Rtreemix (version 1.34.0)

likelihoods-methods: Method for predicting the likelihoods of a set of samples with respect to a mutagenetic trees mixture model

Description

This function predicts the (log, weighted) likelihoods of the samples in a given dataset according to a given mutagenetic trees mixture model. The dataset and the model have to be specified.

Usage

"likelihoods"(model, data)

Arguments

model

An RtreemixModel object specifying the probabilistic framework in which the likelihoods of the genetic patterns are computed.

data

An RtreemixData object giving the samples for which the likelihoods are to be calculated.

Value

This method returns an RtreemixStats object that containes the weghted- and log-likelihoods of the samples in the given dataset with respect to the given mutagenetic trees mixture model.

References

Learning multiple evolutionary pathways from cross-sectional data, N. Beerenwinkel et al.

See Also

RtreemixData-class, RtreemixModel-class, fit-methods, distribution-methods

Examples

## Create an RtreemixData object from a randomly generated RtreemixModel object.
rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
data <- sim(model = rand.mod, no.draws = 300)
show(data)

## Compute the likelihoods of the samples in data with respect to the model rand.mod
mod.stat <- likelihoods(model = rand.mod, data = data)
show(mod.stat)