\name{tabulate.top.dep.features}
\alias{tabulate.top.dep.features}
\title{Lists the p-values for the dependent features}
\description{Lists the integrated analysis p-values for the dependent features in the analyzed regions, 
together with the available annotation.
}

\usage{
tabulate.top.dep.features(input.regions = "all chrs", adjust.method = c("BY", "BH", "raw"), run.name = NULL)
}

\arguments{
 \item{input.regions}{\code{\link{vector}} indicating the regions to be analyzed. Can be defined in four w
ays:
  \code{1) predefined input region: } insert a predefined input region, choices are:
  \code{"all chrs"}, \code{"all chrs auto"}, \code{"all arms"}, \code{"all arms auto"}
  In the predefined regions \code{"all arms"} and \code{"all arms auto"} the arms 13p, 
  14p, 15p, 21p and 22p are left out, because in most studies there are no or few probes 
  in these regions. To include them, just make your own \code{\link{vector}} of arms.
  \code{2) whole chromosome(s): }insert a single chromosome or a list of chromosomes as a \code{\link{vector}:}
  \code{c(1, 2, 3)}.
  \code{3) chromosome arms: } insert a single chromosome arm  or a list of chromosome arms like 
  \code{c("1q", "2p", "2q")}.
  \code{4) subregions of a chromosome: } insert a chromosome number followed by the start and end position
 like \code{c("chr1_1-1000000")}
  These regions can also be combined, e.g. \code{c("chr1_1-1000000","2q", 3)}.
  See \code{details} for more information.}

  \item{adjust.method}{Method used to adjust the p-values for multiple
  testing. Either \code{"BY"} (recommended when copy number is used as dependent data), 
  \code{"BH"} or \code{"raw"}. Defaults to "BY". See \code{\link{SIM}} for more information about adjustin
g p-values.}
   
  \item{run.name}{Name of the analysis. The results will be stored in a folder with this 
  name in the current working directory (use \code{getwd()} to print the current working 
  directory). If the \code{run.name = NULL}, the default folder \code{"analysis_results"} 
  will be generated.}
}
\details{Output is a .txt file containing a table with sorted integrated analysis p-values of the 
dependent features. It includes the \code{ann.dep} columns that were read in the \code{\link{assemble.data}} function.}

\value{No values are returned. The results are stored in a subdirectory of \code{run.name} as txt.}

\author{Marten Boetzer, Melle Sieswerda, Renee X. de Menezes  \email{R.X.Menezes@lumc.nl}}

\seealso{
\code{\link{SIM}}, \code{\link{assemble.data}}, \code{\link{integrated.analysis}}, 
\code{\link{sim.plot.zscore.heatmap}}, \code{\link{sim.plot.pvals.on.region}}, 
\code{\link{sim.plot.pvals.on.genome}}, \code{\link{tabulate.pvals}}, 
\code{\link{tabulate.top.indep.features}}, \code{\link{impute.nas.by.surrounding}}, 
\code{\link{sim.update.chrom.table}}
}


\examples{
#load the datasets and the samples to run the integrated analysis
data(expr.data)
data(acgh.data)
data(samples) 
         
#assemble the data
assemble.data(dep.data = acgh.data, indep.data = expr.data, ann.dep = colnames(acgh.data)[1:4], ann.indep = colnames(expr.data)[1:4], dep.id="ID",dep.chr = "CHROMOSOME",dep.pos = "STARTPOS",dep.symb="Symbol", indep.id="ID",indep.chr = "CHROMOSOME", indep.pos = "STARTPOS", indep.symb="Symbol", overwrite = TRUE,run.name = "chr8")

#run the integrated analysis
integrated.analysis(samples = samples, input.regions = 8, adjust=FALSE, zscores=TRUE, method = "auto", run.name = "chr8")

#get the top dependent features with lowest p-value
tabulate.top.dep.features(input.regions = 8, adjust.method="BY",run.name = "chr8")
}
\keyword{misc}