Package Recipe 'bioconductor-tadar'

recipe bioconductor-tadar

Transcriptome Analysis of Differential Allelic Representation

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/tadar.html
License:: GPL-3
Recipe:: /bioconductor-tadar/meta.yaml

This package provides functions to standardise the analysis of Differential Allelic Representation (DAR). DAR compromises the integrity of Differential Expression analysis results as it can bias expression, influencing the classification of genes (or transcripts) as being differentially expressed. DAR analysis results in an easy-to-interpret value between 0 and 1 for each genetic feature of interest, where 0 represents identical allelic representation and 1 represents complete diversity. This metric can be used to identify features prone to false-positive calls in Differential Expression analysis, and can be leveraged with statistical methods to alleviate the impact of such artefacts on RNA-seq data.

package bioconductor-tadar¶

Versions:

1.8.0-0, 1.4.0-0, 1.0.0-0

Depends:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-gviz >=1.54.0,<1.55.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-matrixgenerics >=1.22.0,<1.23.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on bioconductor-variantannotation >=1.56.0,<1.57.0
on r-base >=4.5,<4.6.0a0
on r-ggplot2
on r-lifecycle
on r-rlang

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-tadar

to add into an existing workspace instead, run:

pixi add bioconductor-tadar

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-tadar

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-tadar

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-tadar:<tag>

(see bioconductor-tadar/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¶

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-tadar/README.html)