recipe grenedalf

Toolkit for Population Genetic Statistics from Pool-Sequenced Samples, e.g., in Evolve and Resequence experiments

Homepage:

https://github.com/lczech/grenedalf

Documentation:

https://github.com/lczech/grenedalf/wiki

License:

GPL-3.0-only

Recipe:

/grenedalf/meta.yaml

Links:

arXiv: :arXiv:`2306.11622`

grenedalf is a collection of commands for working with population genetic data, in particular from pool sequencing. Its main focus are statistical analyses such as Tajima's D and Fst. The statistics follow the approaches of PoPoolation and PoPoolation2, as well as poolfstat and npstat. However, compared to those, grenedalf is significantly more scalable, more user friendly, and offers more settings and input file formats.

package grenedalf

versions:

0.6.2-1,  0.6.2-0,  0.6.1-0,  0.6.0-0,  0.5.2-0

depends bzip2:

>=1.0.8,<2.0a0

depends libgcc:

>=13

depends liblzma:

>=5.6.3,<6.0a0

depends libstdcxx:

>=13

depends libzlib:

>=1.3.1,<2.0a0

depends xz:

depends zlib:

requirements:

additional platforms:

linux-aarch64

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 grenedalf

and update with::

   mamba update grenedalf

To create a new environment, run:

mamba create --name myenvname grenedalf

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/grenedalf:<tag>

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

Download stats

Link to this page

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