We then modified the driver model to create the “driver-d” model, where each cell divides with a constant probability g0 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 kd ∼ Pois(md/2) driver mutations and can accumulate Nd driver mutations at maximum. Each driver mutation decreases the cell death probability by e fold: d = d0e−nd, where d0 is a cell base death probability and nd 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 md, e and P to log scale, i.e., md' = log10 md', e' = log10 e and P' = log10 P, and then tested every combination of md' ∈ {-4, -3.5, -3,...,-1}, md ∈ {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 |
|---|---|
| kd | number of driver mutations obtained in a cell division |
| nd | 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 |
|---|---|---|
| md | expected number of driver mutations generated per cell division | {10-4, 10-3.5, 10-3,...,10-1} |
| Nd | maximum number of driver mutations accumulated in a cell | {1, 2, 3, 4} |
| e | decrease of the cell death probability per driver mutation | {100.1, 100.15, 100.2,...,101.0} |
| g0 | base cell division probability | 10-2 |
| d0 | base cell death probability | 10-2 |
| P | maximum population size | {103, 104, 105, 106} |
| T | maximum number of time steps | 106 |