- recipe r-saccharis
A rendering package for creating phylogenetic trees from SACCHARIS .json and .tree files, in the R statistical computing language.
- Homepage:
- License:
GPL / GPL-3.0-or-later
- Recipe:
This package will use metadata .json and .tree files output from SACCHARIS v2 to generate annotated phylogenetic tree PDF files. Highly customizable, as the formatting of the tree is done using ggplot2. Of course plotting functions can easily be manipulated as desired. To use, call A_load_data() and B_plots_all() and follow prompts. Our default plots used for publication are domain_ECno_numeric.
- package r-saccharis¶
- Versions:
1.0.5-0- Depends:
on bioconductor-ggtree
on r-ape
on r-base
>=4.3,<4.4.0a0on r-dplyr
on r-ggnewscale
on r-ggplot2
on r-jsonlite
on r-knitr
on r-magrittr
on r-rcolorbrewer
on r-stringr
- Additional platforms:
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install r-saccharis
to add into an existing workspace instead, run:
pixi add r-saccharis
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install r-saccharis
Alternatively, to install into a new environment, run:
conda create -n envname r-saccharis
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/r-saccharis:<tag>
(see r-saccharis/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/r-saccharis/README.html)
