report.plot: Array image and a genomic representation of a normalized...

In MANOR: CGH Micro-Array NORmalization

Description

Displays an array image and a genomic representation of a normalized arrayCGH.

Usage

## S3 method for class 'arrayCGH'
report.plot(arrayCGH, x="PosOrder", y=c("LogRatioNorm",
  "LogRatio"), chrLim=NULL, layout=TRUE, main=NULL, zlim=NULL, ...)
## Default S3 method:
report.plot(spot.data, clone.data, design, x="PosOrder",
  y=c("LogRatioNorm", "LogRatio"), chrLim=NULL, layout=TRUE, main=NULL,
  zlim=NULL, ...) 

Arguments

arrayCGH	an object of type arrayCGH.
spot.data	data.frame with spot-level information to be passed to arrayPlot.
clone.data	data.frame with clone-level information to be passed to genome.plot.
design	vector of length 4 with array design: number of blocks per column and per row, number of columns and rows per block.
x	a variable name from arrayCGH\$cloneValues giving the order position of the clones along the genome.
y	a vector of one or two variable names to be plotted on the array and along the genome. The first one is taken from arrayCGH\$arrayValues and is plotted on the array; the second one (or the first one if only one name was provided) is taken from arrayCGH\$cloneValues and is plotted along the genome.
chrLim	an optional variable name from arrayCGH\$cloneValues giving the limits of each chromosome.
layout	if TRUE, plot layout is set to a 1*2 matrix with relative column widths 1 and 4.
main	title for the genomic profile.
zlim	numeric vector of length 2 to be passed to arrayPlot: minimum and maximum signal values for array image display.
...	further arguments to be passed to genome.plot.

Details

This function successively calls arrayPlot and genome.plot.

Note

People interested in tools for array-CGH analysis can visit our web-page: http://bioinfo.curie.fr.

Author(s)

Pierre Neuvial, [e-mail].

See Also

genome.plot, arrayPlot, html.report

Examples

data(spatial)

### edge: local spatial bias
## aggregate arrayCGH without normalization for comparison with
## normalized array
edge.nonorm <- norm(edge, flag.list=NULL, FUN=median, na.rm=TRUE) 
edge.nonorm <- sort(edge.nonorm, position.var="PosOrder")

layout(matrix(c(1,2,4,5,3,3,6,6), 4,2),width=c(1, 4), height=c(6,1,6,1))
report.plot(edge.nonorm, chrLim="LimitChr", layout=FALSE,
main="Pangenomic representation (before normalization)", zlim=c(-1,1),
ylim=c(-3,1))  
report.plot(edge.norm, chrLim="LimitChr", layout=FALSE,
main="Pangenomic representation (after normalization)", zlim=c(-1,1),
ylim=c(-3,1)) 

### gradient: global array Trend
## aggregate arrayCGH without normalization for comparison with
## normalized array
gradient.nonorm <- norm(gradient, flag.list=NULL, FUN=median, na.rm=TRUE) 
gradient.nonorm <- sort(gradient.nonorm)

layout(matrix(c(1,2,4,5,3,3,6,6), 4,2),width=c(1, 4), height=c(6,1,6,1))
report.plot(gradient.nonorm, chrLim="LimitChr", layout=FALSE,
main="Pangenomic representation (before normalization)", zlim=c(-2,2),
ylim=c(-3,2)) 
report.plot(gradient.norm, chrLim="LimitChr", layout=FALSE,
main="Pangenomic representation (after normalization)", zlim=c(-2,2),
ylim=c(-3,2)) 

MANOR documentation built on Nov. 8, 2020, 6:52 p.m.