\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 }