\name{qualVarAnalysis}
 \alias{qualVarAnalysis}
 \title{Tests association between qualitative variables and components.}
 \usage{
   qualVarAnalysis(params, icaSet, keepVar,
     keepComp = indComp(icaSet),
     keepSamples = sampleNames(icaSet),
     adjustBy = c("none", "component", "variable"),
     method = "BH", doPlot = TRUE, typePlot = "density",
     addPoints = FALSE, onlySign = TRUE,
     cutoff = params["pvalCutoff"],
     colours = annot2col(params), path = "qualVarAnalysis/",
     filename = "qualVar", typeImage = "png")
 }
 \arguments{
   \item{params}{An object of class
   \code{\link[MineICA:MineICAParams-class]{MineICAParams}}
   providing the parameters of the analysis.}
 
   \item{icaSet}{An object of class
   \code{\link[MineICA:IcaSet-class]{IcaSet}}.}
 
   \item{keepVar}{The variable labels to be considered, must
   be a subset of \code{varLabels(icaSet)}.}
 
   \item{keepComp}{A subset of components, must be included
   in \code{indComp(icaSet)}. By default, all components are
   used.}
 
   \item{keepSamples}{A subset of samples, must be included
   in \code{sampleNames(icaSet)}. By default, all samples
   are used.}
 
   \item{adjustBy}{The way the p-values of the Wilcoxon and
   Kruskal-Wallis tests should be corrected for multiple
   testing: \code{"none"} if no p-value correction has to be
   done, \code{"component"} if the p-values have to be
   corrected by component, \code{"variable"} if the p-values
   have to be corrected by variable}
 
   \item{method}{The correction method, see
   \code{\link{p.adjust}} for details, default is
   \code{"BH"} for Benjamini & Hochberg.}
 
   \item{doPlot}{If TRUE (default), the plots are done, else
   only tests are performed.}
 
   \item{addPoints}{If TRUE, points are superimposed on the
   boxplot.}
 
   \item{typePlot}{The type of plot, either \code{"density"}
   or \code{"boxplot"}.}
 
   \item{onlySign}{If TRUE (default), only the significant
   results are plotted.}
 
   \item{cutoff}{A threshold p-value for statistical
   significance.}
 
   \item{colours}{A vector of colours indexed by the
   variable levels, if missing the colours are automatically
   generated using \code{\link{annot2Color}}.}
 
   \item{path}{A directory _within resPath(params)_ where
   the files containing the plots and the p-value results
   will be located. Default is \code{"qualVarAnalysis/"}.}
 
   \item{typeImage}{The type of image file to be used.}
 
   \item{filename}{The name of the HTML file containing the
   p-values of the tests, if NULL no file is created.}
 }
 \value{
   Returns A data.frame of dimensions 'components x
   variables' containing the p-values of the non-parametric
   tests (Wilcoxon or Kruskal-Wallis tests) wich test if the
   samples groups defined by each variable are differently
   distributed on the components.
 }
 \description{
   This function tests if the groups of samples formed by
   the variables are differently distributed on the
   components, in terms of contribution value (i.e of values
   in matrix \code{A(icaSet)}). The distribution of the
   samples on the components are represented using either
   density plots of boxplots. It is possible to restrict the
   tests and the plots to a subset of samples and/or
   components.
 }
 \details{
   This function writes an HTML file containing the results
   of the tests as a an array of dimensions 'variables *
   components' containing the p-values of the tests. When a
   p-value is considered as significant according to the
   threshold \code{cutoff}, it is written in bold and filled
   with a link pointing to the corresponding plot. One image
   is created by plot and located into the sub-directory
   "plots/" of \code{path}. Each image is named by
   index-of-component_var.png. Wilcoxon or Kruskal-Wallis
   tests are performed depending on the number of groups of
   interest in the considered variable (argument
   \code{keepLev}).
 }
 \examples{
 ## load an example of IcaSet
 data(icaSetCarbayo)
 
 ## build MineICAParams object
 params <- buildMineICAParams(resPath="carbayo/")
 
 ## Define the directory containing the results
 dir <- paste(resPath(params), "comp2annot/", sep="")
 
 ## Run tests, make no adjustment of the p-values,
 # for variable grade and components 1 and 2,
 # and plot boxplots when 'doPlot=TRUE'.
 qualVarAnalysis(params=params, icaSet=icaSetCarbayo, adjustBy="none", typePlot="boxplot",
                 keepVar="GRADE", keepComp=1:2, path=dir, doPlot=FALSE)
 }
 \author{
   Anne Biton
 }
 \seealso{
   , \code{\link{qualVarAnalysis}}, \code{\link{p.adjust}},
   \code{link{writeHtmlResTestsByAnnot}},
   \code{wilcox.test}, \code{kruskal.test}
 }