Package Recipe 'bioconductor-basicstan'

recipe bioconductor-basicstan

Stan implementation of BASiCS

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/BASiCStan.html
License:: GPL-3
Recipe:: /bioconductor-basicstan/meta.yaml

Provides an interface to infer the parameters of BASiCS using the variational inference (ADVI), Markov chain Monte Carlo (NUTS), and maximum a posteriori (BFGS) inference engines in the Stan programming language. BASiCS is a Bayesian hierarchical model that uses an adaptive Metropolis within Gibbs sampling scheme. Alternative inference methods provided by Stan may be preferable in some situations, for example for particularly large data or posterior distributions with difficult geometries.

package bioconductor-basicstan¶

Versions:

1.12.0-0, 1.8.0-0, 1.4.0-0, 1.2.0-0, 1.0.0-1, 1.0.0-0

Depends:

on bioconductor-basics >=2.22.0,<2.23.0
on bioconductor-basics >=2.22.0,<2.23.0a0
on bioconductor-glmgampoi >=1.22.0,<1.23.0
on bioconductor-glmgampoi >=1.22.0,<1.23.0a0
on bioconductor-scran >=1.38.0,<1.39.0
on bioconductor-scran >=1.38.0,<1.39.0a0
on bioconductor-scuttle >=1.20.0,<1.21.0
on bioconductor-scuttle >=1.20.0,<1.21.0a0
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-bh >=1.66.0
on r-rcpp >=0.12.0
on r-rcppeigen >=0.3.3.3.0
on r-rcppparallel >=5.0.1
on r-rstan >=2.18.1
on r-rstantools >=2.1.1
on r-stanheaders >=2.18.0
on tbb-devel >=2022.3.0,<2022.4.0a0

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-basicstan

to add into an existing workspace instead, run:

pixi add bioconductor-basicstan

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-basicstan

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-basicstan

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-basicstan:<tag>

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