\name{summarize.region.parameters}
\alias{summarize.region.parameters}
\title{Summarize overlapping models.}
\description{Given a chromosomal region, summarize the model parameters
  from overlapping models. This heuristics gives a brief summary on
  average sample and probe effects within the region and aids
  interpretation. If multiple alteration profiles are detected within
  the region, the models are grouped and summarization is applied
  separately for each group containing overlapping models with high similarity.}
\usage{
summarize.region.parameters(region.genes, model, X, Y, grouping.th = 0.9, rm.na = TRUE)
}

\arguments{
  \item{region.genes}{A vector of gene names determining the investigated region.}
  \item{model}{Object of \linkS4class{ChromosomeModels} or \linkS4class{GenomeModels} class.}
  \item{X}{Data object. See help(screen.cgh.mrna). For instance, geneExp
  from our example data set.}
  \item{Y}{Data object. See help(screen.cgh.mrna). For instance, geneCopyNum
    from our example data set.}
  \item{grouping.th}{Similarity threshold for joining neighboring
    models.}
  \item{rm.na}{Remove genes with NA values from the output.}
}
\details{Grouping of the models is based on heuristics where highly
  correlating models (>grouping.th) are merged. Will be improved
  later.}
\value{
  \item{z}{Mean sample effects, averaged over the overlapping models for
    each sample.}
  \item{W}{Mean probe effects, averaged over the overlapping models for
  each probe. This is a list with elements X, Y, corresponding to the
  two data sets.}  
}
\references{See citation("pint")}
\author{Leo Lahti \email{leo.lahti@iki.fi}}
\seealso{merge.top.regions}
\examples{
#  tmp <- summarize.region.parameters(top.region.genes, model, geneExp, geneCopyNum)
#  wx <- tmp$W$X
#  z <- tmp$z
}
\keyword{ utilities }