scPhyloX.simulation.tumor
Classes
Cell division/differentiation type |
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Cell class |
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Gillespie simulation |
Functions
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Module Contents
- class Reaction(rate=0.0, num_lefts=None, num_rights=None, index=None)
Cell division/differentiation type
- Args:
- rate:
reaction rate function
- num_lefts:
Cell numbers before reaction
- num_right:
Cell numbers after reaction
- index:
Reaction index
- rate = 0.0
- num_lefts
- num_rights
- num_diff
- index = None
- combine(n, s)
- propensity(n, t)
- class Cell(seq=None, gen=None, cellid=None, celltype=None, is_alive=True, lseq=10000, init=False)
Cell class
- Args:
- seq:
DNA sequence
- gen:
Cell generation
- cellid:
Cell id
- celltype:
Cell type, neutral/advantageous cell
- is_alive:
Is cell alive or died
- lseq:
Length of DNA seq
- init:
if init, cell will generate DNA seq with given length lseq automatically
- seq = None
- gen = None
- celltype = None
- lseq = 10000
- cellid = None
- is_alive = True
- initialize(lseq)
- class System(num_elements, inits=None, nbase=1500, mut_rate=1, max_t=35, start_t=0)
Gillespie simulation
- Args:
- num_elements:
Cell type number
- inits:
Initial cell number
- nbase:
length of cell DNA seq
- mut_rate:
mutation rate of DNA seq, follows Poisson distribution
- max_t:
maximum simulation time
- start_t:
Mutate start time
- num_elements
- reactions = []
- start_t = 0
- max_t = 35
- mut_rate = 1
- global_id
- Neutral
- Advantageous
- mut_num = 0
- cell_num
- mut_time = []
- mut_num_NC
- mut_num_AC
- log_cells
- lineage_info
- add_reaction(rate=0.0, num_lefts=None, num_rights=None, index=None)
Add reactions to simulation
- Args:
- rate:
reaction rate function
- num_lefts:
Cell numbers before reaction
- num_right:
Cell numbers after reaction
- index:
Reaction index
- mutate(cell, mutrate)
simulation DNA mutation
- Args:
- cell:
cell
- mutrate:
mutation rate
- Return:
- cell:
cell with mutated DNA seq
- ncrenewal()
neutral cell -> 2 neutral cells
- acrenewal()
advantageous cell -> 2 advantageous cells
- advmut()
neutral cell -> advantageous cell
- ncdeath()
neutral cell -> death
- acdeath()
advantageous cell -> death
- evolute(steps)
- simulation(x0, max_t, mut_rate, r, a, s, u)