recipe bioconductor-ribodipa

Differential pattern analysis for Ribo-seq data

Homepage:

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

License:

LGPL (>= 3)

Recipe:

/bioconductor-ribodipa/meta.yaml

This package performs differential pattern analysis for Ribo-seq data. It identifies genes with significantly different patterns in the ribosome footprint between two conditions. RiboDiPA contains five major components including bam file processing, P-site mapping, data binning, differential pattern analysis and footprint visualization.

package bioconductor-ribodipa

(downloads) docker_bioconductor-ribodipa

versions:

1.10.0-01.8.0-01.6.0-11.6.0-01.2.0-21.2.0-11.2.0-01.0.0-0

depends bioconductor-biocfilecache:

>=2.10.0,<2.11.0

depends bioconductor-biocfilecache:

>=2.10.1,<2.11.0a0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biocgenerics:

>=0.48.1,<0.49.0a0

depends bioconductor-deseq2:

>=1.42.0,<1.43.0

depends bioconductor-deseq2:

>=1.42.0,<1.43.0a0

depends bioconductor-genomicalignments:

>=1.38.0,<1.39.0

depends bioconductor-genomicalignments:

>=1.38.0,<1.39.0a0

depends bioconductor-genomicfeatures:

>=1.54.0,<1.55.0

depends bioconductor-genomicfeatures:

>=1.54.1,<1.55.0a0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-genomicranges:

>=1.54.1,<1.55.0a0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0a0

depends bioconductor-qvalue:

>=2.34.0,<2.35.0

depends bioconductor-qvalue:

>=2.34.0,<2.35.0a0

depends bioconductor-rsamtools:

>=2.18.0,<2.19.0

depends bioconductor-rsamtools:

>=2.18.0,<2.19.0a0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-s4vectors:

>=0.40.2,<0.41.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx-ng:

>=12

depends r-base:

>=4.3,<4.4.0a0

depends r-data.table:

depends r-doparallel:

depends r-elitism:

depends r-foreach:

depends r-ggplot2:

depends r-matrixstats:

depends r-rcpp:

>=1.0.2

depends r-reldist:

requirements:

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-ribodipa

and update with::

   mamba update bioconductor-ribodipa

To create a new environment, run:

mamba create --name myenvname bioconductor-ribodipa

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-ribodipa:<tag>

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

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