recipe svdss

Structural Variant Discovery from Sample-specific Strings.

Homepage:

https://github.com/Parsoa/SVDSS

Documentation:

https://github.com/Parsoa/SVDSS/blob/v2.0.0/README.md

License:

MIT / MIT

Recipe:

/svdss/meta.yaml

Links:

biotools: svdss, doi: 10.1038/s41592-022-01674-1

package svdss

versions:

2.0.0-1,  2.0.0-0,  1.0.5-2,  1.0.5-1,  1.0.5-0,  1.0.4-1,  1.0.4-0,  1.0.3-0

depends _openmp_mutex:

>=4.5

depends bcftools:

>=1.9

depends bzip2:

>=1.0.8,<2.0a0

depends gsl:

>=2.7,<2.8.0a0

depends htslib:

>=1.21,<1.22.0a0

depends libgcc:

>=13

depends libgomp:

depends liblzma:

>=5.6.3,<6.0a0

depends libstdcxx:

>=13

depends libzlib:

>=1.3.1,<2.0a0

depends samtools:

>=1.9

requirements:

additional platforms:

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 svdss

and update with::

   mamba update svdss

To create a new environment, run:

mamba create --name myenvname svdss

with myenvname being 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/svdss:<tag>

(see `svdss/tags`_ for valid values for ``<tag>``)

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