recipe riassigner

GC-MS retention index calculation

Homepage:

https://github.com/RECETOX/RIAssigner

License:

MIT / MIT

Recipe:

/riassigner/meta.yaml

RIAssigner is a python tool for retention index (RI) computation for GC-MS data

package riassigner

versions:

0.4.1-0,  0.4.0-0,  0.3.4-4,  0.3.4-3,  0.3.4-2,  0.3.4-1,  0.3.4-0,  0.3.3-1,  0.3.3-0, 

0.4.1-0,  0.4.0-0,  0.3.4-4,  0.3.4-3,  0.3.4-2,  0.3.4-1,  0.3.4-0,  0.3.3-1,  0.3.3-0,  0.3.2-0,  0.3.1-0,  0.3.0-0,  0.2.0-0

depends fastparquet:

>=2023.10.1,<2024.0.0

depends matchms:

>=0.24.1,<0.25.0

depends numpy:

depends pandas:

depends pint:

>=0.23.0,<0.24.0

depends python:

>=3.10,<3.13

depends scipy:

depends urllib3:

1.26.15.*

requirements:

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 riassigner

and update with::

   mamba update riassigner

To create a new environment, run:

mamba create --name myenvname riassigner

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/riassigner:<tag>

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

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