\name{HyperGResult-accessors}
\alias{HyperGResult-accessors}

\alias{pvalues}
\alias{pvalues,HyperGResult-method}
\alias{pvalues,ChrMapHyperGResult-method}

\alias{geneCounts}
\alias{geneCounts,HyperGResultBase-method}

\alias{universeCounts}
\alias{universeCounts,HyperGResultBase-method}

\alias{universeMappedCount}
\alias{universeMappedCount,HyperGResultBase-method}

\alias{geneMappedCount}

\alias{chrGraph}
\alias{chrGraph,ChrMapHyperGResult-method}

\alias{annotation}

\alias{description}
\alias{description,HyperGResultBase-method}

\alias{annotation,HyperGResultBase-method}

\alias{geneIds}
\alias{geneIds,HyperGResultBase-method}

\alias{geneIdUniverse}
\alias{geneIdUniverse,HyperGResult-method}
\alias{geneIdUniverse,ChrMapHyperGResult-method}

\alias{condGeneIdUniverse}
\alias{condGeneIdUniverse,HyperGResultBase-method}
\alias{condGeneIdUniverse,ChrMapHyperGResult-method}

\alias{geneIdsByCategory}
\alias{geneIdsByCategory,HyperGResultBase-method}

\alias{sigCategories}
\alias{sigCategories,HyperGResultBase-method}

\alias{geneMappedCount}
\alias{geneMappedCount,HyperGResultBase-method}

\alias{testName}
\alias{testName,HyperGResultBase-method}

\alias{isConditional,HyperGResultBase-method}
\alias{isConditional,ChrMapHyperGResult-method}

\alias{pvalueCutoff}
\alias{pvalueCutoff,HyperGResultBase-method}
\alias{testDirection}
\alias{testDirection,HyperGResultBase-method}


\alias{oddsRatios}
\alias{oddsRatios,HyperGResult-method}
\alias{oddsRatios,ChrMapHyperGResult-method}

\alias{expectedCounts}
\alias{expectedCounts,HyperGResult-method}
\alias{expectedCounts,ChrMapHyperGResult-method}

\alias{summary,HyperGResultBase-method}
\alias{summary,KEGGHyperGResult-method}
\alias{summary,PFAMHyperGResult-method}

\alias{htmlReport}
\alias{htmlReport,HyperGResultBase-method}
\alias{htmlReport,KEGGHyperGResult-method}
\alias{htmlReport,PFAMHyperGResult-method}


\docType{genericFunction}

\title{Accessors for HyperGResult Objects}

\description{
  This manual page documents generic functions for extracting data
  from the result object returned from a call to \code{hyperGTest}.
  The result object will be a subclass of \code{HyperGResultBase}.
  Methods apply to all result object classes unless otherwise noted.
}

\usage{

pvalues(r)
oddsRatios(r)
expectedCounts(r)

geneCounts(r)
universeCounts(r)
universeMappedCount(r)
geneMappedCount(r)

geneIds(object, ...)
geneIdUniverse(r, cond = TRUE)
condGeneIdUniverse(r)
geneIdsByCategory(r, catids = NULL)
sigCategories(r, p)

## R CMD check doesn't like these
## annotation(r)
## description(r)

testName(r)
pvalueCutoff(r)
testDirection(r)

chrGraph(r)


}

\arguments{
  \item{r, object}{An instance of a subclass of
    \code{HyperGResultBase}.}

  \item{catids}{A character vector of category identifiers.}
  \item{p}{Numeric p-value used as a cutoff for selecting a subset of
    the result.}
  \item{cond}{A logical value indicating whether to return conditional
  results for a conditional test.  The default is \code{TRUE}.  For
  non-conditional results, this argument is ignored.}
  \item{...}{Additional arguments that may be used by specializing methods.}
}

\section{Accessor Methods (Generic Functions)}{
 \describe{

  \item{geneCounts}{returns an \code{"integer"}
      vector: for each category term tested, the number of genes from
      the gene set that are annotated at the term.}

  \item{pvalues}{returns a \code{"numeric"}
      vector: the ordered p-values for each category term tested.}

  \item{universeCounts}{returns an \code{"integer"}
      vector: for each category term tested, the number of genes from
      the gene universe that are annotated at the term.}

  \item{universeMappedCount}{returns an \code{"integer"}
      vector of length one giving the size of the gene universe set.}

