recipe bioconductor-basicstan

Stan implementation of BASiCS

Homepage:

https://bioconductor.org/packages/3.16/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:

1.0.0-0

Depends:

• bioconductor-basics >=2.10.0,<2.11.0

• bioconductor-glmgampoi >=1.10.0,<1.11.0

• bioconductor-scran >=1.26.0,<1.27.0

• bioconductor-scuttle >=1.8.0,<1.9.0

• bioconductor-singlecellexperiment >=1.20.0,<1.21.0

• bioconductor-summarizedexperiment >=1.28.0,<1.29.0

• libblas >=3.9.0,<4.0a0

• libgcc-ng >=12

• liblapack >=3.9.0,<4.0a0

• libstdcxx-ng >=12

• r-base >=4.2,<4.3.0a0

• r-bh >=1.66.0

• r-rcpp >=0.12.0

• r-rcppeigen >=0.3.3.3.0

• r-rcppparallel >=5.0.1

• r-rstan >=2.18.1

• r-rstantools >=2.1.1

• r-stanheaders >=2.18.0

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-basicstan

and update with:

conda update bioconductor-basicstan

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-basicstan:<tag>

(see bioconductor-basicstan/tags for valid values for <tag>)

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