Infer growth rates for each clone and subclone.

Usage

fit_growth_rates(
  x,
  steps = 500,
  warmup_steps = 500,
  highlight = c(),
  timepoints_to_int = c(),
  timepoints = get_timepoints(x),
  growth_model = "exp.log",
  which = "pop",
  force = T,
  tree_score = 1,
  py_pkg = NULL,
  mutations = F
)

Arguments

x: a mvnmm object.
steps: maximum number of steps for inference.
highlight: set of clusters to run the inference for. If not specified, it will be run on all the clusters.
timepoints_to_int: if the provided timepoints are not integers nor a timepoints-to-int list is stored in x, a list mapping their values to integers is required.
growth_model: string specifying the type of growth model to use, between exp and log corresponding to exponential and logistic models, respectively.
force: if the model has already been fitted, setting force to FALSE will keep the computed rates. Setting force to TRUE will fit the model again for the specified clusters.

Value

A mvnmm object with the additional tibble growth.rates containing the estimated population genetics parameters.