- recipe r-genekitr
Provides features for searching, converting, analyzing, plotting, and exporting data effortlessly by inputting feature IDs. Enables easy retrieval of feature information, conversion of ID types, gene enrichment analysis, publication-level figures, group interaction plotting, and result export in one Excel file for seamless sharing and communication.
- Homepage:
- License:
GPL3 / GPL-3.0-only
- Recipe:
- package r-genekitr¶
- Versions:
1.2.8-0- Depends:
on bioconductor-clusterprofiler
on r-base
>=4.5,<4.6.0a0on r-dplyr
on r-europepmc
on r-fst
on r-geneset
on r-ggplot2
on r-ggraph
on r-ggvenn
on r-igraph
on r-magrittr
on r-openxlsx
on r-rlang
on r-stringi
on r-stringr
on r-tidyr
- 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-genekitr
to add into an existing workspace instead, run:
pixi add r-genekitr
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-genekitr
Alternatively, to install into a new environment, run:
conda create -n envname r-genekitr
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-genekitr:<tag>
(see r-genekitr/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-genekitr/README.html)
