- recipe cosap
COSAP - Comparative Sequencing Analysis Platform
- Homepage:
- Documentation:
- License:
MIT
- Recipe:
- package cosap¶
-
- Versions:
0.1.0-0- Depends:
on bbmap
39.01on bcftools
>=1.16,<1.17on black
on bowtie2
2.5.1on bwa
0.7.17on bwa-mem2
2.2.1on click
on docker-py
on elprep
5.1.3on fastp
0.23.2on fastqc
0.11.9on gatk4
>=4.5,<4.6on genefuse
on libtiff
on matplotlib-venn
on msisensor-pro
on numpy
on openjdk
>=17,<18on perl-dbi
on perl-lwp-simple
on picard
>=2,<3on pillow
on pygraphviz
on pyranges
on python
>=3.9on qualimap
2.2.2don samtools
>=1.16,<1.17on scikit-learn
on seaborn
on shortuuid
on snakefmt
on snakemake
>=7,<8on snpeff
5.1on somatic-sniper
1.0.5.0on upsetplot
on vardict-java
1.8.3on varscan
2.4.4on yaml
- 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 cosap
to add into an existing workspace instead, run:
pixi add cosap
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 cosap
Alternatively, to install into a new environment, run:
conda create -n envname cosap
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/cosap:<tag>
(see cosap/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/cosap/README.html)