default is 46, equivalent to "."), cex, cex.lab, cex.main, cex.axis, las, tcl, mar and mgp (see par on these). In addition, a range of graphical arguments specific for plotSample (as well as the similar functions plotChrom, plotGenome and plotAllele) may be specified: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Details

Several plots may be produced on the same page with the layout option. If the number of plots exceeds the desired page layout, the user is prompted before advancing to the next page of output.

See Also

plotChrom, plotGenome

Examples

#Lymphoma data
data(lymphoma)
#Take out a smaller subset of 6 samples (using subsetData):
sub.lymphoma <- subsetData(lymphoma,sample=1:6)

#Winsorize data:
wins.data <- winsorize(data=sub.lymphoma)

#Use pcf to find segments:        
uni.segments <- pcf(data=wins.data,gamma=12)

#Use multipcf to find segments as well:
multi.segments <- multipcf(data=wins.data,gamma=12)

#Plot data and pcf-segments for one sample separately for each chromosome:
plotSample(data=sub.lymphoma,segments=uni.segments,sample=1,layout=c(5,5))
#Add cytoband text to ideogram (one page per chromosome to ensure sufficient 
#space)
plotSample(data=sub.lymphoma,segments=uni.segments,sample=1,layout=c(1,1),
    cyto.text=TRUE)
#Add multipcf-segmentation results, drop legend
plotSample(data=sub.lymphoma,segments=list(uni.segments,multi.segments),sample=1,
    layout=c(5,5),seg.col=c("red","blue"),seg.lwd=c(3,2),legend=FALSE)
#Plot by chromosome for two samples, but only chromosome 1-9. One window per 
#sample:
plotSample(data=sub.lymphoma,segments=list(uni.segments,multi.segments),sample=
    c(2,3),chrom=c(1:9),layout=c(3,3),seg.col=c("red","blue"),
    seg.lwd=c(3,2),onefile=FALSE)

#Zoom in on a particular region by setting xlim:    
plotSample(data=sub.lymphoma,segments=uni.segments,sample=1,chrom=1,plot.ideo=
    FALSE,xlim=c(140,170))