plotScaleSpace: Plot multiple significant regions in one figure

In KCsmart: Multi sample aCGH analysis package using kernel convolution

Description

Plots significant regions in different scale spaces in one figure

Usage

plotScaleSpace(spms, sigLevels, chromosomes=NULL, type='b')

Arguments

spms	List of sample point matrices
sigLevels	List of significance levels
chromosomes	Takes a vector of chromosomes to be plotted. Defaults to all chromosomes.
type	Determines which data is plotted. 'g' for gains only, 'l' for losses only and 'b' for both. When type='b' is used, two devices (x11) will be opened.

Details

Takes sample point matrices that were calculated using (different) kernel widths (sigma), then calculates the significant regions given the cutoffs as defined by 'sigLevels' and plots these in one figure.

Value

Depending on the 'type' parameter, produces one or two plots, one for the gains and one for the losses. The heatmap color indicates the level of the gain or loss.

Author(s)

Jorma de Ronde

See Also

plot

Examples

data(hsSampleData)
data(hsMirrorLocs)

spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)
spm4mb <- calcSpm(hsSampleData, hsMirrorLocs, sigma=4000000)

siglevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)
siglevel4mb <- findSigLevelTrad(hsSampleData, spm4mb, n=3)

plotScaleSpace(list(spm1mb, spm4mb), list(siglevel1mb, siglevel4mb), type='g')

KCsmart documentation built on Nov. 8, 2020, 7:08 p.m.