fitBiasedDrift: Fit crypt biased stem cell drift model.
In MorrisseyLab/CryptDriftR: Analyse crypt lineage tracing data

Description Usage Arguments Value Examples

fitBiasedDrift will run an mcmc algorithm to infer the parameters from the biased drift model.

fitBiasedDrift(
  x,
  time_interval,
  WT_params,
  max_iter = 80000,
  n_par_chains = 2,
  burn_in = 5000,
  thin = 50
)

`x`	Clone size counts. With a column per day and a row per size clone size.
`time_interval`	vector of time point values. Should have same number of elements as columns in x.
`WT_params`	List with wild type neutral drift parameters (N, lambda and tau).
`max_iter`	number of mcmc iterations to run.
`n_par_chains`	number of parallel chains (and cpus used) to run.
`burn_in`	mcmc burn in
`thin`	mcmc thining

Will retrun a list that can be used directly with the plotting functions. The list contains an mcmc matrix, the data and time vector used to fit, as well as the MAP estimate of the parameters.

time_points = c(4, 7, 10, 14, 21)
WT_params = list(lambda = 0.1, N  = 5, tau = 1)
x = simulateBiasedDriftData(WT_params$lambda, WT_params$N, WT_params$tau, Pr = 0.7, time_points, 8, 300)

fit_out = fitBiasedDrift(x, time_points, WT_params)
plotsConvergence_Biased(fit_out)
plotsBiasDrift_Fit(fit_out)