heatmapModels.BigBang {galgo} | R Documentation |
Plots models using heatmap plot.
## S3 method for class '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$main, scale=if (traspose) "column" else "row", col=c(rgb(0,8:0/8,0),rgb(1:8/8,0,0)), RowSideColors=NULL, ColSideColors=NULL, hclustfun=function(x) hclust(x, method="ward"), distfun = dist, histscale=1, nc=NULL, byclasscolor=FALSE, Colv=NULL, Rowv=NULL, heatmapfunc=heatmap, use.ranks=FALSE, columns=NULL, ...)
models |
The models(chromosomes) to plot. It can be a chromosome list or models resulted from |
data |
Data if this is not provided in |
geneNames |
Names for the genes. The default uses the |
traspose |
Traspose the data (for display and data restrictions). |
subset |
To limit the usage of |
scale,col,RowSideColors,ColSideColors |
Heatmap parameters. Provided for compatibility. If col is -1,-2,-3, or -4, standard microarray colors are used. If length(col)==3, these three colours are used to build a gradient. |
geneColors |
A list of specific RowSideColors parameter for every model. |
sampleColors |
Colors for samples. |
hclustfun |
Function to heatmap. The default use “ward” method. Use |
... |
Other parameters for |
Returns nothing.
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
For more information see BigBang
.
*plot()
,
*forwardSelectionModels()
,
heatmap
().
## Not run: #bb is a BigBang object heatmapModels(bb, bb$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]])) ## End(Not run)