- recipe r-monocle3
An analysis toolkit for single-cell RNA-seq.
- Homepage:
- Documentation:
https://cole-trapnell-lab.github.io/monocle3/docs/introduction
- Developer docs:
- License:
MIT / MIT
- Recipe:
- Links:
biotools: monocle, doi: 10.1038/nbt.2859, doi: 10.1038/nmeth.4402, doi: 10.1038/s41586-019-0969-x
- package r-monocle3¶
-
- Versions:
1.4.26-0,1.3.1-1,1.3.1-0,1.0.0-5,1.0.0-4,1.0.0-3,1.0.0-2,1.0.0-1,1.0.0-0,1.4.26-0,1.3.1-1,1.3.1-0,1.0.0-5,1.0.0-4,1.0.0-3,1.0.0-2,1.0.0-1,1.0.0-0,0.2.3-1,0.2.3-0,0.2.2-0,0.2.1-1,0.2.1-0,0.2.0-1,0.2.0-0,0.1.3-0- Depends:
on bioconductor-batchelor
>=1.22.0,<1.23.0a0on bioconductor-biobase
>=2.66.0,<2.67.0a0on bioconductor-biocgenerics
>=0.28on bioconductor-biocgenerics
>=0.52.0,<0.53.0a0on bioconductor-delayedarray
>=0.32.0,<0.33.0a0on bioconductor-delayedarray
>=0.8on bioconductor-delayedmatrixstats
>=1.28.0,<1.29.0a0on bioconductor-delayedmatrixstats
>=1.4on bioconductor-hdf5array
>=1.34.0,<1.35.0a0on bioconductor-limma
>=3.38.3on bioconductor-limma
>=3.62.1,<3.63.0a0on bioconductor-s4vectors
>=0.44.0,<0.45.0a0on bioconductor-singlecellexperiment
>=1.28.0,<1.29.0a0on bioconductor-summarizedexperiment
>=1.11.5on bioconductor-summarizedexperiment
>=1.36.0,<1.37.0a0on libgcc
>=13on libstdcxx
>=13on r-assertthat
>=0.2.1on r-base
>=4.4,<4.5.0a0on r-bpcells
>=0.3.0,<0.4.0a0on r-dplyr
>=0.8.0.1on r-ggdist
on r-ggforce
on r-ggplot2
>=3.1.1on r-ggrastr
on r-ggrepel
>=0.8.1on r-grr
on r-htmlwidgets
>=1.3on r-igraph
>=1.2.4on r-irlba
>=2.3.3on r-knitr
on r-leidenbase
on r-lme4
on r-lmtest
>=0.9_36on r-mass
>=7.3_51.4on r-matrix
>=1.2_17on r-matrix.utils
on r-pbapply
>=1.4on r-pbmcapply
>=1.4.1on r-pheatmap
on r-plotly
>=4.9on r-plyr
>=1.8.4on r-proxy
>=0.4_23on r-pryr
>=0.1.4on r-pscl
>=1.5.2on r-purrr
>=0.3.2on r-rann
>=2.6.1on r-rcpp
>=1.0.1on r-rcpphnsw
on r-rcppparallel
on r-reshape2
>=1.4.3on r-reticulate
>=1.11.1on r-rhpcblasctl
on r-rmarkdown
on r-rsample
>=0.0.5on r-rtsne
>=0.15on r-shiny
on r-slam
>=0.1_45on r-spdep
>=1.1_2on r-speedglm
>=0.3_2on r-spelling
on r-stringr
>=1.4on r-terra
on r-testthat
>=2.1on r-tibble
>=2.1.1on r-tidyr
>=0.8.3on r-uwot
>=0.1.3on r-viridis
>=0.5.1
- 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-monocle3
to add into an existing workspace instead, run:
pixi add r-monocle3
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-monocle3
Alternatively, to install into a new environment, run:
conda create -n envname r-monocle3
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-monocle3:<tag>
(see r-monocle3/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-monocle3/README.html)