recipe bioconductor-cpvsnp

Gene set analysis methods for SNP association p-values that lie in genes in given gene sets







biotools: cpvsnp, doi: 10.1038/nmeth.3252

Gene set analysis methods exist to combine SNP-level association p-values into gene sets, calculating a single association p-value for each gene set. This package implements two such methods that require only the calculated SNP p-values, the gene set(s) of interest, and a correlation matrix (if desired). One method (GLOSSI) requires independent SNPs and the other (VEGAS) can take into account correlation (LD) among the SNPs. Built-in plotting functions are available to help users visualize results.

package bioconductor-cpvsnp

(downloads) docker_bioconductor-cpvsnp



depends bioconductor-biocparallel:


depends bioconductor-genomicfeatures:


depends bioconductor-gseabase:


depends r-base:


depends r-corpcor:

depends r-ggplot2:

depends r-plyr:



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-cpvsnp

and update with::

   mamba update bioconductor-cpvsnp

To create a new environment, run:

mamba create --name myenvname bioconductor-cpvsnp

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

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