Package Recipe 'bioconductor-dotseq'

recipe bioconductor-dotseq

Genome-wide Detection of Differential ORF Usage

Homepage:: https://bioconductor.org/packages/3.23/bioc/html/DOTSeq.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-dotseq/meta.yaml

Differential open reading frame (ORF) translation analysis framework for ribosome profiling (Ribo-seq) with matched RNA-seq. Implements (i) Differential ORF Usage (DOU), a beta-binomial generalized linear model that models the expected proportion of Ribo-seq versus RNA-seq reads mapping to each ORF within a gene, and (ii) ORF-level Differential Translation Efficiency (DTE), a negative binomial GLM that capture changes in translation efficiency of individual ORFs across experimental conditions. Supports ORF-level read summarization for bulk and single-cell Ribo-seq.

package bioconductor-dotseq¶

Versions:

1.0.0-0

Depends:

on __osx >=10.13
on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-annotationdbi >=1.72.0,<1.73.0a0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0a0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-biocparallel >=1.44.0,<1.45.0a0
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-deseq2 >=1.50.0,<1.51.0
on bioconductor-deseq2 >=1.50.2,<1.51.0a0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomeinfodb >=1.46.2,<1.47.0a0
on bioconductor-genomeinfodbdata >=1.2.15,<1.3.0
on bioconductor-genomeinfodbdata >=1.2.15,<1.3.0a0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0a0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0a0
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-rsamtools >=2.26.0,<2.27.0
on bioconductor-rsamtools >=2.26.0,<2.27.0a0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-rtracklayer >=1.70.1,<1.71.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on bioconductor-txdbmaker >=1.6.0,<1.7.0
on bioconductor-txdbmaker >=1.6.2,<1.7.0a0
on libcxx >=19
on r-ashr
on r-base >=4.5,<4.6.0a0
on r-boot
on r-data.table
on r-emmeans
on r-glmmtmb
on r-matrix
on r-pbapply
on r-rcpp

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-dotseq

to add into an existing workspace instead, run:

pixi add bioconductor-dotseq

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-dotseq

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-dotseq

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-dotseq:<tag>

(see bioconductor-dotseq/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

.. Create all the necessary plots for each package by loading all the correct specs and data. Important points on the place and implementation of this script block: 1. It is here, and not in a separate HTML file, as it needs to have the `package.name` rendered in for each package. 2. All packages are handled in one `window.onload` function, as multiple instances of this throughout a (rendered) HTML just overwrite each other.

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-dotseq/README.html)