spatial: Examples of array-CGH data with spatial artifacts

In MANOR: CGH Micro-Array NORmalization

Description

This data set provides an example of array-CGH data with spatial artifacts, consisting of including arrayCGH objects before and after normalization

Usage

data(spatial)

Format

• edge, gradientarrayCGH objects before normalization:

  	arrayValues	spot-level information
  	arrayDesign	block design of the array
  	cloneValues	additionnal clone-level data (chromosome, position)

• edge.norm, gradient.normarrayCGH objects after normalization

Details

'edge' presents local spatial bias in the top-right edge corner, and 'gradient' presents global spatial trend. 'edge' and 'gradient' are arrayCGH objects before normalization. They have been created respectively from spot and gpr files using import. 'edge.norm' and 'gradient.norm' are the corresponding arrayCGH objects after normalization using norm.arrayCGH.

flag objects used for data normalization come from flags dataset.

Note

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

Author(s)

Pierre Neuvial, [e-mail].

Source

Institut Curie, [e-mail].

See Also

flags

Examples

data(spatial)

## edge: example of array with local spatial effects

layout(matrix(1:4, 2, 2), height=c(9,1))
GLAD::arrayPlot(edge, "LogRatio", main="Log-ratios before normalization",
zlim=c(-1,1), bar="h", layout=FALSE, mediancenter=TRUE)
GLAD::arrayPlot(edge.norm, "LogRatioNorm", main="Log-ratios after spatial
normalization", zlim=c(-1,1), bar="h", layout=FALSE, mediancenter=TRUE) 

## gradient: example of array with spatial gradient

layout(matrix(1:4, 2, 2), height=c(9,1))
GLAD::arrayPlot(gradient, "LogRatio", main="Log-ratios before normalization",
zlim=c(-2,2), bar="h", layout=FALSE)
GLAD::arrayPlot(gradient.norm, "LogRatioNorm", main="Log-ratios after spatial
normalization", zlim=c(-2,2), bar="h", layout=FALSE)   

Example output

Attaching package: ‘MANOR’

The following object is masked from ‘package:base’:

    norm

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