R: Visualize the transitions in a probabilistic Boolean network

plotPBNTransitions {BoolNet} | R Documentation

## Visualize the transitions in a probabilistic Boolean network

### Description

Visualizes the state transitions and their probabilities in a probabilistic Boolean network. This takes the transition table information calculated by the `markovSimulation` method. Only transitions with non-zero probability are included in the plot. The function requires the igraph package.

### Usage

    plotPBNTransitions(markovSimulation,
                       stateSubset,
                       drawProbabilities = TRUE,
                       drawStateLabels = TRUE,
                       layout = layout.fruchterman.reingold,
                       plotIt = TRUE, ...)

### Arguments

`markovSimulation` | An object of class `MarkovSimulation`, as returned by `markovSimulation`. As the transition table information in this structure is required, `markovSimulation` must be called with `returnTable` set to TRUE.
`stateSubset` | An optional list of states, where each element of the list must be a vector with a 0/1 entry for each gene. If this argument is supplied, the graph only contains the specified states and transitions between these states.
`drawProbabilities` | If set to true, the edges of the graph are annotated with the probabilities of the corresponding transitions. Default is TRUE.
`drawStateLabels` | If set to true, the vertices of the graph are annotated with the gene values of the corresponding states. Defaults to TRUE.
`layout` | A layouting function that determines the placement of the nodes in the graph. Please refer to the `layout` manual entry in the igraph package for further details. By default, the Fruchterman-Reingold algorithm is used.
`plotIt` | If this is true, a plot is generated. Otherwise, only an object of class `igraph` is returned, but no plot is drawn.
`...` | Further graphical parameters to be passed to `plot.igraph`.

### Details

This function uses the `plot.igraph` function from the igraph package. The plots are customizeable using the `...` argument. For details on possible parameters, please refer to `igraph.plotting`.

### Value

Returns an invisible object of class `igraph` containing the wiring graph.

### See Also

`markovSimulation`

### Examples

    # load example network
    data(examplePBN)

    # perform a Markov chain simulation
    sim <- markovSimulation(examplePBN)

    # plot the transitions and their probabilities
    plotPBNTransitions(sim)

[Package BoolNet version 2.1.4 Index]