We then modified the driver model to create the “driver-d” model, where each cell divides with a constant probability *g*_{0} and dies with a probability *d*. Moreover, we assumed that cell death occurs only in the case of *p* > 1, to prevent the simulation from halting before clonal expansion. In each cell division, each of the two daughter cells acquires *k*_{d} ∼ Pois(*m*_{d}/2) driver mutations and can accumulate *N*_{d} driver mutations at maximum. Each driver mutation decreases the cell death probability by *e* fold: *d* = *d*_{0}*e*^{−nd}, where *d*_{0} is a cell base death probability and *n*_{d} is the number of driver mutations accumulated in a cell.

Information of variables and parameters are listed in Tables 1 and 2.
In MASSIVE, we converted *m*_{d}, *e* and *P* to log scale, i.e., *m*_{d}' = log_{10} *m*_{d}',
*e*' = log_{10} *e* and *P*' = log_{10} *P*, and then tested every combination of
*m*_{d}' ∈ {-4, -3.5, -3,...,-1},
*m*_{d} ∈ {1, 2, 3, 4},
*e*' ∈ {0.1, 0.15, 0.2,...,1.0} and
*P*' ∈ {3, 4, 5, 6}.
All results are explorable in the focused and comparative view modes of the MASSIVE viewer.

Table 1. a list of the variabes

symbol | description |
---|---|

k_{d} |
number of driver mutations obtained in a cell division |

n_{d} |
number of driver mutations accumulated in a cell |

p |
population size |

t |
number of time steps |

d |
cell death probability |

Table 1. a list of the parameters

symbol | description | value |
---|---|---|

m_{d} |
expected number of driver mutations generated per cell division | {10^{-4}, 10^{-3.5}, 10^{-3},...,10^{-1}} |

N_{d} |
maximum number of driver mutations accumulated in a cell | {1, 2, 3, 4} |

e |
decrease of the cell death probability per driver mutation | {10^{0.1}, 10^{0.15}, 10^{0.2},...,10^{1.0}} |

g_{0} |
base cell division probability | 10^{-2} |

d_{0} |
base cell death probability | 10^{-2} |

P |
maximum population size | {10^{3}, 10^{4}, 10^{5}, 10^{6}} |

T |
maximum number of time steps | 10^{6} |