recipe bioconductor-metagenomeseq

Statistical analysis for sparse high-throughput sequencing







biotools: metagenomeseq, doi: 10.1038/nmeth.2658

metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.

package bioconductor-metagenomeseq

(downloads) docker_bioconductor-metagenomeseq



depends bioconductor-biobase:


depends bioconductor-limma:


depends bioconductor-wrench:


depends r-base:


depends r-foreach:

depends r-glmnet:

depends r-gplots:

depends r-matrix:

depends r-matrixstats:

depends r-rcolorbrewer:



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-metagenomeseq

and update with::

   mamba update bioconductor-metagenomeseq

To create a new environment, run:

mamba create --name myenvname bioconductor-metagenomeseq

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-metagenomeseq/tags`_ for valid values for ``<tag>``)

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