recipe bioconductor-bg2

Performs Bayesian GWAS analysis for non-Gaussian data using BG2

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/BG2.html

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-bg2/meta.yaml

This package is built to perform GWAS analysis for non-Gaussian data using BG2. The BG2 method uses penalized quasi-likelihood along with nonlocal priors in a two step manner to identify SNPs in GWAS analysis. The research related to this package was supported in part by National Science Foundation awards DMS 1853549 and DMS 2054173.

package bioconductor-bg2

(downloads) docker_bioconductor-bg2

versions:

1.2.0-01.0.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-caret:

>=6.0-86

depends r-ga:

>=3.2

depends r-mass:

>=7.3-58.1

depends r-matrix:

>=1.2-18

depends r-memoise:

>=1.1.0

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-bg2

and update with::

   mamba update bioconductor-bg2

To create a new environment, run:

mamba create --name myenvname bioconductor-bg2

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/bioconductor-bg2:<tag>

(see `bioconductor-bg2/tags`_ for valid values for ``<tag>``)

Download stats