BinFeaturesPlot: Plot of a selection of features
In IntClust: Integrated Data Analysis via Clustering

Description Usage Arguments Value Author(s) Examples

The function BinFeaturesPlot plots the binary data matrix for a selection of features. It is possible to separate between compounds of interest and the other compounds. This is a visualization to see which characteristics are (not) expressed in a specific cluster.

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BinFeaturesPlot(LeadCpds, OrderLab, Features, Data, ColorLab, nrclusters = NULL, 
cols = NULL, name = c("FP"),colors1 = c("gray90", "blue"), colors2 = c("gray90",
"green"),margins=c(5.5,3.5,0.5,5.5),plottype="new",location=NULL)

`LeadCpds`	A character vector containing the compounds one wants to separate from the others.
`Features`	A character vector containing the selection of features to be plotted.
`Data`	The data matrix the features are derived from.
`OrderLab`	Optional. If the compounds are to set in a specific order of a specific clustering.
`ColorLab`	Optional. The clustering result that determines the clusters of the labels of the objects in the plot.
`nrclusters`	Optional. The number of clusters to consider if ColorLab is specified.
`cols`	The colors for the clusters of the labels of the objects as determined by ColorLab.
`name`	The overall name to give the features.
`colors1`	Colors to indicate the present and abscence of features of the compounds not in LeadComps.
`colors2`	Colors to indicate the present and abscence of features of the LeadComps.
`margins`	Optional. Margins to be used for the plot.
`plottype`	Should be one of "pdf","new" or "sweave". If "pdf", a location should be provided in "location" and the figure is saved there. If "new" a new graphic device is opened and if "sweave", the figure is made compatible to appear in a sweave or knitr document, i.e. no new device is opened and the plot appears in the current device or document.
`location`	If plottype is "pdf", a location should be provided in "location" and the figure is saved there.

A plot indicating the values of the features of the LeadCpds in green and those of the others in blue.

Marijke Van Moerbeke

data(fingerprintMat)
data(targetMat)
data(geneMat)

MCF7_F = Cluster(fingerprintMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="ward",gap=FALSE,maxK=55)
MCF7_T = Cluster(targetMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="ward",gap=FALSE,maxK=55)
## Not run: 
MCF7_Interactive=ChooseFeatures(Interactive=TRUE,LeadCpds=NULL,ClusterResult=MCF7_T,
ClusterColors=MCF7_F,BinData=list(fingerprintMat),Datanames=c("FP"),geneMat,
topChar = 20, topG = 20,nrclusters=7,N=1)

Lead=MCF7_Interactive$"Choice 1"$Compounds$LeadCpds
Feat=MCF7_Interactive$"Choice 1"$Characteristic$FP

BinFeaturesPlot(LeadCpds=Lead,Features=Feat,Data=fingerprintMat,OrderLab=MCF7_F,ColorLab=MCF7_F,
nrclusters=7,cols=Colors1,name=c("FP"),margins=c(5.5,3.5,0.5,5.5),plottype="new",location=NULL)

## End(Not run)