- recipe bioconductor-rlmm
A Genotype Calling Algorithm for Affymetrix SNP Arrays
- Homepage:
- License:
LGPL (>= 2)
- Recipe:
- 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¶
- Versions:
1.72.0-0,1.68.0-0,1.64.0-0,1.62.0-0,1.60.0-0,1.56.0-0,1.54.0-0,1.52.0-1,1.52.0-0,1.72.0-0,1.68.0-0,1.64.0-0,1.62.0-0,1.60.0-0,1.56.0-0,1.54.0-0,1.52.0-1,1.52.0-0,1.50.0-0,1.48.0-0,1.46.0-1,1.46.0-0,1.44.0-0,1.42.0-0,1.40.0-0,1.38.0-0- Depends:
on r-base
>=4.5,<4.6.0a0on r-mass
- 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 bioconductor-rlmm
to add into an existing workspace instead, run:
pixi add bioconductor-rlmm
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 bioconductor-rlmm
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-rlmm
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/bioconductor-rlmm:<tag>
(see bioconductor-rlmm/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:
[](http://bioconda.github.io/recipes/bioconductor-rlmm/README.html)
