galgo (version 1.4)

heatmapModels.BigBang: Plots models using heatmap plot

Description

Plots models using heatmap plot.

Usage

# S3 method for BigBang
heatmapModels(	O, 
	models, 
	data=O$data$data, 
	geneNames=paste(pad(1:length(O$geneNames), char="  ")," : ",O$geneNames,sep=""),
	traspose=TRUE, 
	subset=NULL, 
	main=O$main, 
	scale=if (traspose) "column" else "row", 
	col=c(rgb(0,8:0/8,0),rgb(1:8/8,0,0)), 
	RowSideColors=NULL, 
	ColSideColors=NULL,
	hclustfun=function(x) hclust(x, method="ward"),
    distfun = dist,
	histscale=1,
	nc=NULL,
    byclasscolor=FALSE,
    Colv=NULL,
    Rowv=NULL,
    heatmapfunc=heatmap,
    use.ranks=FALSE,
    columns=NULL,
	...)

Arguments

models

The models(chromosomes) to plot. It can be a chromosome list or models resulted from forwardSelectionModel.

data

Data if this is not provided in $data$data from the BigBang object.

geneNames

Names for the genes. The default uses the $geneNames from BigBang object.

traspose

Traspose the data (for display and data restrictions).

subset

To limit the usage of models.

scale,col,RowSideColors,ColSideColors

Heatmap parameters. Provided for compatibility. If col is -1,-2,-3, or -4, standard microarray colors are used. If length(col)==3, these three colours are used to build a gradient.

geneColors

A list of specific RowSideColors parameter for every model.

sampleColors

Colors for samples.

hclustfun

Function to heatmap. The default use ``ward'' method. Use hclustfun=hclust to restore the original heatmap behaviour.

...

Other parameters for heatmap function.

Value

Returns nothing.

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see BigBang. *plot(), *forwardSelectionModels(), heatmap().

Examples

# NOT RUN {
   #bb is a BigBang object
   heatmapModels(bb, bb$bestChromosomes[1])

   fsm <- forwardSelectionModels(bb)
   fsm
   names(fsm)
   heatmapModels(fsm, subset=1)
   fsm <- forwardSelectionModels(bb, minFitness=0.9,
   fitnessFunc=bb$galgo$fitnessFunc)
   heatmapModels(fsm, subset=1)
   pcaModels(fsm, subset=1)
   fitnessSplits(bb, chromosomes=list(fsm$models[[1]]))
   
# }
# NOT RUN {
 
# }