recipe codingquarry

CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.

Homepage:

https://sourceforge.net/p/codingquarry/

License:

GPL / GPL-3

Recipe:

/codingquarry/meta.yaml

Links:

doi: 10.1186/s12864-015-1344-4

package codingquarry

(downloads) docker_codingquarry

versions:
2.0-11,  2.0-10,  2.0-9,  2.0-8,  2.0-7,  2.0-6,  2.0-5,  2.0-4,  2.0-3, 

2.0-11,  2.0-10,  2.0-9,  2.0-8,  2.0-7,  2.0-6,  2.0-5,  2.0-4,  2.0-3,  2.0-2,  2.0-1,  2.0-0

depends biopython:

depends libgcc:

>=13

depends libstdcxx:

>=13

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

requirements:

additional platforms:
linux-aarch64,  osx-arm64

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 codingquarry

and update with::

   mamba update codingquarry

To create a new environment, run:

mamba create --name myenvname codingquarry

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/codingquarry:<tag>

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

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