pcaModels.BigBang: Plots models in principal components space

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Plots models in principal components space.

Usage

## S3 method for class 'BigBang'
pcaModels(	O, 
	models, 
	data=O$data$data, 
	traspose=FALSE, 
	center=TRUE,
	scale=TRUE, 
	subset=NULL, 
	main=O$main, 
	sampleColors=NULL, 
	sampleNames=NULL,
	npc=4, 
	pch=19, 
	gap=0.25,
	classes=NULL,
    show.loadings=FALSE,
    loadings.round=6,
    labels=TRUE,
    order=0,
    col=1:200,
    columns=NULL,
    jitterFactor=0,
	...)

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.
traspose	Traspose the data (for display and data restrictions).
subset	To limit the usage of models.
center	Logical value indicating whether scalling by genes to mean 0. See prcomp.
scale	Logical value indicating whether scalling by genes to 1 variance. See prcomp.
main,gap,pch	Plot parameters (method pairs). If pch==NULL, sampleColors are used instead.
sampleColors	Colors for samples.
sampleNames	To plot the samples names. Use the variable $sampleNames to from the BigBang object.
classes	Sample classes. The default is using $classes from bigbang object.
...	Other parameters for pairs (or plot) function.

Value

Returns the results of prcomp in a list.

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(), prcomp(), princomp().

Examples

## Not run: 
   #bb is a BigBang object
   pcaModels(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)
 

galgo documentation built on May 2, 2019, 4:20 a.m.