recipe bioconductor-mina

Microbial community dIversity and Network Analysis






An increasing number of microbiome datasets have been generated and analyzed with the help of rapidly developing sequencing technologies. At present, analysis of taxonomic profiling data is mainly conducted using composition-based methods, which ignores interactions between community members. Besides this, a lack of efficient ways to compare microbial interaction networks limited the study of community dynamics. To better understand how community diversity is affected by complex interactions between its members, we developed a framework (Microbial community dIversity and Network Analysis, mina), a comprehensive framework for microbial community diversity analysis and network comparison. By defining and integrating network-derived community features, we greatly reduce noise-to-signal ratio for diversity analyses. A bootstrap and permutation-based method was implemented to assess community network dissimilarities and extract discriminative features in a statistically principled way.

package bioconductor-mina

(downloads) docker_bioconductor-mina



depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-apcluster:

depends r-base:


depends r-biganalytics:

depends r-bigmemory:

depends r-foreach:

depends r-ggplot2:

depends r-hmisc:

depends r-mcl:

depends r-paralleldist:

depends r-plyr:

depends r-rcpp:

depends r-rcpparmadillo:

depends r-rcppparallel:

depends r-reshape2:

depends r-rspectra:

depends r-stringr:



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-mina

and update with::

   mamba update bioconductor-mina

To create a new environment, run:

mamba create --name myenvname bioconductor-mina

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

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