Learn R Programming

made4 (version 1.46.0)

plotarrays: Graph xy plot of variable (array) projections from ordination, between group analysis or coinertia analysis.

Description

Graph xy plot of variables using s.var, s.groups or s.match.col. Useful for visualising array coordinates (\$li) resulting from ord, bga or cia of microarray data.

Usage

plotarrays(coord, axis1 = 1, axis2 = 2, arraylabels = NULL, classvec=NULL, graph = c("groups", "simple", "labels", "groups2", "coinertia","coinertia2"), labelsize=1, star=1, ellipse=1, arraycol=NULL, ...)

Arguments

coord
a data.frame or matrix or object from ord bga or cia analysis with at least two columns, containing x, y coordinates to be plotted
axis1
An integer, the column number for the x-axis. Default is 1, so axes 1 is dudivar[,1]
axis2
An integer, the column number for the y-axis. Default is 2, so axes 2 is dudivar[,2]
arraylabels
A vector of variables labels. Default is row.names(coord)
classvec
A factor or vector which describes the classes in coord. Default is NULL. If included variables will be coloured by class.
graph
A character of type "groups", "simple", "labels", "groups2", "coinertia" or "coinertia2" which specifies the type of plot type or "graph" to be drawn. By default the graph will be selected depending on the class of cooord, and whether a classvector is specified
labelsize
Size of sample labels, by default=1
star
If drawing groups, whether to join samples to centroid creating a "star"
ellipse
If drawing groups, whether to draw an ellipse or ring around the samples
arraycol
Character with length equal to the number of levels in the factor classvec. Colors for each of the levels in the factor classvec
...
further arguments passed to or from other method

Value

An xy plot

Details

plotarrays calls the function s.var, s.groups or s.match.col.

If you wish to return a table or list of the top array at the end of an axis, use the function topgenes.

See Also

See Also as s.var and s.label

Examples

Run this code
data(khan)
if (require(ade4, quiet = TRUE)) {
khan.bga<-bga(khan$train, khan$train.classes) 
}
attach(khan.bga)
par(mfrow=c(2,1))
plotarrays(khan.bga)
plotarrays(khan.bga, graph="simple")
plotarrays(khan.bga, graph="labels")
plotarrays(khan.bga, graph="groups")
plotarrays(khan.bga, graph="groups2")

Run the code above in your browser using DataLab