recipe bioconductor-rlmm

A Genotype Calling Algorithm for Affymetrix SNP Arrays

Homepage:

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

License:

LGPL (>= 2)

Recipe:

/bioconductor-rlmm/meta.yaml

Links:

biotools: rlmm, doi: 10.1093/bioinformatics/bti741

A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.

package bioconductor-rlmm

(downloads) docker_bioconductor-rlmm

versions:
1.64.0-0,  1.62.0-0,  1.60.0-0,  1.56.0-0,  1.54.0-0,  1.52.0-1,  1.52.0-0,  1.50.0-0,  1.48.0-0, 

1.64.0-0,  1.62.0-0,  1.60.0-0,  1.56.0-0,  1.54.0-0,  1.52.0-1,  1.52.0-0,  1.50.0-0,  1.48.0-0,  1.46.0-1,  1.46.0-0,  1.44.0-0,  1.42.0-0,  1.40.0-0,  1.38.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-mass:

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-rlmm

and update with::

   mamba update bioconductor-rlmm

To create a new environment, run:

mamba create --name myenvname bioconductor-rlmm

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-rlmm:<tag>

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

Download stats

Link to this page

Render an install-with-bioconda 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-rlmm/README.html)