\title{Tests association between qualitative variables and components.}
   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")
   \item{params}{An object of class
   providing the parameters of the analysis.}
   \item{icaSet}{An object of class
   \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
   \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
   \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
   \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.}
   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.
   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
   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
 ## load an example of IcaSet
 ## 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)
   Anne Biton
   , \code{\link{qualVarAnalysis}}, \code{\link{p.adjust}},
   \code{wilcox.test}, \code{kruskal.test}