Package Recipe 'bioconductor-cellid'

recipe bioconductor-cellid

Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/CelliD.html
License:: GPL-3 + file LICENSE
Recipe:: /bioconductor-cellid/meta.yaml

CelliD is a clustering-free multivariate statistical method for the robust extraction of per-cell gene signatures from single-cell RNA-seq. CelliD allows unbiased cell identity recognition across different donors, tissues-of-origin, model organisms and single-cell omics protocols. The package can also be used to explore functional pathways enrichment in single cell data.

package bioconductor-cellid¶

Versions:

1.18.0-0, 1.14.0-0, 1.10.1-0, 1.8.1-0, 1.6.0-1, 1.6.0-0, 1.2.1-1, 1.2.1-0, 1.2.0-0,

1.18.0-0, 1.14.0-0, 1.10.1-0, 1.8.1-0, 1.6.0-1, 1.6.0-0, 1.2.1-1, 1.2.1-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-biocparallel >=1.44.0,<1.45.0a0
on bioconductor-fgsea >=1.36.0,<1.37.0
on bioconductor-fgsea >=1.36.2,<1.37.0a0
on bioconductor-scater >=1.38.0,<1.39.0
on bioconductor-scater >=1.38.0,<1.39.0a0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-data.table
on r-fastmatch
on r-ggplot2
on r-glue
on r-irlba
on r-matrix
on r-matrixstats
on r-pbapply
on r-rcpp
on r-rcpparmadillo
on r-reticulate
on r-rtsne
on r-seurat >=4.0.1
on r-stringr
on r-tictoc
on r-umap

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 bioconductor-cellid

to add into an existing workspace instead, run:

pixi add bioconductor-cellid

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 bioconductor-cellid

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-cellid

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/bioconductor-cellid:<tag>

(see bioconductor-cellid/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:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-cellid/README.html)