View source: R/simulate.uncor.lnorm.R
simulate.uncor.lnorm | R Documentation |
Simulate the rate of evolution along a phylogenetic tree using the lognormal model described in Drummond et al. (2006)
simulate.uncor.lnorm(tree, params = list(mean.log = -5, sd.log = 0.5))
tree |
A phylogenetic tree of class 'phylo'. The branch lengths should be in units of time (chronogram) |
params |
parameters for the uncorrelated rates function. This should be a list with two items: |
mean.log |
This is the mean rate of the lognormal distribution. It should be in log scale |
sd.log |
The standard deviation of the lognormal distribution |
None
An object of class 'ratesim'. This is a list with two items:
phylogram |
The phylogenetic tree with branch lengths in units of substitutions (phylogram) |
tree.data.matrix |
This is a matrix with the number of substitutions, rates, and times along every branch in the tree. See get.tree.data.matrix for more details |
None
Sebastian Duchene. See the reference for the description of the model.
Drummond, A.J., et al. "Relaxed phylogenetics and dating with confidence." PLoS biology 4.5 (2006): e88.
simulte.uncor.exp
set.seed(1234525)
myTree <- rcoal(50)
rateTree <- simulate.uncor.lnorm(tree = myTree, params = list(mean.log = -5, sd.log = 0.5))
plot(rateTree, col.lineages = rainbow(50))
#See the histogram of the branch-wise rates
hist(rateTree$tree.data.matrix[, 5])
## The function is currently defined as
function (tree, params = list(mean.log = -5, sd.log = 0.5))
{
mean.log <- params$mean.log
sd.log <- params$sd.log
data.matrix <- get.tree.data.matrix(tree)
branch.rates <- rlnorm(n = length(tree$edge.length), meanlog = mean.log,
sdlog = sd.log)
data.matrix[, 5] <- branch.rates
data.matrix[, 6] <- data.matrix[, 5] * data.matrix[, 7]
tree$edge.length <- data.matrix[, 6]
res <- list(tree, data.matrix)
names(res) <- c("phylogram", "tree.data.matrix")
class(res) <- "ratesim"
return(res)
}
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