- recipe r-ramclustr
A feature clustering algorithm for non-targeted mass spectrometric metabolomics data. This method is compatible with gas and liquid chromatography coupled mass spectrometry, including indiscriminant tandem mass spectrometry data <DOI: 10.1021/ac501530d>.
- Homepage:
- License:
GPL2 / GPL-2.0-or-later
- Recipe:
- package r-ramclustr¶
- Versions:
1.3.1-1,1.3.1-0,1.3.0-1,1.3.0-0,1.2.4-1,1.2.4-0,1.2.3-0,1.2.2-0,1.2.1-1,1.3.1-1,1.3.1-0,1.3.0-1,1.3.0-0,1.2.4-1,1.2.4-0,1.2.3-0,1.2.2-0,1.2.1-1,1.2.1-0,1.0.9-1,1.0.9-0- Depends:
on bioconductor-msnbase
on bioconductor-pcamethods
on r-base
>=4.3,<4.4.0a0on r-biocmanager
on r-dynamictreecut
on r-e1071
on r-fastcluster
on r-ggplot2
on r-gplots
on r-httr
on r-interpretmsspectrum
on r-jsonlite
on r-rcurl
on r-readxl
on r-stringi
on r-stringr
on r-webchem
on r-xml2
- 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-ramclustr
to add into an existing workspace instead, run:
pixi add r-ramclustr
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-ramclustr
Alternatively, to install into a new environment, run:
conda create -n envname r-ramclustr
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-ramclustr:<tag>
(see r-ramclustr/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-ramclustr/README.html)
