heatmapModels.BigBang {galgo}R Documentation

Plots models using heatmap plot

Description

Plots models using heatmap plot.

Usage

## 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"),
        ...)

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.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

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

   #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]]))
[Package galgo version 1.0-10 Index]