Package Recipe 'bioconductor-scgraphverse'

recipe bioconductor-scgraphverse

scGraphVerse: A Gene Network Analysis Package

Homepage:: https://bioconductor.org/packages/3.22/bioc/html/scGraphVerse.html
License:: GPL-3 + file LICENSE
Recipe:: /bioconductor-scgraphverse/meta.yaml

A package for inferring, comparing, and visualizing gene networks from single-cell RNA sequencing data. It integrates multiple methods (GENIE3, GRNBoost2, ZILGM, PCzinb, and JRF) for robust network inference, supports consensus building across methods or datasets, and provides tools for evaluating regulatory structure and community similarity. GRNBoost2 requires Python package 'arboreto' which can be installed using init_py(install_missing = TRUE). This package includes adapted functions from ZILGM (Park et al., 2021), JRF (Petralia et al., 2015), and learn2count (Nguyen et al. 2023) packages with proper attribution under GPL-2 license.

package bioconductor-scgraphverse¶

Versions:

1.0.0-0

Depends:

on bioconductor-biocbaseutils >=1.12.0,<1.13.0
on bioconductor-biocbaseutils >=1.12.0,<1.13.0a0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-biocparallel >=1.44.0,<1.45.0a0
on bioconductor-genie3 >=1.32.0,<1.33.0
on bioconductor-genie3 >=1.32.0,<1.33.0a0
on bioconductor-graph >=1.88.0,<1.89.0
on bioconductor-graph >=1.88.1,<1.89.0a0
on bioconductor-multiassayexperiment >=1.36.0,<1.37.0
on bioconductor-multiassayexperiment >=1.36.1,<1.37.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
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 libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-distributions3
on r-doparallel
on r-dorng
on r-dplyr
on r-glmnet
on r-httr
on r-igraph
on r-jsonlite
on r-mass
on r-matrix
on r-mpath
on r-reticulate
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 bioconductor-scgraphverse

to add into an existing workspace instead, run:

pixi add bioconductor-scgraphverse

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-scgraphverse

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-scgraphverse

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-scgraphverse:<tag>

(see bioconductor-scgraphverse/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-scgraphverse/README.html)