Package Recipe 'bioconductor-signer'

recipe bioconductor-signer

Empirical Bayesian approach to mutational signature discovery

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/signeR.html
License:: GPL-3
Recipe:: /bioconductor-signer/meta.yaml
Links:: 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¶

Versions:

2.12.0-0, 2.8.0-0, 2.4.0-0, 2.2.1-0, 2.0.0-1, 2.0.0-0, 1.20.0-2, 1.20.0-1, 1.20.0-0,

2.12.0-0, 2.8.0-0, 2.4.0-0, 2.2.1-0, 2.0.0-1, 2.0.0-0, 1.20.0-2, 1.20.0-1, 1.20.0-0, 1.18.0-0, 1.16.0-1, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-1, 1.8.0-0, 1.6.1-0, 1.4.0-0, 1.2.2-0, 1.0.1-0

Depends:

on bioconductor-biocfilecache >=3.0.0,<3.1.0
on bioconductor-biocfilecache >=3.0.0,<3.1.0a0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0a0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-biostrings >=2.78.0,<2.79.0a0
on bioconductor-bsgenome >=1.78.0,<1.79.0
on bioconductor-bsgenome >=1.78.0,<1.79.0a0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomeinfodb >=1.46.2,<1.47.0a0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-rtracklayer >=1.70.1,<1.71.0a0
on bioconductor-variantannotation >=1.56.0,<1.57.0
on bioconductor-variantannotation >=1.56.0,<1.57.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-ada
on r-base >=4.5,<4.6.0a0
on r-broom
on r-bsplus
on r-class
on r-clue
on r-cowplot
on r-dplyr
on r-dt
on r-e1071
on r-future
on r-future.apply
on r-ggplot2
on r-ggpubr
on r-glmnet
on r-kknn
on r-listenv
on r-magrittr
on r-mass
on r-maxstat
on r-nloptr
on r-nmf
on r-pheatmap
on r-pmcmrplus
on r-ppclust
on r-proc
on r-proxy
on r-pvclust
on r-randomforest
on r-rcolorbrewer
on r-rcpp
on r-rcpparmadillo >=0.7.100
on r-readr
on r-reshape2
on r-scales
on r-shiny
on r-shinycssloaders
on r-shinydashboard
on r-shinywidgets
on r-survival
on r-survminer
on r-tibble
on r-tidyr
on r-vgam

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-signer

to add into an existing workspace instead, run:

pixi add bioconductor-signer

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-signer

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-signer

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-signer:<tag>

(see bioconductor-signer/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-signer/README.html)