- recipe djinn
Convert your linked-read data between formats, almost like magic.
- Homepage:
- Documentation:
- License:
GPL3 / GPL-3.0-or-later
- Recipe:
There are disagreements between formats for linked-read data. Haplotagging thinks linked-read barcodes and FASTQ files should look one way, stLFR a different way, and TELLseq yet another. Djinn lets you convert to a standard format, convert between these FASTQ formats, barcode styles, etc. It also provides a convenient method to upload linked-read data to NCBI that preserves barcode information.
- package djinn¶
- Versions:
2.4-0,2.3-0,2.2.1-0,2.2-0,2.1.1-0,2.1-0,2.0-0,1.1-0,1.0.1-0,2.4-0,2.3-0,2.2.1-0,2.2-0,2.1.1-0,2.1-0,2.0-0,1.1-0,1.0.1-0,1.0-0- Depends:
on click
>=8.2on pysam
>=0.23on python
>=3.11on rich-click
1.9.*on samtools
>=1.22
- 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 djinn
to add into an existing workspace instead, run:
pixi add djinn
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 djinn
Alternatively, to install into a new environment, run:
conda create -n envname djinn
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/djinn:<tag>
(see djinn/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/djinn/README.html)
