ML.MSBD-package: Maximum Likelihood Inference on Multi-State Trees

In ML.MSBD: Maximum Likelihood Inference on Multi-State Trees

Description

Inference of a multi-states birth-death model from a phylogeny, comprising a number of states N, birth and death rates for each state and on which edges each state appears. Inference is done using a hybrid approach: states are progressively added in a greedy approach. For a fixed number of states N the best model is selected via maximum likelihood. Reference: J. Barido-Sottani, T. G. Vaughan and T. Stadler (2018) <doi:10.1098/rsif.2018.0512>.

Details

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Author(s)

Joelle Barido-Sottani [aut, cre]

Maintainer: Joelle Barido-Sottani <[e-mail]>

References

J. Barido-Sottani and T. Stadler. Accurate detection of HIV transmission clusters from phylogenetic trees using a multi-state birth-death model, BioRXiv 2017. (https://www.biorxiv.org/content/early/2017/11/10/215491)

See Also

ape

Examples

# Simulate a random phylogeny
set.seed(25)
tree <- ape::rtree(10)

# Calculate the log likelihood under a multi-states model with 2 states 
# and full extant & extinct sampling
likelihood_MSBD(tree, shifts = matrix(c(2,1.8,2), nrow = 1), 
  gamma = 0.05, lambdas = c(10, 6), mus = c(1, 0.5), sigma = 1)

# Infer the most likely multi-states birth-death model with full extant & extinct sampling
## Not run: ML_MSBD(tree, initial_values = c(0.1, 10, 1), sigma = 1, time_mode = "mid") 
# Infer the most likely multi-states birth-death model with exponential decay 
# and full extant & extinct sampling
## Not run: ML_MSBD(tree, initial_values = c(0.1, 10, 0.5, 1), sigma = 1, 
  stepsize = 0.1, time_mode = "mid")
## End(Not run)

ML.MSBD documentation built on April 17, 2021, 1:07 a.m.