recipe bioconductor-resolve

RESOLVE: An R package for the efficient analysis of mutational signatures from cancer genomes

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/RESOLVE.html

License:

file LICENSE

Recipe:

/bioconductor-resolve/meta.yaml

Cancer is a genetic disease caused by somatic mutations in genes controlling key biological functions such as cellular growth and division. Such mutations may arise both through cell-intrinsic and exogenous processes, generating characteristic mutational patterns over the genome named mutational signatures. The study of mutational signatures have become a standard component of modern genomics studies, since it can reveal which (environmental and endogenous) mutagenic processes are active in a tumor, and may highlight markers for therapeutic response. Mutational signatures computational analysis presents many pitfalls. First, the task of determining the number of signatures is very complex and depends on heuristics. Second, several signatures have no clear etiology, casting doubt on them being computational artifacts rather than due to mutagenic processes. Last, approaches for signatures assignment are greatly influenced by the set of signatures used for the analysis. To overcome these limitations, we developed RESOLVE (Robust EStimation Of mutationaL signatures Via rEgularization), a framework that allows the efficient extraction and assignment of mutational signatures. RESOLVE implements a novel algorithm that enables (i) the efficient extraction, (ii) exposure estimation, and (iii) confidence assessment during the computational inference of mutational signatures.

package bioconductor-resolve

versions:

1.4.0-0,  1.2.0-0,  1.0.0-0

depends bioconductor-biostrings:

>=2.70.0,<2.71.0

depends bioconductor-bsgenome:

>=1.70.0,<1.71.0

depends bioconductor-bsgenome.hsapiens.1000genomes.hs37d5:

>=0.99.0,<0.100.0

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-mutationalpatterns:

>=3.12.0,<3.13.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends r-base:

>=4.3,<4.4.0a0

depends r-data.table:

depends r-ggplot2:

depends r-glmnet:

depends r-gridextra:

depends r-lsa:

depends r-nnls:

depends r-reshape2:

requirements:

additional platforms:

Installation

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-resolve

and update with::

   mamba update bioconductor-resolve

To create a new environment, run:

mamba create --name myenvname bioconductor-resolve

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 quay.io/biocontainers/bioconductor-resolve:<tag>

(see `bioconductor-resolve/tags`_ for valid values for ``<tag>``)

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-resolve/README.html)