Dendrograms for Evolutionary Analysis.
phylogram
The phylogram R package is a tool for for developing phylogenetic trees as deeply-nested lists known as "dendrogram" objects. It provides functions for conversion between "dendrogram" and "phylo" class objects, as well as several tools for command-line tree manipulation and import/export via Newick parenthetic text. This improves accessibility to the comprehensive range of object-specific analytical and tree-visualization functions found across a wide array of bioinformatic R packages.
Installation
To download phylogram from CRAN and load the package, run
install.packages("phylogram")
library("phylogram")
To download the latest development version from GitHub, run:
devtools::install_github("ropensci/phylogram", build_vignettes = TRUE)
library("phylogram")
Example: reading and writing trees
Consider the simple example of a tree with three members named "A", "B" and "C", where "B" and "C" are more closely related to eachother than they are to "A". An unweighted Newick string for this tree would be "(A,(B,C));". This text can be imported as a dendrogram object using the read.dendrogram
function as follows:
library("phylogram")
newick <- "(A,(B,C));"
x <- read.dendrogram(text = newick)
plot(x)
The following command writes the object back to the console in Newick format without edge weights:
write.dendrogram(x, edges = FALSE)
The syntax is similar when reading and writing text files, except that the text
argument is replaced by file
and a valid file path is passed to the function.
To convert the dendrogram to a "phylo" object, run
y <- as.phylo(x)
These and more examples are available in the package vignette. To view the vignette, run vignette("phylogram-vignette")
or access it directly from CRAN.
Help
An overview of the package with links to the function documentation can be found by running
?phylogram
If you experience a problem using this package please either raise it as an issue on GitHub or post it on the phylogramgoogle group.
Acknowledgements
This software was developed at Victoria University of Wellington with funding from a Rutherford Foundation Postdoctoral Research Fellowship award from the Royal Society of New Zealand.