- recipe bioconductor-bambu
Context-Aware Transcript Quantification from Long Read RNA-Seq data
- Homepage:
- License:
GPL-3 + file LICENSE
- Recipe:
bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.
- package bioconductor-bambu¶
-
- Versions:
3.12.1-1,3.12.1-0,3.8.3-0,3.4.0-1,3.4.0-0,3.2.4-0,3.0.8-1,3.0.8-0,3.0.6-0,3.12.1-1,3.12.1-0,3.8.3-0,3.4.0-1,3.4.0-0,3.2.4-0,3.0.8-1,3.0.8-0,3.0.6-0,3.0.5-0,3.0.1-0,2.0.6-1,2.0.6-0,2.0.5-0,2.0.3-0,2.0.0-0,1.2.0-0,1.0.2-1,1.0.2-0,1.0.0-2- Depends:
on bioconductor-biocgenerics
>=0.56.0,<0.57.0on bioconductor-biocgenerics
>=0.56.0,<0.57.0a0on bioconductor-biocparallel
>=1.44.0,<1.45.0on bioconductor-biocparallel
>=1.44.0,<1.45.0a0on bioconductor-bsgenome
>=1.78.0,<1.79.0on bioconductor-bsgenome
>=1.78.0,<1.79.0a0on bioconductor-genomeinfodb
>=1.46.0,<1.47.0on bioconductor-genomeinfodb
>=1.46.2,<1.47.0a0on bioconductor-genomicalignments
>=1.46.0,<1.47.0on bioconductor-genomicalignments
>=1.46.0,<1.47.0a0on bioconductor-genomicfeatures
>=1.62.0,<1.63.0on bioconductor-genomicfeatures
>=1.62.0,<1.63.0a0on bioconductor-genomicranges
>=1.62.0,<1.63.0on bioconductor-genomicranges
>=1.62.1,<1.63.0a0on bioconductor-iranges
>=2.44.0,<2.45.0on bioconductor-iranges
>=2.44.0,<2.45.0a0on bioconductor-rsamtools
>=2.26.0,<2.27.0on bioconductor-rsamtools
>=2.26.0,<2.27.0a0on bioconductor-s4vectors
>=0.48.0,<0.49.0on bioconductor-s4vectors
>=0.48.0,<0.49.0a0on bioconductor-summarizedexperiment
>=1.40.0,<1.41.0on bioconductor-summarizedexperiment
>=1.40.0,<1.41.0a0on libblas
>=3.9.0,<4.0a0on libgcc
>=14on liblapack
>=3.9.0,<4.0a0on liblzma
>=5.8.2,<6.0a0on libstdcxx
>=14on libzlib
>=1.3.1,<2.0a0on r-base
>=4.5,<4.6.0a0on r-data.table
on r-dplyr
on r-rcpp
on r-rcpparmadillo
on r-tidyr
on r-xgboost
- Additional platforms:
linux-aarch64
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-bambu
to add into an existing workspace instead, run:
pixi add bioconductor-bambu
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-bambu
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-bambu
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-bambu:<tag>
(see bioconductor-bambu/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:
[](http://bioconda.github.io/recipes/bioconductor-bambu/README.html)