Package Recipe 'r-rldne'

recipe r-rldne

A Convenient R Interface For NeEstimator V2.1

Homepage:: https://github.com/zakrobinson/RLDNe
License:: GPL-2.0-only
Recipe:: /r-rldne/meta.yaml

An R-package that conveniently interfaces with NeEstimator 2.1 (Do et al. 2014). NeEstimator V2.1 executables are distributed with this package freely, for non-commericial, educational purposes only. Given that NeEstimator is quite straightfoward to run, a common use case for this package is when you want to simulate/downsample and run many iterations of the LD-method via R. This package allows the LD-Method in NeEstimator V2.1 to be easily executed via R.

package r-rldne¶

Versions:

1.0.0-1, 1.0.0-0

Depends:

on r-base >=4.5,<4.6.0a0
on r-devtools
on r-dplyr
on r-efglmh
on r-readr
on r-remotes >=2.1.0
on r-tibble
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 r-rldne

to add into an existing workspace instead, run:

pixi add r-rldne

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-rldne

Alternatively, to install into a new environment, run:

conda create -n envname r-rldne

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-rldne:<tag>

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