\HeaderA{assessSymmetry}{A function that calcualtes some directed degree statistics on
graphs using a binomial error model}{assessSymmetry}
\keyword{datagen}{assessSymmetry}
\begin{Description}\relax
This function takes in a bait to prey protein-protein interaction
graph (undirected) and calculates the reciprocated degree, the
unreciprocated in and out degrees. Using this information and binomial
error model, it asses the p-value for the in and out degree of each
protein. Lastly, it plots the countour curves for these p-values
\end{Description}
\begin{Usage}
\begin{verbatim}
assessSymmetry(bpMat, bpGraph = FALSE,
  prob=0.5, pLevels = 1e-4)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{bpMat}] Either a bait to prey directed graphNEL or its
corresponding adjacency matrix.
\item[\code{bpGraph}] A logical. If TRUE, than bpMat is passed in by the user
as a graphNEL.
\item[\code{pLevels}] A numeric vector. It gives the levels to calculate the
countours of the function in p in the (n-in, n-out)-plane
\item[\code{prob}] A numeric. The bias of the coin used in the function
pbinom call.
\end{ldescription}
\end{Arguments}
\begin{Value}
A list:

\begin{ldescription}
\item[\code{deg}] A 3xn matrix. The rows are indexed by each protein. Column
one gives the number of reciprocated edges; column two gives the
number of unreciprocated out edges; colunm three gives the number of
unreciprocated in-edges
\item[\code{p}] The p-value for each protein with experimental in and out degrees
\item[\code{countours}] The countours as a function of p
\end{ldescription}
\end{Value}
\begin{Author}\relax
W Huber
\end{Author}
\begin{Examples}
\begin{ExampleCode}
library(ppiData)
assessSymmetry(Ito2001BPGraph, bpGraph=TRUE)
\end{ExampleCode}
\end{Examples}

