- recipe bioconductor-transcriptr
An Integrative Tool for ChIP- And RNA-Seq Based Primary Transcripts Detection and Quantification
- Homepage:
https://bioconductor.org/packages/3.18/bioc/html/transcriptR.html
- License:
GPL-3
- Recipe:
- 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:
1.30.0-0,1.28.0-0,1.26.0-0,1.22.0-0,1.20.0-0,1.18.0-1,1.18.0-0,1.16.0-0,1.14.0-0,1.30.0-0,1.28.0-0,1.26.0-0,1.22.0-0,1.20.0-0,1.18.0-1,1.18.0-0,1.16.0-0,1.14.0-0,1.12.0-1,1.10.0-0,1.8.0-0,1.6.0-0- depends bioconductor-biocgenerics:
>=0.48.0,<0.49.0- depends bioconductor-chipseq:
>=1.52.0,<1.53.0- 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-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-caret:
- depends r-e1071:
- depends r-ggplot2:
- depends r-proc:
- 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-transcriptr and update with:: mamba update bioconductor-transcriptr
To create a new environment, run:
mamba create --name myenvname bioconductor-transcriptr
with
myenvnamebeing 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-transcriptr:<tag> (see `bioconductor-transcriptr/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-transcriptr/README.html)