  \item{expectedCounts}{returns a \code{"numeric"} vector
      giving the expected number of genes in the selected gene list to
      be found at each tested category term.}

  \item{oddsRatios}{returns a \code{"numeric"} vector giving
      the odds ratio for each category term tested.}

    \item{annotation}{returns the name
        of the annotation data package used.  }

    \item{geneIds}{returns the input
        vector of gene identifiers intersected with the universe of
        gene identifiers used in the computation. }

    \item{geneIdUniverse}{returns a list named by the
      tested categories.  Each element of the list is a vector of gene
      identifiers (from the gene universe) annotated at the
      corresponding category term.}

    \item{geneIdsByCategory}{returns a list similar to
      \code{geneIdUniverse}, but each vector of gene IDs is
      intersected with the list of selected gene IDs from
      \code{geneIds}.  The result is the selected gene IDs annotated at
      each category.}

    \item{sigCategories}{returns a character vector of category
      identifiers with a significant p-value.  If argument \code{p} is
      missing, then the cutoff obtained from \code{pvalueCutoff(r)} will
    be used.}

    \item{geneMappedCount}{returns the size of
        the selected gene set used in the computation.  This is simply
        \code{length(geneIds(obj))}.}

    \item{pvalueCutoff}{accessor for the
        \code{pvalueCutoff} slot.}

    \item{testDirection}{accessor for the
        \code{testDirection} slot.  Contains a string indicating
        whether the test was for \code{"over"} or \code{"under"}
        representation of the categories.}

    \item{description}{returns a character
        string description of the test result. }

    \item{testName}{returns a string
        describing the testing method used.}

    \item{isConditional}{returns \code{TRUE} if the
          result was obtained using a conditional algorithm.}

    \item{summary}{returns
      a \code{data.frame} summarizing the test result.  Optional
      arguments \code{pvalue} and \code{categorySize} allow
      specification of maximum p-value and minimum categorySize,
      respectively.}

    \item{htmlReport}{writes
      an HTML version of the table produced by the \code{summary}
      method.  The first argument should be a \code{HyperGResult}
      instance (or subclass). The path of a file to write the report to
      can be specified using the \code{file} argument.  The default is
      \code{file=""} which will cause the report to be printed to the
      screen.  If you wish to create a single report comprising multiple
      results you can set \code{append=TRUE}.  The default is
      \code{FALSE} (overwrite pre-existing report file).  You can
      specify a string to use as an identifier for each table by
      providing a value for the \code{label} argument.  The number of
      digits displayed in numerical columns can be controlled using
      \code{digits} (defaults to 3).  The \code{summary} method is
      called on the \code{HyperGResult} instance to generate a data
      frame that is transformed to HTML.  You can pass additional
      arguments to the \code{summary} method which is used to generate
      the data frame that is transformed to HTML by specifying a named
      list using \code{summary.args}.}

  }
}

\details{
}

\author{Seth Falcon}
\seealso{
  \code{\link{hyperGTest}}
  \code{\link{HyperGResult-class}}
  \code{\link{HyperGParams-class}}
  \code{\link{GOHyperGParams-class}}
  \code{\link{KEGGHyperGParams-class}}
}
\examples{
## Note that more in-depth examples can be found in the GOstats
## vignette (Hypergeometric tests using GOstats).
library("hgu95av2.db")
probids <- ls(hgu95av2GENENAME)[1:300]
## Select for probeids that have PFAM ids
hasPFAM <- sapply(mget(probids, hgu95av2PFAM), function(ids)
                  if(!is.na(ids) && length(ids) > 1) TRUE else FALSE)
probids <- probids[hasPFAM]
## get unique Entrez Gene IDs
probids <- unique(getLL(probids, "hgu95av2"))
## Now do the same for the universe
univ <- ls(hgu95av2GENENAME)
univHasPFAM <- sapply(mget(univ, hgu95av2PFAM), function(ids)
                      if(!is.na(ids) && length(ids) > 1) TRUE else
                         FALSE)
univ <- univ[univHasPFAM]
univ <- unique(getLL(univ, "hgu95av2"))

p <- new("PFAMHyperGParams", geneIds=probids, universeGeneIds=univ,
         annotation="hgu95av2")
## this takes a while...
if(interactive()){
hypt <- hyperGTest(p)
summary(hypt)
htmlReport(hypt, file="temp.html", summary.args=list("htmlLinks"=TRUE))
}
}
\keyword{htest}