Expand description
Simulate the dynamics of a stem cell population undergoing proliferation and differentiation according to a Moran process (fixed population size).
Whenever a cell divides, it acquires a Poisson number of passenger mutations, which do not give any proliferative advantage.
On top of that, cells can also acquire one proliferative advantageous
mutation upon division.
In this case, the cell creates a new clone, which has a birth-rate of
lambda_i = lambda_0 ( 1 + s_i), where lambda_0 is the birth-rate of the
wild-type, the clone without any proliferative mutations.
Modules§
- genotype
- The neutral mutations representing the genotype of the stem cells.
- process
- The events to simulate for this Markov process.
- proliferation
- The proliferation of cells with the simulation of neutral and fit mutations.
- stemcell
- The agents whose state defines the system simulated by the process.
- subclone
- The classes defining the proliferative advantage.
Structs§
Enums§
- Probs
- Probabilities used in the simulations.
Constants§
- MAX_
SUBCLONES - Maximal number of fit clones that can arise during the simulation.
- TIME_
AT_ BIRTH - The time at birth measured in years used for background mutations in the exponential growing phase.
Functions§
- write2file
- Write vector of float into new file with a precision of 6 decimals. Write NAN if the slice to write to file is empty.