recipe bioconductor-martini

GWAS Incorporating Networks






martini deals with the low power inherent to GWAS studies by using prior knowledge represented as a network. SNPs are the vertices of the network, and the edges represent biological relationships between them (genomic adjacency, belonging to the same gene, physical interaction between protein products). The network is scanned using SConES, which looks for groups of SNPs maximally associated with the phenotype, that form a close subnetwork.

package bioconductor-martini

(downloads) docker_bioconductor-martini



depends bioconductor-snpstats:


depends bioconductor-snpstats:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-igraph:


depends r-matrix:

depends r-memoise:


depends r-rcpp:


depends r-rcppeigen:




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-martini

and update with::

   mamba update bioconductor-martini

To create a new environment, run:

mamba create --name myenvname bioconductor-martini

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

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