perturbTrajectories {BoolNet} | R Documentation |

## Perturb the state trajectories and calculate robustness measures

### Description

Perturbs the state trajectories of a network and assesses the robustness by comparing the successor states or the attractors of a set of initial states and a set of perturbed copies of these initial states.

### Usage

```
perturbTrajectories(network,
measure = c("hamming", "sensitivity", "attractor"),
numSamples = 1000,
flipBits = 1,
updateType = c("synchronous", "asynchronous", "probabilistic"),
gene,
...)
```

### Arguments

`network` |
A network structure of class |

`measure` |
Defines the way the robustness is measured (see Details). |

`numSamples` |
The number of randomly generated pairs of initial states and perturbed copies. Defaults to 1000. |

`flipBits` |
The number of bits that are flipped to generate a perturbed copy of an initial state. Defaults to 1. |

`updateType` |
If |

`gene` |
If |

`...` |
Further parameters to |

### Details

The function generates a set of `numSamples`

initial states and then applies `flipBits`

random bit flips to each initial state to generate a perturbed copy of each initial state. For each pair of initial state and perturbed state, a robustness statistic is calculated depending `measure`

:

If `measure="hamming"`

, the normalized Hamming distances between the successor states of each initial state and the corresponding perturbed state are calculated.

If `measure="sensitivity"`

, the average sensitivity of a specific transition function (specified in the `gene`

parameter) is approximated: The statistic is a logical vector that is `TRUE`

if `gene`

differs in the successor states of each initial state and the corresponding perturbed state.

If `measure="attractor"`

, the attractors of all initial states and all perturbed states are identified. The statistic is a logical vector specifying whether the attractors are identical in each pair of initial state and perturbed initial state.

### Value

A list with the following items:

`stat` |
A vector of size |

`value` |
The summarized statistic (i.e. the mean value) over all state pairs. |

### References

I. Shmulevich and S. A. Kauffman (2004), Activities and Sensitivities in Boolean Network Models. Physical Review Letters 93(4):048701.

### See Also

`testNetworkProperties`

, `perturbNetwork`

### Examples

```
## Not run:
data(cellcycle)
# calculate average normalized Hamming distance of successor states
hamming <- perturbTrajectories(cellcycle, measure="hamming", numSamples=100)
print(hamming$value)
# calculate average sensitivity of transition function for gene "Cdh1"
sensitivity <- perturbTrajectories(cellcycle, measure="sensitivity", numSamples=100, gene="Cdh1")
print(sensitivity$value)
# calculate percentage of equal attractors for state pairs
attrEqual <- perturbTrajectories(cellcycle, measure="attractor", numSamples=100)
print(attrEqual$value)
## End(Not run)
```

*BoolNet*version 2.1.9 Index]