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Last data update: 2014.03.03

R: Spatial image of microarray spots statistic

arrayPlot

R Documentation

Spatial image of microarray spots statistic

Description

The function arrayPlot creates spatial images of shades of gray or colors that correspond to the values of a statistic for each spot on the array. The statistic can be the intensity log-ratio, a spot quality measure (e.g. spot size or shape), or a test statistic. This function can be used to explore whether there are any spatial effects in the data, for example, print-tip or cover-slip effects.

Usage

## Default S3 method:
arrayPlot(Statistic, Col, Row,
                  ArrCol, ArrRow, SpotCol, SpotRow,
                  mediancenter=FALSE,
                  col=myPalette("green", "red", "yellow"),
                  contour=FALSE, nlevels=5,
                  zlim=NULL, bar=c("none", "horizontal", "vertical"),
                  layout=TRUE, ...) 

## S3 method for class 'arrayCGH'
arrayPlot(arrayCGH, variable,
                   mediancenter=FALSE,
                   col=myPalette("green", "red", "yellow"),
                   contour=FALSE, nlevels=5,
                   zlim=NULL, bar=c("none", "horizontal", "vertical"),
                   layout=TRUE, ...)

Arguments

`arrayCGH`	Object of class `arrayCGH`.
`variable`	Variable to be plotted
`Statistic`	Statistic to be plotted.
`Col`	Vector of columns coordinates.
`Row`	Vector of rows coordinates.
`ArrCol`	Number of columns for the blocs.
`ArrRow`	Number of rows for the blocs.
`SpotCol`	Number of column for each bloc.
`SpotRow`	Number of rows for each bloc.
`mediancenter`	If `mediancenter=TRUE`, values of `Statistic` are median-centered.
`col`	List of colors such as that generated by `Palettes`. In addition to these color palettes functions, a new function `myPalette` was defined to generate color palettes from user supplied low, middle, and high color values.
`contour`	If `contour=TRUE`, contour are plotted, otherwise they are not shown.
`nlevels`	Numbers of levels added by `contour` if `contour=TRUE`.
`zlim`	Numerical vector of length 2 giving the extreme values of `z` to associate with colors `low` and `high` of `myPalette`. By default `zlim` is the range of `z`. Any values of `z` outside the interval `zlim` will be truncated to the relevant limit.
`bar`	If `bar=='horizontal'` (resp. `'vertical'`), an horizontal (resp. vertical) calibration color bar is shown to the right of the image.
`layout`	If `layout==TRUE` plot layout is automatically set when a color bar is asked for
`...`	Graphical parameters can be given as arguments to function `image`.

N.B. : Col takes the values in 1:arrayRow*SpotRow and Row takes the values in 1:arrayCol*SpotCol

Details

This function is very similar to the maImage written by Sandrine Dudoit (available in marrayPlots package) with added options zlim, mediancenter and layout.

Value

An image is created on the current graphics device.

Note

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

Author(s)

Examples

data(arrayCGH)

pdf(file="arrayCGH.pdf",height=21/cm(1),width=29.7/cm(1))
arrayPlot(array2$Log2Rat, array2$Col, array2$Row, 4,4,21,22, main="Spatial Image of array CGH")
dev.off()


# object of class arrayCGH

array <- list(arrayValues=array2, arrayDesign=c(4,4,21,22))
class(array) <- "arrayCGH"

arrayPlot(array,"Log2Rat", main="Spatial Image of array CGH")

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(GLAD)

######################################################################################

Have fun with GLAD

For smoothing it is possible to use either
the AWS algorithm (Polzehl and Spokoiny, 2002,
or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics,  2008,

If you use the package with AWS, please cite:
Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,

If you use the package with HaarSeg, please cite:
Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,

For fast computation it is recommanded to use
the daglad function with smoothfunc=haarseg

######################################################################################

New options are available in daglad: see help for details.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/GLAD/arrayPlot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: arrayPlot
> ### Title: Spatial image of microarray spots statistic
> ### Aliases: arrayPlot arrayPlot.default arrayPlot.arrayCGH
> ### Keywords: hplot
> 
> ### ** Examples
> 
> data(arrayCGH)
> 
> pdf(file="arrayCGH.pdf",height=21/cm(1),width=29.7/cm(1))
> arrayPlot(array2$Log2Rat, array2$Col, array2$Row, 4,4,21,22, main="Spatial Image of array CGH")
> dev.off()
png 
  2 
> 
> 
> # object of class arrayCGH
> 
> array <- list(arrayValues=array2, arrayDesign=c(4,4,21,22))
> class(array) <- "arrayCGH"
> 
> arrayPlot(array,"Log2Rat", main="Spatial Image of array CGH")
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>