Package Recipe 'bioconductor-transcriptr'

recipe bioconductor-transcriptr

An Integrative Tool for ChIP- And RNA-Seq Based Primary Transcripts Detection and Quantification

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/transcriptR.html
License:: GPL-3
Recipe:: /bioconductor-transcriptr/meta.yaml
Links:: biotools: transcriptr, doi: 10.1038/nmeth.3252

The differences in the RNA types being sequenced have an impact on the resulting sequencing profiles. mRNA-seq data is enriched with reads derived from exons, while GRO-, nucRNA- and chrRNA-seq demonstrate a substantial broader coverage of both exonic and intronic regions. The presence of intronic reads in GRO-seq type of data makes it possible to use it to computationally identify and quantify all de novo continuous regions of transcription distributed across the genome. This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events. Furthermore, the integration of ChIP- and RNA-seq data allows the identification all known and novel active transcription start sites within a given sample.

package bioconductor-transcriptr¶

Versions:

1.38.3-0, 1.34.0-0, 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,

1.38.3-0, 1.34.0-0, 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:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-chipseq >=1.60.0,<1.61.0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on r-base >=4.5,<4.6.0a0
on r-caret
on r-ggplot2
on r-proc
on r-reshape2

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-transcriptr

to add into an existing workspace instead, run:

pixi add bioconductor-transcriptr

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-transcriptr

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-transcriptr

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-transcriptr:<tag>

(see bioconductor-transcriptr/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-transcriptr/README.html)