scPhyloX.estimation.mutation_rate
Classes
Estimation of generations with given LR distance distribution and mutaion rate |
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Probability distribution of LP distance |
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Functions
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Mutation rate estimation using DE |
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Mutation rate estimation using DE-MCMC |
Module Contents
- class GenerationEst(lr_dist, mu: float, gennum=None)
Estimation of generations with given LR distance distribution and mutaion rate
- Args:
- lr_dist:
distribution of LR distance
- mu:
mutation rate
- lr_dist
- mu
- u1
- s1
- generation = None
- generation_map(mn: float)
MAP estimation of given lr-dist
- Args:
- mn:
lr-distance
- Returns:
- float:
Estimated generation
- estimate(cell_number=None)
Generation estimation of all given lr distance in self.lr_dist
- class BranchLength(mu, delta)
Probability distribution of LP distance
- Args:
- mu:
mutation rate
- delta:
Probability of branching division
- mu
- delta
- prob(x)
Probability density function of lp-dist
- Args:
- x:
lp-dist
- Return:
- float:
probability density
- likelihood(data)
Likelihood of lp-dist
- Args:
- data:
Observed lp dist
- Return:
- float:
Sum of log-likelihood of given lp dist
- mutation_rate_de(data, n_iter: int = 100, bootstrape: int = 0)
Mutation rate estimation using DE
- Args:
- data:
lp-dist
- n_iter:
Iterations of de estimation
- bootstrape:
Weather using bootstrape to accuratly estimate mutation rate, 0 to turn off.
- Return:
- tuple:
(accepted parameters, loss, de-estimator)
- class LogLike(loglike, data)
Bases:
pytensor.tensor.Op- itypes
- otypes
- likelihood
- data
- perform(node, inputs, outputs)
- my_loglike(theta, data)
- mutation_rate_mcmc(data, draw=1000, tune=1000, chain=4, mu0=2, sigma=0.2)
Mutation rate estimation using DE-MCMC
- Args:
- data:
Observed lp-dist
- draw:
Number of smaples to draw
- tune:
Number of iterations to tune
- chain:
number of chains to sample
- mu0:
mean of prior distribution of mutation rate
- sigma:
variation of prior distribution of mutation rate