\name{simOGraph}
 \alias{simOGraph}
 \title{
   Simulate oncogenetic/CBN/XMPN DAGs.
 }
 \description{
   Simulate DAGs that represent restrictions in the accumulation of mutations.
 }
 \usage{

 simOGraph(n, h = ifelse(n >= 4, 4, n), conjunction = TRUE, nparents = 3,
 multilevelParent = TRUE, removeDirectIndirect = TRUE, rootName = "Root",
 geneNames = seq.int(n), out = c("adjmat", "rT"),
 s = 0.1, sh = -0.1, typeDep = "AND")
 

 }
 
 \arguments{
   \item{n}{
     Number of nodes, or edges, in the graph. Like the number of genes.
 }
   \item{h}{
     Approximate height of the graph. See details.
   }
   \item{conjunction}{
     If TRUE, conjunctions (i.e., multiple parents for a node) are allowed.
 }
 \item{nparents}{
   Maximum number of parents of a node, when \code{conjunction} is TRUE.
 }
 \item{multilevelParent}{
   Can a node have parents at different heights (i.e., parents that are
   at different distance from the root node)?
 }
   \item{removeDirectIndirect}{
     Ensure that no two nodes are connected both directly (i.e., with an
   edge between them) and indirectly, through intermediate nodes. If

   TRUE, we return the transitive reduction of the DAG.
   %% the final DAG returned is the transitive reduction of thethe direct
   %% connections are removed from the graph starting from the bottom.

 }
 \item{rootName}{
   The name you want to give the "Root" node.

 }

 \item{geneNames}{
   The names you want to give the the non-root nodes.

 }

 
 
 \item{out}{Whether the ouptut should be an adjacency matrix  or a
   "restriction table", as used in   \code{\link{allFitnessEffects}}.}
 
 \item{s}{If using as output a restriction, the default value for s. See
 \code{\link{allFitnessEffects}}.}
 
 \item{sh}{If using as output a restriction, the default value for
 sh. See \code{\link{allFitnessEffects}}}
 
 \item{typeDep}{If using as output a restriction, the default value for
 "typeDep". See \code{\link{allFitnessEffects}}}
 

 }

 \details{
   This is a simple, heuristic procedure for generating graphs of
   restrictions that seem compatible with published trees in the
   oncogenetic literature.
 
   The basic procedure is as follows: nodes (argument \code{n}) are split
   into approximately equally sized \code{h} groups, and then each node
   from a level is connected to nodes chosen randomly from nodes of the
   remaing superior (i.e., closer to the Root) levels. The number of
   edges comes from a uniform distribution between 1 and \code{nparents}.
 
   The actual depth of the graph can be smaller than \code{h} because
   nodes from a level might be connected to superior levels skipping
   intermediate ones.
 
   See the vignette for further discussion about arguments. 
 
 }
 \value{

   An adjacency matrix for a directed graph or a data frame to be used as
   input, as "restriction table" in  \code{\link{allFitnessEffects}}.
 

 }
 \author{Ramon Diaz-Uriarte}
 
 \examples{
 (a1 <- simOGraph(10))
 library(graph) ## for simple plotting
 plot(as(a1, "graphNEL"))

 
 simOGraph(3, geneNames = LETTERS[1:3])

 }
 
 \keyword{ graphs }
 \keyword{ datagen }