\name{gene.gene.statistic}
\alias{gene.gene.statistic}
\title{ Compute gene-gene statistics }
\description{
 Computes gene gene statistics.
}

\usage{
gene.gene.statistic(g1, g2, paperLens = paperLen())
}

\arguments{
  \item{g1}{The Entrez Gene identifier for one of the genes. }
  \item{g2}{The Entrez Gene identifier for the other gene. }
  \item{paperLens}{ A vector with the 
   number of citations for each paper.  }
}

\details{
For the two genes identified by their Entrez IDs a number
of two-way table statistics, i.e. those computed via \code{\link{twTStats}},
are returned, as are their gene and paper size adjusted variants.
}

\value{
A list with entries
  \item{original}{The output of \code{\link{twTStats}} on the observed data.}
  \item{gs}{The output of \code{\link{twTStats}} on the data scaled for
   gene size.}
  \item{ps}{The output of \code{\link{twTStats}} on the data scaled for
  paper size.}
  \item{both}{The output of \code{\link{twTStats}} on the data scaled for
  both paper and gene size.}
}

\references{Testing Gene Associations Using Co-citation, by B. Ding and
R. Gentleman. Bioconductor Technical Report, 2004}

\author{B. Ding and R. Gentleman}
\seealso{\code{\link{twowayTable}} }

\examples{

 g1 = "10"  #Entrez ID for gene 1
 g2 = "101"  #Entrez ID for gene 2
 pLens = paperLen()
 gene.gene.statistic(g1, g2, pLens)

}
\keyword{manip}