First, we constructed the “driver” model, which contains only driver genes, aiming to study the two Darwinian evolution modes: linear and branching evolution. We employed an agent-based model, where each agent corresponds to each cell in a tumor. The simulation started from one cell without mutations. In a unit time, a cell divides into two daughter cells with a probability *g*. This model assumes that an immortalized cell, which just divides without dying. In each cell division, each of the two daughter cells acquires *k*_{d} driver mutations. Here, *k*_{d} is sampled from a Poisson distribution with the parameter *m*_{d}/2, i.e., *k*_{d} ∼ Pois(*m*_{d}/2), which means that one cell division generates *m*_{d} mutations on average. We assumed that driver mutations acquired by different division events occur at different genomic positions and each cell can accumulate *N*_{d} mutations at maximum. In this study, we assumed that all mutations are driver mutations, which increase the cell division rate. When the cell acquires mutations, the cell division rate increases *f* fold per mutation; that is, when a cell has *n*_{d} (=∑*k*_{d}) mutations in total, the cell division probability *g* is defined as *g* = *g*_{0}*f*^{nd}, where *g*_{0} is a base division probability. In each time step, every cell is subject to a cell division trial, which is repeated until population size *p* reaches *P* or the number of time steps *t* reaches *T*.

Information of variables and parameters are listed in Tables 1 and 2.
In MASSIVE, we converted *m*_{d}, *f* and *P* to log scale, i.e., *m*_{d}' = log_{10} *m*_{d}',
*f*' = log_{10} *f* and *P*' = log_{10} *P*, and then tested every combination of
*m*_{d}' ∈ {-4, -3.5, -3,...,-1},
*m*_{d} ∈ {1, 2, 3, 4},
*f*' ∈ {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 |

g |
cell division 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} |

f |
increase of the cell division probability per driver mutation | {10^{0.1}, 10^{0.15}, 10^{0.2},...,10^{1.0}} |

g_{0} |
base cell division probability | 10^{-4} |

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

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