\HeaderA{plot}{Method plot for objects defined in this package}{plot}
\methaliasA{plot.maiges}{plot}{plot.maiges}
\methaliasA{plot.maigesActMod}{plot}{plot.maigesActMod}
\methaliasA{plot.maigesActNet}{plot}{plot.maigesActNet}
\methaliasA{plot.maigesANOVA}{plot}{plot.maigesANOVA}
\methaliasA{plot.maigesClass}{plot}{plot.maigesClass}
\methaliasA{plot.maigesDE}{plot}{plot.maigesDE}
\methaliasA{plot.maigesDEcluster}{plot}{plot.maigesDEcluster}
\methaliasA{plot.maigesRaw}{plot}{plot.maigesRaw}
\methaliasA{plot.maigesRelNetB}{plot}{plot.maigesRelNetB}
\methaliasA{plot.maigesRelNetM}{plot}{plot.maigesRelNetM}
\keyword{array}{plot}
\begin{Description}\relax
Generic function \code{\LinkA{plot}{plot}} to display scatter plots
or other types of graphical representation for objects defined in this
package.
\end{Description}
\begin{Usage}
\begin{verbatim}
## S3 method for class 'maigesRaw':
plot(x, bkgSub="subtract", z=NULL, legend.func=NULL,
    ylab="W", ...)

## S3 method for class 'maiges':
plot(x, z=NULL, legend.func=NULL, ylab="W", ...)

## S3 method for class 'maigesANOVA':
plot(x, z=NULL, legend.func=NULL, ylab="W", ...)

## S3 method for class 'maigesDE':
plot(x, adjP="none", idx=1, ...)

## S3 method for class 'maigesDEcluster':
plot(x, adjP="none", idx=1, ...)

## S3 method for class 'maigesClass':
plot(x, idx=1, ...)

## S3 method for class 'maigesRelNetB':
plot(x=NULL, cutPval=0.05, cutCor=NULL,
name=NULL, ...)

## S3 method for class 'maigesRelNetM':
plot(x=NULL, cutPval=0.05, names=NULL, ...)

## S3 method for class 'maigesActMod':
plot(x, type=c("S", "C")[2], keepEmpty=FALSE, ...)

## S3 method for class 'maigesActNet':
plot(x, type=c("score", "p-value")[1], ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] an object of any class defined in this package, except \code{\LinkA{maigesPreRaw}{maigesPreRaw}}.
\item[\code{bkgSub}] string specifying the method for background
subtraction. See function \code{\LinkA{backgroundcorrect}{backgroundcorrect}} to
find the available options.
\item[\code{z}] accessor method for stratifying data, see \code{\LinkA{maPlot}{maPlot}}.
\item[\code{legend.func}] string specifying options to show legend in the figure.
\item[\code{ylab}] character string specifying the label to y axis.
\item[\code{adjP}] type of p-value adjustment, see function
\code{\LinkA{mt.rawp2adjp}{mt.rawp2adjp}} in package multtest.
\item[\code{idx}] index of the test statistic to be plotted in case of
objects of classes \code{\LinkA{maigesDE}{maigesDE}} and
\code{\LinkA{maigesDEcluster}{maigesDEcluster}} or the index of the clique to be plotted
in case of object with class \code{\LinkA{maigesClass}{maigesClass}}.
\item[\code{cutPval}] real number in [0,1] specifying a cutoff p-value to
show significant results from relevance network analysis. For class
\code{\LinkA{maigesRelNetB}{maigesRelNetB}}, if this parameter is specified the
argument \code{cutCor} isn't used.
\item[\code{cutCor}] real number in [0,1], specifying a coefficient
correlation value cutoff (in absolute value) to show only absolute
correlation values greater than this value. Pay attention, to use
this cutoff it is necessary to specify \code{cutPval} as NULL.
\item[\code{name}] character string giving a name for sample type tested to
be plotted as a name in the method for class \code{\LinkA{maigesRelNetB}{maigesRelNetB}}.
\item[\code{names}] similar to the previous one, but it is a vector of length
3.
\item[\code{type}] string specifying the type of colour map to be plotted. For
class \code{\LinkA{maigesActMod}{maigesActMod}} it must be 'S' or 'C' for samples
or biological conditions, respectively. For class
\code{\LinkA{maigesActNet}{maigesActNet}} it must be 'score' or 'p-value' for the
statistics or p-values of the tests, respectively.
\item[\code{keepEmpty}] logical, if true the results of all gene groups are
displayed, else only the gene groups that present at least one
significant result are displayed.
\item[\code{...}] additional arguments for method
\code{\LinkA{maPlot}{maPlot}} or \code{\LinkA{plot}{plot}}
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This method uses the function \code{\LinkA{maPlot}{maPlot}} to display
scatter plots ratio vs mean values for objects of class
\code{\LinkA{maiges}{maiges}}, \code{\LinkA{maigesRaw}{maigesRaw}} or
\code{\LinkA{maigesANOVA}{maigesANOVA}}. For objects of class \code{\LinkA{maigesDE}{maigesDE}}
or \code{\LinkA{maigesDEcluster}{maigesDEcluster}}, this method display volcano
plots. For objects of class \code{\LinkA{maigesClass}{maigesClass}} it do 2 or 3
dimensions scatter plots that facilitate the visualisation of good
classifying cliques of genes For objects of class
\code{\LinkA{maigesRelNetM}{maigesRelNetM}} the method displays 3 circular graphs
representing the correlation values for the two groups tested and the
p-values of the tests. For class \code{\LinkA{maigesRelNetB}{maigesRelNetB}} it
displays only one circular graph showing the correlation values for
the type tested. In objects of class \code{\LinkA{maigesActMod}{maigesActMod}} and
\code{\LinkA{maigesActNet}{maigesActNet}} the method do the same job as
\code{\LinkA{image}{image}}.

