getTransitionTable: Retrieve the transition table of a network

In BoolNet: Construction, Simulation and Analysis of Boolean Networks

Retrieve the transition table of a network

Description

Retrieves the transition table and additional attractor information of a network.

Usage

getTransitionTable(attractorInfo)

Arguments

attractorInfo

An object of class AttractorInfo, as returned by getAttractors, or of class SymbolicSimulation, as returned by simulateSymbolicModel. As the transition table information in this structure is required, getAttractors must be called in synchronous mode and with returnTable set to TRUE. Similarly, simulateSymbolicModel must be called with returnGraph=TRUE.

Details

Depending on the configuration of the call to getAttractors or simulateSymbolicModel that returned attractorInfo, this function either returns the complete transition table (for exhaustive synchronous search) or the part of the transition table calculated in a heuristic synchronous search. Asynchronous search is not supported, as no transition table is calculated.

Value

Returns a generic dataframe of the class TransitionTable. For n genes, the first n columns code for the original state (in this case, the state parameter), i.e. each column represents the value of one gene. The next n columns code for the successive state after a transition. The column attractorAssignment indicates the attractor to the state is assigned. If this information is available, the column stepsToAttractor indicates how many transitions are needed from the original state to the attractor. The table has a row for each possible input state. The TransitionTable class supports pretty printing using the print method.

See Also

getStateSummary, getBasinOfAttraction, getAttractors, simulateSymbolicModel

Examples

## Not run: 
# load example data
data(cellcycle)

# get attractors
attractors <- getAttractors(cellcycle)

# print the transition table
print(getTransitionTable(attractors))

## End(Not run)

BoolNet documentation built on Oct. 2, 2023, 5:08 p.m.