recipe bioconductor-mdqc

Mahalanobis Distance Quality Control for microarrays



LGPL (>= 2)




biotools: mdqc, doi: 10.1093/bioinformatics/btm487

MDQC is a multivariate quality assessment method for microarrays based on quality control (QC) reports. The Mahalanobis distance of an array's quality attributes is used to measure the similarity of the quality of that array against the quality of the other arrays. Then, arrays with unusually high distances can be flagged as potentially low-quality.

package bioconductor-mdqc

(downloads) docker_bioconductor-mdqc



depends r-base:


depends r-cluster:

depends r-mass:



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-mdqc

and update with::

   mamba update bioconductor-mdqc

To create a new environment, run:

mamba create --name myenvname bioconductor-mdqc

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<tag>

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

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