Pay attention that, even using the method \code{\LinkA{maPlot}{maPlot}}
from \emph{marray} package, we plot \emph{W} values against \emph{A}
values instead of \emph{MA} plots.
\end{Details}
\begin{Author}\relax
Gustavo H. Esteves <gesteves@vision.ime.usp.br>
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{mt.rawp2adjp}{mt.rawp2adjp}},
\code{\LinkA{backgroundcorrect}{backgroundcorrect}}, \code{\LinkA{maPlot}{maPlot}} in
the package marray, \code{\LinkA{plot}{plot}} in the base package.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Loading the dataset
data(gastro)

## Example with an object of class maigesRaw, without and with backgound
## subtraction, also we present a plot with normexp (from limma package)
## subtract algorithm.
plot(gastro.raw[,1], bkgSub="none")
plot(gastro.raw[,1], bkgSub="subtract")
plot(gastro.raw[,1], bkgSub="normexp")

## Example with an object of class maigesNorm.
plot(gastro.norm[,1])


## Example for objects of class maigesDE.

## Doing bootstrap from t statistic test fot 'Type' sample label, k=1000
## specifies one thousand bootstraps
gastro.ttest = deGenes2by2Ttest(gastro.summ, sLabelID="Type")

plot(gastro.ttest) ## Volcano plot

## Example for object of class maigesClass.

## Doing LDA classifier with 3 genes for the 6th gene group comparing
## the 2 categories from 'Type' sample label.
gastro.class = classifyLDA(gastro.summ, sLabelID="Type",
  gNameID="GeneName", nGenes=3, geneGrp=6)

plot(gastro.class) ## plot the 1st classifier
plot(gastro.class, idx=7) ## plot the 7th classifier


## Example for object of class maigesActNet

## Doing functional classification of gene groups for 'Tissue' sample label
gastro.mod = activeMod(gastro.summ, sLabelID="Tissue", cutExp=1,
  cutPhiper=0.05)

plot(gastro.mod, "S", margins=c(15,3)) ## Plot for individual samples
plot(gastro.mod, "C", margins=c(21,5)) ## Plot for unique biological conditions


## Example for object of class maigesRelNetB

## Constructing the relevance network (Butte's method) for sample
## 'Tissue' equal to 'Neso' for the 1st gene group
gastro.net = relNetworkB(gastro.summ, sLabelID="Tissue", 
  samples="Neso", geneGrp=1, type="Rpearson")

plot(gastro.net, cutPval=0.05)



## Example for object of class maigesRelNetM

## Constructing the relevance network for sample
## 'Tissue' comparing 'Neso' and 'Aeso' for the 1st gene group
gastro.net = relNetworkM(gastro.summ, sLabelID="Tissue", 
  samples = list(Neso="Neso", Aeso="Aeso"), geneGrp=11,
  type="Rpearson")

plot(gastro.net, cutPval=0.05)
plot(gastro.net, cutPval=0.01)


## Example for objects of class maigesActNet

## Doing functional classification of gene networks for sample Label
## given by 'Tissue'
gastro.net = activeNet(gastro.summ, sLabelID="Tissue")

plot(gastro.net, type="score", margins=c(21,5))
plot(gastro.net, type="p-value", margins=c(21,5))
\end{ExampleCode}
\end{Examples}

