Package Recipe 'bioconductor-sracipe'

recipe bioconductor-sracipe

Systems biology tool to simulate gene regulatory circuits

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/sRACIPE.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-sracipe/meta.yaml

sRACIPE implements a randomization-based method for gene circuit modeling. It allows us to study the effect of both the gene expression noise and the parametric variation on any gene regulatory circuit (GRC) using only its topology, and simulates an ensemble of models with random kinetic parameters at multiple noise levels. Statistical analysis of the generated gene expressions reveals the basin of attraction and stability of various phenotypic states and their changes associated with intrinsic and extrinsic noises. sRACIPE provides a holistic picture to evaluate the effects of both the stochastic nature of cellular processes and the parametric variation.

package bioconductor-sracipe¶

Versions:

2.2.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-1, 1.14.0-0, 1.10.0-2, 1.10.0-1, 1.10.0-0,

2.2.0-0, 1.22.0-0, 1.18.0-0, 1.16.0-0, 1.14.0-1, 1.14.0-0, 1.10.0-2, 1.10.0-1, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-1

Depends:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
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-dofuture
on r-dorng
on r-foreach
on r-future
on r-ggplot2
on r-gplots
on r-gridextra
on r-htmlwidgets
on r-mass
on r-rcolorbrewer
on r-rcpp
on r-reshape2
on r-umap
on r-visnetwork

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-sracipe

to add into an existing workspace instead, run:

pixi add bioconductor-sracipe

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-sracipe

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-sracipe

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-sracipe:<tag>

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