Package Recipe 'r-smartsva'

recipe r-smartsva

Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves an order of magnitude faster running time while trading no accuracy loss in return.

Homepage:: https://CRAN.R-project.org/package=SmartSVA
License:: GPL3 / GPL-3
Recipe:: /r-smartsva/meta.yaml

package r-smartsva¶

Versions:

0.1.3-10, 0.1.3-9, 0.1.3-8, 0.1.3-7, 0.1.3-6, 0.1.3-5, 0.1.3-4, 0.1.3-3, 0.1.3-2,

0.1.3-10, 0.1.3-9, 0.1.3-8, 0.1.3-7, 0.1.3-6, 0.1.3-5, 0.1.3-4, 0.1.3-3, 0.1.3-2, 0.1.3-1, 0.1.3-0

Depends:

on bioconductor-sva >=3.58.0,<3.59.0a0
on libgcc >=14
on libstdcxx >=14
on r-base >=4.5,<4.6.0a0
on r-isva
on r-rcpp
on r-rcppeigen
on r-rspectra

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 r-smartsva

to add into an existing workspace instead, run:

pixi add r-smartsva

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 r-smartsva

Alternatively, to install into a new environment, run:

conda create -n envname r-smartsva

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/r-smartsva:<tag>

(see r-smartsva/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/r-smartsva/README.html)