phylo_generate_uncertainty: Generate uncertainty in branch lengths using a lognormal.

In datelife: Scientific Data on Time of Lineage Divergence for Your Taxa

Generate uncertainty in branch lengths using a lognormal.

Description

Generate uncertainty in branch lengths using a lognormal.

Usage

phylo_generate_uncertainty(
  phy,
  size = 100,
  uncertainty_method = "other",
  age_distribution = "uniform",
  age_sd = NULL,
  age_var = 0.1,
  age_scale = 0,
  alpha = 0.025,
  rescale = TRUE
)

Arguments

phy	A phylo object.
size	A numeric vector indicating the number of samples to be generated.
uncertainty_method	A character vector specifying the method to generate uncertainty. mrbayes is default.
age_distribution	A character string specifying the type of calibration. Only "fixed" and "uniform" are implemented for now. fixed The age given in ncalibration will be used as fixed age. lognormal The age given in ncalibration will be used as mean age. The standard deviation can be provided. # still need to add this option. By default, a 95 CI sd is used. uniform The age given in ncalibration will be used as mean age. Where min_age = 0.9 * mean age, and max_age = 1.1 * mean age.
age_sd	The standard deviation around the age to use for generating the uncertainty. If not a numeric value, var will be used to calculate it.
age_var	The variance to calculate age_sd and generate uncertainty.
age_scale	How to scale sd by the depth of the node. If 0, same sd for all. If not, older nodes have more uncertainty
alpha	The significance level on uncertainty to generate. By default 0.025
rescale	Boolean. If true, observed age will be rescaled each round.

Details

If you want to change the size of sampled trees you do not need to run mrbayes again. Just use sample_trees("mrbayes_trees_file_directory", size = new_size) and you will get a multiPhylo object with a new tree sample.

Value

A phylo or multiPhylo object with the same topology as phy but different branch lengths

Examples

## Not run: 
# Generate uncertainty over feline species SDM chronogram.
# Load the data:

data(felid_sdm)

# By default, generates a sample of 100 trees with var = 0.1:

unc <- phylo_generate_uncertainty(felid_sdm$phy)
length(unc)

# Make an LTT plot:

max_age <- max(sapply(unc, ape::branching.times))
ape::ltt.plot(phy = unc[[1]], xlim = c(-max_age, 0), col = "#cce5ff50")
for (i in 2:100) {
  ape::ltt.lines(phy = unc[[i]], col = "#cce5ff50")
}
ape::ltt.lines(felid_sdm$phy, col = "red")
title(c("fake uncertainty", "in Felidae SDM chronogram"))

## End(Not run) # end dontrun

datelife documentation built on July 10, 2023, 2:02 a.m.