recipe bioconductor-drimseq

Differential transcript usage and tuQTL analyses with Dirichlet-multinomial model in RNA-seq

Homepage:

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

License:

GPL (>= 3)

Recipe:

/bioconductor-drimseq/meta.yaml

Links:

biotools: drimseq

The package provides two frameworks. One for the differential transcript usage analysis between different conditions and one for the tuQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts) with the Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.

package bioconductor-drimseq

versions:

1.30.0-0,  1.28.0-0,  1.26.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.16.0-0,  1.14.0-0, 

1.30.0-0,  1.28.0-0,  1.26.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.16.0-0,  1.14.0-0,  1.12.0-1,  1.10.0-0,  1.8.0-0,  1.6.0-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-edger:

>=4.0.0,<4.1.0

depends bioconductor-genomicranges:

>=1.54.0,<1.55.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

depends r-mass:

depends r-reshape2:

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-drimseq

and update with::

   mamba update bioconductor-drimseq

To create a new environment, run:

mamba create --name myenvname bioconductor-drimseq

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-drimseq:<tag>

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

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