recipe bioconductor-hiergwas

Asessing statistical significance in predictive GWA studies






Testing individual SNPs, as well as arbitrarily large groups of SNPs in GWA studies, using a joint model of all SNPs. The method controls the FWER, and provides an automatic, data-driven refinement of the SNP clusters to smaller groups or single markers.

package bioconductor-hiergwas

(downloads) docker_bioconductor-hiergwas



depends r-base:


depends r-fastcluster:

depends r-fmsb:

depends r-glmnet:



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-hiergwas

and update with::

   mamba update bioconductor-hiergwas

To create a new environment, run:

mamba create --name myenvname bioconductor-hiergwas

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

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