recipe bioconductor-signer

Empirical Bayesian approach to mutational signature discovery







biotools: signer

The signeR package provides an empirical Bayesian approach to mutational signature discovery. It is designed to analyze single nucleotide variation (SNV) counts in cancer genomes, but can also be applied to other features as well. Functionalities to characterize signatures or genome samples according to exposure patterns are also provided.

package bioconductor-signer

(downloads) docker_bioconductor-signer



depends bioconductor-biocfilecache:


depends bioconductor-biocfilecache:


depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends bioconductor-biostrings:


depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-bsgenome:


depends bioconductor-genomeinfodb:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicranges:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-iranges:


depends bioconductor-rtracklayer:


depends bioconductor-rtracklayer:


depends bioconductor-variantannotation:


depends bioconductor-variantannotation:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-ada:

depends r-base:


depends r-bsplus:

depends r-class:

depends r-clue:

depends r-cowplot:

depends r-dplyr:

depends r-dt:

depends r-e1071:

depends r-future:

depends r-future.apply:

depends r-ggplot2:

depends r-ggpubr:

depends r-glmnet:

depends r-kknn:

depends r-listenv:

depends r-magrittr:

depends r-mass:

depends r-maxstat:

depends r-nloptr:

depends r-nmf:

depends r-pheatmap:

depends r-pmcmrplus:

depends r-ppclust:

depends r-proc:

depends r-proxy:

depends r-pvclust:

depends r-randomforest:

depends r-rcolorbrewer:

depends r-rcpp:

depends r-rcpparmadillo:


depends r-readr:

depends r-reshape2:

depends r-scales:

depends r-shiny:

depends r-shinycssloaders:

depends r-shinydashboard:

depends r-shinywidgets:

depends r-survival:

depends r-survivalanalysis:

depends r-survminer:

depends r-tibble:

depends r-tidyr:

depends r-vgam:



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-signer

and update with::

   mamba update bioconductor-signer

To create a new environment, run:

mamba create --name myenvname bioconductor-signer

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

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