recipe bioconductor-riboprofiling

Ribosome Profiling Data Analysis: from BAM to Data Representation and Interpretation

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-riboprofiling/meta.yaml

Links:

biotools: riboprofiling, doi: 10.12688/f1000research.8964.1

Starting with a BAM file, this package provides the necessary functions for quality assessment, read start position recalibration, the counting of reads on CDS, 3'UTR, and 5'UTR, plotting of count data: pairs, log fold-change, codon frequency and coverage assessment, principal component analysis on codon coverage.

package bioconductor-riboprofiling

versions:

1.32.0-0,  1.30.0-0,  1.28.0-0,  1.24.0-0,  1.22.0-0,  1.20.0-1,  1.20.0-0,  1.18.0-0,  1.16.0-0, 

1.32.0-0,  1.30.0-0,  1.28.0-0,  1.24.0-0,  1.22.0-0,  1.20.0-1,  1.20.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-1,  1.12.0-1,  1.12.0-0,  1.10.0-0,  1.7.1-0,  1.6.0-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biostrings:

>=2.70.0,<2.71.0

depends bioconductor-genomeinfodb:

>=1.38.0,<1.39.0

depends bioconductor-genomicalignments:

>=1.38.0,<1.39.0

depends bioconductor-genomicfeatures:

>=1.54.0,<1.55.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-ggbio:

>=1.50.0,<1.51.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-rsamtools:

>=2.18.0,<2.19.0

depends bioconductor-rtracklayer:

>=1.62.0,<1.63.0

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-plyr:

depends r-reshape2:

depends r-sqldf:

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-riboprofiling

and update with::

   mamba update bioconductor-riboprofiling

To create a new environment, run:

mamba create --name myenvname bioconductor-riboprofiling

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-riboprofiling:<tag>

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

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